>> TheCUBE presents HPE Discover 2022 brought to you by HPE. >> Welcome back to theCUBE's coverage of HPE Discover 2022. We're here at the Venetian convention center in Las Vegas Dave Vellante for John Furrier. Cam Amirs here is the director of technical alliances at Cribl'. Cam, good to see you. >> Good to see you too. >> Cribl'. Cool name. Tell us about it. >> So let's see. Cribl' has been around now for about five years selling products for the last two years. Fantastic company, lots of growth, started there 2020 and we're roughly 400 employees now. >> And what do you do? Tell us more. >> Yeah, sure. So I run the technical alliances team and what we do is we basically look to build integrations into platforms such as HPE GreenLake and Ezmeral. And we also work with a lot of other companies to help get data from various sources into their destinations or, you know other enrichments of data in that data pipeline. >> You know, you guys have been on theCUBE. Clint's been on many times, Ed Bailey was on our startup showcase. You guys are successful in this overfunded observability space. So, so you guys have a unique approach. Tell us about why you guys are successful in the product and some of the things you've been doing there. >> Yeah, absolutely. So our product is very complimentary to a lot of the technologies that already exist. And I used to joke around that everyone has these like pretty dashboards and reports but they completely glaze over the fact that it's not easy to get the data from those sources to their destinations. So for us, it's this capability with Cribl' Stream to get that data easily and repeatably into these destinations. >> Yeah. You know, Cam, you and I are both at the Snowflake Summit to John's point. They were like a dozen observability companies there. >> Oh yeah. >> And really beginning to be a crowded space. So explain what value you bring to that ecosystem. >> Yeah, sure. So the ecosystem that we see there is there are a lot of people that are kind of sticking to like effectively getting data and showing you dashboards reports about monitoring and things of that sort. For us, the value is how can we help customers kind of accelerate their adoption of these platforms, how to go from like your legacy SIM or your legacy monitoring solution to like the next-gen observability platform or next-gen security platform >> and what you do really well is the integration and bringing those other toolings to, to do that? >> Correct, correct. And we make it repeatable. >> How'd you end up here? >> HP? So we actually had a customer that actually deployed our software on the HPS world platform. And it was kind of a light bulb moment that, okay this is actually a different approach than going to your traditional, you know, AWS, Google, et cetera. So we decided to kind of hunt this down and figure out how we could be a bigger player in this space. >> You saw the data fabric announcement? I'm not crazy about the term, data fabric is an old NetApp term, and then Gartner kind of twisted it. I like data mesh, but anyway, it doesn't matter. We kind of know what it is, but but when you see an announcement like that how do you look at it? You know, what does it mean to to Cribl' and your customers? >> Yeah. So what we've seen is that, so we work with the data fabric team and we're able to kind of route our data to their, as a data lake, so we can actually route the data from, again all these very sources into this data lake and then have it available for whatever customers want to do with it. So one of the big things that I know Clint talks about is we give customers this, we sell choice. So we give them the ability to choose where they want to send their data, whether that's, you know HP's data lake and data fabric or some other object store or some other destination. They have that choice to do so. >> So you're saying that you can stream with any destination the customer wants? What are some examples? What are the popular destinations? >> Yeah so a lot of the popular destinations are your typical object stores. So any of your cloud object stores, whether it be AWS three, Google cloud storage or Azure blob storage. >> Okay. And so, and you can pull data from any source? >> Laughter: I'd be very careful, but absolutely. What we've seen is that a lot of people like to kind of look at traditional data sources like Syslog and they want to get it to us, a next-gen SIM, but to do so it needs to be converted to like a web hook or some sort of API call. And so, or vice versa, they have this brand new Zscaler for example, and they want to get that data into their SIM but there's no way to do it 'cause a SIM only accepts it as a Syslog event. So what we can do is we actually transform the data and make it so that it lands into that SIM in the format that it needs to be and easily make that a repeatable process >> So, okay. So wait, so not as a Syslog event but in whatever format the destination requires? >> Correct, correct. >> Okay. What are the limits on that? I mean, is this- >> Yeah. So what we've seen is that customers will be able to take, for example they'll take this Syslog event, it's unstructured data but they need to put it into say common information model for Splunk or Elastic common schema for Elastic search or just JSON format for Elastic. And so what we can do is we can actually convert those events so that they land in that transformed state, but we can also route a copy of that event in unharmed fashion, to like an S3 bucket for object store for that long term compliance user >> You can route it to any, basically any object store. Is that right? Is that always the sort of target? >> Correct, correct. >> So on the message here at HPE, first of all I'll get to the marketplace point in a second, but it's cloud to edge is kind of their theme. So data streaming sounds expensive. I mean, you know so how do you guys deal with the streaming egress issue? What does that mean to customers? You guys claim that you can save money on that piece. It's a hotly contested discussion point. >> Laughter: So one of the things that we actually just announced in our 350 release yesterday is the capability of getting data from Windows events, or from Windows hosts, I'm sorry. So a product that we also have is called Cribl' Edge. So our capability of being able to collect data from the edge and then transit it out to whether it be an on-prem, or self-hosted deployment of Cribl', or or maybe some sort of other destination object store. What we do is we actually take the data in in transit and reduce the volume of events. So we can do things like remove white space or remove events that are not really needed and compress or optimize that data so that the egress cost to your point are actually lowered. >> And your data reduction approach is, is compression? It's a compression algorithm? >> So it is a combination, yeah, so it's a combination. So there's some people what they'll do is they'll aggregate the events. So sometimes for example, VPC flow logs are very chatty and you don't need to have all those events. So instead you convert those to metrics. So suddenly you reduced those events from, you know high volume events to metrics that are so small and you still get the same value 'cause you still see the trends and everything. And if later on down the road, you need to reinvestigate those events, you can rehydrate that data with Cribl' replay >> And you'll do the streaming in real time, is that right? >> Yeah. >> So Kafka, is that what you would use? Or other tooling? >> Laughter: So we are complimentary to a Kafka deployment. Customer's already deployed and they've invested in Kafka, We can read off of Kafka and feed back into Kafka. >> If not, you can use your tooling? >> If not, we can be replacing that. >> Okay talk about your observations in the multi-cloud hybrid world because hybrid obviously everyone knows it's a steady state now. On public cloud, on premise edge all one thing, cloud operations, DevOps, data as code all the things we talk about. What's the customer view? You guys have a unique position. What's going on in the customer base? How are they looking at hybrid and specifically multi-cloud, is it stitching together multiple hybrids? Or how do you guys work across those landscapes? >> So what we've seen is a lot of customers are in multiple clouds. That's, you know, that's going to happen. But what we've seen is that if they want to egress data from say one cloud to another the way that we've architected our solution is that we have these worker nodes that reside within these hybrid, these other cloud event these other clouds, I should say so that transmitting data, first egress costs are lowered, but being able to have this kind of, easy way to collect the data and also stitch it back together, join it back together, to a single place or single location is one option that we offer customers. Another solution that we've kind of announced recently is Search. So not having to move the data from all these disparate data sources and data lakes and actually just search the data in place. That's another capability that we think is kind of popular in this hybrid approach. >> And talk about now your relationship with HPE you guys obviously had customers that drove you to Greenlake, obviously what's your experience with them and also talk about the marketplace presence. Is that new? How long has that been going on? Have you seen any results? >> Yeah, so we've actually just started our, our journey into this HPE world. So the first thing was obviously the customer's bringing us into this ecosystem and now our capabilities of, I guess getting ready to be on the marketplace. So having a presence on the marketplace has been huge giving us kind of access to just people that don't even know who we are, being that we're, you know a five year old company. So it's really good to have that exposure. >> So you're going to get customers out of this? >> That's the idea. [Laughter] >> Bring in new market, that's the idea of their GreenLake is that partners fill in. What's your impression so far of GreenLake? Because there seems to be great momentum around HP and opening up their channel their sales force, their customer base. >> Yeah. So it's been very beneficial for us, again being a smaller company and we are a channel first company so that obviously helps, you know bring out the word with other channel partners. But HP has been very, you know open arm kind of getting us into the system into the ecosystem and obviously talking, or giving the good word about Cribl' to their customers. >> So, so you'll be monetizing on GreenLake, right? That's the, the goal. >> That's the goal. >> What do you have to do to get into a position? Obviously, you got a relationship you're in the marketplace. Do you have to, you know, write to their API's or do you just have to, is that a checkbox? Describe what you have to do to monetize. >> Sure. So we have to first get validated on the platform. So the validation process validates that we can work on the Ezmeral GreenLake platform. Once that's been completed, then the idea is to have our logo show up on the marketplace. So customers say, Hey, look, I need to have a way to get transit data or do stuff with data specifically around logs, metrics, and traces into my logging solution or my SIM. And then what we do with them on the back end is we'll see this transaction occur right to their API to basically say who this customer is. 'Cause again, the idea is to have almost a zero touch kind of involvement, but we will actually have that information given to us. And then we can actually monetize on top of it. >> And the visualization component will come from the observability vendor. Is that right? Or is that somewhat, do you guys do some of that? >> So the visualization is right now we're basically just the glue that gets the data to the visualization engine. As we kind of grow and progress our search product that's what will probably have more of a visualization component. >> Do you think your customers are going to predominantly use an observability platform for that visualization? I mean, obviously you're going to get there. Are they going to use Grafana? Or some other tool? >> Or yeah, I think a lot of customers, obviously, depending on what data and what they're trying to accomplish they will have that choice now to choose, you know Grafana for their metrics, logs, et cetera or some sort of security product for their security events but same data, two different kind of use cases. And we can help enable that. >> Cam, I want to ask you a question. You mentioned you were at Splunk and Clint, the CEO and co-founder, was at Splunk too. That brings up the question I want to get your perspective on, we're seeing a modern network here with HPE, with Aruba, obviously clouds kind of going next level you got on premises, edge, all one thing, distributed computing basically, cyber security, a data problem that's solved a lot by you guys and people in this business, making sure data available machine learnings are growing and powering AI like you read about. What's changed in this business? Because you know, Splunking logs is kind of old hat you know, and now you got observability. Unification is a big topic. What's changed now? What's different about the market today around data and these platforms and, and tools? What's your perspective on that? >> I think one of the biggest things is people have seen the amount of volume of data that's coming in. When I was at Splunk, when we hit like a one terabyte deal that was a big deal. Now it's kind of standard. You're going to do a terabyte of data per day. So one of the big things I've seen is just the explosion of data growth, but getting value out of that data is very difficult. And that's kind of why we exist because getting all that volume of data is one thing. But being able to actually assert value from it, that's- >> And that's the streaming core product? That's the whole? >> Correct. >> Get data to where it needs to be for whatever application needs whether it's cyber or something else. >> Correct, correct. >> What's the customer uptake? What's the customer base like for you guys now? How many, how many customers you guys have? What are they doing with the data? What are some of the common things you're seeing? >> Yeah. I mean, it's, it's the basic blocking and tackling, we've significantly grown our customer base and they all have the same problem. They come to us and say, look, I just need to get data from here to there. And literally the routing use case is our biggest use case because it's simple and you take someone that's a an expensive engineer and operations engineer instead of having them going and doing the plumbing of data of just getting logs from one source to another, we come in and actually make that a repeatable process and make that easy. And so that's kind of just our very basic value add right from the get go. >> You can automate that, automate that, make it repeatable. Say what's in the name? Where'd the name come from? >> So Cribl', if you look it up, it's actually kind of an old shiv to get to siphon dirt from gold, right? So basically you just, that's kind of what we do. We filter out all the dirt and leave you the gold bits so you can get value. >> It's kind of what we do on theCUBE. >> It's kind of the gold nuggets. Get all these highlights, hitting Twitter, the golden, the gold nuggets. Great to have you on. >> Cam, thanks for, for coming on, explaining that sort of you guys are filling that gap between, Hey all the observability claims, which are all wonderful but then you got to get there. They got to have a route to get there. That's what got to do. Cribl' rhymes with tribble. Dave Vellante for John Furrier covering HPE Discover 2022. You're watching theCUBE. We'll be right back.

