What are the differences between Process Mining and BI (Business Intelligence)?

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Process Mining and Business Intelligence share the same goal of helping companies make effective decisions based on factual data. However, these tools differ in the depth of process analysis:

BI allows you to detect and visualize errors, but determining the root cause of problems requires expert interpretation.

Process Mining analyzes not individual venezuela mobile phone numbers database facts, but sequences of events from different information systems, which allows us to answer not only the question "how", but also "why".

Traditional Business Intelligence is unable to display:

Discrepancies between actual and planned business processes.

Alternative implementation options for algorithms.

Various deviations from the process (skipping stages, looping, blocking).

In essence, Process Mining is an advanced, algorithm-oriented version of BI. It not only visualizes data, but also solves specific problems and identifies the roots of problems in detail.

When is it appropriate to use Process Mining?
In principle, PM can be applied in any situation where the activities of employees are reflected in information systems and one of two conditions is met:

We are talking about simple mass processes performed thousands (tens, hundreds of thousands) of times daily. For example, customer service in a bank. Here the sequence of actions is honed to the smallest detail, and the main attention is paid to the efficiency of individual employees and departments. Although it is unlikely that it will be possible to radically change the mechanics of the algorithm, optimization of each link can give a significant overall effect.

Complex, extended individual processes are considered, covering the activities of many departments. In this case, Process Mining is aimed not so much at acceleration, but at simplifying the algorithm, optimizing the number of stages, eliminating defects, unnecessary cycles, unjustified involvement of new participants, etc.