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The real risk of easy AI answers isn't that the tools surpass us, but that we lose the slow, uncertain exploration that makes answers stick and curiosity possible. When answers are this cheap, the scarce resource becomes the quality of our questions and the patience to stay with them.
Operational Excellence, Improvement, and Innovation
AI doesn't have to mean layoffs
There is a long-standing habit in organizations of measuring productivity almost entirely through the lens of labour cost. Fewer people, lower costs, better margins. It is a narrow view that has always left value on the table, and the current wave of AI adoption is making it narrower still.
Many organizations are not waiting for AI to deliver its promised gains before acting. They are pre-emptively eliminating roles, cutting headcount ahead of any evidence that the technology has actually improved how value gets created. They are absorbing the human cost before capturing the benefit, and calling it transformation.
Schneider Electric, with a global workforce of over 160,000 people, is making a different bet. Rather than using AI to reduce its people, the company is using it to elevate them. That means deploying AI to eliminate genuinely wasteful and non-value-added work, and to help teams crack problems that have resisted solution for years. One example: optimizing the process for “cooking” silver tips, the precision electrical contacts used in circuit breakers and switches, a technical challenge that had long defied easy answers.
The distinction matters. AI used to eliminate waste creates capacity. AI used to eliminate people creates fear. One builds an organization's capability to solve harder problems. The other hollows it out.
Leaders have a choice about which story they want to be part of. Schneider Electric is showing that the more ambitious path is also the more human one.
Has Lean really failed? Or are we asking the right question?
Critics of lean often ask “why hasn't the lean community created more ‘Toyotas'?” to offer proof that it “doesn't work”. It's a reasonable question, but a flawed criticism. For example, Toyota has taken many decades to develop its systems and culture, and rather than being a “destination”, is an organization in a state of continuous becoming. A hospital that dramatically reduces patient harm, or a manufacturer that halves its defect rate, is a lean success story even if it never appears on a business school case study.
Resolve the conflict between efficiency and resilience
Think about a hospital operating at 100% bed capacity. Everything runs smoothly, until it doesn't. A flu outbreak, a mass casualty event, an unexpected spike in admissions. With no slack in the system, there is nowhere to absorb the shock. Patients wait in hallways. Staff are overwhelmed. The system doesn't just strain, it fails.
The same dynamic plays out in supply chains, road networks, and manufacturing lines. Any system designed and operated for maximum utilization is optimized for the best case and catastrophically fragile in every other case.
I've worked across many different industries and while the details vary enormously, this principle holds almost universally: don't design your system for 100% utilization.
Deming understood this deeply. His work on systems thinking was a persistent reminder that optimizing individual parts of a system, squeezing every last drop of efficiency from every node, reliably produces a system that is worse overall. Slack, buffers, and the capacity to absorb unexpected fluctuation are not waste. They are the architecture of resilience.
The pressure to maximize utilization is real and often comes from legitimate places: financial constraints, shareholder expectations, competitive intensity. But operational excellence ultimately requires holding two things at once: the discipline to eliminate genuine waste, and the wisdom to protect the buffers that keep your system standing when things go sideways.
Creating a Culture of Improvement
How to hold onto your beloved organization
Fifteen years ago, Eric Ries gave leaders and founders a new playbook with The Lean Startup: start small, iterate fast, and scale what works. Many did exactly that, building valuable, meaningful organizations from the ground up. And then, quietly or sometimes suddenly, lost them.
Ries spent the years since observing this pattern and asking why. What he found is a paradox: the very qualities that make founders successful are the same qualities that make them vulnerable. Ries calls one of these mechanisms “financial gravity.” As companies grow, the pull of short-term financial performance becomes harder and harder to resist. Decisions that once centered on people and purpose slowly bend toward the numbers. And founders, often without realizing it, find themselves running something that no longer resembles what they set out to build.
His new book, Incorruptible: Why Good Companies Go Bad… and How Great Companies Stay Great is a warning and a guide for leaders who want to protect what they've created. The reminder at its core is uncomfortably simple: you are one meeting away from turning something you love into something you hate.
Ries joined Dave Stachowiak on Coaching for Leaders episode 784: How to Protect the Organization You Love, with Eric Ries, where they discussed the book, including concepts like redefining profit as “human flourishing”, and why viewing principles as opportunities rather than burdens helps protect your organization in the long term.
Small experiments, super teams
In the spring of 2022, the Oklahoma City Thunder sat near the bottom of the NBA standings after a grueling 58-loss season. What happened next became one of the more remarkable turnaround stories in recent sports history. They didn't chase a blockbuster outcome or overhaul everything at once. They got relentlessly better, incrementally, over time.
Ron Friedman, a psychologist and researcher who has spent his career studying high-performing teams, points to this kind of trajectory as the signature of what he calls a “superteam.” In a world where complexity is rising and organizations can no longer afford the long, slow cycles of team formation, the question of how good teams get great has never been more important. Friedman's research points to a consistent answer: superteams experiment often and stay focused on overcoming obstacles through continuous improvement rather than chasing grand outcomes.
Over 25 years of working across many different organizations and industries, I've seen this play out consistently. The best teams I've been part of or worked alongside are the ones that seek feedback constantly, run small experiments weekly or even daily, and rally around problems rather than avoid them. The worst teams I've encountered go to great lengths to sidestep problems, resist feedback, and preserve an artificial harmony that slowly hollows out their capability.
Continuous improvement isn't always exciting. Neither is compound interest. But both have a way of producing results that nothing else can match.
Coaching – Developing Self & Others
The cost of easy answers
Last week I wrote about the risk of reaching for AI before giving our own thinking a chance to work. Anne-Laure Le Cunff put her finger on exactly why this matters. A colleague told her he remembers the content of papers he wrote before AI tools far better than recent ones, and she recognized the feeling immediately. The journey of earning an answer through slow, uncertain exploration leaves a mark that easy answers simply don't. The deeper risk, she argues, isn't that AI becomes more capable than us. It's that when every gap in understanding gets filled instantly, we lose the conditions that make human curiosity possible in the first place. Her antidote is simple: delay the lookup, use AI to expand your thinking rather than replace it, and protect the unstructured time where slow and unexpected questions can actually emerge. When answers are this abundant, the scarce resource is the quality of your questions, and the willingness to stay with them long enough.
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