At the LCS conference Oliver Conger took us back to the 9th September 2016, the day his first son was born. Forty minutes later, his phone was ringing off the hook.
It was one of his biggest customers, in the Middle East, demanding to know where a huge order was. Oliver called his factory in South Wales and nobody knew. Nobody could say when that customer, or any other, would get what they’d ordered. The next morning, instead of being at home with his wife and newborn, he was back in the office.
That was his rock bottom. Almost a decade on, his business has cut the front end of one ordering process to under 60 seconds using automation and AI. Yet as he told the LCS Conference 2026, the technology wasn’t where the transformation started. Lean and AI worked because they came in the right order.
Oliver’s closing keynote included one of the most striking examples of the day.
In one of his processes, he described how a purchase order would arrive and be loaded by the sales team, engineering would then create a drawing and someone on the shop floor would program the CNC machine, cut the metal, test it, inspect it and pack it.
End to end, it took six weeks.
Lean came first and through a series of improvements, the team cut that lead time to three days. Only then did they turn to the admin at the front end. Today, an order lands in the inbox and nobody touches it until the metal is cut. In under 60 seconds, the order is loaded, the drawing is created and the machine code is ready.
“Lean is the basis. It’s like turbochargers, AI… it’s like putting it on steroids because you’ve got all your processes nailed down.” Oliver Conger
Another speaker described the automation wastage. Linda Spinks, Continuous Improvement Leader at the University of Cambridge, first came to CI as a business analyst implementing a student system. What it taught her, she said, was that “we were very good at implementing expensive tech on top of not so great process.”
It’s a pattern many CI professionals will recognise, and AI makes the risk bigger. If you put a fast, powerful tool on top of a confused process and you don’t remove the waste, you scale it.
When a delegate asked Oliver how his business avoids compounding waste with automation and AI, his answer was clear. Teams have to prove they’ve leaned a process as much as possible before automating it. Automation is the last step, not the first and there’s a simple rule he has implemented: “We don’t touch anything unless it’s got a productivity gain.”
He’d learned that the hard way. When everyone in the business started experimenting with AI, the main result was what he called “email slop”: longer, flowerier messages that added nothing. The lesson wasn’t that AI doesn’t work. It was that AI without a clear purpose creates its own kind of waste.
Oliver visits a lot of businesses, from companies with ten people to those with 100,000. What he sees, he said, is AI “not being used in any coordinated fashion.” His conclusion: “people need to have a proper strategy on AI.”
His own strategy started with a vision. Oliver had shared a detailed picture of where he wanted the business to be in five years. His head of AI and Automation took that and wrote his own version for automation. Three years ago, the business had no robots, no automation and no use of AI, yet today it runs three automation pillars: physical, AI and data. It was one of five UK businesses selected to partner with AWS, and the Welsh Government now wants to use it as an AI exemplar for Wales.
Crucially, it didn’t start with the technology. Instead it started with clear processes and a clear direction, and the technology followed.
Catrin Archer, who leads the Lean Competency System, told delegates that AI is beginning to completely change the profession. That raises an understandable fear. If AI can analyse processes and automate tasks, where does that leave the people who improve them?
Leon Hardwick, who heads OpX’s software division, argued the opposite. CI professionals, he said, are going to become “even more valuable as we move into this automated AI world.” When organisations push into automation and AI, “they’re going to need the gaps to be filled. And you guys are the ones that understand where the gaps are and what the information in those gaps actually means to the business.”
People benefit too. On one of Oliver’s lines, a colleague called Molly used to spend her days putting orders through by hand. Once that was automated, she upskilled and is now one of the business’s best planners. Her verdict, as Oliver told it: thank goodness that boring old job had gone.
Computacenter’s Managed Services team won the Digital and AI-Enabled Improvement award at the LCS Awards 2026 for its “Triple A” approach: analytics, automation and AI, built on a Lean and CI culture. Its award entry is clear about the purpose. The tools are there to strengthen Lean thinking, not replace it.
The team learned the same lesson as Oliver. Early conversations focused on moving fast with automation and AI, but teams soon recognised they needed to document processes and create standards first. Today, its CI team helps teams “pick the right problems (and data) before anyone automates.”
In one service desk example, CI Champions spotted voice handling times creeping up by around 2% a month while customer sentiment fell. Using DMAIC, with AI speeding up the analysis, they traced the root cause to a complex password reset process with no self-service option. The fixes, including AI-powered self-service, cut handling time by 5%, saving 68 hours, and improved sentiment scores.
People stay in charge throughout. When the team introduced AI call routing, its biggest fear was overloading its best analysts, so it added workload balancing to protect them. As the awards entry puts it, “it is vitally important that a person retains accountability for choosing solutions.”
The organisations best placed to benefit from AI may not be the ones with the biggest technology budgets. They may be the ones that already know how to understand a process, solve problems and create clarity.
That’s exactly what continuous improvement teaches. Before you automate anything, ask whether the process deserves to exist in its current form. Fix it first. Then let AI make it fly.
This article is part of our series on the big themes from the LCS Conference 2026. Read the first: Scaling Continuous Improvement: What Happens When Your CI Team Disappears?
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