The case Prediction Markets: A new Tool for Strategic Decision Making is about a new way of preventing uncertainty when making important strategic decision by private businesses and public agencies. With prediction market you have a theoretical proof that your decision is correct because it is based on betting markets. Even with its limitations I think it is a good thing that more methods are being introduced. Decision makers can decide by themselves which one they like to use.
The case The Collective Intelligence Genome is about the building blocks of websites based on collective intelligence. To find these building blocks you have to answer 4 questions: what, who, why or how? The answers are called ‘genes’ and the combination of genes can be viewed as the ‘genome’ of that system. This case identifies them, explores the condition under which each gene is useful and suggests possibilities to combine the genes.With the Collective Intelligence framework, managers can choose a combination of genes to maximize their websites potential. I think this is a good way to do this because the possibilities to build a website based on collective intelligence are quite complex but a framework gives a better overview of them.
The case Which Kind of Collaboration Is Right for You? Is about the different types of collaboration you can make use of when you are a business. There are 4 dimensions called, Open, Closed, Hierarchical and Flat which you can combine at 4 different ways. All dimensions have their advantages and disadvantages and are only effective under certain scenarios. I think it’s important to carefully think about which collaboration you choose for. When you choose for a combination of dimension which not match to your strategy, then your strategy will likely fail. This case gives a good explanation to prevent this from happening.
My related article is called Putting crowd wisdom to work. In this article Google explains that they they make use of prediction markets because they want to forecast more precisely thing that are strategic important to Google, like product launch dates and new office openings. I can understand that Google tries this new way of predicting markets. As I say earlier there is empirical proof that predicting the market by use of a bet system often works. Of course the system does not always work and there are more cons to consider but the prediction market is relatively new and Google has always been the first in trying new things out.
To clarify the accuracy of the prediction market concept I will explain two mini-case examples. The first one tells us more about the flaws of the system. It is called “Interpreting the Predictions of Prediction Markets”. The second one shows us that the prediction markets do work under certain conditions and it is called “Risk Aversion, Beliefs, and Prediction Market Equilibrium. I think the second one is the better case because it extends the first case with better variables.
