Our client, a large retailer, faced significant challenges in optimizing inventory deployment across stores and e-commerce channels. Excessive early inventory shipments to stores left the Distribution Center (DC) understocked for timely online order fulfillment. This imbalance strained operational resources in both the DC and stores, leading to costly, inefficient fulfillment processes, longer delivery lead times for online customers, and lower overall customer satisfaction.
MontWave identified the primary factors causing inaccuracies in e-commerce demand forecasting during peak periods. By refining seasonal measures and promotional forecasting for e-commerce, we optimized inventory allocation, ensuring adequate reserves were held for online sales.
Our client faced significant challenges in integrating a new inventory allocation system. They struggled to clearly understand the system’s functionalities, which prevented them from using it to its full potential. This led to a lack of confidence within the company regarding the system’s ability to support accurate forecasting and inventory allocation.
Our client, a large retailer, faced significant obstacles with forecast accuracy. Their inventory allocation process was lagging behind, requiring extensive manual override to adjust allocation quantities. This placed considerable pressure on the inventory allocation team, especially given the short lifecycle and highly seasonal nature of their products. Additionally, human errors were inevitable, leading to frequent overstocking in some locations while causing understocking in others.
MontWave conducted an in-depth analysis and continuous monitoring of sales history and forecast data over several weeks. This investigation led to the discovery of a critical data integrity issue that impacted nearly 60% of the client’s data on a daily bais. Working closely with the client’s IT team, they implemented the necessary corrections to stabilize data input and streamline forecasting processes.
