Tuesday, December 03, 2013

BI and Big Data Analytics Force an Overdue Reckoning Between IT and Business Interests

Transcript of a Briefings Direct podcast on how advanced analytics aligns business and IT goals to bring further collaboration on innovation within the enterprise.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Dell Software.

Dana Gardner: Hi, this is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re listening to BriefingsDirect.

Gardner
Today, we present a sponsored podcast discussion on how big data and business intelligence (BI) trends are hastening a breach between enterprise IT groups and business units. We'll examine how a traditional ebb and flow between IT centralization and decentralization are now swinging in the direction of business groups and even shadow IT. This runs the risk of neglecting essential management security and scalability requirements.

Our discussion now will focus on how big data and analytics should actually force more collaboration and lifecycle-based relationships among and between business and IT groups. For those organizations -- where innovation is being divorced from IT discipline -- we'll explore ways that a comprehensive and virtuous adoption of rigorous and protected data insights can both make the business stronger and make IT more valued.

Here now to share his insights on gaining sustainable, competitive advantage by using enterprise big data strategically, we’re joined by John Whittaker, Senior Director of Marketing for Dell Software's Information Management Solutions Group. Welcome, John. [Disclosure: Dell Software is a sponsor of BriefingsDirect podcasts.]

John Whittaker: Thank you very much, Dana. I’m looking forward to having this conversation and sharing a little bit with your audience about how we at Dell Software look at this particular problem. I’ll offer some suggestions about how we might be able to implement big data and gain lasting sustainable advantage with the solutions that exist today, but doing so in a manner that’s going to deliver long-term success.

Gardner: John, we seem to go back and forth between resources in organizations being tightly controlled and governed by IT, and then resources and control resting largely with the line of business or even, as I mentioned, with a shadow IT group of some sort. So over the past 20 or more years, why has this problem been so difficult to overcome? Why is it persistent? Why do we keep going back and forth?

Whittaker: That’s an interesting question, and I agree. I've been in IT for longer than 20 years and certainly in your study of history you can see that this ebb and flow of centralized management to gain some constraints or some controls in governance and security has been one of the primary motivators of IT. It’s one of the big benefits they provide, but in the backdrop, you have lines of business that want to innovate and want to go in new directions.

Whittaker
Behind all of these things occurring, you have these mega trends that show up, these new technology innovations and these new approaches. There periodically seems to be times when the innovation cycle is really an arc.

We’re entering one of those times right now with big data and the advent of analytics, and it’s driving lines of business to push into these new technologies, and maybe  in ways that IT isn’t ready for just yet.

This, as you mentioned, has been going on for some time. The last iteration where this occurred was back in the ’90s when e-commerce and the Web captured the imagination of business. We saw a lot of similarities to what's occurring today.

Big-data push

It ultimately caused some problems back in the ’90s around e-commerce and leveraging this great new innovation of the Internet, but doing it in a way that was more decentralized. It was a little bit more of the Wild West-based approach and ultimately led to some pretty significant issues that I think we are going to see out of the big data and analytics push that’s occurring right now.

Gardner: I suppose to be fair to each constituency here, it’s the job of IT to be cautious and to try to dot all the i’s and cross the t’s. There were a lot of people in 1996-97 who didn’t necessarily think the Internet was going to be that big of a thing, it seemed to have lots of risk associated with it. So, I suppose due diligence needed to be brought to bear.

http://software.dell.comOn the other hand, if the businesses didn’t recognize that this could be a huge opportunity and we needed to take those risks -- create a website, and enter into a direct dialogue with customers to a new channel -- they would have missed a big opportunity. So these are sort of natural roles, but they can’t be too brittle.

Whittaker: You’re absolutely right. At their core, both groups had, and have, good motivations. IT lives in a world of constraints, of governance, security, and of needing to deliver something that’s going to be stable, that’s going to scale, that’s going to be secure, and that’s not going break governance.
Nobody in either group is trying to harm the business or anything close to it.

Those are laudable goals to have in mind. From the line-of-business perspective, the business wants to innovate and doesn’t want to be outmoded by its competitors. They rightfully see that all these great innovations are coming, and analysts, pundits, and experts are talking about how this is going to make a huge difference for businesses.

So they inevitably want to embrace those, and you have this cognitive dissonance occurring between the IT goals around constraints and the desire to keep things running in a clean and efficient manner. IT is seeing this new technology and saying, “Hold on. We don’t necessarily want to jump into this. This is going to break our model.”

Ultimately, IT gets to a point where maybe they suggest we shouldn’t do it or we should push it off for some time. That’s where the chasm between the two gets started. From the business perspective, the answer “no” is unacceptable, if they feel that’s what they need to do to achieve success in business. They own the profit and loss responsibilities. That’s where these problems come from.

Nobody in either group is trying to harm the business or anything close to it. They just have different motivations and perspectives on how to approach something, and when one gets wildly far apart from the other, that’s where these problems tend to occur. Again, when these big innovation cycles happen, you’re more likely to see a lot of these problems start to occur.

I definitely remember back in 1996-1997. We didn’t call it shadow IT at the time, but you saw IT-like personnel being hired into functional business areas to institute these new technologies, and that ultimately led to a pretty serious hangover at the end of that innovation cycle.

Gardner: What’s the risk of ignoring IT, doing an end-run around them, or downplaying the role? What form does it take?

