Good Data, Bad Decisions

Barnaby S. Donlon in the BI Review (http://www.bireview.com/bnews/10000989-1.html) gives a good description of how data goes to information, to knowledge, and then to decisions. He's saying all the right things, and all the things I've been hearing for years, but you know -- I don't think it works anything like that.

When we start with the data, it's all too much. It's too easy to generate endless ideas, endless leads, endless stories. I've seen it happen when an organization suddenly gets analytic capability.

Before, the organization was very limited in it's abilities to make decisions because they had limited information. The organizational leaders have ideas, and because of the lack of information they have no way of deciding what is a good idea or a bad idea. After the organization starts an analytic department, then suddenly every idea that the leadership gets can be investigated. The paradoxical result is that the leadership still can't make informed decisions. Every idea generates an analysis, and virtually every analysis can generate some kind of results. Without data, the result is inertia; with too much data the result is tail-chasing.

The right way to do this is to begin with the end. Think about the decisions that need to be made. Then think about how to make those decisions in the best possible way. Starting with the end means the beginning -- the data, the analysis, the information -- is focused and effective.