>>from around the globe. It's the Cube with digital coverage of Dell Technologies. World Digital Experience Brought to You by Dell Technologies. >>Welcome to the Cubes Coverage of Dell Technologies World 2020. The digital coverage Find Lisa Martin And then we started to be talking with one of Dell Technologies customers. Earth Camp. Joining Me is built sharp, the senior VP of product development and strategy from Earth Camp Phil, Welcome to the Cube. >>Thank you so much. >>So talk to me a little bit. About what Earth Cam does this very interesting Web can technology? You guys have tens of thousands of cameras and sensors all over the globe give her audience and understanding of what you guys are all about. >>Sure thing. The world's leading provider of Webcam technologies and mentioned content services were leaders and live streaming time lapse imaging primary focus in the vertical construction. So a lot of these, the most ambitious, largest construction projects around the world, you see, these amazing time lapse movies were capturing all of that imagery. You know, basically, around the clock of these cameras are are sending all of that image content to us when we're generating these time lapse movies from it. >>You guys, you're headquartered in New Jersey and I was commenting before we went live about your great background. So you're actually getting to be on site today? >>Yes, Yes, that's where lives from our headquarters in Upper Saddle River, New Jersey. >>Excellent. So in terms of the types of information that you're capturing. So I was looking at the website and see from a construction perspective or some of the big projects you guys have done the Hudson Yards, the Panama Canal expansion, the 9 11 Museum. But you talked about one of the biggest focus is that you have is in the construction industry in terms of what type of data you're capturing from all of these thousands of edge devices give us a little bit of insight into how much data you're capturing high per day, how it gets from the edge, presumably back to your court data center for editing. >>Sure, and it's not just construction were also in travel, hospitality, tourism, security, architectural engineering, basically, any any industry that that need high resolution visualization of their their projects or their their performance or of their, you know, product flow. So it's it's high resolution documentation is basically our business. There are billions of files in the isil on system right now. We are ingesting millions of images a month. We are also creating very high resolution panoramic imagery where we're taking hundreds and sometimes multiple hundreds of images, very high resolution images and stitching these together to make panoramas that air up to 30 giga pixel, sometimes typically around 1 to 2 giga pixel. But that composite imagery Eyes represents millions of images per per month coming into the storage system and then being, uh, stitched together to those those composites >>the millions of images coming in every month. You mentioned Isil on talk to me a little bit about before you were working with Delhi, EMC and Power Scale. How are you managing this massive volume of data? >>Sure we had. We've used a number of other enterprise storage systems. It was really nothing was as easy to manage Azazel on really is there was there was a lot of a lot of problems with overhead, the amount of time necessary from a systems administrator resource standpoint, you to manage that, uh, and and it's interesting with the amount of data that we handle. This is being billions of relatively small files there there, you know, half a megabyte to a couple of megabytes each. It's an interesting data profile, which, which isil on really is well suited for. >>So if we think about some of the massive changes that we've all been through the last in 2020 what are some of the changes that that Earth Kemp has seen with respect to the needs for organizations? Or you mentioned other industries, like travel hospitality? Since none of us could get to these great travel destinations, Have you seen a big drive up in the demand and the need to process data more data faster? >>Yeah, that's an injury interesting point with with the Pandemic. Obviously we had to pivot and move a lot of people toe working from home, which we were able to do pretty quickly. But there's also an interesting opportunity that arose from this, where so many of our customers and other people also have to do the same. And there is an increased demand for our our technology so people can remotely collaborate. They can. They can work at a distance. They can stay at home and see what's going on in these projects sites. So we really so kind of an uptick in the in the need for our products and services. And we've also created Cem basically virtual travel applications. We have an application on the Amazon Fire TV, which is the number one app in the travel platform of people can kind of virtually travel when they can't really get out there. So it's, uh, we've been doing kind of giving back Thio to people that are having having some issues with being able to travel around. We've done the fireworks of the Washington Mall around the Statue of Liberty for the July 4th, and this year will be Webcasting and New Year's in Times Square for our 25th year, actually. So again, helping people travel virtually and be, uh, maintain can be collectivity with with each other and with their projects, >>which is so essential during these times, where for the last 67 months everyone is trying to get a sense of community, and most of us just have the Internet. So I also heard you guys were available on Apple TV, someone to fire that up later and maybe virtually travel. Um, but tell me a little bit about how working in conjunction with Delta Technologies and Power Cell How is that enabled you to manage this massive volume change you've experienced this year? Because, as you said, it's also about facilitating collaboration, which is largely online these days. >>Yeah, I mean, the the great things they're working with Dell has been just our confidence in this infrastructure. Like I said, the other systems we worked with in the past we've always found ourselves kind of second guessing. Obviously, resolutions are increasing. The camera performance is increasing. Streaming video is everything is is constantly getting bigger and better, faster. Maurits And we're always innovating. We found ourselves on previous storage platforms having to really kind of go back and look at the second guess we're at with it With with this, this did L infrastructure. That's been it's been fantastic. We don't really have to think about that as much. We just continue innovating everything scales as we needed to dio. It's it's much easier to work with, >>so you've got power scale at your core data center in New Jersey. Tell me a little bit about how data gets from thes tens of thousands of devices at the edge, back to your editors for editing and how power scale facilitates faster editing, for example. >>Basically, you imagine every one of these cameras on It's not just camera. We have mobile applications. We have fixed position of robotic cameras. There's all these different data acquisition systems were integrating with weather sensors and different types of telemetry. All of that data is coming back to us over the Internet, so these are all endpoints in our network. Eso that's that's constantly being ingested into our network and say WTO. I salon the big the big thing that's really been a timesaver Working with the video editors is, instead of having to take that content, move it into an editing environment where we have we have a whole team of award winning video editors. Creating these time lapse is we don't need to keep moving that around. We're working natively on Iselin clusters. They're doing their editing, their subsequent edits. Anytime we have to update or change these movies as a project evolves, that's all it happened right there on that live environment on the retention. Is there if we have to go back later on all of our customers, data is really kept within that 11 area. It's consolidated, its secure. >>I was looking at the Del Tech website. There's a case study that you guys did earth campaign with Deltek saying that the video processing time has been reduced 20%. So that's a pretty significant increase. I could imagine what the volumes changing so much now but on Li not only is huge for your business, but to the demands that your customers have as well, depending on where there's demands are coming from >>absolutely and and just being able to do that a lot faster and be more nimble allows us to scale. We've added actually against speaking on this pandemic, we've actually added person who we've been hiring people. A lot of those people are working remotely, as as we've stated before on it's just with the increase in business. We have to continue to keep building on that on this storage environments been been great. >>Tell me about what you guys really kind of think about with respect to power scale in terms of data management, not storage management and what that difference means to your business. >>Well, again, I mean number number one was was really eliminating the amount of resource is amount of time we have to spend managing it. We've almost eliminated any downtime of any of any kind. We have greater storage density, were able to have better visualization on how our data is being used, how it's being access so as thes as thes things, a revolving. We really have good visibility on how the how the storage system is being used in both our production and our and also in our backup environments. It's really, really easy for us Thio to make our business decisions as we innovate and change processes, having that continual visibility and really knowing where we stand. >>And you mentioned hiring folks during the pandemic, which is fantastic but also being able to do things much in a much more streamlined way with respect to managing all of this data. But I am curious in terms of of innovation and new product development. What have you been able to achieve because you've got more resource is presumably to focus on being more innovative rather than managing storage >>well again? It's were always really pushing the envelope of what the technology can do. As I mentioned before, we're getting things into, you know, 20 and 30 Giga pixel. You know, people are talking about megapixel images were stitching hundreds of these together. We've we're just really changing the way imagery is used, uh, both in the time lapse and also just in archival process. Ah, lot of these things we've done with the interior. You know, we have this virtual reality product where you can you can walk through and see in the 3 60 bubble. We're taking that imagery, and we're combining it with with these been models who are actually taking the three D models of the construction site and combining it with the imagery. And we can start doing things to visualize progress and different things that are happening on the site. Look for clashes or things that aren't built like they're supposed to be built, things that maybe aren't done on the proper schedule or things that are maybe ahead of schedule, doing a lot of things to save people, time and money on these construction sites. We've also introduced a I machine learning applications into directly into the workflow in this in the storage environment. So we're detecting equipment and people and activities in the site where a lot of that would have been difficult with our previous infrastructure, it really is seamless and working with YSL on now. >>Imagine, by being able to infuse AI and machine learning, you're able to get insight faster to be ableto either respond faster to those construction customers, for example, or alert them. If perhaps something isn't going according to plan. >>A lot of it's about schedule. It's about saving money about saving time and again, with not as many people traveling to the sites, they really just have have constant visualization of what's going on. Day to day, we're detecting things like different types of construction equipment and things that are happening on the side. We're partnering with people that are doing safety analytics and things of that nature. So these these are all things that are very important to construction sites. >>What are some of the things as we are rounding out the calendar year 2020? What are some of the things that you're excited about going forward in 2021? That Earth cam is going to be able to get into and to deliver >>it, just MAWR and more people really, finally seeing the value. I mean, I've been doing this for 20 years, and it's just it's it's It's amazing how we're constantly seeing new applications and more people understanding how valuable these visual tools are. That's just a fantastic thing for us because we're really trying to create better lives through visual information. We're really helping people with things they can do with this imagery. That's what we're all about that's really exciting to us in a very challenging environment right now is that people are are recognizing the need for this technology and really starting to put it on a lot more projects. >>Well, it's You can kind of consider an essential service, whether or not it's a construction company that needs to manage and oversee their projects, making sure they're on budget on schedule, as you said, Or maybe even just the essential nous of helping folks from any country in the world connect with a favorite favorite travel location or sending the right to help. From an emotional perspective, I think the essential nous of what you guys are delivering is probably even more impactful now, don't you think? >>Absolutely and again about connecting people and when they're at home. And recently we we webcast the president's speech from the Flight 93 9 11 observation from the memorial. There was something where the only the immediate families were allowed to travel there. We webcast that so people could see that around the world we have documented again some of the biggest construction projects out there. The new rate years greater stadium was one of the recent ones, uh, is delivering this kind of flagship content. Wall Street Journal is to use some of our content recently to really show the things that have happened during the pandemic in Times Square's. We have these cameras around the world. So again, it's really bringing awareness of letting people virtually travel and share and really remain connected during this this challenging time on and again, we're seeing a really increase demand in the traffic in those areas as well. >>I can imagine some of these things that you're doing that you're achieving now are going to become permanent, not necessarily artifacts of Cove in 19 as you now have the opportunity to reach so many more people and probably the opportunity to help industries that might not have seen the value off this type of video to be able to reach consumers that they probably could never reach before. >>Yeah, I think the whole nature of business and communication and travel on everything is really going to be changed from this point forward. It's really people are looking at things very, very differently and again, seeing the technology really can help with so many different areas that, uh, that it's just it's gonna be a different kind of landscape out there we feel on that's really, you know, continuing to be seen on the uptick in our business and how many people are adopting this technology. We're developing a lot more. Partnerships with other companies were expanding into new industries on again. You know, we're confident that the current platform is going to keep up with us and help us, you know, really scale and evolved as thes needs air growing. >>It sounds to me like you have the foundation with Dell Technologies with power scale to be able to facilitate the massive growth that you're saying and the skill in the future like you've got that foundation. You're ready to go? >>Yeah, we've been We've been We've been using the system for five years already. We've already added capacity. We can add capacity on the fly, Really haven't hit any limits. And what we can do, It's It's almost infinitely scalable, highly redundant. Gives everyone a real sense of security on our side. And, you know, we could just keep innovating, which is what we do without hitting any any technological limits with with our partnership. >>Excellent. Well, Bill, I'm gonna let you get back to innovating for Earth camp. It's been a pleasure talking to you. Thank you so much for your time today. >>Thank you so much. It's been a pleasure >>for Bill Sharp and Lisa Martin. You're watching the cubes. Digital coverage of Dell Technologies World 2020. Thanks for watching. Yeah,

>>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.