On their own

Whittaker: Ignoring IT can have some pretty serious problems. It all starts with the fact that, and by and large, businesses can embrace these new technologies without the aid of IT.  Cloud-based implementations have made it possible for lines of business to rapidly deploy some of these new big data technologies, and you have vendors in some cases telling them they don’t need IT’s help. So it’s not all that difficult for lines of business to go out on their own and implement a big data technology.

But they don’t typically have the discipline to apply across-the-board governance capabilities and discipline into their deployment and that leads to potential issues with regulatory requirements. It also leads to security issues, and ultimately can lead to problems where you have seriously bad data management issues.

You have data sunk in silos, and maybe the CEO wants to know how much business we’re doing with x, y, and z. No one can deliver that, because we call x, y, and z, something in one system, a different name in another system, and a different name in the third system. Trying to pull that data together becomes really difficult. When you have lines of business independently operating disparate solutions, those core governance issues tend to break down.

Additionally, although they are great at spotting innovation opportunities, line of business people are not necessarily in the business of building scalable, secure, stable environments. That’s not the core of, say, marketing. They need to understand how the technology can be leveraged, but maintaining and managing it is not core to their charter. It tends to be ignored.

We saw in the early 2000s as the last innovation’s hangover started to occur. We saw people discovering that their systems were not scalable, that they weren’t secure, and that they were unstable because they didn’t have somebody there doing the basic care and feeding that is core to IT. That can lead to some very substantial costs. The cost could be enormous and totally unbound if you start talking about security issues that come from a lack of discipline applied at a governance level.
There are a lot of lessons that can be learned from the concept of working closely together, iterating rapidly, and being open to innovation and the idea that changes occur.

Gardner: John, it strikes me that there are some examples within IT that help understand this potential problem and even grab some remediation, and that’s in software development. We’ve seen the complexity in groups working without a lot of coordination and shared process insights and have run aground.

For many years, we saw a very high failure rate among software development projects, but more recently, we’ve seen improvements -- agile, scrum, opening up the process, small iterative steps that then revert back to an opportunity to take stock and know what everyone is doing, checking in, checking out with centralization -- but without stifling innovation. Is there really a lesson here in what’s happened within software development that could be brought to the whole organization?

Whittaker: Absolutely. In fact, within Dell Software itself we embrace agile and use scrum internally. There are a lot of lessons that can be learned from the concept of working closely together, iterating rapidly, and being open to innovation and the idea that changes occur.

Particularly in these major innovation cycles, it’s important to go with the flow and implement some of these new technologies and new capabilities early, so you can have that brain trust built internally among the broad team. You don’t want IT to hold the reins entirely, and at the same time, you don’t want line of business to do it.

We really need to break that model, that back and forth, centralization-decentralization swing that keeps occurring. We need to get to a point where we really are partnering and have good collaboration, where innovation can be embraced and adopted, and the business can meet its goals. But it has to be done in a way that IT can implement sound governance and implement solutions that can scale, are stable, are reliable, and are going to lead to long-term success.

Back-and-forth

We’ve got to get out of these back-and-forth cycles that occur or we’re going to continue to have these problems. As innovations occur more rapidly, you’re going to have more and more problems like these occurring if you don’t find a way to get IT and line-of-business motivations and interests allied.

Gardner: What’s different this time, John? Are the stakes higher because we’re talking about data analysis? That’s basically intelligence about what’s going on within your markets, your organization, your processes, your supply chain, your ecosystem, all of which could have a huge bearing.

We have the ability now to tackle massive amounts of data very rapidly, but if we don’t bring this together holistically, it seems as if there is a larger risk. I’m thinking about a competitive risk. Others that do this well could enter your market and really disrupt.

Whittaker: You’re absolutely right. There’s great potential benefit that organizations receive or can get out of leveraging big data and analytics, that of being able to determine predictively what is going to occur in their business and what are the most efficient routes to market and what areas of improvements can occur.

The businesses that leverage this are going to outmode, outperform, and ultimately win in the markets currently dominated by organizations who aren’t paying attention and who aren’t implementing solutions today. They’re getting a little bit ahead of this cycle so that they are ready and are able to be successful down the road.
We’re really moving into an era where the context of what’s happening is critically important.

We’re really moving into an era where the context of what’s happening is critically important. A data-driven management model is going to be embraced and it’s ultimately going to lead to more successful organizations. Companies and organizations that embrace this today are going to be the winners tomorrow.

If you’re ignoring this or putting this off, you’re really taking a tremendous risk, because this next iteration of innovation that’s occurring around analytics applies to large data sources. It’s being able to build the correlations and determine that this is a more efficient approach, or conversely, that we have a problem with this outlier that’s going to give us issues down the road.

If you’re not doing that as an organization, you really are running a pretty tremendous risk that somebody else is going to walk in and be able to make smarter decisions, faster.

Gardner: At the same time, your customers are gaining insights into how to procure all the better. And so any rewards that might be out there, if you are in a sales role of any kind, would become much more apparent.

Whittaker: That’s definitely true as well. The construct and the conversation has really shifted. With the advent of social media and the pace at which information is shared and opinions are made, it’s no longer the company that is the primary voice about its products and its capabilities or its positions and point of views.

Customers more empowered

It needs to have those. It needs to get them out. It needs to push them. But in this new world we live in, the customers are so much more empowered than they have ever been before, and it should be a good thing. For companies that are delivering great products and solving real problems for their customers, this should be great news.

