Intelligent Enterprise

There are plenty of software moguls living in Santa Barbara, but after twenty years of living here, I haven't met very many. Perhaps it's because, for the first fifteen years, I wasn't here very much, or maybe it's just because I'm not a software mogul myself. So isn't it ironic that I had a very nice lunch a couple of days ago, in Santa Barbara, with one of the few software company CEO's from Santa Barbara I do know, John Patton, CEO of Sight Software. Ironic because he now lives in Hanover, NH.

Among a thousand other things we discussed was a topic that is so interesting, and so crucial these days, that I wonder why it isn't discussed more often – how do I know what needs attention? We may have access to terabytes of information and tools to help sift through it, but where do you start? There is a great deal of material in the industry about BI facilitating better decision-making, but very little about the actual process. The economist Herbert Simon, who wrote on this extensively, divided decision making into steps, starting with problem solving:

"The very first steps in the problem-solving process are the least understood. What brings (and should bring) problems to the head of the agenda? And when a problem is identified, how can it be represented in a way that facilitates its solution? The way in which problems are represented has much to do with the quality of the solutions that are found."

That is precisely what Patton has set out to do. Unlike traditional BI, where analysis is ground out repeatedly through fixed reports, or analysts are required to figure out what needs attention interactively, with no help from the application, Patton proposes to provide process intelligence by creating analytical solutions that are aware of the actual business process models. Data in dimensional models (which were originally designed for hierarchical business data, such as financial information and sales results) is not organized to provide a process view or to possess knowledge of the process elements and steps. Analysis of this data today is mostly after the fact and designed to be informative and enumerative, but not prescriptive.

As the amount of data we gather continues to escalate at a riotous pace, better ways of using it are needed. Alerts for things out of kilter or useful, autonomous robots with some degree of rule-like behavior can help and even some machine learning with rudimentary deductive reasoning are reasonable today, but how can these tools decide what should get attention? That can only come from context and knowledge. We have a long way to go there, but the first step is to find a way to filter out the extraneous information and concentrate on the useful parts. We need more intelligent software that is designed for this purpose. BI reporting tools are not. OLAP is not. Perhaps Patton is on to something, we'll see.

Neil Raden is the founder of Hired Brains, providers of consulting, research and analysis in Business Intelligence, Performance Management, real-time analytics and information/semantic integration. Neil is co-author of the just-released book "Smart Enough Systems," with business rules expert James Taylor.