The Challenge
A large organization was spending significant time each month manually reconciling records between two critical systems. The process required matching thousands of rows of data, identifying discrepancies by hand, and distributing findings across multiple teams. This repetitive task not only consumed valuable staff time but also introduced a risk of human error.
The Solution
A custom-built Python tool was developed to automate the reconciliation process. The program ingests data from both systems, compares rows using predefined matching criteria (e.g., department, project ID, account, employee ID), and isolates only the records that do not match. The unmatched items are then sorted by team and output into easy-to-read, team-specific reports.
The Benefits
- Time savings – reconciliation that once took hours is now completed in minutes
- Targeted focus – staff now review only the exceptions, not the full dataset
- Error reduction – automation reduces manual entry mistakes
- Scalable solution – easily applied across departments or enterprise-wide
- Faster onboarding – intuitive output enables new users to engage quickly
Real Impact
After piloting the tool in one department, which managed over $50M in salary allocations, the improved efficiency and accuracy led to enterprise-wide adoption. The organization now allocates more staff time to higher-value work while maintaining data accuracy for critical reporting needs.
Holcomb Reporting Solutions 