If you’re not listening to what your customers are saying in social media and if you’re not paying attention to the ongoing story line and conversation of your firm in the social sphere, you’re really putting yourself at risk. You’re missing out on a tremendous opportunity to engage with your customers in a new, interesting, and very useful way.

That’s a lot of what we built. We have a lot of capabilities here at Dell Software around data management, data integration, and data analysis. On the analysis side, we spend a great deal of time with products like Kitenga and our social networking analytics platforms to do that semantic analysis and look into that form of big data.

But big data is more than just social. It’s also sensor data. The iterative thing is another area where businesses should be innovating and organizations should be pushing to take advantage of it. That’s where line of business should be saying, “We need to get out into this area, or if we don’t, we’re going to be outmoded by our competitors.” And IT should be encouraging it. They should be pushing for more innovation, bringing new ideas, and being a real partner and collaborator at the table within the business and organization. That’s the right way to do this.
IT could use big data analytics to improve its own environment and to answer this crisis of confidence that exists.

Gardner: Otherwise, we run the risk of peeling back an onion only to find other layers unconnected to one another. We don’t get that one view of the customer, that one view of the patient, or that one view of an extended business process. We just create more silos of data. Centralized IT organizations perhaps are better than almost anyone in understanding how to connect those, rather than keep them spinning off on their own.

Whittaker: Absolutely. And IT itself should be applying some of these technologies. In fairness to line of business, there exists a bit of a crisis of confidence in IT, and there’s really no better way to push against that or fight against that then to be able to run analytics on the solutions you’re providing. How well is IT performing? Are you benchmarking against past performance? How do you benchmark against your industry?

That’s another component. Big-data analytics can be utilized by IT not just to deliver capabilities to the organization or push out and help with connecting to the customer. IT could use big data analytics to improve its own environment and to answer this crisis of confidence that exists.

You could turn these tools internally and look at rates of response as compared to your industry, how your network is performing, how your database is performing, or how the code you write is performing. Are your developers efficient in building clean code?

Everybody has been watching the major shift in the healthcare environment in North America. A big component of that probably should have been more benchmark analysis, analytics on code quality, and things of that nature. That’s a great current and topical example of how IT should be utilizing some of these technologies, not just externally, not just bringing it to line of business, but within its own environment, to prove that it’s building systems that are going to be scalable, secure, and stable.

Gardner: What needs to take place in order for this higher level of coordination and collaboration to take place? Are there any key steps that you have in mind for embarking on this?

Four key areas

Whittaker: I think that there are four key areas that need to occur for this collaboration to happen. Number one, senior executives need to be aligned to what the organization is trying to achieve. They need to articulate a common vision that accounts for the shared interest of both IT and line of business and make it clear that they expect collaboration. That should come at the top of the organization.

We need to get out of the smoke-stacked, completely siloed, organizational approaches and get to something that’s far, far more collaborative, and that needs to come from the top. The current approach is not acceptable. These groups need to work together. That’s a key component. If you don’t have buy-in at the top, it makes it really hard for this collaboration to occur.

Number two, IT needs to get its house in order. This means many things, but primarily, it means overcoming the crisis of confidence line of business has in IT by coming to the table with an approach that works for line of business, something that business aligns with such that it feels like it has IT involvement and that they’re buying into the future that the business wants to head towards. IT needs to show that they have a plan that does not compromise the innovations that the business needs.

IT absolutely can no longer just say no. That’s not an acceptable position. Certainly, if you look back, there were IT organizations that were saying, “No, we’re not going to connect to the Internet. It’s not secure. The answer is just going to be no.”

That didn’t work out for them and it’s not going to work out here either. They should be embracing this shift. We shouldn’t perpetuate this cycle by driving more shadow IT and creating ultimately more for IT down the road as inevitable problems start to emerge.
We shouldn’t perpetuate this cycle by driving more shadow IT and creating ultimately more for IT down the road as inevitable problems start to emerge.

Number three, clear the air and put the executive plan in place. Tensions between IT and line of business have gotten to the point where they can’t be ignored any more. Put the stakeholders together in a room, air out the difficulties, and move forward with a clean slate. This is a tremendous opportunity to build a plan that meets both parties’ needs and allows them to start executing on something that’s really going to make a huge impact for the business.

Finally, the fourth point, seek solutions that emphasize collaboration between IT and the business. Many vendors today are encouraging groups to go rogue and operate in silos, and that’s causing a lot of the problem. At Dell, we’re much more about pushing a more collaborative approach. We think IT is terrific, but business has a point. They need innovation and they need IT to step up. And the business needs to embrace IT.

Instead of conflicting with each other and doing your own thing, back up your commitment to collaboration and utilize tools that empower it. That’s where we’re going to win, and that’s how business is going to succeed in the future.

Gardner: Just to be clear John, it sounds as if these aren’t just issues for large enterprises. Mid-size and mid-market organizations, I should think, are in the same issue set or the same ballgame.

Whittaker: You’re absolutely right. If you have an IT department and you have functional business units, you probably have this problem. Certainly, you can benefit from more collaboration, from implementing and instituting an approach to leverage big data and analytics in order to make smarter business decisions is something that everybody is going to need today.

This isn’t something that the G20, the Fortune 500, or Fortune 2000 alone can benefit from. This goes way down in the hierarchy, in the stack, certainly down to the small- and medium-sized business (SMB) level. And maybe even lower. If you’re a data-intensive small business, you probably need to start implementing and taking a look at big data and what analytics based approaches and data-driven decision making opportunities exist within your organization, or you will be outmoded by organizations that do embrace that.

