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We’ll examine how the tough economy has accelerated the progression toward more data-driven business decisions. To enable speedy proactive business analysis, information management (IM) has arisen as an essential ingredient for making business intelligence (BI) for these decisions pay off.
Yet IM itself can become unwieldy, as well as difficult to automate and scale. So managing IM has become an area for careful investment. Where then should those investments be made for the highest analytic business return? How do companies better compete through the strategic and effective use of its information?
We’ll look at some use case scenarios with executives from HP to learn how effective IM improves customer outcomes, while also identifying where costs can be cut through efficiency and better business decisions.
To get to the root of IM best practices and value, please join me in welcoming our guests, Brooks Esser, Worldwide Marketing Lead for Information Management Solutions at HP. Welcome, Brooks.
Brooks Esser: Hi, Dana. How are you today?
Gardner: I’m great. We’re also here with John Santaferraro, Director of Marketing and Industry Communications for BI Solutions at HP. Hello, John.
John Santaferraro: Hi Dana. I’m glad to be here, and hello to everyone tuning into the podcast.
Gardner: And also, we’re here with Vickie Farrell, Manager of Market Strategy for BI Solutions at HP. Welcome to the show.
Vickie Farrell: Hi, Dana, thanks.
Gardner: Let me take our first question out to John. IM and BI in a sense come together. It’s sort of this dynamic duo in this era of cost consciousness and cost-cutting. What is it about the two together that you think is the right mix for today’s economy?
Santaferraro: Well, it’s interesting, because the customers that we work with tend to have very complex businesses, and because of that, very complex information requirements. It used to be that they looked primarily at their structured data as a source of insight into the business. More recently, the concern has moved well beyond business intelligence to look at a combination of unstructured data, text data, IM. There’s just a whole lot of different sources of information.
The idea that they can have some practices across the enterprise that would help them better manage information and produce real value and real outcomes for the business is extremely relevant. I’d like to think of it as actually enterprise IM.
Very simply, first of all, it’s enterprise, right? It’s looking across the entire business and being able to see across the business. It’s information, all types of information as we identify structured, unstructured documents, scanned documents, video assets, media assets.
Then it’s the management, the effective management of all of those information assets to be able to produce real business outcomes and real value for the business.
Gardner: So the more information you can manage to bring into an analytics process, the higher the return?
Santaferraro: I don’t know that it’s exactly just "more." It’s the fact that, if you look at the information worker or the person who has to make decisions on the front line, if you look at those kinds of people, the truth is that most of them need more than just data and analysis. In a lot of cases, they will need a document, a contract. They need all of those different kinds of data to give them different views to be able to make the right decision.
Gardner: Brooks, tell me a little bit about how you view IM. Is this a life cycle we’re talking about? Is it a category? Where do we draw the boundaries around IM? Is HP taking an umbrella concept here?
Esser: We really are, Dana. We think of IM as having four pillars. The first is the infrastructure, obviously -- the storage, the data warehousing, information integration that kind of ties the infrastructure together. The second piece, which is very important, is governance. That includes things like data protection, master data management, compliance, and e-discovery.
The third, to John’s point earlier, is information processes. We start talking about paper-based information, digitizing documents, and getting them into the mix. Those first three pillars taken together really form the basis of an IM environment. They’re really the pieces that allow you to get the data right.
The fourth pillar, of course, is the analytics, the insight that business leaders can get from the analytics about the information. The two, obviously, go hand in hand. Rugged information infrastructure for your analytics isn’t any better than poor infrastructure with solid analytics. Getting both pieces of that right is very, very important.
Gardner: Vickie, if we take that strong infrastructure and those strong analytics and we do it properly, are we able to take the fruits of that out to a wider audience? Let’s say we are putting these analytics into the hands of more people that can take action.
Farrell: Yes, it is very important that you do both of those things. A couple of years ago, I remember, a lot of pundits were talking about BI becoming pervasive, because tools have gotten more affordable and easier to use. Therefore anybody with a smartphone or PDA or laptop computer was going to be able to do heavy-duty analysis.
