Dave Abrahams, Insurance Australia Group | Red Hat Summit 2018
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
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Garrett McDonald, DHS Australia | IBM Think 2018
>> Announcer: Live from Las Vegas, it's theCUBE. Covering IBM Think 2018. Brought to you by IBM. >> Welcome back to theCUBE live at the inaugural IBM Think 2018 event. I'm Lisa Martin with Dave Vellante. Excited to be joined by a guest from down under, Garrett McDonald, the head of Enterprise Architecture at the Department of Human Services in Australia. Welcome to theCUBE. >> Thank you very much. >> Great to have you. So tell us about the Department of Human Services, DHS. You guys touch 99 percent of the Australian population. >> Yeah, we do. We sit within federal government, we're a large service delivery organization. So through a range of programs and services we touch pretty much every Australian citizen on an annual basis. And within our organization we're responsible for delivery of our national social welfare system, and that picks up people pretty much across the entire course of their lives at different points, we're also responsible for delivering the federally administered portion of our national health system, and that picks up pretty much every Australian every time you go to a doctor, a pharmacy, a hospital, a path lab, indirectly both the provider and the citizen are engaging with our services. We're responsible for running the child support system, but then we also provide IT services for other government departments, so we implement and operate for the Department of Veterans Affairs, and also the National Disability Insurance Agency. And then finally we also run Whole-of-government capabilities, so DHS we operate the myGov platform, that's a Whole-of-government capability for citizens who government authentication and within out program we have 12 million active users and that number continues to grow year on year, and that's the way that you access authenticated services for most of the major interactions that a citizen would have online with government. >> And your role is formerly CTO, right? >> Yep. >> You've got a new role. Can you explain it? >> Yeah, I'm a bit of a jack-of-all-trades within the senior executive at DHS, I've had roles in ICT infrastructure, the role of CTO, the role of national manager for Enterprise Architecture, and I've also had application delivery roles as well. >> Okay, so let's get into the healthcare talk because the drivers in that industry are so interesting, you've got privacy issues, in this country it's HIPAA, I'm sure you're got similar restrictions on data. Um, what's driving your business? You've got that regulation environment plus you've got the whole digital disruption thing going on. You've got cloud, private cloud, what's driving your organization from a technology perspective? >> I think there's two main factors there. We have changing citizen expectations, like we've got this continued explosion in the rate of changing technology, and through that people are becoming increasingly comfortable with the integration of technology in their lives, we've got people who are living their lives through social media platforms and have come to expect a particular user experience when engaging through those platforms, and they're now expecting the same experience when they interact with government. How do I get that slick user experience, how do I take the friction out of the engagement, and how do I take the burden out of having to interact with government? But at the same time, given we are a government agency and we do have data holdings across the entire Australian population, whether it's social welfare, whether it's health or a range of other services, there's this very very high focus on how do we maintain privacy and security of data. >> Yeah, I can't imagine the volumes of transactional data for 12 million people. What are some of the things that DHS is using or leveraging that relationship with IBM for to manage these massive volumes of data? You mentioned like different types of healthcare security requirements alone. What is that like? >> We've been using IBM as our dominant security partner for quite some years now, and it's been the use of data power appliances and ISM power appliances out at the edge to get the traffic into the organization. We're deploying Qradar as our Next Gen SIEM and we're slowly transitioning over to that. And then as we work out way through the mid-range platform through our investment in the power fleet and back to our System Z, we've been using Db2 on Z for quite some years in the health domain to provide that security, the reliability and the performance that we need to service the workloads that hit us on a day-to-day basis. >> So you got a little IoT thing going on. Right? You got the edge, you got the mainframe, you got Db2. Talk a little bit about how, because you've been a customer for a long time, talk about how that platform has evolved. Edge data, modernization of the mainframe, whether it's Linux, blockchain, AI, discuss that a little bit. >> Okay, so over the past three years we've been developing our Next Gen infrastructure strategy. And that really started off around about three years ago, we decided to converge on Enterprise Linux as our preferred operating system. We had probably five or six operating systems in use prior to that, and by converging down on Linux it's given us a, the ability to run same operating system whether it's on x86, on Power, or Z Linux, and that's allowed us to develop a broader range of people with deep skills in Linux, and that's really then given us a common platform upon which we can build an elastic private cloud to service our Next Gen application workloads. >> Now you've talked off-camera. No public cloud. Public cloud bad word (laughs) But