Cloud-based approach

More and more, we’re seeing, particularly in the mid-market, embracing of a cloud-based approach. It's important to point out that that approach is fine and terrific. We love the cloud and we’re big proponents of it, but using a cloud-based solution doesn’t free line of business from the need to collaborate with IT. It will not eliminate this problem.

Yes, you may get a little bit more of stable solution in the cloud, as opposed to managing it yourself, because it's still not core to the functional group. Ultimately, IT is the group that really knows how and where they can apply appropriate constraints, really control those relationships a little better, and ensure that they have solutions in place that allow for you to analyze all the data in the environment.

You need analysis of all the data that exists right now in your cloud implementation, data that exists in all the systems throughout, so you can see all the components and find out where the correlations lie. And if you have siloed data, if you have gone your own way, you’re going to be missing that component.

Gardner: I imagine too that you can’t outsource your alignment of your business strategy with your technology capabilities. In fact, for IT, being able to have more choice with these models for workloads and deployments, frees them up to take more of a role in this alignment.
All businesses want the same thing. They want to find sustainable competitive advantages.

I would think that the role of enterprise architects starts to blend into IT, because they’re no longer looking at the red light-green light issues, keeping the hardware operating. Now, they can really take more of a role and step up to a higher plane on these alignment issues.

Whittaker: Absolutely. We’re seeing terrific IT departments and leadership starting to take a larger role, starting to ultimately become drivers of innovation. That’s really what we want to see. All businesses want the same thing. They want to find sustainable competitive advantages. They want to control spending. They want to reduce risk to the business.

And the most effective and efficient path to achieving all three is getting IT and the business aligned and allowing that collaboration to occur. That’s really at the crux of how businesses are going to gain competitive advantage out of technology in the future.

Gardner: Well, John, I’m afraid we will have to leave it there. We’re about out of time. You’ve been listening to a sponsored BriefingsDirect podcast discussion on how big data and business intelligence trends are hastening a breach or perhaps an alignment between enterprise IT groups and business units. And now is the time to be thinking about which of those directions you will be taking.

You have seen how a more cooperative and innovation fostering relationship, one that can perhaps exploit big data benefits for all is in order and that the stakes are quite high.

And we have learned more about how gaining sustainable competitive advantages using big data strategically among all aspects of enterprises and small businesses should be something made a priority and happen as soon as possible.

Any last words John on recommendations or what you think were some of the more important points that we went over today?

Embrace new technology

Whittaker: Thank you, Dana, this was terrific. And thank you, to the audience, for listening. I would say, again, the big points are, embrace the new technology that’s coming out. The innovation is going to make your business far more successful, and your organization will prosper from these new innovations that will occur.

Number two, do it in a manner that is collaborative between IT and line of business. The CIO, the CMO, the CFO, the CEO, the heads of all of the functional departments, whether you are in sales, marketing, finance, operation, wherever you are, should be aligning with their IT counterparts. It's the combined collaborative approach that’s going to win the day.

And finally, this should really be driven top-down. Senior executives, this is an opportunity to get everybody on the same page to go after and leverage a pretty enormous opportunity before it becomes a huge problem. Let’s get out there right now. We’re still in the early days, but that doesn’t mean there’s not a lot to be gained. And ultimately, in the long-term, we’re going to have more successful organizations able to achieve even greater output through this collaboration and the leveraging of big data analytics.

Gardner: Very good. Thank you to our guest, John Whittaker, Senior Director of Marketing for Dell Software’s Information Management Solutions Group. It was really good talking with you today, John.

Whittaker: Thanks a lot, Dana.

Gardner: And also, a big thank you to our audience for joining this insightful discussion. This is Dana Gardner, Principal Analyst at Interarbor Solutions. Don’t forget to come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: Dell Software.

Transcript of a Briefings Direct podcast on how advanced analytics aligns business and IT goals to bring further collaboration on innovation within the enterprise. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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Wednesday, November 13, 2013

Cardlytics on HP Vertica Powers Millions of Swiftly Tailored Marketing Offers to Bank Card Consumers

Transcript of a BriefingsDirect podcast on how a marketing company uses HP Vertica to match advertisers with potential customers across an ever-growing expanse of data and queries.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for this ongoing discussion of IT innovation and how it’s making an impact on people’s lives.

Gardner
Once again, we’re focusing on how IT leaders are improving their business performance for better access, use and analysis of their data and information. This time we’re coming to you directly from the recent HP Vertica Big Data Conference in Boston.

Our next innovation case study interview highlights how data-intensive credit- and debit-card marketing services provider, Cardlytics, provides millions of highly tailored marketing offers to banking consumers across the United States. We'll learn more about how Cardlytics, in adopting a new analytics platform, gained huge data analysis capacity, vastly reduced query times, and swiftly meets customer demands at massive scale.

So please join me now in welcoming Craig Snodgrass, Senior Vice President for Analytics and Product at Cardlytics Inc., based in Atlanta. Welcome, Craig. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Craig Snodgrass: Thanks for having me.

Gardner: At some point, you must have had a data infrastructure or legacy setup that wasn't meeting your requirements. Tell us a little bit about the journey that you've been on gaining better analytic results for your business.

Snodgrass: As with any other company, our data was growing and growing and growing. Also growing at the same time was the number of advertisers that we were working with. Since our advertisers spanned multiple categories -- they range from automotive, to retail, to restaurants, to quick-serve -- the types of questions they were asking were different.

