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Wayne Eckerson

Welcome to Wayne's World, my blog that illuminates the latest thinking about how to deliver insights from business data and celebrates out-of-the-box thinkers and doers in the business intelligence (BI), performance management and data warehousing (DW) fields. Tune in here if you want to keep abreast of the latest trends, techniques, and technologies in this dynamic industry.

About the author >

Wayne has been a thought leader in the business intelligence field since the early 1990s. He has conducted numerous research studies and is a noted speaker, blogger, and consultant. He is the author of two widely read books: Performance Dashboards: Measuring, Monitoring, and Managing Your Business (2005, 2010) and The Secrets of Analytical Leaders: Insights from Information Insiders (2012).

Wayne is founder and principal consultant at Eckerson Group,a research and consulting company focused on business intelligence, analytics and big data.

Recently in Business Performance Management Category

(Note: This is an excerpt from the opening section of the "Dashboard Verdict," a compendium of dashboard product reviews that I'm writing for the Business Applications Research Center (BARC), a German research firm that does in-depth evaluations of business intelligence products. To be notified when the dashboard reviews are available for purchase, register at www.bileadership.com/mailing-list-form.html.) To view and subscribe to BARC research, go to www.bi-verdict.com.)

One way to differentiate dashboard products is to position them within the MAD framework that I devised several years ago. MAD stands for Monitor, Analyze, and Drill to detail and is represented by a pyramid divided into three sections. The shape of the pyramid represents the amount of data at each level.

A well-designed MAD dashboard consists of about 10 metrics at the top level, 100 metrics at the analysis layer, and 1,000 metrics at the detail layer. The top-ten metrics are filtered by about 20 dimensions, which generate the lower-level views and metrics. In essence, a performance dashboard is an interactive, information sandbox that is big enough to answer 60% to 80% of questions that users might want to ask about their performance objectives, but not so big that they get lost in the data. (See figure 1.)

The monitoring layer consists of graphical metrics (e.g., charts, stoplights, gauges, etc.) tailored to an individual's role. With a quick glance, users can see if everything is going according to plan. If something is awry, they can drill to the analysis layer and perform root cause analysis by slicing and dicing data dimensionally or applying a variety of filters. If they need transaction data to resolve the issue or they want more context about the issue, they can drill into detailed data, which might be stored in the data warehouse, an operational system, or a detailed report. MAD dashboards focus users on key metrics aligned with strategic objectives and provide access to any data they need in three clicks or less.

Five years ago when organizations built custom dashboards, they stitched together multiple tools to implement the MAD framework. Typically, they used portal software for the monitoring layer, an OLAP tool for the analysis layer, and a reporting tool for the detail layer. Today, although there are many so-called dashboard products on the market, very few support the entire framework in a seamless fashion. Most support only one of the three layers.

Figure 1. BI Products Applied to the MAD Framework (Click to expand)
7-27-2011 1-09-24 PM.jpg

For example, dashboard tools, such as Domo CenterView, SAP BusinessObjects Dashboards, and iDashboards primarily support the monitoring layer. Analysis tools, such as Tableau, QlikView, and Information Builder's Visual Discovery primarily support the analysis layer. And reporting tools, such as Microsoft SQL Server Reporting Services and SAP BusinessIntelligence Web Intelligence, only support the detail layer. Only enterprise BI platforms, such as those sold by SAP and Information Builders, and ROLAP tools, such as those from MicroStrategy and Oracle, offer tools that encompass the entire MAD stack. (Note: many BI platforms consist of lightly or non-integrated product modules that don't always deliver a seamless experience as users traverse the three layers of the MAD framework.

(The rest of this section in the soon-to-be-published BARC report uses scalability, architecture, price/performance as ways to differentiate dashboard products.)

Posted July 27, 2011 11:17 AM
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The purpose of business intelligence (BI) is to help organizations use information to make smart decisions. At a strategic level, BI is about making a business more intelligent. At a tactical level, it's about reporting and analysis.

BI professionals know better than anyone else that semantics are fickle. What's a customer? What's a sale? What's a product? Executives can wrangle for months before they agree on an exact definition of these household terms. And the same holds true for semantics within BI.

There has been a long succession of terms used to describe the reporting/analysis domain. (See figure 1.) Every decade, vendors with new technologies and experts with new theories conspire to create a new term to reinvigorate their products, ideas, and the field in general. Each new term creates a wave of hype and expectation, followed by some disenchantment as the organizations confront the harsh realities of implementing the BI flavor-of-the-day.

