>>Good afternoon, I'm wanting or evening depending >>On where you are and welcome to this breakout session around insurance, improve underwriting with better insights. >>So first and >>Foremost, let's summarize very quickly, um, who we're with and what we're talking about today. My name is Mooney castling, and I'm the managing director at Cloudera for the insurance vertical. And we have a sizeable presence in insurance. We have been working with insurance companies for a long time now, over 10 years, which in terms of insurances, maybe not that long, but for technology, it really is. And we're working with, as you can see some of the largest companies in the world and in the continents of the world. However, we also do a significant amount of work with smaller insurance companies, especially around specialty exposures and the regionals, the mutuals in property, casualty, general insurance, life, annuity, and health. So we have a vast experience of working with insurers. And, um, we'd like to talk a little bit today about what we're seeing recently in the underwriting space and what we can do to support the insurance industry >>In there. So >>Recently what we have been seeing, and it's actually accelerated as a result of their recent pandemic that we all have been going through. We see that insurers are putting even more emphasis on accounting for every individual customer's risks, lotta via commercial, a client or a personal person, personal insurance risk in a dynamic and a bespoke way. And what I mean with that is in a dynamic way, it means that risks and risk assessments change very regularly, right? Companies go into different business situations. People behave differently. Risks are changing all the time and they're changing per person. They're not changing the narrow generically my risk at a certain point of time in travel, for example, it might be very different than any of your risks, right? So what technology has started to enable is underwrite and assess those risks at those very specific individual levels. And you can see that insurers are investing in depth capability. The value of, um, artificial intelligence and underwriting is growing dramatically. As you see from some of those quotes here and also risks that were historically very difficult to assess such as networks, uh, vendor is global supply chains, um, works workers' compensation that has a lot of moving parts to it all the time and anything that deals with rapidly changing risks, exposures and people, and businesses have been supported more and more by technology such as ours to help account for that. >>And this is a bit a difficult slide. So bear with me for a second here. What this slide shows specifically for underwriting is how data-driven insights help manage underwriting. And what you see on the left side of this slide is the progress insurers make in analytical capabilities. And quite often the first steps are around reporting and that tends to be run from a data warehouse, operational data store, Starsky, Matt, um, data, uh, models. And then, and reporting really is, uh, quite often as a BI function, of course, a business intelligence function. And it really, you know, at a regular basis informs the company of what has been taken place now in the second phase, the middle dark, the middle color blue. The next step that is shore stage is to get into descriptive analytics. And what descriptive analytics really do is they try to describe what we're learning in reporting. >>So we're seeing certain events and sorts and findings and sorts of numbers and certain trends happening in reporting. And in the descriptive phase, we describe what this means and you know why this is happening. And then ultimately, and this is the holy grill, the end goal we like to get through predictive analytics. So we like to try to predict what is going to happen, uh, which risk is a good one to underwrite, you know, Watts next policy, a customer might need or wants water claims as we discuss it. And not a session today, uh, might become fatherless or a which one we can move straight through because they're not supposed to be any issues with it, both on the underwriting and the claims side. So that's where every insurer is shooting for right now. But most of them are not there yet. Totally. Right. So on the right side of this slide specifically for underwriting, we would, we like to show what types of data generally are being used in use cases around underwriting, in the different faces of maturity and analytics that I just described. >>So you will see that on the reporting side, in the beginning, we start with braids, information, quotes, information, submission information, bounding information. Um, then if you go to the descriptive phase, we start to add risk engineering information, risk reports, um, schedules of assets on the commercial side, because some are profiles, uh, as the descriptions move into some sort of an unstructured data environments, um, notes, diaries, claims notes, underwriting notes, risk engineering notes, transcripts of customer service calls, and then totally to the outer side of this baseball field looking slide, right? You will see the relatively new data sources that can add tremendous value. Um, but I'm not Whitely integrated yet. So I will walk through some use cases around specifically. So think about sensors, wearables, you know, sense of some people's bodies, sensors, moving assets for transportation, drone images for underwriting. It's not necessary anymore to send, uh, an inspection person and inspector or a risk risk inspector or engineer to every building. You know, insurers now fly drones over it, to look at the roofs, et cetera, photos. You know, we see it a lot in claims first notice of loss, but we also see it for underwriting purposes that policies all done out at pretty much say sent me pictures of your five most valuable assets in your home and we'll price your home and all its contents for you. So we start seeing more and more movements towards those, as I mentioned earlier, dynamic and bespoke types of underwriting. >>So this is how Cloudera supports those initiatives. So on the left side, you see data coming into your insurance company. There are all sorts of different states, Dara. Some of them aren't managed and controlled by you. Some audits you get from third parties and we'll talk about Della medics in a little bit. It's one of the use cases, the move into the data life cycle, the data journey. So the data is coming into your organization. You collected, you store it, you make it ready for utilization. You plop it, eat it in an operational environment for processing what in an analytical environment for analysis. And then you close on the loop and adjusted from the beginning if necessary, no specifically for insurance, which is if not the most regulated industry in the world it's coming awfully close. And it will come in as a, as a very admirable second or third. >>Um, it's critically important that that data is controlled and managed in the correct way on all the different regulations that, that we are subject to. So we do that in the cloud era share data experiment experience, which is where we make sure that the data is accessed by the right people. And that we always can track who did watch to any point in time to that data. Um, and that's all part of the Cloudera data platform. Now that whole environment that we run on premise as well as in the cloud or in multiple clouds or in hybrid, most insurers run hybrid models, which are part of that data on premise and part of the data and use cases and workloads in the cloud. We support enterprise use cases around on the writing in risk selection, individualized pricing, digital submissions, quote processing, the whole quote, quote bound process, digitally fraud and compliance evaluations and network analysis around, um, service providers. So I want to walk you through some of the use cases that we've seen in action recently that showcases how this >>Work in real life. First one >>Is to seize that group plus Cloudera, um, uh, full disclosure is obviously for the people that know a Dutch health insurer. I did not pick the one because I happen to be Dutch is just happens to be a fantastic use case and what they were struggling with as many, many insurance companies is that they had a legacy infrastructure that made it very difficult to combine data sets and get a full view of the customer and its needs. Um, as any ensure customer demands and needs are rapidly changing competition is changing. So C-SAT decided that they needed to do something about it. And they built a data platform on Cloudera that helps them do a couple of things. It helps them support customers better or proactively. So they got really good in pinging customers on what potential steps they need to take to improve on their health in a preventative way. >>But also they sped up rapidly their, uh, approvals of medical procedures, et cetera. And so that was the original intent, right? It's like serve the customers better or retain the customers, make sure what they have the right access to the right services when they need us in a proactive way. As a side effect of this, um, data platform. They also got much better in, um, preventing and predicting fraud and abuse, which is, um, the topic of the other session we're running today. So it really was a good success and they're very happy with it. And they're actually starting to see a significant uptick in their customer service, KPIs >>And results. >>The other one that I wanted to quickly mention is Octo as most of you know, Optune is a very, very large telemedics provider, telematics data provider globally speaking with Cloudera for quite some time, this one I want to showcase because it showcases what we can do with data in mass amounts. So for Octo, we, um, analyze on Cloudera 5 million connected cars, ongoing with 11 billion data points and really want to doing as the creating the algorithms and the models and insurers use to, um, to, um, run, um, tell them insurance telematics programs, right to pay as you drive B when you drive the, how you drive. And this whole telemedics part of insurance is actually growing very fast too in, in, still in solidified proof of concept mini projects, kind of initiatives. But, um, what we're succeeding is that companies are starting to offer more and more services around it. >>So they become preventative and predictive too. So now you got to the program staff being me as a dry for seeing Monique you're hopping in the car for two hours. Now, maybe it's time to take a break. Um, we see that there's a Starbucks coming up on the right or any coffee shop. That's part of a bigger chain. Uh, we know because you have that app on your phone, that you are a Starbucks user. So if you stop there, we'll give you a 50 discount on your regular coffee. So we start seeing these types of programs coming through to, again, keep people safe and keep cars safe, but primarily of course the people in it, and those are the types of use cases that we start seeing in that telematic space. >>This looks more complicated than it is. So bear with me for a second. This is a commercial example because we see a data work. A lot of data were going on in commercial insurance. It's not Leah personal insurance thing. Commercial is near and dear to my heart. It's where I started. I actually, for a long time, worked in global energy insurance. So what this one wheelie explains is how we can use sensors on people's outfits and people's clothes to manage risks and underwrite risks better. So there are programs now for manufacturing companies and for oil and gas, where the people that work in those places are having sensors as part of their work outfits. And it does a couple of things. It helps in workers' comp underwriting and claims because you can actually see where people are moving, what they are doing, how long they're working. >>Some of them even tracks some very basic health-related information like blood pressure and heartbeat and stuff like that, temperature. Um, so those are all good things. The other thing that had to us, it helps, um, it helps collect data on the specific risks and exposures. Again, we're getting more and more to individual underwriting or individual risk underwriting, who insurance companies that, that ensure these, these, um, commercial commercial enterprises. So they started giving discounts if the workers were sensors and ultimately if there is an unfortunate event and it like a big accident or big loss, it helps, uh, first responders very quickly identify where those workers are and, and, and if, and how they're moving, which is all very important to figure out who to help first in case something bad happens. Right? So these are the type of data that quite often got implements in one specific use case, and then get broadly move to other use cases or deployed into other use cases to help price risks better, better, and keep, you know, risks, better control, manage, and provide preventative care. Right? >>So these were some of the use cases that we run in the underwriting space that are very excited to talk about. So as a next step, what we would like you to do is considered opportunities in your own companies to advance whisk assessment specific to your individual customer's need. And again, customers can be people they can be enterprises to can be other, any, any insurable entity, right? The police physical dera.com solutions insurance, where you will find all our documentation assets and thought leadership around the topic. And if you ever want to chat about this, you know, please give me a call or schedule a meeting with us. I get very passionate about this topic. I'll gladly talk to you forever. If you happen to be based in the us and you ever need somebody to filibuster on insurance, please give me a call. I'll easily fit 24 hours on this one. Um, so please schedule a call with me. I promise to keep it short. So thank you very much for joining this session. And as the last thing I would like to remind all of you read our blogs, read our tweets. We'd our thought leadership around insurance. And as we all know, insurance is sexy.

(upbeat music) >> Good morning or good afternoon, or good evening depending on where you are, and welcome to this session: Reduce claims fraud with data. Very excited to have you all here. My name is Monique Hesseling and I'm Cloudera's managing director for the insurance vertical. First and foremost, we want to let you know that we know insurance. We have done it for a long time collectively, personally, I've done it for over 30 years. And, you know, as a proof of that, we want to let you know that we insure, we insure as well as we do data management work for the top global companies in the world, in north America, over property casualty, general insurance, health, and life and annuities. But besides that, we also take care of the data needs for some smaller insurance companies and specialty companies. So if you're not one of the huge glomar, conglomerates in the world, you are still perfectly fine with us. So why are we having this topic today? Really digital claims and digital claims management is accelerating. And that's based on a couple of things. First and foremost, customers are asking for it. Customers are used to doing their work more digitally over the last decennium or two. And secondly, with the last year or almost two, by now with the changes that we made in our work processes and the society at large around Covid, both regulators, as well as companies, have enabled digital processing and a digital journey to a degree that they've never done before. Now that had some really good impacts for claims handling. It did meant that customers were more satisfied. They felt they have more control over their processes in the claims, in the claims experience. It also reduced in a lot of cases, both in commercial lines, as well as in personal lines, the time periods that it took to settle on a claim. However, it, the more digital you go, it, it opened up more access points for fraudulence activities. So unfortunately we saw indicators of fraud, and fraud attempts, you know, creeping up over the last time period. So we thought it was a good moment to look at, you know, some use cases and some approaches insurers can take to manage that even better than they already are. And this is how we plan to do that. And this is how we see this in action. On the left side, you see progress of data analytics and data utilization around in this case, we're talking about claims fraud, but it's a generic picture. And really what it means is most companies that start with data efforts pretty much started around data warehousing and preliminary analytics and all around BI and reporting, which pretty much is understanding what we know, right? The data that we already have utilizing that to understand better what we know already. Now, when we move to the middle blue color, we get into different types of analytics. We get into exploratory data science, we get to predictions and we start getting in the space of describing what we can learn from what we know, but also start moving slowly into predicting. So first of all, learn and gather insights of what we already know, and then start augmenting with that with other data sets and other findings, so that we can start predicting for the future, what might happen. And that's the point where we get to AI, artificial intelligence and machine learning, which will help us predict which of our situations and claims are most likely to have a potential fraud or abuse scenario attached to it. So that's the path that insurers and other companies take in their data management and analytics environments. Now, if you look at the right side of this slide, you see data complexity per use cases in this case in fraud. So the bubbles represent the types of data that are being used, or the specific faces that we discussed on the left side. So for reporting, we used a DBA data policy verification, claims, files, staff data, that it tends to be heavily structured and already within the company itself. And when you go to the middle to the more descriptive basis, you start getting into unstructured data, you see a lot of unstructured text there, and we do a use case around that later. And this really enables us to better understand what the scenarios are that we're looking at and where the risks are around, in our example today, fraud, abuse and issues of resources. And then the more you go to the upper right corner, you see the outside of the baseball field, people refer to it, you see new unstructured data sources that are being used. You tend to see the more complex use cases. And we're looking at picture analysis, we're looking at voice analysis there. We're looking at geolocation. That's quite often the first one we look at. So this slide actually shows you the progress and the path in complexity and in utilization of data and analytical tool sets to manage data fraud, fraud use cases optimally. Now how we do that and how we look at that at Cloudera is actually not as complicated as this slide might want to, to, to give you an impression. So let's start at the left side, at the left side, you see the enterprise data, which is data that you as an organization have, or that you have access to. It doesn't have to be internal data, but quite often it is. Now that data goes into a data journey, right? It gets collected first. It gets manipulated and engineered so that people can do something with it. It gets stored something, you know, people need to have access to it. And then they get into analytical capabilities for insight gathering and utilization. Now, especially for insurance companies that all needs to be underpinned by a very, very strong security and governance environment. Because if not the most regulated industry in the world, insurance is awfully close. And if it's not the most regulated one, it's a close second. So it's critically important that insurers know where the data is, who has access to it, for what reason, what is being used for, so terms like lineage, transparency are crucial, crucially important for insurance. And we manage that in the shared data experience that goes over the whole Cloudera platform and every application, or tool, or experience, you use within Cloudera. And on the right side, you see the use cases that tend to be deployed around claims and claims fraud, claims fraud management. So over the last year or so, we've seen a lot of use cases around upcoding, people get one treatment or one fix on a car, but it gets coded as a more expensive one. That's a fraud scenario, right? We see also the more classical fraud things and we see anti-money laundering. So those are the types of use cases on the right side that we are supporting on the platform around claims fraud. And this is an example of how that actually looks like. Now, this is a one that it's actually a live one of a company that had claims that dealt with health situations and pain killers. So that obviously is relevant for health insurers, but you also see it in, in auto claims and car claims, right? You know, accidents. There are a lot of different claims scenarios, that have health risks associated with it. And what we did in this one is, we joined tables in a complex schema. So you have to look at the claimant, the physician, the hospital, all the providers that are involved, procedures that are being deployed medically, medicines has been utilized to uncover the full picture. Now that is a hard effort in itself, just for one claim at one scenario. But if you want to see if people are abusing, for example, painkillers in this scenario, you need to do that over every instant that this member, this claimant has, you know, with different doctors, with different hospitals, with different pharmacies or whatever, That classically it's a very complicated and complex the and costly data operations. So nowadays that tends to be done by graph databasing, right? So you put fraud rings within a graph database and walk the graph. And if you look at it here in that, you can see that in this case, that is a member that was shopping around for painkillers and went to different systems, and different providers to get multiple of the same big LR stat. You know, obviously we don't know what he or she did with it, but that's not the intent of the system. And that was actually a fraud and abuse case. So I want to share some customer success stories and recent AML and fraud use cases. And we have a couple of them and I'm not going to go in an awful lot of detail about them because we have some time to spend on one of them immediately after this. But one of them, for example, is voice analytics, which is a really interesting one. And on the baseball slide that I showed you earlier, that would be a right upper corner one. And what happened there is that an insurance company utilized the, the divorce records. They got from the customer service people, to try to predict which one were potentially fraudulence. And they did it in two ways. They look at actually the contents of what was being said. So they looked at certain words that were being used, certain trigger words, but they also were looking at tone of voice, pitch of voice, speed of talking. So they try to see trends there, and hear trends that would, that would ping them for a potential bad situation. Now, good and bad news of this proof of concept was, it's, we learned that it's very difficult, just because every human is different to get an indicator for bad behavior out of the pitch or the tone or the voice, you know, or those types of nonverbal communication in voice. But we did learn that it was easier to, to predict if a specific conversation needed to be transferred to somebody else based on emotion. You know, obviously as we all understand, life and health situations tend to come with emotions. Also, people either got very sad or they got very angry or, so the proof of concept didn't really get us to affirm understanding of potential fraudulence situation, but it did get us to a much better understanding of workflow around claims escalation in customer service, to route people, to the right person, depending on, you know, what they need, in that specific time. Another really interesting one, was around social media, geo open source, all sorts of data that we put together. And we linked to the second one that I listed on the slide here that was an on-prem deployment. And that was actually an analysis that regulators were asking for in a couple of countries for anti-money laundering scams, because there were some plots out there that networks of criminals would all buy low value policies, surrender them a couple of years later. And in that way, got criminal money into the regular amount of monetary system, whitewashed the money and this needed some very specific and very, very complex link analysis because there were fairly large networks of criminals that all needed to be tied together with the actions, with their policies to figure out where potential pin points were. And that also obviously included ecosystems, such as lawyers, administrative offices, all the other things. Now, but most, you know, exciting, I think that we see happening at the moment and we, we, you know, our partner, of analytics just went live with this with a large insurer, is that by looking at different types, that insurers already have, unstructured data, their claims notes, reports, claims filings, statements, voice records, augmented with information that they have access to, but that's not theirs. So it's just geo information obituary, social media, deployed on the cloud, and we can analyze claims much more effectively and efficiently, for fraud and litigation than ever before. And the first results over the last year or two, showcasing a significant decrease, significant decrease in claims expenses and, and an increase at the right moment of what a right amount in claims payments, which is obviously a good thing for insurers. Right? So having said all of that, I really would like to give Sri Ramaswamy, the CEO of Infinilytics, the opportunity to walk you through this use case, and actually show you how this looks like in real life. So Sri, here you go. >> So insurers often ask us this question, can AI help insurance companies, lower loss expenses, litigation, and help manage reserves better? We all know that insurance industry is majority, majority of it is unstructured data. Can AI analyze all of this historically, and look for patterns and trends to help workflows and improve process efficiencies. This is exactly why we brought together industry experts at Infinilytics to create the industry's very first pre-trained and pre-built insights engine called Charlee. Charlee basically summarizes all of the data, structured and unstructured. And when I say unstructured, I go back to what Monique, basically traded, you know, it is including documents, reports, third party, it reports and investigation, interviews, statements, claim notes included as well, and any third party enrichment that we can legally get our hands on, anything that helps the adjudicate, the claims better. That is all something that we can include as part of the analysis. And what Charlee does is takes all of this data and very neatly summarizes all of this, after the analysis into insights within a dashboard. Our proprietary natural language processing semantic models adds the explanation to our predictions and insights, which is the key element that makes all of our insights action. So let's just get into understanding what these steps are and how Charlie can help, you know, with the insights from the historical patterns in this case. So when the claim comes in, it comes with a lot of unstructured data and documents that the, the claims operations team have to utilize to adjudicate, to understand and adjudicate the claim in an efficient manner. You are looking at a lot of documents, correspondences reports, third party reports, and also statements that are recorded within the claim notes. What Charlee basically does is crunches all, all of this data, removes the noise from that and brings together five key elements, locations, texts, sentiments, entities, and timelines. In the next step. In the next step, we are basically utilizing Charlee's built-in proprietary natural language processing models to semantically understand and interpret all of that information and bring together those key elements into curated insights. And the way we do that is by building knowledge, graphs, and ontologies and dictionaries that can help understand the domain language and convert them into insights and predictions that we can display on the dashboard. And if you look at what is being presented in the dashboard, these are KPIs and metrics that are very interesting for a management staff or even the operations. So the management team can basically look at the dashboard and start with the summarized data and start to then dig deeper into each of the problematic areas and look at patterns at that point. And these patterns that we learn, from not only from what the system can provide, but also from the historic data, can help understand and uncover some of these patterns in the newer claims that are coming in. So important to learn from the historic learnings and apply those learnings in the new claims that are coming in. Let's just take a very quick example of what this is going to look like for a claims manager. So here the claims manager discovers from the summarized information that there are some problems in the claims that basically have an attorney involved. They have not even gone into litigation and they still are, you know, experiencing a very large average amount of claim loss when they compare to the benchmark. So this is where the manager wants to dig deeper and understand the patterns behind it from the historic data. And this has to look at the wealth of information that is sitting in the unstructured data. So Charlee basically pulls together all these topics, and summarizes these topics that are very specific to certain losses combined with entities and timelines and sentiments, and very quickly be able to show to the manager where the problematic areas are and what are those patterns leading to high, severe claims, whether it's litigation or whether it's just high, severe indemnity payments. And this is where the managers can adjust their workflows, based on what we can predict using those patterns that we have learned and predict the new claims. The operations team can also leverage Charlee's deep level insights, claim level insights, in the form of red flags, alerts and recommendations. They can also be trained using these recommendations, and the operations team can mitigate the claims much more effectively and proactively, using these kind of deep level insights that need to look at unstructured data. So at the, at the end, I would like to say that it is possible for us to achieve financial benefits, leveraging artificial intelligence platforms like Charlee and help the insurers learn from their historic data and being able to apply that to the new claims, to work, to adjust their workflows efficiently. >> Thank you very much Sri. That was very enlightening as always. And it's great to see that actually, some of the technology that we all work so hard on together, comes to fruition in, in cost savings and efficiencies and, and help insurers manage potential bad situations, such as claims fraud better, right? So to close this session out as a next step, we would really urge you to assess your available data sources and advanced or predictive fraud prevention capabilities, aligned with your digital initiatives to digital initiatives that we all embarked on, over the last year are creating a lot of new data that we can use to learn more. So that's a great thing. If you need to learn more, want to learn more about Cloudera and our insurance work and our insurance efforts call me, I'm very excited to talk about this forever. So if you want to give me a call or find a place to meet, when that's possible again, and schedule a meeting with us. And again, we love insurance. We'll gladly talk to you until SDC and parts of the United States, the cows come home about it. And we're done. I want to thank you all for attending this session, and hanging in there with us for about half an hour. And I hope you have a wonderful rest of the day.

