The old man and the hammer: Knowing where to tap 

I’ve been using this parable in workshops for the best part of three decades. I’m not remotely tired of it – mainly because every few years the world changes just enough to make it feel newly urgent. This is the 2026 version. Originally published July 2016 “Rethinking the parable of the old man, the hammer and the broken engine”

Knowing where to tap

You will have heard this one. If not, you are about to. Either way, I think it is worth sitting with it again.

A giant engine in a factory failed. The owners had tried several experts. None could fix it.  Eventually they brought in an old man who had been fixing engines for decades. He inspected the machine for a minute or two, pulled a hammer from his bag, and tapped it – gently, precisely – in one specific spot.  Immediately, the engine roared back to life.  A week later, the invoice arrived:

Tapping with a hammer	£2.00
Knowing where to tap	£9,998.00
Total:	£10,000.00

The owners were, the story tells us, flabbergasted.

The standard moral – that knowing where to look is worth more than how long you spend looking – is entirely correct as far as it goes. But it has always struck me that it doesn’t go nearly far enough.

I first wrote about this parable in 2016, and I confess I did not expect many people to read it. Apparently, I was wrong – it has become our most visited page by some margin and shows no sign of slowing down. I think that tells us something: people are still wrestling with how to demonstrate the value of expertise, how to price it, how to develop it. Those questions are not just alive in 2026 – they are louder. Let me explain why.

Lesson 1: “Knowing where to tap” – structured thinking when everything thinks it can ‘think’

The old man walked into a factory and looked at one machine. Simple enough. The consultant or adviser walking into a client in 2026 faces something rather different: a proliferating ecosystem of dashboards, AI-generated summaries, competing data streams and a leadership team each convinced their own read of the numbers is the correct one.

My background is in psychology, and one of the most durable findings in cognitive science is that more information does not reliably produce better decisions. The effect is well-documented: beyond a certain threshold, additional data increases confidence without improving accuracy. The digital age has not solved that problem. If anything, it has turbocharged it.

What has changed most significantly is where the noise now comes from. In 2016 we worried about information overload from data sets. In 2026 we face something subtler: analysis that arrives pre-packaged and confident, generated at speed by AI tools that cannot always be interrogated about their assumptions or sources. The output looks authoritative. It may be. The problem is that it may not be, and it is very hard to tell from the surface.

I have noticed in our programmes that the consultants who navigate this best are not, on the whole, the ones who are quickest to generate analysis. They are the ones who pause longest at the beginning. They insist on defining precisely what question they are trying to answer before they reach for any tool – AI-powered or otherwise. The structured analytical thinking process is not a constraint on good consulting. In a world of instant-output AI, it is the thing that makes good consulting possible.

The old man did not run a search query. He looked at the machine, in front of him, with the full weight of what he knew. That discipline – slow, deliberate, grounded in the specific situation rather than a generalised model – is not becoming obsolete. It is becoming rare, which is another way of saying it is becoming valuable.

Lesson 2: Prior knowledge is not always an advantage and experienced people are particularly at risk

I want to be careful here, because this point is sometimes used as an excuse to discount experience – which is not what I mean at all. But there is a real trap for people who have been doing this for a long time, and I include myself in that category.

I spent time before Openside in strategy consulting. The most dangerous moments I can remember – the ones where we came closest to recommending something genuinely wrong – were not the ones where we lacked experience. They were the ones where we had too much of it. Where the pattern recognition kicked in so fast that we stopped asking whether this situation was really the same as the last one.

The psychological literature on this is clear enough. Experts are prone to what is sometimes called ‘confirmation bias at speed’ – they process incoming data through the filter of what they already believe, and do so more quickly and more selectively than novices. The novice at least looks carefully, because they have nothing else to go on. The expert may have stopped looking without realising it.

Consider how much the operating environment for professional services has shifted since even 2019. Remote and hybrid work, AI-assisted analysis and delivery, platform-based consulting models, a generation of buyers who started their careers in the post-financial-crisis world and have entirely different expectations about what an adviser is actually for. The old man’s machine has been modified. The confident tap in the familiar spot may do nothing at all – or worse.

The value of experience is not the patterns it has stored. It is the judgment to know when a new situation does not match the stored patterns. That distinction matters, and it is one of the things that deliberate, well-designed training helps people develop – not because training replaces experience, but because it builds the critical distance that experience alone does not always produce.

Lesson 3: “Hit here” – simplification is still the job, and AI has made it harder, not easier

The question I am asked most frequently in conversations with managing partners at the moment is a version of: If AI can do the analysis, what are we actually selling? It is a fair question, asked with genuine anxiety. My answer is always the same: the old man did not sell analysis. He implemented a recommendation based on a conclusion.

