My Digital FootPrint

It is all about averages.  If you have a single dimension data set, say height, with a large data set, it is probable that one user will be the average of the entire set. In a two-dimensional data set, height and weight, it is probable that one user may have these two characters as the average of the entire set. In a three-dimensional data set, inside leg measurement, height and weight, it is tending toward impossible that one user may have the three average characters of the entire set. More data makes it more probable, but also more characteristics make average persons more improbable, as mean, mode or medium. Facial recognition uses about 80 nodal points, it is (im)possible that a single data subject in large data set will be average on all points.    The point is that we think more data will create a better understanding of our users. This is unlikely to be the case. What we need to determine are the boundary conditions where the data we have access to enables better decisions.  

This thought piece explores how business executives ought to be debating control over user (data), is less about where data is collected and stored but rather where, or rather how, individual data is used, monetised and by whom. -- Given that platform companies such as Apple, Facebook, Twitter, Google, Baidu, Amazon, Alibaba, Tencent Xiaomi as examples complicate, confuse and officiate what they are actually doing with our personal data, how can leaders position their business to become truly customer centric and put the customer first. As a context, economics defines utility companies (gas, electricity, water, telecoms) as only having one true differentiator - price. Given the ubiquity and certainty of one unit of electricity is the same from where-every you buy it, the market players create bundles and offers to hide the actual price and to make comparisons between the same utility very difficult or near impossible. However, what happens when you don't have a “price” e.g. Fac