>>Good morning or good afternoon or good evening, depending on where you are and welcome to this session, reduce claims, fraud, we're data, very excited to have you all here. My name is Winnie castling and I'm Cloudera as managing director for the insurance vertical. First and foremost, we want to let you know that we know insurance. We have done it for a long time. Collectively, personally, I've done it for over 30 years. And, you know, as a proof of that, we want to let you know that we insure, we insure as well as we do data management work for the top global companies in the world, in north America, over property casualty, general insurance health, and, um, life and annuities. But besides that, we also take care of the data needs for some smaller insurance companies and specialty companies. So if you're not one of the huge Glomar conglomerates in the world, you are still perfectly fine with us. >>So >>Why are we having this topic today? Really digital claims and digital claims management is accelerating. And that's based on a couple of things. First and foremost, customers are asking for it. Customers are used to doing their work more digitally over the last descending year or two. And secondly, with the last year or almost two, by now with the changes that we made in our work processes and in society at large around cuvettes, uh, both regulators, as well as companies have enabled digital processing and the digital journey to a degree that they've never done before. Now that had some really good impacts for claims handling. It did meant that customers were more satisfied. They felt they have more control over their processes in the cloud and the claims experience. It also reduced in a lot of cases, both in commercial lines, as well as in personal lines, the, um, the, the time periods that it took to settle on a claim. However, um, the more digital you go, it, it opened up more access points for fraud, illicit activities. So unfortunately we saw indicators of fraud and fraud attempts, you know, creeping up over the last time period. So we thought it was a good moment to look at, you know, some use cases and some approaches insurers can take to manage that even better than they already >>Are. >>And this is how we plan to do that. And this is how we see this in action. On the left side, you see progress of data analytics and data utilization, um, around, in this case, we're talking about claims fraud, but it's a generic picture. And really what it means is most companies that start with data affords pretty much start around data warehousing and we eliminate analytics and all around BI and reporting, which pretty much is understanding what we know, right? The data that we already have utilizing data to understand better what we know already. Now, when we move to the middle blue collar, we get into different types of analytics. We get into exploratory data science, we get to predictions and we start getting in the space of describing what we can learn from what we know, but also start moving slowly into predicting. So first of all, learn and gather insights of what we already know, and then start augmenting with that with other data sets and other findings, so that we can start predicting for the future, what might happen. >>And that's the point where we get to AI, artificial intelligence and machine learning, which will help us predict which of our situations and claims are most likely to have a potential fraud or abuse scenario attached to it. So that's the path that insurers and other companies take in their data management and analytics environments. Now, if you look at the right side of this light, you see data complexity per use cases in this case in fraud. So the bubbles represent the types of data that are being used, or the specific faces that we discussed on the left side. So for reporting, we used a TPA data, policy verification, um, claims file staff data, that it tends to be heavily structured and already within the company itself. And when you go to the middle to the more descriptive basis, you start getting into unstructured data, you see a lot of instructor texts there, and we do a use case around that later. >>And this really enables us to better understand what the scenarios are that we're looking at and where the risks are around. In our example today, fraud, abuse and issues of resources. And then the more you go to the upper right corner, you see the outside of the baseball field, people refer to it, you see new unstructured data sources that are being used. You tend to see the more complex use cases. And we're looking at picture analysis, we're looking at voice analysis there. We're looking at geolocation. That's quite often the first one we look at. So this slide actually shows you the progress and the path in complexity and in utilization of data and analytical tool sets to manage data fraud, fraud, use cases, optimally. >>Now how we do that and how we look at at a Cloudera is actually not as complicated as, as this slight might want to, um, to, to give you an impression. So let's start at the left side at the left side, you see the enterprise data, which is data that you as an organization have, or that you have access to. It doesn't have to be internal data, but quite often it is now that data goes into a data journey, right? It gets collected first. It gets manipulated and engineered so that people can do something with it. It gets stored something, you know, people need to have access to it. And then they get into analytical capabilities who are inside gathering and utilization. Now, especially for insurance companies that all needs to be underpinned by a very, very strong security and governance, uh, environment. Because if not the most regulated industry in the world, insurance is awfully close. >>And if it's not the most regulated one, it's a close second. So it's critically important that insurers know, um, where the data is, who has access to it for Rodriguez, uh, what is being used for so terms like lineage, transparency are crucial, crucially important for insurance. And we manage that in the shared data experience. So it goes over the whole Cloudera platform and every application or tool or experience you use would include Dao. And on the right side, you see the use cases that tend to be deployed around claims and claims fraud, claims, fraud management. So over the last year or so, we've seen a lot of use cases around upcoding people get one treatment or one fix on a car, but it gets coded as a more expensive one. That's a fraud scenario, right? We see also the more classical fraud things and we see anti money laundering. So those are the types of use cases on the right side that we are supporting, um, on the platform, uh, around, um, claims fraud. >>And this is an example of how that actually looks like now, this is a one that it's actually a live one of, uh, a company that had, um, claims that dealt with health situations and being killers. So that obviously is relevant for health insurers, but you also see it in, um, in auto claims and counterclaims, right, you know, accidents. There are a lot of different claims scenarios that have health risks associated with it. And what we did in this one is we joined tables in a complex schema. So we have to look at the claimant, the physician, the hospital, all the providers that are involved procedures that are being deployed. Medically medicines has been utilized to uncover the full picture. Now that is a hard effort in itself, just for one claim and one scenario. But if you want to see if people are abusing, for example, painkillers in this scenario, you need to do that over every instant that is member. >>This claimant has, you know, with different doctors, with different hospitals, with different pharmacies or whatever that classically it's a very complicated and complex, um, the and costly data operation. So nowadays that tends to be done by graph databases, right? So you put fraud rings within a graph database and walk the graph. And if you look at it here in batch, you can see that in this case, that is a member that was shopping around for being killers and went through different systems and different providers to get, um, multiple of the same big LR stat. You know, obviously we don't know what he or she did with it, but that's not the intent of the system. And that was actually a fraud and abuse case. >>So I want to share some customer success stories and recent, uh, AML and fraud use cases. And we have a couple of them and I'm not going to go in an awful lot of detail, um, about them because we have some time to spend on one of them immediately after this. But one of them for example, is voice analytics, which is a really interesting one. And on the baseball slide that I showed you earlier, that would be a right upper corner one. And what happened there is that an insurance company utilized the, uh, the voice records they got from the customer service people to try to predict which one were potentially fraud list. And they did it in two ways. They look at actually the contents of what was being said. So they looked at certain words that were being used certain trigger words, but they also were looking at tone of voice pitch of voice, uh, speed of talking. >>So they try to see trends there and hear trends that would, um, that would bring them for a potential bad situation. Now good and bad news of this proof of concept was it's. We learned that it's very difficult just because every human is different to get an indicator for bad behavior out of the pitch or the tone or the voice, you know, or those types of nonverbal communication in voice. But we did learn that it was easier to, to predict if a specific conversation needed to be transferred to somebody else based on emotion. You know, obviously as we all understand life and health situations tend to come with emotions, or so people either got very sad or they got very angry or so the proof of concept didn't really get us to a firm understanding of potential driverless situation, but it did get us to a much better understanding of workflow around, um, claims escalation, um, in customer service to route people, to the right person, depending on what they need. >>And that specific time, another really interesting one was around social media, geo open source, all sorts of data that we put together. And we linked to the second one that I listed on slide here that was an on-prem deployment. And that was actually an analysis that regulators were asking for in a couple of countries, uh, for anti money laundering scams, because there were some plots out there that networks of criminals would all buy the low value policies, surrendered them a couple of years later. And in that way, God criminal money into the regular amount of monetary system whitewashed the money and this needed some very specific and very, very complex link analysis because there were fairly large networks of criminals that all needed to be tied together, um, with the actions, with the policies to figure out where potential pain points were. And that also obviously included ecosystems, such as lawyers, administrative offices, all the other things, no, but most, you know, exciting. >>I think that we see happening at the moment and we, we, you know, our partner, if analytics just went live with this with a large insurer, is that by looking at different types that insurers already have, um, unstructured data, um, um, their claims nodes, um, repour its claims, filings, um, statements, voice records, augmented with information that they have access to, but that's not their ours such as geo information obituary, social media Boyd on the cloud. And we can analyze claims much more effectively and efficiently for fraud and litigation and alpha before. And the first results over the last year or two showcasing a significant degree is significant degrees in claims expenses and, um, and an increase at the right moment of what a right amount in claims payments, which is obviously a good thing for insurers. Right? So having said all of that, I really would like to give Sri Ramaswami, the CEO of infinite Lytics, the opportunity to walk you through this use case and actually show you how this looks like in real life. So Sheree, here >>You go. So >>Insurers often ask us this question, can AI help insurance companies, lower loss expenses, litigation, and help manage reserves better? We all know that insurance industry is majority. Majority of it is unstructured data. Can AI analyze all of this historically and look for patterns and trends to help workflows and improve process efficiencies. This is exactly why we brought together industry experts at infill lyrics to create the industries where very first pre-trained and prebuilt insights engine called Charlie, Charlie basically summarizes all of the data structured and unstructured. And when I say unstructured, I go back to what money basically traded. You know, it is including documents, reports, third-party, um, it reports and investigation, uh, interviews, statements, claim notes included as well at any third party enrichment that we can legally get our hands on anything that helps the adjudicate, the claims better. That is all something that we can include as part of the analysis. And what Charlie does is takes all of this data and very neatly summarizes all of this. After the analysis into insights within our dashboard, our proprietary naturally language processing semantic models adds the explanation to our predictions and insights, which is the key element that makes all of our insights >>Actually. So >>Let's just get into, um, standing what these steps are and how Charlie can help, um, you know, with the insights from the historical patterns in this case. So when the claim comes in, it comes with a lot of unstructured data and documents that the, uh, the claims operations team have to utilize to adjudicate, to understand and adjudicate the claim in an efficient manner. You are looking at a lot of documents, correspondences reports, third party reports, and also statements that are recorded within the claim notes. What Charlie basically does is crunches all, all of this data removes the noise from that and brings together five key elements, locations, texts, sentiments, entities, and timelines in the next step. >>In the next step, we are basically utilizing Charlie's built-in proprietary, natural language processing models to semantically understand and interpret all of that information and bring together those key elements into curated insights. And the way we do that is by building knowledge, graphs, and ontologies and dictionaries that can help understand the domain language and convert them into insights and predictions that we can display on the dash. Cool. And if you look at what has been presented in the dashboard, these are KPIs and metrics that are very interesting for a management staff or even the operations. So the management team can basically look at the dashboard and start with the summarized data and start to then dig deeper into each of the problematic areas and look at patterns at that point. And these patterns that we learn from not only from what the system can provide, but also from the historic data can help understand and uncover some of these patterns in the newer claims that are coming in so important to learn from the historic learnings and apply those learnings in the new claims that are coming in. >>Let's just take a very quick example of what this is going to look like a claims manager. So here the claims manager discovers from the summarized information that there are some problems in the claims that basically have an attorney involved. They have not even gone into litigation and they still are, you know, I'm experiencing a very large, um, average amount of claim loss when they compare to the benchmark. So this is where the manager wants to dig deeper and understand the patterns behind it from the historic data. And this has to look at the wealth of information that is sitting in the unstructured data. So Charlie basically pulls together all these topics and summarizes these topics that are very specific to certain losses combined with entities and timelines and sentiments, and very quickly be able to show to the manager where the problematic areas are and what are those patterns leading to high, severe claims, whether it's litigation or whether it's just high, severe indemnity payments. >>And this is where the managers can adjust their workflows based on what we can predict using those patterns that we have learned and predict the new claims, the operations team can also leverage Charlie's deep level insights, claim level insights, uh, in the form of red flags, alerts and recommendations. They can also be trained using these recommendations and the operations team can mitigate the claims much more effectively and proactively using these kind of deep level insights that need to look at unstructured data. So at the, at the end, I would like to say that it is possible for us to achieve financial benefits, leveraging artificial intelligence platforms like Charlie and help the insurers learn from their historic data and being able to apply that to the new claims, to work, to adjust their workflows efficiently. >>Thank you very much for you. That was very enlightening as always. And it's great to see that actually, some of the technology that we all work so hard on together, uh, comes to fruition in, in cost savings and efficiencies and, and help insurers manage potential bad situations, such as claims fraud batter, right? So to close this session out as a next step, we would really urge you to a Sasha available data sources and advanced or predictive fraud prevention capabilities aligned with your digital initiatives to digital initiatives that we all embarked on over the last year are creating a lot of new data that we can use to learn more. So that's a great thing. If you need to learn more at one to learn more about Cloudera and our insurance work and our insurance efforts, um, you to call me, uh, I'm very excited to talk about this forever. So if you want to give me a call or find a place to meet when that's possible again, and schedule a meeting with us, and again, we love insurance. We'll gladly talk to anyone until they say in parts of the United States, the cows come home about it. And we're dad. I want to thank you all for attending this session and hanging in there with us for about half an hour. And I hope you have a wonderful rest of the day. >>Good afternoon, I'm wanting or evening depending on where you are and welcome to this breakout session around insurance, improve underwriting with better insights. >>So first and >>Foremost, let's summarize very quickly, um, who we're with and what we're talking about today. My name is goonie castling, and I'm the managing director at Cloudera for the insurance vertical. And we have a sizeable presence in insurance. We have been working with insurance companies for a long time now, over 10 years, which in terms of insurance, it's maybe not that long, but for technology, it really is. And we're working with, as you can see some of the largest companies in the world and in the continents of the world. However, we also do a significant amount of work with smaller insurance companies, especially around specialty exposures and the regionals, the mutuals in property, casualty, general insurance, life, annuity, and health. So we have a vast experience of working with insurers. And, um, we'd like to talk a little bit today about what we're seeing recently in the underwriting space and what we can do to support the insurance industry in there. >>So >>Recently what we have been seeing, and it's actually accelerated as a result of the recent pandemic that we all have been going through. We see that insurers are putting even more emphasis on accounting for every individual customers with lotta be a commercial clients or a personal person, personal insurance risk in a dynamic and a B spoke way. And what I mean with that is in a dynamic, it means that risks and risk assessments change very regularly, right? Companies go into different business situations. People behave differently. Risks are changing all the time and the changing per person they're not changing the narrow generically my risk at a certain point of time in travel, for example, it might be very different than any of your risks, right? So what technology has started to enable is underwrite and assess those risks at those very specific individual levels. And you can see that insurers are investing in that capability. The value of, um, artificial intelligence and underwriting is growing dramatically. As you see from some of those quotes here and also risks that were historically very difficult to assess such as networks, uh, vendors, global supply chains, um, works workers' compensation that has a lot of moving parts to it all the time and anything that deals with rapidly changing risks, exposures and people, and businesses have been supported more and more by technology such as ours to help, uh, gone for that. >>And this is a bit of a difficult slide. So bear with me for a second here. What this slide shows specifically for underwriting is how data-driven insights help manage underwriting. And what you see on the left side of this slide is the progress in make in analytical capabilities. And quite often the first steps are around reporting and that tends to be run from a data warehouse, operational data store, Starsky, Matt, um, data, uh, models and reporting really is, uh, quite often as a BI function, of course, a business intelligence function. And it really, you know, at a regular basis informs the company of what has been taken place now in the second phase, the middle dark, the middle color blue. The next step that is shore stage is to get into descriptive analytics. And what descriptive analytics really do is they try to describe what we're learning in reporting. >>So we're seeing sorts and events and sorts and findings and sorts of numbers and certain trends happening in reporting. And in the descriptive phase, we describe what this means and you know why this is happening. And then ultimately, and this is the holy grill, the end goal we like to get through predictive analytics. So we like to try to predict what is going to happen, uh, which risk is a good one to underwrite, you know, watch next policy, a customer might need or wants water claims as we discuss it. And not a session today, uh, might become fraud or lists or a which one we can move straight through because they're not supposed to be any issues with it, both on the underwriting and the claims side. So that's where every insurer is shooting for right now. But most of them are not there yet. >>Totally. Right. So on the right side of this slide specifically for underwriting, we would, we like to show what types of data generally are being used in use cases around underwriting, in the different faces of maturity and analytics that I just described. So you will see that on the reporting side, in the beginning, we start with rates, information, quotes, information, submission information, bounding information. Um, then if you go to the descriptive phase, we start to add risk engineering information, risk reports, um, schedules of assets on the commercial side, because some are profiles, uh, as a descriptions, move into some sort of an unstructured data environment, um, notes, diaries, claims notes, underwriting notes, risk engineering notes, transcripts of customer service calls, and then totally to the other side of this baseball field looking slide, right? You will see the relatively new data sources that can add tremendous value. >>Um, but I'm not Whitely integrated yet. So I will walk through some use cases around these specifically. So think about sensors, wearables, you know, sensors on people's bodies, sensors, moving assets for transportation, drone images for underwriting. It's not necessary anymore to send, uh, an inspection person and inspector or risk, risk inspector or engineer to every building, you know, be insurers now, fly drones over it, to look at the roofs, et cetera, photos. You know, we see it a lot in claims first notice of loss, but we also see it for underwriting purposes that policies out there. Now that pretty much say sent me pictures of your five most valuable assets in your home and we'll price your home and all its contents for you. So we start seeing more and more movements towards those, as I mentioned earlier, dynamic and bespoke types of underwriting. >>So this is how Cloudera supports those initiatives. So on the left side, you see data coming into your insurance company. There are all sorts of different data. There are, some of them are managed and controlled by you. Some orders you get from third parties, and we'll talk about Della medics in a little bit. It's one of the use cases. They move into the data life cycle, the data journey. So the data is coming into your organization. You collected, you store it, you make it ready for utilization. You plop it either in an operational environment for processing or in an analytical environment for analysis. And then you close on the loop and adjusted from the beginning if necessary, no specifically for insurance, which is if not the most regulated industry in the world it's coming awfully close, and it will come in as a, a very admirable second or third. >>Um, it's critically important that that data is controlled and managed in the correct way on the old, the different regulations that, that we are subject to. So we do that in the cloud era Sharon's data experiment experience, which is where we make sure that the data is accessed by the right people. And that we always can track who did watch to any point in time to that data. Um, and that's all part of the Cloudera data platform. Now that whole environment that we run on premise as well as in the cloud or in multiple clouds or in hybrids, most insurers run hybrid models, which are part of the data on premise and part of the data and use cases and workloads in the clouds. We support enterprise use cases around on the writing in risk selection, individualized pricing, digital submissions, quote processing, the whole quote, quote bound process, digitally fraud and compliance evaluations and network analysis around, um, service providers. So I want to walk you to some of the use cases that we've seen in action recently that showcases how this work in real life. >>First one >>Is to seize that group plus Cloudera, um, uh, full disclosure. This is obviously for the people that know a Dutch health insurer. I did not pick the one because I happen to be dodged is just happens to be a fantastic use case and what they were struggling with as many, many insurance companies is that they had a legacy infrastructure that made it very difficult to combine data sets and get a full view of the customer and its needs. Um, as any insurer, customer demands and needs are rapidly changing competition is changing. So C-SAT decided that they needed to do something about it. And they built a data platform on Cloudera that helps them do a couple of things. It helps them support customers better or proactively. So they got really good in pinging customers on what potential steps they need to take to improve on their health in a preventative way. >>But also they sped up rapidly their, uh, approvals of medical procedures, et cetera. And so that was the original intent, right? It's like serve the customers better or retain the customers, make sure what they have the right access to the right services when they need it in a proactive way. As a side effect of this, um, data platform. They also got much better in, um, preventing and predicting fraud and abuse, which is, um, the topic of the other session we're running today. So it really was a good success and they're very happy with it. And they're actually starting to see a significant uptick in their customer service, KPIs and results. The other one that I wanted to quickly mention is Octo. As most of you know, Optune is a very, very large telemedics provider, telematics data provider globally. It's been with Cloudera for quite some time. >>This one I want to showcase because it showcases what we can do with data in mass amounts. So for Octo, we, um, analyze on Cloudera 5 million connected cars, ongoing with 11 billion data points. And really what they're doing is the creating the algorithms and the models and insurers use to, um, to, um, run, um, tell them insurance, telematics programs made to pay as you drive pay when you drive, pay, how you drive. And this whole telemedics part of insurance is actually growing very fast too, in, in, still in sort of a proof of concept mini projects, kind of initiatives. But, um, what we're succeeding is that companies are starting to offer more and more services around it. So they become preventative and predictive too. So now you got to the program staff being me as a driver saying, Monique, you're hopping in the car for two hours. >>Now, maybe it's time you take a break. Um, we see that there's a Starbucks coming up on the ride or any coffee shop. That's part of a bigger chain. Uh, we know because you have that app on your phone, that you are a Starbucks user. So if you stop there, we'll give you a 50 cents discount on your regular coffee. So we start seeing these types of programs coming through to, again, keep people safe and keep cars safe, but primarily of course the people in it, and those are the types of use cases that we start seeing in that telematic space. >>This looks more complicated than it is. So bear with me for a second. This is a commercial example because we see a data work. A lot of data were going on in commercial insurance. It's not Leah personal insurance thing. Commercial is near and dear to my heart. That's where I started. I actually, for a long time, worked in global energy insurance. So what this one wheelie explains is how we can use sensors on people's outfits and people's clothes to manage risks and underwrite risks better. So there are programs now for manufacturing companies and for oil and gas, where the people that work in those places are having sensors as part of their work outfits. And it does a couple of things. It helps in workers' comp underwriting and claims because you can actually see where people are moving, what they are doing, how long they're working. >>Some of them even tracks some very basic health-related information like blood pressure and heartbeat and stuff like that, temperature. Um, so those are all good things. The other thing that had to us, it helps, um, it helps collect data on the specific risks and exposures. Again, we're getting more and more to individual underwriting or individual risk underwriting, who insurance companies that, that ensure these, these, um, commercial, commercial, um, enterprises. So they started giving discounts if the workers were sensors and ultimately if there is an unfortunate event and it like a big accident or big loss, it helps, uh, first responders very quickly identify where those workers are. And, and, and if, and how they're moving, which is all very important to figure out who to help first in case something bad happens. Right? So these are the type of data that quite often got implements in one specific use case, and then get broadly moved to other use cases or deployed into other use cases to help price risks, betters better, and keep, you know, risks, better control, manage, and provide preventative care. Right? >>So these were some of the use cases that we run in the underwriting space that are very excited to talk about. So as a next step, what we would like you to do is considered opportunities in your own companies to advance risk assessment specific to your individual customer's need. And again, customers can be people they can be enterprises to can be other any, any insurable entity, right? The please physical dera.com solutions insurance, where you will find all our documentation assets and thought leadership around the topic. And if you ever want to chat about this, please give me a call or schedule a meeting with us. I get very passionate about this topic. I'll gladly talk to you forever. If you happen to be based in the us and you ever need somebody to filibuster on insurance, please give me a call. I'll easily fit 24 hours on this one. Um, so please schedule a call with me. I promise to keep it short. So thank you very much for joining this session. And as a last thing, I would like to remind all of you read our blogs, read our tweets. We'd our thought leadership around insurance. And as we all know, insurance is sexy.