Figure 1. Evolution of BI Semantics
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Next week, I'll fill in the bottom half of this diagram and discuss trends in the BI vendor community.

1980s: Decision Support. Back in the 1980s, the industry's favored term was "decision support." But most "decision support" applications were custom built with hand code and cost a small fortune. This approach clearly didn't scale and couldn't support the aspirations of an emerging industry, and so the term eventually faded away.

1990s: Data Warehousing. In the early 1990s, Barry Devlin, Bill Inmon, and Ralph Kimball began writing about a new approach to reporting and analysis called "data warehousing" and the theory and term caught on. For the rest of the decade, IT professionals focused on getting data out of operational systems and into repositories optimized for query processing. But after the heavy lifting was done, IT professionals realized that simply building a data warehouse didn't guarantee that business people would use it.

2000s: Business Intelligence. So, in the early 2000s, IT professionals began focusing on making it easier for business users to access the data warehouse. They purchased desktop- and Web-based reporting and analysis tools and started talking about tools to make the business more intelligent. Soon, the term "business intelligence" became the industry watchword. (Note: I still use "business intelligence" to describe the entirety of the reporting/analysis domain because I believe it does the best job of describing the business purpose and value it has to offer.)

However, people quickly recognized that simply giving tools to business users doesn't guarantee that they'll use them or, if they do, find anything useful or act on what they've discovered. Soon, BI became shorthand for unwieldy reporting and analysis tools that often became expensive shelfware.

2005-2010: Performance Management. By the mid 2000s, the term business intelligence gave way to a new semantic upstart that focused on business outcomes. "Performance management" uses dashboards, scorecards, and planning tools align strategy with action and optimize performance at all levels of the organization. But executives soon recognized that defining metrics and targets that embody key objectives and goals is a top-down, slow-moving endeavor that is often subject to the vicissitudes of politics and bureaucracy.

2010s+: Analytics. Today, at the beginning of a new decade, a new term has emerged that emphasizes speed and agility and calls on organizations to move beyond monitoring performance to driving it. That term is "analytics."

Analytics initially referred to advanced statistical modeling using tools like SAS and SPSS. It gained preeminence thanks to an influential book written by Tom Davenport and Jeanne Harris titled "Competing on Analytics." Then, IBM began touting the power of analytics in television and magazine ads about the "Smarter Planet." Now, analytics refers to the entire domain of leveraging information to make smarter decisions. In other words, reporting and analysis.

2015+? In the future, perhaps we'll complete the circle and call our domain "decision support" once again. But whatever the term, the value is undeniable and enduring: using information to make better decisions is perhaps the last great frontier of sustainable competitive advantage.

Posted February 22, 2011 7:07 AM
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I had the pleasure this week of talking about performance dashboards and analytics to more than 100 CFOs and financial managers at CFO Magazine's Corporate Performance Management Conference in New York City. They were a terrific audience: highly engaged with great questions and many were taking copious notes. Many were from mid-size companies. The dashboard topic was so popular that the event organizers scheduled a second three-hour workshop to accommodate demand.

I normally talk about business intelligence (BI) to IT audiences, so it was refreshing to address a business audience. Not surprisingly, they came at the topic from a slightly different perspective. Here's a sample of what they were thinking about:

