Where SCM meets data science and AI.
Real-world methods for supply chain and operations management professionals who want to go beyond Excel — with reproducible code, realistic datasets, and techniques you can apply today.
Newest Entries
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AI Model Distillation, Explained: The Compression Trick Behind the $589 Billion Monday
A single Chinese app knocked $589 billion off Nvidia in one day. The trick…
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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…
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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.
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Quantity Discount Analysis: The Hidden Trap in Supplier Pricing That Most Buyers Miss
A supplier offers lower prices for larger orders — sounds great, right? Quantity Discount Analysis reveals that many discount schedules actually charge you more per incremental unit as volumes rise. Learn to spot this hidden trap with R.
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The Bullwhip Effect: Why a 10% Demand Blip Becomes a 400% Supply Chain Earthquake
A small wobble in customer demand can snowball into chaos upstream. We quantify the bullwhip effect with R, simulate a 4-tier supply chain, and show why cutting lead time is the single most powerful lever you have.
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Time Series Analysis for Supply Chain Management: Reading the Rhythm of Demand
Your demand data is trying to tell you something. We use STL decomposition, seasonal diagnostics, and ETS/ARIMA models to extract trend, seasonality, and noise from ice cream sales data — then honestly discuss where these methods break down.
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How Dynamic Buffer Management Works in DDMRP
DDMRP replaces static safety stock with dynamic, color-coded buffers that expand and contract with actual demand. This post explains the math, the logic, and the R code behind buffer sizing, net flow position, and demand-driven replenishment.
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Don’t Push Your Suppliers — Pull Them!
How implementing Demand Driven MRP (DDMRP) transformed supplier lead times, reduced on-hand inventory, and brought lean pull principles to life in our supply chain.
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Advantages of R and Python over Excel
Twelve compelling reasons why R and Python outperform Excel for data analysis — and practical advice on making the transition from spreadsheets to code-based analytics.