According to Nate silver we can live better through statistics by appropriate and best use of Bayes principle as we go on to have more and more data we converge towards a more precise decision with its help.
We will discuss the applications of Bayes theorem in business world where more of past and present data is available which can be used to predict a precise future.
For example if an organization wants to find out relation between higher sales volumes and prices and analysts confirm that higher sales volume leads to higher profit in their business, then that information can (andshould) be informed to the executives who makes decision’s and business strategy for the organization. Then they go on to answer the questions such as: How can they best support high-volume distributors? How can they incentivize other distributors to sell more?
Also the result of above example can show that volume is not a key indicator of profitability (in many cases margin, rather than volume, drives profit), then executives must update their models based on this new information, and shift business strategy based on an updated understanding of profitability.
Another example of the application of Bayesian decision theory using large amounts of past data is for promotional purposes in marketing business by the use of a test sample in order to assess the effectiveness of a promotion prior to a full scale role out. By combining prior subjective data about the occurrence of possible events with experimental empirical evidence gained through a test market, the resultant data can be used to make decisions under risk.
Always if the Bayesian results are away from estimates then more data related to the information can be added to get better and precise results and that’s how we draw the conclusion that “the more accurate information we add, the better our estimates will be”.