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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…
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Your AI Education Is Free: 29 Resources That Cost Nothing But Your Time
Your CEO just asked about your AI strategy. Here are 29 free resources — from Anthropic’s academy to Karpathy’s YouTube — organized by how you like to learn.
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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…
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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…
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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…
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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…
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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…
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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.
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Data Quality Assessment for ERP Systems
Master data quality is the foundation of every ERP system. Learn how to systematically assess and visualize data gaps using R before they undermine your operations.
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Sales Data Visualization: Beyond Pie Charts
Move beyond pie charts to more effective visualizations for sales data — waffle charts for proportions, seasonal decomposition for patterns, and interactive dashboards for forecasting.
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Network Analysis for Supply Chain Risk and Resilience
Your supply chain is a network. Graph theory and R’s igraph package reveal which nodes are critical, where single points of failure hide, and how disruptions propagate —…
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bupaR: The Process Mining Toolkit That Shows You How Your Factory Actually Runs
Your factory has a designed process and an actual process. bupaR — the open-source process mining suite for R — shows you the difference, and that difference is…
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Process Mining a Mobile Phone Assembly Line with bupaR
Using R’s bupaR ecosystem to analyze a smartphone assembly process — from creating event logs to discovering bottlenecks, rework patterns, and resource utilization.
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Five Data Science Capabilities That Transform Supply Chain Operations
Five concrete data science capabilities — from demand forecasting to anomaly detection — that deliver measurable improvements in supply chain planning, procurement, and logistics.
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