Of course, that hasn’t happened. There is more limiting the wide use of BI than the tools themselves. One of the biggest issues is the integration of the data, the quality of the data, and having a data foundation in an environment where the users can really trust it and use it to do the kind of analysis that they need to do.
What we’ve seen in the last couple of years is serious attention on investing in that data structure -- getting the data right, as we put it. It's establishing a high level of data quality, a level of trust in the data for users, so that they are able to make use of those tools and really glean from that data the insight and information that they need to better manage their business.
Esser: We can’t overemphasize that, Dana. There's a great quote by Mark Twain, of all people, who said it isn’t what you don’t know that gets you into trouble -- it’s what you know for certain that just isn’t so. That really speaks to the point Vickie made about quality of data and the importance of having high-quality data in our analytics.
Gardner: We’re defining IM fairly broadly here, but how do we then exercise what we might consider due diligence in the enterprises -- security, privacy, making the right information available to people and then making sure the wrong people don’t have it? How do you apply that important governance pillar, when we’re talking about such a large and comprehensive amount of information, Brooks?
Esser: I think you have to define governance processes, as you’re building your information infrastructure. That’s the key to everything I talked about earlier -- the pillars of a solid IM environment. One of the key ones is governance, and that talks about protecting data, quality, compliance, and the whole idea of master data management -- limiting access and making sure that right people have access to input data and that data is of high-quality.
Farrell: In fact, we recently surveyed a number of data warehouse and BI users. We found that 81 percent of them either have a formal data governance process in place or they expect to invest in one in the next 12 months. There's a lot of attention on that, as Brooks was talking about.
Gardner: Now, as we also mentioned earlier, the economy is still tough. There is less discretionary spending than we’ve had in quite some time. How do you go to folks and get the rationale for the investment to move in this direction? Is it about cost-cutting? Is it about competitiveness? Is it about getting a better return on their infrastructure investments? John, do you have a sense of how to validate the market for IM?
Santaferraro: It’s really simple. By effectively using the information they have and further leveraging the investments that they’ve already made, there is going to be significant cost savings for the business. A lot of it comes out of just having the right insight to be able to reduce costs overall. There are even efficiencies to be had in the processing of information. It can cost a lot of money to capture data, to store it, and cleanse it.
Cleansing can be up to 70 percent of the cost of the data, trying to figure out your retention strategies. All of that is very expensive. Obviously, the companies that figure out how to streamline the handling and the management of their information are going to have major cost reductions overall.
Gardner: What about the business outcomes? Brooks, do we have a sense of what companies can do with this? If they do it properly, as John pointed out, how does that further vary the profitability, their market penetration, or perhaps even their dominance?
The way to compete
Esser: Dana, it’s really becoming the way that leading edge companies compete. I’ve seen a lot of research that suggests that CEOs are becoming increasingly interested in leveraging data more effectively in their decision-making processes. It used to be fairly simple. You would simply identify your best customers, market like heck to them, and try to maximize the revenue derived from your best customers.
Now, what we’re seeing is emphasis on getting the data right and applying analytics to an entire customer base, trying to maximize revenue from a broader customer base. We’re going to talk about a few cases today where entities got the data right, they now serve their customers better, reduced cost at the same time, and increased their profitability.
Gardner: We’ve talked about this at a fairly high level. I wonder if we could get a bit more specific. I’m curious about what is the problem that IM solves that then puts us in a position to leverage the analytics, put it in the hands of the right people, and then take those actions that cut the costs and increase the business outcome. I’m going to throw this out to anybody in our panel. What are the concrete problems that IM sets out to solve?
Esser: I’ll pick that up, Dana. Organizations all over the world are struggling with an expansion of information. In some companies, you’re seeing data doubling one year over the next. It’s creating problems for the storage environment. Managers are looking at processes like de-duplication to try to reduce the quantity of information.
