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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.


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
View image
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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