The Margin Question

The removals industry does not lack for diagnosis. In April 2026 a report titled Getting Britain Moving placed the sector's structural pressures in front of Parliament, and its central observation is the right one: removals is "frequently overlooked in conversations about streamlining and reform," yet the wider housing system "cannot operate as it should" without it. The diagnosis is correct. What it stops short of is the mechanism - it tells government what to change, and is largely silent on what the industry must do for itself.

That is the gap this analysis occupies. It takes the same industry and asks a narrower, more uncomfortable question, the one no policy can answer on an operator's behalf: of everything compressing margin in this sector, how much is actually within a single firm's control - and what is the largest lever it is not pulling?

The answer, we will argue, is not price. It is time.

A crowded industry chasing a flat pound

Begin with the shape of the market, because it is unusual. The UK removals and storage sector turns over roughly £1.2 billion a year - a figure stated plainly in Getting Britain Moving, corroborated by the independent market analyst IBISWorld, and consistent with the British Association of Removers' own estimate that member turnover "approached £1 billion" in 2025. Whichever source one prefers, the order of magnitude is settled: this is a low-single-digit-billion industry, and it is not growing with any conviction. IBISWorld's own figures are internally inconsistent across reports and base years - placing the market variously at £1.2 billion and £1.4 billion - but none of them describe a sector expanding at pace. The honest reading is a market that has been broadly flat to contracting, whipsawed by the housing cycle, for several years.

Now set against that flat revenue pool the structure of the industry competing for it. The published figures put the number of removals and storage companies at around 5,660, of which around 85% employ fewer than ten people - overwhelmingly, a population of micro-businesses. Against that, the sector's principal accreditation body, with a history dating to 1900, directly represents only a few hundred firms - a single-digit fraction of the field. That is the first thing worth stating plainly: the industry's main quality benchmark, whatever its standards, has never scaled to more than a fraction of the market it sits within. The great majority of the field operates outside any accredited code at all - not because no benchmark exists, but because the benchmark has reached so few.

This is the first tension, and it is the one that frames everything else. A large and growing population of very small firms is competing for a quantity of money that is not growing. And the field is getting more crowded, not less, at the bottom end. The industry's own commentary describes the mechanism without euphemism: "man and van" operators have "exploded in numbers in recent years," disturbing "the orderly functioning" of the market. Low-overhead entrants, carrying none of the fixed cost of a depot, a fleet, or an employed crew, can undercut on price indefinitely - because they are not pricing the same business.

The result is visible in the profitability data. Plimsoll, which tracks the financial health of the 752 largest UK removals firms, currently flags 159 of them selling at a loss for the second year running; IBISWorld placed the sector's average profit margin at around 1.4%. That is not a healthy industry having a difficult year. A 1.4% margin is a structural condition: it is what a market looks like when too many participants chase too little revenue and compete the difference away. One hundred and fifty-nine of the largest firms - the ones with the scale to absorb a bad patch - are not absorbing it.

So the question writes itself. In an industry this fragmented, this margin-thin, and this exposed, what is actually pushing the numbers down - and which of those forces can an individual operator do anything about?

Three forces, two of them weather

There are three. It is worth being honest that all three are real, because the temptation - and the error - is to reach for a single villain.

The first is demand, and it is the largest. Removals revenue is mechanically tied to housing transactions: every completed move begins with a property changing hands or a tenancy ending. That demand has been violently unstable. HMRC's residential transaction figures fell by roughly 12% between 2022 and 2023, and a further 17% the year after - a cumulative contraction approaching a third over two years. The market has since steadied: data cited in Getting Britain Moving records approaching 1.2 million house moves in 2025, up around 10% on the year before and marginally above pre-pandemic levels. But the industry's own assessment of that recovery is telling - a market "on a knife edge," with the time to agree a sale at a nine-year high of 77 days. Demand, in short, is volatile, cyclical, and entirely exogenous. No operator controls how many people move house.

The second is cost, and it too is largely external. The adjacent road-haulage sector - the closest comparator the UK economy offers, of which more below - saw input costs rise across the board in a single recent year: diesel up double digits, driver wages up more than 15%, insurance premiums up over 20%. Removals firms face the same pressures, compounded, as Getting Britain Moving notes, by recent increases to employers' National Insurance, the minimum wage, and business rates. These costs land regardless of how well a firm is run. They compress the margin from the outside.

