datamaster summit 2020

How Transamerica is transforming to better serve their customers

 

Vanessa Gonzalez, Anthony Deighton, Blake McDonald, Richard Wang, Ph.D.

Vanessa Gonzalez, Senior Director of Data And Analytics at Transamerica
Anthony Deighton, Chief Product Officer at Tamr
Blake McDonald, Solution Architect at AWS
Richard Wang, Ph.D., Executive Director at MIT CDOIQ Program

In the incredibly competitive insurance industry, providing exceptional customer service is the key element to standing out.

Tune in to hear why Transamerica is taking a data-first approach to customer service.

Transcript

00:11 – 00:16

Vanessa Luzardo Gonzalez

Says that. Right. You can go ahead and get started, Richard.

00:17 – 01:04

Richard Wang

Welcome everyone. I am Doctor Richard Wang, Director of MIT CDOIQ Program. I’m delighted to be part today’s webinar with Transamerica, Tamr and AWS Today, we’re going to hear about Transamerica digital transformation project to better serve customers. Key to this initiative is to have complete, complete customer reviews and customer predictive analytics. We’re going to drill down on how Transamerica obtained. Both partnering was Tamr and AWS. This was a. I’m going to hand over to Ravi to introduce today’s speakers, Ravi, on until thank you, Richard.

01:04 – 01:44

Ravi Halsey

Hi, good afternoon, welcome everybody. My name is Ravi Halsey. I’m Tamr’s Chief Cloud Evangelist. I’m really excited today to be joined by Vanessa Gonzalez, who is a senior director of data and analytics at Transamerica. Joining us with us is Blake McDonald, who, the senior solutions architect. And here we have Anthony Deighton, who’s our Chief Product Officer. So let’s go ahead and get started into the story of Transamerica. So Vanessa, can you help us set the scene here? Can you tell us a little bit about why Transamerica was looking to reinvent its approach to customer service your successful, established insurer? So why would you have a need to change things?

01:46 – 02:16

Vanessa Luzardo Gonzalez

Thank you, both. First, thank you for having me. I’m really excited to be here. And we are looking forward for this conversation, so that’s great. And what I want to say is like the world is changing, it’s changing really quickly. The service that we gave to customers at one point in time is not the same type of service that they are requesting or they are expecting now and today, as you can tell, with all the devices and ways of communication and there’s there’s a lot that we have to do and we have to better our selves day after day.

02:16 – 02:49

Vanessa Luzardo Gonzalez

So what we’re trying to do here and we’re we’re going through a transformation to really, really make sure that we keep giving our customers the service they deserve in and make it as the best that we can and be really best in class. So for that, I think that would be answering the question about why we’re doing this. Yes, we have been very successful, but at the same time, we’ve want to stay there and keep being successful so that that’s the main reason of why we’re always thinking about getting better.

02:50 – 03:13

Ravi Halsey

I think that that’s a great attitude, especially customers have set high expectations for service they receive from companies, and I’m sure that just building out those views of customers and you can even answer a simple question like, well, how many customers do we have that many companies challenge with just answering those questions internally? Can you talk about some of the challenges that you faced around making sense of all of our customer data that you have?

03:14 – 03:55

Vanessa Luzardo Gonzalez

Yeah, definitely. We have a lot of data about our customers and we have many different products. We have benefits. We have retirement services, financial services. So we have many different records for the same customer. And I think that’s where it gets tricky. We may have in one place when you open your online account, you didn’t use your middle initial, but in another place when you open your retirement account, you use your middle initial and in another place you have a different phone number because it was 20 years ago and you changed your number. So how can we tell how many customers we have if we have different information in many places?

03:55 – 04:19

Vanessa Luzardo Gonzalez

So we need to make sure that we we know who our customers are and how that even if we have six different records or six different pieces of information for the same person, we need to know that it’s the same person so we can count them. And we can tell you with precision of who are customers and how many of them we have. So that’s it’s very important, is very important.

04:19 – 04:39

Vanessa Luzardo Gonzalez

important. Tamr has been a great partner to us to help us to do that, that mastering that, that getting on those records together to know who’s the same person using machine learning is the way to go. And we have so much data that we need to make sure that we can do that. We can just go and count so many clients.

04:39 – 05:01

Ravi Halsey

Yeah, it’s a little bit more than just to select star in a database these days. And certainly, I think you mentioned a little bit about taking on Transamerica, working together to clean curates your customer data. So he told the audience a little bit about what it is about Tamr’s approach to mastering data in your eyes that that really works for Transamerica.

05:02 – 05:50

Vanessa Luzardo Gonzalez

So I have to say that what really works with Tamr is that I definitely identify a resolution piece. That of dos is one part. I’m sure that there may be other models that you can use to do that, but what really makes a difference is the partnership that we have with Take. We really get to work together and have Tamr work with our data scientist and with with the team retainer tech team as well, and help us get to where we need to do, where we need to go and do what we need to do to for these identity resolution….. So the product is where it is great. But I think that what we do with them is more the partnering that I value the most on this relationship with with them and us and allow us to be successful on mastering our data.

05:51 – 06:03

Ravi Halsey

And that’s exactly what we see as well. That partnership between a vendor such as Tamr and internal groups, data scientists, other the consumers, they all need to work together really to address the challenge.

06:03 – 06:19

Ravi Halsey

Anthony, a question for you along those lines. Or Vanessa has been talking about that. Just need to clean all that data for these sorts of digital transformation projects. And just the challenges around this is thought of ask is, is this a story that you’re hearing from other team customers?

06:20 – 07:00

Anthony Deighton

It’s a great question, and it comes back to the kind of a core belief. It’s certainly something that I’ve talked about in the past, which is that at its core, every business is a data business. So we might think we’re in the retail business or in the insurance business or a health care provider, or you might think that you make your manufacturer. But those things are true. But really, at its core, the way you’re successful is by being a data business and by thinking about the data that drives the relationships you have with your customers, with your vendors, with your suppliers, how you go to market and what the data behind those processes are.

