Howard's Blog

This is Howard C. Park's blog. Interests: live music, simulations and modeling, languages, iPod, social and business networking, systems thinking, history of science, management, BBQ, trivia, good coffee, organizational learning, traveling, personal histories.

Friday, April 15, 2005

Predicting the Future

This is a reprint of an entry I made on the Industrial Science Blog.

I am often asked by clients, colleagues (and even family), "can your models really predict the future?".

It's enticing to think that it's possible to know, with absolute certainty, how the future will play out--in a business dealing, in world politics, in your stock portfolio, tommorow's game, or tonight's dinner. If we're "smart", and we make our models "smart", couldn't we use it to tell us what will happen? In fact, the early days of computing was marked by an attempt to better predict (and perhaps control!) weather. We know today that our weather reports can be wrong.

"We're not in the buisness the predicting the future. Instead our models help you prepare and, if you're bold enough, help you shape your future." is the sort of reponse I give. In fact, we find that in many organizations there are varying ideas of what the future is and why it's important. Even when confronted with lots of data (and perhaps because there is too much data) it's difficult to put it all together into a coherent viewpoint.

Sometimes its best to think about the range of possible futures to see what's possible. Think of the three ghosts who visit Scrooge--there is but one future (if we ignore the parallel universe argument), but I'll show you what COULD happen. Why is this important? Becuase it causes Scrooge to change behavior NOW. Dickens ends the story here without fast-forwarding to the actual future. He doesn't have to. We the readers "get it".
|| hcpark, 9:28 AM


Well put Howard. While in B-school, I had an internship with a chemical company that wanted to model margins for their product three years into the future. I gathered decades of data -- macroeconomic, industry production, sales, inventory levels, capacity, etc. -- ran my regressions, and created a model. The initial output of the model was garbage so we decided that we needed to remove data associated with special events (wars, industrial accidents, etc.). The result then showed margins quickly reaching an equilibrium point and stabilizing at that level. This was a highly cyclical industry so this did not fit expectations either. However, as we thought about it, we realized that what the model was telling us was that the industry has a theoretical equilibrium which it never reaches due to unpredictable external events that constantly knock the industry out of equilibrium. From that understanding, we were able to use the model to perform various "what if" analyses so the company could prepare for various scenarios. The model was not a crystal ball able to predict the future but a tool to explain possible outcomes given different scenarios.
Anonymous Steve E., at 11:25 AM  
I think of C. S. Lewis’s words from The Screwtape Letters: “[God] wants men to be concerned with what they do; [the devil’s] business is to keep them thinking about what will happen to them.” Although Lewis was writing about Christian moral virtue, there is an application to trading (I can say nothing about applications to business practice). Good traders realize that they cannot reliably predict the future, and that the only way to make money is to react quickly and rationally to present conditions; bad traders believe they can make money by predicting the future, even if only “20 minutes into the future.” Good traders concern themselves with what they do—that is, how they will respond to market movements; bad traders worry about what will happen to them when their predictions don’t pan out.
Anonymous Nils, at 10:57 AM  

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