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Mathnal Insights · 9 Free Issues

The Supply Chain AI Newsletter for People Who Build Decisions from Evidence

Mathnal Insights publishes long-form, technical deep-dives on supply chain AI, Bayesian risk, ML forecasting, optimisation, ESG/Scope 3, and geopolitics. Authored by Krish Naidu, founder of Mathnal Analytics. Read every issue free — no signup required.

What is Mathnal Insights

Mathnal Insights is the free technical newsletter from Mathnal Analytics covering supply chain AI, machine learning, Bayesian risk, mathematical optimisation, ESG/Scope 3 compliance and geopolitical supply chain risk. 9 issues are currently published, each 1,500-4,000 words with formulas, Python code references and quantified case studies.

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9 deep-dives on supply chain AI & risk

Each issue is technical, formula-rich and based on real case data. Ordered newest first.

Issue #09 · ESG & Compliance

ESG & Scope 3 Greenwashing — Are You Compliant or Exposed?

Six regulations now police Scope 3 greenwashing: EU CSRD (mandatory from FY2025), CBAM (full 2026), SEC Climate Rule, EU Green Claims Directive, ISSB IFRS S2, UK Green Claims Code. Penalties reach 5% of global turnover. Full disclosure mapping and supply chain data needs.

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Issue #08 · Inventory

Safety Stock Decision Matrix — When to Hold, Minimise, or Eliminate

Use the ABC × XYZ × Frequency matrix to decide when to hold, minimise or eliminate safety stock. High-value (A) high-variability (Z) low-frequency SKUs need lean make-to-order. Low-value (C) stable (X) high-frequency SKUs warrant generous safety stock. All 27 cell-level policies with formulas.

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Issue #07 · ML & AI

How ML & AI Transform Every Supply Chain Function

Function-by-function map: demand sensing (LSTM/TFT/TimeGPT), inventory (Bayesian + RL), transport (VRP + GNN), procurement (agentic negotiation), warehousing (vision + slotting), S&OP (LLM consensus). Each capability tied to ROI and recommended ML toolkit.

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Issue #06 · Formulas

15 Supply Chain Formulas Every Planner Must Know

Safety stock, reorder point, EOQ, service level (cycle), fill rate, inventory turnover, days of supply, MAPE, wMAPE, RMSE, OEE, perfect order, cash-to-cash, takt time, forecast bias. Each formula with units, interpretation and a Python one-liner.

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Issue #05 · Forecasting

Forecast Bias & Errors: 12 Metrics Complete Guide

Definitions and contrasts for 12 forecast accuracy metrics: MAPE, wMAPE, sMAPE, RMSE, MAE, MASE, MAD, ME (bias), MPE, Tracking Signal, FVA, Theil's U. Each with formula, when it misleads, and recommended excellent/good/poor thresholds.

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Issue #03 · Risk

10 Supply Chain Risks 2026-2030 & KPI Impact Matrix

Geopolitical conflict, climate disruption, supplier concentration, cyber, regulatory (CSRD/CBAM), demand volatility, talent gaps, technology debt, financial shock, ESG/reputation. Each mapped to KPIs (OTIF, fill rate, MAPE, inventory days, Scope 3, cycle time) with impact ranges.

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Issue #02 · Bayesian

Bayesian Statistics for Stockout Optimisation

Updating P(stockout) as new evidence arrives. Using odds-form Bayes: posterior_odds = prior_odds × likelihood_ratio. How to set priors, calibrate likelihoods from lead-time data, and translate posterior P(stockout) into safety-stock decisions — with Python worked examples.

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Issue #01 · Geopolitics

Supply Chain Wins Wars — Hormuz, Drones & Military Logistics

Modern wars are won by supply chains, not soldiers. How the Strait of Hormuz blockade, drone economics ($500 drones vs $2M missiles) and military logistics shape geopolitical outcomes — and what SC leaders should learn about resilience, dual-sourcing and route redundancy.

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