Inside one diagnostic 01 · The first pass 02 · Load consolidation 03 · Haulier spend
Use case · Haulier spend

A 49% saving. Argued down to 5.9%.

Anyone can find savings in a rate card. We took one year of a UK operator's subcontracted haulage and tightened the constraints until the number was one you could take to a board.

Talk to Flow Dynamics Real data · Real constraints · Nothing adjusted
5,027
Subcontracted trips,
one depot, one year
£1.85m
Paid to
third-party hauliers
£93,940
Defensible saving
in haulier selection
01 · The operator

A UK transport operator that buys haulage the way most operators do.

Thousands of trips a year are subcontracted to third-party hauliers, chosen by planners against the rates held in the planning system. This diagnostic examined one regional depot's subcontracted outbound work across a full year.

The work described here is a Flow Dynamics diagnostic: a fixed-scope engagement that takes a slice of the operator's own historical data and answers one commercially significant question with evidence rather than opinion.

The operator is anonymised. Every figure on this page comes directly from the diagnostic notebook run against their transport management system. Nothing has been adjusted for presentation.

02 · The question

"Are we paying the right hauliers the right rates?"

One year of subcontracting was pulled from the TMS: 5,027 trips, £1,853,067 paid. Every trip was re-priced against every haulier rate the planning system held for that lane. The cheapest-compliant total came to £940,527, a gap of £912,540, or 49.24% of spend.

If that number were real it would be the easiest money in logistics. It is not real. Knowing why, and what survives once you find out, is the actual diagnostic.

03 · The finding

A 49% saving is a symptom, not an opportunity.

Two things were hiding inside the headline. The planning system's loose lane mappings offered hauliers that were never genuine options for the work. And a bias check on the choices themselves showed the planners were more rational than the raw model implied.

What looked like favouritism was mostly missing constraints. Once the real rules were in the model, price explained nine tenths of every choice. The planning was not irrational. The data describing it was incomplete, and so was the headline saving.

04 · The method

Tighten the constraints until the number stops moving.

1

Extract the year

Twelve months of subcontracted trips, haulier vouchers and rate cards pulled directly from the operator's TMS. No new systems, no integrations. The data already existed.

2

Re-price naively, then reject the answer

Every trip priced against every listed haulier: a 49.24% gap. Too large to be true, and traceable to catch-all lane mappings offering hauliers that could never have done the work. The first finding was a data-quality finding.

3

Restrict to approved hauliers

The same year re-priced against the depot's approved list only. The modelled saving fell to 10.98%, or £203,436. Closer to reality, still missing the operator's finer rules.

4

Load the full constraint mapping

The operator's own haulier-to-lane mapping applied, and the bias check re-run. With 4,159 trips priced under the complete rule set, the defensible saving in haulier selection settled at 5.93%, or £93,940 for the year.

5

Scan the wider network

The unconstrained pass repeated across every depot: 6,742 trips, £2.59m of spend, and a 58.08% headline gap. A bigger surface, awaiting the same discounting, which tells the operator exactly where to point the next diagnostic.

05 · The result

The number got smaller. Its value went up.

Each pass strips out savings the operator could never have captured. What remains is small by headline standards and large by the standards of money you can actually bank.

PassConstraints appliedTrips pricedModelled savingOf spend
1 · HeadlineEvery haulier the system listed5,027£912,54049.24%
2 · Approved listThe depot's approved hauliers5,027£203,43610.98%
3 · Full mappingThe operator's haulier-to-lane rules4,159£93,9405.93%

£93,940 a year, at one depot, in haulier selection alone. Not the £912,540 the naive model promised. The smaller number is the one that survives scrutiny, and it repeats across every depot in the network.

06 · Read it straight

What this does and doesn't claim.

This is a model run on historical data, and we'd rather you read it that way than as a promise.

What it shows

  • A 5.93% saving in haulier selection at one depot, evidenced under the operator's own constraint mapping.
  • The gap between the 49% headline and the 5.9% answer is itself a finding: loose lane data was quietly distorting every cost view built on it.
  • The method transfers to every depot: the network-wide scan shows where to look next.

What it doesn't

  • The 49% and 58% figures are not savings. They are what unconstrained models produce, and they should make you suspicious of anyone who leads with them.
  • Service quality, volume commitments and haulier relationships are not modelled. Quantifying what survives those is the job of the next stage.
Start of the series · 01 The first pass One extract. Every question that follows.
Run this on your network

Your rate cards already know what you should be paying.

A Flow Dynamics diagnostic runs this analysis on your data, on your infrastructure. Nothing leaves your estate. Fixed fee, fixed scope, invoiced on completion. You end up with evidence, not a sales deck.

Talk to Flow Dynamics
30 days·£10,000 fixed·0 bytes to cloud