>>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 your body, Jeffrey here with the Cube. Welcome back to our ongoing coverage of the busy ops manifesto unveiling its been in the works for a while. But today is 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 on professor at Babson College. We could go on. He's got a lot of great titles and and really illuminate airy 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 post. 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 long term issues, Uh, in how technology works within businesses. Biz ops. What did you see in biz ops? That that kind of addresses one of these really big long term problems? >>Well, yeah. The long term problem is that we've had a poor connection between business people and I t people between business objectives and the i t. 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 busy ops is 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 a nightie 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 a agile software development and the theory that we want to embrace change that that changes okay on. We wanna be able to iterate quickly and incorporate that, and that's been happening in the software world for for 20 plus years. What's taking so long to get that to the business side because the pace of change is change 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 P R D S and M R. D s and big giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. 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 i t. 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, um you know, time for another serious attempt at it, >>right? And do you think doing it this way right with the bizarre coalition, you know, getting a collection of of kind of like minded individuals and companies together and actually even having a manifesto which were making this declarative statement of principles and values. You think that's what it takes to kind of drive this, you know, kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in 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 a coalition is a good idea, and a manifesto is just a good way to kind of lay out. What you see is the key principles of the idea, and that makes it much easier for everybody. Toe I understand and act on. >>Yeah, 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 the principles and and the values, you know. Business outcomes, matter, trust and collaboration, data driven decisions, which is the number three or four and then learn, responded pivot. It doesn't seem like those should have to be spelled out so clearly. 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. Yeah, And a big piece of this is data 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 many stages of analytics. Onda. How has that's evolved over over time? You know, it is 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 think for you? What does that make you? You know, start to think Wow, this is This is gonna be pretty significant. >>Yeah, well, you know, this has been a long term interest of mine. Um, the last generation of a I I was very interested in expert systems. And then e think more than 10 years ago, I wrote an article about automated decision making using, um, what was available then, which is rule based approaches. But, you know, this address is an issue that we've always had with analytics and ai. Um, you know, we tended Thio 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 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 analgesic rhythm 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, >>you know, 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 that actually had an automated trigger on it, We're on the North Korean South Korea border. Um, everything else that you said had to go through some 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 that more easily automated? And then how do you see that kind of morphing over time both as the the data to support that as well as our comfort level, Um, enables us to turn mawr mawr actual decisions over to the machine? >>Well, yeah, I suggested we need 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 the that data. You know, most machine learning models, at least in business, are supervised, and that means we need tohave labeled outcomes in the in the training data. But you know, the pandemic that we're living through is a good illustration of the fact that the data also have to be reflective of current reality. And, you know, one of the things that were finding out quite frequently these days is that the data that we have a do not reflect you know what it's like to do business in a pandemic. I wrote a little piece about this recently with Jeff Cam at Wake Forest University. We call it Data Science Quarantined and it we interviewed 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. Our models may be 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 toe make sure that the data from the past and you know that's all we have, of course, is a good guide toe. You know what's happening in the present and in the future, as far as we understand it. >>Yeah, I used to joke when we started this calendar year 2020 was finally the year that we know everything with the benefit of hindsight. But it turned out 2020 the year we found out we actually know nothing and everything >>we thought we d >>o. 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, um or, you know, kind of appropriate metaphor for driving the value of the biz ops. When now your whole portfolio strategy, um, needs to really be questioned. And, you know, you have to be really well 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 was a senior executive at gen. Packed, and I 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. Digital projects you need to think about. Well, um, given some constraints on resource is and a difficulty economy for a while. Which of our projects do we wanna keep going on Pretty much the way we were for and which ones, um, are not that necessary anymore. You see a lot of that in a I because we had so many pilots. Somebody told me, You know, we've got more pilots around here than O'Hare Airport in a I, um and then the the ones that involve double down there, even mawr 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 ableto interact with you digitally. And so you certainly wouldn't want toe cancel those projects or put them on hold. So you double down on them, get them done faster and better. >>Another. Another thing I came up in my research that that you quoted um, was was from Jeff. Bezos is talking about the great bulk of what we do is quietly but meaning fleeing, 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, applied to a specific problem. And that's where you start to see the value. And, you know, the biz ops manifesto is calling it out in this particular process. But I just 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 the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions, um, the kind of once in a lifetime decisions, uh, the ones that a G laugh. Li, the former CEO of Proctor and Gamble, used to call the big swing decisions. You only get a few of those, he said. In your tenure as CEO, those air probably not going to be the ones that you're automating in part because you don't have much data about them. Your you know, only making them a few times and in part because they really require that big picture thinking and the ability to kind of anticipate the future that the best human decision makers have. Um, but 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 refer to it as boring A. I so you know, sucking data out of a contract in order to compare it Thio 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 a I, as you suggest, is really good at those narrow kinds of tasks. Um, 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. We made some great progress in that area, but everybody seems to agree that they're not gonna be perfect for quite a while. And we really don't wanna be driving around on, um in that 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. Bring up contract management. I had a buddy years ago. They had a startup around contract management, and I'm like and this was way before we had the compute power today and cloud proliferation. I said, You know how How could you possibly built off around contract management? It's language. It's legalese. It's very specific. 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 from 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 could extract a lot of business value without trying to, you know, boil the ocean. >>Yeah, I mean, if you're Amazon, Jeff Bezos thinks it's important toe 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 what a I 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 you let Ugo on on kind of a new topic for you, not really new, but you know, not not the vast majority of your publications. And that's the new way toe 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 gonna 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 gonna be what it was before. So, you know, I wonder and I know you, you tease. You're working on a a new book, you know, some of your thoughts on, you know, kind of this new way, uh, toe 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, this was an interest of mine. I think. Back in the nineties, I wrote an article called a co authored an article called Two Cheers for the Virtual Office. And, you know, it was just starting to emerge than some people were very excited about it. Some people were skeptical, and we said to cheers rather than three cheers because clearly there's some shortcomings and, you know, I keep seeing these pop up. It's 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 you know, things like innovation and creativity and certainly, um a A good, um, happy social life kind of requires some face to face contact every now and then. And so you know, I think we'll go back to an environment where there is some of that. Um, will have, um, time 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 toe jump on airplanes. Thio, Thio, give every little sales call or give every little presentation 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 on 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 and 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, because I forget the stats on how often were interrupted with notifications between email text, slack asana, salesforce The list goes on and on. So, you know, t put an AI layer between the person and all these systems that are begging for attention. And you've written a you know, a book on the attention economy, which is a whole nother topic will 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 the future that we're looking for. >>Great. Totally. Alright, >>Tom. Well, thank you so much for your time. Really enjoyed the conversation. I got to dig into the library. It's very long song. I might started 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. East, Tom. I'm Jeff. You are watching the continuing coverage of the biz ops manifesto. Unveil. Thanks for watching the Cube. 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 your body, Jeffrey here with the Cube. Welcome back to our ongoing coverage of the busy ops manifesto unveiling its been in the works for a while. But today is 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 on professor at Babson College. We could go on. He's got a lot of great titles and and really illuminate airy 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 post. 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 long term issues, Uh, in how technology works within businesses. Biz ops. What did you see in biz ops? That that kind of addresses one of these really big long term problems? >>Well, yeah. The long term problem is that we've had a poor connection between business people and I t people between business objectives and the i t. 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 busy ops is 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 a nightie 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 a agile software development and the theory that we want to embrace change that that changes okay on. We wanna be able to iterate quickly and incorporate that, and that's been happening in the software world for for 20 plus years. What's taking so long to get that to the business side because the pace of change is change 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 P R D S and M R. D s and big giant strategic plans that sit on the shelf for five years. That's just not the way business works anymore. 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 i t. 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, um you know, time for another serious attempt at it, right? >>And do you think doing it this way right with the bizarre coalition, you know, getting a collection of of kind of like minded individuals and companies together and actually even having a manifesto which were making this declarative statement of principles and values. You think that's what it takes to kind of drive this, you know, kind of beyond the experiment and actually, you know, get it done and really start to see some results in, in in production in the field. >>Well, you know, the manifesto approach worked for Karl Marx and communism. So maybe it'll work. Here is Well, now, 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 a coalition is a good idea, and a manifesto is just a good way to kind of lay out. What you see is the key principles of the idea, and that makes it much easier for everybody. Toe I understand and act on. >>Yeah, 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 the principles and and the values, you know, business outcomes, matter, trust and collaboration, data driven decisions, which is the number three or four and then learn responded Pivot, It doesn't seem like those should have to be spelled out so clearly, 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 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 many stages of analytics Onda how that's evolved over over time. You know, it is 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 think for you? What does that make you? You know, start to think Wow, this is this is gonna be pretty significant. >>Yeah, well, you know, this has been a long term interest of mine. Um, the last generation of a I I was very interested in expert systems. And then e think more than 10 years ago I wrote an article about automated decision making using, um, what was available then, which is rule based approaches. But, you know, this address is an issue that we've always had with analytics and ai. Um, you know, we tended Thio 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 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 analgesic rhythm or an AI based system, and that I believe would add to the quality and the precision and the accuracy of decisions in in most organizations. >>You know, 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 that actually had an automated trigger on it, We're on the North Korea and South Korea border. Everything else, as you said, had to go through some 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 Maura Maura actual decisions over to the machine? >>Well, yeah, I suggested we need 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, most machine learning models, at least in business, are supervised, and that means we need tohave labeled outcomes in the in the training data. But, you know, the pandemic that we're living through is a good illustration of the fact that the 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 the data that we have do not reflect. You know what it's like to do business in it. Pandemic it. I wrote a little piece about this recently with Jeff Cam at Wake Forest University. We call it Data Science quarantined, and we interviewed 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. Our models may be 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 toe, make sure that the data from the past and you know, that's all we have, of course, is a good guide toe. You know what's happening in the present and and the future as far as we understand it. >>Yeah, I used to joke when we started this calendar year 2020 is finally the year that we know everything with the benefit of hindsight. But it turned out 2020 the year we found out we actually know nothing and everything way. 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, um or, you know, kind of appropriate metaphor for driving the value of the biz ops. When now your whole portfolio strategy, um, needs to really be questioned. And, you know, You have to be really well, 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 gen. Packed. And I 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 resource is and a difficulty economy for a while. Which of our projects do we wanna keep going on Pretty much the way we were And which ones, um, are not that necessary anymore. You see a lot of that in a I because we had so many pilots, somebody for me, you know, we've got more pilots around here, then O'Hare airport in a I, um and then the the ones that involve double down there, even mawr 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 ableto interact with you, um, digitally. And so you certainly wouldn't want toe cancel those projects or put them on hold. So you double down on them, get them done faster and better. >>Another. Another thing that came up in my research that that you quoted, um, was was from Jeff. Bezos is talking about the great bulk of what we do is quietly but meaning fleeing, 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, applied to a specific problem. And that's where you start to see the value and, you know, the biz ops. Uh, manifesto is calling it out in this particular process, but I just 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 the applications where I can apply this technology to get direct business value. >>Yeah, well, you know, even talking about automated decisions? Uh, the kind of once in a lifetime decisions, uh, the ones that a g laugh Li, the former CEO of Proctor and Gamble, used to call the big swing decisions. You only get a few of those, he said. In your tenure as CEO, those air probably not going to be the ones that you're automating in part because you don't have much data about them. You're only making them a few times, and in part because they really require that big picture thinking and the ability to kind of anticipate the future that the best human decision makers have. Um, but 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 refer to it as boring A I so you know, sucking data out of a contract in order to compare it Thio 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 a I, as you suggest, is really good at those narrow kinds of tasks. Um, 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. 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 wanna be driving around on, um in that 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. Bring up contract management. I had a buddy years ago. They had a startup around contract management, and I'm like, and this was way before we had the compute power today and and cloud proliferation. I said, You know how How could you possibly built off around contract management? It's language. It's legalese. It's very specific. He's like Jeff. We just need to know where's the contract and when does it expire? And who's a signatory? And he built a business on those you know, very simple little facts that weren't being covered because their contracts from 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 could extract a lot of business value without trying to, you know, boil the ocean. >>Yeah, I mean, if you're Amazon, Jeff Bezos thinks it's important toe 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 what a I 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 you let Ugo on on kind of a new topic for you, not really new, but you know, not not the vast majority of your publications. And that's the new way toe 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 gonna 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 gonna be what it was before. So, you know, I wonder and I know you, you tease. You're working on a a new book, you know, some of your thoughts on, you know, kind of this new way. Uh, toe 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, This was an interest of mine. I think back in the nineties, I wrote an article called Ah Co authored 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 we said to 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 you know, things like innovation and creativity and certainly a a good, um, happy social life kind of requires some face to face contact every now and then. And so you know, I think we'll go back to an environment where there is some of that. We'll have, um, time 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 toe jump on airplanes. Thio, Thio give every little mhm, uh, sales call or give every little presentation. 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 a I 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 and 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 oven, a isis some, 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, because I forget the stats on how often were interrupted with notifications between email text, slack asana, salesforce The list goes on on and on. So, you know, t put an AI layer between the person and all these systems that are begging for attention. And you've written a you know, a book on the attention economy, which is a whole nother topic will 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 the future that we're looking for. >>Great 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 song. I might started 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. Unveil. Thanks for watching. The Cube will see you next time.

