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Demand Forecasting Accuracy Cost Calculator — Forecast Error Cost

Calculate the financial cost of demand forecast errors. Overstock holding cost and stockout lost sales — and find the ROI of improving forecast accuracy.

Quick answer: A 20% forecast error on $10M inventory = $500K+ in excess holding cost plus lost sales from stockouts. Improving MAPE from 25% to 15% typically saves $200K–$800K for mid-size distributors.

📊 Demand Forecasting Accuracy Cost Calculator

Mean Absolute Percentage Error — typical: 15–35%
vs stockout. Varies by industry.
Total Forecast Error Cost
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Overstock Holding Cost
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Stockout Opportunity Cost
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How to Use This Calculator

  1. Enter revenue and inventory value — annual revenue and average inventory on hand.
  2. Enter current MAPE — Mean Absolute Percentage Error — your average forecast error. Pull from your ERP/planning system.
  3. Set target MAPE — best-in-class with AI forecasting: 8–12%. Good manual forecasting: 15–20%.

Worked Example

$20M revenue, $4M inventory, 25% MAPE, 12% target, 25% carrying rate, 35% margin, 60% overstock split.

  1. Excess inventory: $4M × 25% × 60% = $600,000
  2. Overstock cost: $600K × 25% = $150,000/yr
  3. Stockout cost: $20M × 25% × 40% × 50% × 35% = $175,000/yr
  4. Total: $325,000/yr
  5. At 12% MAPE: saves $169,000/year

AI demand forecasting platforms (Blue Yonder, o9, Anaplan, Relex) typically achieve 8–15% MAPE and cost $50K–$200K/year — strong ROI for $10M+ inventory businesses.

Frequently Asked Questions

Industry varies widely. Grocery/FMCG: 8–15% is achievable. Retail fashion: 20–35% is typical. Industrial B2B: 15–25%. Best-in-class with ML/AI: 8–12% across most categories. MAPE under 10% at SKU level is world-class.

Sporadic demand (C-items with intermittent sales), new product introductions, promotional spikes, long lead times amplifying forecast horizons, and poor data quality. Address root causes before investing in forecasting tools.