Sand Hill Road to the heart of Silicon Valley it's the cute presenting the people first Network insights from entrepreneurs and tech leaders when I'm John Ferrari with the cube I'm the co-host also the founder of Silicon angle me we are here on Sand Hill Road at Mayfield for the people first conversations I'm John furry with the cube weird Allen being global CTO and IT of innovation at Procter & Gamble formerly the same position at coca-cola has done a lot of innovations over the years also a reference account back in the day for web methods when they call on the financing of that one of the most famous IPOs which set the groundwork for web services and has a lot of history going back to the 80s we were just talking about it welcome this conversation on people first network thank you for inviting me so the people first network is all about people and it's great to have these conversations you're old school you were doing some stuff back on the 80s talking about doing RPA 3270 you've been old school here yeah I go back to APL as my first programming language went through the the third generation languages and of course the old 30 to 70 emulation which is what we know today is our PA one of the cool things I was excited to hear some of your background around your history web methods you were a reference call for venture financing of web methods which was financed on the credit card for the two founders husband and wife probably one of the most successful I appeals but more importantly at the beginning of the massive wave that we now see with web services this is early days this was very early days when I was at DHL we were looking at what we're gonna do for the future and in fact we built one of the first object-oriented frameworks in C++ at the time because that was all that was available to us or the best was available we rejected Corbis and we said look if we're gonna go this direction and one of my developers found web methods found philip merrick it was literally at the time working out of his garage and had this technology that was going to allow us to start moving into this object-oriented approach and I remember the day Robin Vasan form a field called and said hey I'm thinking about investing in web methods what do you think about it and not only was it one of the first startups that I ever worked with but it's actually the first time I met anybody in the venture community way back in nineteen I think 1997 is what had happened and that was a computing time in computer science and then the rest is history and then XML became what it became lingua franca for the web web services now Amazon Web Services you see in cloud computing micro services kubernetes service meshes this is a new stack that's being developed in the cloud and this is the new generation you've seen many waves and at Procter & Gamble formerly coca-cola you're the same role you have to navigate this so what's different now what's different say 15 20 years ago how are you looking at this market how you implementing some of the IT and infrastructure and software development environments I think what's change is you know when we got into the the early 2000s Nicolas car came out and said IT doesn't matter and I think anybody that was an IT had this very objectionable response initially but when you step back and you looked at it what she realised was in many cases IT didn't matter and those were those areas that were non-competitive those things that could be commoditized and it was completely right the reality is IT has always mattered that technology does give you a competitive advantage in certain markets and certain capabilities for a company but back then we had to go out and we had to purchase equipment we had to configure the equipment there was a lot of heavy lifting in corporations just did not want to invest the capital so they outsource the stuff wholesale I think General Motors was the first one that just out sourced everything and was followed by other companies including Procter & Gamble the decision at that time was probably right but as we go forward and we see what's happened with corporations we see the valuations of corporations the amount of return on equity based on the on the capital that's being invested we can see that data is important we can see that agility flexibility is key to competing in the future and therefore what's changing is we are now moving into an age of away from ERP so we're moving into an age away from these outsource providers on a wholesale basis and using it selectively to drive down costs and allowing us to free up money in order to invest in those things that are most important to the company so you're saying is that the folks naturally the server consolidation they've bought all this gear all this software over you know 18-month rollouts before they even see the first implementation those are the glory days of gravy trains for the vendor's yeah not good for the practitioners but you're saying that the folks who reinvested are investing in IT as a core competency are seeing a competitive advantage they certainly are you know I think I made the statement front of a number of the vendors and a few years ago and people were not comfortable with it but what I said was like you gone are the ears of these 10 20 million dollar deals gone are the ears of the million two million dollar deals we're in the ear of throwaway technology I need to be able to use and invest in technology for a specific purpose for a specific period of time and be able to move on to the next one it's the perfect time for startups but startups shouldn't be looking at the big picture they should be looking at the tail on these investments let me try things let me get out in the market let me have a competitive advantage in marketing which is most important to me or in supply chain those are the areas that I can make a difference with my consumers and my customers and that's where the investments have to go so just in constant of throwaway technology and you know you'd also be said of you know being more agile though interesting to look at the cloud SAS business model if Amazon for us I think that's the gold standard where they actually lower prices on a per unit basis and increase more services and value but in the aggregate you're still paying more but you have more flexibility and that's kind of a good tell sign so that you're seeing that ability to reuse either the infrastructure that's commoditized to shift the value this is are people having a hard time understanding this so I want to get your reaction to how should I tea leaders understand that the wave of cloud the wave of machine learning what a I can bring to the table these new trends how how should leaders figure this out is there a playbook as there are things that you've learned that you could share you know that there's really a playbook it's still early on everyone's looking for one cloud fits all the reality is whether it's Google whether it's Amazon whether it's Microsoft whether it's IBM all clouds are different all clouds have our special are purpose-built for different solutions and I think as an IT leader you have to understand you're not going to take everything and lift and shift that's what we used to do we're now in the position where we have to deconstruct our business we have to understand the services the capabilities that we want to bring to market and not lock ourselves in its building blocks its Legos we're in the period of Legos putting these things together in different manners in order to create new solutions if we try to lock ourselves in the past of how we've always financed things how we've always built things then we're not going to be any better off in the new world than we were in the old alan i want to get your reaction to to two words our PA and containers well as i said earlier our PA is 3270 emulation from the 1980s and for those of us that are old enough to remember that i I still remember scraping the the old green screens and and putting a little process around it it what's nice though is that we have moved forward machine learning and AI and other other capabilities are now present so that we can do this I actually played around with neural nets probably back in 1985 with an Apollo computer so that tells you how far back I go but technologies change processing speeds change everything the technology trends are allowing us to now to do these things the question that we have is also a moral dilemma is are we trying to replace people or are we trying to make improvements and I think that you don't look at our PA as a way simply to replace work it's a way to enhance what we're doing in order to create new value for the customer or for the consumer in our case I think in the in the area of containers you know again been around for a while been around for a while it's just another another approach that we're not we don't want lock in we don't want to be dependent on specific vendors we want the portability we want the flexibility and I think as we start moving containers out to the edge that's where we're gonna start seeing more value as the business processes and the capabilities are spread out again the idea of centralized cloud computing is very good however it doesn't need to be distributed what's interesting I find about the conversation here is that you mentioned a couple things earlier you mentioned the vendors locking you in and saying here's the ERP buy this and with this you have to have a certain process because this is our technology you got to use it this way and you were slave to their their tech on your process serve their tech with containers and say orchestration you now the ability to manage workloads differently and so an interesting time there's that does that change the notion of rip and replace lift and shift because if I a container I could just put a container around it and not have to worry about killing the old to bring in the new this is on the fundamental kind of debate going on do you have to kill the old to bring in the new well you need to kill the old sometimes just because it's old it's time to go other times you do need to repackage it and other times I hate to say it you do need to lift and shift if you're a legacy organization they have a long history such as most of the manufacturing companies in the world today we can't get rid of old things that quickly we can't afford to a lot of the processes are still valid as we're looking to the future we certainly are breaking these things down into services we're looking to containerize these things we're looking to move them into areas where we can compute where we want to when we want to at the right price we're just at the beginning of that journey in the industry I still think there's about five to seven years to go to get there now I'll talk about the role of the edge role of cloud computing as it increases the surface area of IT potentially combined with the fact that IT is a competitive advantage bring those two notions together what's the role of the people because you used to have people that would just manage the rack and stack I'm provisioning some storage I'm doing this as those stovepipes start to be broken down when the service area of IT is bigger how does that change the relationship of the people involved you know you win with people at the end of the day you don't win with technology you know a company of such as Proctor and Gamble and I think what's happened if you look at historically the ERP vendors came out probably 99 2000 and it used to be and remember these I'm old to be honest with you but I remember that we used to have to worry about the amount of memory we were managing we had to be able to tune databases in all of this and the vendors went ahead and they started automating all those processes with the idea that we can do it better than a human and a lot of people a lot of the technology talent then started leaving the organizations and organizations were left with people that we're focusing on process and people a process excuse me process and the the the business which is very good because you need the subject matter experts going forward we have to reinvest in people our people have the subject matter expertise they have some technology skills that they've developed over the years and they've enhanced it on their own but we're in this huge change right now where we have to think different we have to act different and we have to behave differently so doubling down on people is the best thing that you can do and the old outsource model of outsourcing everything kind of reduces the core competency of the people yeah now you got to build it back up again exactly I mean we when we left at P&G 15 years ago about 5,000 people left the organization when we outsource them when we outsource the technology to our partner at that time now it's time we're starting to bring it back in we've brought the network team back in and stood up our own sock in our own NOC for the first time in years just this past year we're doing the same thing by moving things out to the cloud more and more is moving to the cloud we're setting up our own cloud operations and DevOps capabilities I can tell you having been on both sides of it it's a lot harder to be able to bring it back in than it is to take it out and you know interesting proctoring games well known as being a very intimate with the data very data-driven company the data is valuable and having that infrastructure NIT to support the data that's important what's your vision on the data future of the data in the world well I think data is has a value to itself but when you tie it to products you tie it to your customers and consumers it's even more valuable and we're in the process now of things that we used to do completely internally with our own technology or technology partners we're now moving all of that out into the cloud now and I must say cloud its clouds plural again going back to certain clouds are better for certain things so you're seeing a dramatic shift we have a number of projects underway that are in the cloud space but for customers and consumers number of cloud projects in the way for our own internal employees it's all about collecting the data processing the data protecting that data because we take that very seriously and being able to use it to make better decisions I want to get your reaction on two points and two quite lines of questioning here because I think it's very relevant on the enterprise side you're a big account for the big whales the old ERP so the big cloud providers so people want to sell you stuff at the same time you're also running IT innovation so you want to play with the new shiny new toys and experiments start up so if startups want to get your attention and big vendors want to sell to you the tables have kind of turned it's been good this is a good it's a good buyers market right now in my opinion so what's your thoughts on that so you know start with the big companies what do they got to do to win you over well they got to look like how they got to engage and for startups how do they get your attention I think the biggest thing for either startup or large companies understanding the company you're dealing with whether it's Procter & Gamble whether it's coca-cola whether it was DHL if you understand how I operate if you understand how decisions are made if you understand how I'm organized that's gonna give you an a competitive advantage now the large corporations understand this because they've been around through the entire journey of computing with these large corporations the startups need to step back and take a look and see where do I add that competitive advantage many times when you're selling to a large corporate you're not selling to a large corporate you're selling two divisions you're selling two functions and that's how you get in I've been working with startups as I said back since web methods and it was just a two-person company but we brought them in for a very specific capability I then took web methods with me when I left DHL I took them to GE when I left GE I took them to ing because I trusted them and they matured along the way I think finding that right individual that has the right need is the key and working it slowly don't think you're gonna close the deal fast if you're start-up know it's gonna take some time and decide if that's in your best interest or not slow things down focus don't try to boil the ocean over too many of them try to boy you're right Jimmy people try to boil the ocean get that win one win will get you another one which will get you another win and that's the best way to succeed get that beachhead Ellen so if you could go back and knowing what you know now and you're breaking into the IT leadership's position looking forward what would you do differently can do a mulligan hey what would you do differently well you know I think one of the one of the dangers of being an innovator in IT is that you really are risk taker and taking risks is counterculture to corporations so I think I would probably try to get by in a little bit more I mean someone once told me that you know you see the force through the trees before anybody else does your problem is you don't bring people along with you so I think I would probably slow down a little bit not in the adoption of technology but I'd probably take more time to build the case to bring people along a lot faster so that they can see it and they can take credit for it and they can move that needle as well yeah always sometimes early adopters and pioneers had the arrows on the back as they say I've had my share now thanks for sharing your experience what's next for you what's the next mountain you're going to climb well I think that as we're looking forward latency is still an issue you know we have to find a way to defeat latency we're not going to do it through basic physics so we're gonna have to change our business models change our technology distribution change everything that we're doing consumers and customers are demanding instant access to enhanced information through AI and m/l right at the point where they want it and that means we're now dealing with milliseconds and nanoseconds of having to make decisions so I'm very interested in looking at how are we going to change consumer behavior and customer behavior by combining a lot of the new technology trends that are underway and we have to do it also with the security in mind now before we security was secondary now as we're seeing with all of the hacks and the malware and everything that's going on in the world we have to go in and think a little bit different about how we're gonna do that so I'm very much engaged in working with a lot of startups I live here in the Silicon Valley I commute to Cincinnati for Procter & Gamble I'm spending time and just flew in from tel-aviv literally an hour ago I'm in the middle of all the technology hotspots trying to find that next big thing and it's a global it's global innovation happens everywhere and anywhere the venture community if you look at the amount of funds it used to be invested out of the Silicon Valley versus the rest of the world it continues to be on a downward trend not because the funding isn't here in the Silicon Valley but because everyone is recognizing that innovation and technology is developed everywhere in the world Alan Bain was the CTO global CTO and IT innovator there at the cube conversation here in San Hill Road I'm John for a year thanks for watching you

(upbeat music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase. We're in Season two, Episode three, and this is the topic of MarTech and the Emerging Cloud-Scale Customer Experiences, the ongoing coverage of AWS's ecosystem of large scale growth and new companies and growing companies. I'm your host, John Furrier. We're excited to have Tim Barnes, Global Director, General Manager of Advertiser and Marketing at AWS here doing the keynote cloud-scale customer experience. Tim, thanks for coming on. >> Oh, great to be here and thank you for having me. >> You've seen many cycles of innovation, certainly in the ad tech platform space around data, serving consumers and a lot of big, big scale advertisers over the years as the Web 1.0, 2.0, now 3.0 coming, cloud-scale, roll of data, all big conversations changing the game. We see things like cookies going away. What does this all mean? Silos, walled gardens, a lot of new things are impacting the applications and expectations of consumers, which is also impacting the folks trying to reach the consumers. And this is kind of creating a kind of a current situation, which is challenging, but also an opportunity. Can you share your perspective of what this current situation is, as the emerging MarTech landscape emerges? >> Yeah, sure, John, it's funny in this industry, the only constant has changed and it's an ever-changing industry and never more so than right now. I mean, we're seeing with whether it's the rise of privacy legislation or just breach of security of data or changes in how the top tech providers and browser controllers are changing their process for reaching customers. This is an inflection point in the history of both ad tech and MarTech. You hit the nail on the head with cookie deprecation, with Apple removing IDFA, changes to browsers, et cetera, we're at an interesting point. And by the way, we're also seeing an explosion of content sources and ability to reach customers that's unmatched in the history of advertising. So those two things are somewhat at odds. So whether we see the rise of connected television or digital out of home, you mentioned Web 3.0 and the opportunities that may present in metaverse, et cetera, it's an explosion of opportunity, but how do we continue to connect brands with customers and do so in a privacy compliant way? And that's really the big challenge we're facing. One of the things that I see is the rise of modeling or machine learning as a mechanism to help remove some of these barriers. If you think about the idea of one-to-one targeting, well, that's going to be less and less possible as we progress. So how am I still as a brand advertiser or as a targeted advertiser, how am I going to still reach the right audience with the right message in a world where I don't necessarily know who they are. And modeling is a really key way of achieving that goal and we're seeing that across a number of different angles. >> We've always talked about on the ad tech business for years, it's the behemoth of contextual and behavioral, those dynamics. And if you look at the content side of the business, you have now this new, massive source of new sources, blogging has been around for a long time, you got video, you got newsletters, you got all kinds of people, self-publishing, that's been around for a while, right? So you're seeing all these new sources. Trust is a big factor, but everyone wants to control their data. So this walled garden perpetuation of value, I got to control my data, but machine learning works best when you expose data, so this is kind of a paradox. Can you talk about the current challenge here and how to overcome it because you can't fight fashion, as they say, and we see people kind of going down this road as saying, data's a competitive advantage, but I got to figure out a way to keep it, own it, but also share it for the machine learning. What's your take on that? >> Yeah, I think first and foremost, if I may, I would just start with, it's super important to make that connection with the consumer in the first place. So you hit the nail on the head for advertisers and marketers today, the importance of gaining first party access to your customer and with permission and consent is paramount. And so just how you establish that connection point with trust and with very clear directive on how you're going to use the data has never been more important. So I would start there if I was a brand advertiser or a marketer, trying to figure out how I'm going to better connect with my consumers and get more first party data that I could leverage. So that's just building the scale of first party data to enable you to actually perform some of the types of approaches we'll discuss. The second thing I would say is that increasingly, the challenge exists with the exchange of the data itself. So if I'm a data control, if I own a set of first party data that I have consent with consumers to use, and I'm passing that data over to a third party, and that data is leaked, I'm still responsible for that data. Or if somebody wants to opt out of a communication and that opt out signal doesn't flow to the third party, I'm still liable, or at least from the consumer's perspective, I've provided a poor customer experience. And that's where we see the rise of the next generation, I call it of data clean rooms, the approaches that you're seeing, a number of customers take in terms of how they connect data without actually moving the data between two sources. And we're seeing that as certainly a mechanism by which you can preserve accessibility data, we call that federated data exchange or federated data clean rooms and I think you're seeing that from a number of different parties in the industry. >> That's awesome, I want to get into the data interoperability because we have a lot of startups presenting in this episode around that area, but why I got you here, you mentioned data clean room. Could you define for us, what is a federated data clean room, what is that about? >> Yeah, I would simply describe it as zero data movement in a privacy and secure environment. To be a little bit more explicit and detailed, it really is the idea that if I'm a party A and I want to exchange data with party B, how can I run a query for analytics or other purposes without actually moving data anywhere? Can I run a query that has accessibility to both parties, that has the security and the levels of aggregation that both parties agree to and then run the query and get those results sets back in a way that it actually facilitates business between the two parties. And we're seeing that expand with partners like Snowflake and InfoSum, even within Amazon itself, AWS, we have data sharing capabilities within Redshift and some of our other data-led capabilities. And we're just seeing explosion of demand and need for customers to be able to share data, but do it in a way where they still control the data and don't ever hand it over to a third party for execution. >> So if I understand this correctly, this is kind of an evolution to kind of take away the middleman, if you will, between parties that used to be historically the case, is that right? >> Yeah, I'd say this, the middleman still exists in many cases. If you think about joining two parties' data together, you still have the problem of the match key. How do I make sure that I get the broadest set of data to match up with the broadest set of data on the other side? So we have a number of partners that provide these types of services from LiveRamp, TransUnion, Experian, et cetera. So there's still a place for that so-called middleman in terms of helping to facilitate the transaction, but as a clean room itself, I think that term is becoming outdated in terms of a physical third party location, where you push data for analysis, that's controlled by a third party. >> Yeah, great clarification there. I want to get into this data interoperability because the benefits of AWS and cloud scales we've seen over the past decade and looking forward is, it's an API based economy. So APIs and microservices, cloud native stuff is going to be the key to integration. And so connecting people together is kind of what we're seeing as the trend. People are connecting their data, they're sharing code in open source. So there's an opportunity to connect the ecosystem of companies out there with their data. Can you share your view on this interoperability trend, why it's important and what's the impact to customers who want to go down this either automated or programmatic connection oriented way of connecting data. >> Never more important than it has been right now. I mean, if you think about the way we transact it and still too today do to a certain extent through cookie swaps and all sorts of crazy exchanges of data, those are going away at some point in the future; it could be a year from now, it could be later, but they're going away. And I think that that puts a great amount of pressure on the broad ecosystem of customers who transact for marketers, on behalf of marketers, both for advertising and marketing. And so data interoperability to me is how we think about providing that transactional layer between multiple parties so that they can continue to transact in a way that's meaningful and seamless, and frankly at lower cost and at greater scale than we've done in the past with less complexity. And so, we're seeing a number of changes in that regard, whether that's data sharing and data clean rooms or federated clean rooms, as we described earlier, whether that's the rise of next generation identity solutions, for example, the UID 2.0 Consortium, which is an effort to use hashed email addresses and other forms of identifiers to facilitate data exchange for the programmatic ecosystem. These are sort of evolutions based on this notion that the old world is going away, the new world is coming, and part of that is how do we connect data sources in a more seamless and frankly, efficient manner. >> It's almost interesting, it's almost flipped upside down, you had this walled garden mentality, I got to control my data, but now I have data interoperability. So you got to own and collect the data, but also share it. This is going to kind of change the paradigm around my identity platforms, attributions, audience, as audiences move around, and with cookies going away, this is going to require a new abstraction, a new way to do it. So you mentioned some of those standards. Is there a path in this evolution that changes it for the better? What's your view on this? What do you see happening? What's going to come out of this new wave? >> Yeah, my father was always fond of telling me, "The customer, my customers is my customer." And I like to put myself in the shoes of the Marc Pritchards of the world at Procter & Gamble and think, what do they want? And frankly, their requirements for data and for marketing have not changed over the last 20 years. It's, I want to reach the right customer at the right time, with the right message and I want to be able to measure it. In other words, summarizing, I want omnichannel execution with omnichannel measurement, and that's become increasingly difficult as you highlighted with the rise of the walled gardens and increasingly data living in silos. And so I think it's important that we, as an industry start to think about what's in the best interest of the one customer who brings virtually 100% of the dollars to this marketplace, which is the CMO and the CMO office. And how do we think about returning value to them in a way that is meaningful and actually drives its industry forward. And I think that's where the data operability piece becomes really important. How do we think about connecting the omnichannel channels of execution? How do we connect that with partners who run attribution offerings with machine learning or partners who provide augmentation or enrichment data such as third party data providers, or even connecting the buy side with the sell side in a more efficient manner? How do I make that connection between the CMO and the publisher in a more efficient and effective way? And these are all challenges facing us today. And I think at the foundational layer of that is how do we think about first of all, what data does the marketer have, what is the first party data? How do we help them ethically source and collect more of that data with proper consent? And then how do we help them join that data into a variety of data sources in a way that they can gain value from it. And that's where machine learning really comes into play. So whether that's the notion of audience expansion, whether that's looking for some sort of cohort analysis that helps with contextual advertising, whether that's the notion of a more of a modeled approach to attribution versus a one-to-one approach, all of those things I think are in play, as we think about returning value back to that customer of our customer. >> That's interesting, you broke down the customer needs in three areas; CMO office and staff, partners ISV software developers, and then third party services. Kind of all different needs, if you will, kind of tiered, kind of at the center of that's the user, the consumer who have the expectations. So it's interesting, you have the stakeholders, you laid out kind of those three areas as to customers, but the end user, the consumer, they have a preference, they kind of don't want to be locked into one thing. They want to move around, they want to download apps, they want to play on Reddit, they want to be on LinkedIn, they want to be all over the place, they don't want to get locked in. So you have now kind of this high velocity user behavior. How do you see that factoring in, because with cookies going away and kind of the convergence of offline-online, really becoming predominant, how do you know someone's paying attention to what and when attention and reputation. All these things seem complex. How do you make sense of it? >> Yeah, it's a great question. I think that the consumer as you said, finds a creepiness factor with a message that follows them around their various sources of engagement with content. So I think at first and foremost, there's the recognition by the brand that we need to be a little bit more thoughtful about how we interact with our customer and how we build that trust and that relationship with the customer. And that all starts with of course, opt-in process consent management center but it also includes how we communicate with them. What message are we actually putting in front of them? Is it meaningful, is it impactful? Does it drive value for the customer? I think we've seen a lot of studies, I won't recite them that state that most consumers do find value in targeted messaging, but I think they want it done correctly and there in lies the problem. So what does that mean by channel, especially when we lose the ability to look at that consumer interaction across those channels. And I think that's where we have to be a little bit more thoughtful with frankly, kind of going back to the beginning with contextual advertising, with advertising that perhaps has meaning, or has empathy with the consumer, perhaps resonates with the consumer in a different way than just a targeted message. And we're seeing that trend, we're seeing that trend both in television, connected television as those converge, but also as we see about connectivity with gaming and other sort of more nuanced channels. The other thing I would say is, I think there's a movement towards less interruptive advertising as well, which kind of removes a little bit of those barriers for the consumer and the brand to interact. And whether that be dynamic product placement, content optimization, or whether that be sponsorship type opportunities within digital. I think we're seeing an increased movement towards those types of executions, which I think will also provide value to both parties. >> Yeah, I think you nailed it there. I totally agree with you on the contextual targeting, I think that's a huge deal and that's proven over the years of providing benefit. People, they're trying to find what they're looking for, whether it's data to consume or a solution they want to buy. So I think that all kind of ties together. The question is these three stakeholders, the CMO office and staff you mentioned, and the software developers, apps, or walled gardens, and then like ad servers as they come together, have to have standards. And so, I think to me, I'm trying to squint through all the movement and the shifting plates that are going on in the industry and trying to figure out where are the dots connecting? And you've seen many cycles of innovation at the end of the day, it comes down to who can perform best for the end user, as well as the marketers and advertisers, so that balance. What's your view on this shift? It's going to land somewhere, it has to land in the right area, and the market's very efficient. I mean, this ad market's very efficient. >> Yeah, I mean, in some way, so from a standards perspective, I support and we interact extensively with the IB and other industry associations on privacy enhancing technologies and how we think about these next generations of connection points or identifiers to connect with consumers. But I'd say this, with respect to the CMO, and I mentioned the publisher earlier, I think over the last 10 years with the rise of programmatic, certainly we saw the power reside mostly with the CMO who was able to amass a large pool of cookies or purchase a large sort of cohort of customers with cookie based attributes and then execute against that. And so almost a blind fashion to the publisher, the publisher was sort of left to say, "Hey, here's an opportunity, do you want to buy it or not?" With no real reason why the marketer might be buying that customer? And I think that we're seeing a shift backwards towards the publisher and perhaps a healthy balance between the two. And so, I do believe that over time, that we're going to see publishers provide a lot more, what I might almost describe as mini walled gardens. So the ability, great publisher or a set of publishers to create a cohort of customers that can be targeted through programmatic or perhaps through programmatic guaranteed in a way that it's a balance between the two. And frankly thinking about that notion of federated data clean rooms, you can see an approach where publishers are able to share their first party data with a marketer's first party data, without either party feeling like they're giving up something or passing all their value over to the other. And I do believe we're going to see some significant technology changes over the next three to four years. That really rely on that interplay between the marketer and the publisher in a way that it helps both sides achieve their goals, and that is, increasing value back to the publisher in terms of higher CPMs, and of course, better reach and frequency controls for the marketer. >> I think you really brought up a big point there we can maybe follow up on, but I think this idea of publishers getting more control and power and value is an example of the market filling a void and the power log at the long tail, it's kind of a straight line. Then it's got the niche kind of communities, it's growing in the middle there, and I think the middle of the torso of that power law is the publishers because they have all the technology to measure the journeys and the click throughs and all this traffic going on their platform, but they just need to connect to someone else. >> Correct. >> That brings in the interoperability. So, as a publisher ourselves, we see that long tail getting really kind of fat in the middle where new brands are going to emerge, if they have audience. I mean, some podcasts have millions of users and some blogs are attracting massive audience, niche audiences that are growing. >> I would say, just look at the rise of what we might not have considered publishers in the past, but are certainly growing as publishers today. Customers like Instacart or Uber who are creating ad platforms or gaming, which of course has been an ad supported platform for some time, but is growing immensely. Retail as a platform, of course, amazon.com being one of the biggest retail platforms with advertising supported models, but we're seeing that growth across the board for retail customers. And I think that again, there's never been more opportunities to reach customers. We just have to do it the right way, in the way that it's not offensive to customers, not creepy, if you want to call it that, and also maximizes value for both parties and that be both the buy and the sell side. >> Yeah, everyone's a publisher and everyone's a media company. Everyone has their own news network, everyone has their own retail, it's a completely new world. Tim, thanks for coming on and sharing your perspective and insights on this key note, Tim Barnes, Global Director, General Manager of Advertiser and Market at AWS here with the Episode three of Season two of the AWS Startup Showcase. I'm John Furrier, thanks for watching. (upbeat music)

>>From around the globe. It's the cube with digital coverage, a BizOps manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto. Unveil. Something has been in the works for a little while. Today's the formal unveiling, and we're excited to have three of the core founding members of the manifesto authors of the manifesto. If you will, uh, joining us again, we've had them all on individually. Now we're going to have a great power panel. First up. We're gonna have Mitt Kirsten returning he's the founder and CEO of Tasktop mic. Good to see you again. Where are you dialing in from? >>Great to see you again, Jeff I'm dialing from Vancouver, >>We're Canada, Vancouver, Canada. One of my favorite cities in the whole wide world. Also we've got Tom Davenport come in from across the country. He's a distinguished professor and author from Babson college, Tom. Great to see you. And I think you said you're at a fun, exotic place on the East coast >>Realm of Memphis shoes. That's on Cape Cod. >>Great to see you again and also joining surge Lucio. He is the VP and general manager enterprise software division at Broadcom surge. Great to see you again, where are you coming in from? >>Uh, from Boston right next to Cape Cod. >>Terrific. So welcome back, everybody again. Congratulations on this day. I know it's been a lot of work to get here for this unveil, but let's just jump into it. The biz ops manifesto, what was the initial reason to do this? And how did you decide to do it in a kind of a coalition, a way bringing together a group of people versus just making it an internal company, uh, initiative that, you know, you can do better stuff within your own company, surge, why don't we start with you? >>Yeah, so, so I think we were at a really critical juncture, right? Many, um, large enterprises are basically struggling with their digital transformation. Um, in fact, um, many recognized that, uh, the, the business side, it collaboration has been, uh, one of the major impediments, uh, to drive that kind of transformation. That, and if we look at the industry today, many people are, whether we're talking about vendors or, um, you know, system integrators, consulting firms are talking about the same kind of concepts, but using very different language. And so we believe that bringing all these different players together, um, as part of the coalition and formalizing, uh, basically the core principles and values in a BizOps manifesto, we can really start to F could have a much bigger movement where we can all talk about kind of the same concepts and we can really start to provide, could have a much better support for large organizations to, to transform. Uh, so whether it is technology or services or, um, or training, I think that that's really the value of bringing all of these players together, right. >>And mic to you. Why did you get involved in this, in this effort? >>So I've been closely involved the agile movement since it started two decades with that manifesto. And I think we got a lot of improvement at the team level, and I think that was just no. Did we really need to improve at the business level? Every company is trying to become a software innovator, trying to make sure that they can pivot quickly and the changing market economy and what everyone's dealing with in terms of needing to deliver value to customers sooner. However, agile practices have really focused on these metrics, these measures and understanding processes that help teams be productive. Those things now need to be elevated to the business as a whole. And that just hasn't happened. Uh, organizations are actually failing because they're measuring activities and how they're becoming more agile, how teams are functioning, not how much quickly they're delivering value to the customer. So we need to now move past that. And that's exactly what the manifesto provides. Right, >>Right, right. And Tom, to you, you've been covering tech for a very long time. You've been looking at really hard challenges and a lot of work around analytics and data and data evolution. So there's a definitely a data angle here. I wonder if you could kind of share your perspective of what you got excited to, uh, to sign onto this manifesto. >>Sure. Well, I have, you know, for the past 15 or 20 years, I've been focusing on data and analytics and AI, but before that I was a process management guy and a knowledge management guy. And in general, I think, you know, we've just kind of optimize that to narrow a level, whether you're talking about agile or dev ops or ML ops, any of these kinds of ops oriented movements, we're making individual project, um, performance and productivity better, but we're not changing the business, uh, effectively enough. And that's the thing that appealed to me about the biz ops idea, that we're finally creating a closer connection between what we do with technology and how it changes the business and provides value to it. >>Great. Uh, surge back to you, right? I mean, people have been talking about digital transformation for a long time and it's been, you know, kind of trucking along and then covert hit and it was instant Lightswitch. Everyone's working from home. You've got a lot more reliance on your digital tools, digital communication, uh, both within your customer base and your partner base, but also then your employees when you're, if you could share how that really pushed this all along. Right? Because now suddenly the acceleration of digital transformation is higher. Even more importantly, you got much more critical decisions to make into what you do next. So kind of your portfolio management of projects has been elevated significantly when maybe revenues are down, uh, and you really have to, uh, to prioritize and get it right. >>Yeah. Maybe I'll just start by quoting Satina Nello basically recently said that they're speeding the two years of digital preservation just last two months in any many ways. That's true. Um, but yet when we look at large enterprises, they're still struggling with a kind of a changes in culture. They really need to drive to be able to disrupt themselves. And not surprisingly, you know, when we look at certain parts of the industry, you know, we see some things which are very disturbing, right? So about 40% of the personal loans today are being, uh, origin data it's by fintechs, uh, of a like of Sophie or, uh, or a lending club, right? Not to a traditional brick and mortar for BEC. And so the, well, there is kind of a much more of an appetite and it's a, it's more of a survival type of driver these days. >>Uh, the reality is that's in order for these large enterprises to truly transform and engage on this digital transformation, they need to start to really align the business nightie, you know, in many ways and make cover. Does agile really emerge from the core desire to truly improve software predictability between which we've really missed is all the way we start to aligning the software predictability to business predictability, and to be able to have continual sleep continuous improvement and measurement of business outcomes. So by aligning that of these, uh, discuss inward metrics, that's, it is typically being using to business outcomes. We think we can start to really ELP, uh, different stakeholders within the organization to collaborate. So I think there is more than ever. There's an imperative to acts now. Um, and, and resolves, I think is kind of the right approach to drive that kind of transformation. Right. >>I want to follow up on the culture comment, uh, with you, Tom, because you've talked before about kind of process flow and process flow throughout a whore and an organization. And, you know, we talk about people process and tech all the time. And I think the tech is the easy part compared to actually changing the people the way they think. And then the actual processes that they put in place. It's a much more difficult issue than just the tech issue to get this digital transformation in your organization. >>Yeah. You know, I've always found that the soft stuff about, you know, the culture of a behavior, the values is the hard stuff to change and more and more, we, we realized that to be successful with any kind of digital transformation you have to change people's behaviors and attitudes. Um, we haven't made as much progress in that area as we might have. I mean, I've done some surveys suggesting that most organizations still don't have data driven cultures. And in many cases there is a lower percentage of companies that say they have that then, um, did a few years ago. So we're kind of moving in the wrong direction, which means I think that we have to start explicitly addressing that, um, cultural, behavioral dimension and not just assuming that it will happen if we, if we build system, if we build it, they won't necessarily come. Right. >>Right. So I want to go to you Nick. Cause you know, we're talking about workflows and flow, um, and, and you've written about flow both in terms of, um, you know, moving things along a process and trying to find bottlenecks, identify bottlenecks, which is now even more important again, when these decisions are much more critical. Cause you have a lot less, uh, wiggle room in tough times, but you also talked about flow from the culture side and the people side. So I wonder if you can just share your thoughts on, you know, using flow as a way to think about things, to get the answers better. >>Yeah, absolutely. And I'll refer back to what Tom has said. If you're optimized, you need to optimize your system. You need to optimize how you innovate and how you deliver value to the business and the customer. Now, what we've noticed in the data, since that we've learned from customers, value streams, enterprise organizations, value streams, is that when it's taking six months at the end to deliver that value with the flow is that slow. You've got a bunch of unhappy developers, unhappy customers when you're innovating half so high performing organizations, we can measure third and 10 float time and dates. All of a sudden that feedback loop, the satisfaction your developer's measurably goes up. So not only do you have people context, switching glass, you're delivering so much more value to customers at a lower cost because you've optimized for flow rather than optimizing for these other approximate tricks that we use, which is how efficient is my agile team. How quickly can we deploy software? Those are important, but they do not provide the value of agility of fast learning of adaptability to the business. And that's exactly what the biz ops manifesto pushes your organization to do. You need to put in place this new operating model that's based on flow on the delivery of business value and on bringing value to market much more quickly than you were before. Right. >>I love that. And I'm going back to you, Tom, on that to follow up. Cause I think, I don't think people think enough about how they prioritize what they're optimizing for. Cause you know, if you're optimizing for a versus B, you know, you can have a very different product that you kick out and let you know. My favorite example is with Clayton Christianson and innovator's dilemma talking about the three inch hard drive. If you optimize it for power, you know, is one thing, if you optimize it for vibration is another thing and sure enough, you know, they missed it on the poem because it was the, it was the game console, which, which drove that whole business. So when you, when you're talking to customers and we think we hear it with cloud all the time, people optimizing for cost efficiency, instead of thinking about it as an innovation tool, how do you help them kind of rethink and really, you know, force them to, to look at the, at the prioritization and make sure they're prioritizing on the right thing is make just said, what are you optimizing for? >>Oh yeah. Um, you have one of the most important aspects of any