Distribution

Because unserved orders usually translate into lost sales that directly impact the bottom line, high customer service levels are critically important to wholesale distributors. But dealing with intermittent or ‘long-tail’ demand is ultimately challenging. They need to serve this demand in the face of seasonality, shorter product life cycles, increasing SKUs counts, obsolescence risk and offshore supplies that create longer, less flexible lead times.

Too often, saddled with inadequate planning systems, wholesalers turn to supply heroics and short-termism without inventory optimization, analytics-based service optimization, or sales and operations planning (S&OP).

They struggle to forecast volatile demand and manage inventory cost effectively.

• Demand modelling and machine-learning to address internal and external demand variations such as market trends, seasonal demand profiles and promotion forecasting.
• Probability-based forecasting that assesses the chance of repeat orders by examining order-line data. Rather than aggregate demand, it keeps track of the number of order-lines placed to reach the total quantity.
• Demand collaboration that brings together demand and forecast data from multiple sources in a web-based consensus platform that even measures Forecast Value Added (FVA).
• Inventory optimization that calculates safety stocks and other inventory parameters for an optimal mix across up to millions of SKU-Locations. It also addresses product expiration, substitution and transportation constraints such as minimum order quantities.
• A “single model” approach that guarantees customer service levels across the network via optimal inventory levels.