>> Host: From San Francisco, it's theCUBE, covering VMware Radio 2019! Brought to you by VMware. >> Welcome to theCUBE, Lisa Martin in San Francisco, at VMware Radio 2019. This is a really cool internal R&D innovation off-site with about 1800 engineers across many business units at VMware, and we're pleased to welcome back to theCUBE the VP of the sustainability strategy at VMware, Nicola Acutt. Nicola, it's great to have you back on theCUBE! >> Thank you, Lisa, it's wonderful to be here and welcome back to Radio! >> This is only the second year that press has been allowed so this is an exclusive for theCUBE, we appreciate being here. So, sustainability. It's a word that is talked about so globally in so many industries, but it has different meanings. When I think of sustainability, the first thing that comes to my mind is energy, but it's more than that. What is sustainability to VMware? >> Great, thank you Lisa. And you're right, sustainability means a lot of things to different people. In its holistic sense, we think of sustainability as the capacity to endure, the ability to endure over time, and it has environmental dimensions, it has social dimensions and of course it has economic dimensions. The way we think about sustainability at VMware is through the lens of innovation, because we really do believe that solving many of the sustainability challenges in the world today is about innovation, and so we're really excited to be able to do that work and to pursue that mission in the office of the CTO. >> So talk a little bit more about that, with the sustainability strategy being within the office of the CTO. What sort of superpowers does that give VMware to amplify what it's doing and really also, in the eyes of your customers and partners, leverage sustainability as a differentiator? >> Yeah, I love that you used the word superpowers. I think of it exactly that. For me, it's about how do we connect our tech superpowers with this vision and foresight around solving really challenging problems? So for us, how we approach that problem, is really in three dimensions. So we think about sustainability and innovation around our operation, so that's walking the talk, first and foremost, right, getting things right internally, and from an innovation perspective, that's not just about innovation in terms of energy management, you used the energy example, right, but it's also about processes. How do we think about our engineering processes, to make sure that our engineering productivity is as efficient as possible. Yesterday our chief research officer David Tennenhouse made a comment to our 18,000 engineers that it's two sides of the same coin when we're talking about innovation for good, we also have to talk about good engineering so it's both, right? So that's one. Innovation in our operations. The second lens that we think about is innovation in terms of what we do, our products and how our products serve our customers and help them achieve their sustainability goals. Also at Radio we were really pleased this year to announce a new product initiative called CAM, the Carbon Awareness Meter, and this is a product feature in Skyline which will be available to our customers later on this year, which will allow them, through the Skyline platform, to derive almost real-time carbon scores and provide them with more information, more transparency into what's happening in their infrastructure, and then serve up information that can make choices around whether it's virtual machine density or opportunities to optimize their hardware, and then also even provide them information about the grid that their data center is operating on, and that then, we hope, will empower them, our huge customer base, to think about what they can do possibly as a result. >> Oh absolutely, I can't imagine what having that insight into their own grid will allow them to do in terms of resource optimization, to be able to use resources better, to identify new products and services. I'm curious about CAM, though, being announced at Radio 2019. Was this a product, or an idea that spun out of a past Radio event, since this is the 15th annual? >> I'm so glad you asked that question. Exactly why I think this is such an exciting announcement, not only is it a really cool product feature, but it tells the story of innovation at VMware and the path that an idea can track through from an idea in someone's head to a product in our customer's system. So that journey at VMware started with this idea going back, gosh, more than three years. In fact it was round about the time that we introduced sustainability to the office of the CTO and this was a challenge we put out to engineers around how can we innovate around sustainability? It first was discussed as a tech talk and then the idea came to Radio, here, as one of these poster papers. It was then also a birds of a feather, a talk, a breakout talk. Later on, the idea then gained more momentum, it was funded as part of X-Labs which is one of our innovation programs. In fact it was so popular it got funded a second time and developed, and now it has graduated from the office of the CTO and the innovation programs into the BU. So that's a great example of this journey that our innovators, our engineers, can take with an idea, from concept to impact. >> One of the things Ray O'Farrell mentioned to John Furrier and me this morning was that this year's Radio, he said, it's kind of surprising that there's a lot of projects around proposals around collaboration. So talk about how CAM was developed, I mean, the spirit of different BUs collaborating, different minds, different engineering minds coming together with ideas that really over time and through not just Radio but the other innovation programs, you mentioned X-Labs, that this idea became something that is now enabling your customers to make big decisions and save a considerable amount of resources. How does collaboration between BUs really get VMware's innovation culture dialed way up? >> That's actually really important, this concept of collaboration. The way I think about it is connecting dots, and a key role that the office of the CTO plays is to do just that, to create the spaces like this event, which you increase the probability that people are going to have a conversation or people are thinking about something and you give them a platform to share that idea and that's where the spark comes from. You hear it in the conversations, you hear it in the energy, but that is critical. I don't think you can create a culture of innovation without creating a culture of collaboration. >> Absolutely, they're hand-in-hand. So you talked about CAM. What are some of the technological changes, improvements that VMware has made to its technologies to become, to really deliver on your sustainability goals? >> Yeah, I think it goes back to our roots, right? The very beginning of VMware, and the legacy of our core product and our core innovation has been a massive contribution to the computing field of course, and to industry and to the world, but it's also been a great, what I call one of the greatest positive externalities in terms of saving energy and resources. So that was a great start to build on, and the announcement of the CAM project today was another step in that journey to now be really intentional about connecting sustainability with innovation, just like we do with quality and with security, and really thinking about this as part of what we do. So what that journey looks like is continuing to invest in, I talked about operational innovation, I talked about our product, the third area of our strategy is really around future bets and the products that are currently off road map but on our radar. You've probably heard, a great example of that is our work on blockchain, and so we're being intentional about developing that software to be energy efficient, number one. You'll hear more about that, I hope, later in the year. We have an intern coming in the summer to help the team work on the sustainability dimensions of our blockchain approach. We just did a demo actually at Radio this week, there was a live demo on stage with our blockchain team testing out a use case in sustainability and sustainable supply to our supply chain custody, with the example of ocean plastics and making sure that we were able to really track that supply chain and blockchain was a really powerful application for a solution like that. So that's just an example of where we're thinking about applying this lens of sustainability and innovation to our future products, as well as to some of the big challenges we face as a global society. >> Right, globally and environmentally, we look at within the data center, outside the data center from the core to the edge. Where does code sustainability fit in, and how does that facilitate reducing carbon footprint at VMware, enabling that for your customers, how does that factor into becoming more efficient and more aware globally and societally as well? >> Right, well it starts with what you do, right? For us, writing code is the core of all of the applications, everything, all of the powerful things that we can do starts with the integrity of the code, and so at Radio we have one of our sessions with principal engineers and the sustainability team is working on a project to define what does that mean for us? So, it's about efficiency, it's about really thinking about how do we optimize? How do we design and pay attention to the very core of what we do? From the get-go, as a priority. >> Last question, from the customer's perspective, what is one of the many VMware customer stories that comes to mind when you think about VMware as an enabler, as a catalyst for helping an organization really dramatically reduce carbon footprint, leverage your technology for their sustainability? >> Such a great question, and y'know something interesting, I'll tell you a story. We recently looked at some of the companies that are making very serious commitments to sustainability, putting their money where their mouth is and, for example, organizations that are committing to being carbon neutral, to being RE100 which is renewable energy 100 powering their organizations through clean power, as well as committing to science-based targets around their operations, and when we looked at the data it was absolutely fascinating to see that many of VMware's best and biggest customers are in that category of leaders and so for us that represents a billion dollars of revenue so this is important, not just to us but to our customers, and so this is a journey. We're working within the office of the CTO with our field teams to really help connect the dots more intentionally and to drive additional value for our customers through their use of our products and their relationship with VMware as a solution provider. >> And it just shows and speaks to the great synergies that VMware has developed over its history with its customers. Nicola, thank you so much for joining me at Radio 2019, and sharing with our audience the massive impact, both internally and externally, that VMware's sustainability strategy is having on the world. Thank you! >> Thank you, Lisa, absolute pleasure. >> Likewise! I'm Lisa Martin, with John Furrier joining me at VMware Radio 2019 in San Francisco. Thanks for watching. (gentle music)

>> From our studios in the heart of Silicon Valley. Holloway Alto, California. It is a cube conversation. >> He will come back and ready Geoffrey here with the Cuban Interpol about those details for acute conversation. We've got a really great guess. He's been on many, many times. We're always excited. Have them on to a bunch of different companies a lot of years and really a great perspective. So we're excited. Guy. Church word. The CEO of Da Terra. Back >> in the politest. EEO guy. Great to see you. >> Thank you, Jeff. Appreciate it. >> Absolutely. So I think last time you were here, I was looking it up. Actually, Was November of twenty eighteen. You were >> kind of just getting started on your day. Terror of the adventure. Give us kind of the update. >> Yeah, I was gonna say last time we had Mark in whose CEO when found a cofounder of Data and I was edging in. So I was executive chairman at the time, you know? And obviously I found the technology. I was looking for an organization that had some forward thinking on storage. Andi, we started to get very close with a large strategic and actually We re announced it on the go to market, I think in February with HP, and I thought that myself and Mark kind of sat down, did a pinky swear and said, OK, maybe it's time for me to step in and take the CEO role just to make sure that we had that sort of marriage of innovation and then some of the operations stuff they could bring inside the business. >> So you've been at this for a >> while, but in the industry for a long time. What was it that you saw? Um, that really wanted you to get deeper in with date. Eriks. Obviously, I'm sure you have tons of opportunities coming your way. You know, to kind of move from the board seat into the CEO position. >> Yeah. Yeah, a bad bet. Maybe stupidity or being drunk. It, to be honest, it was. You know, the first thing is, I was looking for this technology that basically spanned forward, and I had this gut hunch that organizations were looking for data freedom. There's why did the Data Analytics job before that? I did security analytics, and, you know, we were looking at that when we were you know, back when we talk to things like I'm seeing Del and so from appear technology standpoint, I wanted to be in that space, but in the last few months, because you know, jobs are all about learning and then adjusting and learning and adjusting and learning. Adjusting on what I saw is a great bunch of guys, good technology. But we were sort of flapping around on DH had an idea that we were an Advanced data services platform. It's to do with multi, you know, multi cloud. And in essence, I've kind of come to this fundamental kind of understanding because I've been on both sides, which is date era is a bunch of cloud people trying to solve storage needs for what the cloud needs. But they have the experience. They walked that mile. You know, when people say you've gotta learn by walking in their shoes, right? Right on DH there, Done that versus where? Bean. In the past, where we were a ray specialists pushing towards the future that we didn't quite understand, you know, and and there is a fundamental philosopher philosophical difference between the two. Andi weirdly, my analogy or my R har moment came with the Tessler piece. And I know that, you know, you've pinned me a few times on Twitter over this, right? I'm not a tesler. Bigger to the extent of, you know, and probably am now, I should have a test a T shirt on, But I always thought it was