Inventory is one of the largest working capital components on the balance sheet, and excess stock erodes margins through carrying costs, obsolescence, storage, and lost cash flow flexibility. The challenge is not simply reducing inventory but reducing the right inventory without compromising service. The paper starts with the root causes: poor forecast accuracy, demand volatility from promotions, seasonality and new product launches, blanket service targets, limited visibility, and long, static planning cycles.
It then shows how SAP Demand Planning addresses them: statistical forecasting as the baseline with forecast value add and bias tracking, ABC/XYZ and lifecycle segmentation so service levels match each SKU's margin and volatility, and dynamic, SKU-level safety stock calculated from forecast error, service level, and lead-time variability instead of flat weeks-of-supply rules.
Because technology alone doesn't cut inventory, it covers the process side too: consensus forecasting in S&OP, event-based promotion planning with post-event reviews, NPI reference modeling and phase-in/out, KPI tracking, exception planning, and governance. The expected impact it cites includes 10–30% better forecast accuracy, 15–25% lower safety stock, 10–20% lower inventory, and 20–40% less obsolescence.
The full paper is available above as a PDF. See also "SAP Integrated Business Planning (IBP): Overview and Functionality" and "How Supply Chain Executives Can Improve Plant-Level Operations Using SAP" in the Resource Library.