How AI Makes for Better Supply Chain Decisions
Supply Chain Unchained
A supply chain consultant and University of Sydney lecturer with nearly 30 years of experience breaks down how decisions actually get made in supply chains, where AI fits in, and the one question every supply chain manager should be asking before touching any technology.
Most supply chain teams are making thousands of decisions every day, and most of those decisions are based on gut feel, spreadsheets, or incomplete handoffs between departments. In this episode, Greg sits down with Elton Brown, consultant at DMS (Demand Management Systems) and creator of supplychainmaturityscore.com, to explore how AI can help supply chain professionals move from reactive to predictive, and from descriptive to prescriptive.
Elton lectures on intelligent supply chains and AI applications at the University of Sydney Business School, and brings a grounded, practical perspective to a topic that is often buried in hype. The conversation covers where AI is actually working in supply chains right now, why freight forwarding has one of the biggest digitisation opportunities of any industry, and how to start your AI journey without a big budget.
What We Cover
- How supply chain decisions are made across three horizons, strategic, tactical, and operational, and why disconnected planning across those levels creates waste throughout the chain
- The four types of analytics: descriptive (what happened), diagnostic (why it happened), predictive (what will happen), and prescriptive (what to do), and why most organisations are stuck at descriptive
- Why spreadsheets and transaction systems are only ever backward-looking, and what that means for decision-making in an increasingly uncertain world
- The concept of connected planning: aligning micro decisions at the operational level with tactical and strategic intent so the supply chain stops working against itself
- Where AI is genuinely working right now: demand sensing, inventory optimisation, exception management, and real-time risk monitoring using generative AI
- Why freight forwarding has one of the greatest digitisation opportunities in the entire supply chain, and why getting off paper is the essential first step before AI can add value
- The difference between narrow AI, machine learning models, and generative AI, and which problems each is suited to
- Why you should never start with the technology: start with the decision problem, where are decisions slow, difficult, or inaccurate, and then find the AI that fits
- How to use a large language model like ChatGPT or Claude today, even without a budget, to start making probabilistic rather than deterministic forecasts
- What the Supply Chain Maturity Score is, how it works across five dimensions (people, process, technology, strategy, collaboration), and why it is free and takes five minutes
- Elton’s closing advice for anyone starting out in supply chain today: AI is not coming for your job, it is coming for your job description
Guest
Elton Brown
Consultant, DMS (Demand Management Systems)
Creator, supplychainmaturityscore.com. Lecturer, Intelligent Supply Chains and AI Applications, University of Sydney Business School. Nearly 30 years in supply chain
“Where are the areas where decisions are difficult or slow or inaccurate? Because AI is primarily for supply chains for making better decisions faster.”
Elton Brown, Consultant, DMS
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