Data analytics is the enemy of change

Big idea number three. Data analytics is the enemy of change. For the past half century, business education has taught us that the only good business decision is one made on the basis of rigorous, data based analysis. Anything else is unbecoming to a business manager, and we are all taught the methods for performing rigorous database analysis, how to collect samples, how to crunch the numbers, how to test for statistical significance. As part of that, we're helped to understand how important it is to collect a representative sample. The sample has to be randomly selected from a pool that is representative of the universe about which we seek to make a statistical inference. For example, if we want to know what color customers in general prefer, we better not only sample males or elderly people if we're selling to all sorts of customers. But we weren't taught because this is not taught at all, is that since 100% of the world's data is from the past, the implicit assumption we are making whenever we take a sample and draw a statistical inference from it that the future will be identical to the past. Otherwise the sample will be unrepresentative and any analysis made from it deeply flawed and unusable. The only thing that data analytics will do is convince you that the future will be identical to the past or continue the precise trend of the past indefinitely into the future. As such, data analytics is the enemy of change. To create a future that is distinct from the past, you need to heed Aristotle's warning, and Aristotle is the father of data analytics, and recognize that to create the future, you have to imagine possibilities and choose the one for which the most compelling argument can be made. And importantly, Aristotle, the father of science, argued against using data analytics to create a future that is different than the past. The big idea here is that if we want to revere Aristotle's analytical methodology, his scientific method, we should also take seriously his instructions on when to use it and when not.