Where It All Starts – Seeing the Whole Process

Anyone who has run a Six Sigma project knows the power of mapping a process properly. The old SIPOC diagram—Supplier, Input, Process, Output, Customer—has guided improvement work for decades. It forces you to see the big picture, not just your own piece of it.

When I first introduced SIPOC frameworks at GE and later at Honeywell, the goal was always to trace how upstream activity shaped downstream outcomes. That principle hasn’t changed. What has changed is how AI can now bring those relationships to life.

Machine learning algorithms can monitor thousands of process variables simultaneously, spotting subtle trends long before they cause visible issues. What used to take weeks of analysis can now happen in minutes. SIPOC has evolved from a static sketch to a living model—a digital twin that can predict where variation will appear before it reaches the customer.

Balancing Measures – Smarter, Not Harder

In the early days of Six Sigma deployment at GE, we used to spend hours balancing our measures: inputs, process, and outputs. That balance remains crucial, but now AI is doing much of the heavy lifting.

Predictive analytics can warn you when supplier data looks off, long before it impacts quality or delivery. Process control systems can self-adjust, maintaining consistency without human intervention. Instead of reacting to problems, we’re designing systems that prevent them automatically.

That’s a big shift—from measuring performance to managing by exception. It frees teams to focus on solving higher-value problems and drives operational resilience at every level.

From Walking the Floor to Walking the Data

One of my favourite Lean exercises has always been process stapling—literally following a customer order or a production job through every step, from start to finish. I’ve done this in factories, hospitals, and telecoms centres. It’s simple, and it’s powerful, because it shows you what really happens.

Today, AI lets us do that virtually. Using process mining and digital simulation, we can “walk” millions of transactions and instantly see where bottlenecks, delays, or errors occur. It’s like combining the discipline of a gemba walk with the power of advanced analytics.

Of course, the key is still curiosity. AI gives you data, but insight still comes from asking why. The technology enhances Lean thinking—it doesn’t replace it.

Working with Suppliers – Building Intelligent Partnerships

I’ve seen firsthand what happens when organisations choose suppliers purely on cost. It rarely ends well. True excellence comes from partnership—where you and your suppliers understand each other’s processes, data, and goals.

AI now allows that collaboration to happen on a whole new level. Companies like Airbus and Sodexo, for example, are starting to link supplier performance metrics directly into shared analytics platforms. Everyone sees the same data, the same risks, and can work together to fix issues before they escalate.

This level of transparency builds trust and turns suppliers into active contributors to performance, not just providers of parts or services. It’s a genuine shift from transactional to transformational relationships.

AI, Lean, and Six Sigma – The New Operational Triangle

I often describe Lean, Six Sigma, and AI as the new operational excellence triangle.

• Lean still gives us the mindset for eliminating waste.

• Six Sigma provides the structure for reducing variation.

• AI supplies the real-time intelligence that makes both continuous and scalable.

Together, they form a system that doesn’t just perform well—it learns. It adapts, self-corrects, and evolves.

At Game Change, we’re already helping organisations build this integration—training leaders and teams to use data science tools alongside classic Six Sigma methods. It’s not about replacing experience with algorithms, but combining both to achieve levels of performance that weren’t possible even a few years ago.

Never Forget the Human Element

No matter how advanced the tools become, people remain at the heart of improvement. AI might tell us what is happening, but it’s human intuition and experience that uncover why it happens and how to fix it sustainably.

After all these years, I’ve learned that culture, not technology, is what makes or breaks transformation. You can have all the digital dashboards in the world, but without trust, communication, and shared purpose, nothing changes.

The organisations that get it right—those like GE, Honeywell, and the many clients I’ve worked with across Europe—know that operational excellence is never a project. It’s a way of thinking. And AI, when used wisely, is the next step in that evolution.

The Future of the AI Lean Six Sigma Supply Chain

The future supply chain isn’t just efficient—it’s intelligent. It can sense, predict, and respond. It’s powered by AI, guided by Lean, and stabilised by Six Sigma. And most importantly, it’s built on collaboration, trust, and data-driven leadership.

As practitioners, we now have tools that can elevate everything we’ve learned over the past 25 years. The challenge is to use them thoughtfully—to combine the precision of technology with the wisdom of experience.

That’s how we’ll build the next generation of high-performing, resilient, and human-centred supply chains.