Snodgrass
So we had this intersection of more data and different questions happening at a vertical level. Using our existing platform, we just couldn't answer those questions in a timely manner, and we couldn't iterate around being able to give our advertisers even more insights, because it was just taking too long.

First, we weren’t able to even get answers. Then, when there was the back-and-forth of wanting to understand more or get more insight it just ended up taking longer-and-longer. So at the end of the day, it came down to multiple and unstructured questions, and we just couldn't get our old systems to respond fast enough.

Gardner: Tell us a bit about Cardlytics. Who are your customers, and what do you do for them?

Growing the business

Snodgrass: Our customers are essentially anybody who wants to grow their business. That's probably a common answer, but they are advertisers. They're folks who are used to traditional media, where when they do a TV or radio ad. They're hitting everybody, people that were going to come to their store anyways and people who probably weren’t going to come to their store.

We're able to target who they want to bring into their store through looking at both debit-card and credit-card purchase data, all in an anonymized manner. We’re able to look at past spending behavior, and say, based on those spending behaviors, that these are the types of customers that are most likely to come to your store and more importantly, most likely to be a long-term customer for you.

We can target those, we can deliver the advertising in the form of a reward, meaning the customer actually gets something for the advertising experience. We deliver that through their bank.

The bank is able to do this for their customers as well. The reward comes from the bank, and the advertiser gets a new channel to go bring in business. Then, we can track for them over time what their return on ad-spend is. That’s not an advantage they’ve had before with the traditional advertising they’ve been doing.
It works inside of retail, just as well as restaurants, subscriptions, and the other categories that are out there as well.

Gardner: So it sounds like a win, win, win. As a consumer, I'm going to get offers that are something more than a blanket. It's going to be something targeted to me as the bank that’s providing the credit card. They're going to get loyalty by having a rewards effort that works. Then, of course, those people selling goods and services have a new way of reaching and marketing those goods and services in a way they can measure.

Snodgrass: Yeah, and back to this idea of the multiple verticals. It works inside of retail, just as well as restaurants, subscriptions, and the other categories that are out there as well. So it's not just a one-category type reward.

Gardner: But to make it work, to make that value come across to the consumer, it needs to be a quality targeted effort. Therefore you need to take a lot of data and do a lot of queries.

Snodgrass: You got it. A customer will know quickly when something is not relevant. If you bring in a customer for whom it may not be relevant or they weren’t the right customer, they're not going to return.

The advertiser isn't going to get their return on ad-spend. So it's actually in both our interests to make sure we choose the right customers, because we want to get that return on ad-spend for the advertisers as well.

Gardner: Craig, what sort of volume of data are we talking about here?

Intersecting growth

Snodgrass: We're doing roughly 10 terabytes a year. From a volume standpoint, it's a combination of not just the number of transactions we're bringing in, but the number of requests, queries, and answers that we’re having to go against it. That intersection of growth in volume and growth in questions is happening at the same time.

For us right now, our data is structured. I know a lot of companies are working on the unstructured piece. We're in a world where in the payment systems and banking systems, the data is relatively structured and that's what we get, which is great. Our questions are unstructured. They're everywhere from corporate real estate types of questions, to loyalty, to just random questions that they've never known before.

One key thing that we can do for advertisers is, at a minimum, answer two large questions. What is my market share in an area? Typically, advertisers only know when customers come into their store with that transaction. They don't know where that customer goes and, obviously, they don't know when people don’t come into their store.

We have that full 360-degree view of what happens at the customer level, so we can answer, for a geographic area or whatever area that an advertiser wants, what is their market share and how is their market share trending week-to-week.

The other piece is that when we do targeting, there could be somebody that visits a location three times over a certain time period. You don't know if they're somebody who shops the category 30 times or if they only shop them three times. We can actually answer share-of-wallet for a customer, and you can use that in targeting, designing your campaigns, and more importantly, in analysis. What's going on with these customers?
For us, with Vertica, one of the key components isn't just the speed, but how quick we can scale if the number of queries goes up.

Gardner: So this is any marketers' dream. This is what people have been trying to do and thinking about doing for decades, and now we’re able to get there. One of the characteristics, though, if I understand your challenge from a data-processing perspective, is not only the volume. You're going to have many different queries hitting this at once, because you have so many different verticals and customers. The better job you do, the more queries will be generated.

Snodgrass: It's a self-fulfilling prophesy. For us, with Vertica, one of the key components isn't just the speed, but how quick we can scale if the number of queries goes up. It's relatively easy to predict what our growth and data volume is going to be. It is not easy for me to predict what the growth in queries is going to be. Again, as advertisers understand what types of questions we can answer, it's unfortunately a ratio of 10 to 1. Once they understand something, there are 10 other questions that come out of it.

We can quickly add nodes and scalability to manage the increase in volumes of queries, and it's cheap. This is not expensive hardware that you have to put in. That is one of the main decision points we had. Most people understand HP Vertica on the speed piece, but that and the quick scalability of the infrastructure were critical for us.

Gardner: Just as your marketing customers want to be able to predict their spend and the return on investment (ROI) from it, do you sense that you can predict and appreciate, when you scale with HP Vertica what your costs will be? Is there a big question mark or do you have a sense of, I do this and I have to pay that?