you've chosen not to. Maybe discuss why and what you're doing to get cloud-like experiences. >> Yeah, so we are building out a private cloud and we do have a view towards public cloud at a point in the future, but given mandatory requirements we need to comply with within the Australian government around the use of the Cloud, given the sensitivity of the data that we hold. At this point we're holding all data on premise. >> Can we talk a little bit more about what you guys are doing with analytics and how you're using that to have a positive social impact for these 12 million Australians? >> Yeah, we've got a few initiatives on the go there. On how do we apply whether it's machine learning, AI, predictive analytics, or just Next Gen advanced analytics on how do we change the way we're delivering services to the citizens of Australia, how do we make it a more dynamic user experience, how do we make it more tailored? And on here that we're exploring at the moment is this considerable flexibility in our systems and how citizens can engage with them, so for example in the social welfare space we have a requirement for you to provide an estimate of the income you expect to learn over the next 12 months, and then based on what you actually earn through the year there can be an end-of-year true-up. Right, so that creates a situation where if you overestimate at the start of the year you can end up with an overpayment at the end of the year and we need to recover that. So what we're looking at doing is well how do we deploy predictive analytics so that we can take a look an an individual's circumstances and say well, what do we think the probability is that you may end up with an inadvertent overpayment, and how can we engage with you proactively throughout the year to help true that up so that you don't reach the end of the year and have an overpayment that we need to recover. >> So I wonder if we could talk about the data model. You talk about analytics, but what about the data model? As you get pressure from, you know, digital, let's call it. And healthcare is an industry that really hasn't been dramatically or radically transformed. It hasn't been Uberized. But the data model has largely been siloed, at least in my experience working with the healthcare industry. What's the situation in Australia, and specifically with regard to how do you get your data model in shape to be able to leverage it for this digital world? And I know you're coming at it from a standpoint of infrastructure, but maybe you could provide that context. >> Well, given for privacy reasons we continue to maintain a pretty strong degree of separation between categories of health data for a citizen, and we also have an initiative being deployed nationally around an electronic health record that the citizen is able to control, right, so when you create your citizen record, health record, there is a portion of data that is uploaded from our systems into that health record, and then a citizen can opt in around, well what information when you visit the general practitioner is available in that health record. When you go to a specialist you're able to control through privacy settings what information you're willing to share, so it's still a federated model, but there's a very, very strong focus on well how do we put controls in place so that the citizen is in control of their data. >> I want to follow up in that, this is really important, so okay, if I hear you correctly, the citizen essentially has access to and controls his or her own healthcare information. >> Yeah, that's right. And they're able to control what information are they willing to share with a given health practitioner. >> And it's pretty facile, it's easy for the citizen to do that. >> Yeah. >> And you are the trusted third party, is that right? Or -- >> It's a federated model, so we are a contributor to that service. We provide some of the functionality, we feed some of the data in, but we do have another entity that controls the overarching federation. >> Do you, is there a discussion going on around blockchain? I mean could you apply blockchain to sort of eliminate the need for that third party? And have a trustless sort of network? What's the discussion like there? >> We've been maintaining a watching brief on blockchain for a good couple of years now. We've been trying to explore, well how do we find an initial use case where we can potentially apply block chain where it provides a value and it meets the risk profile. And given it does need to be a distributed ledger, how do we find the right combination of parties where we can undertake a joint proof of technology to identify can we make this work. So not so much in HealthSpace, there are other areas where we're exploring at the moment. >> Okay, so you see the potential of just trying to figure out where it applies? >> Yeah, absolutely, and we're also watching the market to see well what's going to become the dominant distribution, how a regulatory framework's going to catch up and ensure that, you know apart from the technical implementation how do we make sure that it's governed, it's administered -- >> Do you own any Bitcoin? No, I'm just kidding. (laughter) How do you like in the Melbourne Cup? So, let's talk a little bit about the things that excite you as a technologist. We talked about a bunch of them, cloud, AI, blockchain, what gets you excited? >> I think the AI and machine learning is a wonderful area of emerging technology. So we've also been pushing quite hard with virtual assistants over the past two to three years, and we have six virtual assistants in the production environment. And those span both the unauthenticated citizen space, how do we assist them in finding information about the social welfare system, once you authenticate we have some additional virtual assistants that help guide