Why did our revenue rise while profit fell?

Because the extra revenue came from a product that consumes more of the scarce resource per dollar of contribution it delivers. When capacity binds, selling one product means not selling another, so the relevant comparison is contribution per unit of the constraint rather than contribution per unit sold. In the worked example, the premium product earns $45 per unit against the standard product's $30, but it takes 3.0 machine-hours against 1.5, so it earns $15 per machine-hour against $20. Running the same 3,000 hours all-premium produces $150,000 of revenue and $45,000 of contribution, while all-standard produces $100,000 of revenue and $60,000 of contribution. More revenue, less profit, same factory.

What is contribution per constraint unit and how do I calculate it?

It is contribution per unit divided by the number of units of the scarce resource each unit consumes. There are three steps. First, identify the binding constraint, meaning the thing that actually runs out: machine-hours, labor hours, warehouse space, cash, a raw material, or a bottleneck station. Second, measure how much of that constraint each product consumes per unit, which is not revenue and not margin. Third, rank products by contribution per unit of the constraint and fill capacity from the top of the ranking down, bounded by how much of each product you can actually sell. No linear program is needed to start, just the ranking.

Why is the highest-margin product not always the best one to sell?

Because margin percentage and contribution per unit describe a product in isolation and say nothing about throughput. A 60% margin product that crawls through the bottleneck can lose to a 40% margin product that races through it. The true cost of making a product under a constraint is not only its variable cost, it is also the contribution forgone on whatever the constraint could have produced instead. That opportunity cost is invisible on any standard P&L, which is why the instinctive scoreboards of revenue and per-unit contribution both point the wrong way when capacity is full.

How should sales incentives change when capacity is the constraint?

If the sales team is compensated on revenue, it will sell the revenue-rich, constraint-hungry products, which is precisely the behaviour that shrinks profit when the factory is full. Aligning incentives to contribution per constraint unit, even approximately, changes what gets pushed. The practical caution is to respect demand ceilings rather than driving to a single-product mix. You can only sell so many of the constraint-efficient product, so the real move is to satisfy profitable demand for the top-ranked products first and then use remaining capacity down the list.

When does contribution per constraint unit stop being the right tool?

It assumes one dominant binding constraint. Where several constraints interact, the problem becomes a genuine optimization and a simple ranking can mislead, which is where formal methods such as linear programming earn their keep. It also sets aside strategic reasons to make an arithmetically worse product: a premium line that anchors the brand, protects a customer relationship, or opens a market can be worth its capacity even when the ranking disagrees. The discipline is to measure contribution per constraint unit anyway, so you can see what that strategy costs, and then decide with your eyes open.

Why More Revenue Made You Poorer: A Product Mix Story

Core Argument

A manufacturer had a strong quarter. Revenue was up, the flagship was selling well, and the sales team had leaned hard into its highest-value line: a premium unit at $150 that threw off $45 of contribution every time one went out the door. The factory ran at capacity the whole quarter. Profit came in below the previous quarter, when revenue had been lower. When a resource is scarce, the profitability of a product is not what it earns per unit. It is what it earns per unit of the scarce resource it consumes.

The core insight

Per-unit thinking asks: how much does this product make each time we sell one? That question feels obviously right, and under a binding constraint it is dangerously incomplete.

When capacity is limited, selling one product means not selling another. The real question is not "how much does this unit earn?" but "how much does this unit earn for the machine-hour, the shelf slot, the cash, or the labor hour it ties up?" A product with a high contribution per unit can be a poor use of the constraint if it consumes a lot of the constraint to deliver it. A humble-looking product can be the best thing you sell, because it sips the scarce resource instead of gulping it.

The premium product looked like the star because it earned the most per unit. But it hogged the factory to do it. Measured against what it consumed, it was one of the weakest uses of the company's scarcest asset.

"When a resource is scarce, profit does not come from what a product earns. It comes from what a product earns for the scarcity it consumes."

The framework: contribution per constraint unit

The method has three steps and no advanced math.

Contribution per Constraint Unit

Contribution per Constraint Unit = Contribution per Unit ÷ Constraint Units per Unit

Rank on this number, then fill capacity from the top down, bounded by what you can actually sell.