Snodgrass: It is the "I do this and I'll have to pay that," the linearness. For those who understand Vertica, that’s a bit of a pun, but the linear relationship is that if we need to scale, all we need to do is this. It's very easy to forecast. I may not know the date for when I need to add something, but I definitely know what the cost will be when we need to add it.

Compare and contrast

Gardner: How do you measure, in addition to that predictability of cost, your benefits? Are there any speeds and feeds that you can share that compare and contrast and might help us better understand how well this works?

Snodgrass: There are two numbers. During the POC phase, we had a set of 10 to 15 different queries that we used as a baseline. We saw anywhere from 500x to 1,000x or 1,500x speed in return of getting that data. So that’s the first bullet point.

The second is that there were queries that we just couldn't get to finish. At some point, when you let it go long enough, you just don't know if it is going to converge. With Vertica, we haven't hit that limit yet.

Vertica has also allowed to have varying degrees of analysts’ capabilities when it comes to SQL writing. Some are elegant and they write fantastic, very efficient queries. Others are still learning the best way to go put the queries together. They will still always return with Vertica. In the legacy world prior to Vertica, those are the ones that just wouldn't return.
In a SaaS shop, there are a lot of things that you're going to do in SaaS that you are not going to go do in SQL

I don’t know the exact number for how much more productive they are, but the fact that their queries are always returning, and returning in a timely manner, obviously has dramatically increased their productivity. So it's a hard one to measure, but forget how fast the queries have returned, the productivity of our analyst has gone up dramatically.

Gardner: What could an analytics platform do better for you? What would you like to see coming down the pipeline in terms of features, function, and performance?

Snodgrass: If you could do something in SQL, Vertica is fantastic. We'd like more integration with R, more integration with software as a service (SaaS), more integration with these sophisticated tools. If you get all the data into their systems, maybe they can manipulate it in a certain way, but then, you are managing two systems.

Vertica is working on a little bit better integration with R through distributed R, but there's also SaaS as well. In a SaaS shop, there are a lot of things that you're going to do in SaaS that you are not going to go do in SQL. That next level of analytics integration is where we would love to go see the product go.

Gardner: Last question. Do you expect that there will be different types of data and information that you could bring to bear on this? Perhaps some sort of camera, sensor of some sort, point-of-sale information, or mobile and geospatial information that could be brought to bear? How important is it for you to have a platform that can accommodate seemingly almost any number of different information types and formats?

Snodgrass: The best way to answer that one is that we don't ever want to tell business development that the reason they can't pursue a path is because we don't have a platform that can support that.

Different paths

Today, I don't know where the future holds from these different paths, but there are so many different paths we can go down. It's not just the Vertica component, but the HP HAVEn components and the fact that they can integrate with a lot of the unstructured, I think they call it “the human data versus the machine data.”

It's having the human data pathway open to us. We don't want to be the limiting factor for why somebody would want to do something. That's another bullet point for HP Vertica in our camp. If a business model comes out, we can support it.

Gardner: Clearly there's a revolution taking place in retail, and it sounds like you are on the vanguard of that.
I don't know where the future holds from these different paths, but there are so many different paths we can go down.

Snodgrass: Yeah, I agree.

Gardner: Okay, well I'm afraid we'll have to leave it there. We've been learning how data-intensive credit card marketing services provider Cardlytics is providing millions of highly tailored marketing offers to their banking consumers and customers for marketing activities in sales across the U.S.

And we've also heard how they deployed an HP Vertica Analytics Platform to provide better analytics to deliver those insights to these many customers. So a big thank you to our guest, Craig Snodgrass, Senior Vice President for Analytics and Product at Cardlytics.

Snodgrass: Thank you, Dana.

Gardner: And thank you also to our audience for joining us for this special HP Discover Podcast coming to you directly from the recent HP Vertica Big Data Conference in Boston.

I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP sponsored discussions. Thanks again for joining, and come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Transcript of a BriefingsDirect podcast on how a marketing company uses HP Vertica to match advertisers with potential customers across an ever-growing expanse of data and queries.
Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

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Wednesday, November 06, 2013

Efficient Big Data Capabilities Help Cerner Drive Needed Improvements into Healthcare Outcomes

Transcript of a Briefings Direct podcast on how a large provider of healthcare services is providing insight into patient outcomes as well as EMR system performance.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Dana Gardner: Hello, and welcome to the next edition of the HP Discover Podcast Series. I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your moderator for this ongoing discussion of IT innovation and how it’s making an impact on people’s lives.

Gardner
Once again, we’re focusing on how IT leaders are improving their business performance for better access, use and analysis of their data and information. This time we’re coming to you directly from the recent HP Vertica Big Data Conference in Boston.

Our next innovation case study highlights how a healthcare solutions provider leverages big-data capabilities. We’ll see how they deployed the HP Vertica Analytics platform to help their customers better understand population healthcare trends, as well as to help them run their own systems internally.

To learn more about how high performing and cost effective big data processing forms a foundational element to improving healthcare quality and efficiency, please join me now in welcoming our guest, Dan Woicke, Director of Enterprise Systems Management at Cerner Corp. based in Kansas City, Missouri. Welcome, Dan. [Disclosure: HP is a sponsor of BriefingsDirect podcasts.]

Dan Woicke: First of all, thank you very much for having me. It’s my first time in Boston. So I'm having a blast here.

Gardner: Terrific. Let’s start at a high level and talk a little bit about why, in the healthcare industry in particular, big data is super important. We're going through some major transitions in how payments are going to be made and how even the definition of good care is defined. We're moving from pay for procedures to more pay for outcomes. So tell me about Cerner, and why big data is such a big deal.