decision or, um, attempt to resolve a problem in an organization is the framing process. And, um, you know, it's, it's a difficult aspect of the decision to frame it correctly in the first place. Um, there, it's not a technology issue. In many cases, it's largely a human issue, but if you frame that decision or that problem incorrectly to narrowly say, or you frame it as an either or situation where you could actually have some of both, um, it, it's very difficult for the, um, process to work out correctly. So in many cases that I think we need to think more at the beginning about how we bring this issue or this decision in the best way possible before we charge off and build a system to support it. You know, um, it's worth that extra time to think, think carefully about how the decision has been structured, right >>Surgery. I want to go back to you and talk about the human factors because as we just discussed, you can put it in great technology, but if the culture doesn't adopt it and people don't feel good about it, you know, it's not going to be successful and that's going to reflect poorly on the technology, even if it had nothing to do with it. And you know, when you look at the, the, the core values, uh, of the Bezos manifesto, you know, a big one is trust and collaboration, you know, learn, respond and pivot. I wonder if you can share your thoughts on, on trying to get that cultural shift, uh, so that you can have success with the people or excuse me, with the technology in the process and helping customers, you know, take this more trustworthy and kind of proactive, uh, position. >>So I think, I think at the ground level, it truly starts with the realization that we're all different. We come from different backgrounds. Um, oftentimes we tend to blame the data. It's not uncommon my experiments that we spend the first 30 minutes of any kind of one hour conversation to debate the validity of the data. Um, and so, um, one of the first kind of, uh, probably manifestations that we've had or revelations as we start to engage with our customers is spike, just exposing, uh, high-fidelity data sets to different stakeholders from their different lens. We start to enable these different stakeholders to not debate the data. That's really collaborate to find a solution. So in many ways, when, when, when we think about kind of the types of changes we're trying to, to truly affect around data driven decision making, it's all about bringing the data in context, in the context that is relevant and understandable for, for different stakeholders, whether we're talking about an operator or develop for a business analyst. >>So that's, that's the first thing. The second layer I think, is really to provide context to what people are doing in their specific cycle. And so I think one of the best examples I have is if you start to be able to align business KPI, whether you are counting, you know, sales per hour, or the engagements of your users on your mobile applications, whatever it is, you can start to connect that PKI to the business KPI, to the KPIs that developers might be looking at, whether it is the number of defects or a velocity or whatever, you know, metrics that they are used to to actually track you start to, to be able to actually contextualize in what we are the effecting, basically a metric that is really relevant in which we see is that DC is a much more systematic way to approach the transformation than say, you know, some organizations kind of creating, uh, some of these new products or services or initiatives, um, to, to drive engagements, right? >>So if you look at zoom, for instance, zoom giving away a it service to, uh, to education, he's all about, I mean, there's obviously a marketing aspect in therapists. It's fundamentally about trying to drive also the engagement of their own teams. And because now they're doing something for good and the organizations are trying to do that, but you only can do this kind of things in a limited way. And so you really want to start to rethink how you connect to, everybody's kind of a business objective fruit data, and now you start to get people to stare at the same data from their own lens and collaborate on all the data. Right, >>Right. That's a good, uh, Tom, I want to go back to you. You've been studying it for a long time, writing lots of books and getting into it. Um, why now, you know, what w why now are we finally aligning business objectives with, with it objectives? You know, why didn't this happen before? And, you know, what are the factors that are making now the time for this, this, this move with the, uh, with the biz ops? >>Well, and much of the past, it was sort of a back office related activity. And, you know, it was important for, um, uh, producing your paychecks and, uh, um, capturing the customer orders, but the business wasn't built around it now, every organization needs to be a software business, a data business, a digital business, the auntie has been raised considerably. And if you aren't making that connection between your business objectives and the technology that supports it, you run a pretty big risk of, you know, going out of business or losing out to competitors. Totally. So, um, and, uh, even if you're in a, an industry that hasn't historically been terribly, um, technology oriented customer expectations flow from, uh, you know, the digital native, um, companies that they work with to basically every industry. So you're compared against the best in the world. So we don't really have the luxury anymore of screwing up our it projects or building things that don't really work for the business. Um, it's mission critical that we do that well. Um, almost every time, I just want to follow up by that, Tom, >>In terms of the, you've talked extensively about kind of these evolutions of data and analytics from artismal stage to the big data stage, the data economy stage, the AI driven stage and what I find diff interesting that all those stages, you always put a start date. You never put an end date. Um, so you know, is the, is the big data I'm just going to use that generically a moment in time finally here, where we're, you know, off mahogany row with the data scientists, but actually can start to see the promise of delivering the right insight to the right person at the right time to make that decision. >>Well, I think it is true that in general, these previous stages never seemed to go away. The, um, the artisinal stuff is still being done, but we would like for less than less of it to be artisinal, we can't really afford for everything to be artisinal anymore. It's too labor and time consuming to do things that way. So we shift more and more of it to be done through automation and B to be done with a higher level of productivity. And, um, you know, at some point maybe we reached the stage where we don't do anything artisanally anymore. I'm not sure we're there yet, but, you know, we are, we are making progress. Right, >>Right. And Mick, back to you in terms of looking at agile, cause you're, you're such a, a student of agile when, when you look at the opportunity with ops, um, and taking the lessons from agile, you know, what's been the inhibitor to stop this in the past. And what are you so excited about? You know, taking this approach will enable. >>Yeah. I think both Sergeant Tom hit on this is that in agile what's happened is that we've been measuring tiny subsets of the value stream, right? We need to elevate the data's there. Developers are working on these tools that delivering features that the foundations for, for great culture are there. I spent two decades as a developer. And when I was really happy is when I was able to deliver value to customers, the quicker I was able to do that the fewer impediments are in my way, that quicker was deployed and running in the cloud, the happier I was, and that's exactly what's happening. If we can just get the right data, uh, elevated to the business, not just to the agile teams, but really these values of ours are to make sure that you've got these data driven decisions with meaningful data that's oriented around delivering value to customers. Not only these legacies that Tom touched on, which has cost center metrics from an ITK, from where, for it being a cost center and something that provided email and then back office systems. So we need to rapidly shift to those new, meaningful metrics that are customized business centric and make sure that every development the organization is focused on those as well as the business itself, that we're measuring value and that we're helping that value flow without interruptions. >>I love that mic. Cause if you don't measure it, you can't improve on it and you gotta, but you gotta be measuring the right thing. So gentlemen, uh, thank you again for, for your time. Congratulations on the, uh, on the unveil of the biz ops manifesto and together this coalition >>Of, of, uh, industry experts to get behind this. And, you know, there's probably never been a more important time than now to make sure that your prioritization is in the right spot and you're not wasting resources where you're not going to get the ROI. So, uh, congratulations again. And thank you for sharing your thoughts with us here on the cube. Alright, so we had surge, Tom and Mick I'm. Jeff, you're watching the cube, it's a biz ops manifesto and unveil. Thanks for watching. We'll see you next time >>From around the globe. It's the cube with digital coverage of BizOps manifesto, unveiled brought to you by biz ops coalition and welcome back Friday, Jeff Frick here with the cube we're in our Palo Alto studios. And we'd like to welcome you back to our continuing coverage of biz ops manifesto, unveil exciting day to really, uh, kind of bring this out into public. There's been a little bit of conversation, but today's really the official unveiling and we're excited to have our next guest to share a little bit more information on it. He's Patrick tickle. He's a chief product officer for planned view. Patrick. Great to see you. Yeah, it's great to be here. Thanks for the invite. So why the biz ops manifesto, why the biz optical edition now when you guys have been at it, it's relatively mature marketplace businesses. Good. What was missing? Why, why this, uh, why this coalition? >>Yeah, so, you know, again, why is, why is biz ops important and why is this something I'm, you know, I'm so excited about, but I think companies as well, right. Well, you know, in some ways or another, this is a topic that I've been talking to, you know, the market and our customers about for a long time. And it's, you know, I really applaud, you know, this whole movement, right. And, um, in resonates with me, because I think one of the fundamental flaws, frankly, of the way we've talked about technology and business literally for decades, uh, has been this idea of, uh, alignment. Those who know me, I occasionally get off on this little rant about the word alignment, right. But to me, the word alignment is, is actually indicative of the, of the, of the flaw in a lot of our organizations and biz ops is really, I think now trying to catalyze and expose that flaw. >>Right. Because, you know, I always say that, you know, you know, alignment implies silos, right. Instantaneously, as soon as you say there's alignment, there's, there's obviously somebody who's got a direction and other people that have to line up and that, that kind of siloed, uh, nature of organizations. And then frankly, the passive nature of it. Right. I think so many technology organizations are like, look, the business has the strategy you guys need to align. Right. And, and, you know, as a product leader, right. That's where I've been my whole career. Right. I can tell you that I never sit around. I almost never use the word alignment. Right. I mean, whether I never sit down and say, you know, the product management team has to get aligned with Deb, right. Or the dev team has to get aligned with the delivery and ops teams. I mean, what I say is, you know, are we on strategy, right? >>Like we've, we have a strategy as a, as a full end to end value stream. Right. And that there's no silos. And I mean, look, every on any given day we got to get better. Right. But the context, the context we operate is not about alignment. Right. It's about being on strategy. And I think I've talked to customers a lot about that, but when I first read the manifesto, I was like, Oh yeah, this is exactly. This is breaking down. Maybe trying to eliminate the word alignment, you know, from a lot of our organizations, because we literally start thinking about one strategy and how we go from strategy to delivery and have it be our strategy, not someone else's that we're all aligning to it. And it's a great way to catalyze that conversation. That I've, it's been in my mind for years, to be honest. Right. >>So, so much to unpack there. One of the things obviously, uh, stealing a lot from, from dev ops and the dev ops manifesto from 20 years ago. And as I look through some of the principles and I looked through some of the values, which are, you know, really nicely laid out here, you know, satisfy customers, do continuous delivery, uh, measure, output against real results. Um, the ones that, that jumps out though is really about, you know, change, change, right? Requirements should change frequently. They do change frequently, but I'm curious to get your take from a, from a software development point, it's easy to kind of understand, right. We're making this widget and our competitors, beta widget plus X, and now we need to change our plans and make sure that the plus X gets added to the plan. Maybe it wasn't in the plan, but you talked a lot about product strategy. So in this kind of continuous delivery world, how does that meld with, I'm actually trying to set a strategy, which implies the direction for a little bit further out on the horizon and to stay on that while at the same time, you're kind of doing this real time continual adjustments. Cause you're not working off a giant PRD or MRD anymore. >>Yeah, yeah, totally. Yeah. You know, one of the terms, you know, that we use internally a lot and even with my customers, our customers is we talked about this idea of rewiring, right. And I think, you know, it's kind of a, now an analogy for transformation. And I think a lot of us have to rewire the way we think about things. Right. And I think at Planview where we have a lot of customers who live in that, you know, who operationalize that traditional PPM world. Right. And are shifting to agile and transforming that rewire is super important. And, and to your point, right, it's, you've just, you've got to embrace this idea of, you know, just iterative getting better every day and iterating, iterating, iterating as to building annual plans or, you know, I get customers occasionally who asked me for two or three year roadmap. >>Right. And I literally looked at them and I go, there's no, there's no scenario where I can build a two or three year roadmap. Right. You, you, you think you want that, but that's not, that's not the way we run. Right. And I will tell you the biggest thing that for us, you know, that I think is matched the planning, uh, you know, patents is a word I like to use a lot. So the thing that we've like, uh, that we've done from a planning perspective, I think is matched impedance to continuous delivery is instituting the whole program, implement, you know, the program, increment planning, capabilities and methodologies, um, in the scaled agile world. Right. And over the last 18 months to two years, we really have now, you know, instrumented our company across three value streams. You know, we do quarterly PI program increment 10 week planning, you know, and that becomes, that becomes the Terra firma of how we plant. >>Right. And it's, what are we doing for the next 10 weeks? And we iterate within those 10 weeks, but we also know that 10 weeks from now, we're going to, we're going to adjust iterate again. Right. And that shifting of that planning model, you know, to being as cross-functional is that as that big room planning kind of model is, um, and also, uh, you know, on that shorter increment, when you get those two things in place, all sudden the impedance really starts to match up, uh, with continuous delivery and it changes, it changes the way you plan and it changes the way you work. Right? >>Yeah. Their thing. Right. So obviously a lot of these things are kind of process driven, both within the values, as well as the principles, but there's a whole lot, really about culture. And I just want to highlight a couple of the values, right? We already talked about business outcomes, um, trust and collaboration, uh, data driven decisions, and then learn, respond and pivot. Right. A lot of those are cultural as much as they are process. So again, is it the, is it the need to really kind of just put them down on paper and you know, I can't help, but think of, you know, the hammering up the, uh, the thing in the Lutheran church with their, with their manifesto, is it just good to get it down on paper? Because when you read these things, you're like, well, of course we should trust people. And of course we need an environment of collaboration and of course we want data driven decisions, but as we all know saying it and living, it are two very, very different things. >>Yeah. Good question. I mean, I think there's a lot of ways you bring that to life you're right. And just hanging up, you know, I think we've all been through the hanging up posters around your office, which these days, right. Unless you're going to hang a poster and everybody's home office. Right. You can't even, you can't even fake it that you think that might work. Right. So, um, you know, you really, I think we've attacked that in a variety of ways. Right. And you definitely have to, you know, you've got to make the shift to a team centric culture, right. Empowered teams, you know, that's a big deal. Right. You know, a lot of, a lot of the people that, you know, we lived in a world of quote unquote, where we were lived in a deep resource management world for a long, long time. >>And right. A lot of our customers still do that, but you know, kind of moving to that team centric world is, uh, is really important and core the trust. Um, I think training is super important, right. We've, you know, we've internally, right. We've trained hundreds employees over the last a year and a half on the fundamentals really of safe. Right. Not necessarily, you know, we've had, we've had teams delivering in scrum and the continuous delivery for, you know, for years, but the scaling aspect of it, uh, is where we've done a lot of training and investment. Um, and then, you know, I think, uh, leadership has to be bought in. Right. You know? And so when we pie plan, you know, myself and Cameron and the other members of our leadership, you know, we're NPI planning, you know, for, for four days. Right. I mean, it's, it's, you've got to walk the walk, you know, from top to bottom and you've got to train on the context. Right. And then you, and then, and, and then once you get through a few cycles where you've done a pivot, right. Or you brought a new team in, and it just works, it becomes kind of this virtuous circle where he'll go, man, this really works so much better than what we used to do. Right. >>Right. The other really key principle to this whole thing is, is aligning, you know, the business leaders and the business prioritization, um, so that you can get to good outcomes with the development and the delivery. Right. And we, we know again, and kind of classic dev ops to get the dev and the production people together. So they can, you know, quickly ship code that works. Um, but adding the business person on there really puts, puts a little extra responsibility that they, they understand the value of a particular feature or particular priority. Uh, they, they can make the, the, the trade offs and that they kind of understand the effort involved too. So, you know, bringing them into this continuous again, kind of this continuous development process, um, to make sure that things are better aligned and really better prioritize. Cause ultimately, you know, we don't live in an infinite resources situation and people got to make trade offs. They got to make decisions as to what goes and what doesn't go in for everything that goes. Right. I always say you pick one thing. Okay. That's 99 other things that couldn't go. So it's really important to have, you know, this, you said alignment of the business priorities as well as, you know, the execution within, within the development. >>Yeah. I think that, you know, uh, you know, I think it was probably close to two years ago. Forester started talking about the age of the customer, right. That, that was like their big theme at the time. Right. And I think to me what that, the age of the customer actually translates to and Mick, Mick and I are both big fans of this whole idea of the project and product shift, mixed book, you know, it was a great piece on a, you're talking about, you know, as part of the manifesto is one of the authors as well, but this shift from project to product, right? Like the age of the customer, in my opinion, the, the embodiment of that is the shift to a product mentality. Right. And, and the product mentality in my opinion, is what brings the business and technology teams together, right? >>Once you, once you're focused on a customer experience is delivered through a product or a service. That's when I that's, when I started to go with the alignment problem goes away, right. Because if you look at software companies, right, I mean, we run product management models yeah. With software development teams, customer success teams, right. That, you know, the software component of these products that people are building is obviously becoming bigger and bigger, you know, in an, in many ways, right. More and more organizations are trying to model themselves over as operationally like software companies. Right. Um, they obviously have lots of other components in their business than just software, but I think that whole model of customer experience equaling product, and then the software component of product, the product is the essence of what changes that alignment equation and brings business and teams together because all of a sudden, everyone knows what the customer's experiencing. Right. And, and that, that, that makes a lot of things very clear, very quickly. >>Right. I'm just curious how far along this was as a process before, before COBIT hit, right. Because serendipitous, whatever. Right. But the sudden, you know, light switch moment, everybody had to go work from home and in March 15th compared to now we're in October and this is going to be going on for a while. And it is a new normal and whatever that whatever's going to look like a year from now, or two years from now is TBD, you know, had you guys already started on this journey cause again, to sit down and actually declare this coalition and declare this manifesto is a lot different than just trying to do better within your own organization. >>Yeah. So we had started, uh, you know, w we definitely had started independently, you know, some, some, you know, I think people in the community know that, uh, we, we came together with a company called lean kit a handful of years ago, and I give John Terry actually one of the founders LeanKit immense credit for, you know, kind of spearheading our cultural change and not, and not because of, we were just gonna be, you know, bringing agile solutions to our customers, but because, you know, he believed that it was going to be a fundamentally better way for us to work. Right. And we kind of, you know, we started with John and built, you know, out of concentric circles of momentum and, and we've gotten to the place where now it's just part of who we are, but, but I do think that, you know, COVID has, you know, um, I think pre COVID a lot of companies, you know, would, would adopt, you know, the would adopt digital slash agile transformation. >>Um, traditional industries may have done it as a reaction to disruption. Right. You know, and in many cases, the disruption to these traditional industries was, I would say a product oriented company, right. That probably had a larger software component, and that disruption caused a competitive issue, uh, or a customer issue that caused companies and tried to respond by transforming. I think COVID, you know, all of a sudden flatten that out, right. We literally all got disrupted. Right. And so all of a sudden, every one of us is dealing with some degree of market uncertainty, customer uncertainty, uh, and also, you know, none of us were insulated from the need to be able to pivot faster, deliver incrementally, you know, and operate in a different, completely more agile way, uh, you know, post COVID. Right. Yeah. That's great. >>So again, a very, very, very timely, you know, a little bit of serendipity, a little bit of planning. And, you know, as, as with all important things, there's always a little bit of lock in, uh, and a lot of hard work involved. So a really interesting thank you for, for your leadership, Patrick. And, you know, it really makes a statement. I think when you have a bunch of leaderships across an industry coming together and putting their name on a piece of paper, uh, that's aligned around us some principles and some values, which again, if you read them who wouldn't want to get behind these, but if it takes, you know, something a little bit more formal, uh, to kind of move the ball down the field, and then I totally get it and a really great work. Thanks for, uh, thanks for doing it. >>Oh, absolutely. No. Like I said, the first time I read it, I was like, yep. Like you said, this is all, it's all makes complete sense, but just documenting it and saying it and talking about it moves the needle. I'll tell you as a company, you gotta, we're pushing really hard on, uh, you know, on our own internal strategy on diversity and inclusion. Right. And, and like, once we wrote the words down about what, you know, what we aspire to be from a diversity and inclusion perspective, it's the same thing. Everybody reads the words that goes, why wouldn't we do this? Right. But until you write it down and kind of have again, a manifesto or a Terra firma of what you're trying to accomplish, you know, then you can rally behind it. Right. As opposed to it being something that's, everybody's got their own version of the flavor. Right. And I think it's a very analogous, you know, kind of, uh, initiative. Right. And, uh, and it's happening, both of those things right. Are happening across the industry these days. Right. >>And measure it too. Right. And measure it, measure, measure, measure, get a baseline. Even if you don't like to measure, even if you don't like what the, even if you can argue against the math, behind the measurement, measure it. And at least you can measure it again and you can, and you've got some type of a comp and that is really the only way to, to move it forward. We're Patrick really enjoyed the conversation. Thanks for, uh, for taking a few minutes out of your day. >>It's great to be here. It's an awesome movement and we're glad to be a part of it. >>All right. Thanks. And if you want to check out the biz ops, Manifesta go to biz ops, manifesto.org, read it. You might want to sign it. It's there for you. And thanks for tuning in on this segment will continuing coverage of the biz op manifesto unveil you're on the cube. I'm Jeff, thanks for watching >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back, everybody Jeffrey here with the cube. We're coming to you from our Palo Alto studios. And welcome back to this event is the biz ops manifesto unveiling. So the biz ops manifesto and the biz ops coalition had been around for a little while, but today's the big day. That's kind of the big public unveiling, or we're excited to have some of the foundational people that, you know, have put their, put their name on the dotted, if you will, to support this initiative and talk about why that initiative is so important. And so the next guest we're excited to have is dr. Mick Kirsten. He is the founder and CEO of Tasktop mic. Great to see you coming in from Vancouver, Canada, I think, right? Yes. Great to be here, Jeff. Thank you. Absolutely. I hope your air is a little better out there. I know you had some of the worst air of all of us, a couple, a couple of weeks back. So hopefully things are, uh, are getting a little better and we get those fires under control. Yeah. >>Things have cleared up now. So yeah, it's good. It's good to be close to the U S and it's going to have the Arabic cleaner as well. >>Absolutely. So let's, let's jump into it. So you you've been an innovation guy forever starting way back in the day and Xerox park. I was so excited to do an event at Xerox park for the first time last year. I mean, that, that to me represents along with bell labs and, and some other, you know, kind of foundational innovation and technology centers, that's gotta be one of the greatest ones. So I just wonder if you could share some perspective of getting your start there at Xerox park, you know, some of the lessons you learned and what you've been able to kind of carry forward from those days. >>Yeah. I was fortunate to join Xerox park in the computer science lab there at a fairly early point in my career, and to be working on open source programming languages. So back then in the computer science lab, where some of the inventions around programming around software development games, such as object programming, and a lot of what we had around really modern programming levels constructs, those were the teams I had the fortunate of working with, and really our goal was. And of course, there's, as, as you noticed, there's just this DNA of innovation and excitement and innovation in the water. And really it was the model that was all about changing the way that we work was looking at for how we can make it 10 times easier to white coat. But this is back in 99. And we were looking at new ways of expressing, especially business concerns, especially ways of enabling people who are wanting to innovate for their business to express those concerns in code and make that 10 times easier than what that would take. >>So we create a new open source programming language, and we saw some benefits, but not quite quite what we expected. I then went and actually joined Charles Stephanie, that former to fucking from Microsoft who was responsible for, he actually got Microsoft word as a sparking into Microsoft and into the hands of bill Gates and that company that was behind the whole office suite and his vision. And then when I was trying to execute with, working for him was to make PowerPoint like a programming language to make everything completely visual. And I realized none of this was really working, that there was something else, fundamentally wrong programming languages, or new ways of building software. Like let's try and do with Charles around intentional programming. That was not enough. >>That was not enough. So, you know, the agile movement got started about 20 years ago, and we've seen the rise of dev ops and really this kind of embracing of, of, of sprints and, you know, getting away from MRDs and PRDs and these massive definitions of what we're going to build and long build cycles to this iterative process. And this has been going on for a little while. So what was still wrong? What was still missing? Why the biz ops coalition, why the biz ops manifesto? >>Yeah, so I basically think we nailed some of the things that the program language levels of teams can have effective languages deployed to soften to the cloud easily now, right? And at the kind of process and collaboration and planning level agile two decades, decades ago was formed. We were adopting and all the, all the teams I was involved with and it's really become a self problem. So agile tools, agile teams, agile ways of planning, uh, are now very mature. And the whole challenge is when organizations try to scale that. And so what I realized is that the way that agile was scaling across teams and really scaling from the technology part of the organization to the business was just completely flawed. The agile teams had one set of doing things, one set of metrics, one set of tools. And the way that the business was working was planning was investing in technology was just completely disconnected and using a whole different set of measures. Pretty >>Interesting. Cause I think it's pretty clear from the software development teams in terms of what they're trying to deliver. Cause they've got a feature set, right. And they've got bugs and it's easy to, it's easy to see what they deliver, but it sounds like what you're really honing in on is this disconnect on the business side, in terms of, you know, is it the right investment? You know, are we getting the right business ROI on this investment? Was that the right feature? Should we be building another feature or should we building a completely different product set? So it sounds like it's really a core piece of this is to get the right measurement tools, the right measurement data sets so that you can make the right decisions in terms of what you're investing, you know, limited resources. You can't, nobody has unlimited resources. And ultimately you have to decide what to do, which means you're also deciding what not to do. And it sounds like that's a really big piece of this, of this whole effort. >>Yeah. Jeff, that's exactly it, which is the way that the agile team measures their own way of working is very different from the way that you measure business outcomes. The business outcomes are in terms of how happy your customers are, but are you innovating fast enough to keep up with the pace of a rapidly changing economy, roughly changing market. And those are, those are all around the customer. And so what I learned on this long journey of supporting many organizations transformations and having them try to apply those principles of agile and dev ops, that those are not enough, those measures technical practices, uh, those measured sort of technical excellence of bringing code to the market. They don't actually measure business outcomes. And so I realized that it really was much more around having these entwined flow metrics that are customer centric and business centric and market centric where we need it to go. Right. >>So I want to shift gears a little bit and talk about your book because you're also a bestselling author from project to product and, and, and you, you brought up this concept in your book called the flow framework. And it's really interesting to me cause I know, you know, flow on one hand is kind of a workflow and a process flow and, and you know, that's how things get done and, and, and embrace the flow. On the other hand, you know, everyone now in, in a little higher level existential way is trying to get into the flow right into the workflow and, you know, not be interrupted and get into a state where you're kind of at your highest productivity, you know, kind of your highest comfort, which flow are you talking about in your book? Or is it a little bit of both? >>That's a great question. It's not one I get asked very often cause to me it's absolutely both. So that the thing that we want to get, that we've learned how to master individual flow, that there's this beautiful book by me, how you teaches me how he does a beautiful Ted talk by him as well about how we can take control of our own flow. So my question with the book with question replies, how can we bring that to entire teams and really entire organizations? How can we have everyone contributing to a customer outcome? And this is really what if you go to the biz ops manifesto, it says, I focus on outcomes on using data to drive whether we're delivering those outcomes rather than a focus on proxy metrics, such as, how quickly did we implement this feature? No, it's really how much value did the customer go to the future? >>And how quickly did you learn and how quickly did you use that data to drive to that next outcome? Really that with companies like Netflix and Amazon have mastered, how do we get that to every large organization, every it organization and make everyone be a software innovator. So it's to bring that, that concept of flow to these end to end value streams. And the fascinating thing is we've actually seen the data. We've been able to study a lot of value streams. We see when flow increases, when organizations deliver value to a customer faster, developers actually become more happy. So things like that and point out promoter scores, rise, and we've got empirical data for this. So that the beautiful thing to me is that we've actually been able to combine these two things and see the results and the data that you increase flow to the customer. Your developers are more, >>I love it. I love it, right, because we're all more, we're all happier when we're in the flow and we're all more productive when we're in the flow. So I, that is a great melding of, of two concepts, but let's jump into the, into the manifesto itself a little bit. And you know, I love that you took this approach really of having kind of four key values and then he gets 12 key principles. And I just want to read a couple of these values because when you read them, it sounds pretty brain dead. Right? Of course. Right. Of course you should focus on business outcomes. Of course you should have trust and collaboration. Of course you should have database decision making processes and not just intuition or, you know, whoever's the loudest person in the room, uh, and to learn and respond and pivot. But what's the value of actually just putting them on a piece of paper, because again, this is not this, these are all good, positive things, right? When somebody reads these to you or tells you these are sticks it on the wall, of course. But unfortunately of course isn't always enough. >>No. And I think what's happened is some of these core principles originally from the agile manifesto in two decades ago, uh, the whole dev ops movement of the last decade of flow feedback and continue learning has been key. But a lot of organizations, especially the ones undergoing digital transformations have actually gone a very different way, right? The way that they measure value, uh, in technology and innovation is through costs for many organizations. The way that they actually are looking at that they're moving to cloud is actually as a reduction in cost. Whereas the right way of looking at moving to cloud is how much more quickly can we get to the value to the customer? How quickly can we learn from that? And how quickly can we drive the next business outcome? So really the key thing is, is to move away from those old ways of doing things of funding projects and cost centers, to actually funding and investing in outcomes and measuring outcomes through these flow metrics, which in the end are your fast feedback and how quickly you're innovating for your customer. >>So these things do seem very obvious when you look at them. But the key thing is what you need to stop doing to focus on these. You need to actually have accurate realtime data of how much value you fund to the customer every week, every month, every quarter. And if you don't have that, your decisions are not driven on data. If you don't know what your bottleneck is. And this is something that in decades of manufacturing, a car manufacturers, other manufacturers, master, they always know where the bottom back in their production processes. You ask a random CIO when a global 500 company where their bottleneck is, and you won't get a clear answer because there's not that level of understanding. So have to actually follow these principles. You need to know exactly where you fall. And I guess because that's, what's making your developers miserable and frustrated, then having them context, which I'm trash. So the approach here is important and we have to stop doing these other things, >>Right? There's so much there to unpack. I love it. You know, especially the cloud conversation because so many people look at it wrong as, as, as a cost saving a device, as opposed to an innovation driver and they get stuck, they get stuck in the literal. And I, you know, I think at the same thing, always about Moore's law, right? You know, there's a lot of interesting real tech around Moore's law and the increasing power of microprocessors, but the real power, I think in Moore's laws is the attitudinal change in terms of working in a world where you know that you've got all this power and what you build and design. I think it's funny to your, your comment on the flow and the bottleneck, right? Cause, cause we know manufacturing, as soon as you fix one bottleneck, you move to your next one, right? You always move to your next point of failure. So if you're not fixing those things, you know, you're not, you're not increasing that speed down the line, unless you can identify where that bottleneck is or no matter how many improvements you make to the rest of the process, it's still going to get hung up on that one spot. >>That's exactly it. And you also make it sound so simple, but again, if you don't have the data driven visibility of where the bottom line is, and these bottlenecks are adjusted to say, it's just whack-a-mole right. So we need to understand is the bottleneck because our security reviews are taking too long and stopping us from getting value for the customer. If it's that automate that process. And then you move on to the next bottleneck, which might actually be that deploying yourself into the cloud was taking too long. But if you don't take that approach of going flow first, rather than again, that sort of cost reduction. First, you have to think of that approach of customer centricity and you only focused on optimizing costs. Your costs will increase and your flow will slow down. And this is just one of these fascinating things. Whereas if you focus on getting back to the customer and reducing your cycles on getting value, your flow time from six months to two weeks or two, one week or two event, as we see with, with tech giants, you actually can both lower your costs and get much more value that for us to get that learning loop going. >>So I think I've seen all of these cloud deployments and one of the things that's happened that delivered almost no value because there was such big bottlenecks upfront in the process and actually the hosting and the AP testing was not even possible with all of those inefficiencies. So that's why going float for us rather than costs where we started our project versus silky. >>I love that. And, and, and, and it, it begs repeating to that right within the subscription economy, you know, you're on the hook to deliver value every single month because they're paying you every single month. So if you're not on top of how you're delivering value, you're going to get sideways because it's not like, you know, they pay a big down payment and a small maintenance fee every month, but once you're in a subscription relationship, you know, you have to constantly be delivering value and upgrading that value because you're constantly taking money from the customer. So it's such a different kind of relationship than kind of the classic, you know, big bang with a maintenance agreement on the back end really important. Yeah. >>And I think in terms of industry shifts that that's it that's, what's catalyzed. This interesting shift is in this SAS and subscription economy. If you're not delivering more and more value to your customers, someone else's and they're winning the business, not you. So one way we know is to delight our customers with great user experiences. Well, that really is based on how many features you delivered or how much, how big, how many quality improvements or scalar performance improvements you delivered. So the problem is, and this is what the business manifesto, as well as the full frame of touch on is if you can't measure how much value you delivered to a customer, what are you measuring? You just backed again, measuring costs and that's not a measure of value. So we have to shift quickly away from measuring cost to measuring value, to survive in the subscription economy. >>We could go for days and days and days. I want to shift gears a little bit into data and, and, and a data driven, um, decision making a data driven organization cause right day has been talked about for a long time, the huge big data meme with, with Hadoop over, over several years and, and data warehouses and data lakes and data oceans and data swamps, and can go on and on and on. It's not that easy to do, right? And at the same time, the proliferation of data is growing exponentially. We're just around the corner from, from IOT and 5g. So now the accumulation of data at machine scale, again, this is going to overwhelm and one of the really interesting principles, uh, that I wanted to call out and get your take right, is today's organizations generate more data than humans can process. So informed decisions must be augmented by machine learning and artificial intelligence. I wonder if you can, again, you've got some great historical perspective, um, reflect on how hard it is to get the right data, to get the data in the right context, and then to deliver it to the decision makers and then trust the decision makers to actually make the data and move that down. You know, it's kind of this democratization process into more and more people and more and more frontline jobs making more and more of these little decisions every day. >>Yeah. I definitely think the front parts of what you said are where the promises of big data have completely fallen on their face into the swamps as, as you mentioned, because if you don't have the data in the right format, you've cannot connect collected at the right way. You want that way, the right way you can't use human or machine learning effectively. And there've been the number of data warehouses in a typical enterprise organization. And the sheer investment is tremendous, but the amount of intelligence being extracted from those is, is, is a very big problem. So the key thing that I've noticed is that if you can model your value streams, so yes, you understand how you're innovating, how you're measuring the delivery of value and how long that takes. What is your time to value these metrics like full time? You can actually use both the intelligence that you've got around the table and push that down as well, as far as getting to the organization, but you can actually start using that those models to understand and find patterns and detect bottlenecks that might be surprising, right? >>Well, you can detect interesting bottlenecks when you shift to work from home. We detected all sorts of interesting bottlenecks in our own organization that were not intuitive to me that had to do with, you know, more senior people being overloaded and creating bottlenecks where they didn't exist. Whereas we thought we were actually an organization that was very good at working from home because of our open source roots. So that data is highly complex. Software value streams are extremely complicated. And the only way to really get the proper analyst and data is to model it properly and then to leverage these machine learning and AI techniques that we have. But that front part of what you said is where organizations are just extremely immature in what I've seen, where they've got data from all their tools, but not modeled in the right way. Right, right. >>Right. Well, all right. So before I let you go, you know, let's say you get a business leader, he buys in, he reads the manifesto, he signs on the dotted line and he says, Mick, how do I get started? I want to be more aligned with, with the development teams. You know, I'm in a very competitive space. We need to be putting out new software features and engaging with our customers. I want to be more data-driven how do I get started? Well, you know, what's the biggest inhibitor for most people to get started and get some early wins, which we know is always the key to success in any kind of a new initiative. >>Right? So I think you can reach out to us through the website, uh, there's the manifesto, but the key thing is just to get you set up it's to get started and to get the key wins. So take a probably value stream that's mission critical. It could be your new mobile and web experiences or, or part of your cloud modernization platform or your analytics pipeline, but take that and actually apply these principles to it and measure the end to end flow of value. Make sure you have a value metric that everyone is on the same page on the people, on the development teams, the people in leadership all the way up to the CEO. And one of the, what I encourage you to start is actually that content flow time, right? That is the number one metric. That is how you measure it, whether you're getting the benefit of your cloud modernization, that is the one metric that Adrian Cockcroft. When the people I respect tremendously put into his cloud for CEOs, the metric, the one, the one way to measure innovation. So basically take these principles, deploy them on one product value stream, measure, sentiment, flow time, and then you'll actually be well on your path to transforming and to applying the concepts of agile and dev ops all the way to, to the business, to the way >>You're offering model. >>Well, Mick really great tips, really fun to catch up. I look forward to a time when we can actually sit across the table and, and get into this. Cause I just, I just love the perspective and, you know, you're very fortunate to have that foundational, that foundational base coming from Xerox park and they get, you know, it's, it's a very magical place with a magical history. So to, to incorporate that into, continue to spread that well, uh, you know, good for you through the book and through your company. So thanks for sharing your insight with us today. >>Thanks so much for having me, Jeff. >>All right. And go to the biz ops manifesto.org, read it, check it out. If you want to sign it, sign it. They'd love to have you do it. Stay with us for continuing coverage of the unveiling of the business manifesto on the cube. I'm Jeff. Rick. