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Narahari Rao of SLB on implementing AI in supply chain: why bolting AI onto old processes is like plugging a motor into horse-and-carriage infrastructure, and why a successful supply chain should be invisible to the customer. The conversation covers the engineering mindset that makes for stronger procurement negotiators, why digitization doesn't require 100% clean data to get started, the case for narrow, edge-of-the-ERP use cases over full-process overhauls, and how to embed risk management directly into the workflow instead of leaving it stranded in a dashboard nobody opens.
🎧 Episode Highlights
[4:03] How an engineering mindset makes for strong procurement negotiators. You don't need the deep technical expertise, but you need to know enough.
[8:46] The digitization starting point. Harmonizing data across ERPs doesn't require 100% clean data. Roughly 70% good data is enough to begin.
[12:40] Thinking backward from the customer instead of function by function, and why procurement too often feels disconnected from who it ultimately serves.
[17:56] The Model T analogy. Why bolting AI onto an existing process just builds a better horse-drawn carriage instead of designing the automobile.
[23:06] Dashboards are where insights go to die. Why risk data still needs a human to interpret it, and where AI can actually help.
[29:33] Embedding risk management directly into the sourcing workflow, instead of asking buyers to jump between disconnected systems to connect the dots.
[34:14] The supplier outage story. A single hidden raw-material dependency shut down a "backup" supplier too, and what that reveals about the illusion of multi-sourcing.
[39:34] Building narrow, purpose-built AI agents for known risks. Hurricanes today, wildfires or cyber threats tomorrow.
[52:28] Lean roots at Toyota and why continuous improvement is a cultural shift, not a one-time initiative.
[55:22] The case for starting with front-line pain points. Small, fast wins build the ROI story before you attempt large-scale transformation.
🔑 Key Takeaways
· A successful supply chain is invisible to the customer. The product shows up at the right time, cost, and quality without the customer ever having to think about how it got there. That outcome, not process optimization for its own sake, should anchor every transformation decision.
· You don't need perfect data to start. Waiting for 100% clean, harmonized data before beginning a digitization journey is a common trap. Roughly 70% good data is enough to start building insight and momentum.
· Multi-sourcing isn't real risk mitigation if your suppliers share a hidden dependency. A "backup" supplier that draws from the same raw-material source, region, or single point of failure as your primary supplier isn't actually diversification. The risk is just one layer removed.
🧭 Frameworks Worth Saving
· Work backward from the customer, not forward from your function. Hari's approach to scoping any transformation: define who the customer actually is (internal or external), then work backward from what they need to experience through planning, sourcing, and logistics. The goal is resisting the pull to optimize each function in its own silo, disconnected from that end goal.
· Look at the edges of the ERP before rebuilding the core. Where Hari sees AI use cases pay off first: start with a narrow, well-defined question, like "when will this product show up at my desk?", and use existing ERP data, stepping slightly outside the walled garden to answer it, rather than optimizing the whole sourcing process before proving value at the edges.
· Embed risk management inside the workflow, not next to it. The pattern for making risk management usable at scale: build risk checks into the intake process itself rather than a separate tool buyers have to remember to check, avoid siloed systems that require manually connecting the dots across screens, and build a bespoke model matched to your company's policies and culture rather than tying yourself to a vendor's release schedule.
💬 Notable Quotes
A successful supply chain is one which makes the consumer not think about how that product actually showed up at their door.
Narahari Rao
You don't actually have to have 100% clean data before you actually progress on this journey.
Narahari Rao
Lean is not something you do just at your workplace. It's a cultural shift.
Narahari Rao
👤 About The Guest
Narahari Rao, Global Procurement Risk and Resilience Director, SLB
Narahari Rao is the Global Procurement Risk and Resilience Director at SLB, where he manages supply base risk across 30 global business units. With over 20 years of experience in supply chain, strategic sourcing, and engineering, he specializes in building resilient supply networks for complex global operations. He holds a Master of Science in Mechanical Engineering from Texas A&M University and is a Certified Lean Six Sigma Champion. Throughout his career, Narahari has led major digital transformations, SAP deployments, and process optimizations across global teams. He actively serves on the Editorial Board for the Lean Six Sigma review. Outside of his corporate role, he frequently speaks at industry conferences on supply chain strategy and operational excellence. He is a budding amateur astronomer and when he is not focused on risk management within Supply Chain, he is looking up at the stars and the galaxies that hold them.
🎙️ About The Host
Derek Aranda
Derek Aranda spent over two decades as a global executive operating across commercial, supply chain, and digital transformation roles at scale. That span across the full value chain shapes his lens: the decisions, incentives, trust, economics, and governance that determine whether technology actually works inside real supply chains. On Supply ChAInge, he pressure-tests the autonomous future and helps leaders shape the framework to build it on their own terms.
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Produced by Speakerbox Media.
