Warehouse fulfillment and delivery operations are critical components of the retail supply chain. The efficiency of these operations hinges on effective labor and resource planning to ensure customer orders are fulfilled swiftly, and deliveries are made on time. High-quality, business-relevant demand forecasts for outbound shipments from fulfillment centers to customers via delivery hubs are essential for making these planning decisions. A practical and effective approach is to prioritize forecasts that lean towards overestimating demand rather than underestimating it. In scenarios where it's challenging to quickly scale up fulfillment or delivery capacity, under-forecasting can lead to delays in meeting customer orders. Therefore, it is more efficient from a supply chain perspective to plan for sufficient capacity (by biasing towards over-forecasting) that ensures all customer orders are fulfilled in a timely manner, thereby maintaining customer satisfaction. I designed and implemented this approach for one of the largest B2B retailers in the US. This is an example where the forecasting model was tweaked to inherently serve the primary supply chain objective.