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube come due from our Palo Alto studios today for a big, big reveal. We're excited to be here. It's the biz ops manifesto unveiling a thing's been in the works for awhile and we're excited to have our next guest. One of the, really the powers behind this whole effort. And he's joining us from Boston it's surge, Lucio, the vice president, and general manager enterprise software division at Broadcom surge. Great to see you. >>Hi, good to see you, Jeff. Glad to be here. >>So you've been in this business for a very long time. You've seen a lot of changes in technology. What is the biz ops manifesto? What is this coalition all about? Why do we need this today and in 2020? >>Yeah. So, so I've been in this business for close to 25 years, right? So about 20 years ago, the agile manifesto was created. And the goal of the agile manifesto was really to address the uncertainty around software development and the inability to predict the efforts to build software. And, uh, if you, if you roll that kind of 20 years later, and if you look at the current state of the industry, uh, the product, the project management Institute, estimates that we're wasting about a million dollars, every 20 seconds in digital transformation initiatives that do not deliver on business results. In fact, we were recently served a third of the, uh, a number of executives in partnership with Harvard business review and 77% of those executives think that one of the key challenges that they have is really at the collaboration between business and it, and that that's been kind of a case for, uh, almost 20 years now. >>Um, so the, the, the key challenge we're faced with is really that we need a new approach and many of the players in the industry, including ourselves, I've been using different terms, right? Some are being, are talking about value stream management. Some are talking about software delivery management. If you look at the site, reliability engineering movement, in many ways, it embodies a lot of these kind of concepts and principles. So we believed that it became really imperative for us to crystallize around, could have one concept. And so in many ways, the, uh, the BizOps concept and the business manifesto are bringing together a number of ideas, which have been emerging in the last five years or so, and, and defining the key values and principles to finally help these organizations truly transform and become digital businesses. And so the hope is that by joining our forces and defining public key principles and values, we can help the industry, uh, not just, uh, by, you know, providing them with support, but also, uh, tools and consulting that is required for them to truly achieve the kind of transformation that everybody's seeking. >>Right, right. So COVID now we're six months into it, approximately seven months into it. Um, a lot of pain, a lot of bad stuff still happening. We've got a ways to go, but one of the things that on the positive side, right, and you've seen all the memes and social media is, is a driver of digital transformation and a driver of change. Cause we had this light switch moment in the middle of March and there was no more planning. There was no more conversation. You've suddenly got remote workforces, everybody's working from home and you got to go, right. So the reliance on these tools increases dramatically, but I'm curious, you know, kind of short of, of the beginnings of this effort in short of kind of COVID, which, you know, came along unexpectedly. I mean, what were those inhibitors because we've been making software for a very long time, right? The software development community has, has adopted kind of rapid change and, and iterative, uh, delivery and, and sprints, what was holding back the connection with the business side to make sure that those investments were properly aligned with outcomes. >>Well, so, so you have to understand that it is, is kind of a its own silos. And traditionally it has been treated as a cost center within large organizations and not as a value center. And so as a result could have a traditional dynamic between it and the business is basically one of a kind of supplier up to kind of a business. Um, and you know, if you, if you go back to, uh, I think you'll unmask a few years ago, um, basically at this concept of the machines to build the machines and you went as far as saying that, uh, the machines or the production line is actually the product. So, um, meaning that the core of the innovation is really about, uh, building, could it be engine to deliver on the value? And so in many ways, you know, we have missed on this shift from, um, kind of it becoming this kind of value center within the enterprises. >>And, and he talks about culture. Now, culture is a, is a sum total of beavers. And the reality is that if you look at it, especially in the last decade, uh, we've agile with dev ops with, um, I bring infrastructures, uh, it's, it's way more volatile today than it was 10 years ago. And so the, when you start to look at the velocity of the data, the volume of data, the variety of data to analyze this system, um, it's, it's very challenging for it to actually even understand and optimize its own processes, let alone, um, to actually include business as sort of an integral part of kind of a delivery chain. And so it's both kind of a combination of, of culture, um, which is required as well as tools, right? To be able to start to bring together all these data together, and then given the volume variety of philosophy of the data, uh, we have to apply some core technologies, which have only really, truly emerged in the last five to 10 years around machine learning and analytics. And so it's really kind of a combination of those freaks, which are coming together today to really help organizations kind of get to the next level. Right, >>Right. So let's talk about the manifesto. Let's talk about, uh, the coalition, uh, the BizOps coalition. I just liked that you put down these really simple, you know, kind of straightforward core values. You guys have four core values that you're highlighting, you know, business outcomes, over individual projects and outputs, trust, and collaboration, oversight, load teams, and organizations, data driven decisions, what you just talked about, uh, you know, over opinions and judgment and learned, respond and pivot. I mean, surgery sounds like pretty basic stuff, right? I mean, aren't, isn't everyone working to these values already. And I think he touched on it on culture, right? Trust and collaboration, data driven decisions. I mean, these are fundamental ways that people must run their business today, or the person that's across the street, that's doing it. It's going to knock them out right off their blog. >>Yeah. So that's very true. But, uh, so I'll, I'll mention in our survey, we did, uh, I think about six months ago and it was in partnership with, uh, with, uh, an industry analyst and we serve at a, again, a number of it executives to understand how many we're tracking business outcomes I'm going to do with the software executives. It executives we're tracking business outcomes. And the, there were less than 15% of these executives were actually tracking the outcomes of a software delivery. And you see that every day. Right? So in my own teams, for instance, we've been adopting a lot of these core principles in the last year or so, and we've uncovered that 16% of our resources were basically aligned around initiatives, which are not strategic for us. Um, I take, you know, another example, for instance, one of our customers in the, uh, in the airline industry and Harvard, for instance, that a number of, uh, um, that they had software issues that led to people searching for flights and not returning any kind of availability. >>And yet, um, you know, the, it teams, whether it's operations, software environments were completely oblivious to that because they were completely blindsided to it. And so the connectivity between kind of the inwards metrics that RT is using, whether it's database time, cycle time, or whatever metric we use in it are typically completely divorced from the business metrics. And so at its core, it's really about starting to align the business metrics with what the, the software delivery chain, right? This, uh, the system, which is really a core differentiator for these organizations. It's about connecting those two things and, and starting to, um, infuse some of the agile culture and principles. Um, that's emerged from the software side into the business side. Um, of course the lean movement and other movements have started to change some of these dynamic on the, on the business side. And so I think this, this is the moment where we are starting to see kind of the imperative to transform. Now, you know, Covina obviously has been a key driver for that. The, um, the technology is right to start to be able to weave data together and really kind of, uh, also the cultural shifts, uh, Prue agile through dev ops through, uh, the SRE movement, uh frulein um, business transformation, all these things are coming together and that are really creating kind of the conditions for the BizOps manifesto to exist. >>So, uh, Clayton Christianson, great, uh, Harvard professor innovator's dilemma might still my all time favorite business books, you know, talks about how difficult it is for incumbents to react to, to disruptive change, right? Because they're always working on incremental change because that's what their customers are asking for. And there's a good ROI when you talk about, you know, companies not measuring the right thing. I mean, clearly it has some portion of their budget that has to go to keeping the lights on, right. That that's always the case, but hopefully that's an, an ever decreasing percentage of their total activity. So, you know, what should people be measuring? I mean, what are kind of the new metrics, um, in, in biz ops that drive people to be looking at the right things, measuring the right things and subsequently making the right decisions, investment decisions on whether they should do, you know, move project a along or project B. >>So there, there are only two things, right? So, so I think what you're talking about is portfolio management, investment management, right. And, um, which, which is a key challenge, right? Um, in my own experience, right? Uh, driving strategy or a large scale kind of software organization for years, um, it's very difficult to even get kind of a base data as to who is doing what, uh, um, I mean, some of our largest customers we're engaged with right now are simply trying to get a very simple answer, which is how many people do I have and that specific initiative at any point in time, and just tracking that information is extremely difficult. So, and again, back to a product project management Institute, um, there, they have estimated that on average, it organizations have anywhere between 10 to 20% of their resources focused on initiatives, which are not strategically aligned. >>So, so that's one dimensional portfolio management. I think the key aspect though, that we are, we're really keen on is really around kind of the alignment of a business metrics to the it metrics. Um, so I'll use kind of two simple examples, right? And my background is around quality and I've always believed that the fitness for purpose is really kind of a key, um, uh, philosophy if you will. And so if you start to think about quality as fitness for purpose, you start to look at it from a customer point of view, right. And fitness for purpose for a core banking application or mobile application are different, right? So the definition of a business value that you're trying to achieve is different. Um, and so the, and yeah, if you look at our, it, operations are operating there, we're using kind of a same type of, uh, kind of inward metrics, uh, like a database off time or a cycle time, or what is my point of velocity, right? >>And so the challenge really is this inward facing metrics that it is using, which are divorced from ultimately the outcome. And so, you know, if I'm, if I'm trying to build a poor banking application, my core metric is likely going to be uptight, right? If I'm trying to build a mobile application or maybe your social, a mobile app, it's probably going to be engagement. And so what you want is for everybody across it, to look at these metric and what are the metrics within the software delivery chain, which ultimately contribute to that business metric. And some cases cycle time may be completely irrelevant, right? Again, my core banking app, maybe I don't care about cycle time. And so it's really about aligning those metrics and be able to start to, um, Charles you mentioned, uh, around the, the, um, uh, around the disruption that we see is, or the investors is the dilemma now is really around the fact that many it organizations are essentially applying the same approaches of, for innovation, like for basically scrap work, then they would apply to kind of over more traditional projects. And so, you know, there's been a lot of talk about two-speed it, and yes, it exists, but in reality are really organizations, um, truly differentiating, um, all of the operate, their, their projects and products based on the outcomes that they're trying to achieve. And this is really where BizOps is trying to affect. >>I love that, you know, again, it doesn't seem like brain surgery, but focus on the outcomes, right. And it's horses for courses, as you said, this project, you know, what you're measuring and how you define success, isn't necessarily the same as, as on this other project. So let's talk about some of the principles we talked about the values, but, you know, I think it's interesting that, that, that the BizOps coalition, you know, just basically took the time to write these things down and they don't seem all that super insightful, but I guess you just got to get them down and have them on paper and have them in front of your face. But I want to talk about, you know, one of the key ones, which you just talked about, which is changing requirements, right. And working in a dynamic situation, which is really what's driven, you know, this, the software to change in software development, because, you know, if you're in a game app and your competitor comes out with a new blue sword, you got to come out with a new blue sword. >>So whether you had that on your Kanban wall or not. So it's, it's really this embracing of the speed of change and, and, and, and making that, you know, the rule, not the exception. I think that's a phenomenal one. And the other one you talked about is data, right? And that today's organizations generate more data than humans can process. So informed decisions must be generated by machine learning and AI, and, you know, in the, the big data thing with Hadoop, you know, started years ago, but we are seeing more and more that people are finally figuring it out, that it's not just big data, and it's not even generic machine learning or artificial intelligence, but it's applying those particular data sets and that particular types of algorithms to a specific problem, to your point, to try to actually reach an objective, whether that's, you know, increasing the, your average ticket or, you know, increasing your checkout rate with, with, with shopping carts that don't get left behind in these types of things. So it's a really different way to think about the world in the good old days, probably when you got started, when we had big, giant, you know, MRDs and PRDs and sat down and coded for two years and came out with a product release and hopefully not too many patches subsequently to that. >>It's interesting. Right. Um, again, back to one of these surveys that we did with, uh, with about 600, the ITA executives, and, uh, and, and we, we purposely designed those questions to be pretty open. Um, and, and one of them was really wrong requirements and, uh, and it was really a wrong, uh, kind of what do you, what is the best approach? What is your preferred approach towards requirements? And if I were to remember correctly, over 80% of the it executives set that the best approach they'll prefer to approach these core requirements to be completely defined before software development starts, let me pause there we're 20 years after the agile manifesto, right? And for 80% of these idea executives to basically claim that the best approach is for requirements to be fully baked before salt, before software development starts, basically shows that we still have a very major issue. >>And again, our hypothesis in working with many organizations is that the key challenge is really the boundary between business and it, which is still very much contract based. If you look at the business side, they basically are expecting for it deliver on time on budget, right. But what is the incentive for it to actually delivering on the business outcomes, right? How often is it measured on the business outcomes and not on an SLA or on a budget type criteria? And so that's really the fundamental shift that we need to, we really need to drive up as an industry. Um, and you know, we, we talk about kind of this, this imperative for organizations to operate that's one, and back to the, the, um, you know, various Doris dilemna the key difference between these larger organization is, is really kind of, uh, if you look at the amount of capital investment that they can put into pretty much anything, why are they losing compared to, um, you know, startups? What, why is it that, uh, more than 40% of, uh, personal loans today or issued not by your traditional brick and mortar banks, but by, um, startups? Well, the reason, yes, it's the traditional culture of doing incremental changes and not disrupting ourselves, which Christiansen covered the length, but it's also the inability to really fundamentally change kind of a dynamic picture. We can business it and, and, and partner right. To, to deliver on a specific business outcome. >>All right. I love that. That's a great, that's a great summary. And in fact, getting ready for this interview, I saw you mentioning another thing where, you know, the, the problem with the agile development is that you're actually now getting more silos. Cause you have all these autonomous people working, you know, kind of independently. So it's even a harder challenge for, for the business leaders to, to, as you said, to know, what's actually going on, but, but certainly I w I want to close, um, and talk about the coalition. Um, so clearly these are all great concepts. These are concepts you want to apply to your business every day. Why the coalition, why, you know, take these concepts out to a broader audience, including either your, your competition and the broader industry to say, Hey, we, as a group need to put a stamp of approval on these concepts, these values, these principles. >>So first I think we, we want, um, everybody to realize that we are all talking about the same things, the same concepts. I think we were all from our own different vantage point, realizing that things after change, and again, back to, you know, whether it's value stream management or site reliability engineering, or biz ops, we're all kind of using slightly different languages. Um, and so I think one of the important aspects of BizOps is for us, all of us, whether we're talking about, you know, consulting agile transformation experts, uh, whether we're talking about vendors, right, provides kind of tools and technologies or these large enterprises to transform for all of us to basically have kind of a reference that lets us speak around kind of, um, in a much more consistent way. The second aspect is for, to me is for, um, DS concepts to start to be embraced, not just by us or trying, or, you know, vendors, um, system integrators, consulting firms, educators, thought leaders, but also for some of our old customers to start to become evangelists of their own in the industry. >>So we, our, our objective with the coalition needs to be pretty, pretty broad. Um, and our hope is by, by starting to basically educate, um, our, our joint customers or partners, that we can start to really foster these behaviors and start to really change some of dynamics. So we're very pleased at if you look at, uh, some of the companies which have joined the, the, the, the manifesto. Um, so we have vendors such as desktop or advance, or, um, uh, PagerDuty for instance, or even planned view, uh, one of my direct competitors, um, but also thought leaders like Tom Davenport or, uh, or cap Gemini or, um, um, smaller firms like, uh, business agility, institutes, or agility elf. Um, and so our goal really is to start to bring together, uh, fall years, people would have been LP, large organizations, do digital transformation vendors. We're providing the technologies that many of these organizations use to deliver on this digital preservation and for all of us to start to provide the kind of, uh, education support and tools that the industry needs. Yeah, >>That's great surge. And, uh, you know, congratulations to you and the team. I know this has been going on for a while, putting all this together, getting people to sign onto the manifesto, putting the coalition together, and finally today getting to unveil it to the world in, in a little bit more of a public, uh, opportunity. So again, you know, really good values, really simple principles, something that, that, uh, shouldn't have to be written down, but it's nice cause it is, and now you can print it out and stick it on your wall. So thank you for, uh, for sharing this story and again, congrats to you and the team. >>Thank you. Thanks, Jeff. Appreciate it. >>Oh, my pleasure. Alrighty, surge. If you want to learn more about the BizOps manifest to go to biz ops manifesto.org, read it and you can sign it and you can stay here for more coverage. I'm the cube of the biz ops manifesto unveiled. Thanks for watching. See you next >>From around the globe. It's the cube with digital coverage of this ops manifesto unveiled brought to you by bill. >>Hey, welcome back, everybody Jeffrey here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto unveiling. It's been in the works for awhile, but today's the day that it actually kind of come out to the, to the public. And we're excited to have a real industry luminary here to talk about what's going on, why this is important and share his perspective. And we're happy to have from Cape Cod, I believe is Tom Davenport. He is a distinguished author and professor at Babson college. We could go on, he's got a lot of great titles and, and really illuminary in the area of big data and analytics Thomas. Great to see you. >>Thanks Jeff. Happy to be here with you. >>Great. So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn posts. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address longterm issues, uh, in how technology works within businesses, biz ops. What did you see in biz ops, uh, that, that kind of addresses one of these really big longterm problems? >>Well, yeah, but the longterm problem is that we've had a poor connection between business people and it people between business objectives and the, it solutions that address them. This has been going on, I think since the beginning of information technology and sadly it hasn't gone away. And so biz ops is a new attempt to deal with that issue with, you know, a new framework, eventually a broad set of solutions that increase the likelihood that we'll actually solve a business problem with an it capability. >>Right. You know, it's interesting to compare it with like dev ops, which I think a lot of people are probably familiar with, which was, you know, built around, uh, agile software development and a theory that we want to embrace change that that changes. Okay. Uh, and we want to be able to iterate quickly and incorporate that. And that's been happening in the software world for, for 20 plus years. What's taken so long to get that to the business side, because as the pace of change has changed on the software side, you know, that's a strategic issue in terms of execution on the business side that they need now to change priorities. And, you know, there's no PRDs and MRDs and big, giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. It took a long time to get here. >>Yeah, it did. And you know, there have been previous attempts to make a better connection between business and it, there was the so called alignment framework that a couple of friends of mine from Boston university developed, I think more than 20 years ago, but you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's time for another serious attempt at it. Right. >>And do you think doing it this way, right. With the, with the biz ops coalition, you know, getting a collection of, of, of kind of likeminded individuals and companies together, and actually even having a manifesto, which we're making this declarative statement of, of principles and values, you think that's what it takes to kind of drive this kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in, uh, in production in the field. >>I think certainly, um, no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think our coalition is a good idea and a manifesto is just a good way to kind of lay out what you see as the key principles of the idea. And that makes it much easier for everybody to understand and act on. >>I think it's just, it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the, of the values as well as, as the, uh, the principles and the values, you know, business outcomes matter trust and collaboration, data driven decisions, which is the number three or four, and then learn, respond and pivot. It doesn't seem like those should have to be spelled out so clearly, but, but obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are, but you're the data guy. You're the analytics guy, uh, and a big piece of this is data and analytics and moving to data-driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process and informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the mini stages of analytics. Um, and how has that's evolved over, over time, you know, as you think of analytics and machine learning, driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that, what's that thing for you? What does that make you, you know, start to think, wow, this is, this is going to be pretty significant. >>Yeah. Well, you know, this has been a longterm interest of mine. Um, the last generation of AI, I was very interested in expert systems. And then, um, I think, uh, more than 10 years ago, I wrote an article about automated decision-making using what was available then, which was rule-based approaches. Um, but you know, this addresses an issue that we've always had with analytics and AI. Um, you know, we, we tended to refer to those things as providing decision support. The problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions, um, with now contemporary AI tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think at least for, you know, repetitive tactical decisions, um, involving a lot of data, we want most of those, I think to be at least recommended if not totally made by an algorithm or an AI based system, and that I believe would add to the quality and the precision and the accuracy of decisions and in most organizations, >>No, I think, I think you just answered my next question before I, before Hey, asked it, you know, we had dr. Robert Gates on a former secretary of defense on a few years back, and we were talking about machines and machines making decisions. And he said at that time, you know, the only weapon systems, uh, that actually had an automated trigger on it were on the North Korea and South Korea border. Um, everything else, as you said, had to go through a sub person before the final decision was made. And my question is, you know, what are kind of the attributes of the decision that enable us to more easily automated? And then how do you see that kind of morphing over time, both as the data to support that as well as our comfort level, um, enables us to turn more and more actual decisions over to the machine? >>Well, yeah, it's suggested we need, um, data and, um, the data that we have to kind of train our models has to be high quality and current. And we, we need to know the outcomes of that data. You know, um, most machine learning models, at least in business are supervised. And that means we need to have labeled outcomes in the, in the training data. But I, you know, um, the pandemic that we're living through is a good illustration of the fact that, that the data also have to be reflective of current reality. And, you know, one of the things that we're finding out quite frequently these days is that, um, the data that we have do not reflect, you know, what it's like to do business in a pandemic. Um, I wrote a little piece about this recently with Jeff cam at wake forest university, we called it data science quarantined, and we interviewed with somebody who said, you know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Um, our models maybe have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have to make sure that the data from the past and that's all we have of course, is a good guide to, you know, what's happening in the present and the future as far as we understand it. Yeah. >>I used to joke when we started this calendar year 2020, it was finally the year that we know everything with the benefit of hindsight, but it turned out 20, 20 a year. We found out we actually know nothing and everything thought we knew, but I wanna, I wanna follow up on that because you know, it did suddenly change everything, right? We got this light switch moment. Everybody's working from home now we're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold fold or double down. And, and I can't think of a more, you know, kind of appropriate metaphor for driving the value of the BizOps when now your whole portfolio strategy, um, these to really be questioned and, and, you know, you have to be really, uh, well, uh, executing on what you are, holding, what you're folding and what you're doubling down with this completely new environment. >>Well, yeah, and I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine. Who's a senior executive at Genpact. And, um, I, um, used it mostly to talk about AI and AI applications, but I think you could, you could use it much more broadly to talk about your entire sort of portfolio of digital projects. You need to think about, well, um, given some constraints on resources and a difficult economy for a while, which of our projects do we want to keep going on pretty much the way we were and which ones are not that necessary anymore? You see a lot of that in AI, because we had so many pilots, somebody told me, you know, we've got more pilots around here than O'Hare airport and AI. Um, and then, but the ones that involve double down they're even more important to you. They are, you know, a lot of organizations have found this out in the pandemic, on digital projects. It's more and more important for customers to be able to interact with you, um, digitally. And so you certainly wouldn't want to, um, cancel those projects or put them on hold. So you double down on them and get them done faster and better. >>Right, right. Uh, another, another thing that came up in my research that you quoted, um, was, was from Jeff Bezos, talking about the great bulk of what we do is quietly, but meaningfully improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which, which gets way too much buzz, but really applied right. Applied to a specific problem. And that's where you start to see the value. And, you know, the, the BizOps, uh, manifesto is, is, is calling it out in this particular process. But I'd love to get your perspective as you know, you speak generally about this topic all the time, but how people should really be thinking about where are the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, uh, the kind of once in a lifetime decisions, uh, the ones that, um, ag Lafley, the former CEO of Procter and gamble used to call the big swing decisions. You only get a few of those. He said in your tenure as CEO, those are probably not going to be the ones that you're automating in part because, um, you don't have much data about them. You're only making them a few times and in part, because, um, they really require that big picture thinking and the ability to kind of anticipate the future, that the best human decision makers, um, have. Um, but, um, in general, I think where they are, the projects that are working well are, you know, when I call the low hanging fruit ones, the, some people even report to it referred to it as boring AI. >>So, you know, sucking data out of a contract in order to compare it to a bill of lading for what arrived at your supply chain companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but AI, as you suggested is really good at those narrow kinds of tasks. It's not so good at the, at the really big moonshots, like curing cancer or, you know, figuring out well what's the best stock or bond under all circumstances or even autonomous vehicles. Um, we, we made some great progress in that area, but everybody seems to agree that they're not going to be perfect for quite a while. And we really don't want to be driving around on them very much unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic and you know, that sort of thing, right? That's funny you bring up contract management. >>I had a buddy years ago, they had a startup around contract management and was like, and this was way before we had the compute power today and cloud proliferation. I said, you know, how, how can you possibly build software around contract management? It's language, it's legal, ease. It's very specific. And he's like, Jeff, we just need to know where's the contract. And when does it expire? And who's the signatory. And he built a business on those, you know, very simple little facts that weren't being covered because their contracts contractor in people's drawers and files and homes, and Lord only knows. So it's really interesting, as you said, these kind of low hanging fruit opportunities where you can extract a lot of business value without trying to, you know, boil the ocean. >>Yeah. I mean, if you're Amazon, um, uh, Jeff Bezos thinks it's important to have some kind of billion dollar projects. And he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to, um, what AI has been doing for a long time, which is, you know, making smarter decisions based on, based on data. >>Right? So Tom, I want to shift gears one more time before, before we let you go on on kind of a new topic for you, not really new, but you know, not, not a, the vast majority of, of your publications and that's the new way to work, you know, as, as the pandemic hit in mid March, right. And we had this light switch moment, everybody had to work from home and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not going to be going back to work for a while. And so we're going to continue on this for a while. And then even when it's not what it is now, it's not going to be what it was before. So, you know, I wonder, and I know you, you, uh, you teased, you're working on a new book, you know, some of your thoughts on, you know, kind of this new way to work and, and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess. >>Yeah. I missed was an interest of mine. I think, um, back in the nineties, I wrote an article called, um, a coauthored, an article called two cheers for the virtual office. And, you know, it was just starting to emerge. Then some people were very excited about it. Some people were skeptical and, uh, we said two cheers rather than three cheers because clearly there's some shortcomings. And, you know, I keep seeing these pop up. It's great that we can work from our homes. It's great that we can accomplish most of what we need to do with a digital interface, but, um, you know, things like innovation and creativity and certainly, um, uh, a good, um, happy social life kind of requires some face to face contact every now and then. And so I, you know, I think we'll go back to an environment where there is some of that. >>Um, we'll have, um, times when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and to jump on airplanes, to, to, um, give every little, um, uh, sales call or give every little presentation. Uh, we just have to really narrow down what are the circumstances where face to face contact really matters. And when can we get by with, with digital, you know, I think one of the things in my current work I'm finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next, then make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. >>Yeah. I think such, such a huge opportunity as you just said, cause I forget the stats on how often we're interrupted with notifications between email texts, Slack, a sauna, Salesforce, the list goes on and on. So, you know, to put an AI layer between the person and all these systems that are begging for attention, and you've written a book on the attention economy, which is a whole nother topic, we'll say for another day, you know, it really begs, it really begs for some assistance because you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not, it's just not realistic. And you know what? I don't think that's a feature that we're looking for. I agree. Totally. Alright, Tom. Well, thank you so much for your time. Really enjoyed the conversation. I gotta dig into the library. It's very long. So I might start at the attention economy. I haven't read that one in to me. I think that's the fascinating thing in which we're living. So thank you for your time and, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right. Take care. Alright. He's Tom I'm Jeff. You are watching the continuing coverage of the biz ops manifesto and Vale. Thanks for watching the cube. We'll see you next time.

>>From around the globe. It's the cube with digital coverage, a BizOps manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back everybody. Jeff Frick here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto. Unveil. Something has been in the works for a little while. Today's the formal unveiling, and we're excited to have three of the core of founding members of the manifesto authors of the manifesto. If you will, uh, joining us again, we've had them all on individually. Now we're going to have a great power panel first up. We're gab Mitt, Kirsten returning he's the founder and CEO of Tasktop mic. Good to see you again. Where are you dialing in from? >>Great to see you again, Jeff I'm dialing from Vancouver, >>We're Canada, Vancouver, Canada. One of my favorite cities in the whole wide world. Also we've got Tom Davenport come in from across the country. He's a distinguished professor and author from Babson college, Tom. Great to see you. And I think you said you're at a fun, exotic place on the East coast >>Realm of Memphis shoe sits on Cape Cod. >>Great to see you again and also joining surge Lucio. He is the VP and general manager enterprise software division at Broadcom surge. Great to see you again, where are you coming in from? >>Uh, from Boston right next to kickoff. >>Terrific. So welcome back, everybody again. Congratulations on this day. I know it's, it's been a lot of work to get here for this unveil, but let's just jump into it. The biz ops manifesto, what was the initial reason to do this? And how did you decide to do it in a kind of a coalition, a way bringing together a group of people versus just making it an internal company, uh, initiative that, you know, you can do better stuff within your own company, surge, why don't we start with you? >>Yeah, so, so I think we were at a really critical juncture, right? Many, um, large enterprises are basically struggling with their digital transformation. Um, in fact, um, many recognize that, uh, the, the business side, it collaboration has been, uh, one of the major impediments, uh, to drive that kind of transformation. And if we look at the industry today, many people are, whether we're talking about vendors or, um, you know, system integrators, consulting firms are talking about the same kind of concepts, but using very different language. And so we believe that bringing all these different players together, um, as part of the coalition and formalizing, uh, basically the core principles and values in a BizOps manifesto, we can really start to F could have a much bigger movement where we can all talk about kind of the same concepts and we can really start to provide, could have a much better support for large organizations to transform. Uh, so whether it is technology or services or, um, we're training, I think that that's really the value of bringing all of these players together, right. >>And Nick to you, why did you get involved in this, in this effort? >>So Ben close and follow the agile movement since it started two decades ago with that manifesto. >>And I think we got a lot of improvement at the team level, and I think as satisfies noted, uh, we really need to improve at the business level. Every company is trying to become a software innovator, uh, trying to make sure that they can adapt quickly and the changing market economy and what everyone's dealing with in terms of needing to deliver the customer sooner. However, agile practices have really focused on these metrics, these measures and understanding processes that help teams be productive. Those things now need to be elevated to the business as a whole. And that just hasn't happened. Uh, organizations are actually failing because they're measuring activities and how they're becoming more agile, how teams are functioning, not how much quickly they're delivering value to the customer. So we need to now move past that. And that's exactly what the that's manifested provides. Right, >>Right, right. And Tom, to you, you've been covering tech for a very long time. You've been looking at really hard challenges and a lot of work around analytics and data and data evolution. So there's a definitely a data angle here. I wonder if you could kind of share your perspective of what you got excited to, uh, to sign onto this manifesto. >>Sure. Well, I have, you know, for the past 15 or 20 years, I've been focusing on data and analytics and AI, but before that I was a process management guy and a knowledge management guy. And in general, I think, you know, we've just kind of optimized that to narrow a level, whether you're talking about agile or dev ops or ML ops, any of these kinds of ops oriented movements, we're making individual project, um, performance and productivity better, but we're not changing the business, uh, effectively enough. And that's the thing that appealed to me about the biz ops idea that we're finally creating a closer connection between what we do with technology and how it changes the business and provides value to it. >>Great. Uh, surge back to you, right? I mean, people have been talking about digital transformation for a long time and it's been, you know, kind of trucking along and then covert hit and it was instant lights, which everyone's working from home. You've got a lot more reliance on your digital tools, digital communication, uh, both within your customer base and your partner base, but also then your employees when you're, if you could share how that really pushed this all along. Right? Because now suddenly the acceleration of digital transformation is higher. Even more importantly, you got much more critical decisions to make into what you do next. So kind of your portfolio management of projects has been elevated significantly when maybe revenues are down, uh, and you really have to, uh, to prioritize and get it right. >>Yeah. Maybe I'll just start by quoting Satina Nello basically recently said that they're speeding the two years of digital preservation just last two months in any many ways. That's true. Um, but, but yet when we look at large enterprises, they're >>Still struggling with the kind of a changes in culture that they really need to drive to be able to disrupt themselves. And not surprisingly, you know, when we look at certain parts of the industry, you know, we see some things which are very disturbing, right? So about 40% of the personal loans today, or being, uh, origin data it's by fintechs, uh, of a like of Sophie or, uh, or a lending club, right? Not to a traditional brick and mortar for BEC. And so the, well, there is kind of a much more of an appetite and it's a, it's more of a survival type of driver these days. Uh, the reality is that's in order for these large enterprises to truly transform and engage with this digital transformation, they need to start to really align the business. And it, you know, in many ways, uh, make covered that agile really emerged from the core desire to truly improve software predictability between which we've really missed is all that we, we start to aligning the software predictability to business predictability and to be able to have continual sleep continuous improvement and measurement of business outcomes. So by aligning kind of these, uh, kind of inward metrics, that's, it is typically being using to business outcomes. We think we can start to really ELP different stakeholders within the organization to collaborate. So I think there is more than ever. There's an imperative to act now. Um, and, and resolves, I think is kind of the right approach to drive that transformation. Right. >>I want to follow up on the culture comment, uh, with Utah, because you've talked before about kind of process flow and process flow throughout a whore and an organization. And, you know, we talk about people process and tech all the time. And I think the tech is the easy part compared to actually changing the people the way they think. And then the actual processes that they put in place. It's a much more difficult issue than just the tech issue to get this digital transformation in your organization. >>Yeah. You know, I've always found that the soft stuff about, you know, the culture of the behavior, the values is the hard stuff to change and more and more, we, we realized that to be successful with any kind of digital transformation you have to change people's behaviors and attitudes. Um, we haven't made as much progress in that area as we might have. I mean, I've done some surveys suggesting that, um, most organizations still don't have data-driven cultures. And in many cases there is a lower percentage of companies that say they have that then, um, did a few years ago. So we're kind of moving in the wrong direction, which means I think that we have to start explicitly addressing that, um, cultural, behavioral dimension and not just assuming that it will happen if we, if we build a system, >>If we build it, they won't necessarily come. Right. >>Right. So I want to go to, to you Nick cause you know, we're talking about workflows and flow, um, and, and you've written about flow both in terms of, um, you know, moving things along a process and trying to find bottlenecks, identify bottlenecks, which is now even more important again, when these decisions are much more critical. Cause you have a lot less, uh, wiggle room in tough times, but you also talked about flow from the culture side and the people side. So I wonder if you can just share your thoughts on, you know, using flow as a way to think about things, to get the answers better. >>Yeah, absolutely. And I'll refer back to what Tom has said. If you're optimized, you need to optimize your system. You need to optimize how you innovate and how you deliver value to the business and the customer. Now, what we've noticed in the data, since that we've learned from customers, value streams, enterprise organizations, value streams, is that when it's taking six months at the end to deliver that value with the flow is that slow. You've got a bunch of unhappy developers, unhappy customers when you're innovating house. So high performing organizations we can measure at antenna flow time and dates. All of a sudden that feedback loop, the satisfaction, your developers measurably, it goes up. So not only do you have people context, switching glass, you're delivering so much more value to customers at a lower cost because you've optimized for flow rather than optimizing for these, these other approximate tricks that we use, which is how efficient is my adult team. How quickly can we deploy software? Those are important, but they do not provide the value of agility of fast learning of adaptability to the business. And that's exactly what the biz ops manifesto pushes your organization to do. You need to put in place this new operating model that's based on flow on the delivery of business value and on bringing value to market much more quickly than you were before. Right. >>I love that. And I'm gonna back to you Tom, on that to follow up. Cause I think, I don't think people think enough about how they prioritize what they're optimizing for, because you know, if you're optimizing for a versus B, you know, you can have a very different product that, that you kick out. And, you know, my favorite example is with Clayton Christianson and innovator's dilemma talking about the three inch hard drive, if you optimize it for power, you know, is one thing, if you optimize it for vibration is another thing and sure enough, you know, they missed it on the poem because it was the, it was the game console, which, which drove that whole business. So when you're talking to customers and we think we hear it with cloud all the time, people optimizing for a cost efficiency, instead of thinking about it as an innovation tool, how do you help them kind of rethink and really, you know, force them to, to look at the, at the prioritization and make sure they're prioritizing on the right thing is make just that, what are you optimizing for? >>Oh yeah. Um, you have one of the most important aspects of any decision or attempt to resolve a problem in an organization is the framing process. And, um, you know, it's, it's a difficult aspect to have the decision to confirm it correctly in the first place. Um, there, it's not a technology issue. In many cases, it's largely a human issue, but if you frame >>That decision or that problem incorrectly to narrowly say, or you frame it as an either or situation where you could actually have some of both, um, it, it's very difficult for the, um, process to work out correctly. So in many cases, I think we need to think more at the beginning about how we bring this issue or this decision in the best way possible before we charge off and build a system to support it. You know, um, it's worth that extra time to think, think carefully about how the decision has been structured. Right, >>Sir, I want to go back to you and talk about the human factors because as we just discussed, you can put it in great technology, but if the culture doesn't adopt it and people don't feel good about it, you know, it's not going to be successful and that's going to reflect poorly on the technology, even if that had nothing to do with it. And you know, when you look at the, the, the, the core values, uh, of the Bezos manifesto, you know, a big one is trust and collaboration, you know, learn, respond, and pivot. Wonder if you can share your thoughts on, on trying to get that cultural shift, uh, so that you can have success with the people, or excuse me, with the technology in the process and helping customers, you know, take this more trustworthy and kind of proactive, uh, position. >>So I think, I think at the ground level, it truly starts with the realization that we're all different. We come from different backgrounds. Uh, oftentimes we tend to blame the data. It's not uncommon my experiments that we spend the first 30 minutes of any kind of one hour conversation to debate the validity of the data. Um, and so, um, one of the first kind of, uh, probably manifestations that we've had or revelations as we start to engage with our customers is spoke just exposing, uh, high-fidelity data sets to different stakeholders from their different lens. We start to enable these different stakeholders to not debate the data. That's really collaborate to find a solution. So in many ways, when, when, when we think about kind of the types of changes we're trying to, to truly affect around data driven decision making, he told about bringing the data in context and the context that is relevant and understandable for, for different stakeholders, whether we're talking about an operator or develop for a business analyst. >>So that's, that's the first thing. The second layer I think, is really to provide context to what people are doing in their specific silo. And so I think one of the best examples I have is if you start to be able to align business KPI, whether you are counting, you know, sales per hour, or the engagements of your users on your mobile applications, whatever it is, you can start to connect that PKI to business KPI, to the KPIs that developers might be looking at, whether it is all the number of defects or velocity or whatever over your metrics that you're used to, to actually track you start to be able to actually contextualize in what we are, the effecting, basically a metric of that that is really relevant. And then what we see is that this is a much more systematic way to approach the transformation than say, you know, some organizations kind of creating some of these new products or services or initiatives, um, to, to drive engagements, right? >>So if you look at zoom, for instance, zoom giving away a it service to, uh, to education, he's all about, I mean, there's obviously a marketing aspect in there, but it's, it's fundamentally about trying to drive also the engagement of their own teams. And because now they're doing something for good and many organizations are trying to do that, but you only can do this kind of things in the limited way. And so you really want to start to rethink how you connect to, everybody's kind of a business objective fruit data, and now you start to get people to stare at the same data from their own lens and collaborate on all the data. Right, >>Right. That's a good, uh, Tom, I want to go back to you. You've been studying it for a long time, writing lots of books and getting into it. Um, why now, you know, what, why, why now are we finally aligning business objectives with, with it objectives? You know, why didn't this happen before? And, you know, what are the factors that are making now the time for this, this, this move with