In Economic Modeling, Can Hindsight Lead to Foresight?

In thinking more about my last posting here on failed Wall Street quant models and the dimensionality curse I started to wonder whether we could ever be more than the archetypal Monday morning quarterbacks:  commenting brilliantly on all the reasons why X should never have happened, after X has already happened and done its damage.  Can the mistakes of hindsight lead to foresight?  In other words, can we apply foresight to develop “good” economic models that won’t blow up in our faces?

In trying to answer this postulation we must go back to examine the eternal challenge of good modeling: how to create a simplified representation of reality that in ignoring many real-world features still manages to convey an inherently robust facsimile of the real thing.  For example, one of those maps of New England you buy at Exxon gas stations can serve as a good model for getting you from Hartford, CT to Boston, MA even if it ignores most of the streets and alleyways and other real-world detail that exist along the route.  In their book “Complex Adaptive Systems: An Introduction to Computational Models of Social Life” John H. Miller and Scott E. Page observe that the “ability to ignore is a crucial component of scientific progress”, using the image of a parent’s being able to respond to the incessant “why” questions of a three year old child by saying “just because”.  The trick, as the authors point out, is knowing when (and perhaps more importantly when not) to say “just because”.

While I wholeheartedly agree with that assertion I don’t think that it quite gets us to an adequate level of comfort in applying foresight to the creation of good models.  In his fascinating book “The Origin of Wealth” Eric D. Beinhocker points out that economic modeling took what many consider to be a wrong turn back in the latter years of the 19th century when leading thinkers of the day like Leon Walras and William Stanley Jevons borrowed heavily from the referential context of physics to create models for explaining economic activity, including such notable concepts as a mathematically representable state of equilibrium that continue to serve as the conceptual foundations of modern economics textbooks.  As Beinhocker elaborates, the problem with these models was that some of their fundamental assumptions – like the perfect, robot-like rationality of human beings in making economic choices – didn’t seem to simplify reality as much as contradict reality.  Thus we find ourselves in the present ruminating over the precise, mathematically elegant language of physics and the complex, evolutionary language of biology and debating whether a choice of the wrong science by the founding fathers of economics back in the 19th century led to the failure of models to adequately explain much of what is going on in the economy today and in particular the string of boom-bust upheavals that have become part and parcel of the last 20-odd years of economic activity.

I still don’t think we are there yet in getting closure on the foresight question, but we may be getting closer.  To tie in the strands of thought presented by Miller & Page and Beinhocker, when we get to those basic defining assumptions, Read the rest of this entry »

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Forget Your Competitors, The Power to Consistently Lead Your Market Lies In Understanding How Every Customer Values Your Product

Far too often, we have companies seeking our expertise to ascertain their competitors’ competitive strategy vis-à-vis their pricing, as if this will provide the magical insight they need to help them maximize their own revenues. My advice: save the detective work for Colombo and forget about your competitors! Your bottom line profits should not hinge upon a competitive response strategy that reacts to your competitors’ price moves, where you surrender control over your revenue structure and end up locking your firm into a race-to-the-bottom pricing with the rest of the industry. Escaping this destructive cycle lies in focusing relentlessly on your customers rather than your competitors. If you’ve read the news in the last 10 years, you may have realized that your customers are the most informed consumers in the history of the world! They are utilizing every available resource, from various news and industry websites to trade magazines to word-of-mouth gossip to Oprah to… well, even your price helps them determine their perceived value of your product. They are better informed about their purchases than ever before, but I wonder if you are learning as much about them and how they view your products?

Here’s an example to help you understand the magnitude of the problem your organization is facing: you sell thousands of products to tens of thousands of different customers each and every day, which is equivalent to millions (if not billions) of distinct customer-product interactions every day – impossible for even the most experienced sales managers to analyze individually. Now grab a pen and some paper and write this down: every sale is an interaction whose revenue can be uniquely maximized! Most companies fail to detect the subtle changes in their customers’ preferences over time, leaving significant profits on the table. And hence the reason for the detective work we’re often called to do; companies don’t realize they have all of the necessary data to maximize revenues right under their noses.

The solution here is Scientific Micromarket Management, which makes it possible for organizations to assess how each customer values your product and offer exactly that price every day in every market. Sure, we may be talking pennies and nickels here, but if you multiply these adjustments by the millions of potential customer-product combinations, then multiply these daily adjustments over the course of a year, and you will realize the significant amount of impact this will have on your bottom-line. Capitalizing on these billions of tiny demand shifts with a dynamic pricing system more targeted than human intuition enables companies to finally understand why every single customer buys what they buy from you and what they are willing to pay for it every time. This is far more comprehensive than any pricing strategy; this is a complete revenue optimization solution. Your customers are getting smarter about you, I think its time you got smarter about them.

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