A Multi-Site E-commerce 3PL Boosts Pick Productivity with Qlik Predict Workload Forecasting

Built a planning and execution cockpit in Qlik Cloud and deployed order-volume and SKU-velocity forecasting using Qlik Predict’s model. 
The models refresh daily to highlight upcoming workload spikes and fast-mover shifts so site leaders can plan labor, replenishment, and slotting before congestion hits the aisles. 

Planning was spreadsheet-heavy and often late, creating overtime spikes, replenishment firefighting, and inconsistent performance across sites. SKU velocity shifts were discovered only after pick queues formed, and managers lacked a consistent cross-site view of workload risk. Promotion weeks amplified volatility and made it difficult to align staffing and replenishment to actual demand.

B EYE integrated WMS waves, order history, SKU movement, replenishment cycles, and labor hours in Qlik. Qlik Predict forecasted site-level workload and flagged velocity-change SKUs that would drive operational disruption. Managers used the cockpit to align labor planning with forecasted peaks, trigger replenishment earlier for fast movers, and identify slotting opportunities. Priority sites improved pick productivity, reduced overtime peaks, and achieved more predictable throughput during promotions. 

1. Reusable multi-site pattern – A consistent data model and KPI layer makes cross-site comparisons fair and actionable. 
2. Forecast reliability – Promo-aware features and monitoring reduce drift and keep forecasts useful across seasons. 
3. Manager-ready UX – One sheet for forecast vs plan, hotspot zones, replenishment risk, and fast-mover changes.

“We finally plan the week with confidence. Instead of reacting to spikes, we staff and replenish ahead of time with one source of truth.” 
– Head of Operations