Lots of information is still on paper. You’ve got to somehow get that into the mix, into your decision-making process. Then you have things like RFID tags and sensors adding to the expansion of information. There are legal requirements. When you think about the fact that most documents, even instant messages, are now considered business records, you’ve got to figure a way to capture that.
Then, you’re getting pressure from business leaders for timely and accurate information to make decisions with. So, the challenge for a CIO is that you’ve got to balance the cost of IT, the cost of governance and risk issues involved in information, while at the same time, providing real insight to your business unit customer. It’s a tough job.
Santaferraro: If I could throw another one in there, Dana, I recently talked to a couple of senior IT leaders, and both of them were in the same situation. They’ve been doing BI and IM for 10-plus years in their organization. They had fairly mature processes in place, but they were concerned with trying to take the insight that they had gleaned and turn it into action.
Along with all of the things that were just described by Brooks, there are a lot of companies out there that are trying to figure out how to get the data that last mile to the person on the front line who needs to make a decision. How do I get it to them in a very simple format that tells them exactly what they need to do?
So, it’s turning that insight into action, getting it to the teller in a bank, getting it to the clerk at the point of sale, or the ATM machine, or the web portal, when somebody is logging onto a banking system or a retail site.
Along with all of that, there is this new need to find a way to get the data that last mile to where it impacts a decision. For companies, that’s fairly complex, because that could mean millions of decisions every day, as opposed to just getting a report to an executive.
That whole world of the information worker and the need to use the information has changed as well, driving the need for IM.
Analyze the data
Farrell: Dana, you asked what the challenges are, and one that we see a lot is that people need to analyze the data. They'll traipse from data mart to data mart and pull data together manually. It’s time-consuming and it’s expensive. It’s fraught with error, and the fact that you have data stored in all these different data marts, just indicates that you’re going to have redundant data that’s going to be inconsistent.
Another problem is that you’ll end up with reports from different people and different departments, and they won’t match. They will have used different calculations, different definitions for business terms. They will have used different sources for the data. There is really no consistent reconciliation of all of this data and how it gets integrated.
This causes really serious problems for companies. That’s really what IM is going to help people overcome. In some cases, it doesn’t really cost as much as you’d think, because when you do IM properly, you're actually going to see some savings and correction of some of those things that I just talked about.
Gardner: It also seems to me, if you look at a historic perspective, that many of these information workers we're talking about didn’t even try to go after this sort of analytic information. They knew that it wasn’t going to be available to them. They’d probably have to wait in line.
But, if we open the floodgates and make this information available to them, it strikes me that they are going to want to start using it in new and innovative ways. That’s a good thing, but it could also tax the infrastructure and the processes that have been developed.
How do we balance an expected increase in the proactive seeking of this information? I guess we are starting to talk about the solution to IM. If we're good at it and people want it, how do we scale it? How do we ramp it up? What about that, John? How do we start in on the scaling and the automation aspect of IM?
Santaferraro: With our customers, some of the strategy and planning that we do up front helps them define IM practices internally and create things like an enterprise information competency center where the business is aligned with IT in a way that they are actually preparing for the growth of information usage. Without that close alignment between business and IT, a tie of the IT project to real business outcomes, and that constant monitoring by that group, it could easily get out of hand. The strategy and planning upfront definitely helps out.
Farrell: I'll add to that. The more effectively you bring together the IT people and the business people and get them aligned, the better the acceptance is going to be. You certainly can mandate use of the system, but that’s really not a best practice. That’s not what you want to do.
By making the information easily accessible and relevant to the business users and showing them that they can trust that data, it’s going to be a more effective system, because they are going to be more likely to use it and not just be forced to use it.
Esser: Absolutely, Vickie. When you think about it, it really is the business units within most enterprises that fund activities via a tax or however they manage to pay for these things. Doing it right means having those stakeholders involved from the very beginning of the planning process to make sure they get what they need out of any kind of an IT project.
