Understand the main differences between BI and Process Mining with a real story about WW2 Bombers and digital footprints:
Still on the difference among BI and Process Mining, I recently read this story that helps illustrate it.
During World War II, a consultant was hired by the US Army to help determine the best parts of the bomber planes to be armored.
This consultant mapped every single bomber that returned from a mission and catalogued the bullet holes in their fuselages. Confronting all that data over the schematics of the plane led to set of recommendations of what parts of the plane should be reinforced. That is probably one of the first examples of analytics being applied to military engineering.
The recommendations contrasted with all the knowledge and common sense among military experts. What military experts believed to be critical parts of the plane wouldn’t need to be armored, according to this report, while some not-so-critical parts would deserve extra protection.
“Against data, there is no argument”, some could say.
However, one keen observer solved the puzzle: “It is very interesting that you have mapped all returning planes. But what about the ones that didn’t make it back?”
The consultant forgot to analyze this process from end-to-end. He focused his analysis on a subset of the reality, without fully understanding the whole context.
The key Difference between BI and Process Mining:
Often you are using BI to analyze incomplete, biased data. In process mining, there is this quest for understand a process from end-to-end. Time is of essence. It is about the movie, not the photograph.
When you embrace the process mining philosophy, you are looking for all the events that encompass the process or the customer journey. You are gathering the footprints in the digital sand (files, tables in a database, systems, …) and gluing them into cases. These cases will tell you the whole story, from beginning to end. You rebuild all the paths followed by all process instances; all the flights of every bomber (even the ones that didn’t return).
End-to-end analysis is key to avoid biased analysis and to understanding the essence of a process, or process-like phenomenon, before you can make important decisions. EverFlow Process Mining is End-to-End analysis.