By forecasting store and online fulfillment demand for every SKU and location
By improving inventory alignment by reducing forecast error by 20%
As reflected by a 75% reduction in planner overrides.
By reducing safety stock and on-hand inventory by 20%
Many retailers struggle to decipher explainable data within the noise of their historical data. Yet even those that do, many still fail to gain the full value from their demand predictions if they aren’t used throughout their merchandising and supply chain processes
In this short video presentation, Nicholas Wegman PhD explains how to overcome these challenges.
Watch the 1-minute summary video.
Up to 3% by allocating for both local sales and online fulfillment
By 250% by aligning inventory to the overall omni-demand
By doubling ship completes from better inventory positioning
Today’s allocation requires a complete picture of demand, which means that you must account for those who come into the store and those who live within the vicinity who will order online.
How is this done? Watch this demo.
“Our online demand is up 300%, but our margin decreased from 36.7% to 26.8% as a result of higher fulfillment costs.”
“Our DC capacity cannot keep up with our expected holiday online demand. We are expecting extreme store-based fulfillment.”
These are real challenges that require interconnected and responsive planning across merchandising, supply chain, and marketing functions to solve.
Watch this introductory video to learn more.