The third is price competition - the undercutting described above - and this one is more interesting, because it is partly a consequence of the first two. When demand contracts and costs rise, and when the barrier to entry is a van and a phone, the market floods with operators willing to win work at any price. Price competition is real. But it is a symptom of the structure, not an independent disease, and an established firm cannot solve it by joining the race to the bottom - that way lies the loss-making half of Plimsoll's list.

Here is the crucial observation. Two of these three forces - demand and cost - are weather. An operator can forecast them, hedge against them, and brace for them, but cannot change them. They will do what the housing market and the wider economy dictate. The third, price, is a trap rather than a lever: the firms that compete on it hardest are the firms losing money two years running.

Which leaves a question that the industry's own report does not address, because it is not a policy question: if demand and cost are fixed from outside, and price is a race you lose by winning, what is left that a firm actually controls?

The answer is the one thing none of the three forces describes, because it never appears on an invoice. It is the productive time a firm has already paid for and does not use.

The pattern, told four times

Before turning to that, it is worth establishing that this is not a novel diagnosis. It is, in fact, the most well-worn story in the modern history of fragmented, asset-heavy, margin-thin service industries. Removals is not the first sector to face this exact squeeze. It is, by some distance, the last.

Consider four industries that arrived here before it.

Road haulage is the closest parallel, and the most instructive. It is fragmented, infrastructure-heavy, and chronically thin on margin - the Motor Transport Top 100 hauliers reported pre-tax profits of barely 2% of sales in their most recent results. And it carries a defining, measurable inefficiency: empty running. According to the Department for Transport's domestic road-freight statistics, roughly 30% of all heavy-goods-vehicle kilometres in Britain are run empty - 5,776 million empty kilometres in 2023, on a total of around 19 billion. That figure has barely moved in two decades. Nearly a third of the most expensive miles in the industry carry nothing at all. The firms that have survived the sector's repeated culls - UK road freight recorded 494 insolvencies in 2023, the most in a decade - did not survive by cutting prices. Analysis of the firms that collapsed found that a large majority had a high proportion of capital locked in owned, underused vehicles; the survivors ran leaner, used flexible capacity, and adopted telematics and route optimisation to attack the empty miles. The disease was idle capacity. The cure was using the capacity better, not buying more of it or charging less for it.

Taxis and private hire tell the same story in a different idiom. The defining waste was the idle driver - cruising empty between fares, dispatched by radio and instinct. The economists Cramer and Krueger, in a 2016 study for the National Bureau of Economic Research, measured the gap precisely: across five US cities, app-dispatched UberX vehicles ran with a passenger aboard for around 50% more of their miles than traditional taxis. In Los Angeles, taxis were occupied for just 40.7% of their miles against UberX's 64.2% - for every paid mile, a taxi drove nearly one and a half empty ones; the app-dispatched vehicle drove just over half. The technology did not put more cars on the road. It allocated the cars already there to the demand already waiting. The operators who adopted algorithmic dispatch pulled away; the radio rooms were squeezed out.

Last-mile parcel delivery is the same disease again - hand-planned routes, half-loaded vans, dead miles - met with the same class of cure: the mathematics of route optimisation. The canonical example is UPS's ORION system, the subject of a 2016 award case study by the operational-research society INFORMS, which by the firm's own account was saving it more than $300 million a year and cutting around 100 million miles annually. The carriers that built or bought that capability scaled; the sub-scale, hand-routed couriers were consolidated or disappeared.

Field service and the trades - plumbing, HVAC, telecoms installation - completes the set. The waste was the engineer scheduled off a whiteboard: idle between jobs, backtracking across a region, the wrong skill sent to the wrong call. The cure was field-service-management software that optimised scheduling and dispatch. The scale of the prize is no longer in doubt: ServiceTitan, a company built almost entirely on solving this single problem for trades businesses, floated on the Nasdaq in December 2024, raising around $625 million and rising 42% on its first day, on revenues of over $600 million growing at more than 30% a year. A multi-billion-dollar enterprise was constructed on the premise that under-digitised, fragmented service industries are losing money to idle time - and that whoever helps them reclaim it captures enormous value.

Four industries. The same disease every time: expensive assets - vehicles, drivers, technicians - sitting idle for a large fraction of the time they are paid for. The same cure every time: not more assets, not lower prices, but better allocation of the assets already owned. And the same outcome every time: the firms that measured and reclaimed the waste pulled ahead, and the firms that did not were consolidated or failed.