  • Scorecards. The CFOs were more interested in scorecards than I anticipated. Since there are entire conferences devoted to scorecards (e.g. Palladium and the Balanced Scorecard Collaborative), which have largely attracted a financial audience, I thought that this would be old news to them. But I was wrong. They were particularly interested in how to cascade metrics throughout an organization and across scorecard environments.
  • Metrics. Not surprisingly, many found it challenging to create metrics in the first place. Most found that "the business" couldn't decide what it wanted or achieve consensus among various departmental heads. We talked about the challenges of "top-down" metrics-driven BI versus bottom-up ad hoc BI, and the tradeoffs of each approach.
  • The "Business." Since I've always considered finance to be part of the "business" it was surprising to hear finance refer to the "business" as a group separate from them. But, then it dawned on me that finance, like IT, is a shared service that is desperately trying to move from the back-office to the front-office and deliver more value to the business. Many CFOs in the audience have astutely recognized that providing consistent information and metrics via a dashboard is a great way to add value.
  • Project Management. The CFOs didn't have much perspective on how to organize a dashboard project. They didn't realize that you need a steering committee (e.g. sponsors), KPI team (e.g., subject matter experts plus one IT person) and a development team, and that the team doesn't disband after the project ends (i.e. project versus program management.)
  • Two to Tango. They also seemed to recognize that the business is the primary reason for failed BI projects not the IT team. If the business says it wants a new dashboard but the sponsor doesn't devote enough time to see the project through or free up the time of key subject matter experts to work with the BI team, the project can't succeed. Performance dashboards must be business owned and business-driven to succeed.
  • Requirements. Many CFOs also didn't realize that you need to development requirements (i.e., define metrics) before purchasing a tool. They admit that many projects they've been involved in have put the "cart before the horse" so to speak.
  • Technology. Not surprisingly, the CFOs had little understanding of the tools and architecture required to drive various types of dashboards. I don't talk much about dashboard technology and architectures to IT audiences because they know most of it already. But it's all new to the business, even basic things like how the data gets into a dashboard screen.
  • Build Once, Deploy Many Times. Perhaps the biggest revelation for many business people was the notion that you build a dashboard once and configure the views based on user roles and permissions. They didn't understand that one dashboard could consist of separate and distinct views for sales, marketing, finance, etc. and that within each of those views, the data could vary based on your level in the organization and permissions.
  • Change Management. Most recognized change management as a huge issue. Most had experienced internal resistance to new performance measurements and were eager to share stories and swap ideas for ensuring adoption.

What I Learned

I learned a few things, too. First, three hours is not enough time to address all the topics that business people need to learn to have a working knowledge of performance dashboards. Thankfully, I covered the most important topics in my book, "Performance Dashboards: Measuring, Monitoring, and Managing Your Business" which just came out in its second edition.

Second, I realized I have a lot to offer a business audience. Although I've been addressing IT audiences for the past 22 years, the way I present information resonates better with a business audience. It's not that I avoid technical issues; rather, I place technology in a business and process context and provide pragmatic examples and advice so people can apply the information back in the office.

Hopefully, I'll be delivering more business-oriented presentations in the coming months and years!

Posted February 2, 2011 11:23 AM
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This is my first week as a director of research at TechTarget. I've been asked by quite a few folks why I made the move. The answer is simple: I believe TechTarget is best positioned to help me take my coverage of business intelligence to the next level.

TechTarget's business model is geared to "targeting" high growth segments in the information technology industry. It supports these markets with dedicated, content-rich Web sites that serve up news, expert opinion, and "how to" advice. Several years ago, it started SearchDataManagement.com to target the data warehousing and data integration markets, and earlier this year, it launched SearchBusinessAnalytics.com to create a community around business intelligence and analytics. Six months ago, it purchased BeyeNetwork to add a community of experts and thought leaders to its BI portfolio.

I've been associated with the BI industry since 1995 and have watched it grow from infancy to adulthood. Today, it's clear that BI has gone mainstream. (As evidence, see the article about BI published last week in USA Today.) As I look in my crystal ball, I believe the future growth for education, training, and information about BI will occur in niche or micro-markets, that is the "long tail" of BI. Increasingly, BI professionals want to learn about BI in the context of their vertical industry or functional department. Also, there is already sizable interest in BI within the small-and-medium sized business (SMB) market, and I expect significant growth in less developed regions around the world (e.g. China, Eastern Europe, Latin and South America.) I believe TechTarget is best positioned to nurture and capitalize on the growth in these niche segments.

TechTarget took a first step in this direction earlier this year with its purchase of BeyeNetwork, which was founded in 2005 by Ron Powell. Back then, Ron's vision was to deliver BI content largely through vertical channels. Looking back, it's clear that Ron was ahead of his time. The good news is that the market is ready for BI verticalization. Ron has put together a strong framework to pursue this strategy, and I'm eager to help him realize his vision.

I'm also eager to join TechTarget because they are giving me the opportunity to offer consulting services to user and vendor organizations through my own company, BI Leader Consulting. (The Web site, www.bileader.com, will be up and running soon.) I believe that any respectable BI thought leader needs to spend time working in the trenches with users to truly understand the challenges facing BI professionals. Although I've performed consulting work in the past, this new arrangement gives me the opportunity to do so more consistently.

I applaud TechTarget's flexibility, and whether they know it or not, my consulting work will play to their advantage. TechTarget is a highly disciplined media company that focuses on delivering high quality and objective content to its online communities. Armed with insights from my hands-on work, I'll contribute more insightful content valued by TechTarget readers than I would locked up in an ivory research tower. Let the fun begin!

Posted November 20, 2010 1:21 PM
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