07:01 – 07:58

Anthony Deighton

And so, yes, I mean, to answer your question very directly, this is a theme we hear very consistently across every or customer. And what’s interesting is that it spans many different industries and use cases. So you might have an example like society in general, which is looking at their spend or the Department of Homeland Security in the public sector space, which is looking at travelers and understanding people across borders. Or you might think about an organization like Hamas, which is looking at data coming from wells that oil wells or an example closer to what Transamerica is doing like a Toyota that’s looking at customer data or one of my favorite examples Creative Artists, which is looking at artists and venues and locations of performances. But at its core, all of these examples across all these very different industries come back to the same core idea, which is they are thinking about their business as a data business.

08:00 – 08:19

Ravi Halsey

And it’s not really interesting and prime examples, you mentioned lots of different industries, but suddenly a theme in terms of customers such as Transamerica just cleaning up customer data first. The reason why why companies start customer data and what does that lead to them, then some the once they’ve done that?

08:19 – 08:49

Anthony Deighton

Yeah, no. I think there’s a really good reason that most customers start with customer data, and that’s because at it’s at the heart of every business. Is that customer relationship and how you service that relationship provide a great experience, a high quality product offering, whether that product as a service or a physical good at its core. When you understand that the relationship with you have with that customer and then you can understand that completely so that you can understand all the surrounding data that fits around that.

08:51 – 09:26

Anthony Deighton

In many cases, we think of that customer and that Customer ID we call it, of course, a Tamr ID. The idea for that customer that really is at the center of the the heart of the relationship and that drives so many other parts of your business. How you think about the supplier relationships you have, how you think about employee relationships that you have at the core is this idea of who is my customer. And then I actually think earlier, Vanessa talked very well about this idea that getting a handle on that of figuring out what those relationships are really is at the core of creating a great experience.

09:27 – 09:33

Ravi Halsey

Thank you, Anthony. That’s a really good context. We can show the audience there can move back to Vanessa.

09:33 – 10:04

Ravi Halsey

Just question a little bit more about his role in the success of this project. Now Transamerica is run a cloud native deployments of Tamr on us. Can you tell the audience a little bit about why you decide to go to the IWC rather than making use of team, perhaps on the on premise environment? Technical benefits you can share of using Tamr and IWC together that resonated for Transamerica, so we are in the middle of a full transformation.

10:04 – 10:40

Vanessa Luzardo Gonzalez

It’s like our data transformation where we’re migrating our data into the cloud. We are partnering with IWC for many of the same reasons that we partner with Tamr. They’re great partners to us. They support us in what we need. They have a great product and they really can provide what we’re needing at this point to be able to to do good analytics. We need speed. We need able to have all the data in one place. We need to be able to access it. For Tamr to to run nicely and run well needs to have access to the data like we cannot. We’re going to have it work without without the data in one place.

10:41 – 11:33

Vanessa Luzardo Gonzalez

As you can imagine, a company like ours that has been around for more than 100 years, it’s going to it has. We have a lot of data and it’s very easy to get lost in that data if you’re not careful. So having so much data and having either we were able to to be able to scale and grow and use as many resources as we need when we need them and be able to store as much as we need to do to store the time and then the amazing tools, they don’t even get me there about going, about the machine learning tools they have like. Really, we’re really very excited about that piece as well, but there’s a lot that we can do with them and the partnership we have with them, they’re very supportive as they come to us and talk to us about what we need when we needed them to do so. Different teams, and that’s where a huge value we see.

11:33 – 12:01

Vanessa Luzardo Gonzalez

I know there are other cloud providers are there, but we went with a W because of these difference in service, what they can give us and how they continue to provide that to us. So that being able to run Tamr on the cloud and being able to access data in a quicker fashion and as real time as we can or as we as we’re moving our data into the lake it’s going to is very powerful now and it’s going to be even more powerful as we go through our transformation.

12:03 – 12:20

Ravi Halsey

Thank you. I think there’s a lot of things that speed, agility, just the ability to deliver results. And as you mentioned, you’ve got it halfway through this digital transformation. Can you share a bit of information about the future plans of once once you finish this phase? What next for Transamerica and.

12:21 – 12:47

Vanessa Luzardo Gonzalez

Yeah, definitely. So where we are right now, we’re hydrating our lake, where we’re moving all our data in into the lake, we’re going to be adding a lot better data quality. We’re mastering our data. We’re adding data governance to it. We are making sure that our that also our environment, our data is more secure and help us with that piece as well, that it’s easier to access. There’s always a lot that we can do there.

12:47 – 13:42

Vanessa Luzardo Gonzalez

So first phase move the data all in one place, start using the right tools at the right time and getting what we need to be more agile, be quicker and really face how the world is changing. That’s the main thing in the future is that we don’t know how it’s going to look like five years from now. We have never thought that it was going to change as quickly as it had in the last 10 years, the world that we’re living now. So we have to to really have a very strong infrastructure. B. Be sure that we’re agile enough and nimble enough to adapt and change. And that’s why, like I thought with our story with IWC is that they see that as well, and they’re moving and changing and adding what they need when they need to to help us provide those service, meal services or new ways of doing business or new ways to access our data. So that’s what I see in the future for people working together.

13:43 – 14:07

Ravi Halsey

Certainly, I think from personal experience, every time I go to that IWC service, Carter Page, there’s a new service being added every single day. One yet one may want to pounce on that. As we’re talking about IWC Place, let’s let’s bring you into this conversation as well. Yeah, from the stories that we’ve shared with Vanessa, are you hearing similar things from your other customers around why they’re using in such a manner for digital transformation?