>> Narrator: From around the globe, it's theCUBE. With digital coverage of IBM Think 2021. Brought to you by IBM. >> Hello, welcome back to theCUBE's coverage of IBM Think virtual 2021. I'm John Furrier, your host of theCUBE. We've got three great guests here to talk about IBM Cloud Satellite and AI operations. Laura Guio, GM of Global Cisco Alliance. Matthew Angelstad, IBM Partner, Lead Client Partner for Canada, Financial Services. And Kuberan Kandasamy, VP of Personal Insurance at Economical Insurance. Folks, thanks for coming on theCUBE, this great panel on Cloud Satellite and AI ops. Thanks for joining me. >> Thank you, John. >> Thank you. >> Thank you, John, good to see you. >> Well, first, let's start with you. There's the General Manager for the IBM-Cisco strategic partnership. Tell us more about the relationship as cloud has become hybrid and it's pretty much determined that's the standard and multicloud is right around the corner. The programmability of the infrastructure is critical. And so, obviously you can see the modern applications are doing that. Take us through the IBM-Cisco strategic partnership. >> Absolutely, so John, as you know, and we've talked in the past, it's a 25-year relationship between IBM and Cisco, long-standing. Now, if you look at Cisco in the past, they've really been known as a networking and hardware company. But with the evolution of Cisco and how they're changing, they're really switching to be more around a supporting technology and in the services and software areas. With that change coupled with Kyndryl, our spin-off of what we were previously calling NewCo, we have an opportunity now to refocus all of the work that we're doing as IBM and Cisco going forward. You couple that with the Red Hat acquisition that we did almost two years ago, we've got a three-way partnership here that's really bringing a lot of value to the marketplace. Now, when you look at that from a hybrid cloud perspective, we announced our Satellite product, which is built on top of Cisco technology with IBM in that as well. And then really taking the security elements of what Cisco does and bringing all of this into the fold around that hybrid cloud solution. So, we're super excited about this. >> Real quick while I have you, you brought up a couple of key points. I just want to get to, I know we're going to get to it later, but the operating model has shifted. You mentioned with the NewCo and these relationships, ecosystem relationships and network effect, not just like packets, but like businesses and APIs are critical. This new cloud operating model is really the center of that equation. How does that relate into all that? >> So, you know, these operating models and how we're going to market here is changing dramatically. And you take what Cisco's doing, and you know, we've got a client here with us today, Kuberan who's going to talk about what they're doing with some of this technology. But really taking that at the core of how do you bring value at the client. What are they doing to get that hybrid cloud solution put into place? And then what are all those surrounding elements around software, managing the ops and things that we need? This is where IBM and Cisco couple together, really great value. >> Kuberan, you got teed up beautifully there. So, I want to go to you and then I'll go to Matthew after. But, okay, tell us more about this IBM-Cisco dynamic. You guys are a hot growth company doing very well and continuing to grow. And sure, post-pandemic is looking good too. So, take us through why you decided to engage IBM and Cisco. >> Sure. Sure, John, thank you. You know, to appreciate how we got here and why we asked IBM and Cisco to help us, let me first start by providing some background. Our journey started back in 2016 when we launched Sonnet, an MVP. Sonnet is our fully automated, direct-to-customer digital channel, where customers can quote and buy home and auto policies online without the need to engage anyone at Economical. Then in 2018, we launched Vyne, another MVP. Vyne is our simplified self-serve and digitized broker channel, where our broker partners can quote and buy home and auto insurance policies for their customers, again, without the need to engage anyone at Economical. Both Sonnet and Vyne have won awards for innovation and both have been industry disruptors. You know, after launch, we heightened our focus on enhancing business functionality and user experiences. Given that we had started with MVPs, it made sense for us to put a lot of emphasis on enhancements initially. And, you know, we maintain the platform level monitoring capabilities at a macro level. And the way we did the enhancements where we stood up agile pods, you know, focused on very specific business mandate. This approach delivered desired results for our business, but as our excitement grew for our upcoming IPO and our business started ramping up their growth plans, we needed to increase our focus on fine-tuning key components, which included enhancing our focus on stability and predictability for our Sonnet and Vyne platforms. And we needed the ability to look deeper and get into the micro level, so that we can monitor the pulse of, you know, every component of our user's journey across both Sonnet and Vyne, and we needed help with this. And this is where we engaged IBM and Cisco to help us through this journey. >> On that vision real quick. How does the AI fit in? More on the automation side or on the app side? I mean, I can imagine with that growth in the IPO, you think in automation, I'm assuming, can you elaborate quickly? >> Absolutely. So, I mean, if you think about it, it's a lot of data that we get, like it's all digitized, so we have a lot of data in there. And this is where, you know, the ability to be able to actually mine that data and actually be taking proactive steps in terms of predicting, having predictability and all that, that's where the AI ops comes in. But that's part of our journey through this. >> Yeah, it's good. I mean, the theme here is transformation is the innovation at scale. Matthew, you lead the Financial Services division in Canada. What are you seeing as the hot topics with your clients and how are you responding? How is IBM participating? >> Yeah, absolutely. And Kuberan was touching on this from Economical's perspective. They already have two leading digital solutions in market with Sonnet on the retail customer side in Vyne with their broker network. But what we're seeing even more so in the past year so of the pandemic is a dramatic acceleration of that end-to-end digital experience. So, our clients and their customers are expecting digital native solutions that are contextually personalized, highly secure and always available or extremely resilient, right? That obviously plays into IBM's capabilities and our joint capabilities with our partner ecosystem such as Cisco AppDynamics around hybrid, multicloud and AI. >> So, if you don't mind, if you don't mind following up on that AppDynamics point. Can you tell me a little bit more about how that solution played out and how that evolved? >> Yeah, absolutely. So, first off, this was based, again, on our long-standing relationship with Cisco AppDynamics that Laura was speaking about. And then the unique to what Kuberan in Economical was seeking of stitching together the data footprint across the infrastructure architecture but leveraging data in a business context. And I think that is the unique value that AppDynamics brings to this scenario here, is a market-leading solution that does bring together those multiple data sets but contextualizes them in a business context. So, you can understand from a user perspective that end-to-end journey right from initiation in the application, all the way through the technical infrastructure. And it becomes very preventative in terms of identifying and resolving potential issues before they even occur. >> So, AppD and these IBM services work well together right there. That's your key point, right? That's. >> Absolutely, and that's, the point is bringing together the best combination of solutions and services on behalf of our customer set. And this where AppDynamics and IBM and our other partners work incredibly well together. >> Well, we'll talk about the dynamics again. This is, again, this highlights the point of the better together combination here with the Cisco relationship and the IBM evolution you mentioned. What can other clients expect? I mean, this is going to be the playbook. (laughs) I mean, you got the Cloud Satellite. Take us through what this means. What does all this mean? >> Yeah, absolutely. I'll start, and maybe even Laura can add as needed. But from an IBM perspective, absolutely. We're going to work with our partner ecosystem in the hybrid multicloud world. So, we've really evolved whether it's IBM Cloud, AWS, as some of our clients, including Economical and others. Microsoft Azure, Google. It is about bringing those together regardless of strategic decisions made on cloud platform, but understanding how the applications play together. And again, stitching together the data across those application sets to drive value out of it. This is where we're really seeing the evolution of IBM and our partner ecosystem, and the evolution of IBM services as well. >> Awesome. >> Yeah. And if you really look at what Cisco's trying to do, they've declared they're going to be in this hybrid cloud space. They bring the elements to the solution when you look at networking. We look at some of the security. And then when we start looking at how this combines with edge technology, we really start getting combinations between the IBM technology, the Cisco technology and how that completes a picture in a solution for the client. >> I love the end-to-end story. I see hybrid as distributed computer in my mind and now you've got multicloud as subsystems and all is going to have to be operated together. And the software that makes that happen. And I can see tons of head room opportunity there. Kuberan, talk about what you guys are seeing as results now. Because this is where you start to see the conversation shift to. It's not just go to the cloud anymore, it's make the cloud operational on all environments. That's really what people want to see. Can you share what you're seeing as a result and where do you go from there? >> Yeah, absolutely. You know, what's awesome about all of this is first of all, in a very short time the team which really was composed of a cross-functional and a highly collaborative group of people, they've already delivered some key pieces that are giving us line of sight into what's going on for a business solution. And, you know, the implemented scope is already detecting symptoms and allowing us to be very proactive and it is also helping us to complete root cause analysis faster. It's helping us to reduce defect linkage through our quality assurance practices. So, you know, for us, as I mentioned earlier, this is a journey like, you know, unlike traditional approaches where implementations are driven by predetermined scope. We are changing the mindset, specifically because we're using a lot of telemetry and continuous discovery in helping transform how our platform is important. You know, it has become part of our philosophy where business and technology are now working closer together. And our vision is to navigate continuously towards having a highly automated monitoring solution that leverages cognitive insights and intelligence. So, you know, to be able to have a robust self-healing capability. And this is where it kind of ties with the whole cloud capability, because now you can actually enable the self-healing capabilities and with AppDynamics bringing in the dynamic capture of issues happening and things like that. And if you kind of step back a bit and if you think of this approach, this is no different than how we envisioned and how we implemented both Sonnet and Vyne, where it was a fully digitized end-to-end solution that provides services and value for, excuse me, for our customers. Right? So, hopefully that kind of stitches the picture for you. >> That's awesome, great insight. Laura, Matthew, Kuberan, thanks for coming on theCUBE. In the last minute that we have, let's go down the line. Laura, Matthew and Kuberan, we'll start with you guys. What's the bottom line for IBM and Cisco's relationship with the Cloud Satellite and AI. What should people walk away with? What's the bumper sticker? What's the summary? >> So, as IBM invest more and more in these strategic hybrid cloud solutions industry-focused, it's really bringing an industry-focused solution to clients without us having to reinvent that every time. And as you've heard from Kuberan here, I mean, we're bringing that value to our customers. >> All right. Matthew? >> Yeah, I'd just like to add, and this is a great example here of being able to co-innovate and collaborate with our partners and with our clients, Economical in this case, to evolve these solutions. And as Kuberan has stated, this is the first step in a journey here and there's lots of exciting things to come. >> Kuberan, take us home, final word. >> Thank you. What I would say is, what we've learned from this is really standing this stuff in more like a garage style kind of a situation where you can actually get something going rapid and you get business results and you start seeing ROI very quickly. So, that's the benefit I've seen. >> Awesome, great points. IBM and Cisco better together. This ecosystem, the co-creation, the new network effects is the new dynamic in the marketplace. This is the table stakes. Thanks for coming on, thanks for sharing the insights. Thanks for coming on theCUBE, appreciate it. >> Thank you. >> Thanks a lot, John. >> Okay, IBM Think 2021. I'm John Furrier with theCUBE. Thank you for watching. (cheerful music)

>>From around the globe. It's the cube with digital coverage of IBM. Think 2021 brought to you by IBM. >>Welcome to the cubes coverage of IBM. Think the digital experience I'm Lisa Martin. I've got two guests with me here today. Ryan Dennings joins us manager of ECM solutions at auto owners insurance company, Ryan, welcome to the program. Thank you. And Michelle Christianson is here as well. VP of enterprise report management practice at end choice, Michelle. It's good to have you on the program. Thank you. Thank you. So let's, let's go ahead and start with you. You guys are a customer of and choice and IBM, talk to us a little bit about auto owners company. I know this is a fortune 500. This was founded in 1916. You've got about nearly 3 million policy holders, but give us an overview of auto owners insurance. >>Sure. So I don't want to said insurance is an insurance company. That's headquartered in Lansing, Michigan. We write insurance in 26 States throughout the United States. Um, just by our name being auto owners insurance, which is how we started. Um, we write all personal lines, commercial lines and also have a life insurance company, >>So comprehensive and that across those nearly 3 million policy holders. Michelle, tell us a little bit about end choice. I know this, you guys are an IBM gold business partner, but this is end choices first time on the cubes. So give us a background. Sure, sure. Great. So in choice are an IBM gold business partner. Uh, we have had 28 years success with IBM as a business partner. Our headquarters are in areas, um, Austin, Texas, and, uh, Tempe, Arizona, as well as Shelton Connecticut. We cover all of North America and we are a hundred percent focused on the IBM digital business automation space. We have about 500 customers now that we've helped, uh, through the years. And we continue to be a leading support provider as well as an implementation partner with all the IBM solutions. And talk to me a little bit Michelle, about how it is that you work with with, um, auto owners. >>So we assisted auto owners recently in their digital transformation journey and they were, uh, dealing with an antiquated product and wanted to get for moving forward, you know, provided better customer satisfaction, um, experience, um, for their clients agents. And so we partnered with them and with IBM and bringing them a content manager on demand solution as well as navigator and several other products within the IBM digital business automation portfolio. Excellent client. Oh, sorry Michelle, go ahead. Nope. That's that's fine. All right, Ryan, tell us a little bit about auto owners, your relationship with IBM and choice and how is it helping you to address some, the challenges in the market today? >>Sure. So I don't know if this has a long-term relationship with IBM. Um, originally starting back as we go as a mainframe customer and then, you know, more recently, um, helping us with different modern technology initiatives. Uh, they were instrumental in the nineties when we created our initial web offerings. And then more recently they've been helping us with our digital business automation, which has helped us to, um, mature our content, offering it. >>So you have had a long standing relationship with IBM. Right. And you mentioned the nineties, ah, a time when we didn't have to wear a mask on our faces. So a couple of decades it goes back. Yeah. >>Yes. For sure. Yes. Even further than that back, you know, back into the seventies from the mainframe side of things, >>Uh, the seventies, another good time. All right. So Michelle had talked to me a little bit about what end choices doing with IBM solutions to help auto owners from a digital transformation perspective is as I said, this is a company that was founded in 1916. And I always love to hear how history companies like that are actually working with technology companies to facilitate that transformation a lot harder than it sounds well. That's correct. Just as I mentioned, we're focused on helping customers develop their strategies, their digital strategy and creating those transformative solutions. So we're helping organizations like auto owners, um, with their journey by first realizing, um, their existing, existing, digital state, what challenges they might have and what needs they might need. And then we break that down or we deconstruct those technical and process. And finally we re-invent, um, their strategic offering with modern capabilities. >>So we're focused on technologies like RPA machine learning, artificial intelligence, they're more efficient, scalable, and secure. So any way we can bring those technologies into the equation we go forward. So this offers us, our clients, um, smarter and more into intuitive interfaces, creating basically a better user experience and a better user experience then becomes disruptive to their competition. So they gain a better place in the market space. Ryan talked to us about that process as much as you were involved in it. I liked that Michelle said, you know, we kind of look at the environment, we deconstruct it and then we reinvent it. Talk to me about how IBM and enChoice have ha has helped auto owners to do that so that your digital infrastructure is much more modern. And I presume much more resilient when there are market dynamics like we're living in now. >>Yeah, for sure. So, you know, we've, we've gone through a couple of transformation journeys at auto owners with IBM. Um, when I started the team about seven years ago, we originally started using file NATS and data cap and case manager and content aggregator, um, as our first, um, movement from a traditional, um, platform that we had for content management into a more modern platform. And that helped us a lot to improve our business process, um, improve how we capture content and bring it into the system and make it actionable more recently, we've been working with Michelle and the team on our, um, migration to a content management on demand platform. And that's really going to be transformative in terms of how we're able to present content and documents and bills, um, to our agents and customers, um, to be able to transform that content and show it in ways that are, um, important, um, for our customers to be able to see it to, um, engage from, with auto owners in a, in a digital era. >>So Ryan, just a couple of questions on that is that, is that a facilitation of like the digitization of processes that had some paper involved cause you guys have about 48,000 agents. So a lot of folks, a lot of content, tell me a little bit more about how, um, that like content manager on demand, for example, and what you're doing with ETF, how has that really revolutionizing and driving part of that digital transformation? >>Sure. So, uh, you know, there's two parts to that in terms of that content management management on demand journey. Um, one is the technology portion of it, but IBM's provided and that suite of software gives us some functionality that we haven't had in the past. Um, specifically some functionality around searching and searchability of our content, um, that will make it easier for people to find the content that they're looking for, um, ability to implement, uh, records management policies and other things that help us manage that content more effectively, um, as well as, um, some different options to be able to present the content, uh, to our customers and agents in a, in a better and more modern way. Um, and I'm choices role rolling that has really been, sorry, guide us on that journey, um, to help us make the right choices along the way on the project and help us get to a successful implementation and production. >>Excellent. Michelle, talk to me about hybrid cloud AI data, a big theme of, uh, IBM think is your, how is enChoice using hybrid cloud and AI, you mentioned some of the ways, but kind of break into that a little bit more about how you're helping customers like auto owners and others really take advantage of those modern technologies. Well, sure, sure. So, um, of course with the Calpec offerings that IBM has come forward with and where we focus in the cloud Pak for automation, um, several of those offerings are, some of them are, um, uh, built specifically to, uh, survive or to, to, um, be hosted in a hybrid environment. And as we working with auto owners, um, transforming their platforms going forward, for example, they just invested in, in a, um, a, uh, I just lost the word here. I, they just invested in a new platform mainframe platform where they're going to be leveraging the red hats and from there they'll drive forward into containerization. >>So, um, Ryan mentioned, uh, some of the ways that we'll be presenting the content for his agents and his customers and a particular, um, that entire viewing platform itself can be moved to a containerization state. So, um, so it's going to be a lot easier for him to transition into that and to maintain it and to management manage it. And of course, um, just that whole, um, the ease of function around it will be a lot easier. So we are in our area as an IBM business partner. Um, we work with, uh, these solutions to try to stay ahead of the game, to try to be able to assist our customers to understand what makes sense, when is it time to move into those? Um, it's great to take advantage of the new stuff, but nobody wants to be, you know, the bleeding game. We want to be the leading game. >>And, um, so that's some of the areas we focus with our clients to really stay tight with the labs tight with IBM and understanding their strategies and convey those and educate our customers on those excellent leading edge. Ran, talk to me a little bit. I love this a bank, uh, sorry. Uh, an insurance company from the early 19 hundreds moving into the using container technology. I'll have stories like that. Talk to me a little bit about hybrid cloud AI and how those technologies are going to be facilitators of the continuation of the digital transformation and probably enabling more opportunities for your agents to meet more needs from, from your policy holders. >>Yeah, for sure. So, uh, first and foremost, um, we were a red hat open shift, uh, customer before IBM acquired them and we were doing microservices development and things like that on the platform. Um, and then we were super excited about IBM's digital business automation strategy to, uh, move to cloud pack, um, and have that available for software products to run on OpenShift. Um, at the end of last year, we updated our license thing so that we can move in that direction and we're starting to, um, deploy, um, digital business automation products on our OpenShift platform, which is super exciting for me. It's going to make for faster upgrades, more scalability. Um, just a lot of ease of use things, um, for my team, um, to make their jobs easier, but also easier for us to adapt new upgrades and software offerings from IBM. Um, there's also a number of products that are in the, um, containerized or OpenShift only offering as they're initially coming out, whether it's mobile capture or automated document processing, um, the same a couple, um, and those are both things that we're looking at auto owners to continue to mature in this space and be able to offer more functionality to our associates, our customers, and our agents, um, to continue to grow the business >>Very forward-thinking uh, awesome Ryan, thanks for sharing with us. What auto insurance or auto owners insurance is doing, how you're being successful and how, how you've done so much transformation already. I want to throw the last question to Michelle. Take us out Michelle with what's next from end choices perspective in terms of your digital transformation. Um, well we have been a hundred percent focus on helping all of our customers develop their digital strategy and, uh, and creating their own transformative solutions. So as we continue to work with our clients, take them through the journey. Um, as I mentioned before, we try to encourage them not to focus on the, the technology itself, but really to focus on creating their exceptional customer experience when driving their digital strategy. And we see ourselves as, you know, helping transform our clients experience such that, you know, customer experience becomes what enChoice does best. >>So we see not only our own organization going through the transformation, but making sure that we're taking our clients with us and with 500 clients, we're, we're really busy. So that's always good. That is good. It sounds like the last year has been, uh, very fruitful for you. And I love that you mentioned customer experience, Michelle. I think that is so important and as well as employee experience, but having a good customer experience, especially these days. Table-stakes I thank you both so much for sharing what you guys are doing with IBM solutions, the transformation that you're both of your companies are on, and we look forward to hearing what's to come. Thank you both for your time. Thank you. Thank you for Rand Dunnings and Michelle Christiansen. I'm Lisa Martin. You're watching the cubes coverage of IBM. Think that digital experience.

>> Live from Las Vegas, it's theCUBE. Covering Dell Technologies World 2019. Brought to you by Dell Technologies and its ecosystem partners. >> Hi, Lisa Martin with theCUBE, live day three of theCUBE's double set coverage of Dell Technologies World 2019 I am with Stu Miniman. We've got one alumni back. We've got Gil Schneorson, Senior Vice President and General Manager of Vxrail. Gil welcome back. >> Thank you nice to be back. >> And it's show and tell you brought Niv Raz CTO of Harel Insurance one of your successful customers, Niv it's great to have you on the program. >> Thank you and great to be here. >> So Niv let's start with you. Give our audience an understanding of Harel Insurance where you're located, what it is that you do and then we'll get into why think Dell EMC is so fantastic. >> Harel Insurance is a insurance company doing a life, now life insurances very wide portfolio of business products in the insurance and investments in Israel. More than 5000 employees and three million customers managing around 240 billion shekels in 2018. So it's very innovative company to work in. >> So Niv interesting. Dell has a podcast and I'm just given a little plug here 'cause at the gym this morning the latest episode by Walter Issacson talks about transformation going on in the insurance business. Some people think, oh insurance has been around a long time, I mean heck to the Roman Era when they had some of this but today Insurance is changing fast. Can you give us at a macro level, give us what are some the changes and stresses on the company and how's that impact your job. >> It's funny you mentioning that. In 2015 our CEO has declared innovative program named Recalculating Routes. The purpose of the program the strategic plan was to take a role from traditional insurance company to more digital transform, data transform. We Israel has the brokers. The brokers are our sales person but once the customer and the sales part, the onboarding part, you want a more innovative service after that. The post service part is very hard in insurance and we investing a lot to make the post service customer experience very advantaged. >> We talk a lot about customer insurance at every, oh sorry, customer insurance, well that's important too, customer experience is the word I was going for. It's essential right because in 2019 customers of any type of product or service have so much choice. So talk to us Niv from looking through that lens of delivering an outstanding customer experience obviously your sales folks need to have innovative technology to deliver that outstanding customer experience. But when a company says we've got to transform digitally we've got to stay ahead of the market, delight our customers Where do you start? Talk to us about maybe a phased approach that you're taking to digital transformation. >> Digital transformation is all about how customer experience feel like in your environment. So if a person entering your website and trying to do some post service and running into some old fashionable process that is very hard to him and its really frustrating to do that. And actually if I look about what our approach about it, we're thinking about the digital transformation, we're thinking about how to take the onboarding part for our brokers, the post service for our customers, to make the process, the services we are offering to our customers easy as possible to just can submit. >> All right so Gil let's bring you into the discussion here. And I think back Converge Infrastructure, Hyper-converge Infrastructure you've been riding the rocket ship that is Vxrail, digital transformation wasn't the leading use for that when we started. It was simplification driving that wave of virtualization, we've heard Vxrail everywhere in the discussion this week. It was like all of these different cloud pieces, what's underneath them, VxRail. Help us connect the dots, the transformations that your customers are going where VxRail and the new solutions built with VxRail help enable your customers. >> Yeah thanks Stu. We talk about a digital transformation a lot. Reality is that many of the customers, not all of them are transformative like Harel Insurance right. Many of them look at ATI and VxRail as the next simple tech refresh. They see the agility, they see the economical benefit but there's a growing majority of customers who look to this is as transformational. And so that's where you see ATI and VxRail specifically in our case starting to grow beyond being an infrastructure for workloads to be an infrastructure for their hybrid cloud and multi cloud environment. So what is so exciting about this show is because we've been very successful we're growing very fast, but by putting this building block in many of our customers' data centers they've made the choice that will enable them to now embark on a more transformational strategy. And I think we demonstrated in the last two days that hybrid cloud is here and it's sellable, operational and with VxRail and the integration with VML cloud foundation and the ability to add and burst into a cloud move workloads It's here and its now, I thinks that's what's nice about this whole thing. >> All right so Gil it's great for you to say it even as an analyst as a media organization for us to say it but what we love is that you brought a customer here to tell us the reality as to where cloud fits into your overall discussion. And I would love your feedback as to what Gil's saying. What's the reality in your world and the impact on your work >> I would connect the previous question this one because it's like a very rolling on questions about it. So you as the customers your expectations about the company is to do every operation from everywhere very easy way and the mobility and the digital transformation itself all the mobile applications, all the things that's taking the customer experience to the next level will took the organization to a phase that I need understand how to scalable the systems. So in this journey when you're looking about digital transformation you must have a infrastructure that support the scalability, the elasticity, the availability that the customer demands. You don't think to yourself that you are enter some E-commerce customer and they will send you on application. sorry Sir, we currently offline the management reasons or maintenance reasons. That thing in 2019 you will not think about and it's not be acceptable. So to do a scalability our multi cloud strategy in Harel is to have infrastructure free environment to focus on the service applications and not to focus on the infrastructure management part. That's the big concerns of our IT teams was how to care about support and matrix's and compatibility and maintenance and when you go into the private cloud environment, the private cloud environment, that's VxRail on the bottom and VML cloud foundation on the top allow Harel is to start the journey to a phase that said okay we're going to our infrastructure free road map. >> Tell us about the outcomes that for example go back to, what we were talking about your brokers who need to be able to deliver any service. I imagine they're out in the field sometimes with customers depending on the types of services that they need to deliver. What has been some of the feedback or maybe the outcomes for the brokers. Are they able to do their jobs faster, deliver quotes faster to customers. What are some of the exciting outcomes that you're seeing as a result of the infrastructure that Dell EMC is helping you to establish. >> Part of digital transformation we're talking about micro servicing a lot of old virtual machines I'm saying that. So service applications on the password virtual machine now your micro services, why you micro servicing it because in 8:00 a.m, perhaps there is 20 persons that's selling your policies but perhaps on the 11:00 after some TV show said something about Harel you can have thousands of customers entering to your website. So how you can support that? So again brokers need the tools to support the operation, the sales operations and the customers need the tools to support the post service for themselves, how to claim, how to do claims how to do more preventives aspects of insurances. So basically again when you're looking about what exciting is, is the reality that I'm seeing a process of a customer and is saying, wow that was easy. So taking the digital transformation to make our customer experience better. >> All right Gil help us zoom out a little bit. We talked to one customer here but the business overall joint product development between Dell EMC and the VMware teams is something that we think was transformational and helped accelerate the HTI growth. What are some the big drivers what's changed in the business. Give us the overall update. >> Yeah look, I think that when we discovered that working together pays off through our joint leadership through examples like VxRail and others we started looking at every part of the business and how collaboration could enable us to add even more value and any value transfer to finances and there's a very strong interest in so this recent innovation we've introduced with integration with cloud foundation, people don't realize how much work goes into integrating two products regardless, even between 1 company you're talking about engineers co-location, you're talking about joint sprints you're talking about test fests, design workshop, customers interaction and so, but you know what I mean, it pays off. You deliver a new outcome that didn't exist before now with VCF and VxRail you can have a full life cycle management of the entire VMX stack and the entire hardware stack drivers, framework everything life cycled together, it's a very, very impressive outcome and it's ready now and I'm really thinking that shift is going to be more than just ATI, people are going to start embracing the full stack because they can, because we're simplifying it. In addition to that Stu I think it's important to understand or I'd like the people to know that the other way we're taking the ATI stack and the full stack is into much more intelligence so machine learning and predictability all the way eventually to remediation and so in this show we introduced the analytical consulting engine for VxRail and we put it out there as a field trial, as an early access. The thought process is we have a very large amount of intelligent customers that could tell us where they need this to take them. What's exciting about it is that every product these days is trying to be intelligent because we have a full stack we have a lot of context, a lot of things we could correlate. So we're very excited about this and we're hoping that our customers will participate in that design, I'm sure Harel will as soon as we can give it to them, the access and, not only full stack but make it much more intelligent, I think it's going to be very exciting year til next time we speak. >> Harel you have? >> Something to say about it. We are customers, us as an organization understand the public cloud allowed us to be infrastructure free and now they said okay some workloads are good for public cloud some workloads are good for private cloud and the multi cloud approach that VMcloud Foundation gives us the infrastructure free to just focus on the services. You need to understand the manageability of traditional infrastructure is very costly. Why? You need to manage it, you need to support it, you need to upgrade the frameworks, the buyers, the drivers and all the time to be concerned about if everything is supportable, how you do that all the job and again once you taking the VxRail as a hardware platform for that and the VMcloud foundation the software you getting a complete life cycle that assist you to just focusing about to be a service broker just add new services to the exist environment. >> Well Niv, thank you so much for stopping by theCUBE and sharing with Stu and me where you guys are on this digital transformation journey, the successes you've achieved so far with Dell EMC, Gil again always great to have you on the program and we can't wait to hear more next year maybe Ace is going to give us some really insightful insights that will be groundbreaking. >> I believe so. Thank you very much. >> For Stu Minneman, I'm Lisa Martin. You're watching us on theCUBE, live from day three of our coverage of Dell Technologies World. Thanks for watching. (upbeat music)