the, uh, with the biz ops? >>Well, and much of a past, it was sort of a back office related activity. And, you know, it was important for, um, uh, producing your paychecks and, uh, capturing the customer orders, but the business wasn't built around it now, every organization needs to be a software business, a data business, a digital business, the auntie has been raised considerably. And if you aren't making that connection between your business objectives and the technology that supports it, you run a pretty big risk of, you know, going out of business or losing out to competitors. Totally. So, um, and even if you're in, uh, an industry that hasn't historically been terribly, um, technology oriented customer expectations flow from, uh, you know, the digital native, um, companies that they work with to basically every industry. So you're compared against the best in the world. So we don't really have the luxury anymore of screwing up our it projects or building things that don't really work for the business. Um, it's mission critical that we do that well. Um, almost every time, I just want to fall by that, Tom, >>In terms of the, you've talked extensively about kind of these evolutions of data and analytics from artismal stage to the big data stage, the data economy stage, the AI driven stage and what I find diff interesting that all those stages, you always put a start date, you never put an end date. Um, so you know, is the, is the big data I'm just going to use that generically a moment in time finally here where we're, you know, off mahogany row with the data scientists, but actually can start to see the promise of delivering the right insight to the right person at the right time to make that decision. >>Well, I think it is true that in general, these previous stages never seemed to go away. The, um, the artisinal stuff is still being done, but we would like for less and less of it to be artisinal, we can't really afford for everything to be artisinal anymore. It's too labor and, and time consuming to do things that way. So we shift more and more of it to be done through automation and B to be done with a higher level of productivity. And, um, you know, at some point maybe we reached the stage where we don't do anything artisanally anymore. I'm not sure we're there yet, but we are, we are making progress. Right. >>Right. And Mick, back to you in terms of looking at agile, cause you're, you're such a student of agile. When, when you look at the opportunity with biz ops and taking the lessons from agile, you know, what's been the inhibitor to stop this in the past. And what are you so excited about? You know, taking this approach will enable. >>Yeah. I think both search and Tom hit on this is that in agile what's happened is that we've been measuring tiny subsets of the value stream, right? We need to elevate the data's there. Developers are working on these tools that delivering features that the foundations for for great culture are there. I spent two decades as a developer. And when I was really happy is when I was able to deliver value to customers, the quicker I was able to do that the fewer impediments are in my way, that quicker was deployed and running in the cloud, the happier I was, and that's exactly what's happening. If we can just get the right data, uh, elevated to the business, not just to the agile teams, but really this, these values of ours are to make sure that you've got these data driven decisions with meaningful data that's oriented around delivering value to customers. Not only these legacies that Tom touched on, which has cost center metrics. So when, from where for it being a cost center and something that provided email and then back office systems. So we need to rapidly shift to those new, meaningful metrics that are customized business centric and make sure that every development the organization is focused on those as well as the business itself, that we're measuring value. And that will help you that value flow without interruptions. >>I love that mic. Cause if you don't measure it, you can't improve on it and you gotta, but you gotta be measuring the right thing. So gentlemen, uh, thank you again for, for your time. Uh, congratulations on the, uh, on the unveil of the biz ops manifesto and bringing together this coalition, uh, of, of, uh, industry experts to get behind this. And, you know, there's probably never been a more important time than now to make sure that your prioritization is in the right spot and you're not wasting resources where you're not going to get the ROI. So, uh, congratulations again. And thank you for sharing your thoughts with us here on the cube. >>Thank you. >>Alright, so we had surge Tom and Mick I'm. Jeff, you're watching the cube. It's a biz ops manifesto unveil. Thanks for watching. We'll see you next time >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back. Variety. Jeff Frick here with the cube. We're in our Palo Alto studios, and we'd like to welcome you back to our continuing coverage of biz ops manifesto unveil some exciting day to really, uh, kind of bring this out into public. There's been a little bit of conversation, but today's really the official unveiling and we're excited to have our next guest is share a little bit more information on it. He's Patrick tickle. He's a chief product officer for planned view. Patrick. Great to see you. >>Yeah, it's great to be here. Thanks for the invite. So why >>The biz ops manifesto, why the biz ops coalition now when you guys have been at it, it's relatively mature marketplace businesses. Good. What was missing? Why, why this, why this coalition? >>Yeah. So, you know, again, why is, why is biz ops important and why is this something that I'm, you know, I'm so excited about, but I think companies as well, right? Well, no, in some ways or another, this is a topic that I've been talking to the market and our customers about for a long time. And it's, you know, I really applaud this whole movement. Right. And, um, it resonates with me because I think one of the fundamental flaws, frankly, of the way we have talked about technology and business literally for decades, uh, has been this idea of, uh, alignment. Those who know me, I occasionally get off on this little rant about the word alignment, right. But to me, the word alignment is, is actually indicative of the, of the, of the flaw in a lot of our organizations and biz ops is really, I think now trying to catalyze and expose that flaw. >>Right. Because, you know, I always say that, you know, you know, alignment implies silos, right. Instantaneously, as soon as you say there's alignment, there's, there's obviously somebody who's got a direction and other people that have to line up and that kind of siloed, uh, nature of organizations then frankly, the passive nature of it. Right. I think so many technology organizations are like, look, the business has the strategy you guys need to align. Right. And, and, you know, as a product leader, right. That's where I've been my whole career. Right. I can tell you that I never sit around. I almost never use the word alignment. Right. I mean, whether, you know, I never sit down and say, you know, the product management team has to get aligned with dev, right. Or the dev team has to get aligned with the delivery and ops teams. I mean, what I say is, you know, are we on strategy, right? >>Like we've, we have a strategy as a, as a full end to end value stream. Right. And that there's no silos. And I mean, look, every on any given day we got to get better. Right. But the context, the context we operate is not about alignment. Right. It's about being on strategy. And I think I've talked to customers a lot about that, but when I first read the manifesto, I was like, Oh yeah, this is exactly. This is breaking down. Maybe trying to eliminate the word alignment, you know, from a lot of our organizations, because we literally start thinking about one strategy and how we go from strategy to delivery and have it be our strategy, not someone else's that we're all aligning to. And I, and it's a great way to catalyze that conversation that I've, it's been in my mind for years, to be honest. Right. >>So, so much to unpack there. One of the things obviously, uh, stealing a lot from, from dev ops and the dev ops manifesto from 20 years ago. And, and as I look through some of the principles and I looked through some of the values, which are, you know, really nicely laid out here, you know, satisfy customer, do continuous delivery, uh, measure, output against real results. Um, the ones that, that jumps out though is really about, you know, change, change, right? Requirements should change frequently. They do change frequently, but I'm curious to get your take from a, from a software development point, it's easy to kind of understand, right. We're making this widget and our competitors, beta widget plus X, and now we need to change our plans and make sure that the plus X gets added to the plan. Maybe it wasn't in the plan, but you talked a lot about product strategy. So in this kind of continuous delivery world, how does that meld with, I'm actually trying to set a strategy, which implies the direction for a little bit further out on the horizon and to stay on that while at the same time, you're kind of doing this real time continual adjustments because you're not working off a giant PRD or MRD anymore. >>Yeah, yeah, totally. Yeah. You know, one of the terms, you know, that we use internally a lot and even with my customers, our customers is we talk about this idea of rewiring, right. And I think, you know, it's kind of a, now an analogy for transformation. And I think a lot of us have to rewire the way we think about things. Right. And I think at Planview where we have a lot of customers who live in that, you know, who operationalize that traditional PPM world. Right. And are shifting to agile and transforming that rewire is super important. And, and to your point, right, it's, you've just, you've got to embrace this idea of, you know, just iterative getting better every day and iterating, iterating, iterating as opposed to building annual plans or, you know, I get customers occasionally who asked me for two or three year roadmap. >>Right. And I literally looked at them and I go, there's no, there's no scenario where I can build a two or three year roadmap. Right. You, you, you think you want that, but that's not, that's not the way we run. Right. And I will tell you the biggest thing that for us, you know, that I think is matched the planning, uh, you know, patents is a word I like to use a lot. So the thing that we've like, uh, that we've done from a planning perspective, I think is matched impedance to continuous delivery is instituting the whole program, implement, you know, the program, increment planning, capabilities, and methodologies, um, in the scaled agile world. Right. And over the last 18 months to two years, we really have now, you know, instrumented our company across three value streams. You know, we do quarterly PI program increment 10 week planning, you know, and that becomes, that becomes the Terra firma of how we plan. >>Right. And it's, what are we doing for the next 10 weeks? And we iterate within those 10 weeks, but we also know that 10 weeks from now, we're gonna, we're gonna adjust iterate again. Right. And that shifting of that planning model to, you know, to being as cross-functional is that as that big room planning kind of model is, um, and also, uh, you know, on that shorter increment, when you get those two things in place, also the impedance really starts to match up, uh, with continuous delivery and it changes, it changes the way you plan and it changes the way you work. Right? >>Yeah. Their thing. Right. So obviously a lot of these things are kind of process driven, both within the values, as well as the principles, but there's a whole lot, really about culture. And I just want to highlight a couple of the values, right? We already talked about business outcomes, um, trust and collaboration, uh, data driven decisions, and then learn, respond and pivot. Right. A lot of those are cultural as much as they are process. So again, is it the, is it the need to really kind of just put them down on paper and, you know, I can't help, but think of, you know, the hammer and up the, a, the thing in the Lutheran church with it, with their manifesto, is it just good to get it down on paper? Because when you read these things, you're like, well, of course we should trust people. And of course we need an environment of collaboration and of course we want data driven decisions, but as we all know saying it and living, it are two very, very different things. >>Yeah. Good question. I mean, I think there's a lot of ways to bring that to life you're right. And just hanging up, you know, I think we've all been through the hanging up posters around your office, which these days, right. Unless you're going to hang a poster in everybody's home office. Right. You can't even, you can't even fake it that you think that might work. Right. So, um, you know, you really, I think we've attacked that in a variety of ways. Right. And you definitely have to, you know, you've got to make the shift to a team centric culture, right. Empowered teams, you know, that's a big deal. Right. You know, a lot of, a lot of the people that, you know, we lived in a world of quote, unquote work. We lived in a deep resource management world for a long, long time, and right. >>A lot of our customers still do that, but, you know, kind of moving to that team centric world is, uh, is really important and core to the trust. Um, I think training is super important, right. I mean, we've, you know, we've internally, right. We've trained hundreds employees over the last a year and a half on the fundamentals really of safe. Right. Not necessarily, you know, we've had, we've had teams delivering in scrum and the continuous delivery for, you know, for years, but the scaling aspect of it, uh, is where we've done a lot of training investment. Um, and then, you know, I think a leadership has to be bought in. Right. You know? And so when we pie plan, you know, myself and Cameron and the other members of our leadership, you know, we're NPI planning, you know, for, for four days. Right. I mean, it's, it's, you've got to walk the walk, you know, from top to bottom and you've got to train on the context. Right. And then you, and then, and, and then once you get through a few cycles where you've done a pivot, right. Or you brought a new team in, and it just works, it becomes kind of this virtuous circle where he'll go, man, this really works so much better than what we used to do. Right. >>Right. The other really key principle to this whole thing is, is aligning, you know, the business leaders and the business prioritization, um, so that you can get to good outcomes with the development and the delivery. Right. And we know again, and kind of classic dev ops to get the dev and the production people together. So they can, you know, quickly ship code that works. Um, but adding the business person on there really puts, puts a little extra responsibility that they, they understand the value of a particular feature or particular priority. Uh, they, they can make the, the, the trade offs and that they kind of understand the effort involved too. So, you know, bringing them into this continuous again, kind of this continuous development process, um, to make sure that things are better aligned and really better prioritize. Cause ultimately, you know, we don't live in an infinite resources situation and people gotta make trade offs. They gotta make decisions as to what goes and what doesn't go in for everything that goes. Right. I always say you pick one thing. Okay. That's 99 other things that couldn't go. So it's really important to have, you know, this, you said alignment of the business priorities as well as, you know, the execution within, within the development. >>Yeah. I think that, you know, uh, you know, I think it was probably close to two years ago. Forester started talking about the age of the customer, right. That, that was like their big theme at the time. Right. And I think to me what that, the age of the customer actually translates to and Mick, Mick and I are both big fans of this whole idea of the project, the product shift, mixed book, you know, it was a great piece on a, you're talking to Mick, you know, as part of the manifesto is one of the authors as well, but this shift from project to product, right? Like the age of the customer, in my opinion, the, the, the embodiment of that is the shift to a product mentality. Right. And, and the product mentality in my opinion, is what brings the business and technology teams together, right? >>Once you, once you're focused on a customer experience, that's delivered through a product or a service that's when I that's, when I started to go with the alignment problem goes away, right. Because if you look at software companies, right, I mean, we run product management models, you know, with software development teams, customer success teams, right. That, you know, the software component of these products that people are building is obviously becoming bigger and bigger, you know, in an, in many ways, right. More and more organizations are trying to model themselves over as operationally like software companies. Right. Um, they obviously have lots of other components in their business than just software, but I think that whole model of customer experience equaling product, and then the software component of product, the product is the essence of what changes that alignment equation and brings business and teams together because all of a sudden, everyone knows what the customer's experiencing. Right. And, and that, that, that makes a lot of things very clear, very quickly. >>Right. I'm just curious how far along this was as a process before, before covert hit, right. Because serendipitous, whatever. Right. But th the sudden, you know, light switch moment, everybody had to go work from home and in March 15th compared to now, we're in October, and this is going to be going on for a while, and it is a new normal and whatever that whatever's going to look like a year from now, or two years from now is TBD, you know, had you guys already started on this journey cause again, to sit down and actually declare this coalition and declare this manifesto is a lot different than just trying to do better within your own organization. >>Yeah. So we had started, uh, you know, w we definitely had started independently, you know, some, some, you know, I think people in the community know that, uh, we, we came together with a company called lean kit a handful of years ago, and I give John Terry actually one of the founders leaned to immense credit for, you know, kind of spearheading our cultural change and not, and not because of, we were just going to be, you know, bringing agile solutions to our customers, but because, you know, he believed that it was going to be a fundamentally better way for us to work. Right. And we kind of, you know, when we started with John and built, you know, out of concentric circles of momentum and, and we've gotten to the place where now it's just part of who we are, but, but I do think that, you know, COVID has, you know, um, I think pre COVID a lot of companies, you know, would, would adopt, you know, the, you would adopt digital slash agile transformation. >>Um, traditional industries may have done it as a reaction to disruption. Right. You know, and in many cases, the disruption to these traditional industries was, I would say a product oriented company, right. That probably had a larger software component, and that disruption caused a competitive issue or a customer issue that caused companies and tried to respond by transforming. I think COVID, you know, all of a sudden flatten that out, right. We literally all got disrupted. Right. And, and so all of a sudden, every one of us is dealing with some degree of market uncertainty, customer uncertainty, uh, and also know none of us were insulated from the need to be able to pivot faster, deliver incrementally, you know, and operate in a different, completely more agile way, uh, you know, post COVID. Right. Yeah. That's great. >>So again, a very, very, very timely, you know, a little bit of serendipity, a little bit of, of planning. And, you know, as, as with all important things, there's always a little bit of luck and a lot of hard work involved. So a really interesting thank you for, for your leadership, Patrick. And, you know, it really makes a statement. I think when you have a bunch of leaderships across an industry coming together and putting their name on a piece of paper, uh, that's aligned around us some principles and some values, which again, if you read them who wouldn't want to get behind these, but if it takes, you know, something a little bit more formal, uh, to kind of move the ball down the field, and then I totally get it and a really great work. Thanks for, uh, thanks for doing it. >>Oh, absolutely. No. Like I said, the first time I read it, I was like, yeah, like you said, this is all, this all makes complete sense, but just documenting it and saying it and talking about it moves the needle. I'll tell you as a company, you gotta, we're pushing really hard on, uh, you know, on our own internal strategy on diversity inclusion. Right? And, and like, once we wrote the words down about what, you know, what we aspire to be from a diversity and inclusion perspective, it's the same thing. Everybody reads the words and goes, why wouldn't we do this? Right. But until you write it down and kind of have again, a manifesto or a Terrafirma of what you're trying to accomplish, you know, then you can rally behind it. Right. As opposed to it being something that's, everybody's got their own version of the flavor. Right. And I think it's a very analogous, you know, kind of, uh, initiative, right. And, uh, and this happening, both of those things, right. Are happening across the industry these days. Right. >>And measure it too. Right. And measure it, measure, measure, measure, get a baseline. Even if you don't like to measure, even if you don't like what the, even if you can argue against the math, behind the measurement, measure it, and at least you can measure it again and you can, and you've got some type of a comp and that is really the only way to, to move it forward. Well, Patrick really enjoyed the conversation. Thanks for, uh, for taking a few minutes out of your day. >>It's great to be here. It's an awesome movement and we're glad >>That'd be part of it. All right. Thanks. And if you want to check out the biz ops, Manifesta go to biz ops, manifesto.org, read it. You might want to sign it. It's there for you. And thanks for tuning in on this segment will continuing coverage of the biz op manifesto unveil here on the cube. I'm Jeff, thanks for watching >>From around the globe. It's the cube with digital coverage of biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back, everybody Jeffrey here with the cube. We're coming to you from our Palo Alto studios. And welcome back to this event is the biz ops manifesto unveiling. So the biz ops manifesto and the biz ops coalition had been around for a little while, but today's the big day. That's kind of the big public unveiling or excited to have some of the foundational people that, you know, have put their, put their name on the dotted, if you will, to support this initiative and talk about why that initiative is so important. And so the next guest we're excited to have is dr. Mick Kirsten. He is the founder and CEO of Tasktop mic. Great to see you coming in from Vancouver, Canada, I think, right? Yes. Thank you. Absolutely. I hope your air is a little better out there. I know you had some of the worst air of all of us, a couple, a couple of weeks back. So hopefully things are, uh, are getting a little better and we get those fires under control. Yeah. >>Things have cleared up now. So yeah, it's good. It's good to be close to the U S and it's going to have the Arabic cleaner as well. >>Absolutely. So let's, let's jump into it. So you you've been an innovation guy forever starting way back in the day and Xerox park. I was so excited to do an event at Xerox park for the first time last year. I mean, that, that to me represents along with bell labs and, and some other, you know, kind of foundational innovation and technology centers, that's gotta be one of the greatest ones. So I just wonder if you could share some perspective of getting your start there at Xerox park, you know, some of the lessons you learned and what you've been able to kind of carry forward from those days. >>Yeah. I was fortunate to join Xerox park in the computer science lab there at a very early point in my career, and to be working on open source programming languages. So back then in the computer science lab, where some of the inventions around programming around software development teams, such as object oriented programming, and a lot of what we had around really modern programming levels constructs, those were the teams I have the fortune of working with, and really our goal was. And of course there's as, as you know, uh, there's just this DNA of innovation and excitement and innovation in the water. And really it was the model back then was all about changing the way that we work, uh, was looking at for how we could make it 10 times easier to write code. But this is back in 99. And we were looking at new ways of expressing, especially business concerns, especially ways of enabling people who are, who want to innovate for their business to express those concerns in code and make that 10 times easier than what that would take. >>So we create a new open source programming language, and we saw some benefits, but not quite quite what we expected. I then went and actually joined Charles Stephanie, that former to fucking Microsoft who was responsible for, he actually got Microsoft word as a spark and into Microsoft and into the hands of bill Gates on that company. I was behind the whole office suite and his vision. And then when I was trying to execute with, working for him was to make PowerPoint like a programming language, make everything completely visual. And I realized none of this was really working in that there was something else, fundamentally wrong programming languages, or new ways of building software. Like let's try and do with Charles around intentional programming. That was not enough. >>That was not enough. So, you know, the agile movement got started about 20 years ago, and we've seen the rise of dev ops and really this kind of embracing of, of, of sprints and, you know, getting away from MRDs and PRDs and these massive definitions of what we're going to build and long build cycles to this iterative process. And this has been going on for a little while. So what was still wrong? What was still missing? Why the BizOps coalition, why the biz ops manifesto? >>Yeah, so I basically think we nailed some of the things that the program language levels of teams can have effective languages deployed soften to the cloud easily now, right? And at the kind of process and collaboration and planning level agile two decades, decades ago was formed. We were adopting and all the, all the teams I was involved with and it's really become a self problem. So agile tools, agile teams, agile ways of planning, uh, are now very mature. And the whole challenge is when organizations try to scale that. And so what I realized is that the way that agile was scaling across teams and really scaling from the technology part of organization to the business was just completely flawed. The agile teams had one set of doing things, one set of metrics, one set of tools. And the way that the business was working was planning was investing in technology was just completely disconnected and using a whole different set of advisors. >>Interesting. Cause I think it's pretty clear from the software development teams in terms of what they're trying to deliver. Cause they've got a feature set, right. And they've got bugs and it's easy to, it's easy to see what they deliver, but it sounds like what you're really honing in on is this disconnect on the business side, in terms of, you know, is it the right investment? You know, are we getting the right business ROI on this investment? Was that the right feature? Should we be building another feature or should we building a completely different product set? So it sounds like it's really a core piece of this is to get the right measurement tools, the right measurement data sets so that you can make the right decisions in terms of what you're investing, you know, limited resources. You can't, no one has unlimited resources and ultimately have to decide what to do, which means you're also deciding what not to do. And it sounds like that's a really big piece of this, of this whole effort. >>Yeah. Jeff, that's exactly it, which is the way that the agile team measures their own way of working is very different from the way that you measure business outcomes. The business outcomes are in terms of how happy your customers are, but are you innovating fast enough to keep up with the pace of a rapidly changing economy, rapidly changing market. And those are, those are all around the customer. And so what I learned on this long journey of supporting many organizations transformations and having them try to apply those principles of agile and dev ops, that those are not enough, those measures technical practices, those measured sort of technical excellence of bringing code to the market. They don't actually measure business outcomes. And so I realized that it really was much more around having these entwined flow metrics that are customer centric and business centric and market centric where we need it to go. Right. >>So I want to shift gears a little bit and talk about your book because you're also a bestselling author, a project, a product, and, and, and you, you brought up this concept in your book called the flow framework. And it's really interesting to me cause I know, you know, flow on one hand is kind of a workflow and a process flow and, and you know, that's how things get done and, and, and embrace the flow. On the other hand, you know, everyone now in, in a little higher level existential way is trying to get into the flow right into the workflow and, you know, not be interrupted and get into a state where you're kind of at your highest productivity, you know, kind of your highest comfort, which flow are you talking about in your book or is it a little bit about, >>Well, that's a great question. It's not what I get asked very often. Just to me, it's absolutely both. So that the thing that we want to get to, we've learned how to master individual flow. That is this beautiful book by me, how he teaches me how he does a beautiful Ted talk by him as well about how we can take control of our own flow. So my question with the book with project replies, how can we bring that to entire teams and really entire organizations? How can we have everyone contributing to a customer outcome? And this is really what if you go to the biz ops manifesto, it says, I focus on outcomes on using data to drive whether we're delivering those outcomes rather than a focus on proxy metrics, such as, how quickly did we implement this feature? No, it's really how much value did the customer go to the feature and how quickly did you learn and how quickly did you use that data to drive to that next outcome? >>Really that with companies like Netflix and Amazon have mastered, how do we get that to every large organization, every it organization and make everyone be a software innovator. So it's to bring that co that concept of flow to these entwined value streams. And the fascinating thing is we've actually seen the data. We've been able to study a lot of value streams. We see when flow increases, when organizations deliver value to a customer faster, developers actually become more happy. So things like the employee net promoter scores rise, and we've got empirical data for this. So the beautiful thing to me is that we've actually been able to combine these two things and see the results in the data that you increase flow to the customer. Your developers are more happy. >>I love it, right, because we're all more, we're all happier when we're in the flow and we're all more productive when we're in the flow. So I, that is a great melding of, of two concepts, but let's jump into the, into the manifesto itself a little bit. And, you know, I love that, you know, took this approach really of having kind of four key values and then he gets 12 key principles. And I just want to read a couple of these values because when you read them, it sounds pretty brain dead. Right? Of course. Right. Of course you should focus on business outcomes. Of course you should have trust and collaboration. Of course you should have database decision making processes and not just intuition or, you know, whoever's the loudest person in the room, uh, and to learn and respond and pivot. But what's the value of actually just putting them on a piece of paper, because again, this is not this, these are all good, positive things, right? When somebody reads these to you or tells you these are sticks it on the wall, of course. But unfortunately of course isn't always enough. >>No. And I think what's happened is some of these core principles originally from the agile manifesto two decades ago, uh, the whole dev ops movement of the last decade of flow feedback and continue learning has been key. But a lot of organizations, especially the ones that are undergoing digital transformations have actually gone a very different way, right? The way that they measure value in technology and innovation is through costs for many organizations. The way that they actually are looking at that they're moving to cloud is actually as a reduction in cost. Whereas the right way of looking at moving to cloud is how much more quickly can we get to the value to the customer? How quickly can we learn from that? And how quickly can we drive the next business outcome? So really the key thing is, is to move away from those old ways of doing things, a funny projects and cost centers, uh, to actually funding and investing in outcomes and measuring outcomes through these flow metrics, which in the end are your fast feedback and how quickly you're innovating for your customer. >>So these things do seem, you know, very obvious when you look at them. But the key thing is what you need to stop doing to focus on these. You need to actually have accurate realtime data of how much value your phone to the customer every week, every month, every quarter. And if you don't have that, your decisions are not driven on data. If you don't know what your boggling like is, and this is something that in decades of manufacturing, a car manufacturers, other manufacturers, master, they always know where the bottom back in their production processes. You ask a random CIO when a global 500 company where their bottleneck is, and you won't get a clear answer because there's not that level of understanding. So let's, you actually follow these principles. You need to know exactly where you fall. And I guess because that's, what's making your developers miserable and frustrated around having them context, which on thrash. So it, the approach here is important and we have to stop doing these other things, >>Right? There's so much there to unpack. I love it. You know, especially the cloud conversation, because so many people look at it wrong as, as, as a cost saving device, as opposed to an innovation driver and they get stuck, they get stuck in the literal and the, and you know, I think at the same thing, always about Moore's law, right? You know, there's a lot of interesting real tech around Moore's law and the increasing power of microprocessors, but the real power, I think in Moore's laws is the attitudinal change in terms of working in a world where you know that you've got all this power and what you build and design. I think it's funny to your, your comment on the flow and the bottleneck, right? Cause, cause we know manufacturing, as soon as you fix one bottleneck, you move to your next one, right? You always move to your next point of failure. So if you're not fixing those things, you know, you're not, you're not increasing that speed down the line, unless you can identify where that bottleneck is or no matter how many improvements you make to the rest of the process, it's still going to get hung up on that one spot. >>That's exactly it. And you also make it sound so simple, but again, if you don't have the data driven visibility of where that bottom line is, and these bottlenecks are adjusted to say defense just whack them. All right. So we need to understand is the bottleneck because our security reviews are taking too long and stopping us from getting value for the customer. If it's that automate that process. And then you move on to the next bottleneck, which might actually be that deploying yourself into the cloud. It's taking too long. But if you don't take that approach of going flow first, rather than again, that sort of cost reduction. First, you have to think of the approach of customer centricity and you only focused on optimizing costs. Your costs will increase and your flow will slow down. And this is just one of these fascinating things. >>Whereas if you focus on getting closer to the customer and reducing your cycles out on getting value, your flow time from six months to two weeks or two, one week or two event, as we see with the tech giants, you actually can both lower your costs and get much more value for us to get that learning loop going. So I think I've, I've seen all these cloud deployments and one of the things happened that delivered almost no value because there was such big bottlenecks upfront in the process and actually the hosting and the AP testing was not even possible with all of those inefficiencies. So that's why going float us rather than costs when we started our project versus silky. >>I love that. And, and, and, and it, it begs repeating to that right within the subscription economy, you know, you're on the hook to deliver value every single month because they're paying you every single month. So if you're not on top of how you're delivering value, you're going to get sideways because it's not like they pay a big down payment and a small maintenance fee every month. But once you're in a subscription relationship, you know, you have to constantly be delivering value and upgrading that value because you're constantly taking money from the customer. So it's such a different kind of relationship than kind of the classic, you know, big bang with a maintenance agreement on the back end really important. Yeah. >>And I think in terms of industry shifts that that's, it that's, what's catalyzed. This industry shift is in this SAS and subscription economy. If you're not delivering more and more value to your customers, someone else's, and they're winning the business, not you. So, one way we know is to delight our customers with great user experience as well. That really is based on how many features you delivered or how much, how much, how many quality improvements or scalar performance improvements we delivered. So the problem is, and this is what the business manifesto, as well as the flow frame of touch on is if you can't measure how much value you deliver to a customer, what are you measuring? You just backed again, measuring costs, and that's not a measure of value. So we have to shift quickly away from measuring costs to measuring value, to survive. And in the subscription economy, >>We could go for days and days and days. I want to shift gears a little bit into data and, and a data driven decision making a data driven organization cause right day has been talked about for a long time, the huge big data meme with, with Hadoop over, over several years and, and data warehouses and data lakes and data oceans and data swamps. And you can go on and on and on. It's not that easy to do, right? And at the same time, the proliferation of data is growing exponentially. We're just around the corner from, from IOT and five G. So now the accumulation of data at machine scale, again, is this gonna overwhelm? And one of the really interesting principles, uh, that I wanted to call out and get your take right, is today's organizations generate more data than humans can process. So informed decisions must be augmented by machine learning and artificial intelligence. I wonder if you can, again, you've got some great historical perspective, um, reflect on how hard it is to get the right data, to get the data in the right context, and then to deliver it to the decision makers and then trust the decision makers to actually make the data and move that down. You know, it's kind of this democratization process into more and more people and more and more frontline jobs making more and more of these little decisions every day. >>Yeah. I definitely think the front parts of what you said are where the promises of big data have completely fallen on their face into the swamps as, as you mentioned, because if you don't have the data in the right format, you've cannot connect, collected that the right way you want it, that way, the right way you can't use human or machine learning on it effectively. And there've been the number of data where, how has this in a typical enterprise organization and the sheer investment is tremendous, but the amount of intelligence being extracted from those is, is, is a very big problem. So the key thing that I've noticed is that if you can model your value streams, so you actually understand how you're innovating, how you're measuring the delivery of value and how long that takes, what is your time to value through these metrics like full time? >>You can actually use both the intelligence that you've got around the table and push that down as well, as far as getting to the organization, but you can actually start using that those models to understand and find patterns and detect bottlenecks that might be surprising, right? Well, you can detect interesting bottlenecks when you shift to work from home. We detected all sorts of interesting bottlenecks in our own organization that were not intuitive to me that have to do with, you know, more senior people being overloaded and creating bottlenecks where they didn't exist. Whereas we thought we were actually an organization that was very good at working from home because of our open source roots. So the data is highly complex. Software value streams are extremely complicated. And the only way to really get the proper analysts and data is to model it properly and then to leverage these machine learning and AI techniques that we have. But that front part of what you said is where organizations are just extremely immature in what I've seen, where they've got data from all their tools, but not modeled in the right way. Right, right. >>Right. Well, all right. So before I let you go, you know, let's say you get a business leader. He, he buys in, he reads the manifesto, he signs on the dotted line and he says, Mick, how do I get started? I want to be more aligned with the, with the development teams. I know I'm in a very competitive space. We need to be putting out new software features and engage with our customers. I want to be more data-driven how do I get started? Well, you know, what's the biggest inhibitor for most people to get started and get some early wins, which we know is always the key to success in any kind of a new initiative. >>Right? So I think you can reach out to us through the website, uh, for the manifesto. But the key thing is just, it's definitely set up it's to get started and to get the key wins. So take a product value stream. That's mission critical if it'd be on your mobile and web experiences or part of your cloud modernization platform where your analytics pipeline, but take that and actually apply these principles to it and measure the end to end flow of value. Make sure you have a value metric that everyone is on the same page on, but the people on the development teams that people in leadership all the way up to the CEO, and one of the, where I encourage you to start is actually that end to end flow time, right? That is the number one metric. That is how you measure it, whether you're getting the benefit of your cloud modernization, that is the one metric that when the people I respect tremendously put into his cloud for CEOs, the metric, the one, the one way to measure innovation. So basically take these principles, deploy them on one product value stream measure, Antonin flow time, uh, and then you'll actually be well on your path to transforming and to applying the concepts of agile and dev ops all the way to, to the, to the way >>You're offering model. >>Well, Mick really great tips, really fun to catch up. I look forward to a time when we can actually sit across the table and, and get into this. Cause I just, I just love the perspective and, you know, you're very fortunate to have that foundational, that foundational base coming from Xerox park and they get, you know, it's, it's a very magical place with a magical history. So to, to incorporate that into, continue to spread that well, uh, you know, good for you through the book and through your company. So thanks for sharing your insight with us today. >>Thanks so much for having me, Jeff. Absolutely. >>All right. And go to the biz ops manifesto.org, read it, check it out. If you want to sign it, sign it. They'd love to have you do it. Stay with us for continuing coverage of the unveiling of the business manifesto on the cube. I'm Jeff. Rick. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage, a biz ops manifesto unveiled brought to you by biz ops coalition. >>Hey, welcome back. You're ready. Jeff Frick here with the cube for our ongoing coverage of the big unveil. It's the biz ops manifesto manifesto unveil. And we're going to start that again from the top three And a Festo >>Five, four, three, two. >>Hey, welcome back everybody. Jeff Frick here with the cube come to you from our Palo Alto studios today for a big, big reveal. We're excited to be here. It's the biz ops manifesto unveiling a thing's been in the works for a while and we're excited to have our next guest. One of the, really the powers behind this whole effort. And he's joining us from Boston it's surge, Lucio, the vice president, and general manager enterprise software division at Broadcom surge. Great to see you. >>Hi, good to see you, Jeff. Glad to be here. >>Absolutely. So you've been in this business for a very long time. You've seen a lot of changes in technology. What is the biz ops manifesto? What is this coalition all about? Why do we need this today and in 2020? >>Yeah. So, so I've been in this business for close to 25 years, right? So about 20 years ago, the agile manifesto was created. And the goal of the agile manifesto was really to address the uncertainty around software development and the inability to predict the efforts to build software. And, uh, if you, if you roll that kind of 20 years later, and if you look at the current state of the industry of the product, the project management Institute, estimates that we're wasting about a million dollars, every 20 seconds in digital transformation initiatives that do not deliver on business results. In fact, we were recently served a third of the, a, a number of executives in partnership with Harvard >>Business review and 77% of those executives think that one of the key challenges that they have is really the collaboration between business and it, and that that's been kind of a case for, uh, almost 20 years now. Um, so the, the, the key challenge that we're faced with is really that we need a new approach. And many of the players in the industry, including ourselves have been using different terms, right? Some are being, are talking about value stream management. Some are talking about software delivery management. If you look at the site, reliability engineering movement, in many ways, it embodies a lot of these kind of concepts and principles. So we believed that it became really imperative for us to crystallize around, could have one concept. And so in many ways, the, a, the BizOps concept and the BizOps manifesto are bringing together a number of ideas, which has been emerging in the last five years or so, and, and defining the key values and principles to finally help these organizations truly transform and become digital businesses. And so the hope is that by joining our forces and defining public key principles and values, we can help the industry, uh, not just, uh, by, you know, providing them with support, but also tools and consulting that is required for them to truly achieve the kind of transformation that everybody's taking. >>Right. Right. So COVID now we're six months into it, approximately seven months into it. Um, a lot of pain, a lot of bad stuff still happening. We've got a ways to go, but one of the things that on the positive side, right, and you've seen all the memes and social media is, is a driver of digital transformation and a driver of change. Cause we had this light switch moment in the middle of March, and there was no more planning. There was no more conversation. You've suddenly got remote workforces, everybody's working from home and you got to go, right. So the reliance on these tools increases dramatically, but I'm curious, you know, kind of short of, of the beginnings of this effort in short of kind of COVID, which, you know, came along unexpectedly. I mean, what were those inhibitors because we've been making software for a very long time, right? The software development community has, has adopted kind of rapid change and, and iterative, uh, delivery and, and sprints, what was holding back the connection with the business side to make sure that those investments were properly aligned with outcomes. >>Well, so, so you have to understand that it is, is kind of a its own silos. And traditionally it has been treated as a cost center within large organizations and not as a value center. And so as a result, kind of a, the traditional dynamic between it and the business is basically one of a kind of supplier up to kind of a business. Um, and you know, if you go back to, uh, I think you'll unmask a few years ago, um, basically at this concept of the machines to build the machines and you went as far as saying that, uh, the, the machines or the production line is actually the product. So, uh, meaning that the core of the innovation is really about, uh, building, could it be engine to deliver on the value? And so in many ways, you know, we, we have missed on this shift from, um, kind of it becoming this kind of value center within the enterprises and end. >>He talks about culture. Now, culture is a, is a sum total of behaviors. And the reality is that if you look at it, especially in the last decade, uh, we've agile with dev ops with, um, I bring infrastructures, uh, it's, it's way more volatile today than it was 10 years ago. And so the, when you start to look at the velocity of the data, the volume of data, the variety of data to analyze the system, um, it's, it's very challenging for it to actually even understand and optimize its own processes, let alone, um, to actually include business as sort of an integral part of kind of a delivery chain. And so it's both kind of a combination of, of culture, um, which is required, uh, as well as tools, right? To be able to start to bring together all these data together, and then given the volume of variety of philosophy of the data. Uh, we have to apply some core technologies, which have only really, truly emerged in the last five to 10 years around machine learning and analytics. And so it's really kind of a combination of those freaks, which are coming together today, truly out organizations kind of get to the next level. Right, >>Right. So let's talk about the manifesto. Let's talk about, uh, the coalition, uh, the BizOps coalition. I just liked that you put down these really simple, you know, kind of straightforward core values. You guys have four core values that you're highlighting, you know, business outcomes, over individual projects and outputs, trust, and collaboration, oversight, load teams, and organizations, data driven decisions, what you just talked about, uh, you know, over opinions and judgment and learned, respond and pivot. I mean, surgery sounds like pretty basic stuff, right? I mean, aren't, isn't everyone working to these values already. And I think he touched on it on culture, right? Trust and collaboration, data driven decisions. I mean, these are fundamental ways that people must run their business today, or the person that's across the street, that's doing it. It's going to knock them out right off their block. >>Yeah. So that's very true. But, uh, so I'll, I'll mention an hour survey. We did, uh, I think about six months ago and it was in partnership with, uh, with, uh, an industry analyst and we serve at a, again, a number of it executives to understand only we're tracking business outcomes. I'm going to get the software executives, it executives we're tracking business outcomes. And the, there were less than 15% of these executives were actually tracking the outcomes of the software delivery. And you see that every day. Right? So in my own teams, for instance, we've been adopting a lot of these core principles in the last year or so, and we've uncovered that 16% of our resources were basically aligned around initiatives, which are not strategic for us. Um, I take another example, for instance, one of our customers in the, uh, in the airline industry and Harvard, for instance, that a number of, uh, um, that they had software issues that led to people searching for flights and not returning any kind of availability. >>And yet, um, you know, the it teams, whether it's operation software environments were completely oblivious to that because they were completely blindsided to it. And so the connectivity between kind of the inwards metrics that RT is using, whether it's database time, cycle time, or whatever metric we use in it are typically completely divorced from the business metrics. And so at its core, it's really about starting to align the business metrics with the, the, the software delivery chain, right? This, uh, the system, which is really a core differentiator for these organizations. It's about connecting those two things and starting to, um, infuse some of the agile culture and principles. Um, that's emerged from the software side into the business side. Um, of course the lean movement and other movements have started to change some of these dynamics on the business side. And so I think this, this is the moment where we are starting to see kind of the imperative to transform. Now, you know, Covina obviously has been a key driver for that. The, um, the technology is right to start to be able to weave data together and really kind of, uh, also the cultural shifts, uh, Prue agile through dev ops through, uh, the SRE movement, uh frulein um, business transformation, all these things are coming together and that are really creating kind of the conditions for the BizOps manifestor to exist, >>Uh, Clayton Christianson, great, uh, Harvard professor innovator's dilemma might steal my all time. Favorite business books, you know, talks about how difficult it is for incumbents to react to, to disruptive change, right? Because they're always working on incremental change cause that's what their customers are asking for. And there's a good ROI when you talk about, you know, companies not measuring the right thing. I mean, clearly it has some portion of their budget that has to go to keeping the lights on, right. That that's always the case, but hopefully that's an ever decreasing percentage of their total activity. So, you know, what should people be measuring? I mean, what are kind of the new metrics, um, in, in biz ops that drive people to be looking at the right things, measuring the right things and subsequently making the right decisions, investment decisions on whether they should do, you know, move project a along or project B. >>So there, there are only two things, right? So, so I think what you're talking about is portfolio management, investment management, right. And, um, which, which is a key challenge, right? Um, in my own experience, right? Uh, driving strategy or a large scale kind of software organization for years, um, it's very difficult to even get kind of a base data as to who is doing what, uh, um, I mean, some of our largest customers we're engaged with right now are simply trying to get a very simple answer, which is how many people do I have and that specific initiative at any point in time and just tracking that information is extremely difficult. So, and, and again, back to a product project management Institute, um, they're, they've estimated that on average, it organizations have anywhere between 10 to 20% of their resources focused on initiatives, which are not strategically aligned. >>So that's one dimension on portfolio management. I think the key aspect though, that we are really keen on is really around kind of the alignment of a business metrics to the it metrics. Um, so I'll use kind of two simple examples, right? And my background is around quality. And so I've always believed that fitness for purpose is really kind of a key, um, uh, philosophy if you will. And so if you start to think about quality as fitness for purpose, you start to look at it from a customer point of view, right. And fitness for purpose for core banking application or mobile application are different, right? So the definition of a business value that you're trying to achieve is different. Um, and so the, and yet, if you look at our, it, operations are operating, they were using kind of a same type of, uh, kind of inward metrics, uh, like a database of time or a cycle time, or what is my point of velocity, right? >>And, uh, and so the challenge really is this inward facing metrics that it is using, which are divorced from ultimately the outcome. And so, you know, if I'm, if I'm trying to build a poor banking application, my core metric is likely going to be uptime, right? If I'm trying to build a mobile application or maybe your social mobile app, it's probably going to be engagement. And so what you want is for everybody across it, to look at these metric, and what's hard, the metrics within the software delivery chain, which ultimately contribute to that business metric and some cases cycle time may be completely irrelevant, right? Again, my core banking app, maybe I don't care about cycle time. And so it's really about aligning those metrics and be able to start to differentiate, um, the key challenges you mentioned, uh, around the, the, um, uh, around the disruption that we see is, or the investors is the dilemma now is really around the fact that many it organizations are essentially applying the same approaches of, for innovation, right, for basically scrap work, then they would apply to kind of over more traditional projects. And so, you know, there's been a lot of talk about two-speed it, and yes, it exists, but in reality are really organizations, um, truly differentiating, um, all of the operate, their, their projects and products based on the outcomes that they're trying to achieve. And this is really where BizOps is trying to affect. >>I love that, you know, again, it doesn't seem like brain surgery, but focus on the outcomes, right. And it's horses for courses, as you said, this project, you know, what you're measuring and how you define success, isn't necessarily the same as, as on this other project. So let's talk about some of the principles we've talked about the values, but, you know, I think it's interesting that, that, that the BizOps coalition, you know, just basically took the time to write these things down and they don't seem all that, uh, super insightful, but I guess you just gotta get them down and have them on paper and have them in front of your face. But I want to talk about, you know, one of the key ones, which you just talked about, which is changing requirements, right. And working in a dynamic situation, which is really what's driven, you know, this, the software to change in software development, because, you know, if you're in a game app and your competitor comes out with a new blue sword, you've got to come out with a new blue sword. >>So whether you had that on your Kanban wall or not. So it's, it's really this embracing of the speed of change and, and, and, and making that, you know, the rule, not the exception. I think that's a phenomenal one. And the other one you talked about is data, right? And that today's organizations generate more data than humans can process. So informed decisions must be generated by machine learning and AI, and, you know, in the, the big data thing with Hadoop, you know, started years ago, but we are seeing more and more that people are finally figuring it out, that it's not just big data, and it's not even generic machine learning or artificial intelligence, but it's applying those particular data sets and that particular types of algorithms to a specific problem, to your point, to try to actually reach an objective, whether that's, you know, increasing the, your average ticket or, you know, increasing your checkout rate with, with, with shopping carts that don't get left behind and these types of things. So it's a really different way to think about the world in the good old days, probably when you got started, when we had big, giant, you know, MRDs and PRDs and sat down and coded for two years and came out with a product release and hopefully not too many patches subsequently to that. >>It's interesting. Right. Um, again, back to one of these surveys that we did with, uh, with about 600, the ITA executives, and, uh, and, and we, we purposely designed those questions to be pretty open. Um, and, and one of them was really role requirements and, uh, and it was really a wrong kind of what do you, what is the best approach? What is your preferred approach towards requirements? And if I remember correctly over 80% of the it executives set that the best approach they'll prefer to approach is for requirements to be completely defined before software development starts. Let me pause there where 20 years after the agile manifesto, right? And for 80% of these idea executives to basically claim that the best approach is for requirements to be fully baked before salt, before software development starts, basically shows that we still have a very major issue. >>And again, our hypothesis in working with many organizations is that the key challenge is really the boundary between business and it, which is still very much contract based. If you look at the business side, they basically are expecting for it deliver on time on budget, right. But what is the incentive for it to actually delivering all the business outcomes, right? How often is it measured on the business outcomes and not on an SLA or on a budget type criteria. And so that, that's really the fundamental shift that we need to, we really need to drive up as an industry. Um, and you know, we, we talk about kind of this, this imperative for organizations to operate that's one, and back to the innovator's dilemma. The key difference between these larger organization is, is really kind of a, if you look at the amount of capital investment that they can put into pretty much anything, why are they losing compared to, um, you know, startups? What, why is it that, uh, more than 40% of, uh, personal loans today or issued not by your traditional brick and mortar banks, but by, um, startups? Well, the reason, yes, it's the traditional culture of doing incremental changes and not disrupting ourselves, which Christiansen covered at length, but it's also the inability to really fundamentally change kind of a dynamic picture. We can business it and, and, and partner right. To, to deliver on a specific business outcome. Right. >>I love that. That's a great, that's a great summary. And in fact, getting ready for this interview, I saw you mentioning another thing where, you know, the, the problem with the agile development is that you're actually now getting more silos because you have all these autonomous people working, you know, kind of independently. So it's even a harder challenge for, for the business leaders to, to, to, as you said, to know, what's actually going on, but, but certainly I w I want to close, um, and talk about the coalition. Um, so clearly these are all great concepts. These are concepts you want to apply to your business every day. Why the coalition, why, you know, take these concepts out to a broader audience, including your, your competition and, and the broader industry to say, Hey, we, as a group need to put a stamp of approval on these concepts, values, these principles. >>So, first I think we, we want, um, everybody to realize that we are all talking about the same things, the same concepts. I think we were all from our own different vantage point, realizing that, um, things after change, and again, back to, you know, whether it's value stream management or site reliability engineering, or biz ops, we're all kind of using slightly different languages. Um, and so I think one of the important aspects of BizOps is for us, all of us, whether we're talking about, you know, consulting agile transformation experts, uh, whether we're talking about vendors, right, provides kind of tools and technologies, or these large enterprises to transform for all of us to basically have kind of a reference that lets us speak around kind of, um, in a much more consistent way. The second aspect is for, to me is for, um, these concepts to start to be embraced, not just by us or trying, or, you know, vendors, um, system integrators, consulting firms, educators, thought leaders, but also for some of our old customers to start to become evangelists of their own in the industry. >>So we, our, our objective with the coalition needs to be pretty, pretty broad. Um, and our hope is by, by starting to basically educate, um, our, our joint customers or partners, that we can start to really foster these behaviors and start to really change, uh, some of dynamics. So we're very pleased at if you look at, uh, some of the companies which have joined the, the, the, the manifesto. Um, so we have vendors and suggest desktop or advance, or, um, uh, PagerDuty for instance, or even planned view, uh, one of my direct competitors, um, but also thought leaders like Tom Davenport or, uh, or cap Gemini or, um, um, smaller firms like, uh, business agility, institutes, or agility elf. Um, and so our, our goal really is to start to bring together, uh, thought leaders, people who have been LP, larger organizations do digital transformation vendors, were providing the technologies that many of these organizations use to deliver on these digital preservation and for all of us to start to provide the kind of, uh, education support and tools that the industry needs. Yeah, >>That's great surge. And, uh, you know, congratulations to you and the team. I know this has been going on for a while, putting all this together, getting people to sign onto the manifesto, putting the coalition together, and finally today getting to unveil it to the world in a little bit more of a public, uh, opportunity. So again, you know, really good values, really simple principles, something that, that, uh, shouldn't have to be written down, but it's nice cause it is, and now you can print it out and stick it on your wall. So thank you for, uh, for sharing this story. And again, congrats to you and the team. Thank you. Appreciate it. My pleasure. Alrighty, surge. If you want to learn more about the biz ops, Manifesta go to biz ops manifesto.org, read it, and you can sign it and you can stay here for more coverage. I'm the cube of the biz ops manifesto unveiled. Thanks for watching. See you next time >>From around the globe. It's the cube with digital coverage of this ops manifesto unveiled and brought to you by >>This obstacle volition. Hey, welcome back, everybody Jeffrey here with the cube. Welcome back to our ongoing coverage of the biz ops manifesto unveiling. It's been in the works for awhile, but today's the day that it actually kind of come out to the, to the public. And we're excited to have a real industry luminary here to talk about what's going on, why this is important and share his perspective. And we're happy to have from Cape Cod, I believe is Tom Davenport. He's a distinguished author and professor at Babson college. We could go on, he's got a lot of great titles and, and really illuminary in the area of big data and analytics Thomas. Great to see you. >>Thanks Jeff. Happy to be here with you. >>Great. So let's just jump into it, you know, and getting ready for this. I came across your LinkedIn posts. I think you did earlier this summer in June and right off the bat, the first sentence just grabbed my attention. I'm always interested in new attempts to address longterm issues, uh, in how technology works within businesses, biz ops. What did you see in biz ops, uh, that, that kind of addresses one of these really big longterm problems? >>Well, yeah, but the longterm problem is that we've had a poor connection between business people and it people between business objectives and the, it solutions that address them. This has been going on, I think since the beginning of information technology and sadly it hasn't gone away. And so biz ops is a new attempt to deal with that issue with a, you know, a new framework, eventually a broad set of solutions that increase the likelihood that will actually solve a business problem with an it capability. >>Right. You know, it's interesting to compare it with like dev ops, which I think a lot of people are probably familiar with, which was, you know, built around, uh, agile software development and a theory that we want to embrace change that that changes. Okay. And we want to be able to iterate quickly and incorporate that. And that's been happening in the software world for, for 20 plus years. What's taken so long to get that to the business side, because as the pace of change has changed on the software side, you know, that's a strategic issue in terms of execution, the business side that they need now to change priorities. And, you know, there's no PRDs and MRDs and big, giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. It took a long time to get here. >>Yeah, it did. And, you know, there had been previous attempts to make a better connection between business and it, there was the so called strategic alignment framework that a couple of friends of mine from Boston university developed, I think more than 20 years ago, but you know, now we have better technology for creating that linkage. And the, you know, the idea of kind of ops oriented frameworks is pretty pervasive now. So I think it's time for another serious attempt at it. >>And do you think doing it this way, right. With the, with the BizOps coalition, you know, getting a collection of, of, of kind of likeminded individuals and companies together, and actually even having a manifesto, which we're making this declarative statement of, of principles and values, you think that's what it takes to kind of drive this kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in, uh, in production in the field. >>I think certainly no one vendor organization can pull this off single handedly. It does require a number of organizations collaborating and working together. So I think our coalition is a good idea and a manifesto is just a good way to kind of lay out what you see as the key principles of the idea. And that makes it much easier for everybody to understand and act on. >>I, I think it's just, it's really interesting having, you know, having them written down on paper and having it just be so clearly articulated both in terms of the, of the values as well as, as the, uh, the principles and the values, you know, business outcomes matter trust and collaboration, data-driven decisions, which is the number three of four, and then learn, respond and pivot. It doesn't seem like those should have to be spelled out so clearly, but, but obviously it helps to have them there. You can stick them on the wall and kind of remember what your priorities are, but you're the data guy. You're the analytics guy, uh, and a big piece of this is data and analytics and moving to data driven decisions. And principle number seven says, you know, today's organizations generate more data than humans can process and informed decisions can be augmented by machine learning and artificial intelligence right up your alley. You know, you've talked a number of times on kind of the mini stages of analytics. Um, and how has that evolved over over time, you know, as you think of analytics and machine learning, driving decisions beyond supporting decisions, but actually starting to make decisions in machine time. What's that, what's that thing for you? What does that make you, you know, start to think, wow, this is this going to be pretty significant. >>Yeah. Well, you know, this has been a longterm interest of mine. Um, the last generation of AI, I was very interested in expert systems. And then, um, I think, uh, more than 10 years ago, I wrote an article about automated decision-making using what was available then, which was rule-based approaches. Um, but you know, this addresses an issue that we've always had with analytics and AI. Um, you know, we, we tended to refer to those things as providing decision support, but the problem is that if the decision maker didn't want their support, didn't want to use them in order to make a decision, they didn't provide any value. And so the nice thing about automating decisions, um, with now contemporary AI tools is that we can ensure that data and analytics get brought into the decision without any possible disconnection. Now, I think humans still have something to add here, and we often will need to examine how that decision is being made and maybe even have the ability to override it. But in general, I think at least for, you know, repetitive tactical decisions, um, involving a lot of data, we want most of those, I think to be at least, um, recommended if not totally made by an algorithm or an AI based system. And that I believe would add to, um, the quality and the precision and the accuracy of decisions and in most organizations, >>No, I think, I think you just answered my next question before I, before I asked it, you know, we had dr. Robert Gates on the former secretary of defense on a few years back, and we were talking about machines and machines making decisions. And he said at that time, you know, the only weapon systems, uh, that actually had an automated trigger on it were on the North Korea and South Korea border. Um, everything else, as you said, had to go through a sub person before the final decision was made. And my question is, you know, what are kind of the attributes of the decision that enable us to more easily automated? And then how do you see that kind of morphing over time, both as the data to support that as well as our comfort level, um, enables us to turn more and more actual decisions over to the machine? >>Well, yeah, as I suggested we need, um, data and the data that we have to kind of train our models has to be high quality and current, and we need to know the outcomes of that data. You know, um, most machine learning models, at least in business are supervised. And that means we need to have labeled outcomes in the, in the training data. But I, you know, um, the pandemic that we're living through is a good illustration of the fact that, that the data also have to be reflective of current reality. And, you know, one of the things that we're finding out quite frequently these days is that, um, the data that we have do not reflect, you know, what it's like to do business in a pandemic. Um, I wrote a little piece about this recently with Jeff cam at wake forest university, we call it data science quarantined, and we interviewed with somebody who said, you know, it's amazing what eight weeks of zeros will do to your demand forecast. We just don't really know what happens in a pandemic. Um, our models maybe have to be put on the shelf for a little while and until we can develop some new ones or we can get some other guidelines into making decisions. So I think that's one of the key things with automated decision making. We have to make sure that the data from the past and that's all we have of course, is a good guide to, you know, what's happening in the present and the future as far as we understand it. >>Yeah. I used to joke when we started this calendar year 2020, it was finally the year that we know everything with the benefit of hindsight, but I turned down 20, 20 a year. We found out we actually know nothing and everything and thought we knew, but I want to, I want to follow up on that because you know, it did suddenly change everything, right? We've got this light switch moment. Everybody's working from home now we're many, many months into it, and it's going to continue for a while. I saw your interview with Bernard Marr and you had a really interesting comment that now we have to deal with this change. We don't have a lot of data and you talked about hold fold or double down. And, and I can't think of a more, you know, kind of appropriate metaphor for driving the value of the biz ops when now your whole portfolio strategy, um, these to really be questioned and, and, you know, you have to be really, uh, well, uh, executing on what you are, holding, what you're folding and what you're doubling down with this completely new environment. >>Well, yeah, and I hope I did this in the interview. I would like to say that I came up with that term, but it actually came from a friend of mine. Who's a senior executive at Genpact. And, um, I, um, used it mostly to talk about AI and AI applications, but I think you could, you could use it much more broadly to talk about your entire sort of portfolio of digital projects. You need to think about, well, um, given some constraints on resources and a difficult economy for a while, which of our projects do we want to keep going on pretty much the way we were and which ones are not that necessary anymore? You see a lot of that in AI, because we had so many pilots, somebody told me, you know, we've got more pilots around here than O'Hare airport and, and AI. Um, and then, but the ones that involve doubled down, they're even more important to you. They are, you know, a lot of organizations have found this out, um, in the pandemic on digital projects, it's more and more important for customers to be able to interact with you, um, digitally. And so you certainly wouldn't want to cancel those projects or put them on hold. So you double down on them and get them done faster and better. Right, >>Right. Uh, another, another thing that came up in my research that, that you quoted, um, was, was from Jeff Bezos, talking about the great bulk of what we do is quietly, but meaningfully improving core operations. You know, I think that is so core to this concept of not AI and machine learning and kind of the general sense, which, which gets way too much buzz, but really applied right. Applied to a specific problem. And that's where you start to see the value. And, you know, the, the BizOps, uh, manifesto is, is, is calling it out in this particular process. But I'd love to get your perspective as you know, you speak generally about this topic all the time, but how people should really be thinking about where are the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, uh, the kind of once in a lifetime decisions, uh, the ones that, um, ag Lafley, the former CEO of Procter and gamble used to call the big swing decisions. You only get a few of those. He said in your tenure as CEO, those are probably not going to be the ones that you're automating in part because, um, you don't have much data about them. You're only making them a few times and in part, because, um, they really require that big picture thinking and the ability to kind of anticipate the future, that the best human decision makers, um, have. Um, but, um, in general, I think where they, I, the projects that are working well are, you know, what I call the low hanging fruit ones, the, some people even report to it referred to it as boring AI. >>So, you know, sucking data out of a contract in order to compare it to a bill of lading for what arrived at your supply chain companies can save or make a lot of money with that kind of comparison. It's not the most exciting thing, but AI, as you suggested is really good at those narrow kinds of tasks. It's not so good at the, at the really big moonshots, like curing cancer or, you know, figuring out well what's the best stock or bond under all or even autonomous vehicles. Um, we, we made some great progress in that area, but everybody seems to agree that they're not going to be perfect for quite a while, and we really don't want to be driving around on, um, and then very much unless they're, you know, good and all kinds of weather and with all kinds of pedestrian traffic and you know, that sort of thing, right? >>That's funny you bring up contract management. I had a buddy years ago, they had a startup around contract management and I've like, and this was way before we had the compute power today and cloud proliferation. I said, you know, how can you possibly build software around contract management? It's language, it's legal, ease. It's very specific. And he's like, Jeff, we just need to know where's the contract. And when does it expire? And who's the signatory. And he built a business on those, you know, very simple little facts that weren't being covered because their contracts are in people's drawers and files and homes. And Lord only knows. So it's really interesting, as you said, these kind of low hanging fruit opportunities where you can extract a lot of business value without trying to, you know, boil the ocean. >>Yeah. I mean, if you're Amazon, um, uh, Jeff Bezos thinks it's important to have some kind of billion dollar project. And he even says it's important to have a billion dollar failure or two every year. But I think most organizations probably are better off being a little less aggressive and, you know, sticking to, um, what AI has been doing for a long time, which is, you know, making smarter decisions based on, based on data. >>Right? So Tom, I want to shift gears one more time before, before we let you go on, on kind of a new topic for you, not really new, but you know, not, not a, the vast majority of, of your publications and that's the new way to work, you know, as, as the pandemic hit in mid March, right. And we had this light switch moment, everybody had to work from home and it was, you know, kind of crisis and get everybody set up. Well, you know, now we're five months, six months, seven months. A number of companies have said that people are not going to be going back to work for a while. And so we're going to continue on this for a while. And then even when it's not what it is now, it's not going to be what it was before. So, you know, I wonder, and I know you, you, uh, you teased, you're working on a new book, you know, some of your thoughts on, you know, kind of this new way to work and, and, and the human factors in this new, this new kind of reality that we're kind of evolving into, I guess. >>Yeah. I missed was an interest of mine. I think, um, back in the nineties, I wrote an article called, um, a coauthored, an article called two cheers for the virtual office. And, you know, it was just starting to emerge. Then some people were very excited about it. Some people were skeptical and, uh, we said two cheers rather than three cheers because clearly there's some shortcomings. And, you know, I keep seeing these pop up. It's great that we can work from our homes. It's great that we can, most of what we need to do with a digital interface, but, um, you know, things like innovation and creativity, and certainly, um, uh, a good, um, happy social life kind of requires some face to face contact every now and then. And so I, you know, I think we'll go back to an environment where there is some of that. >>Um, we'll have, um, times when people convene in one place so they can get to know each other face to face and learn from each other that way. And most of the time, I think it's a huge waste of people's time to commute into the office every day and to jump on airplanes, to, to, um, give every little, um, uh, sales call or give every little presentation. Uh, we just have to really narrow down what are the circumstances where face to face contact really matters. And when can we get by with digital? You know, I think one of the things in my current work I'm finding is that even when you have AI based decision making, you really need a good platform in which that all takes place. So in addition to these virtual platforms, we need to develop platforms that kind of structure the workflow for us and tell us what we should be doing next, then make automated decisions when necessary. And I think that ultimately is a big part of biz ops as well. It's not just the intelligence of an AI system, but it's the flow of work that kind of keeps things moving smoothly throughout your organization. >>I think such, such a huge opportunity as you just said, cause I forget the stats on how often we're interrupted with notifications between email texts, Slack, a sauna, Salesforce, the list goes on and on. So, you know, to put an AI layer between the person and all these systems that are begging for attention, you've written a book on the attention economy, which is a whole nother topic, we'll say for another day, you know, it, it really begs, it really begs for some assistance because you know, you just can't get him picked, you know, every two minutes and really get quality work done. It's just not, it's just not realistic. And you know what? I don't think that's a feature that we're looking for. >>I agree. Totally >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I got to dig into the library. It's very long. So I might start at the attention economy. I haven't read that one. And to me, I think that's the fascinating thing in which we're living. So thank you for your time and, uh, great to see you. >>My pleasure, Jeff. Great to be here. >>All right. He's Tom I'm Jeff. You are watching the continuing coverage of the biz ops manifesto and Vail. Thanks for watching the cube. We'll see you next time.

>> Announcer: From London, England, it's theCUBE, covering Coupa Inspire '19 EMEA, brought to you by Coupa. >> Hey, welcome to theCUBE! Lisa Martin on the ground in London at Coupa Inspire. Because I'm in the UK, I have to say, you know of Sting, right? Well, guess who's here? Somebody cool enough to go by one name, it's Chandar, the CMO at Coupa. Welcome back! >> Great, Lisa, it's great to be here. >> So, this morning kicked off with Rob's talk all about community. One of the interesting things about Coupa is this community that you guys have built. Talk to me about, I know $1.3 trillion of spend is going through the Coupa platform, the community. Talk to me about how you've cultivated this community at Coupa. >> Yeah, it's a great question. Now, if you take a step back, you know, people don't buy features, people buy tribal feelings. And if you think it, if you look at, like, you know, if you look at a product like Harley-Davidson. Anybody can go buy any bike, but people are not buying the features, they're buying the tribal feeling of being part of that community. If you look at a product like Peloton, you know, people can go buy, have any stationary bike or any workout bike today. But they want to be part of that community. And as my wife tells me, Sephora, right? I don't have a lot of experience with that-- >> She's right. >> She is right, great, (Lisa laughs) thanks for the endorsement there. But again, it is about being part of the community and people like that and stuff, and that's what we're doing is, it's the features or the capability, it's the community the tribal feeling, and that's what Rob was talking about, the inspirational attributes of these different people that are part of this community, and how we're trying to, how we are building this community by showcasing the great leaders and their attributes and how they're transforming change in their organizations, and that's what we're creating in this conference, the feeling, the #emotion, of I want to be part of this cool club, and that's what we're doing. >> You know, a lot of companies talk about customer first, customer centricity. The community here is really helping Coupa innovate on its own technology. Talk to me about some of the things that, you know, since we last spoke, a few months ago, that have been inspired by the voice of the community. >> Yeah, so, you know, there is this concept of co-creation that Rob talked about today with our community. And a lot of the community is inspired by the community and it's for the community. And we have a number of innovations, 80 plus innovations that have been inspired in the last one year by the community. And even a concept like Source Together that Rob talked about, and the idea of Source Together is how can we come together as one community and drive the best negotiated savings together with a supplier, this is an idea that's been co-created with the community. So there's a number of different things. You look at community intelligence, Rob talked about commodity insights, as well as a number of other capabilities that we are showcasing today, has been driven, co-created, inspired by the community. And that's what's great. You want to set the innovation agenda for the industry by having this community inspire us. In fact we had our customer advisory board at every conference that is happening for us, and that's what drives to a lot of the innovation that we do today. >> Speaking of customers, Rob shared a lot of examples during his keynote this morning. I lost count of how many of your Coupa Spendsetters were mentioned, other customers, all with very strong business, measurable business outcomes. I know tomorrow in your keynote, you're going to be talking with a number of customers. But some of the things that are interesting about what Rob shared is these are examples that aren't just about refining procurement and reducing spend and, it's much more transformative. Give me some of your favorite examples of where this is beyond improving procurement. >> Yeah, it's a great question. It's a great question. And we have a number of stories, for example, tomorrow in my keynote, I'm going to be talking about storytelling, right. I'm going to be talking about how we can inspire the community through storytelling, and great storytelling starts with great storytellers. And these Spendsetters, and we can see them in the hallways here, we have found about 15 of them, and they're all great storytellers for one reason. They have great transformative stories in business spend management, but what makes them a great storyteller is that they're telling a story beyond the boundaries of the business spend management. Let me give a couple of examples, right. So one story that I'll highlight tomorrow is about Jarkko, the CPO of Telia. Now, I don't know if we know Telia, but 60% of the word's internet traffic goes through Telia. >> 60%? >> 60%. So everyday morning, checking out coupa.com that we all do. >> Every day. >> Or I'm looking at some less popular sites like Facebook or LinkedIn or anything else, you're probably on the Telia network, especially in this part of the world. And their challenge, their business spend management challenge is, they're pretty fragmented across the Nordics and the Baltics and other regions, and now with Jarkko, he's a strategic crusader, not a hired gun, but more of a driven crusader who's come in, transformed the sourcing function, made it more strategic, consolidated seven systems into one system with Coupa, and had 20,000 employees using that as well as all the different people for sourcing, so that they get the global benefits of scale across the regions. Now that's a great business spend management story, but what makes him a great storyteller, he's telling a story beyond the boundaries of business spend management, because he's not talking about savings attainability, he's talking about environmental sustainability, and the story he talks about is what their initiative at a board level is, you know, zero emission and zero waste by 2030, and how the work that his team is doing is directly impacting that board level initiative on how are they driving a communication strategy across the supplier base to get their environmental plans into the Telia's operations, and how me measures plans and progress of every supplier in their CO2 emission, and how that's going to be an explicit part of how they work with their suppliers, and how he is the trusted advisor that he is actually challenging everybody to rethink this whole idea of source to pay. That is telling a boundary beyond the boundaries of business spend management, it's telling a story. So that's one example, right. >> Is that a gentleman who's in procurement in finance within an organization? >> He is the CPO, the procurement-- >> That is having an impact on the sustainability footprint of the company. >> That's right, so directly associating with the initiative at a board level, right. So he's shifted it, by shifting the storytelling from talking about savings attainability to environmental sustainability, he shifted the perception of the organization from something that's operational to something that's very strategic in the organization. So that's one good storytelling. The other one I'll highlight, an example, is Matthieu at Global Fund. Now the Global Fund is the world's largest financier of fighting malaria, AIDS, HIV in 100-plus countries. They disperse $4 billion every year for that. And they have this partner called OneWorld.org, it's powered by Coupa, that Matthieu and his team are doing. So he could get a great business spend management story. He can say, you know, I've driven digital transformation, I've done 99.9% of my POs are electronic, and I've come to this new age of where, you know, on contract spend is being done, et cetera. Now what makes him a great storyteller, he's telling the story beyond the boundaries of BSM again. He's talking about a story of how this, the work that his team is doing, is directly impacting saving 32 million lives. How they are treating millions of people, get the right treatment for HIV, help pregnant mothers or on HIV, they get the right treatment on time, so that the babies don't get infected with HIV, and how they're distributing hundreds of millions of mosquito nets throughout the world for preventing malaria, through this OneWorld tool that's powered by Coupa to get the right medication on time. So that's millions and millions of lives, but the speed and ease of every single medication to get there, has an impact on the life of that person, and that's the story he's telling. >> This is so interesting, because it's so common for businesses to tell the common success story, and a lot of what Coupa shares of customers holding those big white cards with big numbers of what they're saving are very impactful. What was the idea behind the Spendsetters program, 'cause when I was reading a few of them in preparation to come here, it seems like it was a little bit more about the person and how that individual has facilitated transformation. Tell me about the concept-- >> It's a great point. There's two components to it, right. One is empirical, two is emotive. And if you look at both concepts, one of them is the empirical value that, yes, ultimately Coupa is about driving value, and that has to be as a company, has a capability of driving value to our customers. And that's the empirical value of you have driven so much saving, so much percentage of spend, and you know, millions of dollars, billions of dollars savings et cetera. Procter & Gamble, for example, $2.5 billion in savings. That's the empirical value. It's very clear, that's the value. But behind that is a person, and that is the emotive story of what is that person, what is the personal story, what have they gone through in their life, what's their, you know, nurture and nature, and how that's influenced them that's becoming, that made them into the great leader today, and that's the emotive stories we're trying to also tell on the Spendsetters site. So there's the value side of the story, and then there is the emotive side of the story, and the spendsetters.com is purely on telling the human stories, because behind every purchase order is a person, and we're telling the story of that person. >> So as we look at the changing role of the Chief Procurement Officer, the changing role of finance decision makers, not just here in the UK, and I know Coupa recently did a study that showed that 96% of UK financial decision makers said, "Hey, I don't have complete visibility over all my spend", so big opportunity there, but even from a transformation perspective, the Spendsetters examples, how is that showing that Coupa can fundamentally help a business not just change procurement, but have such wide lasting impacts? >> Yeah, I think ultimately, if you look at procurement, you know, for it to go as going from operation to strategic, you're just getting that seat at the table. And getting that seat at the table in any executive discussion is about first aligning to some strategic initiative that is important at that executive table. So more as we align these value stories and the value that procurement is driving, through these strategic initiatives that are important at the board level, at the executive level, the more the profile and the more the R-E-S-P-E-C-T, as we like to say, and get that seat at the table, and that's what this whole Spendsetters program is aiming to do is A, showcase the personal heroes, and B, showcase how they're telling stories that align to bigger level initiatives, that's getting them get that elevate their position and get that seat at the table. And that's what the plan is there. >> So, lots of growth. Second quarter results, I was taking a look at those, revenues up, billings are up, very high renewal rates. So from a customer satisfaction perspective, the data is there to show that Coupa is going in the right direction. From your perspective, how influential are your existing, your incumbent customers in helping prospective customers evaluate Coupa and go, this is the right decision for us. >> It's a great question. You know, I say we live in a peer-bound world, right, where it's really, we more and more, first of all, 80 to 90% of buyers' journeys are self directed, because buyers have more power than ever before, and second of all, anything we do within our personal lives as well as in business decisions, we rely more on peers and people we trust to help us make those decisions, right? From that perspective, our best sellers, the best sellers we have in this conference, are our customers. I just came from an executive luncheon, where we had 50% of the room was customers and 50% of the room was prospects, and we had our best sellers, not our salespeople, our customers talking to the prospects, in real, authentic conversations of what's value, what's their journey, what did they struggle with, and what are the lessons learned, and how did they get there. And those are really meaningful interactions that ultimately is going to make a prospect, influence a prospect on what decision they have to make. >> Absolutely. >> So that's very, very important from us, and then providing a platform for this authentic dialog and these authentic interactions. That's important for us. And also, I think, you know, ultimately in a SaaS business, the true measurement of success, I say is two things, right. One is what I call lifetime value, and two is the number of brand advocates. So the idea there if someone is staying with you longer and giving you lifetime value, and is shouting from the rooftop that I really love my interaction with this brand, then invariably you're driving value to them in a long term way. And that's really the true measure of success, and that's what excites us from our perspective. >> And is the foundation of that trust? >> The foundation of that is two things. It's trust based on value, right, and you've got to deliver value, and Rob has a great line where he talks about, it is not about customer satisfaction, it's about customer success. 'Cause many times a customer may be satisfied, may not really know what their success metrics really mean, but it's not about sometimes a customer may not be satisfied, but really be successful because you're driving the true metrics what is important to the customer. So once you get the value delivered, and do it in an open, authentic way, then, in that case, there's trust that build, and based on that trust, you earned that trust, and that becomes the foundation of the lifetime value. >> We were talking about, well, we, Rachel Botsman was talking about the importance of a brand, any brand, earning trust. A lot of times she gave that example in her keynote where she showed three brand logos, Uber, Facebook, and Amazon, and said, trust is so contextual and so subjective, but clap for which brand you trust the most. And it's so interesting when she started talking about, Facebook got the least, in fact Facebook got no applause at all, I was expecting a few folks (Chandar laughs) to maybe do some clapping, but Amazon being the clear winner, and I thought, yeah, I trust Amazon to deliver whatever it is that I buy when they say they're going to deliver it, and she said she trusts them to do the same, but, would you trust them to pay their taxes on time-- >> Chandar: Sure. >> So when she started talking about trust being subjective and contextual, it really kind of changes the whole dynamic. >> Chandar: It does. >> So that earned trust, but also the ability to reduce the risk that your customers are facing, whether it's overpaying suppliers or paying duplicate invoices, that trust risk balance seems pretty critical as well. >> Ti does, it does. It's an interesting perspective. I think because, in that case of Amazon, I think there's operational trust, that they're going to get the job done and deliver the whatever you ordered in one day with frame or two days with frames, this is operational trust. But is there a trust in the sense of purpose is where she was going with, right. And today for organizations, especially with the millennial crowd, as being customers as well as employees, the question is, you can get operational trust, but you also have a sense of purpose that they trust in, and have that be, and be authentic as an organization. And that's why is say it is not being, you talk about AI, as artificial intelligence, the real AI is authentic interactions. >> Lisa: Authentic interactions. >> And that's really the authenticity as a brand, being open, and acknowledge your failures but strive for excellence for success, and have this open platform with your customers, and always look towards adding value. I think that invariably, over time, creates this trust feeling that ultimately drives long term lifetime value for us. So that I think is the most important thing. >> Absolutely. So tell me again, which three customers are going to be on stage with you tomorrow sharing their stories? >> It's great, I have three. One, Procter & Gamble, a company that my mom knows about, my 86-year-old mom. So one of the greatest brands, so that's a great story about, again, they have a great business spend management story, but they're telling a story beyond the boundaries of business spend management and it's a fun story. And then we're going to have the Global Fund. Again, I told you, one of the world's largest financier of fighting HIV, malaria and AIDS. And we're going to have Telia, one of the largest telecommunications providers. >> Excellent. So really kind of showing the breadth of the technologies and the industries that Coupa helps to transform. >> And the breadth of the personalities, and the people behind that are driving all this change. >> Excellent, well Chandar, thank you for joining me on theCUBE. I wish we were going to be here tomorrow to see your keynote, but it sounds exciting and the Spendsetter program is certainly one that I think is quite differentiated in terms of telling those transformative stories that you said are both empirical and emotional. >> Yes, thank you Lisa, it's great to be here. >> Likewise. >> Great. >> For Chandar, I am Lisa Martin. You're watching theCUBE from Coupa Inspire London. Thanks for watching.