14:08 – 14:59

Blake McDonald

Oh, sure, absolutely, Rob. I mean, our customers across the board, really across industries, the globe, from startups to midsize to Fortune 100, I mean, they’re all really echoing the same reasons why they chose eight of us for their digital transformation projects. A lot of those are similar stories to what Vanessa alluded to. And there’s, you know, some examples of those I’m with the global financial services sector vertical sector with an EPS of which Transamerica is aligned. And, you know, we have several in there that are doing the same things with so much with data these days, as Anthony said, every every day. Every business is a data business and customers are, you know, a lot of them are just realizing that their assets to a lot of time, you know, especially in the financial services sector, you can monetize those as well. So it’s just another path for growth as well for companies.

14:59 – 15:23

Blake McDonald

So the companies that we see kind of fledgling and moving forward are the ones that that really understand that. But but but your more to your question, you know, customers are choosing apps over other providers because, you know, we just we just have a lot more functionality, as you as you mentioned with the with the services. And sometimes I feel your pain on that because that’s just another service I need to learn, right? But it’s all in good fun.

15:23 – 16:13

Blake McDonald

But but we also have the largest and most vibrant community of customers and partners. You know, we have the most a proven operational security expertise in our business is innovating at a very fast clip, especially in those new areas as machine learning, artificial intelligence, internet of things and serverless computing. But but more specifically, you know, it really generally for us comes down to like six major factors. You know, again, apps, we have unmatched experience in the cloud, unmatched maturity, reliability, security and performance. And internally, we have a saying that there’s no compression algorithm for experience. And that’s because you can’t learn certain lessons until you get two different milestones in scale, which of course, can only result from deep experience and lots of lots of customers across all industries and geographies.

16:13 – 16:35

Blake McDonald

You know, we touched upon it, but you know, advice does with all the services, we have more breadth and depth of service than any other cloud provider by a large amount, really. We’re continually expanding services to support virtually any cloud workload. And we now have more than 200 fully featured services. You know, we also have the deepest functionality within those services.

16:36 – 17:05

Blake McDonald

And there’s difference. These are the differences that really matter to our clients. I mean, if you let’s say, take compute, for example, many cloud providers will tell you, yeah, we have compute on the cloud, but it’s not just black and white like that. It’s it’s not just about checking that box. You know, ABS has more meaningful compute instances than anyone else. We have over 400 instance types of compute for virtually every workload and business need, and we’re the only cloud provider to offer that choice the choice of Intel, AMD and arm processors.

17:06 – 17:36

Blake McDonald

And you also see the depth of difference in containers. You know where we also have a lot more capabilities than any other cloud provider. And if you look at service serverless, which is also compute without having to manage the infrastructure. ABC pioneered serverless computing back the. The launch of Lambda in 2014, so and today at Lambda AIDS, Lambda has 140 140 native integrations and event sources. And that’s seven times more than any anyone else. So you have a lot of flexibility in what you can build.

17:37 – 17:57

Blake McDonald

And then if you look at databases, even where we have 15 database options, we don’t believe that one size fits all is right because you’re also paying for everything else you’re not using. So we have the most complete family of purpose built databases to give customers the right tool for the right job so they can spend less money and be more productive and change the customer experience.

17:58 – 18:30

Blake McDonald

I mentioned we’re innovating faster in any way that anyone else and that gap and capability, it continues to expand. You know, for example, in 2011, 10 years ago, we released over 80 significant services and features. And why, while we may have thought that was a lot back then, fast forward 10 years later, and by the end of last year, we released over 20 700 services and features. So, you know, that’s just that shows you how fast we’re innovating. It’s just it’s it’s innovation on tap, you know, absent.

18:30 – 19:06

Blake McDonald

And that is our one of our primary focus is our global footprint also as a compelling reason that customers choose apps, something it’s very difficult to do in on premise datacentre. We have 81 availability zones, 25 geographic regions with with plans to launch 24 more availability zones and eight more regions soon internationally. And that means customers of any size, any a one person shop up to that to the largest enterprises can go global by just logging into the APIs console, spinning off some infrastructure across the world, literally in minutes.

19:08 – 19:42

Blake McDonald

And then I’d also say our pricing philosophy is is something that our customers really like it because, you know, in the cloud, you just provision what you need. And if it turns out you need less, well, that’s fine. Just give it back to us and you start paying for it, right? And that variable expense, as opposed to the capital expenses is it’s lower than what virtually every company can do on its own. Because, you know, ABC has such large scale economies of scale that we pass it on to our customers any of the savings in the form of lower prices. You know, in fact, we’ve lower our prices 109 times now since ABC launched in 2006.

19:43 – 20:26

Blake McDonald

And lastly, I’d say to round out your question, I would say maybe as customers have really just and I think this echoes what Vanessa was saying. They’ve really come to appreciate that our culture is really different. We are and usually customer focused. We are customer obsessed versus competitor focused, which many companies most companies out there are 90 percent of of. What we build is driven specifically by what customers tell us matters. And so we work backwards from their needs. You know, we’re also pioneers. We hire builders who are always looking at how they can reinvent and better the customer experience, you know, so so I’d say those are the primary reasons that set us apart. And you know what? Customers are choosing ABC for their digital transformation journeys.

20:28 – 21:02

Ravi Halsey

Speaking personally, as someone who’s provisioned our marketplace listing on AWB, I scrolled through those 400 instances a lot. It is a lot, certainly comprehensive, and I think one of the themes you mentioned that Blake was just having that journey with customers, bringing them to the cloud. And clearly, Transamerica is a long way into that journey going to the cloud. But for those organizations who are still reluctant, still different. That’s how in the cloud and adoption, it’s also a lot of advice. Can you offer them for maybe address some of their concerns or hesitancy around making that first move?

21:03 – 21:32

Blake McDonald

Great question. You know, first of all, I would like to say you mentioned Transamerica and they are we are thrilled to have Transamerica as a customer. You know, as you can tell by Vanessa’s comments, there are very forward thinking company that focuses on innovating and not just saying that, like some companies do, but they truly innovate because they understand how their data is an asset, and they need to understand why they must digitally transform their business in order to outpace their competition. But more importantly, to provide their customers with a better experience.

