Business models sometimes meet resistance from managers who are not convinced of their utility. Some people don't “get” models like the ACORD Framework's Information Model because they're not clear on the distinction between facts and data. In the most worrying cases, managers mistake the data they happen to have for the facts they really need. Luck and momentum can combine to keep organizations moving along profitably on this basis. Sooner or later, however, the shaky factual basis of their activity leads to failure.
Other people are wary of models because models can look rigid and static. At first sight, any structure that claims to describe a piece of business will look like it's trying to set something fluid in stone. To describe, for many people, is to destroy. They believe that anything we say with certainty today will be wrong tomorrow.
I empathise with this attitude. But there is an inherent danger in adopting any model – the danger of freezing the business to one version of the model. I can also see that doing so could be seen as a worse error than using no model. If you're not using a model, you stand a chance of succeeding despite having a loose grasp on the facts. If you use a model that's perpetually drifting into error – becoming the wrong model – then you lay your self open to much more culpable failure.
The solution to this dilemma is to rethink what a model has to be. The downsides of models that we've just looked at are all implications of a static, once-and-for-all conception of modelling. But models don't have to be like that. They can evolve too. In the next and part of this series, I'll look at how model evolution can be managed.