an electric car and all they've done is electrified a car and there was on DH, You know, I've resisted it for years and bean know exactly an advocate, but I ended up buying one because I just I felt from a technology standpoint, their platform that they were the right thing. And once I started to really understand what they were about, I saw these severe differences. And, you know, we've chatted a little bit about this Onda again. It's part of the analogy of what's happening in the storage industry, but what's happening in the industry in in a global position. But if you compare contrast something like Tesler, too, maybe Volkswagon and it might be a bad example. But you know, Audi there first trance into electric vehicles was the Audi A three, and I could imagine that they were traditional car people pushing their car forward sort is a combustion engine will if I change that and put some salt powertrain in place, which is the equivalent of a you know, a system to basically drive the wheels and then a bunch of batteries Job done or good, right? Right. And I assume the test it was the same. But I had a weird experience, which is, once you get it into autopilot, you can actually set the navigation direction, and then it will indicate it'll it'Ll hint to you went to change lanes. And so, for instance, I'm driving to the office and I'm going along eight eighty and I want to go toe Wanna one? It says, You know you need to pull across. They hit the indicator will change lanes and they'LL do some of the stuff and that's all well and good. But I was up going to a board meeting on two eighty, going off for the Rosewood. You know, Sandra El Santo and I was listening to a book one of these, you know, audiobooks, and I wasn't really paying much attention. I'm in the outside lane, obviously hitting the speed limit gnome or but I wasn't paying attention. And all of a sudden the car basically indicates form A changes lanes, slows down, change lane again and then takes a junction, slows down, comes up to a junction, and you start to realize that actually Tesla's know about electrified vehicles. It's actually about the telemetry and the analytics and then feeding that back into the system. And I always thought Tesler might be collecting how faster cars going when they break. You know the usual thing. Everybody has this conversation. It's always over worked. But if you've sort of look at it and he said no, maybe they collect everything and then maybe what they're doing is they're collecting, hitting the indicator stalk. So when I'm coming out to a junction and I indicate, How long do I stay? Indicating before I break? And then I changed lanes and then I basically slow down and I go into the junction. And then what they do is they take that live information and crowdsource it, pull it back into the system, and then when they're absolutely bulletproof, that junction, then is exactly as a human would normally do this. They then let the car take over So the difference between the two junctions is one they totally understood, the other one there still learning from right when you look at it and you go done. So they're basically an edge telemetry at a micro level organization, you know, And that is a massive difference between what Tesla's doing and a lot of the other car manufacturers are doing. They're catching up, which is really why I believe that they're going to be a head for a long time. >> It's really interesting. I was >> Elektronik wholesale for ten years before come back to school. Can't got in the tech industry. And so really distribution was king from the manufacturer point of view. Always. They just like ship their products for ages, right? These distribution to break bulk thes distribution, educate the customer these distribution just to get this stuff out. But they never knew how people actually operate their products. Whether that be a car, a washing machine. Ah, cassette player, whatever. So what? What What fascinates me about thes connected devices is what, what a fundamentally different set of data. Now manufacturers have people have in how people actually use the product. But even more importantly, that as you said, they could take that data and make adjustments on the fly because since so much of its software now, we talked again before we turned on some of your software upgrades that you've gotten in the Tesla over the last six months, which we're all driven by customers. But they had a platform in place that enabled them to update functionality and to basically repurpose hardware elements for a new function, which is which is, you know, so in sync with Dev ops and kind of this dev up culture in this continuous this continuous upgrade, this continuous innovation with actual data from real people operating the products that they should come to the market. >> Andi, think once you step back. And that was really why was keen to sit down and talk. And it's not specifically around software defined storage, which is the data. A piece in our example is yes, I am the Tessler because we can do all of the analytics and all of the telemetry versus of standard array. If you scratch that away and you say let's have a look at our whole lives are macro lives. Another example was my wife and I. We've got friends of ours always banging on about these sleep by number beds and and so we went past the store wandered in, and the sales rep got us lying on a bed and he was doing there, you know, pumping the bed up to a size. It's just Well, you are sixty five, a US seventy or seventy five, and I kind of got bored of that. And I went here, Okay, I'm that and he goes, Okay, your wife's of fifty and you're a seventy five, Andi said. But let's kind of daft. And he goes, Well, here's and he shows them a map and it shows a thermal image of me lying on the bed. I'm a side sleeper back sleeper, and then what they do is they feed the information so that comes back off their edge, which is now Abed. And then what they do is they then analyzing continuously prove it to try and increase my bed sleeping patterns. So you look at it and you say what they're not doing is just manufacturing of mattress and throwing it out. What they've done is they said, we're going to treat each individual that lies on the mattress differently on, we're going to take feedback and we're going to make that experience even better. So that the same thing, which is this asset telemetry my crisis telemetry happens to be on the edge is identical to what they have, you know. And then I look at it and I go, Why don't I like the array systems? Will, because the majority of stuff is I'm a far system. My brain is inherently looking at the Dr types underneath and saying, As long as that works fine, everything that sits inside that OK, it'LL do its thing right, and that was built around the whole process and premise of an application has a single function. But now applications create data. That data has multiple functions, and as people start to use it in different ways, you need to feed that data on the way in which is processed differently. And so it all has the intelligence houses in home automation. I'm a junkie on anything that has a plug on it, and I've now got to a point where I have light switches or light fittings would have multiple bulbs on every bulb now is actually Khun B has telemetry around it, which I can adjust it dynamically based on the environment. Right? Right. And I wish it got wine. You know, I got the wine. Fridge is that's my biggest beef right now is you gotta wine, fridge. You can have Jules, you know, you have jewels climates, which means that you don't fan to one side of it and they overheat the bottom right. But it'LL break the grapes down. Would it be really cool if the cork actually had some way of figuring out what it needs to be fed? And then each of them could be individual, right? But our entire being, you know, if you think about it's not just technology or technologies driving it, but it's not the IT industry, but our entire lives. And now driven around exactly what you just described, which is manufacturers dropping something out into the wild to the edge and then having enough telemetry to be able to enhance that experience and then provide over the air, you know, enhancements, >> right? And the other thing, I think it's fascinating as it's looking up. We interviewed Derek Curtain >> from the architect council on. That's a group locally that just try work, too, along with municipalities and car manufacturers, tech companies. But >> he made a really interesting >> comment because there's the individual adjustment to you to know that you want to get off it at Page Milan or sandhill on DH. You've got a counter on your point of this is meeting the Rosewood. But >> then the other thing is, when you aggregate >> that now back up. You know, not that you're going to be sharing other people's data, but when he start to get usage patterns from a large population that you can again incorporate best practices into upgrades of the product and used a really good example of this was right after the one pedestrian got killed by the test of the lady with the bike that ran across the front of the street and it it it literally happened a week before. I think the conference so very hot topic at an autonomous vehicle conference and >> what he said, which is really important. You know, if if I get >> in an automobile accident and I'm going to learn something, the person I hits pride gonna learn something. The insurance adjusters going to take some notes and we're going to learn it's a bad intersection. I made a mistake, whatever, but when an autonomous vehicle gets in a Brack when it's connected, all that telemetry goes back up into the system to feed the system, to make improvements for the whole system. So every car learns every time one car has a problem every time one car gets into a sticky situation. So again, kind of this crowd sourced. Learning an optimization opportunity is fundamentally different than I'm just shipping stuff out, and I don't know what's going to happen to it, and maybe a couple pieces come back. So I think people that are not into this into the direct connection are so missing out on those you said this whole different level of data, this whole different level of engagement, a whole different level of product improvement and road map that's not a PR D. It's not an M R G. It's all about Get it out there, you know, get feedback from the usage and make those improvements on this >> guy finish improvements and micro analytics. I mean, even, you know, we talk back when you were adjusting how you deliver content for the Cube, you know, rather than a big blob, You really want to say, Well, I need more value for that. My clients need more value for that. So you've almost done that Mike segmentation by taking the information and then met attacking every single word in every single interview right to enrich the customer's experience, you know, And it kind of Then you Matt back and you say, We've got to the age now where the staff, the execs that we talked to over the other side, the table there, us they're living our lives. They've got the same kids as we've got the same ages we've got. They do the same person's we've got. They understand the same things and they get frustrated when things naturally don't work the way they should. Like I've got a home theater system and I've still got three remote controls. I can't get down. I've got a universal remote control, but it won't work because the components don't think so. What's happened is we've got to a world where everything's kind of interconnected and everything kind of learns and everything gets enriched when something doesn't it now stands out like a sore thumb and goes, That doesn't That is not the right way to do business on DH. Then you look that you say, translate that then into it and then into data centers. And there's these natural big red flag that says That's an old way of doing things. That's the old economy that doesn't enable me to go forward. I need to go forward. I need more agility. You know, I've got to get data freedom and then how do I solve that issue? And then what? Cos they're going to take me there because they're thinking the same ways as we are. This is why Tesler screamingly successful. This is why something like these beds are there. This is why things like Philips Hue systems are good and the list just goes on. And right now we're naturally inclined to work with products that enable us to enrich our lives and actually give feedback and then benefit us over the air. We don't like things that are too static now, and actually, there is this whole philosophy of cloud, which I think from an economic standpoint, is superb, you know? I mean, our product is Tier one enterprise storage in an SD s fashion for public private hybrid clouds. But we're seeing a lot of people doing bring backs. You know, out of the cloud is a whole thread of it right now, but I would actually say maybe it's not because the cloud philosophy is right, but it's the business model of the cloud guise of God. Because a lot of people have looked at cloud as they're setting. Forget, dump my stuff in the cloud. I get good economics. But what we're talking about now is data gets poked and prodded and moved and adjusted constantly. But the movement of the data is such that if you put in, the cloud is going to impinge you based on the business model. So that whole thing is going to mature as well, right? >> You're such a good position to because >> the, you know the growth of date is going. Bananas were just at at Arcee a couple weeks ago. In one of the conversation was about smart smart buildings, another zip zip devices on shades that tie back to the HBC, and if anybody's in the room or not, should be open should be closed. Where's the sun? But >> there was really interesting comment about >> you know, if you look at things from a software to find way you take what was an independent system that ran the elevator and independent system that ran the HBC and independent system that ran the locks? One that ran the fire alarm. But guess what? If the fire alarm goes off, baby, it would be convenient to unlock all the doors and baby. It would convenient automatically throw the elevator control system into fire mode, which is don't move. Maybe, you know so in reconnecting these things in new and imaginative ways, and then you tie it back to the I T side of the house. You know, it's it's it's it's getting a one plus one makes three effect. With all these previously silent systems that now can be, you know, connected. They can be software defined, you know, they can kind of take the operation till I would have never thought of that one hundred years. I thought that just again this fascinating twist of the Linz and how to get more value out of the existing systems by adding some intelligence