you through the process, and then we've also been deploying virtual assistants into the staff-facing side. Now we have one there, she's been in production around about 18 months, and we've got very very complex social welfare legislation, policy, business rules, and when you're on the front line and you have a customer sitting in front of you those circumstances can be really quite complex. And you need to very quickly work through what areas of the policy are relevant, how do I apply them, how does this line up with the legislation, so what we've done is we've put a virtual assistant in place, it's a chat-based VA, and you can ask the virtual assistant some quite complex questions and we've had a 95 percent success rate on the virtual assistant answering a query on the first point of contact without the need to escalate to a subject matter expert and we figure that if we saved, we've had it round about a million questions answered in the last year, and if you think that each one of those probably saves around three minutes of time, engaging in SME, giving them the context and then sorting through to an answer, that's three million minutes of effort that our staff have been able to apply to ensuring that we get the best outcome for our citizen rather than working through how do I find the right answer. So that's a bit of a game-changer for us. >> What are some of the things that you're, related to AI, machine learning, cloud, that you're excited about learning this week at the inaugural IBM Think? And how it may really help your government as a service initiative, et cetera. >> Yeah, so I think I see a lot more potential in the space between say machine learning and predictive analytics. On based on what we know about an individual and based on what we know about similar individuals, how do we help guide that individual back to self-sufficiency? Right, so for many many years we've been highly effective and very efficient at the delivery of our services, but ultimately if we can get someone back to self-sufficiency, they're engaged in society, they're contributing to the economy, and I think that puts everyone in a pretty good place. >> Alright, so I got to ask you, I know again, architecture and infrastructure person, but I always ask everybody in your field. How long before machines are going to be able to make better diagnoses than doctors? >> Uh, not so sure about doctors, but within our space our focus has been on how do we use artificial intelligence and machine learning to augment human capability? Like, the focus is on within our business lines within our business lines we have room for discretion and human judgment. Right, so, we don't expect that the machines will be making the decisions, but given the complexity and the volume of the policy and legislation, we do think there's a considerable opportunity to use that technology to allow an individual to make the most informed and the most consistent and the most accurate decision. >> So then in your term you don't see that as a plausible scenario? >> No. >> Maybe not in our lifetime. >> As I said the focus is very much on, well, how do we augment human capability with emerging technology. >> So Garrett, last question and we've got about a minute left. What are some of the things that you are excited about in your new role as head of Enterprise Architecture for 2018 that you see by the end by the time we get to December, your summertime, that you will have wanted to achieve? >> Okay, so, over the last roughly two years I've been developing the future state technology design that will reshape out social welfare system for probably the next 30 years. This is a generational refresh we're undertaking in that space, so I think it's been a hard slog getting to this point, we're now starting to build on our new digital engagement layer, we've got a new enrichment layer starting to come to life where we do put that machine learning and AI in place and then we're also starting to rebuild the core of our social welfare system, so this is the year for me where we go from planning through to execution, and it brings me an immense sense of pleasure and pride to see the work that you've been pouring yourself into for many years start to come to fruition, start to engage with citizens, start to engage with other government agencies, and start to deliver the value that we know that it's capable of delivering. >> Well, sounds like a very exciting year ahead. We want to thank you so much, Garrett, for stopping by theCUBE and sharing the insights, what you guys are doing to help impact the lives of 12 million Australians. >> Thank you very much. >> Have a great event. >> Thank you. >> And for Dave Vellante I'm Lisa Martin. You're watching theCUBE's live coverage of the inaugural IBM Think 2018. Stick around, we'll be back with our next guest after a short break.
SUMMARY :
Brought to you by IBM. at the Department of Human the Australian population. and that's the way that you Can you explain it? infrastructure, the role of CTO, because the drivers in that and how do I take the burden What are some of the things that DHS and the performance that we You got the edge, you got Okay, so over the past three years to get cloud-like experiences. the data that we hold. and how can we engage with you proactively talk about the data model. so that the citizen is the citizen essentially has access to they're able to control for the citizen to do that. that controls the overarching federation. to identify can we make this work. bit about the things how do I find the right answer. What are some of the things how do we help guide that individual Alright, so I got to and the most consistent As I said the focus the end by the time we get and start to deliver the value and sharing the insights, of the inaugural IBM
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