Removals sits exactly where each of those industries sat before its reckoning. It is fragmented. It is asset-heavy. It is margin-thin. And it is full of idle time that nobody is counting - the surveyor waiting in a layby for an appointment window to open, the crew dispatched without sight of who was actually free, the vehicle going out half-loaded, the route driven the long way because the day was planned around the customer's diary rather than the road.

The only question left is the one the four parallels all answer the same way: not whether this is the lever, but which firms will reach for it first.

The one lever in your control

Demand and cost are exogenous. The flat-then-fragile market, the rising firm count, the price pressure from operators carrying none of your overhead - these are the weather. You can forecast them and brace for them, but you cannot change them.

There is one thing you can control: the productive time you have already paid for. The surveyor idle between appointments, the route driven the long way, the crew dispatched without sight of who was actually free. It is the single largest controllable cost in a labour-intensive operation, and it is the one almost nobody measures.

We set out to measure it - and then, before staking a word of public credibility on the result, to test whether it held. What follows is Moovi's own modelling. We flag it as such deliberately: in an analysis otherwise built on independently sourced public data and the industry's own published figures, our own numbers are owned as exactly that. They are produced under synthetic but realistic conditions, stated in full below, and - crucially - they are not a single flattering week. We ran the same comparison across ten independent, randomly generated weeks specifically to find out which results were robust and which were lucky draws. We publish only the ones that held.

The conditions tested

Each of the ten weeks was modelled against the same fixed, realistic constraints - not a simplified scenario engineered to flatter the result:

• Three surveyors, each beginning the day from a different fixed home location rather than a shared depot - a materially harder problem than a single origin.
• Forty surveys across a four-day week, ten per day.
• A genuine geographic spread: appointments placed at random across the operating area each week - a catchment roughly 13 miles in radius from the central office, some 530 square miles - with no convenient clustering, and a different random geography every week.
• A realistic mix of appointment types: morning-only windows, afternoon-only windows, all-day flexibility, and fixed, non-negotiable appointments pinned to exact times - the hard anchors that genuinely constrain a day.
• Realistic appointment durations including wrap-up, with road-distance factors and average drive speeds applied to every leg rather than straight-line assumptions.
• A maximum of five surveys per surveyor per day.
• Responsible working-time limits enforced as a hard constraint on the optimiser: an eight-hour on-duty day, an uninterrupted midday break, and a defined latest finish. These are the operating limits a duty-of-care employer sets for staff who spend the day driving - the eight-hour day and the finish time are policy choices; the rest break is, beyond six hours' work, a statutory entitlement. A plan that breached any of them was treated as invalid, not merely sub-optimal.

Each week was then planned two ways: by conventional manual scheduling - a balanced carve, ordered by hand, the way an office plans today, with no optimisation - and by our allocation model.

What ten weeks showed

Three findings held across all ten weeks with low variance. We state those plainly. A fourth swung too widely to publish as a fixed number, and we say so rather than pick the flattering draw.

First, and most important - the fork. With three surveyors, conventional manual planning faces an uncomfortable choice every week, and the ten-week run makes it unavoidable to see. To place all forty surveys, the manual method had to breach the working-time limits set above - over-long days, late finishes, the rest break squeezed or skipped - on an average of around nine of every twelve surveyor-days. Forced instead to stay inside those limits, the same planner with the same crew could only fit an average of 29 of the 40 surveys - turning away roughly a quarter of the work, some eleven surveys a week. There is no third option for the manual planner: run the days too long, or refuse roughly a quarter of the work. The optimiser, by contrast, stayed inside every limit on all ten weeks - 120 surveyor-days without a single breach - and fitted more of the forty than the manual method could, because tighter routing freed the time the manual method lost to dead miles and waiting. This is the heart of it: the manual method only ever appeared to complete the week by quietly overrunning the working day to do so.

That distinction matters beyond compliance, because a survey is the front of the funnel. Turning away eleven surveys a week is eleven quotes not given, and some fraction of eleven jobs not won. For a firm trying to grow against a flat market, structurally refusing a quarter of its survey capacity - or running its people past the limits it sets to avoid doing so - is not an efficiency footnote. It is revenue the business cannot capture with manual planning without overrunning the working day to do it.