and adding this back and forth telemetry. >> Yeah, and and and again, part of May is being the CEO of date era. I want advocates the right platform for people to use. But part of this is my visceral obsession of this market is moving through this software defined pattern. So it's going from being hardware resilient to software resilient to allow youto have flexibility across it. But things have to kind of interconnecting work, as you just described on SDF software to find storage as an example comes in different forms. HD is an example of it and clouds an example. I mean, everything is utterly software defined in Amazon. It so is the term gets misused, could be suffered to find you could say data centric data to find or you could say software resilient. But the whole point is what you've just described, which is open it up, allow data freedom, allow access to it and then make sure that your business is agile and whatever you do, Khun, take the feedback in a continuous loop on at lashing. Move forward as opposed to I've just got this sentence forget or lock mentality that allows me just to sort of look down the stack and say, I've got the silo. I'm owning that customer of owning the data and by the way, that's the job. It's going to doe, right? So this is just the whole concept of kind of people opening their eyes on DH. My encouragement on DI we can encourage anybody, whether customers or basically vendors, is to look around your life and figure out what enriches it from a technology standpoint. On odds on it will be something in the arena that we've just described, right? >> Do you think it's It's because I think software defined, maybe in its early days was >> just kind of an alternative thought to somebody doing it to flipping switches. But as you said in the early example, with the car, propulsion wasn't kind of a fundamentally different way to attack the problem. It was just applying a different way to execute action. What we're talking about now is a is a totally higher order of magnitude because now you've got analytics. You actually want to enable action based on the analytics based on the data for your card. Actually take action, not just a guy. Maybe you should you know, give given alert and notice that pops up on your phone. So, you know, >> maybe we need something different because it's not just redoing >> what we did a different way. It's actually elevating the whole interaction on a whole different kind of love. >> And this is this is kind of thank you for that. It was the profound kind of high got wasn't joining data and watching it. It was I got a demo off the cloud. You I the callback piece of what cloud? What data has. And I was watching a dashboard off a live data stream. You know of information that we were getting back from multiple customers and in each of the customers, it would make recommendations of, you know, how many gets on, how many times it would hear cash on DH. So it was actually coming back dynamically and recommending moving workloads across onto or flash systems. You, Khun, do things where once you've got this freedom on application, a data set isn't unknown. It's now basically in a template, and you say this is what priority has. And so you say it's got high priority. So whatever the best legacy you could give me. Give me right, You drop it onto a disk. And at the moment I've got hybrid. That's all I've got, but I decide to addle flash. So I put some all flash into the into the system. Now it becomes part of this fabric and its spots it and goes well on our second. That will disservice me better and then migrates the workload across onto it without you touching it, right? So, in other words, complete lights out so that the whole thing of this is what Mark and the team have done is looked at and said the only way forward is running this massively agile data center based on a swarm of servers that will basically be plugged together into something that would look like a fabric array. But but you can't. Then you've got to assume that you can now handle application life cycles across onto it. It'LL make recommendations like the bed thing. You know what I was saying? I was lying there and what I liked about it. So So I set my thing to fifty nine, and then it realizes I'm not sleeping very well. It's not suggested. Sixty sixty one sixty. Sleeping well, OK, that's it. And then that's good. We'LL do the same thing where an application will actually say, Here's my template. This is what it looks like. The top priority, by the way. I need the most expensive drives you've got, drops it onto it, and then it look at it and go. Actually, we could do just as good a job if there's on hybrid and then migrated across and optimize the workload, right? And so it's not again. Part of it is not. Data is the best STDs, and it is for Tier one for enterprise storage. It's the fact that the entire industry, no matter where you look at it, not just our industry but everybody is providing tech is doing is exactly the same thing, which is, and you kind of look it and you go. It's kind of edge asset micro telemetry, and then that feedback loop and then continuous adjustment allows you to be successful. That's what products are basically getting underpants. >> Just, you know, it's when he's traveling. Just No, we're almost out of time, but I just can't help it but >> say it, you know, because we used to make decisions >> based on samples of old data with samples. And it was old. And now, because of where we are on the technology lifecycle of drives and networks and CPS and GPS, we can now make decisions based on all the data now. And what a fundamentally different, different decision that's going to drive this too. And then to your point, it's like, What do you optimizing for? And you don't necessarily optimize for the same thing all the time that maybe low priority work, load optimized for cost and maybe a super high value workload optimized for speeding late in sea. And that might change >> over time when Anu workload comes in. So it's such a different way to look at the world >> and it is temporal, right? I mean, again, I know you're going kick me off now, but think about it right the old days and writing a car building a car is you thought, well, what's going to need to be in the car in three years time, put it in now, build manufacture, coming out and then with a Tesler i by the current December. Since December, I've now got pinned based authentication I've got century mode. I've got Dash Cam, They've got all free. I've got a pet mode into it now. My car's got more range. It's got high performance. This guy highest top speed, and I haven't even taken the current or it's all over the air And this is all about, continues optimization. They've done around the platform and you just go. That's the way this linked in. Recently, someone posted something said, You know, keep the eyes are dead. Well, the reason there saying that isn't because there's a stupid thing to do Q. B. Ours is because if you're not measuring your business and adjusting on a continuous basis, you're gonna be dead anyway. So our whole economy is moving this way. So you need an infrastructure architecture to support that. But where everybody's the same, we're all thinking the same. And it doesn't matter what industry or, you know, proclivity have this. This adjustment and this speed of adjustment is what you need. And like I said, I'm That's why I wanted to get to date era. That's what I'm excited about it and that is the are hard I had I kinda looked. It went Oh my God, I'm now working with cloud people who understand what they've walked in the shoes And I kind of got this way of sense of can Imagine what it had been like if you were ill on the first time You saw a hundred thousand cars worth of life data spilling in of what power you have right to adjust and to basically help your client base. And you can't do that if you are in fixed things, right? And so that's That's the world moving forward >> just in time for twenty twenty one will all have great insight in a few short months. We'LL all know >> everything Well, guy great Teo Great to >> sit down Love to keep keeping tabs on you on Twitter and social And thanks for stopping by. I >> appreciate it. All >> right. He's guy. I'm Jeff. You're watching the cube within a cube conversation Or Paulo? What? The studio's thanks for watching >> we'LL see you next time

>> Announcer: Live from Las Vegas, it's theCUBE. Covering AWS re:Invent 2017. Presented by AWS, Intel and our ecosystem of partners. >> Hey, welcome back everyone. We're live here in Las Vegas. It's theCUBE's exclusive coverage of AWS. Amazon Web Services re:Invent 2017. Amazon web Services annual conference, 45,000 people here. Five years in a row for theCUBE, and we're going to be continuing to cover years and decades after, it's on a tear. I'm John Furrier, my co-host Stu Miniman. Exciting science, one of the biggest themes here is AI, IoT, data, Deep Learning, DeepLens, all the stuff that's been really trending has been really popular at the show. And the person behind that Amazon is Swami. He's the Vice President of Machine Learning at AWS, among other things, Deep Learning and data. Welcome to theCUBE. >> Stu: Good to see you. >> Excited to be here. >> Thanks for coming on. You're the star of the show. Your team put out some great announcements, congratulations. We're seeing new obstruction layers of complexity going away. You guys have made it easy to do voice, Machine Learning, all those great stuff. >> Swami: Yeah. >> What are you most excited about, so many good things? Can you pick a child? I don't want to pick my favorite child among all my children. Our goal is to actually put Machine Learning capabilities in the hands of all developers and data scientists. That's why, I mean, we want to actually provide different kinds of capabilities right from like machine developers who want to build their own Machine Learning models. That's where SageMakers and n21 platform that lets people build, train and deploy these models in a one-click fashion. It supports all popular Deep Learning frameworks. It can be TensorFlow, MXNet or PyCharm. We also not only help train but automatically tune where we use Machine Learning for Machine Learning to build these things. It's very powerful. The other thing we're excited about is the API services that you talked about, the new obstruction layer where app developers who do not want to know anything about Machine Learning but they want to transcribe their audio to convert from speech to text, or translate it or understand the text, or analyze videos. The other thing coming from academia where I'm excited about is I want to teach developers and students Machine Learning in a fun fashion, where they should be excited about Machine Learning. It's such a transformative capability. That's why actually we built a device meant for Machine Learning in a hands-on fashion that's called DeepLens. We have developers right on re:Invent where from the time they take to un-box to actually build a computer with an application to build Hotdog or Not Hotdog, they can do it in less than 10 minutes. It's an amazing time to be a developer. >> John: Yeah. >> Stu: Oh my God, Swami. I've had so many friends that have sat through that session. First of all, the people that sit through it they get like a kit. >> Swami: That's awesome. >> Stu: They're super excited. Last year it was the Ecodot and everybody with new skills. This year, DeepLens definitely seems to be the one that all the geeks are playing with, really programing stuff. There's a bunch of other things here, but definitely some huge buzz and excitement. >> That's awesome, glad to hear. >> Talk about the culture at Amazon. Because I know in covering you guys for so many years and now being intimate with a lot of the developers in your teams. You guys just don't launch products, you actually listen to customers. You brought up Machine Learning for developers. What specifically jumped out at you from talking to customers around making it easier? It was too hard, was it, or it was confined to hardcore math driven data scientists? Was it just the thirst and desire for Machine Learning? Or you're just doing this for side benefits, it's like a philanthropy project? >> No, in Amazon we don't build technology because it's cool. We build technology because that's what our customers want. Like 90 to 95% of our roadmap is influenced by listening to customers. The other 5 to 10% is us reading between the lines. One of the things I actually ... When I started playing with Machine Learning, having built a bunch of database storage and analytics products. When I started getting into Deep Learning and various things I realized there's a transformative capability of these technologies. It was too hard for developers to use it on a day to day fashion, because these models are too hard to build and train. Our data now, the right level of obstruction. That's why we actually think of it as in a multi-layered strategy where we cater to export practitioners and data scientists. For them we have SageMaker. Then for app developers who do not want to know anything about Machine Learning they say, "I'll give you an audio file, transcribe it for me," or "I'll give you text, get me insights or translate it." For them we actually we actually provide simple to use API services, so that they can actually get going without having to know anything about what is TensorFlow or PyCharm. >> TensorFlow got a lot of attention, because that really engaged the developer community in the current Machine Learning, because we're like, "Oh wow, this is cool." >> Swami: Yeah. >> Then it got, I won't say hard to use, but it was high end. Are you guys responding to TensorFlow in particular or you're responding to other forces? What was the driver? >> In amazon we have been using Machine Learning for like 20 years. Since the year of like 1995 we have been leveraging Machine Learning for recommendation engine, fulfillment center where we use robots to pick packages and then Elixir of course and Amazon Go. One of the things we actually hear is while frameworks like TensorFlow or PyCharm, MXNet or PyCharm is cool. It is just too hard for developers to make use of it. We actually don't mind, our users use Cafe or TensorFlow. We want the, to be successful where they take from idea to product shell. And when we talk to developers, this process took anywhere from 6 to 18 months and it should not be this hard. We wanted to do what AWS did to IT industry for compute storage and databases. We want to do the same for Machine Learning by making it really easy to get started and consumer does in utility. That was our intel. >> Swami, I wonder if you can tell us. We've been talking for years about the flywheel of customers for Amazon. What are the economies of scale that you get for