The Challenge
A tier-1 bank had committed to an automation programme but lacked the operational insight to prioritise correctly. Leadership had assumptions about where inefficiencies lived — but assumptions built on anecdote and intuition had already led to low-ROI automation investments. They needed an objective, data-driven view of how their back-office processes actually ran before committing further capital.
The Solution
We deployed Celonis and UiPath Process Mining across the bank's back-office operations, complemented by SAP Signavio for process modelling. Event log data was extracted from core systems to reconstruct how processes actually executed — not how they were designed to run. Task mining was conducted on individual user workstations to capture the granular, system-level interactions that process logs miss. The result was a complete, quantified map of the operations landscape: where time was lost, where processes deviated from standard, and where automation would generate the highest return.
The Impact
Over 30 automation opportunities were identified and ranked by impact and feasibility. The bank entered its next automation planning cycle with a prioritised, evidence-based roadmap rather than a list of assumptions. Early-stage automation initiatives targeting the top-ranked opportunities were underway within weeks of the engagement closing.
Reflection Question: Is your automation programme targeting the right processes — or the most visible ones? What would an objective, data-driven view of your operations reveal?
Let's run a process mining engagement on your operations and show you where the value is.