The word that ate itself

Why value is the hardest thing to define and what delivery leads can do about it

Toronto waterfront, April 2017, visiting friends in the city. The grain silos of the Canada Malting Company and the CN Tower.

Imagine two people doing the same job.

Same seniority, same type of organisation, similar scope. Ask them both whether they are delivering value and you will get completely different answers.

One is confident: they know what they are there to do and they are doing it.

The other is not sure at all. They are working hard, they are busy, but whether any of it amounts to value — they cannot say.

Same work. Opposite reads.

I have been thinking about this a lot recently. I am part of a team running a very large digital transformation programme over 4 years, and one of the things we are trying to build as a sense-making tool is a value management framework — a way of making decisions about where to invest across a complex portfolio of work.

To do that, we need a shared definition of what value means. Business value, the kind that appears in a business case. Indirect value, the things the programme creates that sit outside it. Intangible value, the kind that matters to people but resists measurement.

Getting those into a single working definition has turned out to be one of the gnarlier problems we are facing. Because value is hard to pin down. And what we are dealing with is a microcosm of what every organisation faces: scarce resource, competing demand, and a word that everybody uses constantly but that has no clear definition.

That word is the subject of this essay.

The thought experiment at the top points at something structural. The two people are not reading their situation differently because one is more perceptive or more confident. They are both operating under the same assumption, that value is a real, legible thing that can be identified and measured — without either of them having stopped to ask whether that assumption holds true.

It largely does not.

Value is not an objective property of work. It is a judgment, shaped by who is making it, what they care about, and what context they are operating inside. The fallacy is not that organisations fail to define it precisely enough. The fallacy is believing that a precise, shared definition is available to find. For most organisations, the definition is loose at best. Often it is something closer to a collective agreement to stop asking the question.

To be clear: at the macro level, organisations do have a definition of value. Revenue, profit, return on investment — these are well understood, rigorously tracked, and the basis on which capital gets allocated. That definition is not the problem. The problem is that it does not travel. The line from what a team does on a given day to what appears in a quarterly earnings report is long, indirect, and in most organisations almost impossible to draw with any confidence.

When a word means everything at the macro level and almost nothing at the level where the work actually happens, it stops being useful as a guide.

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The gap is structural

The distance between the macro definition of value and the work any individual or team does day to day is not a communication problem or a prioritisation problem. It is a structural feature of how organisations operate, and it is largely unsolvable in the way people tend to assume.

Value ladders are a typical standard response. The idea is that you can trace a line from any piece of work upwards through the organisation until it connects to something the business cares about at the top. Map the activities, identify the outputs, define the outcomes, link them to the strategic objectives.

In practice, the further down the chain you go, the weaker that line gets. By the time you are asking a team to connect their sprint output to an organisational KPI, the relationship between the two is so indirect, so dependent on variables outside anyone’s control, that the connection is more of a story than a proof. It tells you something plausible about how the work might matter. It does not tell you whether it does.

A lot of people in knowledge work spend their careers in that gap — expected to create value, held accountable for it, asked to demonstrate it, in an environment where the connection between their work and the measure the organisation actually uses is very hard to establish. It is what happens when you ask people to draw a line that does not exist in a straight form.

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The output trap

Because value is hard to define and harder to measure, organisations do something rational: they start measuring what they can see instead.

Outputs are visible. They are countable, attributable, and defensible in a governance conversation. Outcomes are uncertain, delayed, and shared across too many variables to pin on any one team or decision. When the pressure is on — a quarterly review, a board update, a business case renewal — people reach for what they can count. The result is measuring the wrong thing with great precision.

The economist Charles Goodhart observed this in monetary policy in 1975. When a measure becomes a target, it ceases to be a good measure. The moment you start optimising for the metric, the metric stops telling you what it used to tell you. People are not gaming the system out of bad faith. They are responding rationally to the incentives in front of them.

NHS waiting list optimisation (arguably) sits here. The NHS tracks both the number of people waiting for elective hospital treatment and how long they have been waiting. These are clear, measurable objectives, and there are reasonable grounds for them: longer waits probably do correlate with worse patient outcomes and worse experience. But the focus on the numbers can drift from being a proxy for patient wellbeing into being the thing itself.

Teams optimise for the list rather than the patient behind it. The measures are not wrong. The problem is what happens when hitting them starts to substitute for asking whether the underlying goal is being met.

