Case Study: BLG Logistics achieves 3–5% more accurate weekly staffing predictions with DataRobot

BLG Logistics - Customer Case Study

BLG Logistics, led by Process Manager Raik-Ingo Lehr, faced inaccurate monthly staffing estimates for a growing logistics operation that relied on Excel and manual processes. To reduce costly over- and understaffing and improve employee satisfaction, the company turned to DataRobot to explore machine-learning time-series forecasting for weekly personnel needs.

Using DataRobot’s platform in a proof-of-concept, BLG built time-series models (with support from Alteryx for data prep and Power BI for reporting) to forecast weekly staffing more precisely. DataRobot’s solution delivered a measurable 3–5% improvement in weekly staffing prediction accuracy, helping BLG improve ROI and employee morale while increasing transparency and adoption across operations.

BLG Logistics

Raik-Ingo Lehr

Process Manager