All Things Data Science

With the rise of the 'Data Scientist', a lot has been said about the definition, role, qualifications and skills of the Data Scientist, and how to hire them. A somewhat neglected topic is how to manage data scientists. Indeed, data scientists, by their very nature, are hard to manage. They love to resolve problems, but those problems are not always the business problems you want them to tackle. They are ace players, but they're not always the best team players and some of them can sometimes have difficulty in dealing with (higher) management. They can have bright ideas, but they often lose interest when it comes to implementing those ideas in a profit making activity. They will find clever solutions for you, but they don't always excel in making sure that a structured process is place, let alone the administrative follow up that comes with it. Some of them were hired as 'rock-stars' and have developed an ego that goes with that... On the other hand, they are...

Don't you hate it when people are pestering you with client focus? These days everybody in an organisation should be focused on the client, it seems. I'm not sure this is always a healthy situation. As a matter of fact, I'm writing these words on an airplane heading to Dublin. I hope and I pray that the pilot is not focused on the client, but rather on his airplane dashboard. Sure, we all know that organizations should be client focused if they want to survive, but that does not mean that all members of the organization should be client focused all of the time. It seems to be the business equivalent of the Robinson effect (Robinson, W.S. (1950). "Ecological Correlations and the Behavior of Individuals". American Sociological Review 15: 351 – 357.). Based on the 1930 US census, William S. Robinson found a positive correlation between the literacy rate of a state and the percentage of inhabitants born outside the US, while at the individual level this  correlation...