Has anybody got an example of how that might show up in the real world? Do we have any use cases that capture that virtuous adoption benefit?
Better customer service
Farrell: Well, one comes to mind. It’s an insurance company that we have worked with for several years. It’s a regional health insurance company faced with competition from national companies. They decided that they needed to make better use of their data to provide better services for their members, the patients as well as the providers, and also to create a more streamlined environment for themselves.
And so, to bring the IT and business users together, they developed an enterprise data warehouse that would be a common resource for all of the data. They ensured that it was accurate and they had a certain level of data quality.
They had outsourced some of the health management systems to other companies. Diabetes was outsourced to one company. Heart disease was outsourced to another company. It was expensive. By bringing it in house, they were able to save the money, but they were also able to do a better job, because they could integrate the data from one patient, and have one view of that patient.
That improved the aggregate wellness score overall for all of their patients. It enabled them to share data with the care providers, because they were confident in the quality of that data. It also saved them some administrative cost, and they recouped the investment in the first year.
Gardner: Any other examples, perhaps examples that demonstrate how IM and HP’s approach to IM come together?
Farrell: Another thing that we're doing is working with several health organizations in states in the US. We did one project several years ago and we are now in the midst of another one. The idea here is to integrate data from many different sources. This is health data from clinics, schools, hospitals, and so on throughout the state.
This enables you to do many things like run programs on childhood obesity, for example, assess the effectiveness of the program, and assess the overall cost and the return on the investment of that program. It helps to identify classes of people who need extra help, who are at risk.
Doing this gives you the opportunity to bring together and integrate in a meaningful way data from all these different sources. Once that’s been done, that can serve not only these systems, but also some of the potential systems more real-time systems that we see coming down the line, like emergency surveillance systems that would detect terrorist threat, bioterrorism threats, pandemics, and things like that.
It's important to understand and be able to get this data integrated in a meaningful way, because more real-time applications and more mission-critical applications are coming and there is not going to be the time to do the manual integration that I talked about before.
Gardner: It certainly sounds like a worthwhile thing. It sounds like the return on investment (ROI) is strong and that virtuous adoption is very powerful. So, John Santaferraro, what is that HP does that could help companies get in the IM mode?
Obviously, this is not just something you buy and drop in. It's more than just methodologies as well. What are the key ingredients, and how does HP pull them together?
Bringing information together
Santaferraro: We find that a lot of our customers have very disconnected sets of intelligence and information. So, we look at how we can bring that whole world of information together for them and provide a connected intelligence approach. We are actually a complete provider of enterprise class industry-specific IM solutions.
There are a lot of areas where we drill down and bring in our expertise. We have expertise around several business domains like customer relationship management, risk, and supply chain. We go to market with specific solutions from 13 different industries. As a complete solution provider, we provide everything from infrastructure to financing.
Obviously, HP has all of the infrastructure that a customer needs. We can package their IM solution in a single finance package that hits either CAPEX or OPEX. We've got software offerings. We've got our consulting business that comes in and helps them figure out how to do everything from the strategy that we talked about upfront and planning to the actual implementation.
We can help them break into new areas where we have practices around things like master data management or content management or e-discovery.
Across the entire IM spectrum, we have offerings that will help our customers solve whatever their problems are. I like to approach our customers and say, "Give us your most difficult and complex information challenge and we would love to put you together with people who have addressed those challenges before and with technology that’s able to help you do it and even create innovation as a business."
When we've come in and laid the IM foundation for our customers and given them a solid technology platform -- Neoview is a great example -- we find that they began to look at what they've got. It really triggers a whole lot of brand-new innovation for companies that are doing IM the right way.
Gardner: Given these vertical industries, I imagine there are some partners involved there, a specialist in specific regions as well as specific industries. Brooks, is there an ecosystem at work here as well, and how does that shape up?
Esser: Absolutely, Dana. Everyone in the IM market partners with other firms to some extent. We've chosen some strategic partners that complement our capabilities as well. For example, we team with Informatica for our data integration platform and SAP BusinessObjects and MicroStrategy for our BI platform.
