Diversity and Competition
This article will cover the importance of recognition of the heterogeneous quality of information and how that relates to market competition.
Hot on the heels of MLK Day, let's talk about another kind of diversity. Information is diverse. Even seemingly identical information is not really identical. Consider that you and I both look at a tree. We identify the tree and its various characteristics. It's 7 feet tall, yields apples, has green leaves and a very wide, in our shared opinion, trunk.
We agree on everything about the tree, but are we really considering the exact same information? I may have looked at the tree from a different angle. If the tree is fruit bearing, we may have inspected different fruits of the tree and still come to the same conclusion about the tree. We agree that the trunk is very wide, but why? Is my history of observed tree trunks exactly the same as yours, or only similar? I would guess that our information is similar, but still heterogeneous.
It could be that identical information may be produced through a computer or some other process, but it seems likely that no two people are in possession of identical stored information profiles. This diversity of information is both beautiful and a pain at times.
It is beautiful because this is how markets process so much information at one time with such minimal bias and maximal accuracy. Consider pairs of people with very different stored information profiles; people of different religions, different professional expertise, different cultural upbringing or different formal education. When people who think in very different ways approach the same problem and come to some solution, at least three important things happen:
- Multiple solutions may be produced instead of one.
- When a single solution is found to be exhaustive or optimal by diverse parties, it is more valid because it is less biased than when a single solution is found to be exhaustive or optimal by homogeneous parties or individuals.
- More information may be processed more quickly, resulting in quicker problem solving or superior problem solving in a given period. Greater potential (information/time).
However, diversity can be a pain. Consider that you want to hire a computer technology specialist for a company. You have two applicants with very, very different credentials, but you can only hire one. How on earth can you tell how will do a better job? They may have different skills, different educations, different experience and so forth. They may be asking different salaries. Which is the better ROI (return on investment, as measured by performance/pay)? Diversity can make problems like this extremely complex.
This is why we as people often engage in categorization, labeling, modeling, generalizing and, yes, even stereotyping. Psychologists, the politically correct and others sometimes speak ill of these ways of thinking, but if these ways of thinking are always bad why do we keep doing them? I think the answer is that like most things, these actions are not always bad. They are sometimes bad and sometimes good. These kinds of thinking and acting can be useful for solving otherwise complex problems. It's all about expected value and it's a rational action.
I have no way of knowing the exact education Jim and Joe, the two people trying to get this computer specialist job, received. I do know that Jim went to a school which has a bad reputation and Joe went to a school with a good reputation. I do know that they both received a BS of Comp Sci and had 3.4 GPAs. Are all BS of Comp Sci equal? Are all 3.4 GPAs equal? Of course not! However, we generalize because we have no further information to act on. Does a school with a bad reputation prove that a student received a lower quality education? Certainly not, but it's all about expected value.
It may be the case that Joe partied at Harvard and did not really receive the education indicated by his GPA. Maybe he cheated. Maybe Jim would do a better job than Joe. These are all possibilities, but at the end of the day Joe is going to get this job because of my perception of the value of each of these guys.
As our example just pointed out, these small calculations can be erroneous. I think the interesting thing is that although these calculations using generalizations can be erroneous, they are in reality usually not erroneous. That leads to a whole other discussion. Perhaps it's survival of the fittest or some high quality intelligent design?