Woicke: Obviously, you hit the nail on the head. The key element here is that the payment structure is changing to more of an outcome model. In order for that to happen, we need to get all the sources of data from many, many disparate systems, bring them in, and let our analysts work on what the right trends are and predict quality outcomes, so that you can repeat those and stay profitable in the new system.

Gardner: It’s interesting that, on one side of the coin, you're looking to bring large data sets together to analyze what’s going on in the field, but in order to allow you to better serve those needs, you also have big IT systems. They're putting out a lot of data, and you need to analyze them. Tell us a little bit about two ways in which big data is being employed there at Cerner.

Woicke: We’ll touch on more of the clinical side of how we are processing this data in the new model. My direct responsibility is to bring in massive amounts of performance data. This is how our Cerner Millennium systems are running.

We have hundreds of clients, both in the data center and those that manage their own systems with their own database administrators (DBAs). The challenge is just to have a huge system like that running with tens of thousands of clinicians on the system.

We need to make sure that we have the right data in place in order to measure how systems are running and then be able to predict how those systems will run in the future. If things are happening that might be going negative, how can we take the massive amounts of data that are coming into our new analytical platform, correlate those parameters, predict what’s going to happen, and then take action before there is a negative?

Effect change

We want to be able to predict what’s happening, so that we can effect change before there is a negative impact on the system.

Gardner: Everybody, almost across any business you talk to, wants to be more proactive and get out in front of these issues. Tell me how big data and the ability to manage big data gets you closer to the real time and then, ultimately, proactive.

Woicke: Since January of this year, we've started to bring in what we call Response Time Measurement System (RTMS) records. For example, when a doctor or a nurse is in our electronic medical record (EMR) system is signing an order, I can tell you how long it took to log into the system. I can tell you how long you were in the charting module.

Woicke
All those transactions produce 10 billion timers, per month, across all of our clients. We bring those all into our HP Vertica Data Warehouse. Right now, it’s about a two-hour response time, but my goal, within the next 12 months, is to get it down to 10 minutes.

I can see in real time when trends are happening, either positive or negative, and be able to take action before there is an issue.

Gardner: That’s impressive. Tell us a little bit about Cerner and describe the company -- what they do, and this idea that you have not just your own systems, but you're managing systems that other people use as well.

Woicke: We have two data centers in Kansas City, Missouri and we host more than half for our clients in those data centers. The trend is moving toward being remote-hosted managed like that. We still have a couple of hundred clients that are managing their own Millennium domains. As I said before, we need to make sure that we provide the same quality of service to both those sets of clients.

Gardner: So you're used primarily by healthcare organizations. Tell us how you actually function within healthcare and the services that you provide to these organizations.

Woicke: We run the largest EMR in the world. We have well over 400 domains to manage  -- we call them domains -- which allows us to hook up multiple facilities to those domains. Once we have multiple facilities connecting into those domains, at any given time, there are tens of thousands clinicians  on the system at one time.

Gardner: I'm still trying to tease out a little bit of more understanding of the function that you provide to these health providers. Are you doing their medical records inventory for them or do you have a set of applications in addition to that? Help us understand better what services you provide.

Single database

Woicke: Cerner Millennium is a suite of products or solutions. Millennium is a platform where the EMR is placed into a single database. Then, we have about 55 different solutions that go on top of that platform, starting with ambulatory solutions. This year was really neat. We were able to launch our first ambulatory iPad application.

There are about 55 different solutions, and it's growing all the time with surgery and lab that fit into the Cerner Millennium system. So we do have a cohesive set of data all within one database, which makes us unique.

Gardner: Before we go to some more insights about the healthcare industry, population health, and some of the great analytics that can be brought there, let’s drill down a little bit into what you're doing on site. Where does the data come from primarily? Is this log information. Do you have a set of management systems of your own, and how much data we are talking about?

Woicke: We're talking about quite a bit of data, and that’s why we had to transform something away from a traditional OLTP database into an MPP type database, because those systems that are now sending data to Cerner. 

We have claims data, and HL7 messages. We're going to get all our continuous care records from Millenium. We have other EMRs. So that’s pretty much the first time that we're bringing in other EMR records.
What that's going to do is bring the total cost of your healthcare down, which is really the goal.

We have health-plan enrollments, and then of course, within Millennium, we're going to drill down into outcomes, re-admissions, diagnosis, and allergies. That’s the data that we need to be able to predict what kind of care we are going to have in the future.

Gardner: Now, you're also looking to how you can better understand the marketplace and provide insights, so that people can literally change on a dime, change the wings on the airplane while it’s still in the air, if you will, in healthcare and population health. What are the insights that you can get there and what are the data sets that you need in order to do that?

Woicke: The data sets are similar to what we just discussed. You’ll have that claim data that comes in from multiple sources, multiple EMRs, but the whole goal of population health is to get a population to manage their own health. That means that we need to give them the tools in their hands. And they need to be accurate, so that they can make the right decisions in the future. What that's going to do is bring the total cost of your healthcare down, which is really the goal.

Gardner: So it seems to me that we talk about "Internet of things." We're also going to the "Internet of people." More information from them about their health comes back and benefits you and benefits the healthcare providers. But ultimately, they can also provide great insights to the patients themselves.

Do you see, in the not too distant future, applications where certain data -- well-protected and governed of course -- is made into services and insights that allow for a better proactive approach to health.

