The Client
The client operates a large, decentralized network of Quick Service Restaurants (QSR). In an industry defined by thin margins and strict labor regulations, workforce management is a critical operational pillar.
The Business Need
Manual auditing processes created a systemic "blind spot," allowing process leakage to go undetected across thousands of weekly shifts.
The Challenge
Data observation revealed 480 instances of employees logging 9–14 hour shifts without recorded breaks over a 3-month period.
- Financial Impact: Excess payroll costs totaling $320,000.
- Legal Exposure: 96 employees exceeded legal shift limits.
- Process Failure: High operational pressure during peak windows led to "impossible" shift logs.
The Solution
We implemented a 100% automated dual-layer technology solution to replace reactive manual sampling.
Phase 1: Python Logic Layer
Python scripts were deployed to ingest raw CRM logs and enforce forensic logic:
- Standardization of inconsistent time-log formats.
- Automated flagging of continuous work blocks exceeding 4 hours.
- Precise calculation of financial leakage for every unlogged break.
Phase 2: Power BI Intelligence
The forensic data was visualized in Power BI, moving the organization to a daily refresh capability.
- Store Burn Rate: Metrics identifying specific financial loss per location.
- Supervisor Risk Index: Targeted visibility into enforcement gaps.
- Network Visibility: 100% coverage across all stores and shifts.
Value Delivered
The transformation delivered immediate capital recovery, allowing the client to reinvest savings into staffing and store modernization.