Valuations

The routes are the asset. Most sellers cannot prove them.

A route-based service business is priced on density, retention and the cost to serve. Those numbers usually come from hand-kept records: a dispatch board, a spreadsheet of stops, an owner's memory of who gets serviced how often. We rebuild them from the trucks' own position data, so the diligence side is reading measurements instead of assertions.

Talk about a deal See a sample read

Illustrative sample

What the read looks like when it lands

This is the shape of the deliverable: the territories on a map, the measures that price the business, and the month-by-month trend, all reading from one selection. Select a territory and everything else follows it. Select a month and the map and the trend follow that.

Modeled sample data. A fictional route book, not a client result.

Route book read

Five territories · Jan to Jun 2026

Modeled sample data

Data as of Tue 30 Jun 2026 23:59 UTC

Stops served

8,778

of 9,190 scheduled

Completion

95.5%

served against scheduled

Revenue per effort-hour

$77.91

$431,021 over 5,532 crew-hours

Places past cadence

past their own normal interval

TerritoriesModeled

Circle area is stops served. Columbus, Ohio.

This map needs JavaScript. The territory figures below it do not.

Stops served by monthModeled

Column height is stops served. Each column splits urban against suburban, because the total barely moves and the composition does.

This is the finding, and it is the reason the total is the wrong thing to look at: stops served across the book rose 2.9% over the six months while the two urban territories lost 25% of theirs. A revenue line built on the total looks healthy. The trucks say the density is rotating out of the dense half of the book.

Territory detailModeled

Downtown core

2,498

94.8% completion · $71.84 per hour · 14 past cadence
Upper Arlington

2,061

96.3% completion · $82.97 per hour · 7 past cadence
Clintonville

1,742

96.5% completion · $83.26 per hour · 5 past cadence
Hilltop

1,398

93.7% completion · $74.56 per hour · 11 past cadence
Obetz

1,079

96.5% completion · $80.45 per hour · 4 past cadence

Every number above is staged. It is a fictional route book in a real place, produced to show the shape of the deliverable, and no client engagement stands behind it. Two of the four measures do not decompose by month on this sample and say so when a month is selected, which is the same behaviour the real report has: not every measure is available at every grain, and a report that pretends otherwise is the problem this one exists to replace.

The gap

Soft numbers on the one thing that sets the price

Waste, pest control, landscaping, portable sanitation, last-mile: the thesis is route density, and the diligence questions are always the same. How many stops actually get served, how often, how far apart, and what does a truck cost to run for a day. In the lower middle market those answers are typically reconstructed from billing paperwork, which records what was invoiced rather than what happened. The two are close in a healthy book and quietly far apart in a distressed one, and the gap is exactly what a buyer is trying to find.

The vehicles already know. A truck emits position the whole working day, and that stream is independent of the billing system, the dispatch board and the seller's account of the business.

Illustrative sample

The designed state, and the driven state

A seller's own system shows the business as it was designed to run: routes as planned, stops as scheduled, work as quoted. Position data shows how it ran. The gap between the two lands in the same ratios every time, and it is the part a quality-of-earnings built from the general ledger cannot see.

Below is that frame applied to four businesses with almost nothing in common operationally. The ratios compare across them. The absolute figures do not, which is why the unit of effort is declared for each column before anything is measured against it. Every figure is modeled, produced by our own generators run against published industry bands. There is no client engagement behind it and no client data in it.

Modeled sample data. Not a client result.

Four columns. Scroll the table sideways to reach trucking, additive service and rail.

	Flat serviceone price, recurring visit	Truckingline haul and detention	Additive servicebase visit plus add-ons	Railcars charged per day at tariff
Effort unit	crew-hour	vehicle-hour	crew-hour	car-day
Asset utilization	47.2%	88.4%	79.6%	n/a
Revenue per effort-hour	$82.98	$57.73	$101.95	n/a
Completion	96.2%	97.2%	96.9%	n/a
Top-10 concentration	6.5%	44.0%	n/a	n/a

n/a marks a ratio this read did not produce for that column. On rail the reason is structural: the charge is a published per car-day tariff, so an hourly rate and a utilization percentage are not the unit of measure there.

