Category: Forecasting
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Does Your Forecast Beat a Sticky Note? The Placebo Test for Demand Planning
Your forecast has exactly one job: beat a sticky note that says ‘same as last year.’ Most don’t. Here’s the placebo test that proves it.
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30 Books Every Forecaster, Demand Planner, and S&OP Lead Should Read — The Inphronesys Bookshelf
An interactive 30-book bookshelf for forecasters, demand planners, S&OP leads, supply chain strategists, and the data scientists who keep them honest. Filter by category and level, build a reading list for your role.
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The Folly of Forecasting
From the Pythia at Delphi to Google’s GraphCast — humans have always demanded the future. Why some forecasts have gotten dramatically better, why others haven’t, and why AI will not deliver the silver bullet.
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Why VAR Beat Google’s TimesFM — and How to Build One in R
A peer-reviewed 2025 study put Google’s TimesFM foundation model head-to-head with vector autoregression on real hospital data. Spoiler: the 1980s econometric model won. Here’s what VAR is, why it works for supply chain, and how to build one in R.
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Global Forecasting with XGBoost in R: A Walmart Weekly Walkthrough
A hands-on walkthrough of global XGBoost forecasting in R with tidymodels and modeltime, applied to the Walmart weekly sales dataset. What the feature importance reveals, when ML earns its complexity, and when ETS or SNAIVE quietly wins.
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The 20 Most Influential People in Forecasting (And What to Learn From Each)
A TIME 100-style guide to the academics, ML engineers, and supply chain voices who shaped modern forecasting — and the one resource to start with for each.
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When the Algorithm Is Wrong and the Expert Is Right
Statistical models don’t know about your supplier’s factory fire, your competitor’s clearance sale, or the regulation that just changed. Here’s when expert judgment beats the algorithm — and the biases that make it worse.
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The M5 Lesson: Why Simple Still Beats Fancy in Supply Chain Forecasting
The 2020 M5 competition taught a lesson the forecasting world keeps forgetting: on real supply chain data, simple models win more often than you’d think. Here’s what the Walmart SKU benchmark actually showed — and why it matters for today’s Time Series Foundation Model hype.