1

Identify the binding constraint.
What actually limits your output? Machine-hours, labor hours, warehouse space, cash, a raw material, a bottleneck station. If nothing is truly scarce, this framework does not apply and you should simply sell more of everything profitable. It matters only when a resource genuinely runs out.
2

Measure how much of the constraint each product consumes.
Not revenue, not margin. Units of the constraint per unit of product.
3

Rank products by contribution per unit of the constraint.
Fill capacity from the top of that ranking down, subject to how much of each product you can actually sell.

The manufacturer's real picture

The constraint was machine-hours.

Line	Premium product (A)	Standard product (B)
Price	$150	$50
Variable cost	$105	$20
Contribution per unit	$45	$30
Machine-hours per unit	3.0	1.5
Contribution per machine-hour	$15	$20

Look at the per-unit lines and A wins on everything: higher price, higher contribution per unit. Any report ranked by revenue or by per-unit dollars puts A on top, which is exactly why the sales team pushed it. But the last line is the only one that matters when the factory is full. Per machine-hour, B earns $20 against A's $15.

Now run the whole factory each way

3,000 machine-hours, one product at a time:

Line	All Premium (A)	All Standard (B)
Units produced	1,000	2,000
Revenue	$150,000	$100,000
Contribution	$45,000	$60,000

There is the paradox, fully assembled. Chasing the premium product produces $50,000 more revenue and $15,000 less contribution. More revenue made them poorer, because every hour spent on the high-revenue product was an hour not spent on the more constraint-efficient one. Reality is a blend of the two, bounded by demand, but the direction is the entire lesson: the mix that maximizes revenue is not the mix that maximizes profit, and under a constraint they can point in opposite directions.

Why experienced managers get this wrong

1

They rank by the wrong number.
Revenue and per-unit contribution are the instinctive scoreboards, and both ignore consumption of the constraint. The product that looks best per unit is often the one that ties up the most scarce resource per dollar of profit.
2

They forget the constraint has an opportunity cost.
Every unit of a scarce resource used on one product is unavailable for another. The true cost of making the premium product is not just its variable cost. It is the contribution forgone on whatever the constraint could have produced instead. That cost is invisible on any standard P&L.
3

They confuse "high margin" with "best use of capacity."
Margin percentage and contribution per unit describe the product in isolation. Neither accounts for throughput. A 60% margin product that crawls through the bottleneck can lose to a 40% margin product that races through it.
4

They manage the mix only when capacity is full, then forget the lesson.
The constraint binds hardest in the good times, exactly when everyone is too busy celebrating revenue to notice the mix is quietly suboptimal. The better the quarter looks on the top line, the more this can be costing you.

Putting it to work tomorrow

Find your one binding constraint and rank your products against it. You do not need a linear program to start, and the constraint mix calculator will do the ranking and the capacity fill for you. Pick the resource that actually runs out, compute contribution per unit of it for your main products, and sort. The ranking alone usually reveals a product or two that deserve more capacity and a "star" that deserves less.
Feed the ranking into sales incentives. If the sales team is compensated on revenue, they will sell the revenue-rich, constraint-hungry products, precisely the behavior that shrank profit here. Aligning incentives to contribution per constraint unit, even loosely, changes what gets pushed.
Respect demand ceilings and do not go to a corner. The all-A and all-B tables above make the point vividly, but you almost never want a single-product mix. You can only sell so many of the efficient product. The real move is to satisfy profitable demand for the top-ranked products first, then use remaining capacity down the list.

Know when the framework does not apply

It assumes one dominant binding constraint. With several interacting constraints, this becomes a genuine optimization problem and the simple ranking can mislead, which is where formal methods earn their keep. It also sets aside strategic reasons to make a "worse" product: a premium line that anchors the brand, protects a customer relationship, or opens a market can be worth its capacity even when the arithmetic disagrees. Measure the contribution per constraint unit so you can see what that strategy costs, then decide with your eyes open.

The principle worth keeping

When a resource is scarce, profit does not come from what a product earns. It comes from what a product earns for the scarcity it consumes.

"Before you push your most impressive product, check what it costs you in the resource you have least of. The most profitable thing you sell is often not the one that looks most profitable."

Free Excel Model: Pricing Optimization

When more than one constraint binds at once, the ranking stops being enough. This model solves the mix properly, with a Solver engine over 5 products and 6 business constraints, and names the constraint costing you the most.

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