Second, dead time. Across the ten weeks the manual method generated an average of around 33 hours of pure idle time per week - surveyors on the clock, paid, sitting between appointments waiting for a window to open. The optimised plan reduced that by an average of 97%, to under an hour a week, and never by less than 94% in any single week. We publish this conservatively as "over 90%," because that floor held in every one of the ten runs and would survive any re-run. The recovered idle - roughly 32 hours a week for a three-surveyor team - becomes redeployable capacity: paid time that was producing nothing, now available for revenue-generating work. (We keep that figure distinct from any baseline slack a short day leaves; the 97% is waste removed, not total free capacity, and we do not conflate the two.)

Third, mileage - stated as miles, not as a percentage, deliberately. The manual method drove an average of around 774 team miles a week; the optimised plan, around 388 - a saving of roughly 386 miles a week, or about 18,500 miles a year for a three-surveyor team (around 6,200 miles per surveyor). On a fuel-only basis that is roughly £3,000 a year; at a true running cost of 30 pence a mile - fuel, wear, servicing and depreciation - around £5,500 a year, in vehicle costs alone, before counting the paid hours the surveyor spent behind the wheel to drive them. We state the absolute mileage rather than a percentage on purpose: across the ten weeks the proportional saving swung enormously with geography, from 15% to 75%, while the miles saved per week stayed steady. The honest figure is the one that holds on a re-run; the percentage was a single-week artefact, and we have buried it accordingly.

And one finding stated as honesty, not as a boast. Only three of the ten weeks were fully feasible for three surveyors. On the other seven, at least one randomly generated day was genuinely over-constrained for only three people - too many fixed and evening slots against the working-day limits. On those days the optimiser did not fabricate a completed schedule by overrunning the day; it placed everything it could fit within the limits and surfaced the shortfall - telling the operator, in effect, that the week needs a fourth surveyor or a moved appointment. The manual method "solved" those same weeks by quietly running the days too long, nine days in twelve. One approach refuses to fake completion; the other hides the overrun inside an apparently finished plan. We therefore make no claim that the system "always completes all forty surveys." It completes everything that fits within a sustainable working day, and tells you the truth about the rest.

It is worth being clear about why the gap exists, because it is not that the manual planner is careless. It is that the problem is larger than anything a person can search by hand. Ten survey appointments, shared across three surveyors - deciding who takes which job, and in what order each drives their route - can be arranged in close to 240 million ways, for a single day, before a single time-window, break or home start point is even applied. And it does not sit still: every new booking, cancellation and moved appointment reshapes it entirely. No human searches 240 million arrangements; no one can. A skilled planner finds a workable plan quickly, by experience and instinct, and stops there - which is the only rational way to plan by hand. But workable is not optimal, and the distance between the plan a person can reach and the best one available in a space that large is exactly where the idle hours accumulate. The waste is not a mistake. It is the unavoidable cost of solving an intractable problem by feel.

The optimisation method itself is the Travelling Salesman Problem with Time Windows - a member of the same family of combinatorial-optimisation problems that underpins UPS's ORION, commercial route-planning software, and field-service scheduling engines, solved exactly at the scale a single survey day operates at. That much is established mathematics, not invention. Our specific implementation is ours, and stays behind glass. What it does differently from a human is not work harder - it searches the space a person cannot, and returns the best plan within the limits, effectively instantly: at every booking, and again every morning when the board has changed. What matters for this analysis is not how it is done, but that the gap is real, it is consistent across ten independent weeks, and it sits entirely within the operator's control.

The conclusion the whole picture points to

Every force examined in this issue - the flat-to-volatile market, the fragmentation, the margin compression, the pattern already played out in haulage, taxis, last-mile parcel and field service - converges on the same place. The firms that endured those squeezes did not do so by charging more or working harder. They did it by measuring and reclaiming the waste that nobody else was counting. The disease was identical each time; so was the cure.

The reforms now before Parliament address the forces an operator cannot control - the shape of the market, the cost of compliance, the conduct of the informal economy. They are necessary, and worth pressing for. But policy is slow, external, and uncertain, and it asks its questions of government. It is conspicuously quiet on the other half of the reform agenda: what the industry must do to professionalise itself, from the inside, without waiting for Westminster. That is the half this analysis is concerned with - the one variable that has always sat outside the policy list because it belongs to the operator alone: the use of the time it has already paid for.

The two are not in competition; they are two halves of the same reform. One works on the weather. The other works on the one thing the weather never touched - and it does not require an Act of Parliament to begin. Removals is next. The only question for any individual firm is whether it reclaims that lever before the market reclaims it for them.