21:32 – 22:03

Blake McDonald

So, but but to answer your question for it, customers that are kind of still reluctant, you know, this might surprise many, but it really it’s not about for most companies. The biggest challenge isn’t technical, you know, they aren’t technical reasons. They’re about really people and culture. That’s what we’re finding the biggest differences between organizations that talk about moving to the cloud and those that actually do it and are having the most success really comes down to a few key things.

22:04 – 22:46

Blake McDonald

First off, senior leadership needs to be aligned and truly committed that they want to move to the cloud and they need to be setting a clear direction, you know, and expectations with the rest of the organization to get everyone on the same page working towards the same goal. It’s easy for others to do nothing or block things. If the leadership team isn’t making the move and backing it and making it a priority and building a culture for that change, you know the most successful companies also are, you know, that are moved to the cloud or has started with a tall, aggressive top down goal that forced the organization to move much faster than it would have organically. And you know, it’s really important.

22:46 – 23:07

Blake McDonald

I think Vanessa would agree with this as well, that organizations are trained on the cloud and comfortable kind of get their sea legs, you know, because then they are ready to they get better informed and ready to start owning some of these and moving more workloads. They’re feeling more comfortable about it as part of the whole process. And we train hundreds of thousands of people a year for that, for that purpose.

23:08 – 24:01

Blake McDonald

And really, lastly to your question, I think sometimes what happens is a lot of times actually find customers just. They get paralyzed, it’s like, you know, paralysis by analysis, kind of like you said, you see all these services, what do you do? Which one do you go to? But then they have to figure out not only which ones do I use, but how do I move what I have existing and translate that to to which applications they and they can’t figure out to move every last workload? And so, so it stalls, right? But you know, they just have to understand that there’s no need to do that. There’s no need to boil the ocean. So we often work with customers to do a portfolio analysis to assess each application and build a plan for for what time of short term medium term. And then last and this helps organizations get the benefits, you know, of the cloud for many of their applications much more quickly. And it really helps inform how they how they move the rest of the workloads.

24:02 – 24:26

Ravi Halsey

Yes, I think you’ve touched upon a couple of good points there, especially not the technical benefits of IWC, but which they’re quite extensive, but also partnering with a company just to help them achieve their business goals. Can you tell me a bit more about the streams? Are a little bit more about why it’s important the work of a company who really understands both the technical and business needs of the business to ensure them to be successful in their projects?

24:27 – 25:00

Blake McDonald

Yeah, I’m glad you brought that up. The need to partner with others. You know, just just as I said, we’re thrilled to have Transamerica as a customer. We’re equally thrilled and fortunate really to have a great relationship with with Tamara because, you know, as I mentioned, Andreas has millions of active customers every month. And with that large of a global footprint, we must rely on our partner network. We just can’t do it alone, number one. But nor would we want to do it alone because generally that’s not always what’s best for our customers. And that’s what matters most to us, right? What’s best for our customers?

25:00 – 25:37

Blake McDonald

Let’s let’s face it, many partners specialize in specific areas of industry or application where it really makes sense more to use their partner because they have maybe a better skill set or more deep experience. Like you said, some may have the technical experience, but many partners have specific business and industry knowledge that is a huge differentiator, and they can talk to customers talk. And I would certainly put Tamr in that category, Tamara, that category. And because, you know, with a deep focus and expertise on data cleansing and you know, it leads to uncovering data insights that help our mutual customers innovate and grow in ways that they they never imagined before.

25:38 – 26:19

Blake McDonald

As you’ve heard, you know, I’ve been a statistic from the customer perspective, so so partnering is not just a win win, but a win win win, right? You know, HP wins the partners win and most importantly, the customer wins because of that collaboration. So, so really, you know, for those reasons, we’ve built the largest community of customers and partners. We have well over 100000 partners now from more than 150 countries, and almost 70 percent of those are headquartered outside the United States. And so when you look at our partner network, it’s not just the thousands of systems integrators who build practices around it.

26:19 – 26:58

Blake McDonald

Yes. You know, there are these ISP’s and SAS providers who who they adapt their technology initially to to work on just a single platform, right? Because it’s very difficult to to to operate and to get going on on multiple platforms because of all the dependencies, perhaps and in a system. But but some will do too, and very few will architectures to three platforms, cloud platforms. But generally, what we’re seeing there, they’re all starting with eight of us because of our significant leadership position. You know, it’s why you see a much more vibrant collection of ice fees and SAS providers on us as you’re moving to the cloud and you want you want those capabilities like Tamara has.

26:58 – 27:25

Blake McDonald

So you know, you can look at the workday at Splunk and you see it when Salesforce runs the vast majority of what they do on on top of attributes and informatica in4 and Datadog and Databricks. And, you know, just just sort of name some off the top of my head, but just a broader, broader, much broader collection of software that when you’re moving to the cloud, you get you can use really easily on top of our platform.

27:27 – 27:41

Ravi Halsey

Yeah, I think that’s a great perspective, like in this kind of conversation going really well, it’s a reminder to the audience. Yeah, if you do have questions for the panelists, please feel free to type them into the Q&A box in the webinar.

27:41 – 27:57

Ravi Halsey

I’m going to switch back to Vanessa now. Just really in terms of looking from a business perspective, how can a business ensure that the vendors they’re working with are really going to be a good technical and good business partner? Are there any key criteria that they should be looking out for?

27:59 – 28:41

Vanessa Luzardo Gonzalez

Yes, so I think it has to like any relationship, you have to work on it. I have to make sure that that that you have that communication open, it doesn’t work and saying, OK, tell me about your project or your product and just go say yes, no and and not that feedback as well to our partners. So I feel that that what makes it successful and for us to understand you’ve the partnering and we’re going to be working on when we’re in another tool search process or another, like our partner search that we compare. We don’t go deals with the first one. Would we hear that there? It’s there. Sometimes we do pursue, so we try to see it like we test out the applications in some cases with us.

