Learn about demand planning and forecasting
Practical guides on sales forecasting, Machine Learning, S&OP and inventory to make better decisions with your data.
ABC/XYZ analysis: stop treating every SKU the same
How to segment your catalog with ABC (value) and XYZ (demand variability), the 3×3 matrix with a strategy for each cell, and where sharper forecasts pay off most — with formulas and a worked example.
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Forecast accuracy metrics that actually matter: MAPE, WMAPE and bias
How to measure forecast error the right way — why plain MAPE can mislead you (with a worked example), when to use WMAPE, how bias quietly piles up inventory, and what FVA reveals about your process.
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S&OP in plain terms: getting sales and operations to agree on one number
Sales and Operations Planning aligns commercial, supply and finance around a single demand plan. The monthly cycle, what 'one number' really means, and the measured payoff.
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Safety stock, explained: how much buffer inventory do you really need
What safety stock is, the formulas to size it from demand variability and lead time (with a worked example), and why better forecasts shrink the buffer you need.
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What is demand planning and why Machine Learning beats Excel
A practical guide to demand planning: what the research says about spreadsheet errors, the evidence that Machine Learning forecasts better, and when it's time to leave Excel behind.
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5 forecasting failures that cost millions
Five documented demand-planning disasters — Cisco's $2.25B write-off, Nike's $100M i2 failure, Target Canada's collapse, KFC's empty stores and Walmart's 2022 inventory glut — what each one cost, what failed, and what would have prevented it.
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