Cost-to-Serve Modeling by Customer and Channel

From use case: Cost-to-Serve Modeling by Customer and Channel

A global food and beverage manufacturer faced increasing supply chain volatility that made it difficult to ensure products were positioned correctly based on customer demand across multiple regions. The company implemented a digital twin-based supply chain modeling platform to calculate cost-to-serve automatically across its network. According to Coupa, the manufacturer can now quickly create and compare scenarios to evaluate how manufacturing, distribution, and logistics changes affect product placement and cost. The implementation resulted in 60% faster decision-making and enabled the company to reconfigure distribution networks in Mexico, North America, and China to reduce both costs and carbon emissions simultaneously. Prior to the digital twin deployment, the company had also achieved a 14 to 20% reduction in inventory through AI-driven forecast accuracy improvements, with every 1% improvement in forecast accuracy yielding a 2% reduction in safety stock.

In the B2B distribution sector, a wholesale HVAC and refrigeration distributor in North Carolina implemented a customer stratification analytical tool integrated with its ERP system to calculate the profitability of individual customers. The tool evaluates buying power, loyalty, margins, and cost-to-serve factors to classify customers into profitability tiers. According to Earnest and Associates, the distributor was able to identify marginal and service-drain customers and change their behaviors, with the operations manager noting that marginal customers can become profitable customers once the organization knows who they are. The company also shifted customers to online self-service ordering, freeing outside salespeople to allocate more time to high-value accounts.

A consumer packaged goods company discovered that profit margins were declining despite believing it had negotiated favorable pricing. According to a 2025 Plante Moran analysis, the company was not accounting for the full cost of fulfilling individual retailer requirements, including unique displays, distinct labeling, pallet specifications, and extensive rebate programs. After implementing a structured cost-to-serve dashboard covering material cost, conversion cost, warehouse management, freight, and service fees, the company identified that lower-cost customers were subsidizing those with more complex service requirements.