(upbeat tech music) >> Announcer: From London, England it's theCUBE, covering Coupa Insp!re 19 Emea. Brought to you by Coupa. >> Hey, welcome to theCUBE, Lisa Martin on the ground in London at Coupa Insp!re 19. Very pleased to welcome back to theCUBE the CEO and Chairman of Coupa, Rob Bernshteyn. Rob, welcome back. >> Thank you so much, thank you for being with me. >> It's great to be here, so we are in with all of these customers and partners, this has been busy all day. You started things off today with a great keynote. I was telling you before we went live, I lost count of how many big customer examples were sprinkled, and I think infused throughout your keynote. I was looking at some numbers, Coupa just keeps doing this. 5x increase in spend under management since 2016, that's only three years. You guys have thousands of customers, five million suppliers on the platform, lot of growth. What are some of the key drivers to this great growth that you're seeing? Well a couple of things, I mean first of all, this is a huge total addressable market. Every company in the world could do a better job of the way they manage their business spending, and they could use information technology, hopefully from Coupa to help make that happen, and we are so proud to cultivate this community of like minded, thoughtful professionals that want to apply best practices, best in-class modern technology solutions like the ones we offer obviously, to drive quantifiable, measurable, outcomes for the companies that they work for. So in many ways, this is a celebration of our customer community and it's a wonderful opportunity to be with our customers here like this every year in Europe and every year in the United States, and now frankly in lots of other places around the world. >> So one of the themes that was also expressed during the keynote was Rachel Botsman's theme of trust and I think about the open community, the open platform and the community that Coupa is building, there's a lot of earned trust there that Coupa has earned from this growing community. Talk to me about what that means to you and the whole team and how it's influencing the direction that Coupa is going in. >> It means a lot to me personally frankly. The O in Coupa stands for Open, and that means not only technically open in terms of APIs and integrations, but it means open in spirit, open in dialogue, honest, transparent communications. I feel that our industry in enterprise software has a legacy or a history of a lot of PowerPoints, and a lot of demos, but frankly, quite a few failures of large scale deployments and a whole host of sectors. And we want to be part of the solution, we want to have an open, authentic, honest communication with our customers, with our prospective customers in the sales process, with our partners, with all of my Coupa colleagues, so we can avoid the friction and nonsense of politics that often gets in the way of driving measurable, meaningful value for every constituent. It's a very, very important thing to me, it's important to my team, and that's something we're doing our very best to cultivate in this Coupa community that we're creating. >> Speaking of cultivation, Coupa is cultivating this category of Business Spend Management. Tell us a little bit more about that and where you are with that. >> Sure, Business Spend Management is a pretty straightforward three words to describe the fact that our buyers and our customers are responsible for literally trillions of dollars and pounds and dollars and euros of spend all over the world. And as information becomes more and more transparent, the buyer, the one who's repsonsible for that spend becomes more and more powerful. So we sit on the side of that buyer, we give them information technology solutions from sourcing, to inventory management, to spend analytics, to procurement, to expensing, to invoicing, to payments, to supplier performance. All the capabilities needed to help them make the best purchasing decisions for their organizations, and help their companies become more profitable so that every one of these Coupa community customers we have here could get more bang for their buck and be that much more operationally efficient frankly in driving their own company's visions and missions and whatever it is that they bring to the world. And that's very aspirational for us and we're excited that so many have come on board with this establishment of the Business Spend Management category with us. >> So if we look at the PIPE, as you were calling it this morning, P-I-P-E, procure, invoice, pay, expense, I memorized that, you've got this one platform that can deliver all of that to this growing community of users who have the ability to get that visibility. That is one of the biggest challenges, I was reading some stats recently about the number of businesses, they were the percentages of businesses that don't have complete visibility over their spend, it's high. >> It's very high, we just did a study of 250 or so CFOs in the UK, and they're doing a great job at budgeting and reporting, but they have minimal visibility into their supply relationships, especially with what's happening here with Brexit. They have minimal visibility in supply risks, supply chain risks, and one of the ingredients that I think we're very special at and I'm proud of is the U in Coupa, the user centricity. In order to have visibility into your spend, you have to have adoption, you have to have people purchasing, spending, expensing, paying, processing invoices, everything that you just mentioned through this pipe on one centralized platform with a common UI layer, User Experience layer or User Interface, common business logic layer, common data model, use of community intelligence to help you make the best purchasing decisions, spend decisions. So we're really on the forefront of something very, very exciting because this adoption level is happening through this user centricity, and it's given these companies control and visibility of spend, and what could be more important to driving profitability, sustained business development? I think we're in a very unique position to help these customers. >> So is one of the biggest challenges for those, think it was 96% of those UK financial decision makers that you guys surveyed said, "We don't have complete visibility." Is it because they have legacy siloed solutions that don't give them that common layer? Or is it because maybe that and a mixture of users just not adopting it because it's not as intuitive to use? >> It's a number of things. First of all, for every process, whether it's procurement, expenses, invoicing, or payments, they have seperate systems to your point. Some cases, they don't even have systems. They're calling in orders, they're handling paper invoices, so there are different levels of maturity in each of those four areas. So one is getting them on to a common platform where all of those are orchestrating together. Secondarily, there's an opportunity to create synergy between those areas, so a lot of things that are getting expensed really should be preapproved and should be routed toward preferential pricing that procurement can negotiate on behalf of the user. Many times invoices are duplicate coming in from suppliers and AP departments are so excited that they pay quickly, but they're not necessarily sure whether they received the goods and services that the invoice is for. So having one common platform, that's the C in Coupa, Comprehensive. One common comprehensive platform for all these business processes is critical, leveraging the synergy of all them working together is critical, and getting that widespread user adoption is part of the secret formula here. >> Let's talk about the community. It's big, it's growing, 1.3 trillion in spend managed, and I watched our video back that you and I did a few months ago, it was 1.2. So that was four months ago, and you showed a bar chart today of just the last 12 months, had to look up this way to see that, so this community that has the ability to help derive and leverage the insights, talk to me about the insights and being able to help businesses go from reactive to predictive as a game changer for Coupa. >> Sure, it's a huge game changer and we really aspire to be, if you will, the tail that wags the dog in the enterprise software industry overall because the enterprise software industry, in effect, every customer is on their own island using information technology for a certain business process. What we've done with community intelligence is we've aggregated, anonymized, and sanitized data from the customer base and then are distilling insights that we could be prescriptive about. So we could tell our customers and we're telling them, "Hey, our community is having challenges with such "and such supplier based on literally perhaps millions "of dollars and millions of pounds in transactional spend. "We recommend you consider this supplier in "that same category because our community is having "great success with them. "The products are being shipped on time, "there's no war over invoicing, there's no breakage in "what's delivered." Those are just some examples, we're helping them think through commodities. A lot of our customers forgiven commodity, they have 20, 30 different suppliers. We're helping them think through in their industry. How can they do supply consolidation that makes sense based on benchmarking across the entire industry? We're helping them avoid supplier risk, we're helping them avoid fraud, we're identifying employees that may be expensing things or doing things that are fraudulent based on the collective intelligence of what we're seeing around the entire world in real time and we're prescribing actions to be taken before payments go out. So these are just some examples of what we're doing, we're doing things in benchmarking based on community intelligence, we're really just at the tip of the sphere of what's possible and we've prescribed tens of thousands of prescriptions in our platform to our customers. Many of them are taking those prescriptions and are making their businesses more operationally fit, and more agile, which is something we're very, very proud of. >> Speaking of those prescriptions, I think the number you shared this morning was 22,000 prescriptions delivered in one year? >> In the last 12 months, that's right. >> So we've got to talk about acceleration 'cause we've talked about the COUP, the acceleration, that is one example of that. I also saw that you guys have gotten, customers are doing approvals 30% faster than they were a year ago. You're getting mid-market customers up and running in four months, large enterprises up in eight months, talk to me about that acceleration that you guys are achieving. >> Absolutely, the A in Coupa is about Accelerated, it's about learning from our entire customer base and taking those learnings and making them part of best practices-based appointments so we could go faster and faster and faster. We look at retail customer, we've done dozens of retail customers, large and small. We know how to set up catalogs, we know how to set up workflow, we know how to think through the analytics that they need. So when they get going with the deployment from Coupa, they can get up and running way faster than with going back to five or six years ago where you have to think about it from scratch and a blueprint. They could leverage the insight from the community with doing that in mid-market, with doing that in subverticals like credit unions, for example. Biotechs, we're doing it in insurance, we're doing it in pharma, all hosts of industries, and I think as we learn from every deployment and collect those insights, we're going to be able to drive value faster and faster to our customers. And the other element that's important here is it's not just taking the customer live, all of our customers grow with us. They get more and more value every year, this is why our renewal rate is so strong and customers add more business with us because they're getting value and that value continues to grow, and that's really what value as a service is about. We're not a software company, and we're not a software as a service company. We're truly a value as a service company, which is a very different concept and one that we're cultivating in this marketplace. >> What are some of your favorite, I know you love being in front of the customers, what are some of your favorite examples that really show the value that Coupa is delivering to the changing role of procurement, making that girl or guy much more strategic and much more of a partner to the business? >> Sure, I shared some examples this morning that I really loved and appreciated celebrating some of our trendsetters, or what we call spendsetters. You look at Zalando, our retailer where they weren't necessarily going to take them so seriously about savings, but when they went to marketing and said, "We can give you much more bang "for your marketing budget "so you could reach more potential consumers," well of course they embraced that. And we gave them a usable opportunity, a usable platform for doing that as similar Zalando, they engaged. Now they have something like 85% spender management. When we started working with them, they had zero purchase orders, everything was the wild west. You look at, I was just speaking to one of our customers at Procter & Gamble just five minutes ago here at the expo. They've run more than 50 billion pounds of spend through the Coupa platform, 50 billion. That's not easy, but they've done that in just a couple of years with us, and not only did they have visibility spent, but they're saving, they're routing purchases to preferred suppliers, so the list just goes on and on and on our website, at Coupa.com on the Customers tab, you'll see obviously dozens of customers holding up signs of the real measurable value they're getting from working with us and that's something that we really take a lot of pride in. >> That speaks for itself. Last question for you Rob, talk to me about those strategic partnerships that Coupa has. I know some news coming out today with what you guys are doing with American Express. >> Sure, we've entered the payment space and we entered it because our customer community asked us for it. They said, "Look, if we're procuring goods "and services through you, why wouldn't we all, "and we're doing invoice and we're doing all "of the components of the pipe, "why wouldn't we also go deeper into payments, help us pay." Because many now have to log in to all these different ERP systems and kick off batch process, so we went into payments. And in payments, we have a host of partnerships. Now, today we announced the relationship with American Express in the UK and Australia for virtual credit card payments. Now it's very simple in Coupa, someone needs a good or service, it gets routed through workflow for approval. Once approved, a dynamic credit card number is generated by American Express, the individual makes the purchase, and all the reconciliation, the back-end is handled by Coupa. All the reporting, the visibility, the insights to price points and category assessments are there and visible and the company's in a position to fine tune their spend profile. So that's just one example, and we're doing things in dynamic discounting and accelerating payments. We've just launched today in general availability and Robby will be discussing it tomorrow ahead of business acceleration. We launched our batch payments capability, the ability to do invoice payments in batch along any rail, whether it be banking relationships, whether it be eCheck, whether it be credit card, going into one environment and kicking off batch payments without having to wait for all these different ERP systems to take hold. So we're really at the, in my mind, at the very beginning of addressing a huge market opportunity, we're proud of what we've achieved so far. I'm particularly proud of the customer community developing around us, and we're excited about the days, weeks, months, quarters, and years to come. >> So you talked about, last question, the big TAM, in this total adjustable market. What are some of the core elements to Coupa's path to a billion in revenue? >> We're not as exciting to many investors as a hot startup that grows really quickly and maybe has some sort of viral component to it. We've been at this for over 10 years, we've grown thoughtfully, we've grown carefully. The growth is fast 30, 40 plus percent, but it's thoughtful and careful, it's one customer at a time. We're careful in how much we spend on sales and marketing, especially want customers to choose us rather than us hard-selling them on everything, we want the offering to sell itself. We have an ecosystem of systems integrators, now more than 3,000, Centric, APMG, Deloitte, and others that are certified on deploying Coupa. We're expanding our product footprint, our customers now use on average 4.7 applications from us and they're consuming those applications rather than us pushing them on them. We're expanding globally, we're expanding in terms of the enterprise business and the mid-market business. Our mid-market business is now really at scale and scaling beautifully, it's a beautiful business model. So those are just some of the vectors in which we'll continue to expand, but I think the path to $1 billion for us is very clear, and ultimately comes down to execution, delivering for every customer, making sure they're getting value from working with us year in and year out, and I think before you know it, we'll be on the doorstep of that $1 billion. >> Excellent. Rob, it's been a pleasure having you back on theCUBE. Thank you for having theCUBE out here in London, we appreciate your time. >> Thank you. >> For Rob Bernshteyn, I am Lisa Martin, you're watching theCUBE from Coupa Insp!re 19. Thanks for watching. (upbeat tech music)

>> Announcer: From Sand Hill Road in the heart of Silicon Valley, it's "theCUBE," presenting the People First Network, insights from entrepreneurs and tech leaders. (upbeat electronic music) >> Hi, everyone, welcome to this special "CUBE" conversation. I'm John Furrier, co-host of "theCUBE" and co-founder of SiliconANGLE Media. We are on Sand Hill Road at Mayfield Fund, the venture capitalist funding startups. We're here with Tara Vaishnav, who is the vice president of technology, innovation, and advanced analytics at The Clorox Company, as part of the People First Network co-creation of content with SiliconANGLE and Mayfield. Tara, welcome. >> Well, thank you very much for having me! And congratulations to Mayfield on 50 amazing years, wow! >> 50 years they have been in Sand Hill Road, they've been investing in some great startups. They really have a great philosophy about people first. >> Yep. >> And you've had a very distinguished career in technology, IT, in big companies. Long tenures, too, like, you know, decades. >> Yes, oh, yes. >> And now at Clorox, a consumer company. So talk about your journey, where your experience is, where you started, tell us about your background. >> Yeah, well, I grew up in India, if it's not obvious already. I came to the United States after I finished my undergrad in India, I had an undergrad in electrical engineering. Came over here, got my electrical engineering master's at the University of Southern California, go Trojans. And after that, I worked for several companies, but mostly in health care and life sciences. So the past four years, I have been the vice president of IT at The Clorox Company, which is a CPG company, so quite a bit of a learning curve there. >> Health care, serving patients, now you're serving consumers. >> That's right, that's right. >> Clorox is well-known for their analytics, well-known for technology, innovation. >> Tara: Yes, yeah. >> I've interviewed a bunch of folks at Clorox, they've always been at the head of the curve. >> Tara: Yeah. >> Like Procter & Gamble, you guys, consumer companies have to be. >> Tara: Definitely. >> Now, more than ever, digital disruption is an opportunity for companies to have a better relationship with their customers. >> Tara: Absolutely. >> And changes the makeup of their brand as well, since it touches the customer. How do you see that evolving? What's the current state of the art of some of the things you're working on? >> Yeah, it's pretty fascinating, actually. And I hate to use cliches, but things like consumer experience is really at the heart of it. We're a brand company, at the end of the day, and how people feel about us is really, really important. It's not so much, it is about the products, and we make amazing products, but how do they feel about us as a company, and how do they engage with us differently than they did before? We do not buy the same way as we did even five years ago. And so, learning that, learning the new, evolving consumer, and getting really close to what's important to them, that's really on the forefront of how we think about our digital transformation. >> One of the cool things that's great about the People First Network that we've been doing-- >> Tara: Yeah. >> This content, is that we have a lot of luminaries who have had a storied career, like yourself, have looked at the changes and the waves of innovation that have come before, and now, more than ever, omnichannel, how you advertise and reach customers, how they interact, how they buy and consume. When you look at health care and some of the things you've been involved in, in the '90s, remember, client-server was big, they had computers. >> Tara: (laughs) Oh, yes. Oh, yeah. >> IT has changed a lot. >> It has. >> What is the most striking thing that you see from those changes in this new wave that we're living now? >> You know, so, (sharply exhales) I was fortunate in that I decided that data was where it was at, right from the beginning of my career. That's how I kind of made my way up my career ladder, is really that focus on data. I had a software engineering background, but really felt the power of data to change things. What has happened, if I think about some of the big changes, or the key milestones, if you will, in my career, one of the first real big changes came about when data, which was up until that point really sort of coming along for the ride, you had applications, applications had data, when data actually became the mainstay and the applications kind of came and went. I remember one of my mentors in the past, a past CIO, actually, telling me that applications come and go, but data is forever. And when that really started to become a thing was when big data and big data technologies became, came of enterprise age, if you will, along with cloud technologies. That marriage really, that was, I think, the tipping point where the things that you could do with data and the way that you could get insights from data really took on a life of its own, if you will. >> You know, one of the things, that's a great point. I'd love to get your insights as a leader and as you grew with data, because it wasn't really obvious at that time. Certainly, people had databases and that, the big data, the applications had data. >> Tara: Sure, sure, yeah. >> But it was always kind of old-school data. "Hey, get some data, let's look at the demographics, "let's look at the Consumer Price Index," blah, blah, blah, all kinds of data. But access to data became driven by the database. >> Tara: Correct. >> So there might've been data available-- >> Tara: Yeah. >> But getting it in the hands of the practitioners even now is hard, but even back then, you might not have had the data. So as a leader who's sought data-- >> Tara: Yeah. >> As a strategic advantage. By the way, that's rare early, isn't it? So, (laughs) awesome for you. >> You know, I got lucky. >> How did you get through that? How did you lead the organization to make data at the center of things? >> It is a very good question. There were a few things that started to take shape once big data and the marriage of the cloud started to happen. It started to open up doors, break down organizational silos. When you brought that data together, the business value, or the potential business value that could be unlocked, became obvious. The way that we approached it, though, under my leadership, I always believe in small steps. I believe in leapfrog, but I believe that you have to feed innovation or innovative thinking out in small doses. People are not always ready to consume it in one big (laughs) fell swoop, if you will. So doing things incrementally, but with an idea towards transformation, was, I think, the secret sauce that I used to approach these things. So as a couple of examples, in Kaiser Permanente, when I worked there for almost seven years, I was instrumental in bringing their big data platform to life. But it was not just a matter of, "Here's the technology "for technology's sake." It was a matter of, "Here are some real problems "that we are having a lot of difficulty in solving today. "Let's show you how we can solve those differently "in an amazing way." And we proved that. It was an experiment, that we proved that, and that really started to get us those adopters, if you will. >> John: So take baby steps. >> Yep. >> Don't try to do wholesale changes hardcore. >> Correct, correct. >> Let people get used to it. >> Yeah. >> This must've had an impact on culture. >> Yes, yes. >> And this comes up a lot in the DevOps culture we've seen in the past decade, even now. >> Yeah. >> Getting people to change has become very difficult. >> Yes! >> John: We all know that person-- >> Yes. >> Has their project that's their baby, adding features, "No, don't take my "baby away from me." >> Tara: Yes, yes, yes. >> "I don't want to change." >> (laughs) Oh, yeah. >> How do you make that happen? How do you lead people through that very difficult transformation at an emotional level, on a business level? What's the strategy there? What's your technique? >> Yeah, so, again, back to, you have to show results. And you have to show results incrementally in a way that people can appreciate them and consume them. You have to look at technology from a business value perspective. Business value comes first, technology is just along for the ride. That's how people see it, and that's how they should see it. >> John: Mm-hm. >> It's what you can do with the technology that makes a difference. So, some of the techniques that I have used in the past have been, number one, you do have to find like-minded people in the organization. You can't go at it alone. You have to start to build your clan, if you will, of innovators, so you've got a target audience that you're chippin' away at, slowly, but you've got to build credibility. Because results build credibility. Credibility builds trust. Trust removes barriers. So that's kind of the way that I approach things. I bring like-minded people together, I find people in the organization, of the people that are resistant, that I can bring onto "my side," if you will, and I use their knowledge, their insights, their knowledge of how this person who is obviously a stakeholder, and an important stakeholder, how they think and what's important to them, and I use that language and that person to be able to approach individuals in different ways. It's about culture. >> And it's always good to make them, you know, success has many fathers, if you will-- >> Yep. >> Is always an expression. Making them feel part of the solution. >> Absolutely. >> So I got to ask you a question. Is having a software background, coming into the tech world and the business world, this, now, you're starting to see applications really dictate to the infrastructure. Elastic clouds are out there. >> Tara: Yes. >> You have data as a resource now. If you were entering the market as a young software engineer today, and you were asked to come in and make an impact, knowing what you know, how do you see the world today? Because, you know, a lot of software engineers creating value from men, and, now, a lot more women are coming on board. >> Yeah, yeah. >> It's still lower numbers, but still, software's not just that software engineer. >> Yeah. >> It's software architecture, it's software engineering, software development, UX, UI-- >> Tara: Yeah. >> Analytics, a lot of range-- >> Tara: Yeah, yeah. >> Of software opportunities. How would you attack the marketplace today if you were coming in and entering the workforce or in the middle of your career? >> Yes, you know, when I look at my career, which is a little longer than I'd like to admit, I see myself as a young undergraduate student in India. I was one of six girls in a class of about 50. I was striving to get a degree in what was called, actually, electronics and telecommunication. I was in a minority. I came over here to the United States, and I continued to be in the minority. I look at my career, which is more than 25 years old. I have also continued to stay in the minority throughout that career. The biggest difference between where I am now in my career versus where I was then is I don't care as much anymore that I'm in the minority. (both laugh) Right? What is fascinating to me, though, John, is when I look at some of the very young students, actually, we had a high school intern program for the first time this year at Clorox, which is actually interesting. We typically have college interns, but this year, Clorox, a 105-year-old company in the middle of the Silicon Valley, having the ability to see that the very, very young generation can think very differently, and bringing in the high school intern, or a set of high school interns, to help with that journey, I think, was forward-thinking for the company. And those kids, the confidence that they have? They are not shackled by knowing too much, you know? >> John: Yes. >> But they know what's relevant, they know how to make things happen, and boy, do they know how to use technology to make problems that we consider problems that would take months, happen so quickly. They were with us for four weeks. In four weeks, they developed an app, a website. They developed our logo. They developed a PR video for us. They had an innovation showcase. In four weeks, four little students. >> It's interesting, for the first time (Tara laughs) in my career, I can admit that, from a self-awareness standpoint, "Well, I really don't know what I'm talking about." These young kids have a different view, because now their experiences are different. >> Tara: Yes. >> And so, the insight coming out of this new generation really is pretty compelling. >> Tara: It is. >> They are adding a lot more because there's been a shift in expectations, there's been a shift in experiences-- >> Tara: Yes. >> For this new generation, and they're at the forefront, so it's a big wave coming. What's your thoughts on that? Because analytics is a big part of your career now, and it always-- >> Tara: Yes, yes. >> Has been, but now, more than ever-- >> Yeah. >> The younger generation, they want instant gratification, they want value. >> They do. >> They don't want to wait and be told-- >> They do. >> They want to see the immediacy. >> They do. >> Talk about this new shift, this new younger generation. >> Yeah, yeah. You know, there used to be the good old days, where we could, say, put a product out there and, you know, eventually it kind of works its way into the consumer ecosystem, and then we'd get to hear back, over the course of time. Customers would call in with a recommendation or a complaint. It's very different now. Things are out there instantaneously. We put something out there, you're getting comments and reviews, some of them good, some of them not so good. It's out there, and it's out there instantly. And that also, the modern consumer is not shy. They kind of hide behind the keyboard, and they're putting their comments out there, right? (both laugh) They're the keyboard warriors! >> John: (laughs) Yeah. >> So being able to respond to that and having not just the data, but the ability to extract insights from data and to extract insights in real time, that is crucial. And so, gone are the days where you had months to do your analytics. You have to be able to do your analytics in the flow, you have to be able to take in new information, incorporate it into your models, be able to do predictive analytics on it. So technology and the way that it is evolving is super critical for survival these days. >> So, survival, and also competitive advantage, we've heard-- >> Oh, for sure. >> From other CIOs, and also CSOs, from a security standpoint-- >> Yes, yes. >> There's business risks involved. How real-time do you see the advantage being? Obviously, near real time is pretty much what people talk about. >> Yeah. >> Real time is to the second, and self-driving cars will certainly need that. >> Yeah, yeah, yeah. >> But as a leader chasing the real-time holy grail-- >> Yeah. >> Seems to be a theme we hear. How do you react to that, and how do you view real-time data? >> There is definitely something that builds up to the richness of data that you can take advantage of in "real time." And I am saying "real time" in quotes because there is a contextuality associated with it. The wonder of modern advanced analytics and machine learning is that you have an existing model that you're tweaking and evolving with new information, and that model is serving as your guide as you receive new information. So, does it have to be reactive, or can it be proactive? You're building the insights, and then you're adding on new information as you see it. And you're using technology to help you make more holistic decisions. And at the end of the day, there is something to be said about the human aspect of it. The machine can give you guidance-- >> John: Yes. >> But the human being needs to make the decision. >> I'd love to ask you a quick question on that, because I think this is something that we talk about all the time. >> Yeah. >> Humans are critical in the equation, machines augment the humans. >> Yes. >> In the data world, if you're "data-driven," which has been (laughs) a cliche, "We're data-driven!" >> Tara: Yes, yes. >> It takes on multiple forms. >> Tara: Yes. >> I've seen multiple actors saying, "We're data-driven," but they're really just correlating data. >> Tara: Yeah. >> The causation side of it is, what's causing things, that's more of a management thing. >> Tara: Yeah. >> So causation and correlation are two different variables-- >> Tara: Yes. >> In the analytics field right now-- >> Tara: Yeah. >> That are being amplified as, you got to know the distinction between correlation, because you can correlate anything, causation is something that might be more designed towards figuring out something, and you really can't rest on one more than the other. >> Yeah. (laughs) >> Your thoughts on the balance between the two. >> You're talking to someone who worked in health care for-- (laughs) >> John: (laughs) I probably won't get you to continue. >> For almost seven years. Causation and correlation are-- >> John: More important than ever. >> Are more important than ever. And I think more and more, the boundary between what machines can do and how they can augment human beings, versus actually having the machines help you make decisions, it's getting fuzzier, and machines are able to do more and more. I mean, all of the knowledge that you could read about 24 hours a day cannot sit in your head. You have to be able to leverage machines to help you make those decisions. So as far as causation and correlation, I think the correlation is something that the machine can be the master of. It can see patterns where you may not even think to look for patterns. So I think that, let's give it up to the machines. Correlation is where-- >> John: They got that. >> The machines have got that, and you got to set them up so that they can do that for you. Causation is where the tricky area starts to happen. Because there is a lot to say, especially when you talk about doctors, about experience and working with individuals. Each individual is different. You can't say that the causation for this person is the same as that because the correlations are similar. No, you have to look, there are so many factors that go into what is causing-- >> John: Yeah. >> A disease or a condition in a person. So I think that is where the human element and experience really, really still make a difference. >> In the media business, we call it behavioral and contextual. >> Yes. >> Context is really important for really aligning-- >> It is. >> With whatever the problem statement may be. >> Yes, yes. >> Correlation, behavior, machines can do that. >> Correct. >> That's awesome, great, great, great insight there. A final question for you is, for other folks out there, CIOs or IT executives, as they look at the digital transformation journey, which, again, very cliche, but very real, there's a lot of opportunities, but also potential pitfalls if not executed properly. >> Tara: Yeah. >> Your thoughts on general roadmaps or best practices around how to tackle transformation, if they're doing it, coming in for the first time or at the beginning, or if they're in the middle of a digital transformation, and they're stuck in the mud-- >> Yeah, yeah. >> Or "Oh my God, "my head person quit. "I got to get more people." >> Yeah. >> "I need developers," or people on the back end of the transformation, different parts of the journey. What's your advice? >> Yeah, I've got a couple of, again, from the scars of my past, a couple of things that I think are important. Number one, when I joined Clorox, I had the stretch goal of actually building out their cybersecurity program. I had not done that in the previous part of my career. I was an enterprise architect, that's where I would spend most of my many years. But cybersecurity, and I hired the CSO and built out that program for Clorox, it puts a whole different lens on how you look at your transformation, and it is an important lens. And I think I would not have been rounded, as either an enterprise architect who's developing technology strategy or a digital technology innovator, if I did not have that lens of, there is risk that you need to consider. Now, the point to remember is that you can't over-rotate one way or the other. You have to consider risk and opportunity, and there's a fine line. And I think the smartest CIOs and senior executives know where that fine line exists, and are able to tell when you need to go this way or that way. So that's one thing that I would say, is don't lose that lens. Technology can do wonderful things for you, but so can the hackers from a different-- >> You got to be aware-- >> You've got to be aware. >> And then, you've got to shape it, too, as it evolves. Is that something that you see as important? >> You have to have that lens of, you're doing this wonderful, amazing thing, however, what if the unintended audience is able to access whatever you're doing? And what can they do with it? So that's one thing that I would say, is keep that balance in mind. Again, don't over-rotate one way or the other, but keep that balance in mind. The other thing that I would say is, innovation is a state of mind that needs to be nurtured and developed, and it needs to be sought from every part of the organization. The only way to scale innovation is to have everybody be an innovator in the organization. So that would be my advice, is innovation can come from the youngest high school intern, or, we actually just had someone at Clorox celebrate their 50th year at Clorox. So, you know-- >> John: Yeah. >> Innovation can come from anywhere in the organization. You have to always be ready, open-minded, and prepared to grab that opportunity when it happens. >> My final takeaway for this is in context to where we are now, we're on Sand Hill Road-- >> Yes. >> At Mayfield Fund, they're a venture capitalist. >> Yes. >> They fund early-stage and growth. >> Yep. >> The younger generation, we just talked about the insights that they can have, new shifts that are happening in experiences, expectations. The startups, more than ever, have an opportunity to have customers like Clorox. >> Tara: Yes, yes. >> What used to be, "Well, a startup, "risk, don't go through the, go through TSA, "and when you get approved, "then we'll talk to you," kind of thing. (Tara guffaws) It's a big, painful process. >> Used to be? >> Now, more than ever, startups want to land the big Clorox deals. >> Yes, yes. >> They want to show the value proposition, time to value, shortening, with cloud and other things. What's your advice to startups who want to sell to you or hope to, aspire to, be successful in the marketplace? >> You know, I love startups, and I spent a lot of time with them. What I have seen as differentiating in the startups that I have seen is, some of them, they're out there, they want your business. So they are looking at you from that, "Can I get your business?" And then there are other startups that, I'm sure they've got that lens, but they don't make it obvious to you. To them, the value is in working with you. You're a company that is well-reputed. You've got a ton of amazing data that can be used to develop your models. You've got a ton of insights and understanding of the business that you can get by just working with this "reputed" company, like Clorox. Those in itself, you can't put a tangible, material value on that, but that is what helps startups build relevant and amazing products. And that, in itself, is "payment." The money will come, but look to the experiences, look to the ability to leverage data, and, above all, look to how you can position your product in a way that it is solving a business problem. Don't do technology for technology's sake. >> So, your advice would be, don't focus on on the PO. If they're venture-backed, they probably have some runway. >> Yes. >> Focus on the value proposition. >> Absolutely, and learning how companies operate and what's important to them, take the time to do that. >> How about scale? Do you hear that a lot with startups, they want to try to use the value proposition? One, they have to get in the door and show value, so that's one. >> Tara: Of course. >> Kind of table stakes, get through the door. >> Okay, yep. >> Then it's more about how they can be operationalized. That becomes something I've seen with startups. What's your thoughts on that? Because one of the benefits of getting in the door is getting (laughs) in the door, but staying in-- >> Yeah. >> Is about operationalizing that new value proposition. How do you look at that as a leader? >> (sharply exhales) Yeah, the word operationalization is an interesting one. So, companies like Clorox, I mean, while I love to work with startups, I will tell you that I do experiments, four, six, eight weeks, we've got a metric. If we go beyond that, it's probably a project that needs to go through a different route. But we do these experiments, and we do them quickly. The thing that we do worry about is, "Okay, great startup, great product. "Is it enterprise-ready?" You know? And I think that is where a lot of startups struggle a little bit, is, can they prove to you that their product is Fort Knox, that it won't be a way through which your systems get hacked? Can they prove to you that they've got a good handle on where they are going, what their roadmap is, what capabilities they are developing in their roadmap? Can they showcase that to you in a way that makes sense to you? We're looking for companies that are not just here today and gone tomorrow, companies that are here for the long run. And then, even if they can't do all of that, show that you integrate really well with our other products. Because, guess what, if you don't work out so well for us, little startup, we want to be able to replace you. We want to have that option. And if you don't integrate seamlessly and can be plucked out and put back in again, then we're stuck with something that we can't extract from our environment. So they've got to think how we think, is what I would advise them. (laughs) >> Tara, thanks so much for this great insight. For startups out there, for folks entering their career, for other women who are looking to break into tech, we have a great inspirational leader here. >> Thank you. >> John: Thank you for spending the time, we really appreciate it. >> Thank you very much, really appreciate it. >> Thank you very much. I'm John Furrier. You're watching the People First program with SiliconANGLE and Mayfield. Thanks for watching. (upbeat electronic music)

>> From Cambridge, Massachusetts, it's theCUBE. Covering MIT Chief Data Officer and Information Quality Symposium 2019. Brought to you by SiliconANGLE Media. (futuristic music) >> Welcome back to Cambridge, Massachusetts everybody. You're watching theCUBE, the leader in live tech coverage. We go out to the events and we extract the signal from the noise. This is day two, we're sort of wrapping up the Chief Data Officer event. It's MIT CDOIQ, it started as an information quality event and with the ascendancy of big data the CDO emerged and really took center stage here. And it's interesting to know that it's kind of come full circle back to information quality. People are realizing all this data we have, you know the old saying, garbage in, garbage out. So the information quality worlds and this chief data officer world have really come colliding together. Robert Abate is here, he's the Vice President and CDO of Global IDS and also the co-chair of next year's, the 14th annual MIT CDOIQ. Robert, thanks for coming on. >> Oh, well thank you. >> Now you're a CDO by background, give us a little history of your career. >> Sure, sure. Well I started out with an Electrical Engineering degree and went into applications development. By 2000, I was leading the Ralph Lauren's IT, and I realized when Ralph Lauren hired me, he was getting ready to go public. And his problem was he had hired eight different accounting firms to do eight different divisions. And each of those eight divisions were reporting a number, but the big number didn't add up, so he couldn't go public. So he searched the industry to find somebody who could figure out the problem. Now I was, at the time, working in applications and had built this system called Service Oriented Architectures, a way of integrating applications. And I said, "Well I don't know if I could solve the problem, "but I'll give it a shot." And what I did was, just by taking each silo as it's own problem, which was what EID Accounting Firm had done, I was able to figure out that one of Ralph Lauren's policies was if you buy a garment, you can return it anytime, anywhere, forever, however long you own it. And he didn't think about that, but what that meant is somebody could go to a Bloomingdale's, buy a garment and then go to his outlet store and return it. Well, the cross channels were different systems. So the outlet stores were his own business, retail was a different business, there was a completely different, each one had their own AS/400, their own data. So what I quickly learned was, the problem wasn't the systems, the problem was the data. And it took me about two months to figure it out and he offered me a job, he said well, I was a consultant at the time, he says, "I'm offering you a job, you're going to run my IT." >> Great user experience but hard to count. >> (laughs) Hard to count. So that's when I, probably 1999 was when that happened. I went into data and started researching-- >> Sorry, so how long did it take you to figure that out? You said a couple of months? >> A couple of months, I think it was about two months. >> 'Cause jeez, it took Oracle what, 10 years to build Fusion with SOA? That's pretty good. (laughs) >> This was a little bit of luck. When we started integrating the applications we learned that the messages that we were sending back and forth didn't match, and we said, "Well that's impossible, it can't not match." But what didn't match was it was coming from one channel and being returned in another channel, and the returns showed here didn't balance with the returns on this side. So it was a data problem. >> So a forensics showdown. So what did you do after? >> After that I went into ICICI Bank which was a large bank in India who was trying to integrate their systems, and again, this was a data problem. But they heard me giving a talk at a conference on how SOA had solved the data challenge, and they said, "We're a bank with a wholesale, a retail, "and other divisions, "and we can't integrate the systems, can you?" I said, "Well yeah, I'd build a website "and make them web services and now what'll happen is "each of those'll kind of communicate." And I was at ICICI Bank for about six months in Mumbai, and finished that which was a success, came back and started consulting because now a lot of companies were really interested in this concept of Service Oriented Architectures. Back then when we first published on it, myself, Peter Aiken, and a gentleman named Joseph Burke published on it in 1996. The publisher didn't accept the book, it was a really interesting thing. We wrote the book called, "Services Based Architectures: A Way to Integrate Systems." And the way Wiley & Sons, or most publishers work is, they'll have three industry experts read your book and if they don't think what you're saying has any value, they, forget about it. So one guy said this is brilliant, one guy says, "These guys don't know what they're talking about," and the third guy says, "I don't even think what they're talking about is feasible." So they decided not to publish. Four years later it came back and said, "We want to publish the book," and Peter said, "You know what, they lost their chance." We were ahead of them by four years, they didn't understand the technology. So that was kind of cool. So from there I went into consulting, eventually took a position as the Head of Enterprise and Director of Enterprise Information Architecture with Walmart. And Walmart, as you know, is a huge entity, almost the size of the federal government. So to build an architecture that integrates Walmart would've been a challenge, a behemoth challenge, and I took it on with a phenomenal team. >> And when was this, like what timeframe? >> This was 2010, and by the end of 2010 we had presented an architecture to the CIO and the rest of the organization, and they came back to me about a week later and said, "Look, everybody agrees what you did was brilliant, "but nobody knows how to implement it. "So we're taking you away, "you're no longer Director of Information Architecture, "you're now Director of Enterprise Information Management. "Build it. "Prove that what you say you could do, you could do." So we built something called the Data CAFE, and CAFE was an acronym, it stood for: Collaborative Analytics Facility for the Enterprise. What we did was we took data from one of the divisions, because you didn't want to take on the whole beast, boil the ocean. We picked Sam's Club and we worked with their CFO, and because we had information about customers we were able to build a room with seven 80 inch monitors that surrounded anyone in the room. And in the center was the Cisco telecommunications so you could be a part of a meeting. >> The TelePresence. >> TelePresence. And we built one room in one facility, and one room in another facility, and we labeled the monitors, one red, one blue, one green, and we said, "There's got to be a way where we can build "data science so it's interactive, so somebody, "an executive could walk into the room, "touch the screen, and drill into features. "And in another room "the features would be changing simultaneously." And that's what we built. The room was brought up on Black Friday of 2013, and we were able to see the trends of sales on the East Coast that we quickly, the executives in the room, and these are the CEO of Walmart and the heads of Sam's Club and the like, they were able to change the distribution in the Mountain Time Zone and west time zones because of the sales on the East Coast gave them the idea, well these things are going to sell, and these things aren't. And they saw a tremendous increase in productivity. We received the 2014, my team received the 2014 Walmart Innovation Project of the Year. >> And that's no slouch. Walmart has always been heavily data-oriented. I don't know if it's urban legend or not, but the famous story in the '80s of the beer and the diapers, right? Walmart would position beer next to diapers, why would they do that? Well the father goes in to buy the diapers for the baby, picks up a six pack while he's on the way, so they just move those proximate to each other. (laughs) >> In terms of data, Walmart really learned that there's an advantage to understanding how to place items in places that, a path that you might take in a store, and knowing that path, they actually have a term for it, I believe it's called, I'm sorry, I forgot the name but it's-- >> Selling more stuff. (laughs) >> Yeah, it's selling more stuff. It's the way you position items on a shelf. And Walmart had the brilliance, or at least I thought it was brilliant, that they would make their vendors the data champion. So the vendor, let's say Procter & Gamble's a vendor, and they sell this one product the most. They would then be the champion for that aisle. Oh, it's called planogramming. So the planogramming, the way the shelves were organized, would be set up by Procter & Gamble for that entire area, working with all their other vendors. And so Walmart would give the data to them and say, "You do it." And what I was purporting was, well, we shouldn't just be giving the data away, we should be using that data. And that was the advent of that. From there I moved to Kimberly-Clark, I became Global Director of Enterprise Data Management and Analytics. Their challenge was they had different teams, there were four different instances of SAP around the globe. One for Latin America, one for North America called the Enterprise Edition, one for EMEA, Europe, Middle East, and Africa, and one for Asia-Pacific. Well when you have four different instances of SAP, that means your master data doesn't exist because the same thing that happens in this facility is different here. And every company faces this challenge. If they implement more than one of a system the specialty fields get used by different companies in different ways. >> The gold standard, the gold version. >> The golden version. So I built a team by bringing together all the different international teams, and created one team that was able to integrate best practices and standards around data governance, data quality. Built BI teams for each of the regions, and then a data science and advanced analytics team. >> Wow, so okay, so that makes you uniquely qualified to coach here at the conference. >> Oh, I don't know about that. (laughs) There are some real, there are some geniuses here. >> No but, I say that because these are your peeps. >> Yes, they are, they are. >> And so, you're a practitioner, this conference is all about practitioners talking to practitioners, it's content-heavy, There's not a lot of fluff. Lunches aren't sponsored, there's no lanyard sponsor and it's not like, you know, there's very subtle sponsor desks, you have to have sponsors 'cause otherwise the conference's not enabled, and you've got costs associated with it. But it's a very intimate event and I think you guys want to keep it that way. >> And I really believe you're dead-on. When you go to most industry conferences, the industry conferences, the sponsors, you know, change the format or are heavily into the format. Here you have industry thought leaders from all over the globe. CDOs of major Fortune 500 companies who are working with their peers and exchanging ideas. I've had conversations with a number of CDOs and the thought leadership at this conference, I've never seen this type of thought leadership in any conference. >> Yeah, I mean the percentage of presentations by practitioners, even when there's a vendor name, they have a practitioner, you know, internal practitioner presenting so it's 99.9% which is why people attend. We're moving venues next year, I understand. Just did a little tour of the new venue, so, going to be able to accommodate more attendees, so that's great. >> Yeah it is. >> So what are your objectives in thinking ahead a year from now? >> Well, you know, I'm taking over from my current peer, Dr. Arka Mukherjee, who just did a phenomenal job of finding speakers. People who are in the industry, who are presenting challenges, and allowing others to interact. So I hope could do a similar thing which is, find with my peers people who have real world challenges, bring them to the forum so they can be debated. On top of that, there are some amazing, you know, technology change is just so fast. One of the areas like big data I remember only five years ago the chart of big data vendors maybe had 50 people on it, now you would need the table to put all the vendors. >> Who's not a data vendor, you know? >> Who's not a data vendor? (laughs) So I would think the best thing we could do is, is find, just get all the CDOs and CDO-types into a room, and let us debate and talk about these points and issues. I've seen just some tremendous interactions, great questions, people giving advice to others. I've learned a lot here. >> And how about long term, where do you see this going? How many CDOs are there in the world, do you know? Is that a number that's known? >> That's a really interesting point because, you know, only five years ago there weren't that many CDOs to be called. And then Gartner four years ago or so put out an article saying, "Every company really should have a CDO." Not just for the purpose of advancing your data, and to Doug Laney's point that data is being monetized, there's a need to have someone responsible for information 'cause we're in the Information Age. And a CIO really is focused on infrastructure, making sure I've got my PCs, making sure I've got a LAN, I've got websites. The focus on data has really, because of the Information Age, has turned data into an asset. So organizations realize, if you utilize that asset, let me reverse this, if you don't use data as an asset, you will be out of business. I heard a quote, I don't know if it's true, "Only 10 years ago, 250 of the Fortune 10 no longer exists." >> Yeah, something like that, the turnover's amazing. >> Many of those companies were companies that decided not to make the change to be data-enabled, to make data decision processing. Companies still use data warehouses, they're always going to use them, and a warehouse is a rear-view mirror, it tells you what happened last week, last month, last year. But today's businesses work forward-looking. And just like driving a car, it'd be really hard to drive your car through a rear-view mirror. So what companies are doing today are saying, "Okay, let's start looking at this as forward-looking, "a prescriptive and predictive analytics, "rather than just what happened in the past." I'll give you an example. In a major company that is a supplier of consumer products, they were leading in the industry and their sales started to drop, and they didn't know why. Well, with a data science team, we were able to determine by pulling in data from the CDC, now these are sources that only 20 years ago nobody ever used to bring in data in the enterprise, now 60% of your data is external. So we brought in data from the CDC, we brought in data on maternal births from the national government, we brought in data from the Census Bureau, we brought in data from sources of advertising and targeted marketing towards mothers. Pulled all that data together and said, "Why are diaper sales down?" Well they were targeting the large regions of the country and putting ads in TV stations in New York and California, big population centers. Birth rates in population centers have declined. Birth rates in certain other regions, like the south, and the Bible Belt, if I can call it that, have increased. So by changing the marketing, their product sales went up. >> Advertising to Texas. >> Well, you know, and that brings to one of the points, I heard a lecture today about ethics. We made it a point at Walmart that if you ran a query that reduced a result to less than five people, we wouldn't allow you to see the result. Because, think about it, I could say, "What is my neighbor buying? "What are you buying?" So there's an ethical component to this as well. But that, you know, data is not political. Data is not chauvinistic. It doesn't discriminate, it just gives you facts. It's the interpretation of that that is hard CDOs, because we have to say to someone, "Look, this is the fact, and your 25 years "of experience in the business, "granted, is tremendous and it's needed, "but the facts are saying this, "and that would mean that the business "would have to change its direction." And it's hard for people to do, so it requires that. >> So whether it's called the chief data officer, whatever the data czar rubric is, the head of analytics, there's obviously the data quality component there whatever that is, this is the conference for, as I called them, your peeps, for that role in the organization. People often ask, "Will that role be around?" I think it's clear, it's solidifying. Yes, you see the chief digital officer emerging and there's a lot of tailwinds there, but the information quality component, the data architecture component, it's here to stay. And this is the premiere conference, the premiere event, that I know of anyway. There are a couple of others, perhaps, but it's great to see all the success. When I first came here in 2013 there were probably about 130 folks here. Today, I think there were 500 people registered almost. Next year, I think 600 is kind of the target, and I think it's very reasonable with the new space. So congratulations on all the success, and thank you for stepping up to the co-chair role, I really appreciate it. >> Well, let me tell you I thank you guys. You provide a voice at these IT conferences that we really need, and that is the ability to get the message out. That people do think and care, the industry is not thoughtless and heartless. With all the data breaches and everything going on there's a lot of fear, fear, loathing, and anticipation. But having your voice, kind of like ESPN and a sports show, gives the technology community, which is getting larger and larger by the day, a voice and we need that so, thank you. >> Well thank you, Robert. We appreciate that, it was great to have you on. Appreciate the time. >> Great to be here, thank you. >> All right, and thank you for watching. We'll be right back with out next guest as we wrap up day two of MIT CDOIQ. You're watching theCUBE. (futuristic music)

