I had to chuckle at Doug Henschen’s blog on the confusing terminology on business intelligence and performance management. We in IT seem to use whatever term will generate the most buzz and to heck with whatever confusion ensues. “Analytics” is yet another term in which vendors use it to mean different things, and we all interpret it differently.
In a recent conversation with SAS, we seemed to be talking at cross purposes. SAS kept using the term “analytics” when really what they were referring to was predictive analytics. My incorrect interpretation was that they were talking about general data analysis. Given that predictive analytics is one of SAS biggest differentiators, misinterpretation is not good, kind of like a genericized trademark.
In Competing on Analytics, authors Tom Davenport and Jeanne Harris define analytics as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” At a cursory glance, that sounds similar to business intelligence, but the words “statistical” and “predictive models” are what differentiate analytics from broader business intelligence. The authors clarify that business intelligence encompasses analytics but it is a unique—and frequently missing—component.
And yet, analytics as a term is used loosely throughout the industry. For example, I recently got an email from Applix (just acquired by Cognos) touting business analytics as a way of enabling businesses to be more agile, and yet, they are selling a performance management solution. Information Builders touts their Active Reports as portable analytics; they are highly interactive reports, but they are not predictive. When I was with Deloitte & Touche, we struggled to brand our consulting services (data warehousing sounded too technical) and ultimately chose “decision analytics,” thinking it had more business appeal.
You would think that qualifying “analytics” as predictive would ensure clarity, and yet, it doesn’t. One vendor claims they can do predictive analytics because they can do moving averages. No models. No Chi-square. Just a simple, moving average.
For my own clarity, predictive analytics means forward looking and must include applying a model to maximize an outcome or predict the future. Analytics (without the predictive) could be potentially anything else in the BI spectrum, so when in doubt, clarify.
Now that we are clear on terminology, let's also be clear on the increasing interest in predictive analytics: for the third session running, predictive analytics was the highest voted wild card demo topic at last week's TDWI BI bake off. Do all BI suite vendors have predictive analytic capabilities? No.
Cindi Howson, Founder, BIScorecard, a web-site for in-depth BI product reviews