In an article entitled “The Changing Face of Business Intelligence,” last month Dave Wells eloquently described how the business intelligence industry has strayed from its original vision and how it is now changing to recover what’s been lost. A longtime veteran of data warehousing and business intelligence, Wells is one of the leaders in the industry who have shaken free of the technology-centric perspective that holds the industry back.
Wells begins by reminding us of Howard Dresner’s original vision when he coined the term “business intelligence” (BI) in the early 1990s. Dresner defined BI as “a set of concepts and methodologies to improve decision making in business through use of facts and fact-based systems.” Over the years, the industry that took hold of Dresner’s visionary term (mostly data warehousing vendors at the time) buried the goal of decision making in an emphasis on technology. As Wells says: “The troubling thing is that all of the definitions are IT-centric” and “too much of today’s business analytics has little connection with real business analysis.”
He goes on to offer a new definition of business intelligence, which recaptures the essence of the original and enhances it to further clarify the goals. I don’t want to give too much away by quoting his definition here; you should read Wells’ words directly. I do want to include one more quote, however, which is central to Well’s vision of BI’s transformation:
It is analysts – the people who perform analysis – who find meaning in the data. These are the people who explore cause-effect relationships and who guide decision-making processes. It is they who will lead the charge to reshape decision making in business.
To recover the original vision, the business intelligence industry must shift from an emphasis on technology to an emphasis on the people who use the technology. Only then will it begin to fulfill its original promise.
(Note: While I consider Wells’ argument brilliant, I believe that some of the software products that he lists as examples of “next generation of analytics” don’t belong there. In fact, I believe that some of the products on the list exemplify little understanding of and support for data analysis. This difference of opinion suggests that our common vision must become informed by clear definitions of data analysis and analytics and clear criteria for assessing products’ ability to deliver. All in good time.)