Process Automation ROI
Why 65% of RPA Projects Stall Without Process Mining
Automation without workflow visibility creates expensive digital chaos
65% of RPA initiatives fail to scale beyond pilot because teams automate based on assumptions rather than data. Process mining reveals the actual workflow patterns that determine the success or failure of automation.
The common belief is that business users understand their own processes well enough to guide bot development. In practice, documented procedures rarely match real execution patterns. Hidden variations, exception handling, and informal workarounds emerge only under observation. Automating the "official" process while ignoring actual behavior results in bots that handle only perfect-case scenarios.
What actually works:
A mid-market logistics company used process mining before RPA deployment:
Captured six months of actual transaction data across invoice processing
Identified 40% more process variations than documented procedures suggested
Designed bots to handle the top 80% of real-world patterns
Results: 85% straight-through processing rate and 55% cost reduction within three months
Data-driven automation design eliminated the guesswork that kills most RPA projects.
Strategic insight: Successful automation starts with understanding what actually happens, not what should happen. Process mining transforms automation from expensive experiments into predictable investments.
If you'd like to explore how to implement data-driven automation strategies, reach out anytime.
—Your Global Consultant