28:41 – 29:02

Vanessa Luzardo Gonzalez

So I’m not sure exactly what how was the story of how we moved into a WC? I was not there yet, but something that we do is that we started with projects. We don’t go, we don’t go from one day to another and say, we’re going to move. Everything in one day doesn’t happen that way, a journey. And we started with pieces and we see, OK, this is working great.

29:02 – 29:38

Vanessa Luzardo Gonzalez

Let’s let’s move to the next phase. Let’s move it more. Make sure that how that relationship is going the same thing with Tamr. We we tried with a smaller matching project and then we go a little bit further and a little bit further. And now we it has. It has gone to the point that we’re relying on there on how to like that, how strong they’re technically in, how they give us that support when we need it on that side in. And we know that the culture in their company is the same thing with us, that they’re there to support us and we appreciate that.

29:38 – 30:18

Vanessa Luzardo Gonzalez

And we try to be good partners in return. We try to help out. We try to give feedback when there’s things that we need, let’s say with the team or that we think that if, if, if something was a little bit different, it would be better. And they take that feedback and incorporate it in their in their newer versions of the product. And we’re like, OK, this is great and the same thing with us when we need their help and we say, this is what we’re doing, they don’t come to you and say, Well, you have to use these. They say, What are you using? What do you need? And then they tried to say, you could. You could use this in this way, and we can help you support you in this way. And you can keep the tools that you have, but do it in this different way. So.

30:18 – 30:55

Vanessa Luzardo Gonzalez

So getting that all that feedback. It shows that they’re technically very strong and that they’re also there for us is very important that their culture, it’s also strong. So we can we can. We can be a good match and have a good relationship with our partner. So we’re very thorough on. When we look at partnerships, we don’t go with the first one, we do a lot of testing, we do a lot of trying out. And once we find a good partner, then we take good care of our partnership because we value that like that work ethic that we see in others and we try to to give those high standards for ourselves as well.

30:56 – 31:33

Vanessa Luzardo Gonzalez

So that’s I think that’s how, you know, it’s hard to tell sometimes with some something that is so new and that you don’t have experience with. And as you say, you see these 300 options well, you start by asking your partners, what do you recommend? Sometimes you know one time and sometimes you don’t. So that’s where that that that strength in technical expertise comes through and the answers and how they support us and help us there. So that’s that’s some of what we of what we do. I’m sure a lot of companies do it in a similar way, others in a different way. But that has worked for us and we keep doing it as we go.

31:35 – 32:03

Ravi Halsey

From a personal perspective, I completely agree with that, Vanessa. Certainly, the customer engagements I pass throughout my career have have been the most successful one is that consultative approach and having the ability to have that channel to provide feedback to a vendor to say, I hate how we should improve things and and make the partnership better. So on that note, sorry, I’d love to get your your perspective as well. And well, how should vendors and customers really form that Floyd partnership and maximized their working together?

32:05 – 32:08

Vanessa Luzardo Gonzalez

So go ahead, I’m sorry. I’m sorry, go ahead.

32:10 – 32:47

Anthony Deighton

So I think one thing to think about, or there are really two things that are the foundation of those solid partnerships. So the first is, is there actually a point of technical difference and benefit to the relationship that say Timor has with IWC that is at its core really needs to be that foundational idea that really needs to be something better. We call it sort of better together. What is it? Why are these things better when they work together? Just to be clear on that as it relates to Tamr and the U.S. for a moment.

32:47 – 33:29

Anthony Deighton

Tamr is the only cloud native data mastering solution in the market. And the reason it’s cloud native is because it’s based on machine learning. This idea that the machine is going to be better at cleaning enterprise data than simply doing it manually with spreadsheets.. And we look up, you know, we can do this better if we could train a machine learning model and do it that way, that machine learning first approach demands a highly scalable infrastructure with machine learning by its nature, is computationally intense, and we want to have access to large amounts of data. We want to be able to have access to infinitely scalable compute in order to process that data with machine learning.

33:30 – 33:57

Anthony Deighton

Well, what better place to get infinitely scalable elastic compute with great storage than us? Right, so. So the reason this is so important is we’re taking two really powerful capabilities to bring them together, and they’re better when they work together. So a machine learning based approach married with infinite compute and cost effective storage, that’s really much better together than it is independently.

33:59 – 34:30

Anthony Deighton

The second thing that I think everyone should look to when they’re talking to vendors is a common view of the customer relationship, putting the customer at the center of that customer relationship and focusing on business outcomes. So, you know, I am a computer geek, worked in this industry for many years, loves technology, all that kind of stuff. I’m confident Blake is the same way. You know that that is wonderful and I enjoy technology as much as the next person.

34:30 – 35:10

Anthony Deighton

But what matters is that Vanessa is solving her business challenges at Transamerica and doing that at pace and getting business value that she can go back to the organization and say, Look, we had data before we worked with these great partners. And look, we have this great business outcome that came out of that relationship, and that’s our singular focus. And it’s the relationship between, you know, Tamr. And we were asked to achieve that outcome for Vanessa and for Transamerica more generally. So two big ideas. Number one is there must be a better together story, technically founded foundation about why these things worked well and then the rest of this myopic focus on business outcomes for the customer.

35:11 – 35:31

Ravi Halsey

It makes absolute, absolute sense when when you put it like that, Anthony, yeah, let’s switch gears a little bit. Vanessa, can you tell us a bit more about how Transamerica is using data that’s being cleansed by Tamara and the who’s who’s who’s excited about it? And he’s he’s really thrilled at the prospects of having good customer data readily available.

35:32 – 36:14

Vanessa Luzardo Gonzalez

So we we have several users of Timah like the big one, but we have is to clean up our customer data and that is being used by the business as well, and we’re using it more and more. But as we’re going to be using, it is like to really when we have, let’s say that we get all our Salesforce data that is in Salesforce. We compare to these customer master and see, OK, these are the same or these are different or it’s kind of our I would say it’s our guide of who our customers are, and we use that as the guide to compare everything else to it. We have hundreds of databases, so if you think about it, we need at least a guy that say, this is these are our customers and then we compare to it.