>> Announcer: Live from Las Vegas, it's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to theCUBE's live coverage of ServiceNow Knowledge18 here in Las Vegas, Nevada. I'm your host Rebecca Knight, along with my co-host Dave Vellante. We're joined by Michael D'Ippolito. He is the VP of Run Services at Nationwide Insurance. He's coming to us straight from Columbus, Ohio. So thanks so much for joining us. >> Thanks for having me, appreciate it. >> So tell our viewers a little bit about what you do. What is Run Services? What do you do at Nationwide? >> Sure, yes. We are a part of what we call our infrastructure and operations group and we're really an enterprise services group. Basically in my resposibility, I have resposibility over our data centers, over what we call our enterprise command centers. Pretty much the eyes on glass, 24 by 7 operations that kind of keeps everything running. Also, I have resposibility for all our run processes. So our ITSM processes, both from a process ownership and a process management. So that's where ServiceNow really comes in. >> So we've talked about this before, Mike. It's just in terms of the insurance business. Some of the things that are driving that business. We always talk about digital disruption but it's really, the insurance business hasn't really been digitally disrupted. Maybe it's coming. Not maybe, I'm sure it's coming. But what's driving your business today and how important, important is the wrong word. How much of a factor is digital in terms of the decisions that you make on a day-to-day basis? >> Well, it's huge. You know, as you probably heard we're really at a big inflection point in the world today and we are going to be disrupted and we actually focus on how can we disrupt ourselves because somebody else is going to. It's just a matter of time until Amazon wants to get into the insurance business. >> Dave: That's right. (Rebecca and Dave laugh) >> We laugh but you know. >> No, I know they're planning it. >> They're selling groceries. You're not really competing with other insurance carriers anymore. You're competing with Amazon and Google for that experience, that user experience, that ease of use, that direct interaction. You know, when you think about it, home and auto insurance, it's kind of a commodity. It's like buying your gas and electric. So you've got to be able to create that direct experience to our members, to our consumers just like an Amazon would. >> We hear so much of these buzzwords at this conference but also just in general in the technology industry. Automation, streamlining, this emphasis on customer experience. How do these play in to your digital transformation in terms of what you're thinking about at Nationwide? >> Yeah, right now one of our big drivers is what we call the need for speed. Speed is everything right now in terms of staying competitive, coming out with features as fast as possible. And when you think about it, the only way to really get fast is you have to be automated, right? You can't be manual and fast. So really now we have to look at, how can we automate everything and how do we treat infrastructure like software, basically, like code. And we can roll out changes any time, any day, any hour, versus the old days when you had these big releases once a month of your applications. Those days are kind of gone. >> So I got to ask you about, I mean, one of the things that cloud brought was this notion of self-service. There's certainly pressure for customers to do self-service. You see that, they're going to comparison shop, they're going to pick their package, et cetera. So that's part of the disruption and then the other part is potentially on the actuarial side, the actuarial robots. What do you see happening there and how is that affecting your business? >> That actually is an interesting use case. That's probably where big data is really coming into play. So for example, in auto insurance, your rates change every six months and what we do is we look backwards and say how did you drive over those last six months? Did you have accidents? Did you have tickets? You know, et cetera, and then we price you accordingly. Well, now with the information, the data we can get out of your vehicle 24 by 7, we can price you every day. So we can look at basically what's called metered insurance or insurance by the mile that we use the technology to enable that kind of a pricing model. >> And I would imagine you're at the point where you can begin to predict riskier situations. >> Absolutely, and anticipate it just like they do in health care, right, so, you know, not much different but yeah, that's definitely a new thing coming. >> You're collecting all of this data. I mean and this is the thing about the collection of the data is the easy part really but it's really knowing what the data is telling you and then how to act on the data in the right way. >> Yes. >> So is it a lot of trial and error or how are you determining what insights are the actionable ones? >> Well, as you know, a very popular skill out there are data scientists. Data and analytics, that's huge right now. So getting people who have that skill to understand the so what from the data and to be able to make good decisions on it, and then how do you even automate that? That's a big field right now actually. >> We're obvioulsy ways away but you see it in the news pretty much every day. You go to Silicon Valley, you can't miss it. What's the conversation like around autonomous vehicles? Because everybody says, well the problem is who's liable if something goes wrong and then you see that big accident, the Uber situation. What's the conversation like internally around that? >> It's going to be here sooner than you think. It's already here. You're seeing it more and more. You're seeing every car getting smarter now. It's getting closer and closer. It's an inevitable future. We are going to have those. And so now we have to look at what is going to be the actual model around that? We'll figure that out. But as you know, in a lot of these industries, the technology has really been ahead of the regulation. When Uber came out, there were basically discussions about coverage and liability and all those kinds of things. So normally in any fast-paced technology, usually it leads and then the rest follows. It'll get figured out. >> And I think you will figure it out because you guys are good with numbers. (laughs) Insurance companies can always figure out the cost of insuring something, right? >> Right. >> Should we envision kind of a hybrid shared risk model between the consumer and the technology supplier? Or do you think it's all going to be in the consumer? >> Well, it's hard to say exactly but we know there will be some compression in insurance because of it. And really, you might get to the point where the software is what gets insured and not the person. >> Right. >> Right. So we're already talking to automakers about how do you insure the actual vehicle versus the person driving it because they're not driving it anymore. >> That's a shock to the 100-plus-year-old system, isn't it? (laughs) >> Absolutely. Again, it was a shock when people said, you mean we're not going to use horses anymore? >> (Rebecca laughs) Good point. Point taken. >> So you go through time and there's these big revolutions that happen and I think we're approaching one. >> Talk about the ServiceNow situation. We've talked about your journey before but maybe remind us of that, where you are, what you thought of the new announcements today, maybe give us an update. >> Yeah, we're excited. We've been on ServiceNow for almost three years. Over the last year, we've made tremendous progress in terms of, we have a program now called IT Simplification and a little shout out to my partner Rick Schnierer who is my AVP who runs the platform for us. They do a great job. I'm kind of like the business partner to them. Right now what we're doing is it's a focus on configuration management and we're slowly retiring legacy systems and repositories across the company into the one single source which is in ServiceNow. We're also really focused on hardware and software asset management. Getting an understanding of all the assets we own and constantly scanning the network to understand who's connecting in and if it's a threat, if it's a good guy or a bad guy, that's important. Very important right now. And then lastly, like I said, the need for speed. How can our operations side support this need for increased pace of development? Because once you put it in, it's got to operate, right? And it's go to run. >> So where are you at today? Mostly, so ITSM, doing SecOps or did I infer that or no? >> Yeah, we have all the ITSM in. Actually we're moving to Kingston this weekend. We're doing that upgrade. We are involved with the HR module. We're bringing in Workday as our platform in July and ServiceNow will integrate with that. We're looking at the portfolio management. So now that we have the ITSM under control, we're slowly looking at where else can ServiceNow play for us? Cloud's a big play for us so, you know, we're right now working with a cloud provider and then there's a lot of APIs and interfacing back into ServiceNow. So that's going to be important for us. >> And you're saying for infrastructure? Cloud for infrastructure? >> Correct. >> Or infrastructure's a service? >> Correct, right now, well, we focus on SaaS first. Anything that can be SaaS, we want to go SaaS. ServiceNow is a perfect example. Salesforce.com, all those kinds of SaaS solutions. Then IaaS and PaaS are also important, right? So right now, by the end of 2018, we'll only be about probably 10% external cloud and 90% on-prem, but three years from now, it'll be the other way around. We'll probably be 90% cloud. >> Awesome. >> What keeps you coming back to Knowledge? >> You know, it's just the, look at this crowd. >> I know, it's true. >> I mean, the networking, the peers you meet. It's been so great because you have that time of year where you can share ideas, share stories, and all that. Where ServiceNow is going with the platform is always so interesting and appealing. We're really interested in hearing and getting to that agent workspace which I think would be great for internal, like our help desk services. So, more automation inline with where we're going. We think it's a great platform for that. >> Rebecca: Great, well Michael, thank you so much for coming on theCUBE. It was great talking to you. >> Great, thank you. >> Thanks, enjoyed it, thank you. >> I'm Rebecca Knight, for Dave Vellante, we will have more from theCUBE's coverage of ServiceNow Knowledge18 just after this.

from San Francisco it's the queue covering Red Hat summit 2018 brought to you by Red Hat hey welcome back everyone's two cubes live coverage here in San Francisco California at Moscone West I'm John for a co-host of the cube with my analyst this week co-host John Troy a co-founder of tech reckoning our next guest is Dave Abrams executive general manager of data at Insurance Australia group welcome to the cube thanks for having me we were just you know talking on an off-camera before we came on about the challenges of data as cloud scale you guys have been around for many many years yeah you're dealing with a lot of legacy yeah you guys out right on the front step what's going on with you take a minute to explain what you guys do in your role in your environment absolutely now it's you know so we're we're large insurance trying we we've got offices in New Zealand and across Southeast Asia so we're kind of expanding out in our in our reach but um we've been around for a hundred odd years and and we've really grown a lot through merger and acquisition over time and so what that's meant ah this is a bit of a byproduct of those kind of merge and acquisition process is that data has been siloed and fragmented in different brands and different products and so it's been hard to get for example just a holistic view of a customer what does the customer have all the products they hold you know are they a personal customer as well as a business caste and all that sort of stuff doesn't kind of line up so we've had that big challenge in we've been working over the last couple of years to even just kind of consolidate all that unify that data into one platform so that we can see across the group from from a holistic perspective and and build that single view of customer and that's now helped us sort of understand you know what our customers are doing in and what's important to them and how we can better support them and yeah and offer better services and what are you doing here at Red Hat this week what's what's the objective what are you doing what do you have you know I'm speaking you talking the folk what's the what's the solution with Red Hat well so yeah we're primarily here as a result of the Innovation Awards so we you know we were nominated and we're successful in our in our award for that category in our region which was wonderful we we're really honored with that so we're here because of that we sharing our customer story with the rest of the Red Hat team and the rest of the open-source community around really what it's meant for us to use open source within a big corporate that's kind of traditionally been based on a lot of vendor technology right a live Ben driven predominantly by the big tech vendors you know that have come in and sort of helped us build big solutions and platforms which which were great and wonderful in the fact that you know they they were there and they lasted like ten years plus and that was all good but now because things are changing so fast we need to be more adaptable and and unfortunately those platforms become so entrenched into the organization and and and sort of lock you in that it's a to adjust into it to be adaptable you can't you can't take it out very easily it doesn't even stack up sometimes from a business case so why would we take that technology out we'll just have to dig deeper and we'll just have to spend more right so we're trying to we're trying to re reverse-engineer some of that and the role open source for you guys have been part of new systems recruiting talent everything director what's been a benefit the impact of absolutely it's huge inand you're right I think one of the biggest benefits for us that that really plays out is there is in the talent side right for our people to say not only are we transitioning our organization as a whole and the way we the way we operate but we're really transitioning out people we're transition from kind of the work force that we that we had and they've got us to where we are today but we're now setting ourselves up for the workforce of the future and it is a different skill set it is a different way of approaching problems so you know bringing bring this new technology to the table and allowing people to experiment to learn and to update their skills and capabilities exactly what we what we need for our company so we're pushing that hard yeah that's great it's like a real cultural shift give me maybe transfer transfer over a little bit to the actual tech problem you had right so you multiple countries multiple data warehouses multiple systems yours so what were you looking at and then what was the solution that you kind of figured out and then when yeah when so when I first started the roll a couple of years back we had something like 23 different separate individual data warehouses there were all sort of interconnected and dependent on each other and had copies of each other in each other and it was just it was a little bit of a mess so so the first challenge was to really sort of rationalize and clean up a lot of that so so that's that's what we spent a fair bit of time upfront doing which was basically really acquiring the organization's data from a massive amount of call source systems so in the vicinity of I think we take data from roughly about 150 to 200 call systems and we want to take that data essentially in as close to real time as we possibly can and pump that into her into a and to a new clean unified data Lake right just to make that data all line up so that was the big challenge in the first instance and then the second instance was really a scale problem right so getting the right technology that would help us scale into you know because we've predominately been using our own data centers and keeping a lot of stuff you know in that sort of on-prem mode but we really wanted to be able you know self scale to not only to be able to you know take advantage of cloud infrastructure just to give us that extra computing that extra storage and processing but really also to be able to leverage the the commoditization that's happening in cloud right because you know all all cloud companies around the world commoditizing technology like machine learning and you know artificial intelligence so that it's it's it's available to lots of organizations and the way we see it is really that that we're not going to be able to compete or out engineer those those companies so we need to make it you know accessible and available for our people to be able to use and leverage that innovation on our work as well as is you know do some some smart stuff ourselves are using infrastructures of service OpenStack or what's your solution I mean what are you guys doing solution is yet to use I've been stack is is our first sort of real step into infrastructure-as-a-service so that's really helped us set up like I was showing this morning set up the capability for us to turn our scale in a really cost-efficient way and we've ported a lot of our traditional dedicated you know applications on infrastructure that you know was like appliance based and things like that on to OpenStack now so that we can it gives us a lot more portability and we can move that around and put that in the place where we think gets us the best value so so that's really helped I'm kind of curious you work with Red Hat consulting and was I was I was curious about that process did you was that the result of a kind of a bake-off or we were already Red Hat customers and said oh hey by the way can you give us some advice yeah it really came about I mean we've been working with Red Hat for many years you know and it started back just sort of in the support area of Linux and and rel and using that kind of capability and rit has been there for us for quite a long time now and I think we've sort of done some some Explorer exploratory type exercise with them around you know I've been shifting and The Container well but but what really started the stick was just getting their expertise in from our OpenStack perspective and when you that was a key platform that we really wanted to dive into an enable and so having them there is our partner and helping us provide that extra consulting knowledge and expertise was was what we really needed helped us deliver on that project and we delivered in a mazing ly tight timeframe so it was a fast delivery faster live what about the business impact why people look at OpenStack and some of these new technologies and certainly with the legacy stuff going on you have got all these things everywhere what was the actual business benefits can you highlight like did you get like faster time-to-market was it like a claims issue and what were the key things that you look back and saying well we kicked ass and we did these three things I mean really what it boils down to as faster time-to-market right and just the ability to move quicker so to give you an example the way we used to work is it would take you say probably weeks maybe even longer to to provision and get infrastructure stood up and ready to go for different projects so I meant that there was all this lead time that projects nearly go through before they could start to write code and even start to add value to to customer so we wanted to sort of take that away and and and and that was a that was a big hindrance to to be able to experiment and to be on a play we think so again we want to take that out of the picture in and really free people up to sort of say well the infrastructure is done and it spins up in a matter of seconds now on OpenStack and you can get on with the job of trying something out experimenting and actually delivering and writing code that will that will produce an outcome to launch new applications what was a specific outcome that came from standing up putting that over stack together I see you experimenting result not adding yeah not only in the app spice but more so the biggest the biggest sort of benefit with God is really in the data space where we've now been able to essentially stand up our entire data stack using open source technology and we've never been able to do that before and this is you know this is this is the environment it's allowed us to do that by just allowing for us to do that test and trial and say you know he's kafir you're gonna be the right tool for us is it you know is he gonna we're gonna use Post Chris whatever that is it's allowed us to sort of really do that in a rapid way and then figure that thing out and start to move forward so you know ask our kiss you guys have done a lot of work out there good work so I gotta ask you the question with kubernetes containers now part of the discussion as a real viable way to handle legacy but also new software development projects how do you look at that what it's what's the your your reaction to that as that practitioner yeah you guys excited yeah yeah things in motion what's your what's your color um absolutely it's in fact it's been something that we've kind of had on the radar for quite a while because we've we've we've been working with containers so dock in particular and and and one of the things that you know you come across this just management of containers and just ongoing maintenance of of those kind of things where they start to get a little bit unwieldy a little bit out of control so you know we've been trying to we try to start which started off trying to build our own you know in solution to that is there's a lot of corporates are doing quickly found out less that's it that's a huge engineering challenge so things like kubernetes that have now come along and the investment that's been put in that platform will really open up that avenue for and even seeing just the the new innovation that's been put into our OpenShift here that sort of takes a lot of that management and service you know administration out of the out of the equation few is wonderful for a company like us because at the end of the day we're an insurance company right we're not a we're not a technology engineering company while although we have some capability it's never going to be our our strengths right we're really here to service our customers and and to help them in the times when they need our help you guys are a data company data is critical for any trivet yeah how how is you how we've become more data-driven as a result of all this yeah so so now that we've got our data all in one place and we're able to get their single views of customers we're able to put that data now into the hands of people that can really add value to us so for example into our analytics teams and get them to look for optimization in price or in service claims processing all those kind of good things that that are helping our customers reduce the the time frames that they would normally go through in that part of that experience and I think one of the other things is not only that but also enrich our digital capability right and rich that digital channel so make it more convenient for customers you know where it used to be that customers would come along and it's literally like coming to the organization for the first time every time you know I say fill in that form again from blank you're like we don't know anything about you but now we're able to enrich your form exactly it's very painful I see your name and you know you wanted to show your house tell us all about that house you know what does it made of you know what what type of roof material what's the wall we know all that we've probably seen that house ten times already so why wouldn't we just be able to pre-populate that kind of information and make it more convenient forecasting personalization becomes critical absolutely absolutely I like the way you underscored and told the story just like with cloud you just can't take your broken old IT apps and just throw them up at the cloud you had to you had to do a data exercise and you had to do a consolidation and the cleaning strong and sure that involved open source but you didn't get the tech stack first first you have to picture picture data app and and that was a key part here yeah so that's difficult and that's you know that's one of the things that I think we really we really invested in it was because a lot of the time what we've seen is organizations have sort of attacked the low-hanging fruit like the the the kind of the external the digital data that they might be able to get but not that offline data that's been you know one and and generated by the branch and the call centers and all those kind of areas and we dug in deep and invested in that space and got that right first which really helped us a lot to accelerate and now we're I think we're in a better position we can definitely take advantage of that yeah thanks for sharing your insights here in the cube I gotta ask you a final question as the folks watching that they're looking at you say wow this guy he got down and dirty fixed some things he's gone forward innovative what advice would you give someone watching is pregnant practitioner what have you learned what's the learnings that you've that have been magnified out of this process for you and your view going forward yeah yeah there's a there's a lot of learnings we can share but I think some of the key ones is you know I think there's sometimes a bit of a bit of a sort of attempt to try and solve everything yourself right and and we definitely did that where I try and build it all yourself and do everything right but it's it's a challenge and and use partners and look for look for you know things that are kind of gonna help you accelerate and give you some of the foundational work you don't have to build yourself right you don't have to build everything yourself and I think that acknowledgement is really key so that was one of the big things for us the other thing is you know just just investing early and getting things right upfront life pulling your data and consolidating it into into a single platform even though that takes a lot of time and and it's and it's quite challenging to sort of go back and redo things that's actually a huge investment in a big winter to really help you accelerate at the end that investment upfront does does pay off so congratulations on your Innovation Award thank you Davis is general manager at I I AG insurance Australia group here inside the cube sharing the best practices it's it's a world you got to do the homework upfront open source is the way it's and it's an operating model for innovation the cube bringing you all the action here on day two of coverage stay with us for more live right after this short break

