Model Dogma - The Map is NOT the Territory

I'm taking an online project management course right now. While it's pretty good, I simultaneously find the standards surprisingly low while some of the test questions range from plain stupid, to very challenging to irrelevant or even wrong. By that I mean, some of the answers are both possible and reasonable options in the REAL world but were marked wrong on the multiple choice tests.

Here's the gist:

Q: As a project manager, how could you assure that a SMART goal was attainable within the set timeline?

A: Ask relevant stakeholders. Was it wrong?

And yet the remaining options were so vague as to be almost irrelevant to the question:-?

All models are wrong, but some are more accurate.

This was the inspiration for this article, and reminiscent of my Nothing is Everything Article.

George Box, a statistician brilliantly said " All models are wrong, but some are useful." and he's right. And the more famous " The map is not the territory " Both make the same point, a model is a pale imitation of reality. Maps and models are very useful and convenient, but once you start forcing reality, and your processes to comply with the simplified analogie of reality, you've probably gone astray.

Back in the real world, if I was managing a project, or working with a client to improve a business process, I'd be an arrogant idiot to think that I knew better than a software engineer how long it will take to program ANYTHING.

Other than looking at historical data of similar tasks, I'd have no way of judging how long the programming would take. Even then, I know about as much about programming as a software engineer is likely to know about the electro-physiology of a neuron. I'm not qualified to judge if that data is equivalent:-? I therefore REJECT, asking a subject matter expert as an incorrect answer in said " test ".

Models and system frameworks are useful generalized GUIDES, but never forget that they're merely convenient reality wannabes. Drive the model until it's wheels fall off by all means, but then hold solutions up to the harsh light of reality, common sense and empirical testing aka science to produce the best possible results.

tim #bgreen??

P.S. How Do You Assure That Your Processes Match REALITY, Rather Than an Inevitably Oversimplified Model of It ?

P.P.S. My Next Article: Track Results Not Data...