A single profit number tells you whether last year worked. It does not tell you which customers you subsidise, how much capacity you paid for and did not use, or where price quietly erodes between list and pocket. The Profitability Benchmark Framework is a set of five dimensions that turn a vague sense of "we could be more profitable" into a scored position you can compare, defend and act on. It is built from the operating models we deliver, and every range on this page is dated and observed in our own models, not surveyed.
Cost and Profitability Consulting · 150+ TDABC models since 2010
A profitability benchmark scores a business on five dimensions that a headline margin hides: the share of customers who are unprofitable to serve, the cost-to-serve tail, the cost of idle capacity, the margin cascade leakage between list and pocket price, and the costing maturity that determines whether you can even see the other four. Each dimension has an observed range from the models we build. You place your own number against the range, and the widest gap is where the recoverable margin sits.
A benchmark does not tell you whether you are good or bad. It tells you where you sit on a distribution, and how far that is from where the recoverable margin usually hides. Two businesses with the same reported profit can sit at opposite ends of every dimension below: one earns its margin cleanly across the book, the other earns a large margin on a few accounts and gives most of it back on a long tail it cannot see.
This framework is deliberately built from operating models rather than from a survey. A survey tells you what finance leaders believe about their costs. A model tells you what the costs actually are once operational effort is attributed down to the customer and the order. The ranges here come from the second kind of evidence. Because the sample is our own engagement base and not the whole market, we present each range as a signal, not a census.
Each dimension answers one question, is measured one way, and has a typical range from the models we deliver. Read your own number against the range; the dimension where your gap is widest is where to start.
The percentage of customers that contribute negatively to profit once the true cost of serving them is attributed. The business can be profitable overall and still not know where.
How much more the most expensive customers cost to serve than the average, driven by small, frequent, complex orders, returns and rush jobs.
The share of practical capacity that is paid for and not used, expressed in money. The number missing from most income statements.
How much margin drains away between list price and pocket price through discounts, terms, rebates and unpriced service.
Whether the costing mechanics can even produce the four numbers above. Weak mechanics mean the other dimensions are guesses.
The five compound. Weak costing maturity hides the idle capacity, which inflates unit costs, which distorts the cost-to-serve tail, which corrupts every price in the margin cascade. That is why the framework scores all five together rather than one at a time.
THE BENCHMARK TABLE
| Dimension | What it measures | Typical observed range | Your number |
|---|---|---|---|
| Unprofitable-customer share | % of customers contributing negatively to profit after full cost attribution | 20% to 40% | [your %] |
| Cost-to-serve tail | Cost multiple of the most-expensive-to-serve decile vs the average customer | 3 to 6 times | [your ×] |
| Idle-capacity cost | Practical capacity paid for and not used, as % of resource-group cost | 15% to 30% | [your %] |
| Margin cascade leakage | Margin lost between list and pocket price through discounts, terms and unpriced service | 10% to 25% | [your %] |
| Costing maturity | Profit Check score across seven dimensions, out of 100 | 40 to 55 | [your score] |
Every range above is a placeholder until replaced with Miguel's real observed ranges from the engagement base. Do not publish with placeholder tokens visible.
Placing yourself is simple. For each dimension, put your own number in the last column and see how far it sits from the observed range. A number inside the range is normal, not safe: it still represents recoverable margin. A number far outside the range in the wrong direction is where a diagnostic pays for itself fastest.
A short illustration, with illustrative figures. Suppose a distributor scores near the middle of the range on four dimensions but finds that a large share of its customers contribute negatively once cost-to-serve is attributed. Cumulative profit climbs to well above the reported total on the profitable core, then a long tail of small, frequent orders drags it back down. The gap between the peak and the reported total is the recoverable margin. The answer is almost never to drop those customers. It is to re-price, consolidate orders and match effort to value.
Recoverable margin = peak cumulative profit - reported total profit Where the peak sits above the total, the difference is margin the business already earns and then gives back on the unseen tail.
Illustrative figures. The point is the shape, not the numbers: a profitability curve that peaks above the reported total is the signature of a book that earns well and leaks quietly.
THE PROFITABILITY CURVE
Illustrative. Cumulative profit rises on the profitable core, peaks above the reported total, then the unseen tail drags it back. The gap between peak and reported total is recoverable margin.
As automation absorbs work that used to sit in people, the freed capacity becomes idle capacity with a cost unless something fills it, and the margin cascade gains new leakage points as AI-driven pricing and discounting scale faster than anyone can review them. Businesses that already benchmark on these five dimensions can see, in money, exactly what automation changed. Businesses that do not simply watch their unit costs move and cannot tell a saving from a demand drop.
Each range is built from the operating models we deliver, attributing operational cost down to individual customers, orders and resource groups. We date every figure and refresh the ranges as the base grows. Because the sample is our own engagement base rather than the whole market, it likely skews toward organisations that already suspect a costing problem. We present each range as what our models show, not as a market census.
Sample and dating: 150+ models, spanning distribution, logistics, manufacturing, retail, healthcare and professional services, most recent refresh July 2026. Where a dimension has too few models to publish a range, we mark it as not yet reportable rather than filling it with a guess.
The Profit Check takes five minutes and needs no data upload. It scores your costing maturity and points to where the other four numbers are most likely hiding. Or go straight to ProfitAudit 360 for the full diagnostic.