Why does analytics need to be demystified? And what has prevented the advanced analytics market from growing to the size of the general BI market?

Doug Henschen, Executive Editor, Enterprise Apps

April 5, 2010

3 Min Read

This week, Intelligent Enterprise is launching "Advantage in Analytics," a TechCenter that explores what has become a very hyped business intelligence discipline and technology subset. There's good reason for all the hype: analytics can help you predict customer needs and wants, changing market conditions, system outages or equipment failures, winning pricing strategies. You name the business scenario; advanced analytic techniques can likely be applied to make better, preemptive decisions rather than reacting to unanticipated problems or failures later.

Why does analytics need to be demystified? Well, for one thing, vendors are throwing the term around wherever and whenever possible, with the references tending to fall into three categories:Web-, text- and data-analytics Marketing analytics and customer relationship management (CRM) analytics Enterprise operations-, process- and performance-analytics .It's not that one of these camps doesn't have a legitimate claim to the term. But the style of analytics we'll explore in our tech center -- and the type that many organizations are most interested in today -- is predictive and statistical analytics (the form most associated with operations-, process- and performance-analytics).

SAS, the largest provider of what Gartner and IDC call "advanced analytics," draws a simpler distinction between the styles of analytics. "Every vendor out there seems to have an analytic offering, but to us, there are two broad categories," says Jim Davis, senior vice president and chief marketing officer. "One supports reactive decision-making, while the second supports proactive decision-making."

Summary statistics, query and reporting on various rows and columns, and alerts and thresholds look at past data and are in the first camp, says Davis. Things like forecasting, predictive modeling and operations research that can be used for optimization are in the second camp.

What has prevented the advanced analytics market from growing to the size of the general BI market? That question has been raised in a number of articles appearing on Intelligent Enterprise in recent months (like this interview with Tom Davenport and this article on analytics education).

There's much more to come on this topic in our TechCenter. For now, suffice it to say that the small size of the analytics market -- about a quarter the size of the total query/analysis/reporting BI market, according to industry figures -- is much more about lack of awareness, skills and a demand for fact-based decision-making within organization. The technology -- whether from SAS, IBM SPSS, KXEN, the growing R community or any number of others on the growing list of vendors -- has not really been the obstacle.

Stay tuned to our TechCenter for more, starting with "Advanced Analytics: Seven Steps Toward Adoption," a free, 16-page Strategy Session report downloadable from the Tech Center. Enjoy and please comment on what you'd like to see in our Advantage in Analytics TechCenter coverage.Why does analytics need to be demystified? And what has prevented the advanced analytics market from growing to the size of the general BI market?

About the Author(s)

Doug Henschen

Executive Editor, Enterprise Apps

Doug Henschen is Executive Editor of InformationWeek, where he covers the intersection of enterprise applications with information management, business intelligence, big data and analytics. He previously served as editor in chief of Intelligent Enterprise, editor in chief of Transform Magazine, and Executive Editor at DM News. He has covered IT and data-driven marketing for more than 15 years.

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