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Busting the Myths in Business Intelligence

By SiliconIndia   |   Thursday, 31 May 2012, 07:11 Hrs
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Bangalore: It is frequently claimed that what is done in BI classifies as decision support rather than business intelligence. In essence, BI tools support decision making; to attribute intelligence to business or software is misleading.  There is another problem with business intelligence, it implies a level of rationality in decision making, which is not always true in the real world.  This implication is carried even further when various analysts and vendors begin to talk about business analytics as the best solution for all business decision-making needs.

The current fixation on analytics is dangerous.  It's based on several misconceived notions and errors.  It is a simplification that business is a fact-driven process rooted in rationality.  It is a misconception that you can predict the future if you are given accurate data.  It is a downright error to assume that in the future, business can be entirely driven by analytics.

This does not mean that we should abandon analytics.  If business users can avoid statistical errors such as confusing correspondence with causality then they can use data to gain insight.  There are many examples of businesses that adopt analytics and increase revenues.



Putting rational and logical intelligence in the spotlight blurs two other keys aspects of decision maker: Intent and intuition; Intent is ignored and intuition is dismissed.  The intention is what drives everything from the kind of data gathered, its evaluation, and the final choice of action. Many business decisions are not driven by measurable or predictable metrics, but by intuition.  Low prices may be important, but so are ambience and history when customers decide where they would like to shop. Factors like history and personal relationships cannot be accurately defined and quantified. The intuition of an experienced manager is necessary in such cases. 



According to a story in the New York Times, Target's decision to focus on marketing of maternity products to women in the early stages of pregnancy was based on sound analytics, but the reaction of prospective customers was intuitively obvious.

To focus exclusively on big data and analytics is very risky.  There is a need to move beyond traditional concepts of business intelligence and decision support so we can view the full spectrum of business insight.


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