>> Announcer: From the Cosmopolitan Hotel in Las Vegas, Nevada, it's theCUBE. Covering Coupa Inspire 2019. Brought to you by Coupa. >> Welcome to theCUBE. Lisa Martin on the ground at Coupa Inspire '19 from the Vegas. I'm very pleased to welcome not Bono, not Sting, it's Chandar, the CMO of Coupa. Chandar, welcome to theCUBE. >> Lisa, thank you, it's great to be here today. >> This is a really cool event. Procurement is sexy. >> It is sexy. >> It can be so incredibly transformative to any organization. I loved how the last two days, what you guys have done is a great job of articulating Coupa's value in procurement, invoicing, payments, expense, through the voices of your customers and I think there's no better brand value that you can get. >> Sure, absolutely. >> Tell us a little bit about your role as the CMO of Coupa and marketing in a fast-growing company with a product that people might go, "I haven't heard of that, what is that again?" >> Yeah, it's a good question. I think if I look at it, my role is at Coupa, especially, for Coupa, what's interesting about it, as you said, is that every company makes money, every company spends money. So, invariably, Coupa can be used across a set of different companies. One from the Golden State Warriors to Procter & Gamble to the Lukemia & Lymphoma Society. Across the board. And then, from our perspective, holistically, we're looking at business, but managed from different aspects of spend. You said procurement was in expenses. So, my role is to build a marketing engine to get the flywheel effect of first you drive awareness. All marketing starts with awareness and you said people haven't heard of it. And so, to first to drive awareness in a very thoughtful way to the right contextual community we want to go after. And, two, drive acquisition, we'll drive close synergies between sales and marketing to ultimately drive pipeline and win rates and ultimately deals. And then, very importantly in today's world, is to drive the advocacy and get your most passionate customers to evangelize about the brand, so that you create the flywheel effect of awareness, acquisition, and advocacy. And, that's really what my role today is. >> And, I love how I read an article where you call that the stairway to marketing heaven. So, I thought, I wonder if you're a guitar guy, but you're right. It's how to drive awareness, but in a meaningful, thoughtful way. Especially today, with all all the technology, we wake up with it, right? Our phone is our alarm clock. We are bombarded by ads. If we're on Instagram, following our favorite celebrities or whatnot and it's scary when they have the right context, but it has to be thoughtful. We need to know our audience. So, you describe this stairway to marketing heaven, as you just mentioned, it's awareness, it's acquisition, which is key. But, I feel like a lot of companies don't forget the advocacy part, but they don't invest enough in it because that's the best salesperson for your technology, is the people that are using it successfully, right? >> Totally. Yeah, so, in fact, there was a study about a couple of years which looked at how balanced the boat is in terms of spending in presale versus post-sale. And, it's interesting that 87% of B2B marketing spend was presale. In other words, only 13% of people were investing in retention marketing, adoption mastery, customer marketing, and this is what advocacy marketing. And, in today's world, that doesn't work because you got to balance the boat because, to your point, you're getting in a peer-bond world where your existing customers are your best sellers. And, prospects who have all the buying power today are looking to your existing customers to guide them in their purchasing decisions. So, as an organization, if you balance the boat, then you're going to get the flywheel effect going for you in terms of driving the right advocacy across all channels. Just not your own channel if you earn channels to ultimately drive that acquisition going. >> Do you think that's actually more valuable? 'Cause it's one thing to have on your .com site, your social media sites, all these great things about your technologies, etc., coming from customers or from product experts, from influencers. Talk about the value. As technology advances so much and we are influenced by so many other channels, the value of the earned channel and that peer-to-peer relationship. >> Yeah, I think, as I say, that every mom says her baby is good-looking. But, in software, not every baby is really good-looking. Which means, if you take that analogy and extend it, if you're coming to your own channel, invariably, you're going to see some great customer videos about your product, you're going to see some great endorsements and testimonials, you're going to see some great quotes about your product. The reality, there's no bad news about your product on your own website, on your own channel. But, the reality is there are some, some people who might have different opinions. If you go to Glassdoor, no company gets a five on Glassdoor. And, if you take the same thing and extend it to earned channels for advocacy, folks like G2 Crowd, TrustRadius, and B2B, for example, are becoming more relevant today than before because two things. One is 85% of our customers' journey is self-directed. >> Lisa: That much? >> That much and Forrester has anywhere from 60 to 80, but reality is whether you're buying a car or you're buying Coupa. Today, a customer is discovering more journeys. And, in that process, they are looking to more of these earned channels as validation of which ones to go after than just your own channels. So, that's why we got to balance the boat and distribute our advocacy spend dollars across both your own channels and your earned channels. And, that's really important for you and the flywheel will pay off for you over time from that perspective. >> It will and that seems like a lot of the things that Suzy Irwin was talking about to the audience earlier. That's common sense. Why is it that you see these marketing budgets that are so heavily weighted towards just getting awareness, getting customers acquired, and then not thinking about retention marketing account based marketing. >> I'll tell you why. I think any smart CMO will conceptually agree with you. Nobody's going to say, of course, this is not important for me to get advocacy. The challenge comes in in terms of how that marketing department is measured. What gets measured gets funding at the end of the day. >> Lisa: That's a good point. >> And, reality is a lot of these B2B companies are still measuring marketing based on, what's the pipeline you're driving and what's at the top of the funnel metrics that you're driving? In reality, that's a little bit of a skewed thing because then if that's what you're being measured at the board level, at the executive level, then guess what? All your funding is going to go towards that. But, really, the true measurement of marketing, one, is about, yes, you have to get pipeline. You have to influence win rates at the bottom of the funnel and that's where product marketing comes in. But, as importantly, you have to look at the number of brand advocates you create and lifetime value of a customer. >> Yes, CLV, yes. >> And, that's really, really, customer lifetime value is so important because in a SaaS business, ultimately, the Mufasa metric, I'm a Lion King fan. The Mufasa metric is really lifetime value because if a customer stays longer with you, pays you more, and is shouting from the rooftop, then, invariably, that SaaS business is doing well. And, that's why you have to balance the boat in terms of post-advocacies, post-acquisition spend into advocacy, as much as you've done in pre-acquisition. >> When you came into Coupa a couple of years ago, have you been able to shift those budgets because you're able to demonstrate the value that that advocacy piece generates with the flywheel? >> Absolutely and I have a very progressive-thinking CEO who's partners with me on this too. So, we've been absolutely able to do that. In fact, what we're trying to do at the end of the day and most software companies, the real goal should be creating a tribe. In technology, you have to create a tribe to be a titan. And, it's just not about the capability, it's about the community. And, that's really what we're trying to do at Coupa is to create the tribal community feeling. So, if the community is bigger than the brand, it is about the community itself and learning, sharing, and growing with each other and being successful. And, we're just fostering that. So, from that perspective, if you look at this conference and the investment we're making here, some of the programs we're doing in terms of advocacy, what we call spend sellers, etc., is all about that community tribal feeling and go establish that. To use some inspiration from our consumer brands, if you really think about it, people don't buy what they want. People buy what they want to be. So, let me give you what I mean by that. What I want could be a bike. It could be any motorbike, but what I want to be could be part of a very special community and that's why Harley Davidson is successful. What I want could be any stationary bike today, but what I want to be is part of some cool community like Peloton. That's why Peloton is successful. So, similarly for us, what I want could be some spend management software, but what I want to be is part of this community, this cool club, and that's the feeling we're trying to create in the post-acquisition cycle. >> I love that you said that because you talked about that this morning and I loved how you had the word community on the slide and then broke that out into communication unity. And, one of the senses that I got yesterday when-- >> Chandar: Rob was talking about it. >> Yeah, when Rob kicked off everything is this is a very collaborative community. We think about that in terms in terms even like a developer community or something like that. But, Coupa is now managing $1.2 trillion of spend through the platform that every other business that's using Coupa gets to benefit from. It's customer-centric, it's supplier-centric, but it's about applying the right technologies, AI, machine learning, to all this data, so everybody benefits. >> That's right and one of the interesting aspects of community building is one aspect of community building is that Marc Benioff had a great, evangelistic marketing was a way of community building. He would come in and really evangelize and this is where we're going and you all need to come with us. When I was at Marketo, it was interesting. Community building was through more educational marketing and doing it through this, I'm going to educate you through though leadership. Another good way of community building is through product intelligence, which is community intelligence. So, collectively, the sum of all parts are smarter than the parts themselves. And, Rob has a great line, which says, "None of us is as smart as all of us." And, the fundamental community intelligence offering is based on this first principle. So, example, if I'm the community of Coupa customers, the next customer is smarter than the previous customer because the collective intelligence grew, which means I can then go benchmark it myself. I gave an example this morning of USO, the company that provides services to the United States troops. And, when Rick Quaintance at USO benchmarked himself using community intelligence, versus the rest of the community, he realizes that his invoice cycle times are seven times lower. So, that kind of intelligence is extremely beneficial and invaluable to companies. So, that's the value of the community, is providing the collective intelligence. Waze is a great consumer example. Those of us who use Waze for traffic know that it's all community driven and each one of us is smarter because we're collectively using it. It's the same concept in applying that to B2B software. >> So, as we see, you mentioned the over 80% of the buying decision is self-directed whether we're buying a car or Coupa software. Did Coupa foresee that in the last decade to see we're going to have to go to a more community-driven collaboration because the consumer of any thing, any product or service, is going to be so empowered 'cause that's a part of the Coupa foundation. >> It is. >> Lisa: Which, we don't see a lot in companies that are 10 plus years old. >> Yeah, and credit to Rob for his vision for this. It's because I think early part of the company, he wrote into the contracts that the company can benefit. Collectively, every company can benefit by being part of this community. And, the fact is data's aggregated, abstracted, there's no information that is sensitive, etc. But, the fact is we all can collectively benefit through it. That was a great vision of Rob and early people and that's benefited us because the benefit is really over scale and time. Now, your $1.2 trillion, it is really statistically significant in each different industry to get that intelligence. And, that is one of the other reasons we launched our business spend index. It's called spendindex.com. Where we can use the billions of dollars spent in the community to provide a leading indicator of economic growth based on current business spend sentiment. You think of ADP as this payroll, it's called ADP payroll thing that comes out and the gross domestic product report comes out. Those tend to be rear-view mirror lagging indicators. But, as we're using community-based intelligence to provide a windshield, a leading indicator of where the economy is going. So, there's so many different use cases. Benefiting based on spend you're doing as well as where the economy is going and all this is based on the intelligence. >> It's so powerful because, to your point, you're not looking behind. >> Chandar: It's the windshield. >> Exactly, able to be looking forward. So, with all the announcements and the great things that have come out with the AWS expansion, what you guys are doing with Coupa Pay. I was shocked to learn the percentages of businesses that are still writing paper checks. Or, the fact that a lot of companies have 10 plus banks that they're working with. There's still so much manual processes. You must just be, the future is so bright, you got to wear shades with Coupa. But, what excites you about what you guys have announced the last coupe of days and the feedback that you're hearing from your tribe? >> I think there's two kinds of things. One is continue to set the innovation agenda for the industry. And, really, you have to look at every customer on their unique journey of maturity and maturation, so we have a very thoughtful, what we call, maturity index, The business spend management index. Whereas, you are seeing some of these customers, for example, you mentioned, may be in the first stage of this maturity, where, for them, it's just getting automation and going from paper to paperless could be the first step. But, some other customers might say, "I've gotten there, "but I want to get the next level of sophistication "to orchestrate these business spend processes." So, what's exciting for us in the feedback is we're creating product capability across this maturation journey for our customers to make them successful at each of those places. And, Coupa Pay is one example of that. Whereas, some of the other pieces we talked about, we announced about some of the community offerings that we did also is on that. So, that's one exciting piece. The other exciting piece that customers tell us at this conference is, "Foster platforms for us "to engage with each other, learn from each other, "share from each other, and grow with each other." So, even stuff that Rob talked about, which is sourced together. This concept of customers coming together to drive a sourcing process and, again, the collective intelligence in the community, that, we're getting very, very positive feedback from that perspective. And, ultimately, Rob has a really good saying that, "It is not about customer satisfaction. "It is about customer success." That's a delineation there. A customer could be very satisfied with you, but they may not be necessarily successful. And, we say, it's not about satisfaction. It's about success. And, by creating this innovation cycle and then having a post-implementation process that's getting true value, that's truly how we drive customer success. >> And, something that I've heard over and over as I've talked to a number of your customers yesterday and today is how much they're feeling Coupa is listening. Their feedback is being incorporated. They're actually influencing the development of the technology and that was loud and clear the last two days. >> Yeah, I think there is, Rob talked about the number of features that are being influenced by the community and we have these-- >> 300 plus in the last 12 months. >> Yes, 300 plus in the last 12 months. And, there's this concept of two ears, one mouth. And, listen, learn, and innovate and that's the philosophy here. But, it's a right mix of listening to customers, learning from them, and getting the right input from them for driving innovation, as well as having strategic vision on where this market is going and having the right mix of those to provide the capability to customers. >> Wow, you're on a rocket ship. Chandar, it was great to have you on theCUBE. You'll have to come back. >> Yes, Lisa, absolutely, I'll come back and it was a pleasure being here. Awesome. >> Awesome, thank you so much. For Chandar, I'm Lisa Martin and you're watching theCUBE from Coupa Inspire '19. Thanks for watching. (techno music)

>> from the Cosmopolitan Hotel in Las Vegas, Nevada. It's the Cube covering Cooper inspired 2019. >> Brought to You by Cooper. >> Welcome to the Cube from Cooper inspired 99 Lisa Martin in The Cosmopolitan of Las Vegas. And guess who I have with me from the main stage CEO. Rob Bernstein. Welcome to the Cube. >> You so much. Thank you for having me >> exciting start today. One of Inspire really enjoyed the general session this morning. I learned three things more than three, but there's three that really stick out. One. You like pizza >> I do >> to you like kittens and kittens. And three, since 2016 there has been a five X increase and the spend going through the coop a platform with rocket ship. >> That's right. Huge momentum were well over 1.2 trillion dollars and spend that's gone through the platform. It's accelerating, and our customers are getting a lot of value and visualizing that spending, routing it to prefer contract saving money doing in smart, compliant ways. It's a really exciting time for us. >> It is, and this is across every industry manufacturing, healthcare, retail, et cetera. Every industry has the opportunity to leverage this wealth of data absolute. Cooper has to be able to get that visibility and control of all their spent. That's really revolutionary for any business. >> Well, we're really excited about it. Our community of customers is very excited about it, where building something very special here. I'll tell you one of the most exciting things. When you see that data being used in a way that drives intelligence for each individual customers, you know, we're helping them understand Where is their potential fraud with their expenses, where their suppliers maybe sending them duplicate invoices by accident? But Ari, I picks that up. So we are taking the space to a completely new level, and it's it could be more exciting. Honestly, >> well, the amount. You know, we go 1,000,000 shows a year, maybe a little bit less, But we always hear data is oil data is gold. It is. If you have access to it, you can extract insights from it really quickly and be able to act on it faster than your competition. >> Absolutely. You have to be able to normalize the data first informal, so you need a I capabilities. To do that, you have to access a massive data store you have to anonymous. The data obviously needs to be very, very secure, and then you have to draw insights out of that data. And one of things I share this morning is that we've given our customers just in 2019 more than 18,000 prescriptions of things they should consider, for example, putting some suppliers on hold if we think there's some risk with those suppliers. So absolutely, it's a I, but it's a I as the underlying element that brings out what we call community intelligence. And that's what's what's so powerful >> and the community as well, another really kind of under town that I felt and heard this morning from us. It's a community of collaboration, thes air, other businesses benefiting from what others have learned suppliers as well. So the customer centric city, the supplier central city, is there. >> Absolutely. It's all about this community concept, and we have well over 1000 companies that we've helped spend smarter, effectively and their community because these customers air sharing both in person and online, best practices, ideas for doing things differently, ideas for stretching this space beyond where it's ever been before, and that's really rewarding and every individual customers getting the benefit from that. Eso This community is developing very, very nicely, and it's serving the purposes of establishing this category, this new category of businessmen management, that world driving toward >> talk about that because that's something that's pretty innovative for Cooper. Business SPEND MANAGEMENT The role of procurement has changed. The role of finance has changed. They have the opportunity to become very strategic and really drive top line value. Talk to us about business, spend management What it means, how Coop is defining it >> absolutely well. First of all, any person I am in the world, and I've been asked this question for well over a decade. Now, do you think your company is doing a great job in managing its spending on older business needs that the company has, and you never get a resounding positive answer that, yes, we're doing a great job. And if you ask them, are you applying information technology to that problem in an effective way? The the answers or even worse? So we are attacking this full on with our customers in establishing the space, and that means everything from procurement expense reporting to invoice processing, two payments strategic sourcing, spend analytics supplier management contract lifecycle management. All of these application areas working together in concert help companies get their arms around spending and manage it in a much more smart way. And that's what this is. This is all about. >> One of the biggest challenges is you think about poor I t. Because every every line of business, whether your marketing, finance or engineering anything. Oh, engineering. I want to use lock. Start using flack. Marketing wants to use salesforce market Whatever these tools are in, suddenly this proliferation of shadowing T that's right and challenging to manage. But you can imagine how many supplier contracts are being duplicated triplicate, ID and even within the same organization, not getting the ideal price. So one of the great things big announcement today is the expansion of the relationship with Amazon in the AWS marketplace and wow, c I ose I t folks are gonna be able to do >> a lot >> through the Cupid platform. Tell us >> girls, that's right. Well, first of all, it's powered by an open by technology that we've developed, which allows you to have a very seamless experience. It's a purchasing experience that feels just like you're out on the Web, looking for any kind of item that you'd like to buy. But now you'll be able to subscribe to Service Is Cloud based. Service is through the Amazon AWS marketplace, and these Air service is that obviously would be approved by your CEO be approved by the folks involved in checking that it's secure, approved by legal and also approved by procurement So you can procure these cloud based service is very, very seamlessly right out of Cooper into AWS marketplace and back. And we think it's going to allow for obviously more volume of controlled spend, but also visibility into that spends. So it's properly matters >> that visibility is. You know, it's a word that we use in so many different applications. We don't want better visibility in our lives. In general, that is not easy to achieve. You talked about kind of these four core categories. You actually mentioned Maur that Cooper delivers its procurement, its invoices, expenses that can imagine travel management contingent workers getting an organization, whether it's a big organization like a staples or a smaller organization, that visibility is massively game changing. >> Yes, I think so. And I think one of the things that allows us to view that is we've really empowered the central hub organizations. Many the ones you described to roll out platforms to the end users all over the country, all over the world, wherever these people have employees to take control over spend. But have that Spence still routed to preferred, contractually righteous kind of spend categories that give them the results that they want. So this is a platform that is getting wide, wide adoption. And I'll tell you one of our application areas. We've seen more than a three x acceleration in the number of users over the last one year simply because of the adoption is so broadly accepted. And that has to do with our design and technology. Make it very, very usable. Our design concept of the best, you wise. No, you are right. So that's really how we're getting to where we're getting with a customer committee >> Adoptions challenging, you know. And there's if you look at the number of applications that an organization has a gonna work our list of sites, there's a lot and they're only effective if they're being utilized effectively by all of the folks that need to be doing that talk a little bit more. I love how you in your general session this morning shared with the audience. What c o u P a. Each acronym means. But and I saw that on the website best. Do I know you? I know what are some of the things that you think Cooper is doing really well that are really facilitating that adoption. That's again, that's hard to achieve. >> Well, it's in each of the letters in Cooper. So first, a comprehensive approach. That's what the C stands for. So cover every area of spend in one platform. We've never seen that before in the history of enterprise software, about a lot of siloed solutions all over the place, people trying to integrate them. We've put this all on one comprehensive platform. Secondly, doing it openly. That's what the old stands for. So being able to integrate to any ear piece system integrates a whole host of systems you mentioned slack earlier. We integrate into slack you could approve or reject spent purchased directly and slack. You have to get out to Cooper to do it, but you're doing it. The date is captured in Cooper. You is the user centrist city, so putting all the weight on the application itself and less of the weight on the employees themselves. Right now, we support guided buying with support all these capabilities, but our focus is on. You don't need any guidance in the future. Should require in the gun she should be. It should be so intuitive. The P stands for prescriptive, and this is using this community. Data we were discussing earlier to give real prescriptive advice. Teach customer, but how they should be spending or best practices, expenditures or benchmarks of how they could approve in the A stands for accelerated. It's the time of deployment. We're getting our customers live in a matter of months. They're accelerating their business process internally. I shared a stat that our customers in the last 12 months have improved the speed of their approvals by 30%. That's an aggregate. That's millions of millions, hundreds of billions of dollars in spend buying. So these five there is really differentiate us and they're really the vision areas that we focus on is a company with our with our community of customers. >> I was looking at some of the numbers from Cooper. You guys have consistently managed to grow revenues over 40% your rear in your fiscal year. 20 Q one earnings, which was just what last month or so. So revenue up 44% year over. You're crushing Wall Street's estimates by more than a 10 point gap. Lot of moment in, As you mentioned, let's talk about customers because at the end of the day, that's what you're all working towards. I know some of your proudest moments are when you get to talk with customers whose businesses have been transformed and you're giving them that the ah ha moments all the time. I love this morning how there >> was a lot >> of the voice of the customer covered there from so many different industries. The impact that you guys are making it Rolls Royce, for example, and MasterCard massive. Tell me some of your favorite stories that really articulate the breadth and depth of the value that delivers. I >> love it when the story begins in a situation where the CEO or CFO of the company don't necessarily get it, but somebody within our community steps up and shows them the business case of what we could achieve together. And then we, as a team is a collective unit delivered on achieving. Looking at was on themselves. I mean, they're processing more than $2,000,000,000 a month >> through our platform. I >> mentioned Procter Gamble. It process more than $50,000,000,000. Star Platform. Now >> these air, >> not initials. These were early adopter customers. They didn't have to go in our direction. There was some individual in that company that saw the spark of opportunity seized it, got it approved and worked with us hand in hand to drive it. And that's the stories that I love the most. And I shared so many of them this morning, but there are literally hundreds of them. All over the world in this community were cultivated. >> There are, and it's that's I think there's no bread or brand value that you can get Van it being articulated from the voice of a successful customer who it's not just normal, agile. We're saving money. It's no, we're driving shareholder value. There are significant business imperatives that are being driven because procurement is changing. We got to react to pricing pressures and forces like consumer ization. You know, we think of way have these expectations as consumers private lives, of getting anything that we want within a day when it shows up, you forgot what you ordered. It was that fast. That's right, what you guys are doing to enable the business buyers to have that same capability in their business lives. But to get that visibility, that 360 is really interesting. >> And the key also is to handle all the complexity on the back end for them. I could tell you so many companies I know that a really proud of crossing their paper based invoices very, very quickly, but they may not even know whether or not they got the goods of service is for which they're paying the invoice. So we do all of that heavy lifting on the back end on the platform itself, alleviating then users from that complexity and allowing them to have the experience that's similar to the one that that you just described >> can imagine how much money is being wasted on paper. They probably have absolutely no idea, absolutely no idea where you guys launched an Index. The Cooper Business Spend Index Just, I think, a month or two ago this is behavioral based data that you're bleeding from your community. Talk to us about the coupe of business spent index and some of the insights that you're already uncovering about the economy. >> Absolutely so. One of the things about this business spending nexus. It's something I've been thinking about frankly for over a decade. Can we collect enough data that's statistically significant enough actually be a leading indicator to future economic sentiment. You think about the data. We're looking at an aggregate. We know the average spend companies have per employee. We know how long approval cycles are, and we know the changes in those approval cycles. We know what percentage of spend is actually being rejected. Verse accepted at a moments notice aggregated those air in combination are leading in the Kidder's to the sentiment that companies have about the future of the economy. So we backwards tested this index that takes an account, these three elements that just described back to 2016 and it's proven to show pretty strong correlation with the way the economy actually played out for many of those quarters that many of those quarters. So last quarter we released our first verse, our first data set of the business spending. Next. And it showed that future economic economic sentiment for the next 3 to 4 months is actually very positive now, in some industries, more than others. But now, with three months later and clearly, the last three months have been pretty strong. So we're gonna be soon releasing our next quarterly Businessmen index. And we're gonna be doing this every quarter. Try to provide the business community with insights about where things are going. That's what everyone of business wants to know, where things are going, not where things have been. And we think we're in a unique position to share that and also, you know, sort of unfairly build awareness for brand out there so that people understand >> what we're all about. >> But that's that's critical. I'm gonna be talking to China tomorrow. You think of awareness Acquisition? Yes, Yes. Advocacy. Yes. Check, Check. Check. Old three. Those are critical last question robbery. As we look at the impact that procurement and getting this visibility of all of the distances spend can have on the business. Where is it as it relates to enabling businesses to digitally transformed >> to be competitive? Well, look, underlying all of this is the digital transformation that's happening for every company in every industry, without a doubt. But the use cases we support us so quantifiable. That's so clear not only in terms of cost savings that only in terms of compliance only in terms of visibility and getting your arms around spent actually drive revenue as well. If you do spend management effectively, you can change the way consumers experience your brand. And I shared a number of those stories. MGM resorts to Lulu Lemon to the Leukemia and Lymphoma Society and others. If you can get your arms around the spent and get people in the company, the goods and service is they need in record time. They're better position to express the company's vision to help them push towards an incredible iconic customer experiences. And we're just so proud to be ableto power that for this fast growing community of customers around the world, >> such an exciting time. Rob, thank you for having to queue, but inspired 19. It's been great. It's for looking forward to talking with lots more of your of your folks as well as amazing innovators and thinkers like Susie Orman and Deepak Chopra. Wow. Awesome stuff. Thank you. Well, thanks for having us. Thank you. All right. For Rob Bernstein. I'm Lisa Martin. You're watching the Cube from Cooper Inspired 19. Thanks for watching.

>> From Boston, Massachusets, it's The Cube. Covering Actifio 2019: Data Driven, Brought to you by Actifio. >> Welcome back to Boston, everybody. We're here at the Intercontinental Hotel at Actifio's Data Driven conference, day one. You're watching The Cube. The leader in on-the-ground tech coverage. My name is is Dave Valante, Stu Minamin is here, so is John Ferrer, my friend Frank Gens is here, he's the Senior Vice President and Chief Analyst at IDC and Head Dot Connector. Frank, welcome to The Cube. >> Well thank you Dave. >> First time. >> First time. >> Newbie. >> Yep. >> You're going to crush it, I know. >> Be gentle. >> You know, you're awesome, I've watched you over the many years, of course, you know, you seem to get competitive, and it's like who gets the best rating? Frank always had the best ratings at the Directions conference. He's blushing but I could- >> I don't know if that's true but I'll accept it. >> I could never beat him, no matter how hard I tried. But you are a phenomenal speaker, you gave a great conversation this morning. I'm sure you drew a lot from your Directions talk, but every year you lay down this, you know, sort of, mini manifesto. You describe it as, you connect the dots, IDC, thousands of analysts. And it's your job to say okay, what does this all mean? Not in the micro, let's up-level a little bit. So, what's happening? You talked today, You know you gave your version of the wave slides. So, where are we in the waves? We are exiting the experimentation phase, and coming in to a new phase that multiplied innovation. I saw AI on there, block-chain, some other technologies. Where are we today? >> Yeah, well I think having mental models of the6 industry or any complex system is pretty important. I mean I've made a career dumbing-down a complex industry into something simple enough that I can understand, so we've done it again now with what we call the third platform. So, ten years ago seeing the whole raft of new technologies at the time were coming in that would become the foundation for the next thirty years of tech, so, that's an old story now. Cloud, mobile, social, big data, obviously IOT technologies coming in, block-chain, and so forth. So we call this general era the third platform, but we noticed a few years ago, well, we're at the threshold of kind of a major scale-up of innovation in this third platform that's very different from the last ten or twelve years, which we called the experimentation stage. Where people were using this stuff, using the cloud, using mobile, big data, to create cool things, but they were doing it in kind of a isolated way. Kind of the traditional, well I'm going to invent something and I may have a few friends help me, whereas, the promise of the cloud has been , well, if you have a lot of developers out on the cloud, that form a community, an ecosystem, think of GitHub, you know, any of the big code repositories, or the ability to have shared service as often Amazon, Cloud, or IBM, or Google, or Microsoft, the promise is there to actually bring to life what Bill Joy said, you know, in the nineties. Which was no matter how smart you are, most of the smart people in the world work for someone else. So the questions always been, well, how do I tap into all those other smart people who don't work for me? So we can feel that where we are in the industry right now is the business model of multiplied innovation or if you prefer, a network of collaborative innovation, being able to build something interesting quickly, using a lot of innovation from other people, and then adding your special sauce. But that's going to take the scale of innovation just up a couple of orders of magnitude. And the pace, of course, that goes with that, is people are innovating much more rapid clip now. So really, the full promise of a cloud-native innovation model, so we kind of feel like we're right here, which means there's lots of big changes around the technologies, around kind of the world of developers and apps, AI is changing, and of course, the industry structure itself. You know the power positions, you know, a lot of vendors have spent a lot of energy trying to protect the power positions of the last thirty years. >> Yeah so we're getting into some of that. So, but you know, everybody talks about digital transformation, and they kind of roll their eyes, like it's a big buzzword, but it's real. It's dataware at a data-driven conference. And data, you know, being at the heart of businesses means that you're seeing businesses transition industries, or traverse industries, you know, Amazon getting into groceries, Apple getting into content, Amazon as well, etcetera, etcetera, etcetera, so, my question is, what's a tech company? I mean, you know, Bennyhoff says that, you know, every company's a sass company, and you're certainly seeing that, and it's got to be great for your business. >> Yeah, yeah absolutely >> Quantifying all those markets, but I mean, the market that you quantify is just it's every company now. Banks, insurance companies, grocers, you know? Everybody is a tech company. >> I think, yeah, that's a hundred percent right. It is that this is the biggest revolution in the economy, you know, for many many decades. Or you might say centuries even. Is yeah, whoever put it, was it Mark Andreson or whoever used to talk about software leading the world, we're in the middle of that. Only, software now is being delivered in the form of digital or cloud services so, you know, every company is a tech company. And of course it really raises the question, well what are tech companies? You know, they need to kind of think back about where does our value add? But it is great. It's when we look at the world of clouds, one of the first things we observed in 2007, 2008 was, well, clouds wasn't just about S3 storage clouds, or salesforce.com's softwares and service. It's a model that can be applied to any industry, any company, any offering. And of course we've seen all these startups whether it's Uber or Netflix or whoever it is, basically digital innovation in every single industry, transforming that industry. So, to me that's the exciting part is if that model of transforming industries through the use of software, through digital technology. In that kind of experimentation stage it was mainly a startup story. All those unicorns. To me the multiplied innovation chapter, it's about- (audio cuts out) finally, you know, the cities, the Procter & Gambles, the Walmarts, the John Deere's, they're finally saying hey, this cloud platform and digital innovation, if we can do that in our industry. >> Yeah, so intrapreneurship is actually, you know, starting to- >> Yeah. >> So you and I have seen a lot of psychos, we watched the you know, the mainframe wave get crushed by the micro-processor based revolution, IDC at the time spent a lot of time looking at that. >> Vacuum tubes. >> Water coolant is back. So but the industry has marched to the cadence of Moore's Law forever. Even Thomas Friedman when he talks about, you know, his stuff and he throws in Moore's Law. But no longer Moore's Law the sort of engine of innovation. There's other factors. So what's the innovation cocktail looking forward over the next ten years? You've talked about cloud, you know, we've talked about AI, what's that, you know, sandwich, the innovation sandwich look like? >> Yeah so to me I think it is the harnessing of all this flood of technologies, again, that are mainly coming off the cloud, and that parade is not stopping. Quantum, you know, lots of other technologies are coming down the pipe. But to me, you know, it is the mixture of number one the cloud, public cloud stacks being able to travel anywhere in the world. So take the cloud on the road. So it's even, I would say, not even just scale, I think of, that's almost like a mount of compute power. Which could happen inside multiple hyperscale data centers. I'm also thinking about scale in terms of the horizontal. >> Bringing that model anywhere. >> Take me out to the edge. >> Wherever your data lives. >> Take me to a Carnival cruise ship, you know, take me to, you know, an apple-powered autonomous car, or take me to a hospital or a retail store. So the public cloud stacks where all the innovation is basically happening in the industry. Jail-breaking that out so it can come, you know it's through Amazon, AWS Outpost, or Ajerstack, or Google Anthos, this movement of the cloud guys, to say we'll take public cloud innovation wherever you need it. That to me is a big part of the cocktail because that's you know, basically the public clouds have been the epicenter of most tech innovation the last three or four years, so, that's very important. I think, you know just quickly, the other piece of the puzzle is the revolution that's happening in the modularity of apps. So the micro services revolution. So, the building of new apps and the refactoring of old apps using containers, using servos technologies, you know, API lifecycle management technologies, and of course, agile development methods. Kind of getting to this kind of iterative sped up deployment model, where people might've deployed new code four times a year, they're now deploying it four times a minute. >> Yeah right. >> So to me that's- and kind of aligned with that is what I was mentioning before, that if you can apply that, kind of, rapid scale, massive volume innovation model and bring others into the party, so now you're part of a cloud-connected community of innovators. And again, that could be around a Github, or could be around a Google or Amazon, or it could be around, you know, Walmart. In a retail world. Or an Amazon in retail. Or it could be around a Proctor & Gamble, or around a Disney, digital entertainment, you know, where they're creating ecosystems of innovators, and so to me, bringing people, you know, so it's not just these technologies that enable rapid, high-volume modular innovation, but it's saying okay now plugging lots of people's brains together is just going to, I think that, here's the- >> And all the data that throws off obviously. >> Throws a ton of data, but, to me the number we use it kind of is the punchline for, well where does multiplied innovation lead? A distributed cloud, this revolution in distributing modular massive scale development, that we think the next five years, we'll see as many new apps developed and deploye6d as we saw developed and deployed in the last forty years. So five years, the next five years, versus the last forty years, and so to me that's, that is the revolution. Because, you know, when that happens that means we're going to start seeing that long tail of used cases that people could never get to, you know, all the highly verticalized used cases are going to be filled, you know we're going to finally a lot of white space has been white for decades, is going to start getting a lot of cool colors and a lot of solutions delivered to them. >> Let's talk about some of the macro stuff, I don't know the exact numbers, but it's probably three trillion, maybe it's four trillion now, big market. You talked today about the market's going two x GDP. >> Yeah. >> For the tech market, that is. Why is it that the tech market is able to grow at a rate faster than GDP? And is there a relationship between GDP and tech growth? >> Yeah, well, I think, we are still, while, you know, we've been in tech, talk about those apps developed the last forty years, we've both been there, so- >> And that includes the iPhone apps, too, so that's actually a pretty impressive number when you think about the last ten years being included in that number. >> Absolutely, but if you think about it, we are still kind of teenagers when you think about that Andreson idea of software eating the world. You know, we're just kind of on the early appetizer, you know, the sorbet is coming to clear our palates before we go to the next course. But we're not even close to the main course. And so I think when you look at the kind of, the percentage of companies and industry process that is digital, that has been highly digitized. We're still early days, so to me, I think that's why. That the kind of the steady state of how much of an industry is kind of process and data flow is based on software. I'll just make up a number, you know, we may be a third of the way to whatever the steady state is. We've got two-thirds of the way to go. So to me, that supports growth of IT investment rising at double the rate of overall. Because it's sucking in and absorbing and transforming big pieces of the existing economy, >> So given the size of the market, given that all companies are tech companies. What are your thoughts on the narrative right now? You're hearing a lot of pressure from, you know, public policy to break up big tech. And we saw, you know you and I were there when Microsoft, and I would argue, they were, you know, breaking the law. Okay, the Department of Justice did the right thing, and they put handcuffs on them. >> Yeah. >> But they never really, you know, went after the whole breakup scenario, and you hear a lot of that, a lot of the vitriol. Do you think that makes sense? To break up big tech and what would the result be? >> You don't think I'm going to step on those land mines, do you? >> Okay well I've got an opinion. >> Alright I'll give you mine then. Alright, since- >> I mean, I'll lay it out there, I just think if you break up big tech the little techs are going to get bigger. It's going to be like AT&T all over again. The other thing I would add is if you want to go after China for, you know, IP theft, okay fine, but why would you attack the AI leaders? Now, if they're breaking the law, that should not be allowed. I'm not for you know, monopolistic, you know, illegal behavior. What are your thoughts? >> Alright, you've convinced me to answer this question. >> We're having a conversation- >> Nothing like a little competitive juice going. You're totally wrong. >> Lay it out for me. >> No, I think, but this has been a recurring pattern, as you were saying, it even goes back further to you know, AT&T and people wanting to connect other people to the chiraphone, and it goes IBM mainframes, opening up to peripherals. Right, it goes back to it. Exactly. It goes back to the wheel. But it's yeah, to me it's a valid question to ask. And I think, you know, part of the story I was telling, that multiplied innovation story, and Bill Joy, Joy's Law is really about platform. Right? And so when you get aggregated portfolio of technical capabilities that allow innovation to happen. Right, so the great thing is, you know, you typically see concentration, consolidation around those platforms. But of course they give life to a lot of competition and growth on top of them. So that to me is the, that's the conundrum, because if you attack the platform, you may send us back into this kind of disaggregated, less creative- so that's the art, is to take the scalpel and figure out well, where are the appropriate boundaries for, you know, putting those walls, where if you're in this part of the industry, you can't be in this. So, to me I think one, at least reasonable way to think about it is, so for example, if you are a major cloud platform player, right, you're providing all of the AI services, the cloud services, the compute services, the block-chain services, that a lot of the sass world is using. That, somebody could argue, well, if you get too strong in the sass world, you then could be in a position to give yourself favorable position from the platform. Because everyone in the sass world is depending on the platform. So somebody might say you can't be in. You know, if you're in the sass position you'll have to separate that from the platform business. But I think to me, so that's a logical way to do it, but I think you also have to ask, well, are people actually abusing? Right, so I- >> I think it's a really good question. >> I don't think it's fair to just say well, theoretically it could be abused. If the abuse is not happening, I don't think you, it's appropriate to prophylactically, it's like go after a crime before it's committed. So I think, the other thing that is happening is, often these monopolies or power positions have been about economic power, pricing power, I think there's another dynamic happening because consumer date, people's data, the Facebook phenomenon, the Twitter and the rest, there's a lot of stuff that's not necessarily about pricing, but that's about kind of social norms and privacy that I think are at work and that we haven't really seen as big a factor, I mean obviously we've had privacy regulation is Europe with GDPR and the rest, obviously in check, but part of that's because of the social platforms, so that's another vector that is coming in. >> Well, you would like to see the government actually say okay, this is the framework, or this is what we think the law should be. I mean, part of it is okay, Facebook they have incentive to appropriate our data and they get, okay, and maybe they're not taking enough responsibility for. But I to date have not seen the evidence as we did with, you know, Microsoft wiping out, you know, Lotus, and Novel, and Word Perfect through bundling and what it did to Netscape with bundling the browser and the price practices that- I don't see that, today, maybe I'm just missing it, but- >> Yeah I think that's going to be all around, you know, online advertising, and all that, to me that's kind of the market- >> Yeah, so Google, some of the Google stuff, that's probably legit, and that's fine, they should stop that. >> But to me the bigger issue is more around privacy.6 You know, it's a social norm, it's societal, it's not an economic factor I think around Facebook and the social platforms, and I think, I don't know what the right answer is, but I think certainly government it's legitimate for those questions to be asked. >> Well maybe GDPR becomes that framework, so, they're trying to give us the hook but, I'm having too much fun. So we're going to- I don't know how closely you follow Facebook, I mean they're obviously big tech, so Facebook has this whole crypto-play, seems like they're using it for driving an ecosystem and making money. As opposed to dealing with the privacy issue. I'd like to see more on the latter than the former, perhaps, but, any thoughts on Facebook and what's going on there with their crypto-play? >> Yeah I don't study them all that much so, I am fascinated when Mark Zuckerberg was saying well now our key business now is about privacy, which I find interesting. It doesn't feel that way necessarily, as a consumer and an observer, but- >> Well you're on Facebook, I'm on Facebook, >> Yeah yeah. >> Okay so how about big IPOs, we're in the tenth year now of this huge, you know, tail-wind for tech. Obviously you have guys like Uber, Lyft going IPO,6 losing tons of money. Stocks actually haven't done that well which is kind of interesting. You saw Zoom, you know, go public, doing very well. Slack is about to go public. So there's really a rush to IPO. Your thoughts on that? Is this sustainable? Or are we kind of coming to the end here? >> Yeah so, I think in part, you know, predicting the stock market waves is a very tough thing to do, but I think one kind of secular trend is going to be relevant for these tech IPOs is what I was mentioning earlier, is that we've now had a ten, twelve year run of basically startups coming in and reinventing industries while the incumbents in the industries are basically sitting on their hands, or sleeping. So to me the next ten years, those startups are going to, not that, I mean we've seen that large companies waking up doesn't necessarily always lead to success but it feels to me like it's going to be a more competitive environment for all those startups Because the incumbents, not all of them, and maybe not even most of them, but some decent portion of them are going to wind up becoming digital giants in their own industry. So to me I think that's a different world the next ten years than the last ten. I do think one important thing, and I think around acquisitions MNA, and we saw it just the last few weeks with Google Looker and we saw Tab Low with Salesforce, is if that, the mega-cloud world of Microsoft, Ajer, and Amazon, Google. That world is clearly consolidating. There's room for three or four global players and that game is almost over. But there's another power position on top of that, which is around where did all the app, business app guys, all the suite guys, SAP, Oracle, Salesforce, Adobe, Microsoft, you name it. Where did they go? And so we see, we think- >> Service Now, now kind of getting big. >> Absolutely, so we're entering a intensive period, and I think again, the Tab Low and Looker is just an example where those companies are all stepping on the gas to become better platforms. So apps as platforms, or app portfolio as platforms, so, much more of a data play, analytics play, buying other pieces of the app portfolio, that they may not have. And basically scaling up to become the business process platforms and ecosystems there. So I think we are just at the beginning of that, so look for a lot of sass companies. >> And I wonder if Amazon could become a platform for developers to actually disrupt those traditional sass guys. It's not obvious to me how those guys get disrupted, and I'm thinking, everybody says oh is Amazon going to get into the app space? Maybe some day if they happen to do a cam expans6ion, But it seems to me that they become a platform fo6r new apps you know, your apps explosion.6 At the edge, obviously, you know, local. >> Well there's no question. I think those appcentric apps is what I'd call that competition up there and versus kind of a mega cloud. There's no question the mega cloud guys. They've already started launching like call center, contact center software, they're creeping up into that world of business apps so I don't think they're going to stop and so I think that that is a reasonable place to look is will they just start trying to create and effect suites and platforms around sass of their own. >> Startups, ecosystems like you were saying. Alright, I got to give you some rapid fire questions here, so, when do you think, or do you think, no, I'm going to say when you think, that owning and driving your own car will become the exception, rather than the norm? Buy into the autonomous vehicles hype? Or- >> I think, to me, that's a ten-year type of horizon. >> Okay, ten plus, alright. When will machines be able to make better diagnosis than than doctors? >> Well, you could argue that in some fields we're almost there, or we're there. So it's all about the scope of issue, right? So if it's reading a radiology, you know, film or image, to look for something right there, we're almost there. But for complex cancers or whatever that's going to take- >> One more dot connecting question. >> Yeah yeah. >> So do you think large retail stores will essentially disappear? >> Oh boy that's a- they certainly won't disappear, but I think they can so witness Apple and Amazon even trying to come in, so it feels that the mix is certainly shifting, right? So it feels to me that the model of retail presence, I think that will still be important. Touch, feel, look, socialize. But it feels like the days of, you know, ten thousand or five thousand store chains, it feels like that's declining in a big way. >> How about big banks? You think they'll lose control of the payment systems? >> I think they're already starting to, yeah, so, I would say that is, and they're trying to get in to compete, so I think that is on its way, no question. I think that horse is out of the barn. >> So cloud, AI, new apps, new innovation cocktails, software eating the world, everybody is a tech company. Frank Gens, great to have you. >> Dave, always great to see you. >> Alright, keep it right there buddy. You're watching The Cube, from Actifio: Data Driven nineteen. We'll be right back right after this short break. (bouncy electronic music)

