Analysts don’t like the “why” questions. They are tough to answer. For instance, in a help desk analysis, it is easy to show which tickets are resolved faster. But it is difficult to say why. In my practice in Sopra
Mistaken by factor of 100,000
Longormal data is very tricky. Wrong visualization methods can lead to radical misinterpretation of the result. In this article I show an example of such a mistake based on a real project, and I demonstrate how to avoid the caveats
Are people fair?
Suppose all you had was a history of user requests to the service desk. Would you be able to determine how many of those requests were honest?