(upbeat music) >> Announcer: Live from Las Vegas. It's theCUBE. Covering ServiceNow Knowledge 2018. Brought to you by ServiceNow. >> Welcome back to theCUBE's live coverage of ServiceNow Knowledge 18, #know18. I'm your host, Rebecca Knight along with Dave Vellante. We're joined by Gemma Kyle. She's the head of management assurance at MLC. She's straight from Sydney. So welcome Gemma. >> Thank you. Thank you very much. >> Let's start off by having you tell our viewers a little bit about MLC. >> Sure. MLC is a life insurance company. It's interestingly Australia's oldest and newest life insurance company. We were recently sold by National Australia Bank to Nipon Life, a Japanese life insurance company. And we are now, thanks to the investment of capital from Nipon into MLC Life Insurance, Australia's newest stand-alone life insurance company. So we come as a 130 year old company with 1.4 million customers. But also we're investing in new technology, new infrastructure, new processes, new business operations. >> So, insurance is one of those industries that hasn't been radically disrupted. And I wonder what the conversation is like internally. Is there a complacency? "Not in our industry," "Not in my lifetime," "I'll be retired by then." Or is there paranoia? >> It's a great question. Look, it hasn't been disrupted, but it will be. I can't talk for the American market, but certainly in the Australian market we have 17 players right now and we know that they are going to consolidate down to eight or nine and we want to be one of those eight or nine. The disruption is going to come from the fact that previously there had been complacency. Customers had not been communicated with, invariably because their life insurance sits within a broader wealth management product called superannuation. Now, what's happening is customers are becoming more informed, more demanding and want more access to more flexible and innovative products that can follow them through their life cycles of marriage and children and mortgage. We really need to be on the front foot to offer the right kind of products and life insurance products to meet our customers' need. >> So, superannuation was not a term that I was familiar with. And I don't want to go too deep into it, but it's basically Australia's version of Social Security, except you can see your money. You can invest, you have control over where it goes and it's yours. >> Gemma: That's correct. >> It's not just some black hole. >> Yeah, that's correct. >> Okay, nice. >> I was just thinking about when you were talking about how customers are starting to demand more. So, when you think about digital transformation, is that what's leading the charge, would you say? >> Absolutely, absolutely. When we talk about digital transformation, it's really about breaking down the silos that previously existed within companies. And it's not just life insurance companies, it's all types of financial services. So previously, we would have the actuaries who do the pricing of our products and the advisors who sell our products, were the gods of the insurance industry. Now, when we look towards digital transformation, it becomes technology, it becomes process and it becomes risk management and control that are in the ascendancy. This is really critical because customers are looking to self-serve. They want to make their own choices. So that's where we need to meet them. We need to break down the traditional barriers between the silos and have a single platform that we can use a data analytics to better serve our customers. >> So, the advisors are getting disrupted by the whole self service trend. The actuaries. Are we getting robo-actuaries now with machines? >> Well, I don't see why not. >> Right, the data's there. >> Yeah, absolutely. You know, we are actually required under regulation to have a chief actuary, and that absolutely makes sense. But what we're starting to have now is automatic underwriting engines. So, previously you would apply for an insurance policy and the underwriter would come in, who has an actuarial background, and they'd price the risk you present to the business. These days we have sufficient data, that as soon as you put your information into the system, we can automatically approve a policy for you. That automated underwriting is an example of the type of disruption we're starting to see. >> But humans are still the last mile, if necessary. Is that right? >> Gemma: Absolutely, absolutely. Advisors are important because they help our customers understand their financial need. And advisors are very strongly regulated within the Australian market. They're required to have a qualification. And we've recently seen changes to our legislation around the requirement to, evidence that they are treating customers honestly, efficiently and fairly. And selling them products that they need, not that they have been encouraged to sell by another supplier. >> What's your biggest challenge? (laughs) Top three. >> Yeah, yeah, top three. Look, without a doubt, it's cultural change. Cultural change. By cultural change, I mean the behaviors and the beliefs that surround not just internally how we manage risk and compliance, but also externally around how customers perceive the insurance industry. We definitely suffer from a lack of trust. Now, the disruption that we're facing is that customers are saying "We don't trust you," and it's not well founded. It actually doesn't bear out in the data in terms of how we pay our claims and how we service our customers. But there's certainly an image problem there. So, we think we need to service, we think we need to address this cultural issue from the inside out. We need to fix ourselves and make sure that we, can with integrity, defend the decisions we make around how we service our customers and then in turn have customers really trust us. See what we do. Trust us by how we behave, not just what we say. >> When you're talking about the behaviors, changing the behaviors, how is security, risk, compliance, how is that all perceived within your company? >> Yeah, yeah. Well, like I said, the actuaries are king. They have sophisticated data models through which they can price policies. And, where we've traditionally been with risk and compliance is very much in a qualitative space around actions that are undertaken, or senses that things aren't working as well as they should do. What we've started to do, and this service now has been absolutely critical to this journey, we're starting to shift the conversation away from risk and compliance and towards business process and control. We're simply shifting the conversation away from a focus on risk exposures, or the things you must do and onto the cost benefit analysis of control investment options. That allows our executive and our board to start to use data and analytics to drive decision making around where we need to focus our efforts. >> So you're turning all of this kind of back office risk oriented stuff into a value proposition for the organization. >> Gemma: Exactly right. >> Can you talk a little bit more on how ServiceNow participates in that process? >> Sure. Ultimately, the value proposition. It is about behaviors, but the value proposition is all around being able to defend the decisions that you make. Being able to demonstrate with data and analytics. And being able to put a quantified amount of money on the bottom line around what's the value to actually changing our behaviors, or changing the way we manage your process. ServiceNow is obviously critical to that, because they have this amazing performance analytics engine that enables us to draw data out of the system as it relates to business process. As it relates to operational loss events. As it relates to customer complaints. As it relates to asset management. And integrate it to tell a story of where we're most exposed. To loss today and potential loss tomorrow. It's a very powerful tool that even our, surprisingly, our CEO, not only does he now use his app that we've created for him, but he personally calls people in the office to say "Hey, I see you've got "an overdue action here, what are you doing about it?" Now, I know, nobody wants that call. (laughs) Nobody wants that call. So consequently, we've got this incredible tone from the top that reinforces how important it is to pay attention to your controls, to your obligations, to genuinely own them. That's when you start to see the cultural change. >> You don't do business in Europe, do you? >> Gemma: No. >> Is there a GDPR equivalent in Australia, if you're familiar with GDPR? >> Gemma: No, sorry. >> Okay, so, it's all about privacy. So, the GDPR? >> Gemma: Oh, oh. Yes, yes. >> The fines go into effect this month and that doesn't affect you because you're not doing business in Europe. But is there something similar in Australia where if a customer says "I want to know "what data you have on me." Or, "I want you to delete that data." You have to prove that. It's quite onerous. But, is there anything similar for you guys? >> Gemma: Absolutely, absolutely. So, we've actually got two things. First of all, we do have the privacy act. And under the privacy act that's been in place for quite some time, all individuals, whether you're an employee or a customer, you have access to your data. And, you also have the right to be taken off lists and call trees and the like. The government's just recently introduced CPS147, which is a prudential standard around data breaches. Now previously, if there was a breach of data. Say for example, we accidentally send a letter to the wrong customer, and in that letter it has personal details about somebody's medical history. Now previously that was not okay from a privacy perspective, but it wasn't notifiable to the regulator. With CPS147, we now have a notifiable data breach system. It's just come in place. And we have to notify the regulator when we breach somebody's privacy, somebody's data. And we could be subject to fines. >> And does the ServiceNow platform play a role in that, in terms of just tracking the notification, or compliance, or? >> Absolutely, absolutely. So, when the change in legislation was introduced, we simply added literally another little tick box into our operational loss event module to say, "Is this a data breach?" And just simply by doing that, now when you log a loss event, and you tick that little box, we can see from across the company where are our data breaches happening? And if they're a cluster. Is there something here that's telling us that we've got a systemic problem that we need to fix? As soon as it came in, we were automatically reporting on it. >> One of the things we're hearing is that there's so much great customer-on-customer learning that takes place at Knowledge. Are you finding that? Are you talking with a lot of customers, and about how you use the platform? And success? >> Absolutely. This is a really exciting conference. I'm really having such a good time and sort of overcoming my jet lag, to tell the truth. It is very exciting. In Australia, we've already started some groups. So, we work with other, myself and my systems manager, Greg Dominich, the two of us tend to go to a lot of companies to talk about our experiences with the implementation of ServiceNow. What worked well, what didn't work well and what we would do better. Because we want to create a community of practice. We want to lift the practice of risk management above where it currently sits. And so, walking around here there's so many networking events, and this hall in particular, is wonderful. So yes, talking to lots of other customers. Just sharing innovations. It's very exciting. >> How long have you, when did you go live with ServiceNow? >> Okay, so, we went live, let's see, probably in, the first GIC module went live in June, 2017. We then had another iteration in September, 2017. So, we've basically spread it out to make sure. The next modules we're looking to introduce are business continuity management. Each time, we follow the same, we use the PPM tool, that ServiceNow provides to actually implement the modules. But then we have a process that we follow ourselves in terms of putting in the data, cleaning it, categorizing it, making sure we've got the analytics right and then we step to the next module. Interestingly enough, cultural change doesn't happen once you've implemented the system. Cultural change starts at the very point where you recognize there's an opportunity to do better. So, as we implement each module, we're also maturing our practices. And we're also changing the culture of how the business approaches risk and compliance. >> What's your relationship with IT in all of this? How does that all work? >> Look, it's very close. It's part of the transformation journey that those silos still exist. And they exist because we all create our own languages for understanding our world and how we engage with a business. Now, it's about breaking down those barriers. So, we work very closely with them on security management, on business continuity management and on incident management. And we're going through the process now of aligning our language so that once we have that shared language, we have the shared data and we can really become quite powerful. >> Rebecca: Great. Well Gemma, thanks so much for coming on theCUBE. It's been a really fun conversation. >> Thank you very much. It's been nice to hear. >> I'm Rebecca Knight for Dave Vellante. We will have more from.

>> Announcer: Live from Santa Clara, in the heart of Silicon Valley, it's theCUBE, covering Cloud Foundry Summit 2017. Brought to you by the Cloud Foundry Foundation and Pivotal. >> Welcome back. I'm Stu Miniman joined by my host, John Troyer. Really excited to welcome to the program one of the keynote speakers from this morning, Mojgan Lefebvre who is the SVP and chief information officer. We always love CIOs, from Liberty Mutual Insurance Global Specialty. Thank you for your keynote this morning and thank you so much for joining us on theCUBE. >> Thank you, thanks for having me. >> So you went through a lot of data and a lot of information in your keynote. Liberty Mutual, you say spent a billion dollars in tech yearly. There's certain technology companies that spend that much. As the CIO, what are some of the biggest things on your plate and we'll get in the discussion of Cloud Foundry and cloud and everything as we go from there. >> Sure so I'd say probably the priorities differ by the business unit you're in. The specialty business has generally been a bit more manual and we have over 200 or so insurance products. So really automating it is very different from automating consumer insurance which is really focused on home and auto. So really right now, our focus is increasing the productivity and the risk assessment for a lot of our underwriters. And then I say probably analytics, pricing. Making sure that we're assessing risks correctly is definitely another point of focus for us. >> Okay with so many products, we understand the rate of change must be difficult. In your keynote you spoke about embracing cloud and agile methodology. Maybe take us back to what some of the pain points were and led to yourself and management to embrace this big change. >> Yeah, absolutely so several things are going on. One is that we see a lot of new players entering the world of insurance, and it both about new capital coming into the world of insurance. Just 'cause there's not enough investments that capital can be put towards so insurance is one place to come to and the other is technology players that are coming into our world. Companies like Metromile, Lemonade, the list goes on and on and so really our world is changing. Technology is driving a lot of that change and so we know that we've got to be a big player in that area as well. And as I said really, we've got to become one of those software companies that can actually sell insurance as opposed to the other way around. I'd say some of the other things that are happening is the fact that our employees. Our consumers now have all these other software companies that they have experience with and so their expectations are very different. They've got one experience when they're at home and then they come into the workplace and it looks like they've gone back 100 years. So that paradigm needs to change. So those are some of the things that have really made us think we have no choice but to truly change the way that deliver software. We've got to get out of this mode where everything takes multiple years and multiple millions of dollars and really at the end of the day. The people that you started the work with are no longer even there to appreciate what you've delivered to them. And usually it's not what they ask for anyway. >> As you adopted the Cloud Foundry platform. One of the things about Cloud Foundry, even very early in it's life cycle was that it was associated with digital transformation, and cloud native. And especially once it was joined up with Pivotal Labs. So how much of, as you all embark on this journey. The great thing about here at Summit, there is a lot of talk about visual transformation. A lot of talk about agile. That's what we were just talking about. Some shows you go to it's a lot about features and a lot about speeds and feeds. And a lot about the latest, greatest. So how much apart of it as you all were adopting this platform? Was that culture of digital transformation surrounding the actual tech. How important was that? >> I think that was very important because again, as I said we know that, that's what the consumers expect. They no longer want things to be manual. They want things to be at the tips of their fingers and so really transforming us from being a company that's very paper intensive to really being more and more digital was critical to us. The very first application that we actually put in the cloud which was in my business unit was for document management in our Al Fresco. And actually what we named it was we're going paperless. As something that we started about three years ago, and today I can say that yep, we are paperless and so the great thing about Al Fresco was that it was indeed cloud native, and that was very important to us. We started out looking at some of the other solutions that are out there. I won't necessarily name them but they did not lend themselves to the cloud. And so really going with a cloud native solution that would enable us to become much more digital and paperless was very critical to us. >> You talked a lot about developer adoption now in your journey. Was that a tough sell at the very beginning or did developers go wait a minute, This is going to save me a lot of time. I'm on board. >> So you mean with Cloud Foundry in general? >> John: With Cloud Foundry, in general. >> So if anything I'd it was probably the developer community that really sorted this out and so by the time that the leadership and management started to pay attention. There were pockets of developers who were just very, very bought into it, and so I would say that went a long way. And then made it easier to sell it to other developers. I say they're much more listening to what their peers are saying than what we have to say. And then really meeting with the Pivotal Labs guys. I'd say those folks have truly a magical way of selling their story and they've truly helped us. Not only sell it to our developers but also sell the story to our business. I'd say that the mindset shift from thinking I'm going to have everything in one go versus no, I'm going to get it in iterations and I'm actually going to trust the fact that the next releases are going to come is a big mind shift and Pivotal was instrumental in helping sell that to us. >> One of the benefits of Cloud Foundry is to give you flexibility as to where your applications and data live. That being said, a majority of customers that have deployed Cloud Foundry are doing it on premises. How do you manage what goes, stays in your own environment. What handles the public cloud. My understanding you're doing quite a bit of AWS today. What's your viewpoint for you and management on public cloud? >> We certainly see public cloud as the future. I know Chip mentioned something about, well it's not going to be cheaper. We're actually counting on that in the end from a total cost of ownership perspective. That it will be cheaper and we truly mean it when we say we want 75% of the people writing code. And by that I mean the staff within the IT group of course. And we don't want them to have to worry about the infrastructure and so while we've started with AWS, we absolutely have a relationship with Microsoft as well. We definitely want to be independent on this cloud and I would say something like Cloud Foundry definitely allows you to do that. >> When you're looking at that total. That full TCO, you don't have fully burden, I have gear and I have people managing that gear and all the operations there. If you can shift that piece of it. You're not differentiated on the infrastructure or at those needs. You want to focus on those thousands of products that you have and your people coding to create those next opportunities. >> Exactly. We want to focus on the value add. That's where we want our people to really be focusing and we want to let the cloud players who do it extremely well to be doing that for us. >> You put forth in your keynotes some pretty audacious metrics. I think it was 60% of the work load public cloud. More than 50% of apps to release code on daily basis and you wanted 75% of the IT staff to write code. How did you come up with those numbers. How are doing against those? >> About a year ago, once we decided that the imperative for change was so critical. The IT leadership team got together. We spent a couple of days off site and we said let's come up with what we're calling today our IT manifesto. And so we said we just have to change and there are multiple things that we're going to change. And we said we're going to put some, what we call bold, audacious moves or BAMS as they've come to be known together. And so those were just some, we knew they were out of right to some extent, but we said if we don't really put some goals that are really hard to reach, we're never going to get there. >> What are some of the head winds there? What have slowed you from meeting those and any lessons learned that you share to your peers on what you've learned going through this. >> Certainly deciding on what goes to the clouds first is one of those areas that we're learning as we're doing. We know that it's easy when you're working in a greenfield and it's something new. So yeah, you can very easily say I'll build in the cloud. When you're looking at what you're existing environment is and what you move to the cloud. One of the questions as well, if we move all of our development environment. How's that going to interact with the production environment. If you have them in different clouds. Other things are how it interacts with active directory and held app and some of those things. And I say finally would be kind of the global applications always make it much more difficult as you think. How do you replicate among different clouds in different geographies. Those are some of the blockers that we've got to tackle and make sure that we get around. >> One of the interesting parts of any management strategy in any company is skills, up skilling. So how have you been approaching that in terms of this new cloud native world. Both for the devs, is this year at Cloud Foundry Summit. Are people here learning? There's new certifications. >> I say it's a multi prong approach. We definitely have partnered with several companies to put some training together to make sure that we're training our staff. We started a program that we call go for code and so we've asked volunteers. For people who are not coding today and who want to get there that actually they go to these coding schools and they're going to spend the next two to three months actually learning how to code. It's very rigorous. >> So they might have been technical in an infrastructure way before and they want to learn how to code? >> Yeah, it may be that or they may have just been business analysts who are just doing requirements gathering or project management, and they want to learn how to code. So we've tried to be as transparent as possible because when you say I want 75% of my IT staff to be coding. Like you've got 50% who are not coding today. There's a message in that and so of course it's up to us to make sure that we're providing the tools and what's needed for that to happen. Our goal is to get anyone on our staff who really wants to get there and is willing to put the sweat in to be able to do it. 'Cause we also know it's not like software engineers are just lying out there on the streets. There is a shortage of software engineers and that's going to become more and more of a problem. So really getting our own employees that we value greatly to be able to do that transformation, I think is critical for us. >> Another great one line, you had your keynote was out with the annual, in with the weekly. I think you said it was 16 releases in five months. The counter to that and I'm curious how you deal with it and talk to your peers is how do people keep up with just all the changes that are happening? I talk to the companies that create code on just regular occasions and they can't keep up. And how do you make sure your staff doesn't get burned out? >> So great, great question again. We're at the very beginnings of our transformation. The one thing I will say is looking at the team that did this and did the 16 releases in five months versus teams that are working on annual releases. The energy, the enthusiasm, the excitement and hopefully some of it came through in the video that you saw is just phenomenal. So I'd say, I'm much less worried about them burning out than hey can we keep the others as excited. I will tell you automation and things like Cloud Foundry that actually help you automate your pipeline are critical. You can not do multiple releases or daily releases if you don't have those tools. If you truly get to the point where you do have the automated pipeline. I think a lot of that is done for you so that's what we're gearing towards and driving towards. >> One of the things that people always love to pontificate is in the future, what is the role of the CIO? We'd love to see you embracing things like cloud because it was like well, when I had gear, and I had capital budget I understood it. But I'm changing the role. I'm doing that. What have you been seeing as the changing role? Anything down the line you see and how that changes? >> You're right, so a lot of people say, well there is no need for a CIO in the future. I'd say there's probably more and more need for very business oriented, strategic CIOs who also understands technology really well and they're the epitome of someone who understands technology and is the head of engineering so to speak. But also making sure that they can work very well with the business and understands the impact of technology on the business. I'll be waiting for the day where the need for someone like that goes away. I don't see it coming too soon. >> Final question I have for you is what brings you to an event like this? Spend the time, give the keynote. What do you get out of it personally and for your company? >> One is really learning 'cause again, if you're a doctor in medicine. If you want to keep up with what's going on around you you've got to educate yourself. So certainly that aspect of go out there, see what's going on. Making sure that you're keeping up with new technology that's one thing. The other was my experience with Pivotal has been phenomenal, and so I thought it was critical to actually take the opportunity to share that. Hopefully others will learn. A lot of the tweets that I saw was well, if a big 100 year old insurance company can do this. Then nobody has an excuse and I'll say yeah of course. So it's really both to give back and to continue to learn and then to reconnect with colleagues. Cornelia and I actually worked together over 10 years ago. So just coming to here and being able to have dinner with her tonight is going to be very enjoyable. >> Absolutely a tight knit community. Really appreciate you coming on the program. We welcome you to theCUBE alumni list now, our community, >> Thank you. Of the thousands that we had on the program. From John and myself, we'll be back with lots more coverage here from the Cloud Foundry Summit. Thanks for watching theCUBE. (uptempo techno music)

(calm tech music) >> Hello everyone. Welcome back to the AWS Cube coverage of Reinvent 2022. I'm John Fur, host of the Cube. We got a great interview segment here co-creating innovation with E.design. We got Shigeo Kuwabara who is with the President and the Chief Executive Officer E.design Insurance, and Akiko Hora Senior Managing Director Financial Services in Japan Inclusion and Diversity Lead at Accenture Japan. Thank you for joining me today. Thanks for coming on the cube. >> You're welcome, You're welcome, Thank you. >> I love this topic. E.design Create co-creating innovation automobile insurance with a product called "&e" It's cloud-based advanced automobile insurance system you guys built and called Safe Driving Together an initiative that uses data to reduce accidents. So great stuff. So let's get into it. Tell us about eDesign Insurance and your vision behind transforming to insurance tech company. Combining the technology, new type of automobile insurance for a digital age. >> Okay. With the pandemic of Covid 19 dissertation is accelerating at rapid pace everywhere. First, insurance were required to define the kind of easy to use, meaningful service they wanted to offer their customers. eDesign in collaboration with Accenture, sought to redefine the company's mission, vision and values by embracing the customer experience in a new way. While a customer's traditional view of automobile insurance is "just in case" Accenture and eDesign form the view that what customers really want is accident prevention. With a redefined objective of co-creating with customers not only peace of mind in the event of an accident, but also a world without accidents. ANDI developed a service that uses cutting edge digital technologies to create a safer and more secure car experience. >> Akiko talk about from insurance perspective and Accenture you know, we know about FinTech, you got InsureTech this is a segment that's growing rapidly, lot of data lot of new capabilities with the cloud. Can you share your thoughts on this new opportunity? >> This is a new innovation for many insurance client especially who owns, the traditional policyholder and the new generations. So they that give the new experience for customers, it makes a big change for the customer experience, and that eDesign is leading this experience in the world I think. >> Awesome. What are the key features of the advanced cloud-based automobile insurance system you guys call ANDI, and how does it work? >> The most advanced full crowd insurance system in the world and it embraces digital convenience to the fullest with a concept of creating safety with data; ANDI enables that initiative Safe Driving Together. It designs new initiative, aims to use available data to reduce the risk and causes of an accident, and to make society as a whole, as a whole safer and more secure. >> Why did you choose Accenture and AWS for this innovation? What unique value do they bring? >> Good question about Accenture. Accenture supported us in a wide range of areas including business, design, and IT. In addition to the industry knowledge embodiment of vision, and definition requirements. The PMO eliminated communication loss between the business and IT sites, and as a result the development was completed in a short period of time. In addition, Accenture studies in cutting edge digital technologies such as AI and data analysis is necessary to become an insured insurance company. And I appreciate Accenture's ability to provide such capabilities as well. >> Akiko talk about the IOT implementation here. A lot of data, a lot of design work. >> Yeah >> Take us through the experience. >> Okay. >> And how does Amazon and Accenture come together. >> ANDI and to support safe driving with eDesign insurance for the compact IOT car sensor with this size to put free charge for all of the policyholders to use a language mobile app. The system captures capture and monitors the drivers driving data, diagnosed and driving mood, and driving behavior which is safe or not and supports safe driving. In the event of the accident the system automatically detect the impact and can summarize the accident situation which is very difficult for the driver to recognize by themselves, and the location, location data. And many others and driver can then report the accident with single tap on their smartphone, very easy. And request assistance or repair shop on the spot. It's very safe and also very smooth for the giving the good experience for customers. >> I know Accenture has great expertise, that's one. But you have been in both involved in this smart market rollout. Can you explain that? The smart market rollout? >> Yeah, it's, it was very interesting that we we had the very smooth importation with eDesign and especially AWS allow us to give the open and crowd system to strong collaboration with many other ecosystem partners and many AI sensors and many IOT sensors opportunity. That gives us a lot of experience and give more opportunity for an eScape company like eDesign sample, so that can be more smooth and open implementation for the future. >> That's great rollout. You know we love this example of AWS Accenture eDesign co-creation. It reminds me of the big super cloud trend where industries can be refactored and and and scaled up. So how was ANDI built and what were the requirements driving the technical solution? >> We, we, we, we brought, we planned the architecture how that works for the future and especially Kuwabarason and the great leadership. He doesn't like something which already in the market and also which can be more fit for the future, the solution which fit for the future and maybe that can allow market customers to have big experience. That's why we, we choose open crowd, new trend, new digital trend and IOT or whatever. That gives our architecture definition, which can, lead by Kuwabarason with AWS with this crowd solution as well as with very packaged basis and also open connection with many other AI in the new technology. So that's why it can be more, this solution going to be grow more in the future and we will have more surprises in the future. Kuwabarason if you have some add add comment please >> Go Ahead. >> (laughing) >> Go ahead. What's your thought? Share? >> Thank, thank you Horason very good comment (laugh). So in collaboration with Accenture, I could develop our team's capability. Because we are working together like one team. That is a key success factor I think. >> Talk about the customer experience, and the results. What feedback have you received from your customers and what does the data say? >> Okay. One interesting feedback we receive is "I was always concerned about my wife's love of driving, but by showing her the ANDI driving score, I was able to point it out to her objectively, which was very helpful." That was a good feedback. In this way there are many positive feedback about the ability of visualize the safety, and danger of ones own driving. When I hear customers say that they can now drive more safely because they can objectively identify their bad driving through ANDI's safe driving program I feel very happy that we created ANDI >> Kiko your thoughts? >> Yeah, it's, it's very obvious that the customers likes how, customers likes the sensor saying how they are driving and they, they they sense my driving behavior is safe they are going to be confident. If not, they going to be very careful in the future that's happening. And maybe that can be aligned with insurance which eDesign is giving is more they feel more confident to drive in in many areas. And also that can give more opportunity that they can have more new type of insurance and new experience with the car. That's, that's kind of the interesting make up of power of the driving including the sensor would be happening. That can be good news for us and we can be more creative to think about new experience for customers. >> Congratulations for receiving the highest IT grand prize from the IT award sponsored by the Japan Institute of Information Technology. What's next for eDesign? Congratulations. What's next? How do you take it further, to change to transform the insurance business? >> Okay. I believe ANDI's strength lies in its data. By sharing data with our customers in a timely manner we contribute to their safe driving. We hope to work with customers to create a safe driving experience that is based on parts and that can be enjoyed like a game. Furthermore, we would like to create a society and community where accidents are less likely to occur. Based on the accumulated data in cooperation with local governments and other organizations. We'd like to contribute to the realization of such a safe and secure society by acquiring and analyzing solid data through ANDI On what kind of accidents occur and under what circumstances. >> Akiko Big awards. What's next? AWS, Accenture, eDesign take us through the vision. >> Yeah, it's, it's, I'm, I'm looking forward to do to do the next things and actually eDesign have not only auto insurance, they cover more home and also many others. So that can be giving the more safer opportunity for customers. They can leave their home very smoothly and even some disaster happening, they can escape very safely. Whatever happening in the family like childcare or maybe even their pet have some challenges we can take care of them and that's kind of many experience which which can align with eDesign's insurance. Most of the things we can give lot of safe and with data and also some IOT things and also insurance that's giving the more opportunity and something can truly resolve the social issue. That can be many opportunities. So that's why we have some plan. But we like to we like to keep a secret for the next future. >> Safe driving together, unlock benefits by gamifying and creating cloud-based advanced data, IOT sensors, encouraging drivers to work together to be safe. This is very, very an important story and thank you so much for sharing. eDesign, thank you for coming on. Congratulations on your awards, and transforming insurance tech. It should be fun. Not a hassle. Thank you for sharing. >> Thank you very much. >> Very much. >> Okay. eDesign co-creating innovation. This is the story of Cloud Next Generation. I'm John Fur the Cube, part of the AWS Reinvent 2022 Cube coverage here with Accenture. Thanks for watching. (calm tech music)