so two points max first off ideas aren't worth a damn ever he's got ideas all right I could give a holy hoot about about ideas I mean I I I got people throw ideas at me all the friggin time you know I don't give a shit I just truly told give a shit right I want actions show me how I'm gonna turn something into an action how am I gonna make something better right and I I want to know ahead of time what that something is am I trying to improve customer attention trying to improve recovery time for an athlete who's got back-to-back games right III I know what I'm trying to do and I want to focus on that where ideas become great and you said it really well max is ideas are something I want to test so but I know what I want to test these of the event what outcome I'm trying to drive so it isn't just it is an ideation for the I eat for the sake of ideation its ideation around the idea that I need to drive an outcome I need to have athletes that are better prepare for the next game who can recover faster who are stronger and can you know it can play through a longer point of the season here we are in March Madness and we know that by the way that the teams that tend to rise to the top are the teams that have gone through a more rigorous schedule played tougher teams right they're better prepared for this and it's really hard for a mid-major team to get better prepared because they're playing a bunch of lollipop teams in their own conference so it's it's ideas really don't excite me ideation does around an environment that allows me to test ideas quickly fail fast in order to find those you know variables or metrics those data sources it just might be better predictors of performance yeah I like the idea of acting quickly failing quickly and learning quickly right you have this loop and what happens is and then I think every strand coach in the world is probably guilty of this is we get an idea and we just apply it you go home you know I think eccentric trainings this great idea and we're going to do an eccentric training block and I just apply it to my athletes and you don't know what the hell happened because you don't have any contextual metrics that you base your test on to actually learn from so you at the day go I think it worked you know they jump high but you're not comparing that to anything right they jump they've been the weight room for three months my god I hope they jump higher I hope they're stronger like I can sit in the weight room probably get stronger for three months and my thought is but let's have context and it's um I call them anchor data points they were always reflecting back on so for example if I have a key performance metric where I want to jump high I'll always track jumping high but then I can apply different interventions eccentric training power training strength training and I can see the stress response of these KPIs so now I've set an environment that we have our charter still there my charter being I'm going to improve my athletic development and that's my goal I'm basing that charter on the KPI of jumping high so key performance indicator of jumping high now I can apply different blocks and interventions with that anchor point over and over again and the example I give is I don't come home and ask my girlfriend how she's doing once every month I ask her every day and that's my anchor point right and I might try different things I might try cookie and I might try making dinner I might do the dishes I might stop forgetting our dates I might actually buy groceries for once well maybe she gets happier then I'll continue to buy groceries maybe I'll remember it's her birthday March 30th I remember that that's my put it on there right and so but the idea is we have in life the way life works we have these modular points where we call anchor points where we were self-reflect and we reflect off of others and we understand our progress in our own life environment based on these anchor points and we progress and we apply different interventions I want this job maybe I'll try having this idea outside of here maybe I'll play in a softball league and we're always reflecting it's not making me happier is that making me feel fulfilled and I don't understand why we don't take what we do every day and like subconsciously and apply it into the sports science world but lava is because it happens unconsciously because that's how our body has learned to evolve we have anchor points I want to survive I want to have kids lots of kids strong kids and I and I die so my kids can have my food and that's what we want as a body right your bison care about anything else and so that's why you walk with a limp after you get hurt you don't want perfect again it's a waste of energy to walk perfect right you can still have kids with a limp I hate to break it to you right we're not running from animals anymore and so we have all these anchor points in life let's apply that same model now and like you said it's like design thinking and actually having that architecture to outline it whether it's in that hypothesis canvas to force us to now consciously do it because we're not just interacting with ourselves now we're interacting with other systems other nodes of information to now have to work together in use in to achieve our company's charter interesting max there's a lot of a lot of key points in there the one that strikes me is measurement John Smail at Procter & Gamble I was there you still I say you are what you measure and you measure what you reward that was his way of saying as an organization that the compensation systems are critical and the story just walked through about what Kelsey right and what you guys are doing and how you increase your your happiness level right now here's the damnest your work I mean that is that is how you're rewarded right if you are rewarded by happiness and so you you learn to measure if you're smart right that you don't miss birthdays that you do dishes you you you help up around the house you do things and when you do those things the happiness meter goes up and when you don't do those things happiness meter goes down and you know because you're you're you're probably pulling not just once a day but as you walk by her throughout the day are on a weekend you're you're constantly knowing right if if you're liking your mom you know when mom's not happy you don't need to be a day to sign this and know mom's not happy and so then you you know you re engineer about okay what did I do wrong that causes unhappiness right and so life is a lot of there's a lot of life lessons that we can learn that we can apply to either our business our operations or sports whatever it might be that your your profession is in about the importance of capturing the right metrics and understanding how those metrics really drive you towards a desired outcome and the rewards you're gonna receive from those outcomes yeah and with those it's the right metrics right that's what not metrics the right metrics if I want to know if someone was happy I wouldn't go look at the weather I wouldn't you know check gas prices especially if I'm curious they're happy with me well maybe they might reflect if they're happy in general if they're happy with me right now I'm contextualizing I'm actually trying to look at I know a little bit more about what I should look at I don't know everything and so you might have metrics that you say you know I know science says this metric is good this metric is good maybe we want to explore of these couple of metrics over here because we think that either aid they're related to one of these metrics or they related to the main outcome itself and that gives you a way to then I have these key and core metrics that's not stacking the deck but it's no one you're gonna get insights out of it and then I have these exploratory metrics over here but you're gonna allow me then to dive and explore elsewhere and if you're a company those can be trade secrets they can be proprietary information if you're a trainer it can be ways to learn how different athletes adapt to make yourself better and again we're talking about a company and we're talking about trainer there's no difference when it comes to trade secrets right trainers keep their trade secrets and companies keep their trade secrets and as we talk about this it's really easy to see how these two environments where they're talking about company athletic development sports science personal training health and wellness are really universally governed by the same concepts because life itself is typically governed by these concepts and when we're playing those kind of home iterations to it you can really begin to quickly learn what's going on and whether or not those metrics that you we're good ARCA and whether or not you can learn new metrics and from that max you raise an interesting question or made a point here that's I might be very different in the sports world than it is in the business world and that is the ability to test and what I mean by that is you know the business world is full of concepts like a bee testing and see both custody and simulations and things like that when you're dealing with athletes individually I would imagine it's really hard to test athlete a with one technique and athlete B with another technique when both these athletes are trying to maximize their performance capabilities in order to maximize you know the money there can they can they can generate how do you deal with that so yes no one wants to get the shitty program yes that's correct yeah for the most part people don't and this I'll take people don't test like that and but here's my solution to us I think being a critic without solutions called being an asshole my solution to that is making it very agile and so we're not going to be able to you know test group a versus group B but what you can do if you're a coach and you have faith in because there are a lot of programs coaches use coaches probably use you know every offseason they might try a new program so there's no real difference in all honesty to try a new program on you know these seven athletes versus and then try a different one that you also trust on these seven athletes and part of that comes from the fact that we have science and evidence to show that both these programs are really good right but there's no one's actually broken down the minutiae of it and so yes you probably could do a and B testing because you have faith in both programs so it's not like either athletes getting the wrong program they're both getting programs that are going to probably elicit an outcome of performing better but who wants to perform the best the second asks the second aspect would be what kind of longitudinal data that you can collect very easily to understand typical progression of athletes for example if you coach and you coach for eight years you'll have you know eight different freshman classes theoretically and you'll begin to understand how a freshman typically progresses to a sophomore in what their key performance indicators typically trend ass and so you can now say okay last year we did this this year we do this I'm gonna see if my freshman class responds differently is this going to give us the perfect answer absolutely not no but without data you're just another person with an opinion that's not my quote I stole that quote but it's true because if we don't try and audit ourselves and try to understand the process of how is someone developing then we're just strictly relying on confirmation bias I mean my program was great you know Pat some guys in the back that jumped higher and we did awesome if we're truly into understanding what's best then we'll actually try and you know measure some of these progress some of this some of these KPIs over time in the example I give and it's unfortunate and fortunate I don't mean anything bad by this either we're on a salary right and so what happens when you're on a salary is no matter really what happens assuming you're doing your job you're gonna keep your job but if you look at a start-up a startup has one option and that's to make money or go out of business right they don't really have the luxury of oh we're just gonna you know hang out and not saying coaches hang up or not we're just gonna you know keep this path we're going on as a coach you know how do I apply a similar model well I start up the bank my startup is you can go from worth zero dollars to worth a hundred you know million two billion dollars in one year at the coach we don't have that same environment because we're not producing something tangible which doesn't always it doesn't have the same capitalistic Drive right the invisible hand pushing us the same way the free market does with you know devices and so we don't always follow the same path that these startups have done yet that same path and same model might provide better insights so max you've hit something I found very interesting confirmation bias if if you don't take the time before you execute a test understand the variables that you're gonna test what happens is if you after the test is over you go back and try to triage what the drivers were that impact and confirmation bias and revisionist history and all these other things that make humans really poor decision-makers get in the way and so but before as a coach I would imagine before as a coach what you'd want to do is is set up ahead of time we're gonna test the following things to see if they have impact by thoroughly like the hypothesis development canvas right they'll really understand against what you're really going to test and then when you've done that test you you will you would have much more confidence in the results of that test versus trying to say wow Jimmy Jimmy jumped two inches higher this year thank God what did he do let's figure out and revision it wasn't what he ate was it where he slept oh he played a lot of video games that must be it he is the video games made him jump higher right so it's I think a lot of sports in particular even more than the business for a lot of sports is based on on heuristics and gut feel it's run by a priesthood of former athletes who are were great because of their own skills and capabilities and it maybe had very little do with her development and I don't want to pick on Michael Jordan but no Michael Jordan was notoriously a poor coach and a poor judge of talent he made some of the most industries when the worst draft choices industry has ever seen and that's because he mistakenly thought that everybody was like him that he revision history about well what made me great were the following thing so I'm gonna look for people like that instead of reversing the course and saying okay let's figure out ahead of time what makes what will make you a better plant player and then trying these tests across a number of different players to figure out okay which of these things actually had impact so sports I think has gotten much better Moneyball sort of opened that people's eyes to it now we're seeing now more and more team who are realizing that that data science is as a discipline it's not something you apply after the fact but in order to really uncover what's the real drivers of performance you have to sit down before you do the test to really understand what it is you're testing because then you can learn from the tests and and let's be honest right learning is a process of exploring and failing and if you don't try and fail enough times if you don't have enough might moments you'll never have any break to a moment and I think what people don't understand is they hear the word fail and assumed oh we did a six-month program and failed nope failure can occur in one day and that's okay right you can use for example I'm going to use this piece of technology as motivation for biofeedback to increase my athletes and tint and the amount of effort they put into the weight room that's right hypothesis you can test that in one day you print out that piece of technology the athletes don't respond well you'd have learned something now okay that technology didn't bring about the motivation I thought why was that you can do reflect and that revision because you had the infrastructure beforehand on maybe notes that you may have taken and scribbled down on your pad or observations from the coaches I am I but you know what the athletes weren't very invested because the technology took too long to set up right it wasn't the technology's fault it was the process of given technology available to act and utilize on so maybe you retest again with it set up beforehand or a piece of technology that's much easier to use and the intent increases so now you say okay it's not the technology's fault it's the application of how we're using the technology at the same time we hear a lot of things like I'm gonna take a little bit of pivot not too far though is in the baseball world you see technology being more used more and more as a tool and it's helping guide immediate actions on the field whether it's not it's a you know spin rates its arm velocities with accelerometers or some sort of measurement they decide to use but that's not necessarily collecting data that's using technology as a performance tool and I think there's a distinction between the two the two are not mutually exclusive you can still use it as a performance tool but that performance data if the infrastructure is not there to store a file and reflect and analyze it's only being used one-sided and so people think oh we're doing sports science we're doing data science because we're collecting data well that's not I can go count ants that's collecting data but that's not you know I don't unless I count ants every day and say oh my game populations decreasing right and kind of a here's a really easy way to think of it in my opinion you have cookies in the fridge right and every day I go and every week will say my mom makes cookies this doesn't happen I wish it did be very cool but I love your mom and we didn't eat cookies every week but in the fridge I go when I count how many cookies there were right and using data I'd say oh twelve cookies if there's any cookies at all I can eat right that's using technology and that moment but doing data Sciences well you know what she's gonna make you know twelve and a couple of days and I have two days left and there's six cookies I can eat three today and three tomorrow because now you're doing prescriptive analytics right because you are prescribing an action based on the information you collected it's based on historical data because you know that every seventh day the cookies are coming no I just take it as I'm using technology as a tool I might only eat one cookie and forever be leaving six cookies on the table right and so there's hid don't want to do that no we don't but we trick ourselves I think we see that not saying baseball does is but I'm saying we've see that in all domains where we use technology we say oh technology good we had someone use technology that's data science no that's not data science that's using technology to help Tripp augment training using data Sciences understand the information that happened during the training process looking at it contextually to them prescribed saying I'm going to do this exercise or this exercise based on the collection and maturation of the information so instead of cookies here I eat one cookie it's a historic Lee I know there's going to be twelve cookies every seven days I have two days left I can eat three cookies now I can hide two and tell my sister Amelia oh there's only one left very weird I don't know who ate data - well let max let me let me let me wrap up with a very interesting challenge that I think all all data scientists face wellmaybe all citizens of data science face and I say did as citizens of data science I mean people who understand how to use the results of data science not necessarily people who are creating the data science and here's here's the challenge that if you if you make your decisions just based on the numbers alone you're likely to end up with suboptimal results and the reason why that happens is because there's lots of outside variables that have huge influence especially when it comes to humans and even machines to a certain extent let me give you an example know baseball is is infatuated with cyber metrics and numbers right everybody is making decisions we're seeing this now in the current offseason you know who was signing contracts and who has given given money and they're using they're using the numbers to show you know how much is that person really worth and and organizations are getting really surgical and their ability to figure out that that person is not worth a you know a six year contract for you know 84 million dollars they're worth a two-year contract for 36 and that's the best way I'm gonna you know pay but minimize my risks and so then the numbers are really drive and allow that but it isn't just the big data that helps to make decisions and in fact I would argue the insights carried from the small data is equally important especially in sports and I think this is a challenge in other parts of the business is the numbers itself the data itself doesn't tell the full story and in particular think about how does an organization leverage the small data the observed data to really help make a better decision so right now in baseball for example in this offseason the teams became infatuated with using numbers to figure out who were they going to offer contracts to how much they were going to pay him for how long and we saw really the contracts in most cases really shrinking and value in size cuz people are using the numbers and comparing that to say always so and so it only got this you're only going to get this and numbers are great but they miss some of the smaller aspects that really differentiate good athletes from great athletes and those are things like fortitude part you know effort resilience these these kind of things that aren't you can't find that in the number so somebody's ability to a closer write who goes out there in the eighth-inning and and just has a shit performance gets beat up all over the place comes back in it still has to lead and and does that person have the guts the fortitude to go back out there after us bad eighth-inning and go do it again who can fight through when they're tired it's late in the game now you've been playing it's a you know 48 minute game you've been playing forty minutes already you've hardly had a break and you're down by two the balls in your hand a three-pointer is gonna win it what are you gonna do my numbers don't measure that it's theirs these these these other metrics out there like fortitude at heart and such that you actually can start to measure they don't show up a numbers where they come from the inside some subject matter experts to say yeah that person has fight and in fact there's one pro team that actually what they do in the minor leagues they actually put their players into situations that are almost no win because they want to see what they're gonna do do they give up or do they fight back and and you know what you again you can't batting average then tell you that if somebody's gonna get up and that you're gonna give up it's a ninth in and you think you've lost you know what I don't want that person out there and so think about in sports how do you complement the data that you can see coming off of devices with the data that experience coach can say that that person's got something extra there they got the fight they have the fortitude they have the resilience when they're down they keep battling they don't give up and you know from experience from from playing and coaching I know from playing and coaching the guy is going to give up you know who they are I don't want them on the court right it made me the best player from a numbers perspective hell if that was the case Carmelo Anthony would be an all-star every time his numbers are always great the guide lacks heart but he doesn't know how to win so think about how as an organization a sporting organization you use the metrics to help give you a baseline but don't forget about the the soft metrics the servable things that you got to tell you that somebody has something special that is an awesome way to bring this together because subject matter experts those are people who have been in the trenches who see it firsthand date is here to augment you in your decisions it's not here to override you it's not here to take your place and so in coaches fear data it's the silliest thing ever because it's giving more ammo to a gunslinger that's all it does right it's not going to win the battle right it's just the bullets you got to still aim it in fire and so when we look at it in regards to performance and athletic development all these numbers they'll never be right ever they'll never be 100% perfect but neither will you and so what we're trying to do is help your decisions with more information that you can process into your brain that you might otherwise not be able to quantify so it's giving that paintbrush not just the color red but given all the colors to you and so now you can make whatever painting you want and you're not constrained by things you can't measure yourself I could add one point max to bill on that data won't make a shitty coach good but it will make a good coach great yeah yeah I couldn't agree more well dad thank you for being on here I really appreciate and for everyone who's listening this is going on prime March Madness time and so to pull away the dean of big data from March Madness who for people listening he made his bracket on the Google cloud using AI and so it only he so I was thanking him to come here and only he would be the one to I guess take I don't say take the fun out of it but try and grid the family bracket for used it all augmented decision-making he possibly can like it the data will make won't make somebody shitty good and I'm still not good Google Cloud couldn't help me I still at the bottom of the family pool it's great to have you in I guess every minute here is worth double being that's March Madness time thanks max for the opportunity it's a fun conversation alright thank you guys for listening really appreciate it and [Music] [Applause] [Music] you

produced from the cube studios this is strong by science in-depth conversations about science based training sports performance and all things health and wellness here's your host max smart [Music] [Applause] [Music] all right thank you guys tune in today I have the one and only Dean of big data the man the myth the legend bill Schwarz oh also my dad is the CTO of Hitachi van Tara and IOC in analytics he has a very interesting background because he is the well he's known as the Dean of big data but also the king of the court and all things basketball related when it comes to our household and unlike most people in the data world and I want to say most as an umbrella term but a some big bill has an illustrious sports career playing at Coe College the Harvard of the Midwest my alma mater as well but I think having that background of not just being computer science but where you have multiple disciplines involved when it comes to your jazz career you had basketball career you have obviously the career Iran now all that plays a huge role in being able to interpret and take multiple domains and put it into one so thank you for being here dad yeah thanks max that's a great introduction I rep reciate that no it's it's wonderful to have you and for our listeners who are not aware bill is referring him is Bill like my dad but I call my dad the whole time is gonna drive me crazy bill has a mind that thinks not like most so he he sees things he thinks about it not just in terms of the single I guess trajectory that could be taken but the multiple domains that can go so both vertically and horizontally and when we talk about data data is something so commonly brought up in sports so commonly drop in performance and athletic development big data is probably one of the biggest guess catchphrases or hot words or sayings that people have nowadays but doesn't always have a lot of meaning to it because a lot of times we get the word big data and then we don't have action out of big data and bill specialty is not just big data but it's giving action out of big data with that going forward I think a lot of this talk to be talking about how to utilize Big Data how do you guys data in general how to organize it how to put yourself in a situation to get actionable insights and so just to start it off Becky talked a little bit on your background some of the things you've done and how you develop the insights that you have thanks max I have kind of a very nos a deep background but I've been doing data analytics a long time and I was very fortunate one of those you know Forrest Gump moments in life where in the late 1980s I was involved in a project at Procter & Gamble I ran the project where we brought in Walmart's point of sales data for the first time into a what we would now call a data warehouse and for many of this became the launching point of the data warehouse bi marketplace and we can trace the effect the origins of many of the BI players to that project at Procter & Gamble in 87 and 88 and I spent a big chunk of my life just a big believer in business intelligence and data warehousing and trying to amass data together and trying to use that data to report on what's going on and writing insights and I did that for 20 25 years of my life until as you probably remember max I was recruited out Business Objects where I was the vice president of analytic applications I was recruited out of there by Yahoo and Yahoo had a very interesting problem which is they needed to build analytics for their advertisers to help those advertisers to optimize or spend across the Yahoo ad network and what I learned there in fact what I unlearned there was that everything that I had learned about bi and data warehouse and how you constructed data warehouses how you were so schema centric how everything was evolved around tabular data at Yahoo there was an entirely different approach the of my first introduction to Hadoop and the concept of a data Lake that was my first real introduction into data science and how to do predictive analytics and prescriptive analytics and in fact it was it was such a huge change for me that I was I was asked to come back to the TD WI data world Institute right was teaching for many years and I was asked to do a keynote after being at Yahoo for a year or so to share sort of what were the observations what did I learn and I remember I stood up there in front of about 600 people and I started my presentation by saying everything I've taught you the past 20 years is wrong and it was well I didn't get invited back for 10 years so that probably tells you something but it was really about unlearning a lot about what I had learned before and probably max one of the things that was most one of the aha moments for me was bi was very focused on understanding the questions that people were trying to ask an answer davus science is about us to understand the decisions they're trying to take action on questions by their very nature our informative but decisions are actionable and so what we did at Yahoo in order to really drive the help our advertisers optimize your spend across the Yahoo ad network is we focus on identifying the decisions the media planners and buyers and the campaign managers had to make around running a campaign know what what how much money to allocate to what sides how much how many conversions do I want how many impressions do I want so all the decisions we built predictive analytics around so that we can deliver prescriptive actions to these two classes of stakeholders the media planners and buyers and the campaign managers who had no aspirations about being analysts they're trying to be the best digital marketing executives or you know or people they could possibly be they didn't want to be analysts so and that sort of leads me to where I am today and my my teaching my books my blogs everything I do is very much around how do we take data and analytics and help organizations become more effective so everything I've done since then the books I've written the teaching I do with University of San Francisco and next week at the National University of Ireland and Galway and all the clients I work with is really how do we take data and analytics and help organizations become more effective at driving the decisions that optimize their business and their operational models it's really about decisions and how do we leverage data and analytics to drive those decisions so what would how would you define the difference between a question that someone's trying to answer versus a decision but they're trying to be better informed on so here's what I'd put it I call it the Sam test I am and that is it strategic is it actionable is it material and so you can ask questions that are provocative but you might not fast questions that are strategic to the problems you're trying to solve you may not be able to ask questions that are actionable in a sense you know what to do and you don't necessarily ask questions that are material in the sense that the value of that question is greater than the cost of answering that question right and so if I think about the Sam test when I apply it to data science and decisions when I start mining the data so I know what decisions are most important I'm going through a process to identify to validate the value and prioritize those decisions right I understand what decisions are most important now when I start to dig through the data all this structured unstructured data across a number different data sources I'm looking for I'm trying to codify patterns and relationships buried in that data and I'm applying the Sam test is that against those insights is it strategic to the problem I'm trying to solve can I actually act on it and is it material in the sense that it's it's it's more valuable to act than it is to create the action around it so that's the to me that big difference is by their very nature decisions are actually trying to make a decision I'm going to take an action questions by their nature are informative interesting they could be very provocative you know questions have an important role but ultimately questions do not necessarily lead to actions so if I'm a a sport coach I'm writing a professional basketball team some of the decisions I'm trying to make are I'm deciding on what program best develops my players what metrics will help me decide who the best prospect is is that the right way of looking at it yeah so we did an exercise at at USF too to have the students go through an exercise - what question what decisions does Steve Kerr need to make over the next two games he's playing right and we go through an exercise of the identifying especially in game decisions exercise routes oh no how often are you gonna play somebody no how long are they gonna play what are the right combinations what are the kind of offensive plays that you're gonna try to run so there's a know a bunch of decisions that Steve Kerr is coach of the Warriors for example needs to make in the game to not only try to win the game but to also minimize wear and tear on his players and by the way that's a really good point to think about the decisions good decisions are always a conflict of other ideas right win the game while minimizing wear and tear on my players right there's there are there are all the important decisions in life have two three or four different variables that may not be exactly the same which is by this is where data science comes in the data science is going to look across those three or four very other metrics against what you're going to measure success and try to figure out what's the right balance of those given the situation I'm in so if going back to the decision about about playing time well think about all the data you might want to look at in order to optimize that so when's the next game how far are they in this in this in the season where do they currently sit ranking wise how many minutes per game has player X been playing looking over the past few years what's there you know what's their maximum point so there's there's a there's not a lot of decisions that people are trying to make and by the way the beauty of the decisions is the decisions really haven't changed in years right what's changed is not the decisions it's the answers and the answers have changed because we have this great bound of data available to us in game performance health data you know all DNA data all kinds of other data and then we have all these great advanced analytic techniques now neural networks and unstructured supervised machine learning on right all this great technology now that can help us to uncover those relationships and patterns that are buried in the data that we can use to help individualize those decisions one last point there the point there to me at the end when when people talk about Big Data they get fixated on the big part the volume part it's not the volume of big data that I'm going to monetize it's the granularity and what I mean by that is I now have the ability to build very detailed profiles going back to our basketball example I can build a very detailed performance profile on every one of my players so for every one of the players on the Warriors team I can build a very detailed profile it the details out you know what's their optimal playing time you know how much time should they spend before a break on the feet on the on the on the court right what are the right combinations of players in order to generate the most offense or the best defense I can build these very detailed individual profiles and then I can start mission together to find the right combination so when we talk about big it's not the volume it's interesting it's the granularity gotcha and what's interesting from my world is so when you're dealing with marketing and business a lot of that when you're developing whether it be a company that you're trying to find more out about your customers or your startup trying to learn about what product you should develop there's tons of unknowns and a lot of big data from my understanding it can help you better understand some patterns within customers how to market you know in your book you talk about oh we need to increase sales at Chipotle because we understand X Y & Z our current around us now in the sports science world we have our friend called science and science has helped us early identify certain metrics that are very important and correlated to different physiological outcomes so it almost gives us a shortcut because in the big data world especially when you're dealing with the data that you guys are dealing with and trying to understand customer decisions each customer is individual and you're trying to compile all together to find patterns no one's doing science on that right it's not like a lab work where someone is understanding muscle protein synthesis and the amount of nutrients you need to recover from it so in my position I have all these pillars that maybe exist already where I can begin my search there's still a bunch of unknowns with that kind of environment do you take a different approach or do you still go with the I guess large encompassing and collect everything you can and siphon after maybe I'm totally wrong I'll let you take it away no that's it's a it's a good question and what's interesting about that max is that the human body is governed by a series of laws we'll say in each me see ology and the things you've talked about physics they have laws humans as buyers you know shoppers travelers we have propensity x' we don't have laws right I have a propensity that I'm gonna try to fly United because I get easier upgrades but I might fly you know Southwest because of schedule or convenience right I have propensity x' I don't have laws so you have laws that work to your advantage what's interesting about laws that they start going into the world of IOT and this concept called digital twins they're governed by laws of physics I have a compressor or a chiller or an engine and it's got a bunch of components in it that have been engineered together and I can actually apply the laws I can actually run simulations against my digital twins to understand exactly when is something likely to break what's the remaining useful life in that product what's the severity of the the maintenance I need to do on that so the human body unlike the human psyche is governed by laws human behaviors are really hard right and we move the las vegas is built on the fact that human behaviors are so flawed but body mate but bat body physics like the physics that run these devices you can actually build models and one simulation to figure out exactly how you know what's the wear and tear and what's the extensibility of what you can operate in gotcha yeah so that's when from our world you start looking at subsystems and you say okay this is your muscular system this is your autonomic nervous system this is your central nervous system these are ways that we can begin to measure it and then we can wrote a blog on this that's a stress response model where you understand these systems and their inferences for the most part and then you apply a stress and you see how the body responds and even you determine okay well if I know the body I can only respond in a certain number of ways it's either compensatory it's gonna be you know returning to baseline and by the mal adaptation but there's only so many ways when you look at a cell at the individual level that that cell can actually respond and it's the aggregation of all these cellular responses that end up and manifest in a change in a subsystem and that subsystem can be measured inferential II through certain technology that we have but I also think at the same time we make a huge leap and that leap is the word inference right we're making an assumption and sometimes those assumptions are very dangerous and they lead to because that assumptions unknown and we're wrong on it then we kind of sway and missed a little bit on our whole projection so I like the idea of looking at patterns and look at the probabilistic nature of it and I'm actually kind of recently change my view a little bit from my room first I talked about this I was much more hardwired and laws but I think it's a law but maybe a law with some level of variation or standard deviation and it we have guardrails instead so that's kind of how I think about it personally is that something that you say that's on the right track for that or how would you approach it yeah actually there's a lot of similarities max so your description of the human body made up of subsystems when we talk to organizations about things like smart cities or smart malls or smart hospitals a smart city is comprised of a it's made up of a series of subsystems right I've got subsystems regarding water and wastewater traffic safety you know local development things like this look there's a bunch of subsystems that make a city work and each of those subsystems is comprised of a series of decisions or clusters of decisions with equal use cases around what you're trying to optimize so if I'm trying to improve traffic flow if one of my subsystems is practically flow there are a bunch of use cases there about where do I do maintenance where do I expand the roads you know where do I put HOV lanes right so and so you start taking apart the smart city into the subsystems and then know the subsystems are comprised of use cases that puts you into really good position now here's something we did recently with a client who is trying to think about building the theme park of the future and how do we make certain that we really have a holistic view of the use cases that I need to go after it's really easy to identify the use cases within your own four walls but digital transformation in particular happens outside the four walls of an organization and so what we what we're doing is a process where we're building journey maps for all their key stakeholders so you've got a journey map for a customer you have a journey map for operations you have a journey map for partners and such so you you build these journey maps and you start thinking about for example I'm a theme park and at some point in time my guest / customer is going to have a pity they want to go do something you want to go on vacation at that point in time that theme park is competing against not only all the other theme parks but it's competing against major league baseball who's got things it's competing against you know going to the beach in Sanibel Island just hanging around right there they're competing at that point and if they only start engaging the customer when the customers actually contacted them they must a huge part of the market they made you miss a huge chance to influence that person's agenda and so one of the things that think about I don't know how this applies to your space max but as we started thinking about smart entities we use design thinking and customer journey match there's a way to make certain that we're not fooling ourselves by only looking within the four walls of our organization that we're knocking those walls down making them very forest and we're looking at what happens before somebody engages it with us and even afterwards so again going back to the theme park example once they leave the theme park they're probably posting on social media what kind of fun they had or fun they didn't have they're probably making plans for next year they're talking to friends and other things so there's there's a bunch of stuff we're gonna call it afterglow that happens after event that you want to make certain that you're in part of influencing that so again I don't know how when you combined the data science of use cases and decisions with design thinking of journey Maps what that might mean to do that your business but for us in thinking about smart cities it's opened up all kinds of possibilities and most importantly for our customers it's opened up all kinds of new areas where they can create new sources of value so anyone listening to this need to understand that when the word client or customer is used it can be substituted for athlete and what I think is really important is that when we hear you talk about your the the amount of infrastructure you do for an idea when you approach a situation is something that sports science for in my opinion especially across multiple domains it's truly lacking what happens is we get a piece of technology and someone says go do science while you're taking the approach of let's actually think out what we're doing beforehand let's determine our key performance indicators let's understand maybe the journey that this piece of technology is going to take with the athlete or how the athletes going to interact with this piece of technology throughout their four years if you're in the private sector right that afterglow effect might be something that you refer to as a client retention and their ability to come back over and over and spread your own word for you if you're in the sector with student athletes maybe it's those athletes talking highly about your program to help with recruiting and understanding that developing athletes is going to help you know make that college more enticing to go to or that program or that organization but what really stood out was the fact that you have this infrastructure built beforehand and the example I give I spoke with a good number of organizations and teams about data utilization is that if if you're to all of a sudden be dropped in the middle of the woods and someone says go build a cabin now how was it a giant forest I could use as much wood as I want I could just keep chopping down trees until I had something that had with a shelter of some sort right even I could probably do that well if someone said you know what you have three trees to cut down to make a cabin you could become very efficient and you're going to think about each chop in each piece of wood and how it's going to be used and your interaction with that wood and conjunction with that woods interaction with yourself and so when we start looking at athlete development and we're looking at client retention or we're looking at general health and wellness it's not just oh this is a great idea right we want to make the world's greatest theme park and we want to make the world's greatest training facility but what infrastructure and steps you need to take and you said stakeholders so what individuals am i working with am I talking with the physical therapist am i talking with the athletic trainer am I talking with the skill coach how does the skill coach want the data presented to them maybe that's different than how the athletic trainer is going to have a day to present it to them maybe the sport coach doesn't want to see the data unless something a red flag comes up so now you have all these different entities just like how you're talking about developing this customer journey throughout the theme park and making sure that they have a you know an experience that's memorable and causes an afterglow and really gives that experience meaning how can we now take data and apply it in the same way so we get the most value like you said on the granular aspect of data and really turn that into something valuable max you said something really important and one of the things that let me share one of many horror stories that that that comes up in my daily life which is somebody walking up to me and saying hey I got a client here's their data you know go do some science on it like well well what the heck right so when we created this thing called the hypothesis development canvas our sales teams hate it or do the time our data science teams love it because we do all this pre work we just say we make sure we understand the problem we're going after the decision they're trying to make the KPI is it's what you're going to measure success in progress what are they the operational and financial business benefits what are the data sources we want to consider here's something by the way that's it's important that maybe I wish Boeing would have thought more about which is what are the costs of false positives and false negatives right do you really understand where your risks points are and the reason why false positive and false negatives are really important in data science because data size is making predictions and by virtue of making predictions we are never 100% certain that's right or not predictions hath me built on I'm good enough well when is good enough good enough and a lot of that determination as to when is good enough good enough is really around the cost of false positives and false negatives think about a professional athlete like the false the you know the ramifications of overtraining professional athlete like a Kevin Durant or Steph Curry and they're out for the playoffs as huge financial implications them personally and for the organization so you really need to make sure you understand exactly what's the cost of being wrong and so this hypothesis development canvas is we do a lot of this work before we ever put science to the data that yeah it's it's something that's lacking across not just sports science but many fields and what I mean by that is especially you referred to the hypothesis canvas it's a piece of paper that provides a common language right it's you can sit it out before and for listeners who aren't aware a hypothesis canvas is something bill has worked and developed with his team and it's about 13 different squares and boxes and you can manipulate it based on your own profession and what you're diving into but essentially it goes through the infrastructure that you need to have setup in order for this hypothesis or idea or decision to actually be worth a damn and what I mean by that is that so many times and I hate this but I'm gonna go in a little bit of a rant and I apologize that people think oh I get an idea and they think Thomas Edison all son just had an idea and he made a light bulb Thomas Edison's famous for saying you know I did you know make a light bulb I learned was a 9000 ways to not make a light bulb and what I mean by that is he set an environment that allowed for failure and allowed for learning but what happens often people think oh I have an idea they think the idea comes not just you know in a flash because it always doesn't it might come from some research but they also believe that it comes with legs and it comes with the infrastructure supported around it that's kind of the same way that I see a lot of the data aspect going in regards to our field is that we did an idea we immediately implement and we hope it works as opposed to set up a learning environment that allows you to go okay here's what I think might happen here's my hypothesis here's I'm going to apply it and now if I fail because I have the infrastructure pre mapped out I can look at my infrastructure and say you know what that support beam or that individual box itself was the weak link and we made a mistake here but we can go back and fix it