We work with a company called Clearwell, and we leverage their e-discovery platform to deliver a solution that helps customers leverage the information in their corporate email systems. We work with Microsoft to deliver HP Enterprise Content Management Solution. So we really have an excellent group of go-to-market partners to leverage.
Gardner: We've talked about the context of the market, why the economy is important, and we looked at some of the imperatives from a business point of view, why this is essential to compete, what problems you need to overcome, and the solution.
So, in order to get towards this notion of a payback, it's important to know where to get started. There seem to be so many inception points, so many starting points. Let me take this to you, John. The holistic approach of being comprehensive, but at the same time, breaking this into parts that are manageable, how do you do that?
Santaferraro: One of the things that we have done is made our best practices available and accessible to our customers. We actually operationalize them. A lot of consulting companies will come and plop a big fat manual on the desk and say we have a methodology.
We've created an offering called the methodology navigator which actually walks the customers through the entire project in an interactive environment, where depending on whatever step of the project they are in, they can click on a little box that represents that step and quickly access templates, accelerators, and best practices that are directly relevant to that particular step.
We look at this holistic approach, but we also break it down into best practices that apply to every single step along the way.
Gardner: This whole thing sounds like a no-brainer to me. I don’t know whether I am overly optimistic, but I can see applying more information to your personal life, your small business as well as your department and then of course, your comprehensive enterprise.
I think we're entering into a data-driven decade. The more data, the more better decisions, the more productivity. It's how you grow. Brooks, why do you think it’s a no-brainer? Am I overstating the case?
Esser: I don’t think you are, Dana. It's how leading edge companies are going to compete, particularly in a tough and the volatile economy, as we have seen over the last 5, 7, 8 years. It's really simple. Better information about your customers can help you drive incremental revenue from your existing customer base. The cool part about it is that better information can help you prevent loss of customers that you already have. You know them better and know how to keep them satisfied.
Every marketer knows that it's a lot less expensive to keep a current customer than it is to go out and acquire a new one. So the ROI for IM projects can be phenomenal and, to your point, that makes it kind of a no-brainer.
Gardner: Vickie, we apply this to customers, we apply it to patients, payers, end-users, but are there other directions to point this at? Perhaps supply chain, perhaps thinking about cloud computing and multiple sources of finding social media metadata about processes, customers, suppliers. Are we only scratching the surface in a sense of how we apply IM?
Farrell: I think we probably are. I don’t know that there are any industries that can't make use of better organizing their data and better analyzing their data and making use of that insight that they’ve gained to make better decisions. In fact, across the board, one of the biggest issues that people have is making better decisions.
In some cases, it's providing information to humans through reports or queries, so that they can make the decisions. What we're going to be seeing -- and this gets to what you were talking about -- is that when data is coming in in real time from sensors and things like that, it has location context. It's very rich data, and it provides you with a lot of information and a lot of variables to make the best decisions based on all those variables that are taking place at that time.
Where once we were maybe developing a handful of possible scenarios and picking the closest one, we don’t have to do that anymore. We can really make use of all of that information and make the absolute best decision right then and there. I don’t really think that there are any industries or domains that can't make use of that kind of capability.
Capturing more data
Santaferraro: Dana, I love what we are doing in the oil and gas industry. We have taken the sensors from our printers, and they are some of the most sensitive sensors in the world, and we are doing a project with Shell Oil, where we are actually embedding our sensors at the tip of a drill head.
As it goes down, it's going to capture seismic data that is 100 times more accurate than anything that's been captured in the past. It's going to send it up through a thing called IntelliPipe which is a five-megabyte feed is this correct that goes up through the drill pipe and back up to the well head, where we will be capturing that in real time.
Seismic data tends to be dirty by nature. It needs to be cleansed. So, we're building a real-time cleansing engine to cleanse that data, and then we are capturing it on the back-end in our digital oil field intelligence offering. It's really fun to see as the world changes, there are all these new opportunities for collecting and using information, even in industries that tend to be a little more traditional and mechanical.