>> Announcer: theCube presents HPE Discover 2022, brought to you by HPE. >> Hey, everyone. Welcome back to Las Vegas. This is Lisa Martin with Dave Vellante live at HPE Discover '22. Dave, it's great to be here. This is the first Discover in three years and we're here with about 7,000 of our closest friends. >> Yeah. You know, I tweeted out this, I think I've been to 14 Discovers between the U.S. and Europe, and I've never seen a Discover with so much energy. People are not only psyched to get back together, that's for sure, but I think HPE's got a little spring in its step and it's feeling more confident than maybe some of the past Discovers that I've been to. >> I think so, too. I think there's definitely a spring in the step and we're going to be unpacking some of that spring next with one of our alumni who joins us, Keith White's here, the executive vice president and general manager of GreenLake Cloud Services. Welcome back. >> Great. You all thanks for having me. It's fantastic that you're here and you're right, the energy is crazy at this show. It's been a lot of pent up demand, but I think what you heard from Antonio today is our strategy's changing dramatically and it's really embracing our customers and our partners. So it's great. >> Embracing the customers and the partners, the ecosystem expansion is so critical, especially the last couple of years with the acceleration of digital transformation. So much challenge in every industry, but lots of momentum on the GreenLake side, I was looking at the Q2 numbers, triple digit growth in orders, 65,000 customers over 70 services, eight new services announced just this morning. Talk to us about the momentum of GreenLake. >> The momentum's been fantastic. I mean, I'll tell you, the fact that customers are really now reaccelerating their digital transformation, you probably heard a lot, but there was a delay as we went through the pandemic. So now it's reaccelerating, but everyone's going to a hybrid, multi-cloud environment. Data is the new currency. And obviously, everyone's trying to push out to the Edge and GreenLake is that edge to cloud platform. So we're just seeing tons of momentum, not just from the customers, but partners, we've enabled the platform so partners can plug into it and offer their solutions to our customers as well. So it's exciting and it's been fun to see the momentum from an order standpoint, but one of the big numbers that you may not be aware of is we have over a 96% retention rate. So once a customer's on GreenLake, they stay on it because they're seeing the value, which has been fantastic. >> The value is absolutely critically important. We saw three great big name customers. The Home Depot was on stage this morning, Oak Ridge National Laboratory was as well, Evil Geniuses. So the momentum in the enterprise is clearly present. >> Yeah. It is. And we're hearing it from a lot of customers. And I think you guys talk a lot about, hey, there's the cloud, data and Edge, these big mega trends that are happening out there. And you look at a company like Barclays, they're actually reinventing their entire private cloud infrastructure, running over a hundred thousand workloads on HPE GreenLake. Or you look at a company like Zenseact, who's basically they do autonomous driving software. So they're doing massive parallel computing capabilities. They're pulling in hundreds of petabytes of data to then make driving safer and so you're seeing it on the data front. And then on the Edge, you look at anyone like a Patrick Terminal, for example. They run a whole terminal shipyard. They're getting data in from exporters, importers, regulators, the works and they have to real-time, analyze that data and say, where should this thing go? Especially with today's supply chain challenges, they have to be so efficient, that it's just fantastic. >> It was interesting to hear Fidelma, Keith, this morning on stage. It was the first time I'd really seen real clarity on the platform itself and that it's obviously her job is, okay, here's the platform, now, you guys got to go build on top of it. Both inside of HPE, but also externally, so your ecosystem partners. So, you mentioned the financial services companies like Barclays. We see those companies moving into the digital world by offering some of their services in building their own clouds. >> Keith: That's right. >> What's your vision for GreenLake in terms of being that platform, to assist them in doing that and the data component there? >> I think that was one of the most exciting things about not just showcasing the platform, but also the announcement of our private cloud enterprise, Cloud Service. Because in essence, what you're doing is you're creating that framework for what most companies are doing, which is they're becoming cloud service providers for their internal business units. And they're having to do showback type scenarios, chargeback type scenarios, deliver cloud services and solutions inside the organization so that open platform, you're spot on. For our ecosystem, it's fantastic, but for our customers, they get to leverage it as well for their own internal IT work that's happening. >> So you talk about hybrid cloud, you talk about private cloud, what's your vision? You know, we use this term Supercloud. This in a layer that goes across clouds. What's your thought about that? Because you have an advantage at the Edge with Aruba. Everybody talks about the Edge, but they talk about it more in the context of near Edge. >> That's right. >> We talked to Verizon and they're going far Edge, you guys are participating in that, as well as some of your partners in Red Hat and others. What's your vision for that? What I call Supercloud, is that part of the strategy? Is that more longer term or you think that's pipe dream by Dave? >> No, I think it's really thoughtful, Dave, 'cause it has to be part of the strategy. What I hear, so for example, Ford's a great example. They run Azure, AWS, and then they made a big deal with Google cloud for their internal cars and they run HPE GreenLake. So they're saying, hey, we got four clouds. How do we sort of disaggregate the usage of that? And Chris Lund, who is the VP of information technology at Liberty Mutual Insurance, he talked about it today, where he said, hey, I can deliver these services to my business unit. And they don't know, am I running on the public cloud? Am I running on our HPE GreenLake cloud? Like it doesn't matter to the end user, we've simplified that so much. So I think your Supercloud idea is super thoughtful, not to use the super term too much, that I'm super excited about because it's really clear of what our customers are trying to accomplish, which it's not about the cloud, it's about the solution and the business outcome that gets to work. >> Well, and I think it is different. I mean, it's not like the last 10 years where it was like, hey, I got my stuff to work on the different clouds and I'm replicating as much as I can, the cloud experience on-prem. I think you guys are there now and then to us, the next layer is that ecosystem enablement. So how do you see the ecosystem evolving and what role does Green Lake play there? >> Yeah. This has been really exciting. We had Tarkan Maner who runs Nutanix and Karl Strohmeyer from Equinix on stage with us as well. And what's happening with the ecosystem is, I used to say, one plus one has to equal three for our customers. So when you bring these together, it has to be that scenario, but we are joking that one plus one plus one equals five now because everything has a partner component to it. It's not about the platform, it's not about the specific cloud service, it's actually about the solution that gets delivered. And that's done with an ISV, it's done with a Colo, it's done even with the Hyperscalers. We have Azure Stack HCI as a fully integrated solution. It happens with managed service providers, delivering managed services out to their folks as well. So that platform being fully partner enabled and that ecosystem being able to take advantage of that, and so we have to jointly go to market to our customers for their business needs, their business outcomes. >> Some of the expansion of the ecosystem. we just had Red Hat on in the last hour talking about- >> We're so excited to partner with them. >> Right, what's going on there with OpenShift and Ansible and Rel, but talk about the customer influence in terms of the expansion of the ecosystem. We know we've got to meet customers where they are, they're driving it, but we know that HPE has a big presence in the enterprise and some pretty big customer names. How are they from a demand perspective? >> Well, this is where I think the uniqueness of GreenLake has really changed HPE's approach with our customers. Like in all fairness, we used to be a vendor that provided hardware components for, and we talked a lot about hardware costs and blah, blah, blah. Now, we're actually a partner with those customers. What's the business outcome you're requiring? What's the SLA that we offer you for what you're trying to accomplish? And to do that, we have to have it done with partners. And so even on the storage front, Qumulo or Cohesity. On the backup and recovery disaster recovery, yes, we have our own products, but we also partner with great companies like Veeam because it's customer choice, it's an open platform. And the Red Hat announcement is just fantastic. Because, hey, from a container platform standpoint, OpenShift provides 5,000 plus customers, 90% of the fortune 500 that they engage with, with that opportunity to take GreenLake with OpenShift and implement that container capabilities on-prem. So it's fantastic. >> We were talking after the keynote, Keith Townsend came on, myself and Lisa. And he was like, okay, what about startups? 'Cause that's kind of a hallmark of cloud. And we felt like, okay, startups are not the ideal customer profile necessarily for HPE. Although we saw Evil Geniuses up on stage, but I threw out and I'd love to get your thoughts on this that within companies, incumbents, you have entrepreneurs, they're trying to build their own clouds or Superclouds as I use the term, is that really the target for the developer audience? We've talked a lot about OpenShift with their other platforms, who says as a partner- >> We just announced another extension with Rancher and- >> Yeah. I saw that. And you have to have optionality for developers. Is that the way we should think about the target audience from a developer standpoint? >> I think it will be as we go forward. And so what Fidelma presented on stage was the new developer platform, because we have come to realize, we have to engage with the developers. They're the ones building the apps. They're the ones that are delivering the solutions for the most part. So yeah, I think at the enterprise space, we have a really strong capability. I think when you get into the sort of mid-market SMB standpoint, what we're doing is we're going directly to the managed service and cloud service providers and directly to our Disty and VARS to have them build solutions on top of GreenLake, powered by GreenLake, to then deliver to their customers because that's what the customer wants. I think on the developer side of the house, we have to speak their language, we have to provide their capabilities because they're going to start articulating apps that are going to use both the public cloud and our on-prem capabilities with GreenLake. And so that's got to work very well. And so you've heard us talk about API based and all of that sort of scenario. So it's an exciting time for us, again, moving HPE strategy into something very different than where we were before. >> Well, Keith, that speaks to ecosystem. So I don't know if you were at Microsoft, when the sweaty Steve Ballmer was working with the developers, developers. That's about ecosystem, ecosystem, ecosystem. I don't expect we're going to see Antonio replicating that. But that really is the sort of what you just described is the ecosystem developing on top of GreenLake. That's critical. >> Yeah. And this is one of the things I learned. So, being at Microsoft for as long as I was and leading the Azure business from a commercial standpoint, it was all about the partner and I mean, in all fairness, almost every solution that gets delivered has some sort of partner component to it. Might be an ISV app, might be a managed service, might be in a Colo, might be with our hybrid cloud, with our Hyperscalers, but everything has a partner component to it. And so one of the things I learned with Azure is, you have to sell through and with your ecosystem and go to that customer with a joint solution. And that's where it becomes so impactful and so powerful for what our customers are trying to accomplish. >> When we think about the data gravity and the value of data that put massive potential that it has, even Antonio talked about it this morning, being data rich but insights poor for a long time. >> Yeah. >> Every company in today's day and age has to be a data company to be competitive, there's no more option for that. How does GreenLake empower companies? GreenLake and its ecosystem empower companies to really live being data companies so that they can meet their customers where they are. >> I think it's a really great point because like we said, data's the new currency. Data's the new gold that's out there and people have to get their arms around their data estate. So then they can make these business decisions, these business insights and garner that. And Dave, you mentioned earlier, the Edge is bringing a ton of new data in, and my Zenseact example is a good one. But with GreenLake, you now have a platform that can do data and data management and really sort of establish and secure the data for you. There's no data latency, there's no data egress charges. And which is what we typically run into with the public cloud. But we also support a wide range of databases, open source, as well as the commercial ones, the sequels and those types of scenarios. But what really comes to life is when you have to do analytics on that and you're doing AI and machine learning. And this is one of the benefits I think that people don't realize with HPE is, the investments we've made with Cray, for example, we have and you saw on stage today, the largest supercomputer in the world. That depth that we have as a company, that then comes down into AI and analytics for what we can do with high performance compute, data simulations, data modeling, analytics, like that is something that we, as a company, have really deep, deep capabilities on. So it's exciting to see what we can bring to customers all for that spectrum of data. >> I was excited to see Frontier, they actually achieve, we hosted an event, co-produced event with HPE during the pandemic, Exascale day. >> Yeah. >> But we weren't quite at Exascale, we were like right on the cusp. So to see it actually break through was awesome. So HPC is clearly a differentiator for Hewlett Packard Enterprise. And you talk about the egress. What are some of the other differentiators? Why should people choose GreenLake? >> Well, I think the biggest thing is, that it's truly is a edge to cloud platform. And so you talk about Aruba and our capabilities with a network attached and network as a service capabilities, like that's fairly unique. You don't see that with the other companies. You mentioned earlier to me that compute capabilities that we've had as a company and the storage capabilities. But what's interesting now is that we're sort of taking all of that expertise and we're actually starting to deliver these cloud services that you saw on stage, private cloud, AI and machine learning, high performance computing, VDI, SAP. And now we're actually getting into these industry solutions. So we talked last year about electronic medical records, this year, we've talked about 5g. Now, we're talking about customer loyalty applications. So we're really trying to move from these sort of baseline capabilities and yes, containers and VMs and bare metal, all that stuff is important, but what's really important is the services that you run on top of that, 'cause that's the outcomes that our customers are looking at. >> Should we expect you to be accelerating? I mean, look at what you did with Azure. You look at what AWS does in terms of the feature acceleration. Should we expect HPE to replicate? Maybe not to that scale, but in a similar cadence, we're starting to see that. Should we expect that actually to go faster? >> I think you couched it really well because it's not as much about the quantity, but the quality and the uses. And so what we've been trying to do is say, hey, what is our swim lane? What is our sweet spot? Where do we have a superpower? And where are the areas that we have that superpower and how can we bring those solutions to our customers? 'Cause I think, sometimes, you get over your skis a bit, trying to do too much, or people get caught up in the big numbers, versus the, hey, what's the real meat behind it. What's the tangible outcome that we can deliver to customers? And we see just a massive TAM. I want to say my last analysis was around $42 billion in the next three years, TAM and the Azure service on-prem space. And so we think that there's nothing but upside with the core set of workloads, the core set of solutions and the cloud services that we bring. So yeah, we'll continue to innovate, absolutely, amen, but we're not in a, hey we got to get to 250 this and 300 that, we want to keep it as focused as we can. >> Well, the vast majority of the revenue in the public cloud is still compute. I mean, not withstanding, Microsoft obviously does a lot in SaaS, but I'm talking about the infrastructure and service. Still, well, I would say over 50%. And so there's a lot of the services that don't make any revenue and there's that long tail, if I hear your strategy, you're not necessarily going after that. You're focusing on the quality of those high value services and let the ecosystem sort of bring in the rest. >> This is where I think the, I mean, I love that you guys are asking me about the ecosystem because this is where their sweet spot is. They're the experts on hyper-converged or databases, a service or VDI, or even with SAP, like they're the experts on that piece of it. So we're enabling that together to our customers. And so I don't want to give you the impression that we're not going to innovate. Amen. We absolutely are, but we want to keep it within that, that again, our swim lane, where we can really add true value based on our expertise and our capabilities so that we can confidently go to customers and say, hey, this is a solution that's going to deliver this business value or this capability for you. >> The partners might be more comfortable with that than, we only have one eye sleep with one eye open in the public cloud, like, okay, what are they going to, which value of mine are they grab next? >> You're spot on. And again, this is where I think, the power of what an Edge to cloud platform like HPE GreenLake can do for our customers, because it is that sort of, I mentioned it, one plus one equals three kind of scenario for our customers so. >> So we can leave your customers, last question, Keith. I know we're only on day one of the main summit, the partner growth summit was yesterday. What's the feedback been from the customers and the ecosystem in terms of validating the direction that HPE is going? >> Well, I think the fantastic thing has been to hear from our customers. So I mentioned in my keynote recently, we had Liberty Mutual and we had Texas Children's Hospital, and they're implementing HPE GreenLake in a variety of different ways, from a private cloud standpoint to a data center consolidation. They're seeing sustainability goals happen on top of that. They're seeing us take on management for them so they can take their limited resources and go focus them on innovation and value added scenarios. So the flexibility and cost that we're providing, and it's just fantastic to hear this come to life in a real customer scenario because what Texas Children is trying to do is improve patient care for women and children like who can argue with that. >> Nobody. >> So, yeah. It's great. >> Awesome. Keith, thank you so much for joining Dave and me on the program, talking about all of the momentum with HPE Greenlake. >> Always. >> You can't walk in here without feeling the momentum. We appreciate your insights and your time. >> Always. Thank you you for the time. Yeah. Great to see you as well. >> Likewise. >> Thanks. >> For Keith White and Dave Vellante, I'm Lisa Martin. You're watching theCube live, day one coverage from the show floor at HPE Discover '22. We'll be right back with our next guest. (gentle music)

(bright music) >> Hey, welcome to this "CUBE Conversation." I'm your host, Lisa Martin. I've got two guests from NETSCOUT here with me today. Eileen Haggerty joins us, the AVP of Product and Solutions Marketing and Jason Chaffee, Senior Product Manager. We're going to be talking about the importance of quality end user experience with UC&C, Unified Communications and Collaborations services for something that will be near and dear to all of our hearts, employee productivity. Eileen, let's go ahead and start with you and the impact of COVID on UC&C, what has it been? >> Oh, Lisa, great question, because we really have seen an evolution in the importance and reliance on UCC. COVID would not have allowed us to go to work, do business continuity, any of those things had it not been for strong communications platforms to help us do that. And in fact, really the hero of all of this has been what's called Unified Communications as a Service or UCaaS. Enterprise businesses really depended entirely on the communications between the home office and the employees remotely. This is also known to be the way we all went to work. It was no longer a car. We picked up the phone basically or the computer. So Zoom, WebEx, Teams, Google Meets, they've all become household names really over the last two years. That's kind of exciting for them. And businesses during that period of time expanded their tools to keep business running and employees in communication using these very platforms, and we'll refer to this a couple of times during this conversation too, Lisa. We did a survey at the end of 2021, IT leaders, about their use of UCaaS and UCC during this period of time. We found that almost of them had used collaboration tools, and in fact, added to their arsenal of tools during this period of time to such an extent that they're now ranging, the majority of them, between three and nine different platforms that their corporate employees use. This became unwieldy, of course, during that time, and so their strategy going forward is going to be to reduce some of that number, but pretty interesting details. >> Yeah, between three and nine is a lot, and certainly, UC&C became a lifeline for all of us, professionally and personally. Even my mom learned how to use Zoom during this time. I was pretty proud of helping her with that. But, Jason, talk to us about all these new communication services. We're completely dependent on them, but overall what have you found out in terms of how they worked out? >> Well, to be honest with you, I think from the IT organization, it's been a challenge. It's been difficult. I think every IT organization is really motivated to ensure the quality of the services throughout the whole company, but as you can imagine, the increase of these communications Eileen just talked about during the pandemic is just significantly increasing the number of IT help desk tickets that have come through. And in that survey that Eileen just talked about, in fact, a third of those that responded said that 50 to 75% of their help desk tickets right now are related to UC&C or UCaaS services, and in fact, they say that over half of them have said that they get those tickets at least once a day, if not multiple times a day. And I think another big aspect of this that's been a challenge is everybody working from home now and the whole hybrid environment, and IT teams are really trying to understand and make sure that they get the same delivery of services if they were in the corporate headquarters, and I think they felt a loss of control and visibility in the services that are being delivered. I think the other thing that came out of this survey was about 25% of those said that they could get these issues if and when they happen, resolved in just a matter of minutes, but most said that it can take hours or even days to get through those, and that's obviously a really bad look for the company and really hinders productivity. So overall, I'd say it's been a challenge. I think as this onslaught of services that have come through and hampered and that everyone's trying to manage and get through, along with the lack of visibility when everybody's working from home. Of course, it's been fantastic for those of us that are working from home and made everything easier, but I think it's just made it that much more difficult for the IT teams that are trying to manage this new environment. >> Right, definitely difficulty behind the scenes there. You talked about the 25% of IT organizations being able to resolve quickly, but that leaves 75% of organizations where it takes more than a few minutes, and I can imagine individually, that might not be a big impact, but, Eileen, overall if it's taking more than a few minutes to resolve UC&C IT help desk issues, what's the overall impact to a business? >> It can be significant, and we hear a lot of little stories sadly sometimes on Lester Holt's evening news, but really what you are looking at here are longer periods of time where employees can't talk to each other. We've got email. We can probably compensate a different manner, but when it happens to be your customers not being able to talk to customer service reps in the contact center, couple of hours, that can be a big issue. Partners and suppliers who might be trying to get you important information very quickly. Maybe it's a supply chain issue item that they want to alert you to that you need to act on. That's a long period of time. And I think it's kind of important here to call out one special group, and that would be corporate executives. I think we've all heard about these big town hall meetings that corporate executives may be holding with employees or investors and all of a sudden their UCaaS support freezes, or it doesn't connect the voice in the video, and all of a sudden, you've got a very embarrassing situation. It really gets the attention of the public. Losing communication for a couple of hours, bottom line, it is going to impact productivity, customer service, and it could impact reputation, especially with those social media influencers that we all both favor and fear. So, when we were talking about our survey results, that is actually a top concern of IT executives, that productivity will get hit if communications problems do exist. So I think really ultimately for all of us in the business, disruptions and communication, it's going to be bad for business, any length. >> It is bad for business at any length, and that's a huge risk for businesses in any industry. I've been on those executive town halls where video wouldn't connect, and you just think, as much as we wanted that human connection during this time, and you couldn't get it, it made the the interaction not as ideal and obviously a risk for the organization. So, Jason, how can IT then jump in and resolve these disruptions faster, because time is of the essence here? >> Well, yeah, exactly. As we've discussed and Eileen just talked about, I think resolving issues quickly is really the key. I think we all know issues are going to happen, they just will, but it's really the IT team that can solve those the fastest is the team that's going to win, and so I think that's really the key to all of that. And one of the things that comes out of that is, again, from this survey is that only about 54% of the respondents said that they felt confident that they could understand root cause and be able to get to those issues quickly, which leaves about 43%, almost as many, that said they were less than confident or somewhat confident in finding that root cause, and so I think that's really the key there is really having the confidence to be able to find that, and to get that confidence, you need to be able to understand root cause quickly. And in order to get that, I think you need a combination of two things, which is passive, packet-based monitoring as well as continuous active testing or monitoring of those solutions. So, what I mean by that is being able to automatically and continuously test these services, even if nobody's on the system and nobody's on trying to make a phone call. So you have somebody who's trying to host, an active agent that's trying to host a meeting and others that are trying to join the meeting and sending an audio and sending and receiving video and looking at the measurements and trying to take all of that data in to really proactively understand what's going on and doing this every 15 minutes or every once an hour to really, again, get ahead of things before they become a problem. But I think beyond that, it's really about being able to take that data and the packets from those transactions that you were just testing and be able to trend that data and define problems and diagnose issues proactively. Again, as Eileen just said, before the CEO gets on there and tries to make his town hall call, so that that's really important to be able to solve those things more quickly. I think it's really a combination of a passive, scalable monitoring solution along with scheduled automatic testing of those, and along with the packets that go with that, that's really a combination of both. It's kind of a best of both worlds in order to get those things solved quickly. >> To get them solved quickly, I want to go back to something that Eileen said. You mentioned the word 'confidence,' and that I think it's important to point out that you're not saying that trivially, that IT needs to have the confidence that it has the right solutions in place to discover these faster. Eileen, from your perspective, talk to me about what that confidence means to IT and how it can shift up the stack to the C-suite. >> You know, honestly, processes and policies in these organizations are critical. They need to be able to notice when the trouble ticket comes in, and there's a lot of 'em, let's face it, and they're coming from all kinds of locations. Now, it's some of the remote offices. Some of 'em are still people at home. You've got to be able to know where to turn, what screen to use, what tool to adjust, what workflow to process, and that does come with practice, but it also comes with a solid set of tools and visibility strategies, and then you follow that process through, you work together. Maybe the voice, people in the network, people have to work together, maybe the cloud people, 'cause it's a contract with UCaaS, work together, gather the evidence and pinpoint the solution that's going to fix the problem with those locations. And it is, it becomes then a confidence builder, proof points. >> Right, proof points are critical. So, the solution that you both talked about, Jason, you elaborated on this, I'd love to get some real world examples. Tell me how you've seen this in practice. Jason, we'll start with you and then, Eileen, we'll go to you. >> Okay, yeah, great, I was just thinking of one that we had that really was one of the largest insurance companies in the country, if not the world, and when the pandemic hit, they suddenly had to send everybody home, and this is the lifeblood of their company, the contact centers that are answering these calls and the ones that were processing these claims. And as everybody went home, their strategy really was to actually go buy new laptops for everyone and implement VPNs that had a little bit of, but not fully and then implement SD-WAN, and so they had all of this traffic going over VPNs and through SD-WANs and new UCaaS solutions and all of this and what they quickly learned and found out was they just didn't have the visibility to be able to fuel, again, that word confidence that they were serving their their customers very well. So, they actually implemented one of our solutions and put these agents out at all their different desktops and started watching and doing these proactive calls and making going through the meeting life cycle and actually testing the bandwidths of their SD-WAN and ensuring all of those services. And what they found was they were able to solve some of the solutions that are even harder to solve normally, because it was affecting some users, but not all of them, and that's often harder to try and get their arms around. And so as they continued to do this, and just got their arms more around it and got more visibility, they really feel like everything's under control. And as of now, they're actually planning on leaving all those users working from home now, because they can actually ensure the same type of experience for both the users and for their customers as if those people were working from their corporate headquarters. >> Jason, that sort of sounds like a bit of a COVID silver lining. >> (laughs) Yeah, I think so. I think a lot of us actually started working from home and so there was kind of the silver lining of flexibility for the employee, but for the customer and the company itself, they learned this new visibility and this new way to ensure that across everywhere, wherever they may be, and I don't know that that would've come out without the COVID silver lining, as you just said. So I think it was something that really came out of it that might've been a good thing. >> And there are a few of those, which is nice. Eileen, talk to me about some of the experiences that you've had. What have you seen out in the field? >> Yeah, we have one really terrific energy company that was talking with us the other day, and their employees use Microsoft Office 365 which has the teams collaboration and communications system with it. And, what they've been doing for those at-home employees was configuring tests on their works stations, much like Jason explained, but it mimics exactly how an employee might be making their call and joining the sessions from video to audio, to going through login and log out. What's interesting is, and this is a compelling differentiator, a lot of tools may just watch traffic as it's happening, and certainly that's a value, but these tests even run when our agents are asleep. And what that does is these are all 24 hour a day businesses, and so maybe they have followed-the-sun contact centers or whatnot and something's happening in one part of the world, but then it's rolling to others, and we have all heard those disaster stories online when we wake up and we're hearing it on the morning news. So, if an organization can find the problem and detect it early enough and then get it when it's a few people that are involved, they can actually resolve it with our tools, find the root cause, implement a corrective action before the majority of their agents are even logging in in the morning. Nobody even knew that there was a problem overnight, because they were able to get to it and resolve it faster, and when you can do that, you're being proactive. And this, again, builds on the confidence that you get doing this kind of activity over and over and over again. But at the same time, it's also enormously beneficial from a business productivity perspective for the employees and certainly reputationally in revenue-based customer service, making sure that things are available whenever they're necessary. So, making sure they can perform their jobs, I know it sounds trite, but it's really the most critical thing we can help 'em with. >> Absolutely, 'cause I think, Eileen, one of the things that I've always thought for years is that employee productivity and employee satisfaction is directly tied to customer satisfaction, customer delight, and as you talked about, there's plenty of social media influencers who are happy to share news, good or bad, so that employee productivity is a direct relation on the customer satisfaction, the brand reputation. Jason, what are your thoughts there? >> Well, I think that's exactly right. I think it's, again, being able to continuously have your arms around that and make sure, because if you can't make phone calls or customers can't call in or things aren't working then it is, it's really a revenue impact, but it's also reputation impact, and you're going to remember that company that just didn't have their act together if you will, so I think it's important to, again, invest in this and make sure that no matter what, wherever your end users are or wherever your employees are, you're providing that experience just as if they were in the corporate office, and even when they're in the corporate office, being able to, as Eileen talked about, know ahead of time and proactively when issues happen in these very complex UCaaS and UC&C solutions that are out there now. >> And last question, Eileen for you, I imagine that these solutions are horizontal across every industry, every type of business, every size of business? >> Yeah, it's one of those phenomenon that's really critical is the ability to be ubiquitous in any environment, not being vendor-specific or dependent because now look at it, we shot that stat, three to nine different platforms in one company. If you had to buy three or nine different platforms to resolve problems, that reduces your ability to build workflows, consistent ones and know what you're doing every single time. You'd have to learn nine different platforms. That's not productive and that's certainly not realistic. So yeah, I think that this is really key. You have to be able to look at all of the traffic and be able to resolve the problems, regardless of what they happen to be running on. >> And the great thing is hearing the tools and the capabilities and solutions that NETSCOUT has to help businesses in any industry, at any size be able to identify these issues, resolve them faster and then create some silver linings. Guys, thank you so much for joining me today. Always a pleasure talking to you. This was really interesting to talk about the importance of quality end user experience with communication services for the employee productivity and of course, ultimately consumer customer satisfaction. We appreciate your insights. >> Thank you so much. >> Thank you. >> For Eileen Haggerty and Jason Chaffee, I'm Lisa Martin, you're watching a "CUBE Conversation." (bright music)

