Global Services Director · Softcat plc Now booking — Q3 & Q4 2026 LinkedIn ↗
The manifesto — a thesis for the next service economy

The Human Operating Model.

Software will define the service. AI will run it. And human beings will be the reason customers choose yours. One argument about what replaces shift left, why the ticket is evidence of failure, and where people create value nothing else can — drawn from the operating floor of a £550M services business.

I. Software defines the service II. Humans differentiate it III. Shift right
01 — The claim

The industry's one big idea has expired.

For thirty years, the services industry has run on a single big idea: shift left. Push work towards cheaper resolution. Automate more. Deflect more. Keep humans away from demand. It was never foolish. In a labour-heavy, queue-driven world, it was a sensible optimisation. The problem is what happened next. We took an optimisation and turned it into doctrine — and once something becomes doctrine, people stop asking whether it is still the right answer.

Then AI arrived. And it did not beat shift left at its own game. It made the game irrelevant. When software can sense, decide and resolve before a human ever sees the problem, there is no "left" worth shifting towards. The cost question is answering itself.

Which leaves the question shift left was never designed to answer: where do human beings create value that nothing else can?

Not human as fallback. Human as differentiator.

That is the Human Operating Model. Not a framework to be certified in. An argument about how services should be designed, sold, delivered and led when software does the running and humans do the differentiating.

02 — Shift right

From the cost curve to the value curve.

Shift left moved work down the cost curve. Shift right moves people up the value curve — deliberately placing human attention at the moments of highest stakes, highest feeling and highest judgement. It is not another workflow diagram. It is an experience architecture. Four modes. Not tiers — modes.

i.

Self-heal by default

The problem resolves itself before the user knows it existed. AI operating within policy. Invisible, frictionless. The best service experience is the one nobody notices.

ii.

Guided self-help

The user needs to act, but they are not alone. Intelligence and the user working together to clarify intent and find resolution. Not a FAQ page. An intelligent conversation.

iii.

Assisted resolution

Human and AI together. The human validates, steers and exercises judgement; the AI carries the administration. Where complex and sensitive demand lives — because a human in the loop adds something automation cannot.

iv.

White-glove moments

Intentionally, fully human. Not because the automation ran out — because the situation demands it. Restoring confidence, exercising real judgement, showing genuine accountability. That is not a cost to be minimised. That is the value.

Underneath the four modes sits something the old model never had: a service sensor layer. Signals from users, from systems, from the business itself. Sensing, interpreting, deciding, changing — without waiting for a ticket to announce that something already went wrong.

By the time a ticket appears, the experience has already failed.

We have spent twenty years optimising what happens after the ticket arrives. The next-generation service organisation optimises to stop the ticket being needed in the first place.

03 — Software-defined services

The operating model becomes a product.

None of this survives as a slogan laid over a manual operation. Shift right is only honest when the routine genuinely disappears — and that requires the service itself to be defined in software. Provisioned in code. Assured by telemetry. Resolved by agents. Improved continuously, the way products are improved, not annually, the way documents are reviewed.

This is the part the industry keeps missing about AI. AI lands or stalls in the operating model. You cannot layer intelligence onto an unintelligent structure and expect transformation. Most operating models were built for a different problem — tickets, not flow; frameworks, not fluency; process compliance, not customer confidence. No amount of platform spend fixes that.

When the operating model is software, it stops being a diagram on a wall and becomes a product you ship. Services stop being org charts with SLAs attached, and start being software with judgement attached.

04 — The human differentiator

The floor is rising. The ceiling is human.

Here is the commercial truth underneath all of it. AI is levelling everyone. When every provider runs on the same models, competence becomes a commodity — the average email, the average deck, the average resolution, available to all at roughly the same price. The floor is rising for everyone. Which means the floor is no longer where you compete.

What remains is the ceiling: trust, taste, language, confidence, the feeling of being in good hands. And people do not experience services rationally. They say they want speed; they usually want certainty. They say they want response; they want confidence that someone competent is in control. It is rarely the waiting. It is the uncertainty. Clarity is part of the service. Expectation design is part of the service. That is not soft — that is operationally intelligent.

Feelings are not a side effect of service delivery. They are the product.

This is where our industry should be learning from the people who understood perception before we did — from behavioural science, from the great marketing minds, from hospitality, from every service business that worked out that how something feels is what it is. The next great idea for IT services will not come from IT services.

The differentiator of service is human. Not human as a cost line that automation failed to remove. Human as the one advantage nobody can download.

05 — The principles

Ten principles of the Human Operating Model.

i.

Software defines the service.

If a machine can sense it, decide it or resolve it, it should — invisibly, within policy, before anyone needs to ask.

ii.

Humans differentiate it.

Deploy people where they change how the moment feels, not where the process happened to run out.

iii.

Shift right, deliberately.

Four modes, not three tiers. Human attention belongs at the moments of dread, judgement and consequence — not the password resets.

iv.

Feelings are the product.

Until services are designed for how people actually think, feel and behave, they will keep working on paper and failing in practice.

v.

Sell confidence, not time.

Nobody buys hours. They buy the feeling that the outcome is safe in your hands. Price it, design it, deliver it.

vi.

Design the uncertainty out.

It is rarely the waiting; it is the not knowing. Clarity, ownership and expectation design are operational disciplines, not soft extras.

vii.

Language is architecture.

If customers need a glossary to understand your catalogue, the problem is not their vocabulary. Every word is a design decision.

viii.

The floor is not where you compete.

AI raises everyone's floor at the same speed. Strategy built on efficiency alone is a detailed plan to become average, faster.

ix.

Steal from outside.

The next great idea for services will come from behavioural science, marketing, design and hospitality — not from another framework revision.

x.

Rigour on the question, not the answer.

The leaders who matter next are uncertainty experts, not certainty performers. They ask why we do it this way — and listen.

06 — Where this comes from

Working notes, not commentary.

This thesis was not assembled on a whiteboard. It is being tested daily — inside a £550M services portfolio, across five service functions and three hundred people, against the demands of thousands of customers and an ecosystem of more than eighty delivery partners. And it carries the scar tissue of both sides of the table: two decades running managed services at scale, and years as the customer holding providers to account.

It has been argued in public — main stage at SITS 26, keynotes at SDI Spark 26, itSMF UK and PropelX London — and in private, in boardrooms deciding where AI investment actually lands. It will keep changing as the evidence does. That is the point.

£550M portfolio ~300 people 80+ partners NPS 68 in year one Both sides of the table
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