Retail/B2B
Demand Forecasting
Business Need
A leading product manufacturer in the US faced difficulties in planning the manufacture and shipping of new product launches. The manual processes of collating information on the likely quantity and timing of orders for these products from retailers spread across the country were prone to inaccuracies and delays.
Solution
The CA team created a solution to collect preliminary demand signals from retailers for upcoming product launches. These inputs were automatically consolidated to provide visibility into overall demand throughout the launch window, enabling more precise forecasting for new models. Order information was integrated into the platform to compare expected demand with actual purchase behavior. A custom ML Model was deveoped to dynamically distribute demand across manufacturing plants and schedule fulfillment across retailers to minimize waiting time and costs.
Highlights
Centralized demand capture by sales staff managing retailersOptimal allocation of demand to manufacturing plants based on their capacityBetter planning of manufacturing and shipping
Outcome
The demand forecasting tool enabled our client to predict demand accurately, leading to more efficient manufacturing and shipping processes. The automatic algorithm that assigns retailers to shipping weeks saved over 150+ hours of manual effort involved in planning shipping. This resulted in reduced inventory costs, minimized stockouts and improved overall supply chain efficiency, ultimately enhancing customer satisfaction and operational performance.
PREVIOUSRetail Analytic Tools
NEXTPrice Catalog Management