the data that you have there. I think of all the training of all the Machine Learning, the developers. How can you leverage the economies of scale that Amazon has in all those kind of environments? >> When you look at Machine Learning, Machine Learning tends to be mostly the icing on the cake. Even when we talk to the expert professors who are the top 10 scientists in the world, the data that goes into the Machine Learning is going to be the determining factor for how good it is in terms of how well you train it and so forth. This is where data scientists keep saying the breath of storage and database and analytics offerings that exist really matter for them to build highly accurate models. When you talk about not just the data, but actually the underlying database technology and storage technology really is important. S3 is the world's most powerful data leg that exists that is highly secure, reliable, scalable and cost effective. We really wanted to make sure customers like Glacier Cloud who store high resolution satellite imagery on S3 and glacier. We wanted them to leverage ML capabilities in a really easy one-click fashion. That's important. >> I got to ask you about the roadmap, because you say customers are having input on that. I would agree with you that that would be true, because you guys have a track record there. But I got to put the dots that I'm connecting in my mind right now forward by saying, you guys ... And telegraphing here certainly heard well, Furner say it and Andy, data is key and opening up that data and we're seeing New Relic here, Sumo Logic. They're sharing anonymous data from usage, workloads really instructive. Data is instructive for the marketplace, but you got to feed the models on the data. The question for you is you guys get so much data. It's really a systems management dream it's an application performance dream. You got more use case data. Are you going to open that up and what's the vision behind it? Because it seems like you could offer more and more services. >> Actually we already have. If you look at x-rays and service that we launched last year. That is one of the coolest capabilities, even I am a developer during the weekends when I cool out. Being able to dive into specific capabilities so one of the performance insights where is the borderline. It's so important that actually we are able to do things like x-raying into an application. We are just getting started. The Cloud transformed how we are building applications. Now with Machine Learning, what is going to happen is we can even do various things like ... Which is going to be the borderline on what kind of datasets. It's just going to be such an amazing time. >> You can literally reimagine applications that are once dominant with all the data you have, if you opened it up and then let me bring my data in. Then that will open up a bigger aperture of data. Wouldn't that make the Machine Learning and then AI more effective? >> Actually, you already can do similar things with Lex. Lex, think of it as it's an automatic speech recognition natural language understanding where we are pre-trained on our data. But then to customize it for your own chat bots or voice applications, you can actually add your own intents and several things and we customize it underlying Deep Learning model specific to your data. You're leveraging the amount of data that we have trained in addition to specifically tuning for yours. It's only going to get better and better, to your point. >> It's going to happen, it's already happening. >> It's already happening, yeah. >> Swami, great slate of announcements on the Machine Learning side. We're seeing the products get all updated. I'm wondering if you can talk to us a little bit about the human side of things. Because we've seen a lot of focus, right, it's not just these tools but it's the tools and the people putting those together. How does Amazon going to help the data scientists, help retrain, help them get ready to be able to leverage and work even better with all these tools? >> Machine Learning, we have seen some amazing usage of how developers are using Machine Learning. For example, Mariness Analytics is a non-profit organization that its goal is to fight human trafficking. They use recognition which is our image processing. They do actually identify persons of interest and victims so that they can notify law enforcement officer. Like Royal National Institute of Blind. They actually are using audio text to speech to generate audio books for visually impaired. I'm really excited about all the innovative applications that we can do to simply improve our everyday lives using Machine Learning, and it's such in early days. >> Swami, the innovation is endless in my mind. But I want to get two thoughts from you, one startup and one practitioner. Because we've heard here in theCUBE, people come here and saying, "I can do so much more now. "I've got my EMR, it's so awesome. "I can do this solving problem." Obviously making it easy to use is super cool, that's one. I want to get your thoughts on where that goes next. And two, startups. We're seeing a lot of startups retooling on Cloud economics. I call it post-2013 >> Swami: Yeah. >> They don't need a lot of money, they can hit critical mass. They can get market product, market fit earlier. They can get economic value quicker. So they're changing the dynamics. But the worry is, how do I leverage the benefit of Amazon? Because we know Amazon is going to grow and all Clouds grow and just for you guys. How do I play with Amazon? Where is the white space? How do I engage, do I just ...? Once I'm on the platform, how do I become the New Relic or slunk? How can I grow my marketplace and differentiate? Because Amazon might come out with something similar. How do I stay in that cadence of growth, even a startup? >> If you see in AWS we have tens of thousands of partners of course, right from ISV, SIs and whatnot. Software industry is an amazing industry where it's not like winner take all market. For example, in the document management space, even though we have S3 and WorkDocs, it doesn't mean Dropbox and Box are not successful either, and so forth. What we provide in AWS is the same infrastructure for any startup or for my team, even though I build probably many of the underlying infrastructure. Nowadays for my AI team, it's literally like a startup except I probably stay in an AWS building, but otherwise I don't get any internal APIs, it's the same API so easy to S3. >> John: It's a level playing field. >> It's a level playing field. >> By the way, everyone should know, he wrote DynamoDB. As an intern or was that ...? (Swami laughs) And then SQS, rockstar techy here, so it's great to have. You're what we call a tech athlete. Great to have you on. No white space, just go for it. >> Innovation is the key. The key thing, what we have seen amazing startups who have done exceptionally well is they intently listen to customers and innovate and really look for what it matters for their customers and go for it. >> The biggest buzz of the show from your group. What's your biggest buzz from the show here? DeepLens? >> DeepLens has been ... Our idea was to actually come up with a fun way to learn Machine Learning. Machine Learning, it used to be, even until recently actually as well as last week, it was actually an intimate thing for developers to learn while there is, it's all the buzz. It's not really straight forward for developers to use it. We thought, "Hey, what is a fun way for developers "to get engaged and build Machine Learning?" That's why we actually can see DeepLens so that you can actually build fun applications. I talked about Hotdog, Not Hotdog. I'm personally going to be building what I call as a Bear Cam. Because I live in the suburbs of Seattle where we actually have bears visiting our backyard digging our trash. I want to actually have DeepLens with a pre-train model that I'm going to train to detect bears. That it sends me a message through SQS and SNS so I get a text. >> Here's an idea we want to do, maybe your team can build it for us. CUBE Cam, we put the DeepLens here and then as anyone goes by, if they're a Twitter follower of theCUBE they can send me a message. (John and Swami laughing) Swami, great stuff. Deep Learning again, more goodness coming. >> Swami: That's awesome. >> What are you most excited about? >> In Amazon we have a phrase called, "It's Day One." Even though we are a 22-year-old company, I jokingly tell my team that, "It's day one for us, "except we just woke up and we haven't even "had a cup of coffee yet." We have just scratched the surface with Machine Learning, there is so much stuff to do. I'm super excited about this space. >> Your goals for this year is what? What's your goals? >> Our goals for this year was to put Machine Learning capabilities in the hands of all developers of all skill levels. I think we have done pretty well so far I think. >> Well, congratulations Swami here on theCUBE. Vice president of Machine Learning and a lot more, all those applications that were announced Wednesday along with the Deep Leaning and the AI and the DeepLens all part of his innovative team here at Amazon. Changing the game is theCUBE doing our part bringing data to you, video and more coverage. Go to Siliconangle.com for all the stories, Wikibon.com for research and of course theCUBE.net. I'm John Furrier and Stu Miniman. Thanks for watching, we'll be right back.

>> Announcer: From the Fairmont Hotel in the heart of Silicon Valley, it's The Cube. Covering when IOT met AI, the intelligence of things. Brought to you by Western Digital. >> Hey, welcome back everybody. Jeff Rick here with The Cube. We're in downtown San Jose at the Fairmont Hotel at a little show called when IOT Met AI, the Intelligence of Things. Talking about big data, IOT, AI and how those things are all coming together with virtual reality, artificial intelligence, augmented reality, all the fun buzz words, but this is where it's actually happening and we're real excited to have a pioneer in this space. He's Jack McCauley. He was a co-founder at Occulus VR, now spending his time at UC Berkeley as an innovator in residence. Jack welcome. >> Thank you. >> So you've been watching this thing evolve, obviously Occulus, way out front in kind of the VR space and I think augmented a reality in some ways is even more exciting than just kind of pure virtual reality. >> Right. >> So what do you think as you see this thing develop from the early days when you first sat down and started putting this all together? >> Well, I come from a gaming background. That's what I did for 30 years. I worked in video game development, particularly in hardware and things, console hardware. >> That's right, you did the Guitar Hero. >> Guitar Hero. Yeah, that's right. >> We got that one at home. >> I built their guitars and designed and built their guitars for Activision. And when were part of Red Octane, which is a studio. I primarily worked in the studio, not the headquarters, but I did some of the IP work with them too, so, to your question, you know when you produce a product and put it on the market, you never really know how it's going to do. >> Jeff: Right. >> So we make, we made two developer kits, put them out there and they exceeded our expectations and that was very good. It means that there is a market for VR, there is. We produce a consumer version and sales are not what we expected for that particular product. That was designated towards PC gamers and hopefully console games. But what has done well is the mobile stuff has exceeded everyone's mildest expectations. I heard numbers, Gear VR, which is Occulus designed product for me, sold 7 million of those. That's a smash hit. Now, worldwide for phone mounted VR goggles, it's about 20 million and that's just in two years, so that's really intriguing. So, what has happened is it's shifted away from an expensive PC based rig with $700 or whatever it costs, plus $1,500 for the computer to something that costs $50 and you just stick your cell phone in it and that's what people, it doesn't give you the best experience, but that's what has sold and so if I were doing a start-up right now, I would not be working on PC stuff, I'd be working on mobile stuff. >> Jeff: Right. >> And the next thing I think, which will play out of this is, and I think you mentioned it prior to the interview, is the 360 cameras and Google has announced a camera that they're going to come out and it's for their VR 180 initiative, which allows you to see 180 video in stereo with a cell phone strapped to your face. And that's very intriguing. There's a couple of companies out there working on similar products. Lucid Cam, which is a start-up company here has a 180 camera that's very, very good and they have one coming out that's in 4K. They just launched their product. So to answer your question, it looks like what is going to happen is for VR, is that it's a cell phone strapped to your face and a camera somewhere else that you can view and experience. A concert. Imagine taking it to a sporting event where 5,000 people can view your video, 10,000 from your seat. That's very intriguing. >> Yeah, it's interesting I had my first kind of experience just not even 360 or live view, but I did a periscope from the YouTube concert here at Levi Stadium a couple of months ago, just to try it out, I'd never really done it and it was fascinating to watch the engagement of people on that application who had either seen them the prior week in Seattle or were anticipating them coming to the Rose Bowl, I think, you know, within a couple of days, and to have an interaction just based on my little, you know, mobile phone, I was able to find a rail so I had a pretty steady vantage point, but it was a fascinating, different way to experience media, as well as engagement, as well as kind of a crowd interaction beyond the people that happened to be kind of standing in a circle. >> You, what's intriguing about VR 180 is that anybody can film the concert and put the video on YouTube or stream it through their phone. And formerly it would require a $10,000 camera, a stereo camera set up professionally, but can you imagine though that a crowd, you know, sourced sort of thing where the media is sourced by the crowd and anyone can watch it with a mobile phone. That's what's happening, I think, and with Google's announcement, it even that reinforces my opinion anyways that that is where the market will be. It's live events, sporting events. >> Right, it's an experience, right? It all comes back to kind of experience. People are so much more experience drive these days than I think thing driven from everything from buying cars versus taking a new Uber and seeing it over and over and over again. People want the experience, but not necessarily, as the