What each read turned up

Flat service
Accounts billing on a schedule they were never on. The visit history shows no stop and the invoice goes out anyway. The same read finds the other direction as well: stops served every cycle that were never on the book and were never charged for.
Trucking
Detention recovered at $63.71 per hour against $66.65 per hour of operating cost. Billing detention at tariff is a loss on every hour billed. Both figures are ATRI's published numbers, not model output.
Additive service
Only 58.6% of the upsells that crews actually performed reach an invoice. $4,840 of work was delivered and never billed, on $1,047 of labor that had already been spent.
Rail
Demurrage is charged per car per day in whole-day steps against a published tariff, so pricing it as a linear hourly rate is wrong by construction. The linear rate computes $11,909.33 where the tariff computes $8,800.00, an overstatement of 35.3%. Across 91 charged cars it agreed with the tariff on none of them.

Calibration check

The trucking model was fitted to exactly one published figure: ATRI's finding that 39.3% of stops are detained. Nothing was fitted to the tail. The share of stops running past four hours came out of the model at 4.3%, and ATRI independently observes 4.9%. That agreement was not engineered, and it is the better reason to trust this frame than any single number inside it.

Published bands and figures are attributed to the American Transportation Research Institute, the Bureau of Labor Statistics, the Surface Transportation Board, Class I published tariffs, Argonne National Laboratory and the National Association of Landscape Professionals. Those figures are cited, not reproduced. Everything else here is modeled output from our own generators run against those bands. It is not a client result, no client engagement stands behind it, and no client data was used.

What we measure

From position data alone, before touching a single system of record

Stops and time on site
Every place a vehicle actually stopped, how long it stayed, and how often it comes back. Stops are clustered into places from the dwell pattern itself, so a service location is discovered rather than taken from a customer list that may be stale.
Service cadence, and where it broke
The normal interval between visits for each place, and the places now past that interval. Silent attrition shows up here first: a customer who stopped being served often keeps being invoiced for months, so a cadence break is visible in the trucks well before it reaches the revenue line.
Concentration
How much of the servicing effort sits in the top handful of locations, measured in visits and time rather than in dollars. Effort concentration and revenue concentration are different risks, and the first one is invisible in the general ledger.
Driving hours and overtime exposure
Time in motion between places, separated from time spent working a property. On city work that is an overtime bill; on highway work it is an hours exposure. Measured per truck against a threshold you set, not a certified hours-of-service record.
Fuel at a published price
Gallons reported by the vehicle, priced at the EIA weekly retail average for the region and the week of travel. Every line carries the region and the published week it was priced from, so the number has a citation a buyer can check rather than an assumed price per gallon.
Over-servicing drift
Places being visited more often than their own history would suggest. Margin leaks out here quietly, and it is one of the few findings that is worth money to the buyer and the seller for the same reason.

Boundaries

What this does not tell you

Saying it plainly is the point of the exercise. A number that turns out to have been an assumption costs more credibility than it ever bought.

Not dollars per stop
Revenue per stop, contract mix and margin per location need the billing system. We compute them when that data is connected and we do not model them when it is not.
Per truck, not per driver
Position data identifies a vehicle. Attributing hours to a named person needs a driver assignment record, and a crew does not always stay with one truck.
A cost basis, not actual spend
Regional fuel pricing is a defensible basis for comparison. Actual spend comes from the operator's own fuel cards, and the gap between the two is itself worth looking at.
Coverage is measured, not assumed
Not every vehicle reports every field, and a day with no record is a gap rather than a day with no driving. Anything we could not measure is reported as uncounted, with the count.

How it runs

Deterministic
The same inputs produce the same outputs, every run. Findings can be re-derived months later in front of a skeptical counterparty, which is the property that matters when a number is being argued over.
In your tenant
The engines deploy into your own cloud. Target data does not move to a vendor, which is usually the shortest path through a confidentiality conversation before an LOI.
Yours to keep
Output is native Excel and PowerPoint that recalculates on your own data, plus a map you can put in Power BI. Nothing depends on us being in the loop after the engagement.
Days, not weeks
Once the position history is available the measurement pass is short. It is built to sit inside a diligence window rather than beside it, and to be run again after new data lands.

Engagements

Buy side, sell side, and after the close

On the buy side this is a check on the story: cadence breaks the seller has not disclosed, effort concentrated in fewer places than the customer list suggests, and a cost to serve built from what the trucks did rather than from what was billed.

On the sell side it is the opposite exercise on the same measurements. A route book that can prove its density and its retention is worth defending at a higher number, and unrecorded service is easier to argue for when it is measured rather than asserted.

After the close the same measurements become the operating baseline, which is where route overlap between two newly combined books turns into a synergy number instead of an estimate.

Send us a deal you are looking at. We will tell you what the position data can and cannot settle before anyone commits to anything.

Talk about a deal