On the true nature of business intelligence

The expression ‘business intelligence’ is in common use. What does it mean, exactly? The definitions vary, seeming to cluster around the central concept of the use of advanced databases and reporting tools to support business decision making.

But there seems to be a lot more going on in the term. I think it will be illuminating to drill into it to try to get at the true nature of business intelligence.

On reflection there are two key ideas woven together in the expression. The first is the idea of intelligence itself. The second is the idea that a business can be intelligent. So we’ll proceed by defining intelligence. Then we’ll look at how a business could be intelligent. We’ll project our definitions of intelligence into our understanding of how a business could be intelligent. And last we’ll compare that to the commonly understood meaning, and see if we’ve discovered anything interesting on the way about how a business might pursue increasing its intelligence.

Steven Pinker has a useful working definition of intelligence in his book ‘How the Mind Works.’ (I have loaned my copy to my daughter Zooey. When I get it back from her, I’ll fix this up with more specific detail After an interesting discussion featuring a definition of ‘what makes a good alien’ from science fiction, and a nice quote from Shakespeare about Romeo’s pursuit of Juliet, Pinker ends up with a working definition: “Intelligence, then, is the ability to attain goals in the face of obstacles by means of decisions based on rational (truth-obeying) rules.” Intelligence is ability for an entity to continue to strive toward a goal in the presence of obtacles by the logical creation and pursuit of new subgoals.

There is another useful definition of intelligence we can infer from Daniel C Dennett’s ‘Conciousness Explained’: intelligence is the honed-by-evolution ability to produce future. The better we are at foretelling the immediate future, the better our chance of survival. Intelligence is the innate ability to foretell the future not by some kind of precognition, but by an understanding of the present and the rules the world obeys.

When we say ‘business intelligence’ do we mean real intelligence, or are we simply using an anthropomorphical metaphor? I believe the former.

In our – software architects and engineers – best practice common data model, a person and a business are the same base entity, usually called ‘party’ as captured by Martin Fowler. A party can enter into agreements, legal and otherwise. A party is accountable for its actions because they could choose to do otherwise. In this model, persons and businesses are subtypes of party.

From another perspective, I believe that identity is best understood as a narrative. This is an idea I first came across in the philosopher Paul Ricoeur’s ‘Time and Narrative,’ and, later, again in Dennett op cit (with no citation of Ricoeur) where he describes identity as ‘the center of narrative gravity.’ I believe this idea of narrative identity has a lot of weight and explanatory power for software, which I’ll go into in another rumination. For now, consider that a business, like a person, has an identity: a beginning, a story with a theme and a plot, an end.

So I think when we speak of a business as being intelligent, it is more than a metaphor. Then the real question of business intelligence is this one: how does a business become smarter?

Our first working definition of intelligence is about logically changing plans in the face of obstacles in order to meet our ultimate goals. In business terms, this means having the ability to quickly change our processes in the face of obstacles in order to continue to meet our objectives. Those companies flourish, they are more intelligent, which empower their people to dynamically change their processes when faced with an obstacle. Having front line people, customer facing people, have the latitude to solve problems creatively is well understood to be a powerful enabler of business success. Now we know why – it’s intelligent.

The risk of rapid process change is that we might violate some constraint. Our constraints may be understood with respect to the speed with which they change: the laws of physics, laws, contracts, and regulations are all constraints that change at different speeds. (The laws of physics maybe right after the big bang – though we are starting to look bang-less.)

So to foster and support rapid process change in order to enable us to work around obstacles, we need an environment where the arena of process change is defined by our constraints.

This might be an adaptation of contract modeling software, which might be generalized to model all constraints, used in conjunction with a BPEL engine and process modeler. The business uses the graphical BPMN modeler to modify their processes. They are prevented by the tool from doing so in a way that would violate a law of physics (too much stuff in one truck, for example), law, contract, or other constraint.

Our other definition of intelligence, future producing, seems more what underlies the conventional definition of BI. We analyze data to understand the present, and use it to make forecasts about the future. In my previous post ‘On Reporting‘ I described what tools a business needs to do this well.

Our richer definition of business intelligence has shown us how a business can become smarter: first, by creating an environment to foster the rapid, safe change of processes in the face of obstacles; second, by polishing their crystal balls.