20–30%
Average Forecast Error (MAPE)
The average forecast error (MAPE) across industries is 20–30%, costing companies billions in excess inventory and stockouts annually.
20–30%
Annual Inventory Carrying Cost (% of value)
Inventory carrying costs typically run 20–30% of total inventory value per year, including capital, storage, obsolescence, and risk.
$1 trillion
Annual Revenue Lost to Stockouts (global retail)
Out-of-stock events cost retailers an estimated $1 trillion in lost sales globally each year.
70–80%
Planner Time Spent on Manual Work
Demand planners spend 70–80% of their time on manual data gathering and spreadsheet maintenance rather than decision-making.
20–50%
Forecast Error Reduction from AI (vs. statistical baselines)
AI-driven demand forecasting reduces forecast errors by 20–50% versus traditional statistical methods.
45%
Profit Loss from Supply Chain Disruptions (per decade)
Companies lose an average of 45% of one year’s profits over a decade due to supply chain disruptions.
4–5 weeks (best-in-class)
S&OP Cycle Time
Best-in-class S&OP processes run monthly with a 4–5 week cycle; median companies take 6–8 weeks per cycle.
15–35%
Inventory Reduction from Advanced Planning Systems
Companies using advanced planning systems reduce inventory levels by 15–35% while maintaining or improving service levels.
up to 40%
Short-Range Forecast Accuracy Improvement from Demand Sensing
Demand sensing shortens the effective planning horizon from weeks to days, improving short-range forecast accuracy by up to 40%.
6–12 months
Typical ROI Timeline for Modern Planning Platform Adoption
Organizations that replace legacy planning tools with modern platforms see ROI within 6–12 months through inventory reduction and planner efficiency gains.