Best in Class

Michael Lock, Research Analyst at Aberdeen Group, moderates an expert panel — Mary Brigden, Vice President of SAP BusinessObjects Center of Excellence, Brad Peters, CEO of Birst, and Mark Christensen, Vice President of Worldwide Sales and Marketing at Corda Technologies — around business intelligence in the enterprise and what makes a company best-in-class.

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MICHAEL LOCK: My research at Aberdeen shows that the top business pressure driving companies to invest in dashboards is the need to improve business process visibility, among other key pressures like mitigating ambiguity in decision making and moving away from spreadsheet-based processes. Does this line up with what you’re seeing from your customers, or are there other key pressures that they are responding to?

Mark Christensen: Yes, I think it does. Focusing on business performance dashboards and having the right-time insight to respond to key pressures within the organization are needed, so that cross-organizational individuals can identify strategic objectives for the company. Other drivers include: the ability to collaborate against those metrics and key performance indicators (KPIs), the ability to provide fast analysis, and the ability for a broad audience to view what’s going on. With your points, along with some of the attributes and the pressures that we’re experiencing in the market today allows for a very fast service-oriented architecture, within a performance dashboard.

Mary Brigden: I think your observation of having better visibility on business processes is really a key motivator. We’ve definitely seen that at SAP BusinessObjects; one of our strengths has been the ability to enable industry best practices in business processes and provide business process modeling capability. One of the key synergies we’ve seen with SAP BusinessObjects is being able to bring visualization to those business processes in a real-time fashion. We’re doing that in many ways, both in terms of enabling dashboards to eliminate processes and embedding visualization within products, like our ERP solution. It’s definitely a key strategy in our company and a key need from our customer base that we see across the board.

Brad Peters: I agree that is the primary business purpose. A key pressure we see in our customer base is what we term the “decision gap.” It’s the gap between the decisions that people want to make that are based on fact around business processes to operate more effectively and those which they can actually enable through technology. The challenge in the organizations that we deal with as customers is it’s a lot of work, a lot of pain, and a lot of cost to be able to make fact-based decisions, and the effort and time of implementation of very complex mechanisms to get that information out to people has created a huge gap between the processes that people want to enable (fact-based decision making) and those with which they are able to. If we can close that gap — that is a huge opportunity.

ML: In responding to the pressures that we’ve been discussing so far, one interesting piece of data that my research uncovered was that best-in-class companies had a much stronger strategic focus on the front-end user-facing piece of the business intelligence stack. Do you find that, by and large, your customers have already taken efforts to build and refine their back-end data sources and are now more focused on efforts to provide visualization for that data?

BP: The reason that companies are best-in-class is because they’ve been able to get over those issues, which really speaks to the fact that there is a big difference between correlation and causation. Those who have been able to get over the hump of the data management issue are able to then focus on (data visualization), so it’s best-inclass people who have the opportunity to do that. It’s one thing to have a pie chart on a Web page or something of the like, but getting to that pie chart is where most of our customers spend their time, effort, cost and delivery, and that is really the big inhibitor for most of these organizations. To get to best-in-class you have to get over those other hurdles. That’s really where we believe the decision gap is most fundamentally felt in organizations. They really want to get the front end and the visualization components, but if you don’t get your data there in the first place, you never really have the opportunity.

MB: I really see this as evolutionary versus revolutionary. As we all know, you can spend a lot of your time, energy and money focused on the data management side and have little pickup from a business side. As an end result, there will be very little value.

On the other hand is the more mature and more pervasive user community in the BI solutions space. I find their expectations of what they need from the data and specifications that they have for the quality of the data grows dramatically. I really can sense that when I’m working with a customer who is very sophisticated in looking at their data cleansing process and their data quality approach, how they’re going to store and standardize certain data elements. Usually the companies that do that best, when I’m in those discussions, are the business users. Initially I was taken aback by this, because I was assuming that I was going to be dealing with more of a technical audience. However, what I’ve seen from the business users is with their expectations and need to bring information into their daily decision processes; they quickly grasp and understand the concept because they consume the data. They quickly recognized when the data quality was off and they were getting bad data, and they’re doing this faster than an IT department might. It’s exciting when that starts to happen and take hold, because then you see an organization ramp up into the best-of-class environment. My experience has been that they go hand in hand, they cannot operate independently and they rarely achieve best-in-class classification either on the data management side or the visualization side without having a “yin and yang” approach.

MC: As companies start (this process) they look at the data and map in data to a strategy. Strategy is certainly important, but I also think that it’s the execution that counts. Being able to provide faster, more customizable implementations for customers and really looking at the success of how to visualize that data is what’s important. So everything from how the visualization — the dashboard, the scorecard, and so on — is designed to how it’s deployed, to how it’s maintained and eventually how accountability and responsibility ties into that. This is where customers really meet that hurdle of getting from just an “average” or “performing well” to a best-in-class type customer.