>>Yeah. Hello. Welcome to the Cubes International Women's Showcase, featuring International Women's Day. I'm John for your host of the queue here in Palo Alto, California. And we have three great guests videoing in from Kuala Lumpur as well as Bangkok. Johann Kwa, group CEO of K s K Group. It's just a Christina Equal, co founder and head of K s, K C Labs and Cindy, co founder of Sunday Insurance in Bangkok. Ladies. Thanks for coming on the cue. Appreciate you coming on. Thanks for Thanks for joining me on this special day. >>Thank you. Thank you so much. You >>guys are three sisters, trailblazing and the insurance and real estate through digital transformation in the cloud taking a three decade old family business to the next level raising the bar, as they say in the cloud business. Congratulations. Tell us how it all started. What's going on now? What does it look like? Where did it come from? Tell the Storey. >>Okay, so maybe I'll start, Uh, you know, since I'm at the group CEO level. So, um, as a quick introduction, you know? Okay. SK group, uh, were about 30 years old now, as a group three decades. Um, we started off as an insurance, uh, nonlife insurance company. Um, and then over the years, um, you know, we we operate in in South East Asia, So we are based in the US and markets. That message is also sitting in, um, and very quickly over the years, you know, we decided to actually venture into property development as well. Um, and really across the journey. Um, you know, we we've always been very, um, obsessed over the customers. You know, uh, and, you know, during this time and age, you know, all the customers are really digital natives now, and and, you know, the tech is very, very interesting. And so So starting in the year of 2017, we decided, um, to actually venture. Cindy and I at least we decided to start up our own, uh, tech, uh, called Sunday. Uh, Cindy is now the full time CEO and co founders. Um, and, you know, uh, it's an exciting journey from then on, uh, where now The first full stack ensure attack in in the whole of of the Asian market, uh, starting off in Thailand. Um, And then when Christine came back, to join the business. You know, since we were already in real estate, we decided, taking on from the inspiration of what we did with Sunday, how about we do the same in in in property? Because we obviously saw, you know, there was super loads of opportunities that we could we could we could do. And and a year ago, we gave birth to cast a city lapse. Um, now a prop tech company based in Malaysia. >>Christine and Cindy tell the storey here because this is actually fascinating. Storey, your sisters, your entrepreneurial. So you know each other? You're related and you've got ups and downs with the startups and growing companies changing landscape. A lot of challenges. You all gotta get along all the time. How's it going? What's it like? Mm. >>Maybe I'll start. I think I think for me I'm probably the newest addition to the trio in the, you know, working together kind of space. So for me, I think it's all about really learning how to, you know, separate your professional and personal life. And like you mentioned, you know, we live together. But we also work together. So for me, I think I took a >>lot of advice >>and direction. Um, both from Johann and, >>uh, help >>me a lot. Um, so So I think that's been my experience. Been great So far, Um, they've been really, really supportive. And I think going through this journey of, you know, like, founding a company together, it's obviously very challenging. And so I feel very fortunate to have two sisters who have already gone through it once, you know? >>So for the other guests is trying to get on the cube here. Over there. Um, sounds like fun. Uh, Christine. So on the city labs, you gotta cheque side of it there in the in the property tech. That's exciting. How's it going over there? >>Uh, super, Super cool. Super fun. Uh, has been one heck of a journey building a company from scratch, let alone in tech. I think you know, we created K s K C d lives because we really wanted to modernise the real estate industry, uh, and create, like, super transformative solutions, uh, many for two reasons. You know, one is to improve the quality of life, um, of the community around us. Uh, and secondly, really to harness all the technology and this unused data right in the real estate industry. And try and say, how can we use that to make more intelligent business decisions? Yeah, so So really, Um, I guess for us, it's been really exciting because we've launched two products. Uh, you know, one of which is Ai driven, dynamic pricing engine. And we realised that actually, the way that homes are priced today, uh, in real estate is super RK right? You only use a few basic variables. Like, how big is your house? What views do you have? But then we realised that, actually hey, with a I where you suddenly can use, like, hundreds of variables, um, and even, you know, consisting of wellness variables, for example. Um, and you can really customise pricing all the way down to a single unit level. Uh, and we realise that by doing this, we could actually unlock, um, ferret prices for our customers while also constantly kind of tracking the financial health of the company. >>Awesome. Cindy, I wanna get you in here. A co founder, Sunday Insurance. That was the origination. But a lot of change data drives everything machine learning. You gotta have the state of the art. What's going on with you? >>Yeah, I think for us, essentially, uh, we're operating in a very old industry. Um, it's one of the oldest industries globally. And if you look at the entire insurance value chain, um, every part of the process can actually, it's all about data. You can. It can be disrupted. Um, but yet every inch of the value chain is also regulated. So I think essentially what we're trying to do is, um, we're trying to really innovate the customer journey. So imagine if, um, even in the States now and even coming back to Asia, a lot of how people buy insurance is still very face to face agency. But I think in the future is going to be remote online on your app, through any partners as well. So I think, uh, we're trying to adopt any machine learning to really scale and automate, uh, the journey of anyone who's trying to buy insurance. But at the same time for insurance companies were also trying to help them automate that function itself. So imagine if banks are trying to dish out loans and you're trying to predict. What's the credit risk of every, um, single customer? That's exactly what insurance company needs to do as well. Um, And I guess insurance is all about buying a service as well. >>It's unlike you >>know, I'm gonna buy an apple. It comes to the hardware, >>right? So we're >>selling a service. So essentially you're service has to also dramatically changed. And I think these days, especially when we're operating in, uh, Thailand, Indonesia is one of the highest adoption rates for mobile these days. Everyone does. Everything lives on on the apps. So, um, insurance companies also needs to really on board their journey on that as well as increased engagement. So I don't just want to be an insurance company where, um, I speak to you and I have an issue with my claim. I want to really build a relationship with you and engage you differently. So I think it's actually that's the mission for a Sunday. So I think Imagine if imagine an insurance company 50 years in the future. How would it be? Uh, that's our mission. >>This is a great example. You guys, First of all, you're very dynamic. Thanks for sharing your storey. But when you get into the tech here, if industries that are transforming because of the digital transformation, the consumers expect the apps. You guys, as co founders and entrepreneurs now running this big business have to meet the demands and leverage the technology. How have you done that? How are you guys manage that? What kinds of decisions have you made? And you share some either experiences or observations of how to navigate and how you're riding that wave. >>Yeah. So I think if you hear from what Cindy and Christine has just mentioned, I mean, uh, we were playing in, you know, two of the oldest and largest industries in the world. Real estate and insurance. And, uh, you know, in both industries, as I said earlier, you know, it's really all about the customers, right? Um you know, in in the past, we used to think of of businesses as you know, what's your vertical and the horizontal today? Um, at least four k s k and and and all the all these, um, you know, tech ventures that we are now venture building. We're really thinking about it from the customer land. So really thinking about it from a customer ecosystem perspective. So instead of, you know, creating products and and having that push out to the customers, you know, we use tech and data and and especially data today and the right amount of data and what type of data that we want understanding that and really, um, building that product and really the services, uh, for the customers. So once you know the customer enters our ecosystem, whether you know, in your real estate, um, ecosystem or whether it's in your insurance ecosystem, we want you to to continue to stay with us, um, and to trust us. Um, and so it's not just about selling you a product, but really, you know, like, what Cindy says building a relationship with you because we think that, you know, obviously you know when insurance is something you really need when when when things go wrong in your life, we don't only want to be there. When things go wrong in your life and for real estate, you know everybody needs a shelter. So so so that's why we think that building relationships are very important and from really true, that lands is when you really think about the ecosystem and you think about data. I think Cindy Increasing gave some examples of how we're approaching it. Um, a lot of people start from from from a, you know, from a traditional business and from within. But for us, um, we decided to actually take it outside. Um, and, you know, take the approach of venture building from a startup, um, but really have, on the back end, really have that Connexion to the core businesses. Because what the core businesses understand is, you know, lifetime and experience of how customers feel and and, you know, um, in insurance, it's really about how to run a financial institution in real estate is really how to build buildings, and that is something that we can't take away. But, you know, you use technology to enable and to power. But what venture and start ups do extremely well is really the way we are extremely nimble and the way you use tech and data to navigate the quick changes of customer demands. And and you know, one thing an app and it's all about quick iterations. Right? When you build a super app, how do you incorporate all the features that are coming in, you have to keep on, you know, iterating changing, innovating, um, and innovating small with quick wins and then taking on a larger scale. And so the way we position ourselves is when you have to start up and you combine that with the core. Um, and putting the two together is how, how, how we look at things and that four minutes, the whole ecosystem >>that's awesome and being agile as fast and speed is key if you want to be there. Startup. But at the core business, that's going kind of slow. You got to kind of make everything go faster. That's a great, great insight. Let's talk about the disruption of the property industry again. That's real estate now with the Internet of things, technologies and also people expect technology. They wanna have access. I don't wanna have all these passwords and, you know they want to have easy in and out. They want good efficiency, save money. What's the disruption angle on? Um, the property neck. Christine, what's your How do you see that? The big disruption going? >>Yeah. So I think as Johann already mentioned before, you know um I think our customers we know are becoming, um, digital natives. Right? And they expect very convenient lifestyles. And we're all about our customers. So, actually, that's why we launched also another product, right where we're taking all of these things that you just mentioned, you know, about Iot into account. So what we found is, um, that actually, today, um, you know, the village about real estate is that we all live through that life as well, so we can experience that. Uh, we found that residents today, um, they find it quite challenging to request, you know, basic services like housekeeping managing, um, their defects, their tenants. Um, you know, even the financial planning and even getting into the building, right, they want more convenience. Um, but we realised that actually, all these services in the real estate industry right now and even in the prop tech space, they are very, very segmented. They're all discussed across multiple different apps. So what we really try to do is hey, let's try and consolidate all of this into one single app, which we have done, which is really cool, And it helps our residents really stay engaged and connected with our property. Um, what we did also was on the Iot front. We we were actually the first developer in Malaysia to also integrate, You know, future proof solutions like remote lift calling as well, um, into the mobile app. And that's to really go like, push on the Iot front. For us as well. >>Must be great for retention. It's all the gadgets are built into the of course. You have good WiFi fibre in their everyone's got good band with >>for sure >>It's like water and plumbing. Uh, I'd like to get everyone everyone loves that. I gotta ask Now, on the on the on the on The disruption is great. Now you've got the clouds, the clouds here for actually Amazon. You guys are big customer because you guys can move fast and they do all the heavy lifting. How are you guys seeing that helped modernise in the industry of insurance? Because that's a big vertical for a W s and you guys are doing is Cindy. What is the What is the modernisation? Um, half that you guys have taken with a W s. >>Yeah, sure. So I think essentially, for insurance, it's a product development. And when we talk about product development means, um how do you price, um, every certain individual or company very differently, right, Because everyone has very different risks surrounding them. Uh, currently, what we face is that it's a flat pricing fixed pricing. Um, and it's not really personalised to you. If you are a very good behaviour and safe kind of customer, it doesn't translate to any premium savings for you. Um, so I think, uh, part of insurance is to give, for example, affordable access to health care. But if your premiums isn't sustainable for health insurance, then it doesn't really need the point. So, uh, for Sunday, like, how we're trying to trying to do it differently is, for example, we use some AWS cloud solutions and AWS Lambda too, really power our machine learning Savalas and Cloud infrastructure. So, for example, uh, Sunday we are a serious bee companies sober and the growth stage. So at any point in time, we need to ensure that our infrastructure is able to support a huge spike in transaction volume, and we're working with large scale partners like telcos, e commerce companies, or even within our organic channels. So our AI machine learning risk prediction model, which is basically, um, powering our premium pricing engines whenever there's any requests coming in front of the Web for foreign quotation. For example, if someone wants to buy health insurance, um, it can go up and spike. But also, the data model is actually pricing, uh, processing billions of calculations, ingesting a lot of data points. Uh, it needs to do that within seconds, so yeah, I think a w s. We've been using it from day one since we launched. It's been, uh, helping us on >>that and make it go faster. That's the big thing. I gotta ask you when you guys have this family business now, three decades, you got a lot going on extending that legacy and sustaining the family legacy. I love the Storey. So who decides whether to do the startup and you guys draw straws? Is that you guys flip a coin? You gotta who runs the big business? How do you guys decide that? Mm. >>Um, maybe I'll >>I >>would say maybe it came very naturally to us. Really? I guess Here we don't have to disclose. Our age is a little bit, so I mean, I mean, we all actually the background and really all three of us. Before we came into the family business, we were all working professionals in very different fields. I was a I was in banking. Cindy was a lawyer, and Christine was a a doctor, actually, Um um, but, you know, I came back first. I'm the eldest, so after, you know, walking outside and looking into the family business. So I came back first, and and And from there, I took over the insurance business and looking at it, it was a very lonely place to be. So, um, you know, after a couple of years of Cindy being a professional life, you know, we said, Hey, would you like to come back? And let's, uh, take a different journey with insurance and see how we can build something different? Uh, since we know a lot about insurance, but let's make make make a difference and and and, you know, be sustainable, but also evolve over time and show the world that insurance is actually pretty sexy, actually. Um, and then, you know, Christine saw the fund that the two of us were having, uh, already started building a real estate on on my end. Uh, and then, uh, she came back. And, you know, we have a conversation, and we said, Look, looking at you know what we're doing in Sunday? You know, building pricing engines and being able to price to a single customer level. Um, we saw that opportunity in real estate, and, uh so I asked her. I said, Look, would you like to do this? You know, because I think there is something cool. Um, the three of us can band together and still inspire each other share ideas across each other. That's an opportunity that a lot of people don't get right. I mean, to all these industries in the world being able to cross share ideas. Uh, and sometimes inspirations and ideas don't come from the same industry. Uh, and so I think. And that's how we started. Really, John, it's not. Maybe we're lucky, and we should be grateful for >>that. You're all power women. I love the storey, and it is good that you come together, and I think the entrepreneurial kind of twist makes it more fun. But not everyone is cut out with the entrepreneurship, but it also gives you more risk management. You can. You can go after opportunities I love. I love the strategy there. You guys are great leaders. Any advice for other aspiring women leaders and entrepreneurs out there who want to make a difference? Make an impact? The world is. Change is getting better for everyone. And and again, entrepreneurial could be in big companies and also big companies doing startups. There's a whole new world. What advice would you guys give other aspiring women leaders? Okay, >>I'll keep it short from my end. I think for me it's about really following your passion following your ambition. And lastly, I think not to try and not feel like you need to conform to any gender stereotypes because I think in male dominated industries such as real estate, our are attack. I think people might have some ideas about you know what a what a tech leader or what a real estate leader might have to look like. But you don't have to conform to that. So that's probably my advice. Uh, >>yeah, I I fully agree with Chris right there. I think, um, gender isn't an issue here. If you have a passion and you identify, there is a market opportunity that you can, you know, you can really do something about it. Just just pursue it. I think most importantly, if you ever want to be an entrepreneur and start your own business or your own, start up. Uh, so long as you have the confidence, I think you're you're good to go. Um, there's a lot of talk out that that or, you know, um, women led start ups are not >>attracting >>funds, but we haven't faced that anyway. In this part of Asia, I think there's a lot of, um, I think it attracts even more attention. If you're a woman in a male dominated that industry like, hey, then you know it's it's quite unique. So I think you have a strength there, and I think there's a lot of diverse talent out there. Um, post pandemic. A lot of people are looking for changes as well, so I think it is a lot of a lot of opportunity out there. >>Yeah, Joanne, you know, you know, the thing is with cloud computing, it's a level centre. It really because if you can come together, whether it's sisters like you guys, powerful sisters and professional experience coming together leverage technology to re factor old industries. It's all about the numbers and the performance. At the end of the day, you know, you move faster and you take territory and beat the competition. >>Ultimate >>the ultimate uh, leveller. Well, congratulations. You guys are great. Thanks for coming on The Cube Sisters. You guys are amazing. Great Storey Love it. Thanks for coming out and celebrating International Women's Day feature today as part of our international women's showcase here in the Cube. Thank you so much. >>Thank you. Thank you for having us. >>Okay. The Cubes International Women's showcase Going on all year, this time featuring International Women's Day The big celebration. I'm John Ferrier, host of the Cube here in Palo Alto, California. Thanks for watching. Mm mm

