How a national logistics company turned 2,000 employees into problem solvers
Profit impact
+£150M growth
Driven by operational efficiency
EBITDA
+40%
Within 18 months
Ops monitoring
AI exception surfacing
Near zero manual
Escalation time
10-minute self-service
95% faster
The Frustration
The Head of Operations could see the opportunity. AI could transform how 2,000 people across the network managed exceptions, tracked performance, and made decisions. But the frontline teams were buried in the day-to-day. Senior managers were skeptical. The CTO had built internal tools that nobody was using. Every meeting about AI ended with agreement in principle and zero action.
The Turning Point
When a competitor automated their last-mile routing and cut delivery costs by 18%, the board demanded a response. The problem wasn’t the technology. It was getting 2,000 people to change how they worked.
The Approach
We embedded at leadership level — two days a week, inside the business. Month one: mapped every high-cost workflow across operations, finance, and customer service. Interviewed 40+ frontline staff to find where the real resistance lived. Built a sequenced rollout plan tied directly to P&L impact. Month two onwards: hands-on sessions with each department. Not training courses. Real workflows, real problems, solved together.
This engagement used our Transformation Partner tier.
The honest bit
The ops team pushed back hard in the first two weeks. They’d seen “transformation initiatives” before and assumed this was another one that would generate a report and disappear. We had to earn trust by solving one small problem with them before they’d engage with the bigger picture.
The Results
Profit impact
Driven by operational efficiency
EBITDA
Within 18 months
Ops monitoring
Near zero manual
Escalation time
95% faster
“Our people went from waiting for instructions to solving problems themselves. That shift changed the entire culture, not just the numbers.”
Head of Operations
National logistics company
Why it stuck
We didn’t build AI systems for them. We taught their people to use AI on the problems they faced every day. The team became self-sustaining — and the gains kept compounding after we finished.
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