ML: You all touched on something that I study a lot, which is the notion of culture around BI. As I analyze my data, I’m continually looking for differentiating elements of a best-in-class strategy that help explain improved performance. Inevitably, a large part of the explanation for that performance comes back to organizational maturity. In this dashboards study, I found that best-in-class companies were far more likely than all other companies to have processes in place for collecting and formulating user needs, as well as formalized training programs around their dashboard tools. Outside of the technology you provide, what kinds of internal capabilities are important for users to build in order to achieve success with a dashboard implementation?

MB: I’m very much in alignment with your point of view on this. Building that culture from the beginning is something that I bring up in every engagement I have with customers because that’s where the “win” is going to be realized: When businesspeople are able to leverage the information themselves for better decision making. This is not just about the technology or the dashboards or having all of the data at your fingertips; it’s part of getting people engaged and using the data and thinking analytically. That’s much more than just a technology.

There are a number of things that I usually recommend to customers; first and foremost is intuitive solutions that are easy for them to grasp. It’s essential that your businesspeople, the people who are asking for the solution, be a part of the process. Typically, I like to advocate an approach, a “BI competency center approach,” where there are not only user requirements but simple things like agreeing on the definition of a “metric.” It never fails to amaze me, even in my own daily work, how often we are not in alignment on things such as where the data should come from, and the definition of a formula and cost of sales means different things to different parts of the organization, and it’s essential to gain consensus, alignment and agreement; otherwise, you’re still going to end up with stovepipes of information. The competency center approach or a center of excellence approach is something I’m very big on. We also have a lot of online capabilities providing training; we engage with a third party.

Another aspect to it is embracing all types of data, not being wedded to the solution. Just thinking out of the box in terms of the types of data and in terms of users that really tend to change the nature of the solution. We’ve worked with different companies, for example Disney: They were able to leverage their approach to information to revolutionize how they manage lines at an amusement park when the weather changes and do that using mobile technology and mobile devices. That came from them. We had the technology, but they had the idea of how to change their business practices as a result. Those are the sorts of things that I find recurrently important — engaging customers. We also promote a value network to our customers where they can share ideas with each other.

ML: The notion of collaboration really comes into play when you talk about BI solutions in particular. One of the things I’ve found is that best-in-class companies are typically much more likely to have something like that in place and that’s a key underpinning of their ability to achieve. Are there any other areas of organizational maturity that you guys find important for your customers?

BP: Having an organizational competency around BI is certainly critical, as well as understanding how BI or intelligence in general can be used to support decision making. The one thing that I would point out, where our more progressive customers are a little further ahead of the curve, is around the executive leadership side of how decisions and organization alignment can be driven by fact-based decision making. Oftentimes, you’ll find in organizations that people at a lower level in the organization have lots of technology processes, and they’re generating multiple reports and dashboards and the enterprise is potentially investing large sums of money in this. However, without the senior executive alignment of what exactly the information is being used for and how that’s going to change the business processes, you don’t get the mileage out of these solutions. What we’ve always focused on is helping the senior leaders in the organization understand how better decision making can transform their business. It isn’t just how fast a chart can get completed, but how are we going to use this to transform our business process?

ML: When it comes to dashboards, there are obviously a multitude of different varieties for a whole host of applications — such as executive dashboards, performance reporting dashboards and HR dashboards, among others. What struck me as interesting from the data that I collected was that best-in-class companies, while there was no specific application for their dashboard tools, have a simultaneously strategic and tactical approach to dashboards. In other words, they are more likely to use operational dashboards for “dayto- day” real-time or businesstime visibility, but they are also more likely to use performance reporting dashboards and other strategic tools to help shape their long-term strategy. Do you encourage your customers along a similar path, or do you like to see a more targeted approach to dashboard implementation?

MC: One of the things we encourage our clients to do is really take a look at what the performance dashboard is trying to do — is it a visual reporting tool that is doing little to change the organizational performance, or a powerful tool to provide insight and drive the breakthrough performance? Really, you have to look it at it almost as a design blueprint for any type of dashboard that you’re doing — whether it’s a high-level strategic, organizational or even a right-time operational one. One of the key questions to look at is, what choice of measures do you have? What are your KPI definitions going to be and then when is it the user access?

It’s really about taking a top-down approach from the executive level and working toward an execution plan that is then supported by a datadriven design; versus the reverse of that, which is looking at the data first and then trying to come up with an execution plan and then asking if it reaches the strategic goals.

ML: My data showed that by aligning the company strategy, best-inclass companies are more likely to have a hierarchal approach to how they measure things in their company. First, they have a toplevel list of performance metrics that they care about across the entire company; then they have a second tier of KPIs that they care about on a departmental level — the finance group and the operations team — which have their own metrics that tie into the toplevel metrics and feed the overall strategy. When you think about tactical versus strategic, are you seeing the same types of things?

