A correction: Thanks to a great discussion with a co-worker (Sacha Arozarena Valladares - http://blogs.msdn.com/sacha/) he told me that my analogy doesn’t work well re: the mortgage industry. He’s right. The issue with my analogy is that the wisdom of crowds assumes that all knowledge is agnostic and created by the crowd itself. In the banking case, a small oligarchy of firms were making hugely bad decisions and not showing how they were coming up with “good information.” Thanks for the catch there Sacha.
Additionally, he mentioned some interesting work going on in the realm of developer-crowding. Take a look at http://stackoverflow.com when you have time. This site takes questions from developers, and then gets answers from the community. People rank how the answers fit the question, and the higher the ranking for the answer or person, the more trusted that answer or person becomes. This is a good example of how crowd mentality can work.
First, I apologize for the extreme delay in posting. Blogging is still interesting to me, but other obligations have taken a priority. I continue to plan to regularly contribute to this content.
Okay - so, the main reason why the wisdom of crowds is not believable is because the system assumes that there is good data supporting the crowd's decision making process. If a crowd receives a mass of bad data, how can anyone expect the wisdom of crowds to work? The best example I can think of in current events right now is the housing crisis. Everyone assumed that the housing market was doing fine, and that people were able to buy into the American dream of home ownership, which really only lasted for several years. Then, as the market started to deteriorate, everything collapsed, affecting worldwide markets. Now the government and financial institutions are saying that they don't know how big the problem is, and people are picking random numbers to try to tackle the issue ($700B for example).
So what the heck does this have to do with knowledge management? Crowds can't be the main barometer to tell you what you need to write about or focus on for KM. If the crowd coming to you has bad data, or they're directed to you inappropriately, whatever work you do to satisfy them isn't going to actually work.
Here's an example. Let's say you have a KB article that has very high hit rates, but very low satisfaction. Surely, there must be something wrong with the content; after all, the crowd has told you that there is something wrong. But if you don't understand the context of where the customers are coming from, and their expectations, the crowd will tell you things that you may not be able to properly take action on.
Continuing with the KB example, if a highly used help file or forum points people for Problem A to your KB article, people will go there to try to solve Problem A. If your KB article however only solves a segment of Problem A, the crowd will inherently be dissatisfied. It's not the fault of the content that the crowd chose to follow a lead that brought them down the wrong path, but the content is to blame because it didn't solve the crowd's issue, even if the issue is different than intended purpose of the content.
This really doesn't have anything to do with the book The Wisdom of Crowds. I think sometimes people apply that philosophy though to areas where it shouldn't be applied. Sometimes, with the wrong information, crowds can be quite stupid. As the book points out, too much of the same information turns people into following herding behavior, which is what I'm really talking about here.
Hunter DonaldProgram Manager - Knowledge Management StrategyCommercial Technical Support