Process Mining: The Hidden Data That Reveals Your Bottlenecks

Before we install any AI or automation, we must first perform a diagnosis. In my practice, I often see leaders relying on "gut feeling" to decide which processes to fix. They often fix the wrong things.

Process Mining is the scientific approach to business architecture. It involves analyzing the "digital footprints" your team leaves behind in their software tools to visualize exactly how work flows—and where it stops.

The Three Common Bottlenecks

• The Approval Trap: Data often reveals that projects sit in a "Pending Approval" state for 40% of their lifecycle. This is an architectural flaw that requires delegation or automated logic rules.
• The Rework Loop: How often is an invoice generated, rejected, and regenerated? Process mining highlights these loops that eat up profitability.
• The Shadow IT: Teams often bypass official tools to use spreadsheets because the main system is too slow. Identifying these "desire paths" tells us what actually needs to be built.

A data-driven mindset isn't just about looking at a sales dashboard; it's about looking at the operational metadata of your business to engineer a leaner, faster machine.