Tag: R
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Four Kinds of Weird in Your Price File: EUR 43,017 of Negotiating Room
A supplier asked for 20.4%. The published indices supported 2.3%. Here is the R workbench that found the gap, and the three things it honestly could not find.
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Your Supplier Isn’t Offering a Discount. They’re Offering You 29.8%
The price-break EOQ math says buy 600 units instead of 87 and save $6,566 a year. Then a carrying rate above 29.8% flips the answer. Here are the three numbers no supplier quote contains.
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I Raced Amazon’s Forecasting AI Against a 66-Year-Old Formula. The Formula Won.
I put Amazon’s zero-shot forecasting AI against five classical models on 148 real retail series. A formula from 1960 beat a 205-million-parameter model by 14 to 16%.
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I Let AI Agents Play a 5-Year Beer Game: Why Sharing Data Beat Buying a Smarter Model
I ran the classic Beer Game for 260 weeks with AI agents in the chairs. Giving the chain real customer demand cut in-game cost by up to 40 percent, far more than paying for a smarter model did.
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Factory Physics: The Laws Your Factory Floor Already Obeys
Throughput, WIP, and cycle time aren’t three dials you can set independently. They’re bound by physics, and ignoring that costs you weeks of lead time.
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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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Sole Source: The $900k Median Problem Your Dual-Source Checkbox Won’t Fix
The dual-source flag teams buy to feel safe moves the median cost of a disruption about $44k. In the wrong direction. The dependency nobody flags moves it $474k.
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The Resilience Ladder: Why the Things You Buy to Feel Safe Don’t Save You
I pulled 3,000 disruptions to find what separates firms that survive a shock from firms that bleed. The dual-source checkbox wasn’t it.