CEO of Zura said, the straps and straddles of ownership, let me have the fun, I don't necessarily want to own it. But I think the other thing that gets less talked about, get your opinion, is really the kind of combination of virtual reality plus the real world, augmented reality. We see the industrial internet of things all the time where, you know, you go take a walk on that factory before you put your goggles on and not only do you see what you see that's actually in front of you, but now you can start to see, it's almost like a heads up display, certain characteristics of the machinery and this and that are now driven from the database side back into the goggles, but now the richness of your observation has completely changed. >> Yes, and in some ways when you think of what Google did with Google Glass, not as well as we had liked. >> But for a first attempt. >> Yeah. They're way ahead of their time and there will come a time when, you know, Snap has their specs, right? Have you seen those? It's not augmented reality, but, there will come a time when you can probably have a manacle on your face and see the kinds of things you need to see if your driving a car for instance that, I mean, a heads up display or a projector projecting right into your retina. So, and, so I think that's the main thing for augmented reality. Will people, I mean, your Pokemon Go, that's kind of a AR game in a way. You look through your cell phone and the character stays fixed on the table or wherever you're looking for it. I mean that uses a mobile device to do that and I can imagine other applications that use a mobile device to do that and I'm aware of people working on things like that right now. >> So do you think that the breakthrough on the mobile versus the PC-based system was just good enough? In being able to just experience that so easily, you know, I mean, Google gave out hundreds and hundreds of thousands of the cardboard boxes, so wow. >> Yeah. Well, it didn't mean that Gear VR didn't move into the market, it did. You know, it did anyways, but to answer your question about AR, you know, I think that, you know, without having good locals, I mean the problem with wearing the Google Glass and the Google cardboard and Gear VR is it kind of makes you sick a little bit and nobody's working on the localization part. Like how to get rid of the nausea effect. I watched a video that was filmed with Lucid Cam at the Pride Parade in San Francisco and I put it on and somebody was moving with the crowd and I just felt nauseous, so that problem probably probably is one I would attempt to attack if I were going to build a company or something like that right now. >> But I wonder too, how much of that is kind of getting used to the format because people when they first put them on for sure, there's like, ah, but you know, if you settle in a little bit and our eyes are pretty forgiving, you get used to things pretty quickly. Your mind can get accustomed to it to a certain degree, but even I get nauseous and I don't get nauseous very easily. >> Okay, so you're title should just be tinkerer. I looked at your Twitter handle. You're building all kinds of fun stuff in your not a garage, but your big giant lab and you're working at Berkeley. What are some of the things that you can share that you see coming down the road that people aren't necessary thinking about that's going to take some of these technologies to the next level. >> I got one for you. So you've heard of autonomous vehicles, right? >> Jeff: Yep, yep. >> And you've heard of Hollow Lens, right. Hollow Lens is an augmented reality device you put on your had and it's got built in localization and it creates what's, it's uses what's know as SLAM or S-L-A-M to build a mesh of the world around you. And with that mesh, the next guy that comes into that virtual world that you mapped will be away ahead. In other words, the map will already exists and he'll modify upon that and the mesh always gets updated. Can you imagine getting that into a self-driving vehicle just for safety's sake, mapping out the road ahead of you, the vehicle ahead of you has already mapped the road for you and you're adding to the mesh and adjusting the mesh, so I think that that's, you know, as far as Hollow Lens is concerned and their localization system, that's going to be really relevant to self-driving cars. Now whether or not it'll be Microsoft's SLAM or somebody else's, I think that that's probably the best, that's the good thing that came out of Hollow Lens and that will bleed into the self-driving car market. It's a big data crunching number and in Jobs, he was actually looking at this a long time ago, like what can we do with self-driving vehicles and I think he had banned the idea because he realized he had a huge computing and data problem. That was 10 years ago. Things have changed. But I think that that's the thing that will possibly come out of, you know, this AR stuff is that localization is just going to be transported to other areas of technology and self-driving cars and so forth. >> I just love autonomous vehicles because everything gets distilled and applied into that application, which is a great application for people to see and understand it's so tangible. >> Yeah, it may change the way we think about cars and we may just not ever own a car. >> I think absolutely. The car industry, it's ownership, it's usage, it's frequency of usage, how they're used. It's not a steel cage anymore for safety as the crash rates go down significantly. I think there's a lot of changes. >> Yeah, you buy a car and it sits for 20 hours a day. >> Right. >> Unutilized. >> All right. Well, Jack I hope maybe I get a chance to come out and check out your lab one time because you're making all kinds of cool stuff. When's that car going to be done? >> I took it upon myself to remodel a house the same time I was doing that, but the car is moving ahead. In September I think I can get it started. Get the engine running and get the power train up and running. Right now I'm working on the electronics and we have an interesting feature on that car that we're going to do an announcement on later. >> Okay, we'll look out for that. We'll keep watching the Twitter. All right, thanks for taking a few minutes. All right, let's check with Cauley. I'm Jeff Rick. You're watching The Cube from When IOT Met AI, the Intelligence of Things in San Jose. We'll be right back after this short break. Thanks for watching. (technological jingle)

live from Gillette Stadium in Foxboro Massachusetts extracting the signal from the noise it's the kue covering Vitas New England winter warmer 2016 now your host Stu minimum welcome back to the cube I'm Stu miniman with Wikibon com we are here at the 2016 v tug winter warmer at Gillette Stadium home of the New England Patriots and very excited to have a patriot Hall of Famer three-time Super Bowl champion number 80 Troy brown Troy thank you so much for stopping by oh man thank you for having me on I appreciate it alright so so so Troy you know we got a bunch of geeks here and they they they we talked about you know their jobs are changing a lot and you know the question I have for you is you did so many different jobs when you're on the Patriot you know how do you manage that how do you go about that from a mindset i mean i think so many of the job you did we're so specialized never spent years doing it yet you know you excelled in a lot of different positions i think first of all i think the coach bill belichick you know I think he does a good job of evaluating is his people and his players and the people that work for them and think about him he never asked an individual to do more than they can handle and I think I was one of those individuals that he saw that could you know didn't get her out about too many different things that didn't get seemed like I was overwhelmed at any moment with the job that I was at already asked to do and if I had to do multiple jobs then I would probably be one of those guys that could handle that type of situation so it started with him and in me I guess it was just my personality and my work havoc and my work ethic and just never letting the opponent know that I was a little bit shaken a little bit weary a little bit tired at times and I just continue to chip away and be my job and not you know and I took a lot of pride in being able to manage and do a lot of different things at one time and and then really accelerate yeah so you saw the transformation in the Patriot organization I mean you know it great organization here in New England but you know we were living in a phenomenal time for the Patriots over the last 20 years it and what do you attribute that that transformation to well I think it started you know you look at when Robert crab bought the team in 94 which I was here year before he bought the team in 93 I was glad to be true Bledsoe and parcels are the first year and that really Parcells really kind of got people around here excited about football I think for the first time they were having you know capacity crowds at training camp out at Bryant college you know something they never did before I mean you're talking about a team that won two games the year prior they were two and 14 and things got so lucky winning those two games in 1992 so you bringing a guy that's you know when a couple super bowls with the Giants high-profile guy gets everybody excited about the possibility of winning and I think things started to change then and then you bring in a hands-on owner because I believe James awethu wine was the previous owner that he bought the team from and lived in st. Louis it can't be hands-on when you you know live you know half the country away from from here so he bought the team and bought the local guy and again that the enthusiasm goes through the roof and expectations in through the roof we make the playoffs in 1994 and you know the things happen they don't get along and then when you go through another coach Pete Carroll for three years and you bring in Belo check and he drives a young quarterback by the name of Tom Brady and you know those types of things those people those guys able to handle different things and different jobs as well you know and you couple that with you surround them with good people like myself david patten Antwone Smith I laws or the lawyer milloy Rodney Harrison guys that kind of embody the Patriot Way and you get what you have today and it all started with the fact that mr. Kraft and Bill Belichick now been together with 15 16 years and I think you look across the NFL across any sport you don't see the type of longevity and the type of continuity that those who have and you throw on Tom Brady into that mixers been along for that entire ride as well you just think you're not going to find out in any other sport any other team maybe a couple here you notice end Antonio Spurs no in longevity I believe it is the key and you have to build that you know see you see too many owners that throwing the town were too quick yeah you know what the young coast is trying to build a team in the system yeah so I have to ask you if you had to choose one for 15 years pray to your Belichick for 15 years yeah 15 years that maybe Brady because you know it eventually will come to an end you know Bella chikan probably coach I want to know one only known for longer than 15 years we had to choose one for 15 years I guess I'll go with Brady but you know I don't think I know if one works not the other you know so that's kind of how to be a question that people be asking for many many years to come yeah so personally for you when you look back at your career you know any favorite moments that they have that mean there's so many to so many the franchise for yourself i mean i could think of all the ones that i had the pleasure to say that was a big punt return against the pittsburgh starters yeah AFC championship no well botas me start up the scoring for us yeah that was a big moment that the strip in 06 in the superbowl that year it was a big play yeah able to get us into the AFC championship game this all the Super Bowls that we were part of and then were able to win and all those moments are just so treasured and value about me that is kind of hard to place a place one over the other but you know it was all a lot of great and fantastic moments for us all right so last question I have for you looking at the Patriots today what's your prediction for the Patriots you know going on in the playoffs here going to the AFC champ I think it a bit difficult task Denver's not been a friendly place for the Patriots over the history of this franchise not just now but it is specifics as to why it's so tough to find there I don't know I don't know what it is I mean you could say the altitude but we've been out then we played well at times even there's team this year they played well the first time they went out there had an unfortunate drop punt you know that kind of changed the complexity of the game and things just changed I mean it's that's the kind of luck that we have the last time I played out there was I think 05 I think of something in the divisional round and I fumbled Kevin Faulk fumble Tom Brady threw a pick-six basically and it was like you threw your most dependable players that turned the football over and didn't play well you know how often that would that happen so Rob Gronkowski gets hit in the knee this year so and then lose him for a couple games and his season starts to turn so just so many unfortunate things that happen out there but you have to give Denver a lot of credit as well because you know they come out and they play hard to have a really good defense quarterback that can be really good you know he's a game manager at this point in his career that's a great job of doing it you know and it seemed to rally behind his presence on the field so it'll be a tough task for the Patriots even though I think the Patriots do have the better football team overall it's just been a difficult place for the New England Patriots to get wins yeah in the past I said you have a matchup for the Super Bowl that you're picking I'm picking the Patriots for sure and from what I saw from Carolina last week I got to go with Carolina playing at home against Arizona I think the defense is just too tough and Cam Newton and that run game and that offensive line has just been been pretty remarkable and surprising after losing probably the best offensive weapon in Kelvin Benjamin so yeah well you know a little something about a Carolina versa you know New England Super Bowl so hopefully things will turn out like it did last time try really appreciate you stopping by thank you so much for trying to save the program will be right back here with a wrap-up of the cubes coverage of the V tug 2016 winter warmer thanks so much for watching you