Since “business analytics” has come into vogue, like all newly popular technologies, everyone is talking about it but few are defining what it is. In his inaugural article for the B-EYE-NETWORK, “Today’s ‘Analytic Applications’ — Misnamed and Mistargeted”, Merv Adrian argues that “analytic applications ought to be defined as those which use analysis to deliver business functionality.” He goes on to say that “the promise of the future is truly analytic business applications, software packages that execute automated business processes with and/or without human intervention, based on policies, rules and real-time analytic results.” Although Adrian never defines the terms “analysis” or “analytics” in his article, it is clear that he defines them differently than I do. As I define “analysis,” saying that a computer could do it “without human intervention” makes no sense.
I believe that data analysis is what we do to make sense of data. I could add a few more words around this basic definition to elaborate a bit, but essentially data analysis is the process of sense-making. It’s what we do with information to understand what it means. It’s the process that bridges the gap between information and knowledge. It’s what we do if we want to make informed decisions, based on evidence. Oh yeah, and when applied to business, it’s the heart and soul of business intelligence.
When software automates actions that are carried out in response to rules, it isn’t engaged in analytics or decision-making. Rather, it is simply enforcing a decision that has already been made, based on prior analysis-analysis that was done by a human. The automation of routine responses to specified conditions is a great use of technology, but let’s not confuse this with analysis. Doing so might give people the false impression that by automating such actions, they are addressing their organization’s vital need to understand its data.
I believe that Adrian’s vision of our analytical future involves something that computer applications have been doing for us all along. Software programs instruct computers to do particular things based on particular conditions. This is what all applications do and have always done. Business applications perform actions based on business rules. We shouldn’t confuse this with a process that involves the careful exploration and examination of information to make sense of it-that is, data analysis. The two are fundamentally different. The enforcement of rules is a procedural process that computers excel at performing. Thinking isn’t required.
Data analysis, on the other hand, requires thinking. The only computers that think are those that we read about in science fiction. Until this changes, if it ever does, data analysis will remain a human activity. Computers can support the process by giving us tools that support and augment our ability to think, but they can’t think for us.
Adrian apparently shares my opinion that the business intelligence industry has failed to deliver on its fundamental promise. But, just as he and I define “analysis” differently, we also understand the nature of this failure and its solution differently. If the business intelligence industry continues down its well-worn path of expecting technology to solve problems that are essentially human problems, without taking the time to understand human needs, abilities, and limitations, it will continue to fail in its primary mission.
Why do so few in the business intelligence industry understand this? Perhaps their analysis is faulty. Perhaps they’re coming at it from the wrong perspective.