36:14 – 37:07

Vanessa Luzardo Gonzalez

But we have other uses and they’re very interesting.. They’re smaller in scale, but our data scientists use them as a tool. They use it all the time when they’re developing their models because they’re going to compare. Maybe they want to compare just like the, let’s say, the address or something in in a specific databases that they’re going to be using as data point data points from there to develop their machine learning models, they use Tamr as just like a tool that they they use it to clean their data to be able to train their model. So it’s that happens more and more like they use it all the time. Different models, many and in many cases. But our big our big project that had to do with that is to understand a 360 view of our customer. But for that, we have to know who they are and that’s where we’re using it, mainly for.

37:08 – 37:36

Vanessa Luzardo Gonzalez

We’re going to move forward in the near future to also not just do that, but also our door, our plan sponsors and also also master plan sponsors, also master agents that there’s that they’re selling a product. So we have a big plans for Tamr and Transamerica. We have to go little by little and make sure that we learn the lessons that we do it the right way. But this is definitely a journey, and it’s a very exciting one for us.

37:37 – 38:12

Ravi Halsey

I’m thrilled to hear that big plans for Tamr Transamerica, and certainly, I think your comments about data scientists having to spend so much time clean data resonates with those who we speak to are just crying out for a solution like payment just to relieve them of that time spent cleansing and preparing data before even getting to build out the models they’re supposed to. The tell me how now that you’ve really come most of these customers, how that changed, how Transamerica carries out its customer service. Are there any other business benefits that you’ve seen from this ability to have that clean view of your customers?

38:13 – 38:45

Vanessa Luzardo Gonzalez

Yeah. So we have been able to like we’re being able to have better communication with our customers like our do more personalized campaign marketing campaigns and by by knowing who our customers are and what is their information. We can communicate better with them. We can serve them better. At the end of the day, what we want is to to do, to do well for our customers. We want to give them the best experience they can have and improve their customer journey.

38:46 – 39:10

Vanessa Luzardo Gonzalez

So we use teamwork to do that, and that’s how that’s it has made already a difference, but it’s going to make a larger impact as we move forward. We’re starting to use that cleans data in our correspondence department and we’re doing that, cleans data and our marketing department, making sure that we’re better at personalizing the service that we give our customers. So that’s that’s awesome.

39:10 – 39:48

Vanessa Luzardo Gonzalez

Just some uses is a bit like it’s becoming the base of what we’re going to add more data sources and try to understand better are what are the products that our customers have? What are the next best products that we should offer to them? And what’s going to make their their relationship with Transamerica, one that that they like and enjoy and that they can they can be happy with the products they have in the service they’re getting. So is just a piece of that. So it’s it’s very there’s a very strong impact and we’re going to see it in the next year, year and a half. We’re going to even see more value coming from all of these.

39:48 – 40:34

Vanessa Luzardo Gonzalez

So if we’re talking a couple of years, you’re going to say, Oh, remember when we asked that you asked this question, I’m going to say, Yeah, I remember we were talking about these things. Now we realize that like that value when and and now our customers are a lot happier. We like we would expect to see that even in one when we go to them and ask them about their experience and surveys that go out. We want to see it there. We want to see happy customers. And when we see happy customers, a piece of that is going to be thanks to these no cleansing of our data and understanding getting the right insights because we have the right data and I do have the right data, we have to know that the quality is good, that what we’re looking is good and that we understand our customers as well.

40:35 – 40:53

Ravi Halsey

I think I think I might have to take you up on that offer reconvening in a couple of years time and see how things have progressed. That’s certainly that’s information, better service, better communication customers. Those are all great things to achieve. So really happy to hear that those are the goals and you’re on your way to achieving them.

40:53 – 41:15

Ravi Halsey

We can move to some Q&A from the audience in a moment, but before we do, I just wanted to go round and round our panel and see if there’s anything they’d like to add on the maybe digital transformation trial. It themes that we’ve spoken about today. That’s let’s start with Anthony and anything to add as we start to wrap up the questions.

41:16 – 42:11

Anthony Deighton

Sure. So I mean, I think this has been a lot of fun, maybe just to sort of bring it full circle. I’ve sort of began with this idea of every business at its core is a data business. I think what you’ve seen from Vanessa Asset Transamerica is a very clear understanding of that. At the center of that, a Transamerica as a business is customer information that we get a handle on that customer information. Then you get this amazing business outcome and I love the way you framed it and a, you know, a happy customer or someone who appreciates the set of services and capabilities that Transamerica provides. And I think that’s a it’s a really wonderful way of encapsulating this core idea, which is putting customer data at the center of the service offering that you have and making it super successful. So it’s really wonderful to see like a real sort of study in how to make being a data driven business a reality.

42:13 – 42:15

Ravi Halsey

Thank you, Anthony. Vanessa, anything for us.

42:17 – 42:52

Vanessa Luzardo Gonzalez

Thanks. Yeah. You know, something that I wanted to to emphasize is that like we have been seeing in the last few years, is that we used to work in silos like you would and you would get in your company. You would have, like one area, work by themselves in a different area, work by themselves. What we’ve seen is that the only way to be successful is to within a company work as a team, really like analytics, data, architecture, data reporting. And it can start growing and growing data quality, data governance, even different teams. They have to just work together.

42:52 – 43:28

Vanessa Luzardo Gonzalez

And now it has gone even further in the last few years. It’s not just partnerships between our teams, but we have to partner with our external external partners like us and Tamr. And then they become part of our teams because we have to work it together. And I think that that that way of leverage, what they’re doing, there’s no way that our technical team can develop inside applications that can do everything that eight of us is developing every day. There’s no way we can have the 20, 700 or even how many how many different options of doing things like.