>>Welcome back to the cubes coverage of splunk.com 21. Finally, some Arten twenty-nine next word Holloway, the director of technology alliances at Z scaler ward. Welcome to the program. >>Thanks for having me great to be here. >>Talk to me a little bit about Zscaler and Splunk working together. How are you helping companies to improve their security posture? >>Yeah, I think, um, you know, we're each, uh, market leaders in our respective areas as these scale are the market leader for cloud delivered security as a service and Splunk is really the market leader in log monitoring and correlation across the entire security environment, uh, really providing their customers deeper insights through zero trust analytics and orchestration, and together our integrated solution protects enterprises from threat campaigns, reduces security operations burdens through automation, and really provides our customers with actionable data much faster than they could do, uh, on their own. >>That actionable data at speed is, is incredibly important. You mentioned zero trust. That's a hot topic right now. Let's dig more into how Z scaler and Splunk handle zero trust. >>Yeah, well, I think first and foremost, um, our integration is cloud native. Um, so you're getting that data in real time and not requiring any on-premise appliances or infrastructure. Um, and that's a real key thing in this cloud enabled cloud-first world that we're all operating in. And by getting that data in quickly to Splunk really enabled, uh, our customers to do some interesting things. Um, we have some prebuilt dashboards, VRR Splunk application, uh, that allows customers to very quickly leverage our data and logs on and give insights into what exactly is going on. And they can view usage, uh, applications threats all immediately. And that data that we're sending to Splunk is, uh, natively configured in splints SIM, uh, logging, uh, protocol. So it natively and easily is, um, leveraged by our users, uh, when they deploy out the Splunk app from Zscaler. >>So what are some of the things that differentiate how's the scalar delivers zero trust network access compared to some of the other guys? >>Well, I think first and foremost, um, zero trust has to enable zero network access. It requires zero access to the network. So you only connect to a particular application, really eliminating the possibility for lateral movement. It's really, uh, like the difference between letting a guest in your office wander around your headquarters on escorted, uh, versus escorting a guest to a meeting room, and then it's scoring them out once the meeting is over. I think the second key really is then also having a zero attack surface. Anything that resolves on the open internet today can be discovered exploited, um, denial of service. This means traditional solutions like firewalls, VPNs, uh, any web portal will that are visible on the internet are ultimately an attack surface, which is really a security risk. Um, if they can find it, if they can discover it, they can attack it. >>If they can't find your application, they can attack it. So that's really the key about a zero trust approach. That's Zscaler takes a, we don't expose anything on the internet and finally we have zero pass-through. So our zero trust exchange, doesn't go through a pass through connection, if utilize as a proxy architecture, which allows you to hold the data, inspect it, and then making a verdict before allowing it to pass. This is really a fundamental key for zero trust, ensure that all connections are secure from threats and data loss, and only allowing things in based on the context of the actual data itself. >>We've seen a massive change in the threat landscape in the last 18, 19 months. I'm wondering what, if you can kind of elaborate on some of the trends from a security perspective, a threat perspective that Zscaler has seen? >>Yeah, I think, um, you know, with the pandemic, obviously, um, it's greatly accelerated, uh, work from home work from anywhere. Um, so users are no longer on their company's corporate networks. Uh, they're working from their homes, they're working from traveling around wherever they might be, uh, in the country. And I think that really has increased, um, the threat attack surface. Um, it's not protected by the traditional security infrastructure that companies have spent years putting in place in their networks because everyone is remote. And we think things like a 500 and 500% increase in ransomware delivered over encrypted channels, for example, uh, and 30% of malware delivered through trusted apps, such as file sharing and collaboration tools. Um, and so ultimately the largest risk is really lateral movement inside of the corporate networks. Uh, once these things get in because traditional approaches such as VPNs are placing the users on the network, uh, and ultimately exposing them to risk. >>You said a 500% increase in ransomware delivered over encrypted channels. That's huge. And that is what, one of the things that we've seen just this year alone is ransomware becoming a household word, everyone understanding what happened with the colonial pipeline, the executive order, that's a huge threat there. And of course, ransomware is also getting more personal. Are you seeing that as well? >>Yeah, definitely. Um, I think again with all of the remote workforce being distributed, um, and no longer protected by the traditional security approaches, um, it's exposing them to this ransomware and it's what attackers are really kind of leaning on to go after, um, these remote users in order to gain access into the corporate infrastructures and ultimately deploy ransomware within those infrastructures. And that's really why zero trust is so important. Zero trust is really the idea of kind of putting an exchange, uh, in the, the cloud itself, so that security is buy all of your users wherever they may be. So regardless of where those users are working, whether it's remotely from home, whether it's traveling at a hotel, uh, whether they've decided to sell everything and get an RV and travel around the country, uh, by placing a zero trust cloud exchange, uh, in place to secure your assets and secure the connections, uh, you're protecting those users wherever they are, and ultimately protecting against that ransomware threat. >>And that's going to be key as this work from anywhere persist for a while. And then eventually there'll be probably some hybrid environment with a good amount of people working remotely and that the need to secure that landscape and deliver that zero trust. Is this going to be table stakes for businesses in any industry? Talk to me about, uh, about digital transformation. We've been talking about that for years now, but what are, how are some of the ways that Z scaler helps your customers? And then what are some of the things that you've seen perhaps accelerate in the last 18, 19 months? >>Yeah, I think we touched on it already. Obviously the pandemic really accelerated the work from anywhere work from our remote, um, dynamic. Um, and I think, uh, you know, that combined with, um, most corporations moving towards embracing the cloud and, uh, software as a service has really accelerated this whole digital transformation movement. Um, and the pandemic has just made it, you know, come to us exceptionally faster. So now that, um, users are working remotely anywhere, and now that your assets are no longer in data centers, but sitting in the cloud, whether it's things like, you know, Workday or Microsoft office 365 or Salesforce or whatever application that you're using, you know, the traditional castle and moat approach to security that we used to take, doesn't really work in this cloud first world. Um, you know, corporations spend a lot of years deploying firewalls, VPNs. DLPs things of that nature in all of the data centers that they physically controlled. >>Uh, and that was great when all of the users were physically at the office and going through that physical infrastructure. But now that the pandemic has accelerated this remote work from anywhere, uh, dynamic, uh, that old castle and load approach doesn't work anymore. So you have these users scattered around, not connecting through your data centers, not connecting through your infrastructure. And the pandemic also really explodes, um, the weakness of that, that model as well. Uh, when everybody got sent home, initially, they were leveraging those VPNs to try to connect back through those legacy data centers and then out the cloud. And we're really experiencing a terrible, uh, experience working in that environment. Uh, the VPNs were overwhelmed. They fell over and a lot of users started just going directly to the cloud themselves. And that's really where you risk this exposure. And this problem with ransomware as they were bypassing traditional security measures, if you had in place and exposing you to a much greater risk. And that's why the zero trust approach that Zscaler takes was much more effective and combined with what we're doing with Splunk really needed to do to get full visibility across that deployed disparate infrastructure, that you have an insight into what those users are doing and the ability to automatically react to it with the integration that we have with Splunk, sor >>That insight is absolutely critical. You talked about that rapid scatter to work from home that occurred 18, 19 months ago. And of course we all, all of us workers that were remote and are still remote we're are reliant on SAS tools, collaboration tools, video conferencing. And of course you mentioned a step now 30% of malware is delivered through trusted apps, like collaboration tools. Talk to me about how Zscaler and Splunk are helping customers combat challenges like that as they still are in this dynamic work from anywhere environment. >>Yeah, I think, um, we've got a couple of interesting integrations. Again, first we're automatically sitting the data from, uh, all of our ZScaler's zero trust infrastructure to Splunk, uh, automatically normalized and their SIM format. So it is natively and easily ingested into Splunk. And you start getting actionable insight from that. Uh, once that data is in Splunk and start doing an analysis, um, and seeing what is going on with those users, looking at things like, uh, most hits sites sites that are blocked, uh, any suspicious information that they're starting to see through their analysis and correlation engine. Uh, and they can even take action on that. If they suddenly see users going to known bad malware sites, for example, they can use the Splunk soar integration that we have to call the endpoint detection and response system that they may have in place and block that user from connecting it. So we're giving users full insight into what their user base is doing and the ability to automatically react to that and even block and prevent a bad actions that can ultimately expose them to risk >>The customer example that you can share of how you guys are doing this together. >>Uh, I mean, we have many examples through multiple verticals, be it financial healthcare, uh, manufacturing, uh, there's one insurance company in particular that I can think of that, uh, has integrated the solutions together. And really, as soon as they put the two integrations in place, we're able to identify a number of users that were hitting malicious sites and automatically block and protect those users from going to those sites and eliminating that risk from their environment. >>Excellent. Talk to me about some of the key, uh, pain points that you're solving for and some of the business outcomes that customers can expect working with Zscaler and Splunk. >>Uh, great question. Uh, I think one of the first is the zero trust exchange. The vScaler Habs enables really the much needed modern workplace, um, that COVID is further accelerated. Um, users really can work anywhere, uh, so that they can safely access any application from any network. Uh, whether that location is external, internal on any device. And the exchange really provides consistent security by being the inline policy enforcement point between all devices and services. The other thing that I think is key is users really require a great experience. And so if something goes wrong, you need to be able to quickly figure out what that is. Um, so we're constantly collecting a huge amount of telemetry, uh, to really understand and see exactly what that user experience is like, uh, and what issues they may be having, and really giving you the ability to see those issues before they arise and cause a problem. >>So you can proactively identify them and eliminate them. So they don't cause a problem. Uh, we've been able to allow our customers to roll the solution out and days and even over the weekend in order to get started. And this really allows them to accelerate, implementing zero trust for their organization by ensuring that all traffic for the internet goes through the zero trust exchange first, where it's fully did prepped it in inspected for any threats or data loss. And that's really key. Uh, I think one of the things that's so important in differentiating about what ZScaler's does is we're able to inspect traffic at scale. Uh, we have over 150 points of presence around the world that allows us to inspect all traffic, including SSL, encrypted traffic. So I think that's really a key point to focus on is that, you know, most of the threats that you and I were talking about earlier, especially around ransomware, tend to try to hide themselves, uh, and SSL, encrypted traffic. So whatever solution you want to deploy for CR trust it's imperative, that it has the ability to fully expect SSL traffic at scale, not just a limited subset of that traffic, but all of it, because so much of the threats today are coming, uh, in an encrypted format. >>And that's probably something that I I'm wondering if you, if you're seeing that those threats in terms of the increase and the, and the significance is only going to persist as this work from any more environment does. So how can customers get started with these scaler and Splunk? Where would, where would they start? >>Well, I think, uh, the great thing is, um, if they are a Z scaler customer or a Splunk customer, uh, it's very easy for them just to go to the Splunk app store and download the Zscaler app, uh, to allow them to very quickly and easily integrate the two solutions together. Uh, once they've made that connection, uh, we start automatically sending all of our logging and telemetry data into Splunk, and then they're able to leverage to the Splunk, the infrastructure and the dashboards that we've created to automatically start getting that insight into what's going on within their user community to see what threats are spooling up and to leverage Splunk, soar, to take automated action, to protect and eliminate those threats from their environment. So it's very easy for our users and our customers to get the application up and running quickly and start realizing value from the deployment itself. >>Yeah. You mentioned a stat a minute ago in terms of being able to deploy over the weekend, not fast time to value in this dynamic, uh, landscape where the threats are constantly changing, that that fast time to value is critical for businesses in any industry. >>Yeah, absolutely. Uh, I think that's the key again in this cloud world where you no longer have, uh, everything in your data center, and it's not a very simple and easy process. Just someone down to the data center to deploy a new solution, the solutions that you do choose need to be able to spin up quickly and easily. And that's really what we've built together with our integration with Splunk. Um, it was designed to be easy, quick to deploy and quick to re leverage value from. >>Excellent. Thank you for joining me talking about what Z scaler and Splunk are doing together, how you're helping customers to solve key pain points and that fast time to value that you're delivering. We appreciate your insights and your time. >>Thank you >>For ward Holloway. I'm Lisa Martin. You're watching the cubes coverage of splunk.com 21.

(upbeat music) >> From around the globe. It's theCUBE with digital coverage of IBM Think 2021 brought to you by IBM. >> Welcome to theCUBE's coverage of IBM Think, The Digital Experience. I'm Lisa Martin. I've got two guests with me here today. Ryan Dennings joins us, Manager of ECM Solutions at Auto-Owners Insurance Company, Ryan, welcome to the program. >> Thank you. And Michelle Christensen is here as well, VP of Enterprise Report Management Practice at enChoice, Michelle, it's good to have you on the program. >> Thank you. Thank you. So let's, Ryan let's go ahead and start with you. You guys are a customer of enChoice and IBM, talk to us a little bit about Auto-Owners Company. I know this is a fortune 500. This was founded in 1916. You've got about nearly 3 million policy holders but give us an overview of Auto-Owners Insurance. >> Sure. So Auto-Owners Insurance is an insurance company that's headquartered in Lansing, Michigan. We write insurance in 26 States throughout the United States. Despite our name being Auto-Owners Insurance, which is how we started, we write all personal lines, commercial lines, and also have a life insurance company. >> So comprehensive and that across those nearly 3 million policy holders. Michelle, tell us a little bit about enChoice. I know this, you guys are an IBM Gold Business Partner but this is enChoice's first time on the Cube, so give us a background. >> Sure, sure, great. So enChoice are an IBM Gold Business Partner. We have had 28 years success with IBM as a business partner. Our headquarters are in areas of Austin, Texas, and Tempe, Arizona, as well as Shelton, Connecticut. We cover all of North America and we are a hundred percent focused on the IBM Digital Business Automation Space. We have about 500 customers now that we've helped through the years and we continue to be a leading support provider as well as an implementation partner with all the IBM Solutions. >> And talk to me a little bit Michelle about how it is that you work with with Auto-Owners. >> So we assisted Auto-Owners recently in their digital transformations journey and they were dealing with an antiquated product and wanted to get moving forward, you know provide a better customer satisfaction experience for their client's agents, and so we partnered with them and with IBM and bringing them a content manager on-demand solution as well as navigator and several other products within the IBM Digital Business Automation Portfolio. >> Excellent, Ryan Oh, sorry Michelle, go ahead. >> Nope. That's that's fine. All right, Ryan, tell us a little bit about Auto-Owners, your relationship with IBM and enChoice and how is it helping you to address some of the challenges in the market today? >> Sure. So Auto-Owners has a long-term relationship with IBM originally starting back years ago as a mainframe customer and then, you know more recently helping us with different modern technology initiatives. They were instrumental in the nineties when we redid our initial web offerings, and then more recently they've been helping us with our Digital Business Automation which has helped us to mature our content offering at Owners. >> So you have had a long standing relationship with IBM, Ryan, and then you mentioned the nineties at a time when we didn't have to wear masks on our faces. (laughing) So a couple of decades it goes back, yeah? >> Yes. For sure. Yes. Even further than that, that, you know back into the seventies from the mainframe side of things. >> The seventies, another good time. (laughing) All right. So Michelle, talk to me a little bit about what enChoice is doing with IBM Solutions to help Auto-Owners from a digital transformation perspective is as I said this is a company that was founded in 1916, and I always love to hear how history companies like that are actually working with technology companies to facilitate that transformation. It's a lot harder than it sounds. >> Well, that's correct. Yes. As I mentioned, we're focused on helping customers develop their strategy, their digital strategy and creating those transformative solutions. So we're helping organizations like Auto-Owners with their journey, by first realizing their existing digital state, what challenges they might have and what needs they might need, and then we break that down or we deconstruct those technical and processizations and finally we re-invent their strategic offering with modern capabilities. So we're focused on technologies like RPA, machine learning, artificial intelligence, they're more efficient, scalable, and secure, so any way we can bring those technologies into the equation we go for it. So this offers us, our clients smarter and more intuitive interfaces creating basically a better user experience, and a better user experience then becomes disruptive to their competition. So they gain a better place in the market space. >> Ryan talked to us about that process as much as you were involved in it. I liked that Michelle said, you know we kind of look at the environment, we deconstruct it and then we re-invent it. Talk to me about how IBM and enChoice has helped Auto-Owners to do that so that your digital infrastructure is much more modern, and I presume much more resilient when there are market dynamics like we're living in now. >> Yeah, for sure. So, you know, we've, we've gone through a couple of transformation journeys at Auto-Owners with IBM. When I started the team about seven years ago we originally started using file NATS and data cap, and case manager, and content aggregator as our first movement from a traditional platform that we had for content management into a more modern platform, and that helped us a lot to improve our business process, improve how we capture content and bring it into the system and make it actionable. More recently, we've been working with Michelle and the enChoice team on our migration to a content management on-demand platform, and that's really going to be transformative in terms of how we're able to present content and documents and bills to our agents and customers, to be able to transform that content and show it in ways that are important for our customers to be able to see it, to engage with Auto-Owners in a, in a digital era. >> So Ryan, just a couple of questions on that, is that is that a facilitation of like the digitization of processes that had some paper involved cause you guys have about 48,000 agents, so a lot of folks, a lot of content, tell me a little bit more about how that like content manager on-demand, for example and what you're doing with ECF, how has that really revolutionizing and driving part of that digital transformation? >> Sure. So, you know, there's two parts to that in terms of that content management on-demand journey. One is the technology portion of it, but IBM's provided, and that suite of software gives us some functionality that we haven't had in the past. Specifically, some functionality around searching and searchability of our content that will make it easier for people to find the content that they're looking for, ability to implement records management policies and other things that help us manage that content more effectively, as well as some different options to be able to present the content to our customers and agents in a in a better and more modern way and enChoice's role in that has really been to guide us on that journey to help us make the right choices along the way on the project and help us get to a successful implementation and production. >> Excellent. Michelle, talk to me about Hybrid Cloud AI Data a big theme of IBM Think this year. How is enChoice using Hybrid Cloud and AI? You mentioned some of the other ways but kind of break into that a little bit more about how you're helping customers like Auto-Owners and others really take advantage of those modern technologies. >> Well, sure, sure. So of course with the Cloud Pak offerings that IBM has come forward with and where we focus in the Cloud Pak for automation, several of those offerings are some of them are built specifically to survive or to to be hosted in a hybrid environment, and as we're working with Auto-Owners transforming their platforms going forward for example, they just invested in, in a, a I just lost the word here. They just invested in a, a new platform, mainframe platform where they're going to be leveraging the red hats, and from there they'll drive forward into containerization. So Ryan mentioned some of the ways that we'll be presenting the content for his agents and his customers in a particular that entire viewing platform itself can be moved to a containerization state. So, so it's going to be a lot easier for him to transition into that and to maintain it and to manage it. And of course, just that whole, the ease of function around it will be a lot easier. So we are in our area as an IBM business partner, we work with these solutions to try to stay ahead of the game, to try to be able to assist our customers to understand what makes sense, when is it time to move into those. It's great to take advantage of the new stuff but nobody wants to be, you know, the bleeding game. We want to be the leading game. And so that's some of the areas we focus with our clients to really stay tight with the labs, tight with IBM and understanding their strategies and convey those and educate our customers on those. >> Excellent leading edge. Ryan, talk to me a little bit. I love this a bank, sorry an insurance company from the early 1900's moving into the using container technology. I love stories like that. Talk to me a little bit about Hybrid Cloud AI and how those technologies are going to be facilitators of the continuation of the digital transformation, and probably enabling more opportunities for your agents to meet more needs from from your policy holders. >> Yeah, for sure. So first and foremost, we were a Red Hat OpenShift customer before IBM acquired them and we were doing microservices development and things like that on the platform, and then we were super excited about IBM's digital business automation strategy to move to a Cloud Pak and have that available for software products to run on OpenShift. At the end of last year, we updated our licensing so that we can move in that direction, and we're starting to deploy digital business automation products on our OpenShift platform which is super exciting for me. It's going to make for faster upgrades, more scalability, just a lot of ease of use things for my team to make their jobs easier but also easier for us to adapt new upgrades and software offerings from IBM. There's also a number of products that are in the containerized or OpenShift only offering as they're initially coming out, whether it's mobile capture or automated document processing to name a couple. And those are both things that we're looking at Auto-Owners to continue to mature in this space and be able to offer more functionality to our associates, our customers, and our agents to continue to grow the business. >> Very forward-thinking, awesome Ryan. Thanks for sharing with us what Auto-Owners Insurance is doing, how you're being successful and how you've done so much transformation already. I want to throw the last question to Michelle. Take us out Michelle with what's next from enChoice's perspective in terms of your digital transformation. >> Well, we have been a hundred percent focused on helping all of our customers develop their digital strategy and and creating their own transformative solutions. So as we continue to work with our clients, take them through the journey, as I mentioned before, we try to encourage them not to focus on the, the technology itself, but really to focus on creating their exceptional customer experience when driving their digital strategy. And we see ourselves as, you know helping transform our client's experience such that you know customer experience becomes what enChoice does best. So we see not only our own organization going through the transformation, but making sure that we're taking our clients with us and with 500 clients we're, we're really busy. So that's always good. >> That is good. It sounds like the last year has been very fruitful for you, and I love that you mentioned customer experience, Michelle. I think that is so important and as well as employee experience, but having a good customer experience, especially these days. Table-stakes. I thank you both so much for sharing what you guys are doing with IBM Solutions, the transformation that both of your companies are on and we look forward to hearing what's to come. Thank you both for your time. >> Thank you. >> Thank you for Ryan Dennings and Michelle Christiansen. I'm Lisa Martin. You're watching theCUBE's coverage of IBM Think The Digital Experience. (upbeat music)

>>from around the globe. It's the Cube with digital coverage of AWS reinvent 2020 sponsored by Intel and AWS. Hello, everyone, and welcome back to the cubes. Continuing coverage of AWS reinvent 2020 Virtual the Cube Virtual. We're here covering the partner ecosystem and some of the new innovations coming from the reinvent community. Let's talk about something that anyone who drives a vehicle can relate to. Roadside assistance with me or Beth Davidson, chief marketing officer at a zero, and Raj borrows the vice president and c t o at zero folks, welcome to the Cube. >>Hello, nice to see you. >>So let's start with you. Maybe talk a little bit about your your mission, how you work with automakers. You've got, you know, a lot of good pipeline, their insurers and other others in the in the ecosystem. Tell us about the company. >>Absolutely. So for 50 years, we've been helping consumers with their cars. Um, that's what it comes down Thio. We know that one in three people has a roadside event every year on the way you think about that is, you know, if in three years you haven't had a roadside event, tick tock. You know, statistically, it's coming for you. We work with everybody. We work with the auto manufacturers. We work with the insurers. What we're trying to do is get closer to consumers. On the reason you may have never heard of a Gero is that's by design. Were white label. We work for our clients typically on. Do you know they trust us with their consumers? They trust us with their brands. Um, and we're just in the business of getting consumers back on the road. >>Thank you for that. So talk a little bit about how you approach this problem. I mean, you looked out roadside assistance, and you know, we can again all relate. Oh, am I up to date or at least the car? So there's gotta be some kind of 800 number in my glove compartment somewhere, right? So what was the state of roadside assistance before you guys got involved? And maybe we could get into sort of how you solve the problem. >>Yeah, I think that's a great question, Dave, as we look at roadside assistance, everyone things about picking up the phone number 800 number from the glove box compartment And over the years we have invested heavily on bringing a fully digital experience to our customers from insurance companies to AM. And when this Alexa opportunity came up earlier this summer, he said, Hi. How about taking that digital experience, adding, all the Alexa do goods goods about voice interaction, making it very interactive for the users to request that experience in a very normal consumer friendly, friendly were and brought that we integrated all those services got that whole uber like experience with for roadside assistance? >>Yeah. Now. So, Beth, you know, I reminded when, like the smart TV first came out, you had a type in right, and we're really getting spoiled now. It should be easy as a blink. Okay, so you're unveiling blink, you know, what's this service all about? >>So this service is about, you know, trying to get to consumers as easy as we can and getting removing the friction. Right? So what Rogers just talking about is again we asked consumers. We say, you know, imagine that tomorrow you went out and there was a flat tire on your car in your driveway. What do you dio? And universally, they pause and They're like, I don't know. I haven't thought about it, right. And then they start making up stuff. Like maybe I'm gonna go through the glove box. Maybe I'm going to go through my files. But wouldn't it be great if they could just kind of talked to the air and say, Alexa, what? Doe ideo and have it work for them, you know, And that's one friction. The second friction is consumers actually don't know their addresses or don't know it. Well, we joke around the office about the difference between saying you're on route one and Route one A is is the difference between 20 minutes of that tow truck getting to you in time. You know, these air points of friction that technology can help us with, you know, and then with payments even better, Right? So the fact that you can pay for this thing with Amazon pay and you don't have to worry about having cash for a driver or have a credit card. I mean, there's just so many points of friction that are reduced by using Alexa. >>Okay, so let's talk about the the integrations here in the technical aspects of how you put everything together and made it work, and we'll get into some of the cloud aspect >>Attack launched. We're asking users to tell what they want, and they can tell the whole address. They can get the address from the Alexa device. Or if it is Alexa Auto. The GPS will provide us the Latin belong. And we take that address and we get what kind of experience they want. Whether it is a flat tire, we're going to send somebody else to put despair. If it is a jump start, we're gonna put send somebody Thio jumps out the vehicle. So depending on that, we put pull all that information together, get this consent for the user to charge their an Amazon parrot card on profile, and then go So it's literally to come to sentences. And then we're on. We're on to sending you experience with some of the text messages that will allow you to truck tractor truck coming down to your driver. >>Now I'll show my age. So yeah, we've all I don't have all but I've been locked out of the car many times Now, in the old days, used to be able to get a coat hanger and pop it open. But so? So that people still get locked out of their cars. >>Yes, cars. More often than not, it's, you know, the key. Fob stopped working, right? Lost the battery of my key fob these days. But it's the equivalent. >>Alright, so All right, so right. What else do you guys do in the cloud? Do you use a W s for your own business? Maybe share with us some of >>the over the years. For the past 78 years, we have, uh, integrated and got all of our technologies into the AWS cloud. And we have now revamped and re innovated on top of those and create a new product lines. We have accident scene management. We do, um, handle automatic clash notifications for some of our partner customers. We dio dealer service appointments, so we do a lot of these things. And all of these are not possible without the amazing teams. 20 or so teams that we have across three continents working on 50 plus, uh, approved services on aws, uh, innovating around the clock, bringing these new innovations to our market. >>So, Beth, you were saying earlier that you, you know, want to reach out to the consumer. I mean, how do you market? Uh, you obviously go through through partners. And I'm curious system, What's your go to market and maybe how you're different from from others in the marketplace, >>right? Eso again because we're white label with most of the client side business that we do, we help our clients message better on DSO. We talked to them about how often you have to remind people that this isn't a one and done, um, on the skill store for Alexa. You know how we're different is you know, you don't aske much as I love the branding that we came up with blank roadside. You know, you don't actually have to use it. You don't have to say, Alexa, open my blank roadside. You could just say, Alexa, help me with my flat tire, which really helps cut out the fact that I actually need to market the brand like a traditional market or would have had Thio. But our biggest problem is how do you market something to someone in that moment of need, right? How do I How do I prime you to get you to think about it way, way before you ever actually have the problem. >>And how do you charge for the service? >>Eso It's it's a flat fee on did. It's better than what consumers would be able to get on their own. Or at least we believe so. But it is a flat fee for any kind of road service, so it's flat tire. It's dead batteries. It's winching you out. You know, it's it's all of those things. Um, that can happen to you that are just kind of those minor everyday mishaps. >>Okay? And so and so do I. How do I get it? Do I do I have tow hope that my you know, if I'm leasing a car that the auto has it, can I go direct? How doe I >>all direct? It's all direct. So you don't have to worry about an I d number membership number. You're just paying for it out of your Amazon account on. Do you know you don't have to worry about knowing your how many digit vin number. You know, none of that stuff. It's just one and done. >>Awesome. So, Raja, I wonder if you could talk a little bit about your your scale. Um, maybe I don't know if you can share any metrics and what What factors? The cloud generally and a W s specifically has has played and enabling that scale. >>Yeah, we have amazing number of integrations with our Fortune 100 insurance companies. Um, over 35 insurance companies and we have 100 and 70 b two b clients today, Um, and we integrate with them were deeply, um, uh integrated into the building systems into their coverage systems. And all of that is to be able to provide that sub minute sub second experience to our customers when they're calling in, uh, when they need the service. Um, right now we do over a billion AP A calls. As a result of these transactions, all these integrations or for quarter and all of these, uh, our third parties, service providers who go around the on the roads and provide this location information today off the tow trucks to us, all of these 8 8000 or so trucks extreme that information to us almost on every hour. So we bring all that information together on the AWS platform, stream it back shaded back in a very secure private manner back to the customers, right at the moment of need. >>Yeah, So I mean, without the cloud, you'd be backing up. You know, the servers to the truck to the loading dock. And it would just take so much longer toe spin up new products. I would imagine that you guys have a lot of ideas about new data products or new services that you can you can provide. Um, you probably I'm sure you can tell us what they are, But but in terms of the time, it takes you to conceive toe to get to the market. That must be impressed with the cloud. >>Yeah, it's a fraction of what it used to take years ago when we were not in AWS, right? And it also allows us to not to spend all this time on worrying about the same thing that you used to worry about for every project. Now you can actually think about how, what how you let be able to leverage new innovations that are coming in and actually improve improve the experience with some kind of intelligence that is added on, which makes the experience much smoother for people. >>Well, Beth will give you last word. But first of all, thanks for helping us make our lives even even better and more convenient. But bring us home. What's the last word here? >>So the last word is, you know, we dio we do 12 million events a year right now, right? And if you if you like math, it's 35,000 day. It's 20 for every minute, you know. And the work that that Rajan team have done to make the scalable means we're ready to do the next 12 million on. Do you know we know. We know there are consumers out there having those events. We just want to be there for you, you know, take care of that frustrating event on get you back >>on the road. Well, it's just, you know, having you there and being able to push a button and talk to a device is just It's a game changer. So thank you guys for coming on the cube and sharing your story really interesting. Yeah. All right. Thanks for watching. Keep it right there. You're watching the cubes coverage of aws reinvent 2020. We'll be right back right after this short break