Autor: Philipp
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Stop Forecasting in Excel: Why R Is the Only Serious Tool for Supply Chain Demand Planning
Excel can’t do seasonality, model comparison, or prediction intervals without heroic effort — R does all three in six lines of code. Here’s why April is the month you finally make the switch.
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I Scored 10 Fortune 500 Giants as Suppliers: Wall Street Would Not Agree
I applied a multi-dimensional supplier risk framework to 10 of the largest Fortune 500 companies — using real public data. The company with the best credit rating scored as the riskiest supplier. Your neighborhood pharmacy landed at number two. Here’s every score, every data source, and the R code to run it on your own…
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Where Should Your Warehouse Be? 12 Lines of R Code Have the Answer
Most companies pick warehouse locations based on gut feel, real estate deals, or where the CEO lives. The optimal location — the one that minimizes total weighted transport cost — can be found with 12 lines of R code. The answer is rarely where you think.
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FPP3: Stop Guessing Which Forecast Model Works — Measure It
Rob Hyndman’s fpp3 ecosystem lets you fit, compare, and evaluate multiple forecasting models in three lines of R code — here’s why supply chain teams should stop fighting Excel and start using a real framework.
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Prophet: The Forecasting Tool That Actually Makes Sense to Non-Statisticians
Meta’s Prophet gives supply chain teams accurate demand forecasts without requiring a statistics degree — here’s how it works, where it shines, and where it doesn’t.
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When S&OP Fails: A Data-Driven Survival Guide for Production Planners
Only 15% of companies run S&OP successfully. For the other 85%, here’s a data-driven toolkit that lets production planners bypass the broken process.
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Master Claude Code: A Free Interactive Training Program
Nine modules, quizzes, hands-on exercises, and a certificate — all in a single HTML file. A free training program to take you from Claude Code beginner to top 10% user.
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Prompting Just Split Into 4 Different Skills — Here’s How to Master Each One
Prompt engineering is dead. In its place, four distinct disciplines have emerged — Prompt Craft, Context Engineering, Intent Engineering, and Specification Engineering. This post breaks down the framework, shows where Klarna’s $40M AI bet went wrong, and gives you a concrete path to mastery.
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The Experience Curve: The Most Powerful Cost Model You’re Probably Not Using
Every time cumulative production doubles, costs fall 20-30%. Here’s how to fit experience curves with R and use them for supplier negotiations, cost forecasting, and strategic sourcing.
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Mastering Claude Code: From First Launch to 250 PRs a Month
Boris Cherny merges 250+ PRs a month with Claude Code. Here’s every trick — from your first /clear to running 10 parallel sessions — organized by difficulty level.
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The $50,000 Prompt: How McKinsey Frameworks Turn AI Into Your Best Supply Chain Consultant
Most supply chain managers ask AI vague questions and get vague answers. McKinsey consultants have spent 100 years perfecting structured thinking frameworks — and those same frameworks transform AI prompts from mediocre to boardroom-ready. Here are 6 frameworks, 12 before/after examples, and the data to prove it.
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Stop the Madness: Why Your MRP Keeps Changing Its Mind (and How Time Fences Fix It)
Your MRP system reschedules 300 orders before lunch. Your shop floor ignores half of them. Your suppliers stopped trusting your forecasts two quarters ago. Time fences are the fix — and the math shows exactly where to set them.
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The $2,700 Post-It Note: How a 1913 Formula Still Beats Your ERP
A procurement manager discovers she’s been wasting $2,700 per year on a single component — and the fix fits on a Post-it note. We use R to show why a 1913 formula still outperforms gut-feel ordering, when it breaks, and what to do about it.