Friday, January 19, 2007

Time horizons, step two

Yesterday, I posted about time horizons in problem solving. Step one was to expand your time horizon when looking at problems to ensure you see potential patterns of problems.

What should you do if you do identify that your problem is part of a pattern?

Step two is to figure out what might be causing that pattern. Often, it's something structural in the organization. In the example I gave, the organization inadvertently hid certain key financial information from managers, and that led to repeated bouts of overspending.

How do you figure out what structural issues might be causing the pattern you're seeing? Sometimes it's obvious; sometimes there are multiple, competing explanations, and you're not sure which is most likely.

One way to pick the right explanation is to do an experiment. Try making the structural changes that you think matter, and see what happens. If you observe no change (or if you make things worse), you probably picked the wrong explanation. If the problem disappears, you probably picked the right explanation.

Of course, patterns play out over (a long) time, and so it may take you a while to be sure whether you've seen a change or not. (If you do see an improvement in a bad situation, be sure you're not just seeing regression to the mean.)

Since you're making structural changes to the organization, you may find your experiments are costly in financial and material resources, in risk to the organization if you select poorly, and in human patience.

Is there a better way?


What if you could create a mockup or simulation of your problem? What if that simulation could recreate the essence of your problem in a simpler form (a model), and you could conduct experiments on the model rather than on the real organization? What if you could take the lessons from that exercise and apply them to your real-world problem successfully?

There are lots of ways to model problems.

  • You can create what is, in essence, a board game, and you can bring in people to help you experiment using the game. Of course, that may take time, and people's patience may run thin if you ask them to try too many different lengthy experiments using the board game.

  • You can create a mathematical model (a set of equations) of your problem and solve them to give you your answer. Unfortunately, most organizational problems need rather complex mathematical models, and we can't solve most of those models as readily as we did homework assignments in school.

  • You can create a computer model of your problem. The computer model may take time to create and test, but it simulates your problem and your proposed solutions much faster than the people playing the board game. The computer doesn't get bored if you ask it to run more experiments.

If done well, your model (of any sort) should exhibit the same problems you see in the real world, and its structure should match the key aspects of the real world.

Now you can try to fix the problem in the model by changing it. There are many approaches to help you do this effectively; the key is to determine which fix (or combination of fixes) in the model eliminates your problem. There's a good chance that your (successful) fix has identified the key factors causing your problem. There's a good chance that the same fixes, if applied in the real world, would fix the real problem. What you learned in making the model work might tell you what you need to monitor closely in the real world.

There's a bit more to it than that, of course, and you need to be skeptical of your model and your conclusions to avoid being misled too easily.

What might such models look like? You can see a small collection of one type of modeling in the archives of my At Any RateTM column published by Pegasus Communications.

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