Case Study: Uni-Select achieves reduced inventory and more accurate forecasting with Manhattan Associates' Demand Forecasting & Replenishment

Machine Learning and Inventory Optimization Accelerate Success for Uni-Select

Uni-Select, a North American leader in automotive refinish and aftermarket parts with 16 distribution centers and hundreds of stores, faced significant demand fluctuation at its Montreal distribution center—especially from seasonality. Internal tools and added headcount failed to curb excess inventory, frequent exceptions and reduced buyer productivity as the DC ships to other centers and 40 retail stores.

Uni‑Select implemented Manhattan Demand Forecasting & Replenishment with Automatic Policy Tuning (APT) to automate and optimize forecasting policies. APT improved forecast accuracy, reduced exceptions and manual changes, shifted slower SKUs to a four‑week cadence, and cut inventory while maintaining high service levels—delivering better fill rates, increased planner productivity and improved receiving dock performance, with rollout expanding to additional SKUs and DCs.

Uni-Select

Jean-Daniel Potvin

Business Analyst for Forecasting and Demand