Monday, August 04, 2008

Bittersweet asphalt

No, it's not that I find asphalt bittersweet (I haven't tried tasting it). It's the news that I find bittersweet.

Five and a half years ago, I published Out of Gas: A Systems Perspective on Potential Petroleum-Fuel Depletion. In that column and in the accompanying simulation model, I suggested that delays due to debates over how to allocate shrinking petroleum stocks might hurt our ability to replace energy resources in a timely fashion.

Today, I read Asphalt shortage disrupts road projects. I'm sure you can find other examples, perhaps closer to your home, in which the imbalance in supply and demand of petroleum is leading companies to prioritize one usage over another, which can cause pain for the unfavored group.

Models such as this aren't designed to predict the future, at least in the sense that they tell you that a certain event will happen in a certain year. They're intended to give insights into the likely and potential ramifications of current and proposed policies, both formal and informal, that we've created. They're intended to help us test policies quickly, inexpensively, and at low risk, so that we can be more confident when we implement a policy in our organizations. They do not provide guarantees, but they can provide very useful and sometimes unexpected insights.

In which areas would you like to think more effectively about the effect your current policies could have on your organization's future?

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2 Comments:

Blogger Ralf Lippold said...

Hi Bill,

thanks for your post on what the purpose of models is..

All too often -still- people are set in the thinking that there must be concrete solution to their problems and don't realize that rethinking or reframing by using a model could get them to new insights of where the problems could have come from.

Best and keep up the great work

Ralf

08 August, 2008 08:03  
Blogger Bill Harris said...

Ralf, thanks for the comments.

Of course, in a way, we do predict with such models. We do say, "If you do such and such, your system may have a tendency to exhibit that pattern of behavior." I can even begin to put some credible intervals around that behavior, given some data and some prior understanding of the situation.

But you're right: the essence of the contribution is insight. When I did the work that led to Applying System Dynamics to Business: An Expense Management Example, I did the work based on a very simplified model. The simulation results were close enough to the real-world results so that you could see the connection, but they in no way could be seen as predicting what expenses would be next month, let alone further into the future.

What that model showed was that a change in the way the organization made spending decisions would lead to drastically improved financial management. That was insight (what should we do), not prediction (what expense variance will we have next month). When we tried the changed policy, our variances went down by 95%, which seemed sufficient to be called a great success.

08 August, 2008 11:26  

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