The same pattern shows up more locally. Many organisations have a well-intentioned focus on celebrating achievements — recognising work, building momentum, making people feel that what they do matters. The risk is when achievement reporting slides into activity reporting: volumes of things, numbers of things happening, outputs that are hard to connect to any meaningful so what. Celebrating activity is not the same as demonstrating value, but in the moment it can feel indistinguishable.

There is also an assumption running underneath a lot of knowledge work culture that effort and value are correlated — that working harder, longer, and more visibly produces more of what the organisation needs.

For many people this is subconscious; they are not consciously equating the two, but behave as if they are, often without realising it. Recognising that the correlation is weak at best, and often absent, is useful. A delivery lead who has one conversation that unblocks a programme has created more value than one who spent the same week producing a detailed report nobody acted on. The report is there. The conversation is not. In many organisations the report gets recognised more readily, for exactly that reason.

Large language model-based AI tools allow teams to generate code, documents, analysis, and plans at a speed that would have been impossible with human effort alone. That paradoxically increases the stakes around value definition. In a world where knowledge and information can be produced at orders of magnitude less cost than before, the question of what is actually worth producing becomes more important, not less. The output trap does not disappear when output gets cheaper. It gets harder to escape.

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What the delivery lead can actually do

If you are a delivery lead, or in any management role where you are largely hands-off and depending on your team to do the work, the value question becomes even more indirect. The line from what you do each day to what the organisation values is longer and harder to trace than it is for someone making things directly.

The agile movement has something of an answer: remove impediments, optimise flow, use data, protect the team from noise. That is real, and useful. It tends to lean more on process than value though.

You can probably describe your activities clearly — the meetings you ran, the risks you managed, the decisions you facilitated. What is harder is articulating what those activities were actually worth to the programme, the department, or the organisation.

The performance conversation is where this gap surfaces: you are asked what value you delivered and you find yourself describing what you did instead. That requires knowing what the role is actually for in your specific context, and what a good version of it looks like — clearly enough to defend it, not just say it.

Make value definition an explicit act at the start of a programme or workstream, rather than something inherited from a business case and never revisited. The question to ask — of yourself and the people around you — is not just “what are we trying to do?” but “what would good look like, for whom, and how will we know?” Those are different questions.

The gap between them is where some teams lose their way. People would rather crack on and execute than stay with not yet knowing what success actually means. Staying with that ambiguity a little longer is usually the better investment.

Your stakeholder audience will not agree on what value means, and looking for the single argument that satisfies everyone is a search that rarely ends well. A finance stakeholder, a product owner, and a programme director are evaluating different things when they look at the same piece of work.

The skill is translation: understanding what each audience values and framing the same work differently for each of them, without changing what the work actually is. Some might call this spin or corporate theatre. It is recognising that value is always assessed from a particular vantage point, and that meeting people where they stand is more productive than asking them to adopt yours.

When outcome definition is genuinely uncertain — which in complex programmes it often is — build for learning rather than pretend to a confidence you do not have. A case built on projected outcomes that nobody quite believes is fragile. A case built on what you will learn, by when, and what decisions that will enable is more defensible and usually more persuasive.

Peter Senge argued in The Fifth Discipline that organisations best equipped to operate in uncertain environments treat learning as a core capability rather than a by-product of delivery. In conditions where you cannot define value upfront with confidence, designing for discovery is the right answer.

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Close

We will keep talking about value. We will keep debating what it really means, writing it into business cases, referencing it in performance conversations, and circling back to it in meetings where nobody quite agrees.

It is structural, it is inherent, and it is subjective in ways that do not resolve cleanly regardless of how much effort goes into the definition.

Navigating that is not about finding a cleaner answer. It is about not waiting for one. Building a working definition for your own context, being confident enough in it to act on it, and being able to defend it clearly when asked — that is what operating well inside this ambiguity actually looks like.

For a delivery lead, making value legible — locally, for the people who need to understand it — is a core part of the job. It is not always made explicit. But it should be.

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Drop me a comment below — what does value mean in your current context, or what is it most often confused with?

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Thinking Delivery is a weekly essay on delivery leadership, AI, and the craft of navigating complex organisations. If you are not subscribed, you can do that below and get a fresh essay in your inbox every Sunday morning.

Olli Drury is Head of Delivery at NHS England, with fifteen years in the delivery leadership trenches across travel, financial services, fintech, retail, and more — in agencies, consultancies, and now (finally) client-side.