The movement from complexity to a single, clear, actionable recommendation is a deeply human act. It requires you to weigh things that cannot be quantified – client culture, political reality, timing, risk appetite, what the organisation can actually absorb – and to arrive somewhere definite. Not ‘on the one hand… on the other hand’, but ‘do this, here, now, for these reasons’.

AI is exceptionally capable at the early stages of that process: gathering information, identifying patterns, generating options. It is considerably less capable at the final stage, which is the one clients are actually paying for. The advisers I see doing well are not the ones who feel threatened by AI-generated analysis. They are the ones who use it to get to the diagnosis faster, and then invest the time that creates in the human work: building the argument, reading the room, earning the trust that makes a recommendation land rather than get filed away.

The old man’s invoice did not charge for the complexity he had absorbed. It charged for the simplicity he produced. That simplicity is considerably more valuable – and considerably harder to produce – when everyone in the room has already seen three AI-generated analyses that all say something slightly different.

Lesson 4: “None of the experts could show them how” – business development is still a behavioural problem, whatever the tools say

The factory owners chose the old man. Several equally credentialled experts were passed over. Why? The parable doesn’t tell us exactly, but working backwards from the result, one has to assume he demonstrated something the others didn’t. He showed them, in the critical moments before any work began, that he understood their specific problem and had a credible path to solving it.

I have been working with professional services firms on business development behaviours for thirty-five years, and the digital transformation of the last decade has produced an interesting paradox. Firms have never had more ways to broadcast their expertise: thought leadership, webinars, AI-personalised content, digital marketing funnels, proposal tools that generate polished documents in minutes. The infrastructure for demonstrating capability has never been more sophisticated. And yet, the firms that consistently win the engagements they deserve are still winning them in the same way they always have: through the quality of the conversation. The questions they ask. The points of view they offer without being prompted. The intellectual confidence that says, ‘we have thought about your situation specifically, and here is what we think’. None of that is in the proposal tool.

The digital tools are excellent at reaching a large audience. They are a poor substitute for the advisory conversation that actually converts. If anything, as proposals and positioning documents become more polished and homogeneous – partly through AI – the moments of genuine human dialogue stand out even more. The old man, I suspect, said something in his first five minutes with the factory owners that the other experts didn’t.

Lesson 5: The invoice shock – and why the value conversation matters more than ever

The factory owners were flabbergasted. I have always found this the most psychologically interesting part of the story. The engine was running. They had got exactly what they wanted. And yet the bill felt wrong.

The reason, of course, is that the old man never had the conversation. He didn’t establish, before the engagement, what the problem was actually costing them – the daily revenue lost, the contracts at risk, the reputational damage accumulating. If he had, £10,000 would have seemed modest. Instead, all they had to anchor on was a man who tapped something with a hammer. Two pounds’ worth of effort. Nine thousand, nine hundred and ninety-eight pounds of presumed cheek.

The pricing environment in professional services in 2026 has added a new layer of complexity to this. Clients now arrive at the first conversation already anchored. An AI has benchmarked the engagement before they walked in. Three articles about comparable projects have been read. There is a number in their head and it was probably not arrived at by sitting quietly and thinking about what it would actually be worth to have their problem solved.

The right conversation is not ‘here is what we will do and here is what it costs’. It is ‘what is this situation costing you, and what would it mean to your business if we resolved it completely?’ That conversation, conducted early and honestly, changes everything about how the eventual invoice is received. The old man’s invoice wasn’t wrong. His sequence was.

So what is the moral of the updated story?

I think the reason this parable keeps attracting readers is that it captures an anxiety that has not gone away: the anxiety of paying for something you cannot see or touch, of trusting expertise you cannot independently verify, of being asked to commit to value before it has been created. That anxiety predates the internet, and it will outlast AI.

What has changed is the environment in which that expertise operates. The analytical tools are more powerful and more accessible. The data is richer and more treacherous. The client is better informed and less easily impressed by credentials. The window in which a firm demonstrates genuine understanding – as opposed to generic capability – has got shorter.

This is precisely why I believe in training more firmly now than I did when I first wrote this piece – not the accumulation of experience, which the old man had in abundance. Deliberate, structured development of the specific skills the modern context demands: analytical rigour, critical thinking that holds its own assumptions to account, advisory behaviours that earn trust rather than assume it, and the ability to articulate value in language the client actually uses.

The firms I have seen navigate the last decade well are not the ones that bought the best AI tools, or produced the most impressive thought leadership. They are the ones that invested consistently in developing the judgment, the communication skills and the commercial instincts of their people. Those things do not emerge by accident or accumulate naturally with seniority. They have to be built.

The hammer is not the point. It never was. Knowing where to tap is. And that kind of knowledge doesn’t happen by accident – it takes deliberate practice, honest feedback and the willingness to keep learning long after you think you already know.