Your demand forecast drives your integrated business planning (IBP) process and is the largest source of uncertainty.
Improving your demand forecast affects the entire supply chain and has a multiplier effect as it travels along the IBP process. That’s why even marginal forecast improvements have a large proportional effect on revenue, costs, profit, and working capital, as well as customer satisfaction. If the demand forecast is accurate, everything else falls into place.
Demand Planning Case Study
A multi-billion dollar company was challenged by their inventory management. Although they had reached an advanced level in logistics management, they lacked a forward-looking view and accuracy in their inventory, distribution, and replenishment planning. They struggled to support fast business growth and adapt their information flow to the rapid development of their enterprise supply chain.
- effectively estimates and models optimum inventory levels based on service levels, delivery times, and costs
- improves predicted demand, transport, inventory replenishment, and key performance indicator (KPI) alerts
- automatically analyzes, models, executes and adjusts predictions for products and regions
- forecasts demand by specific product and outlet
- calculates the replenishment frequency of different regions
- determines the optimal transportation schedule
- fully considers the company’s replenishment network including factories, logistics centers, outside warehouses, and retail stores