Manual productivity tracking in warehouses is reactive and inconsistent, leaving significant labor leverage and throughput gains on the table. A custom automation workflow ingests real-time task completion data from the Warehouse Management System (WMS) and Material Handling Equipment (MHE) APIs, comparing individual associate metrics—like picks per hour, travel distance, and accuracy—against dynamic engineered standards. This continuous data fusion creates an objective, granular performance baseline, eliminating managerial guesswork and enabling precise identification of coaching opportunities before they impact daily throughput.