Gardner: That's a very interesting point that the more precise we get with instrumentation, the more data, the more opportunity to work with it and then to crunch that in real-time offers us the predictive aspect rather than a reactive aspect.
As I said, it's been compelling and a no-brainier for me. John, you mentioned an on ramp to this, that it's really the methodological approach. Are there any resources, are there places people can go to get more information, to start factoring where in their organization they will get their highest returns, perhaps focus there and then start working outward towards that more holistic benefit?
Let me go to you first, Brooks. Where can people go for more information?
Esser: Of course, I'm going to tell folks to talk to their HP reps. In the course of our discussion today, it's pretty obvious that IM projects are huge undertakings, and we understand that. So, we offer a group of assessment and planning services. They can help customers scope out their projects.
We have a couple of ways to get started. We can start with a business value assessment service. This is service that sets people up with a business case and tracks ROI, once they decide on a project. But, the interesting piece of that is they can choose to focus on data integration, master data management, what have you.
You look at the particular element of IM and build a project around that. This assessment service allows people to identify the element in their IM environment, their current environment, that will give them the best ROI. Or, we can offer them a master planning service which generates really comprehensive IM plan, everything from data protection and information quality to advanced analytics.
So, it's really up to the customers in terms of how they want to start out, taking a look at the element of their IM environment, or if they want us to come in and look at the entire environment, we can say, "Here's what you need to do to really transform the entire IM environment."
Obviously, you can get details on those services and our complete portfolio for that matter at www.hp.com/go/bi and www.hp.com/go/im.
Gardner: Vickie, any sense of where you would point people when they ask do I get started, where can I get more information?
Farrell: Well, I think Brooks covered it. All of our information is at www.hp.com/go/bi. We also have another site that's www.hp.com/go/neoview. There is some specific information about the Neoview Advantage enterprise data warehouse platform there.
Gardner: Very well. John Santaferraro, how about from professional services and solutions perceptive; any resources that you have in mind?
Santaferraro: Probably the hottest topic that I have heard from customers in the last year or so has been around the development of the BI competency center. Again if you go to our BI site, you will find some additional information there about the concept of a BICC.
And the other trend that I am seeing is that a lot of companies are wanting to move from just the BI space with that kind of governance. They want to create an enterprise information competency center, so expanding beyond BI to include all of IM.
We have got some great services available to help people set those up. We have customers that have been working in that kind of a governance environment for three or four years. The beautiful thing is that companies that have been doing this for three or four years are doing transformational things for their business.
They are really closely tied to business mission, vision, and objective, versus other companies that are doing a bunch of one-off projects. One customer recently had spent $11 million in a project over the last year, and they were still trying to figure out where they were going to get value out of the project.
Again, heading over to our BI website -- type in BICC, do a search -- there is some great documentation there I think that you will find to help set up some of the governance side.
Gardner: Well great. We've been talking about a natural progression towards data-driven business decisions and using IM to scale that and bring more types of data and content into play. I want to thank our guests for toady's podcast. We've been joined by Brooks Esser, Worldwide Marking Lead for Information Management Solutions at HP. Thank you, Brooks.
Esser: Thanks very much for having me, Dana.
Gardner: John Santaferraro. He is the Director of Marketing and Industry Communications for BI Solutions. Thank you, John.
Santaferraro: Thanks, Dana. Glad to be here.
Gardner: And also, Vickie Farrell, Manager of Market Strategy for BI Solutions. Thanks so much.
Farrell: Thank you, Dana. This is a pleasure.
Gardner: This is Dana Gardner, Principal Analyst at Interarbor Solutions. You’ve been listening to a sponsored BriefingsDirect podcast. Thanks for listening, and come back next time.
Listen to the podcast. Find it on iTunes/iPod and Podcast.com. Download the transcript. Learn more. Sponsor: HP.
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