43:28 – 44:15

Vanessa Luzardo Gonzalez

So we we rely on what under research and what they’re doing on getting these new capabilities that we don’t have to worry about. We don’t have to update, we don’t have to to to make sure that they’re running. And if they don’t run of us takes care of it so we can focus on what we do best. We can focus on our customers and we can really focus on on our teams. Same thing with Tamr. We rely on what they’re doing and making sure that we have these good partnerships that we’re not working in silos. That’s what really makes us successful. And I think that’s the path that we need to take in. Many industries have to do the same thing because you need to do too many things nowadays to be successful. You cannot just do a couple and you have to to get help from from others. And that’s how I see it.

44:17 – 44:28

Ravi Halsey

Thank you, Vanessa and Blake. How about rounding up this trio of perspectives? Anything to add? Looks like you’re on meet. I think, Blake.

44:32 – 45:16

Blake McDonald

Gets me every time. There you go. All these HBO services, I have to learn, I still can’t figure out them, you, but I just really echo the same comments of Vanessa that, you know, it’s really at, you know, Anthony coming back to the customer. For us, everything is about that. All of our services, most of our services, I would say, where evolved from what customers ask us for. Right. So it’s just really about us, you know, keeping your ear on the customer and making sure we’re meeting their needs. And like I said, it creates wins for everyone and ultimately wins for their customers. So, you know, I had nothing really to add. I think they both summed it up very eloquently.

45:17 – 45:24

Ravi Halsey

One for Bank Blake, it looks like, Richard, you got a question there, I was him for some comment.

45:25 – 45:56

Richard Wang

I was was in the White House that White House for dinner party panel and the White House chief data scientist came out at the end of the day and he said, I have a sixty five or so data scientist. I don’t know what they are doing, but I do know one thing that every one of them is doing every day, which is cleaning up data. More than 50 percent of their time is tied to clean data. Now I say, why don’t they call it?

45:59 – 46:01

Ravi Halsey

As a Commonwealth, we’ll wait and see.

46:03 – 46:04

Anthony Deighton

We couldn’t agree more.

46:05 – 46:31

Richard Wang

I believe the real question that is multiple background, how does Tamr’s a data lake or what in a machine learning differ from the traditional data warehouse track? It’ll load and transform. Many companies are happy with what they have. So why should a look at him approach to the payment IP and those type of things to maybe just a question that actually ends up?

46:32 – 47:03

Anthony Deighton

Sure. So I wouldn’t say that a traditional etal extract, transform and load is in competition with Tamer, it’s actually quite complementary. So traditionally ETL tools are focused on moving data from point A to point B. And you know, so and often are very valuable in the context of a cloud migration. You’re moving data from on premise systems, presumably into the US retail tool can be very valuable.

47:04 – 47:53

Anthony Deighton

The issue is is there around messy data? So if you have messy data on Prem and all you’re doing in your cloud transformation is taking the siloed data to Vanessa’s point about breaking down organizational silos and data sets. All of the siloed data that you have on Prem and moving it somewhere else using Intel. You haven’t actually solved the core problem, and the core problem is messy data. And Richard, to your earlier comment, you know, the good news here from a Tamr perspective, is it will be a long time before we clean the world’s enterprise data. There is a tremendous amount of messy enterprise data out there. Every organization in the world struggles with data silos, organizational silos, messy data, inconsistent data.

47:53 – 48:29

Anthony Deighton

Now the difference is, and to your point about, you know, your earlier example, oftentimes that’s where we’re focusing energy. We’re focusing energy on trying to clean up enterprise data instead of focusing it on what Vanessa Transamerica focusing on, which is answering important business questions and providing better service to customers. And so, you know, the what we need in this market is really a new approach. Our view is that a machine learning based approach is going to be really effective for solving that problem. So it’s very complementary towards or to traditional ETL vendors.

48:29 – 49:09

Anthony Deighton

Many of our customers both start with data in a data warehouse or end with data in a data warehouse where I have it in both data warehouse at the beginning and in the end. But most typically, they’re taking data from a range of different systems. They may be using a little tool to move it, and then Tamr is providing that data mastering capability really the linchpin of their data strategy. And then the resulting data is leading back in.. Operational systems are back in a data warehouse so that we can solve a business problem and address the issue of providing better customer service or, you know, answering questions around customers. That help.

49:11 – 49:18

Ravi Halsey

Mean, that’s that’s a great, great point there, I’m starving, helps really explain where it fits in the whole flow.

49:19 – 49:32

Ravi Halsey

So let’s go into a few questions and from the audience. And first one is to see. I think for Vanessa, what specifically was the tipping point for Transamerica to pick eight of us as a partner?

49:35 – 50:33

Vanessa Luzardo Gonzalez

So I have to say that I was not involved in the decision of taking a toll booth. I came after it was fixed. But the reason why, at least in my group of data science, is that we were able to pick the how we were going to be deploying models in there. And we picked a WC and sage maker in particular to deploy our models. And we’re in that transformation right now. I can say that the reason that we picked IWC there is because one the the the full stack of tools that you can get and the full stack of services that you can get all together, that you see integration that is integration with the data that we have in the data lake and that we have in the cloud and also how it was. I think that Blake mentioned it at some points of how many connections and integrations they have with different databases, with different products, with different companies.

50:33 – 51:31

Vanessa Luzardo Gonzalez

When we are getting another tool, let’s say a data quality tool that we’re working on getting right now. It integrates beautifully with Double when we work with Tamr, integrates beautifully with us when we’re doing more deployment, it integrates really well with Bitbucket. So basically like the reason that we we pick the winners because of the service they give us, the products they give us and that integration capability and the innovation piece they don’t say or how they were five years ago, they were very different of what they are today. They still keep the same products they had and they maintain those, but they come with new ideas and with new integrations and with new connections every day. So I think that is the main reason of why we picked DWC for the for the cloud. I was not involved, but for machine learning and data science work. I was and that was my reason for picking it up.

