Process mining is a term that started getting traction in the recent years. The aim of process mining is to visualize the real business process and compare it with plan and theory.
But now business decision makers would ask, why there is a difference between original process and ideal process? We are speaking about 5 points to shed some light on why difference between actual and ideal process may occur:
Employees around the world are getting stretched on numerous tasks that are maybe repeated or unnecessary to the productivity and KPIs, just doing it for the sake of completing a specific task. This usually leads to overloading and distracting employees from devoting the time for the most important stuff.
When business decision makers think about processes, the process plan is usually done as per the happy days, exceptions may not be taken in consideration, resulting in a clear difference between the reality and the planned processes.
We are all humans, and sometimes we have subjective views especially if there is no proof to prove us wrong. Which means we may put emphasis on a specific process step.
Also, this happens when everyone on his/her device is focused on his own piece of work, but not really seeing the rest of processes after his/her work is done. Which creates a problem with the transfer of work happening without full picture in mind.
Unclear and Ambiguous Process:
Sometimes we have no clue on how the process should exactly look like. Which means it gets harder to identify the bottlenecks so harder to improve the process. Especially when it comes to IT based information processes, hard to see what is going on as processes are less tangible.
With the IT systems generated overload of information and data and looking at the above points it shows that it is tricky to manually start looking into your processes step by step. An example below of a transaction data record by IT systems during a business process:
Looks impossible and challenging to analyze such data manually, yes you can look at individual case but not entire data population. With process mining, you can do that.
How process mining works? It starts by recalling data (log data/file) from processes in operation, then create accurate models of the real process out of raw data, then modelling based on objective and complete data, and finally provide ideal basis to build a process plan on.