MB: Absolutely, and I see a preponderance of tactical and strategic; in fact, how you manage that going forward is often a bit of a dilemma and something that we’ll discuss extensively with customers. There’s not one single answer and there’s certainly not one single approach. It depends on the urgency — what the long-term goals are. I will offer this: We certainly have a variety of solutions, some of which are quite fleshed out. We might have a strategy management solution, for example, but at the same time in the financial department, they might want a planning and budgeting-focused solution or a spend-analytics solution. Probably all of us (on the panel) can deliver solutions that will meet those individual solution needs, but it’s also imperative that we have a fundamental strategy in architecture that can allow those solutions to not only coexist, but to leverage each other successfully. The solutions need to enhance a single version of the truth to promote good collaboration and communication; to be cost-efficient so they don’t have the multiplicity of one-off solutions. That has been a growing priority that I’ve seen in the last couple of years. As more solutions and capability have emerged and more businesspeople have been proactive in figuring out how they’re going to solve issues, now it’s about making the most of the investments and sharing the information to allow a larger population to exploit that data and those insights.

BP: I look at it a little differently, in the sense that any organization that has fully internalized the importance of fact-based decision making is going to figure out how to use that decision making both strategically and tactically. Leaders in organizations that understand how to make that a reality understand the closer that you can push the decision to the point of action, the more powerful it’s going to be. The broader you can distribute those capabilities, the better.

One of the gaps and challenges that people have is the proliferation of different ways to approach these things, and there’s been a real Balkanization of different approaches. People have had a hard time assembling the large panoply of different tools and components to try to deliver an integrated solution, and the complexity barrier has really caused many organizations to step back and say, “We can’t really figure all of this out, so we’re just going to provide analytics to the few things we know we’re willing to spend large of sums of money on to deliver insight about.” I think there’s a real opportunity in organizations to extend that insight much more broadly.

MC: I think it’s essential for vendors, such as us, to really partner with our customers and act in a consultative role. We want to help educate them on this exact problem, which is how to determine the KPIs and the measurements of those. The Founder and CEO of Corda has created a ninestep methodology where we actually go in and consult and explain this nine-step process to frame and get the blueprint to drive the performance. It’s interesting, but I think as vendors we also have the responsibility to help educate the market and the customers that reach out to us in trying to accomplish this targeted dashboard implementation approach.

ML: All three of you have touched on something that I think is very important. You talk about the need to allow more people within the organization to participate in the analytical process and making the information more digestible and easier to understand. This comes back to the notion of pervasiveness, and this is something that I’m continually looking at in my research. The last few benchmark reports I’ve conducted have shown that best-in-class companies we’re seeing an increased level of BI adoption both across new functions within the organization — such as the operations department, customer service, or some other new department — but also more roles within each function. Do you see dashboards truly as the type of tool that can pervade into the front line areas of the organization, or do you still think they are better for IT-centric or technically savvy roles?

MC: It has to be pervasive. As you’re building and defining the blueprint for what you’re trying to do through this dashboard, through the reporting tool, you have to be able to provide the user access and the broad audience-reach and enablement that are required. One of the things that we’ve found is that as you start, even within the departmental or organizational level, if properly designed and you provide that simplicity and get a root-cause analysis to be able to make those executive decisions based on data, you’re going to find the pervasiveness grows out from this. It’s really going to catch on and we’ve seen that in several instances.

MB: I would offer that dashboards are a wonderful way to allow pervasiveness. They are intuitive, they’re easy to use, and don’t require training. If they’re well done, anyone can interact with them. They tend to serve specific purposes, but they’re very elegant at getting things done quickly and efficiently. I don’t think it’s the only way to promote pervasiveness and I don’t think it will be your only tool. If you want to do more in-depth analysis or text analysis or highvolumes of data, many of those things will drive you to other options. What I have seen is that is really colorful. An example of an area that is really allowing us to take the next leap in pervasive use of software is a solution that we call Explorer, which we rolled out this spring, and it’s been tremendously exciting because it allows people to look at all sorts of data and it does a lot of the transformation and visualization for you; it intuits the data that it’s looking at. It’s kind of a combination between a Google interface and a visualization tool. There’s new technologies coming that will continue to drive that pervasiveness to the forefront, but I’m in 100 percent agreement that it is empowering all users — that’s the Holy Grail. That is where the opportunity to make better decisions is when really anyone can access it and create insight and make a better decision.

BP: We found with our customers, like Royal Bank in Canada, that the closer you can push decision making to the actual point of action the more powerful “the eye” — or your analysis and decision making — can be. It’s one thing to report on a bad decision after the fact, it’s an entirely different thing to enable the person who’s about to make the decision to make it based on fact and insight and synthesized information so that they can do it in the most effective way possible. RBC for example is actually empowering an entire front-line organization to interact with their clients and customers to have a complete view of that entire customer relationship. When they actually have a conversation on the phone or in person, they have all of the information there, and it’s structured in such a way that the highestpriority items are available. The ability enables the frontline employees, and there’s training to go along with this to make those decisions, rather than what has historically been done, where a manager sits behind an employee and discusses decisions made after the fact. That’s effective and helpful but it doesn’t prevent the problems in the first place. The real benefit in using intelligence is driving the point of interaction where you can get the most leverage.