51:31 – 51:50

Ravi Halsey

On the floor, thank you, I have a follow on question here, which was asked what is Transamerica state’s quality approach and strategy for exponentially growing data, especially customer data? Are you relying on traditional data quality tools or AI Ml based data quality tools?

51:50 – 52:29

Vanessa Luzardo Gonzalez

Well, it’s interesting that you just know that that question came up because we’re right there. We were doing a lot of it manually or more with more traditional tools. Right now, we’re moving into into machine learning and AI based tools, and then we complement with our own data science work when we need it. But yes, you cannot. You cannot have so much data coming from so many places and wanting to scan so many databases in different areas and places with tools that help you out. So we rely on Tamr on helping us out with mastering, helping us out with that data quality there.

52:29 – 52:58

Vanessa Luzardo Gonzalez

there. we have also we’re working right now with Culebra and data quality tool and trying to integrate that piece so we can have the machine learning based tool helping us out to do what we need to do. We, as I see what’s said in the question, we have so much data, we have so many customers that we need to use the best tools we can find in the market to help us leverage what we what we can do.

52:59 – 53:10

Ravi Halsey

Yeah, that’s that’s a great perspective. The question is for Anthony personally, is if time up all machine learning and two humans have some same data cleaning process.

53:11 – 53:53

Anthony Deighton

Oh, it’s great question. You know, any machine learning algorithm needs to be trained. It needs to be taught what the right answer to any given question is. And that’s where timber really uses humans. And so you can think of this as a way of taking all the intelligence that you have inside your organization about how the data fits together and then teaching a machine how to do that and then having the machine scale that across tons and tons of data that you could possibly hire enough people to get to. And so really, it’s the combination of a machine learning algorithm plus human training that is the is the winning formula to solving a problem.

53:54 – 54:11

Ravi Halsey

Thank you, Anthony. Quick question for Blake here. We’ve got a security question. We have security concerns about using the public cloud. So can you tell us what we’ll think about AWB and what they’re doing around security? That’s better than what my own company can achieve if we keep things on prem?

54:12 – 54:54

Blake McDonald

Yeah, yep, I get that one a lot. Can you hear me? Am I off mute, by the way? Oh yeah. OK, good. Yeah. Well, security is very serious to us, and it’s going to always be our top priority among everything. You know, HBC has been architected to be the most flexible. It’s true cloud environment available today. Our core infrastructure is built to satisfy the requirements of military, of global banks, of other highly sensitive organizations. And ABC uses the same secure hardware for that that we do in our commercial cloud and all of our commercial regions. So all of our customers benefit from that and those service offerings.

54:56 – 55:16

Blake McDonald

And, you know, it’s the it’s the only commercial cloud that’s had its service offerings and associated cyber supply chain vetted and accepted as a secure enough for for top secret workloads. You know, it’s backed by a deep set of cloud security tools with more than 230 compliance and government service services and key features.

55:17 – 55:47

Blake McDonald

But also our scale really significantly allows more investment in security, policing and countermeasures than almost any large organization could afford to feed themselves. You know, for example, lots of CEOs worry about the rogue server under under the desk running something destructive or something. They don’t want running, obviously. And today it’s really hard, if not impossible, for CIOs or technology chiefs to know how many orphaned resources are out there and where they might be and what they’re doing.

55:47 – 56:25

Blake McDonald

Yes. So with ABC, you know, they can use tools like ABC config and resource tagging, and they can enforce that being done. In fact, for any new resources that are spun up in the cloud to see what exactly the cloud assets their companies using at any given moment. So there’s no more hidden servers under the desk. Anonymously, place servers and racks are plugged into the corporate network. I’ll also say ABC 98 security standards. You know its certification, so more than any other offering, you know, clean PCI yes or important, obviously in financials. HIPA Fed Ramp GDPR FIPS 140. Two.

56:25 – 56:50

Blake McDonald

Yes. You know, helping satisfy all of those requirements for for, you know, virtually every regulatory agency around the globe. And lastly, I just say, you know, 117 of those 200 plus services that we have store customer data and every one offer the ability to encrypt that data. So so I would say those are, you know, a few ways in which it just provides security in a way that really would be impossible for most companies.

56:51 – 57:05

Ravi Halsey

And for us, it’s a great, comprehensive perspective like, thank you and go, just one last question which came in just just at the end, Vanessa, it’s for you. I’ll put it bluntly, why did Transamerica look to the vendor for customer master and instead of trying to do it themselves in-house?

57:07 – 57:31

Vanessa Luzardo Gonzalez

Well, we we have a limited number of resources to try to do everything in-house, so we leverage partners that we that we can find like like Tamr or or a WAC to help us do some of that work. And then that way we can we can use these tools and then use our data science teams to leverage these tools and do more.

57:31 – 58:23

Vanessa Luzardo Gonzalez

So that’s why it’s it’s one of those things that, well, if you’re going to if you’re going to bake a cake, do you want to bake the the topping of the cake? You want to create your topping of your cake, or maybe you use something that it’s already done and then you spend the time doing something else. So it’s one of those pieces. And also there’s no way we can be as good as they are and developing matching. They have a whole company working on doing mastering. Well, let’s leverage that knowledge. We cannot come up with the knowledge ourselves in everything to solve every problem. So we made sure that we find the right partner to help us out with what they’re good at. And then we try to be good at it in different things. So I think that that’s the main reason.

58:23 – 58:49

Ravi Halsey

One for Thank you, Vincent. I think it’s time to pull into this webinar and then go get some cake. So firstly, Vanessa, let’s thank you for sharing Transamerica story, your perspective. And as always, this wonderful Nancy, thank you for your perspective on really just that product. Customer Alliance and Richard, thank you for perspective as well to our audience. Thank you today for attending and look forward to some of your future.

58:50 – 58:55

Vanessa Luzardo Gonzalez

It’s my pleasure so much for having us. Thanks. Thank you. Have a wonderful.