Proactive approach

Woicke: Without a doubt. We're actually endorsing this internally within the company by launching our own weight-loss challenges, where we're taking our medical records and putting them on the web, so that we have access to them from home.

I can go on the site right now and manage my own health. I can track the number of steps I'm doing. Those are the types of tools that we need to launch to the population, so that they endorse that good behavior, which will ultimately change their quality of life.

Gardner: Then, there is also this notion of anonymized patient information, where you can take an aggregate and find out what works and what doesn’t work when it comes to behavior, patterns of fruition when it comes to things like weight loss. Tell me how that grander view, the holistic view of the data, comes to bear as well. 

Woicke: Right now, we're in production with the operation side that we talked about a little bit about earlier. Then, we are in production with what we call Health Facts, a huge set of blinded data. We hire a team of analysts and scientists to go through this data and look for trends.
You can see what that’s going to do for the speed of the amount of analysis we could do on the same amount of data. It’s game changing.

It’s something we haven’t been able to do until recently, until we got HP Vertica. I am going to give you a good example. We had analysts log a SQL query to do an exploratory type of analysis on the data. They would log that at 5 p.m., then issue it, and hopefully, by the time they came back at 8 a.m. the next day, that query would be done.

In Vertica, we've timed those queries at between two and five seconds. So you can see what that’s going to do for the speed of the amount of analysis we could do on the same amount of data. It’s game changing.

Gardner: Let me ask you, Dan, about that process through which you acquired Vertica. How did you adopt it? What were some of the requirements, and why didn’t some of the other alternatives work out?

Woicke: There were a lot of competitors that would have worked out, but we had a set of criteria that we drilled down on. We were trying to make it as scientific as possible and very, very thorough. So we built a score sheet, and each of us from the operation side and Health Facts side graded and weighted each of those categories that we were going to judge during the proof of concept (POC). We ended up doing six POCs.

We got down to two, and it was a hard choice. But with the throughput that we got from Vertica, their performance, and the number of simultaneous users on the system at a given period of time, it was the right choice for us.

Gardner: And because we're talking about healthcare, costs are super important. Was there a return on investment (ROI) or cost benefit involved as well?

Extremely competitive

Woicke: Absolutely. You could imagine that this would be the one or two top categories weighted on our score sheet, but certainly HP Vertica is extremely competitive, compared to some of the others that we looked at.

Gardner: Dan, looking to the future, what do you expect your requirements to be, say, two years from now? Is there a trajectory that you need to take as an organization, and how does that compare to where you see Vertica going?

Woicke: Having Vertica as a partner, we navigate that together. They invited me here to Boston to sit on the user board. It was really neat to sit right there with [HP Vertica General Manager] Colin Mahony at the same table and be able to say, "This is what we need. These are our needs coming around the corner," and have him listen and be able to take action on that. That was pretty impressive.

To answer your question though, it’s more and more data. I was describing the operations side, where we bring in 10 billion RTMS records. There's going to be another 10 billion type of records coming in from other sources, CPU, Memory, Disk I/O, everything can be measured.

We want to bring it into Vertica, because I'm going to be able to do some correlation against something we were talking about. If I know that the RTMS records show a negative performance that's going to happen within the next 10-15 minutes, I can figure out which one of those operational parameters is most affecting that outcome of that performance, and then can send the analyst directly in to mitigate that problem.
By bringing in more and more data and being able to correlate it, we're going to show all the clients, as well as the providers, how their system is doing.

On the EMR side, it’s more data as well. On the operations side, we're going to apply this to other enterprises to bring in more data to connect to the experts. So there is always somebody out there. That’s the expert. What we're going to do is connect the provider with the payers and the patient to complete that triangle in population health. That’s where we're going in the next few months.

Gardner: I certainly think that managing data effectively is a huge component of our healthcare challenge here in the United States, and of course, you're operating in about 19 countries. So this is something that will be a benefit to almost any market where efficiency, productivity, quality of care come to bear.

Woicke: At Cerner Corp., we're really big on transparency. We have a system right now called the Lights On Network, where we are taking these parameters and bringing them into a website. We show everything to the client, how they're performing and how the system is doing. By bringing in more and more data and being able to correlate it, we're going to show all the clients, as well as the providers, how their system is doing.

Gardner: Well, great. I'm afraid we’ll have to leave it there. We've been learning about how a healthcare solutions provider has been leveraging big-data capabilities, and we've seen how at Cerner Corp. they've deployed HP Vertica Analytics Platform to help their customers better understand population health trends, as well as to gain terrific insights into their own systems and the systems that they host for others.

So, a big thank you to our guest, Dan Woicke, Director of Enterprise Systems Management at Cerner Corp. Thanks so much, Dan.

Woicke: Thank you for having me.

Gardner: And thank you also to our audience for joining this special HP Discover podcast coming to you directly from the recent HP Vertica Big Data Conference in Boston.

I'm Dana Gardner; Principal Analyst at Interarbor Solutions, your host for this ongoing series of HP sponsored discussions. Thanks again for joining, and don’t forget to come back next time.

Listen to the podcast. Find it on iTunes. Download the transcript. Sponsor: HP.

Transcript of a Briefings Direct podcast on how a large provider of healthcare services is providing insight into patient outcomes as well as EMR system performance. Copyright Interarbor Solutions, LLC, 2005-2013. All rights reserved.

You may also be interested in: