What it means
The pattern was first documented in aircraft manufacturing and later found across semiconductors, solar panels, batteries and many services. What makes it useful is its regularity: costs do not fall randomly, they fall in step with accumulated experience, which means they can be forecast.
The mechanism is broader than workers simply getting faster. It includes redesigning products to use fewer parts, negotiating better input prices at higher volumes, automating steps that were manual, and eliminating waste that only becomes visible after thousands of repetitions.
The strategic implication is uncomfortable but important. If costs fall with cumulative volume, the company with the most cumulative volume should have the lowest costs, which is why firms in industries with steep curves often price aggressively early to buy market share they can profit from later.
Curves are quoted as a percentage, and a lower percentage means a steeper decline. An 85% curve is common in mature manufacturing, while 75% to 80% curves appear in electronics and some renewable technologies, and service businesses tend to sit at the shallower end because labour costs are harder to automate away.
The nuance every manager should hold onto is that the curve describes a possibility, not a guarantee. Cost reductions only materialise if someone actively pursues them, and a technology change can reset the curve entirely, wiping out an incumbent's accumulated advantage overnight.
In practice
Real-world examples.
Example
A solar module producer prices its panels below current cost to win a large utility contract, calculating that the volume from that single order will move it two doublings down an 82% curve and make the contract profitable in its second year.
Example
A managed services firm finds that the hours needed to onboard a new client fall from 90 to 62 after its hundredth onboarding, as templates, checklists and a reusable configuration library replace bespoke work each time.
Example
An electric vehicle maker publishes a long-term cost roadmap to investors built explicitly on an experience curve, showing how projected cumulative output translates into a target battery cost, which is then used to justify the price of a future mass-market model.
Think of it
“The experience curve is costs falling as you gain experience-the more you've done, the cheaper it gets.
Formula
Calculation
Cost per unit after n doublings = Initial cost per unit x (Learning rate) raised to the power of n
Take a battery pack manufacturer on an 80% experience curve. At cumulative production of 10,000 units, the cost per pack is $200.
At 20,000 cumulative units (one doubling): $200 x 0.80 = $160
At 40,000 cumulative units (two doublings): $160 x 0.80 = $128
At 80,000 cumulative units (three doublings): $128 x 0.80 = $102.40
So cumulative output rising eightfold cuts unit cost from $200 to $102.40, a fall of just under 49%. If the selling price stays at $250, gross profit per pack rises from $50 to $147.60, which is the whole strategic argument for chasing volume in such an industry.Case study
Seen in the real world.
The following is a fictional illustration. Vantree Modular built prefabricated housing units and priced its first 500 units on a straightforward cost-plus basis at $84,000 each, which reflected its actual cost of $70,000 plus a 20% margin. A larger rival bid against it on a 900-unit local authority framework at $71,000 per unit, below Vantree's cost, and won.
Vantree's management assumed the rival was buying market share irrationally. In fact the rival had modelled an 85% experience curve and knew that the framework would double its cumulative output twice, taking its own unit cost from roughly $68,000 to about $49,000 across the contract.
By the time Vantree understood what had happened, in this illustrative story, the gap was structural rather than temporary. The rival had lower costs because it had built more units, and it had built more units because it had been willing to price against tomorrow's costs rather than today's.
Watch out
Common mistakes.
- Confusing the experience curve with economies of scale, when the curve depends on cumulative output over time and scale economies depend on output in a given period.
- Assuming the cost reduction happens automatically, when in practice it requires deliberate process redesign, capital investment and management attention.
- Pricing against a projected future cost that the company has not yet achieved, which produces real losses today in exchange for savings that may never arrive.
Questions
People also ask.
What learning rate should I assume for my business?
Look at your own historical cost per unit against cumulative volume rather than borrowing a textbook figure, because rates vary widely by industry and process.
Does the curve apply to service businesses?
Yes, though usually more gently, and it shows up as falling hours per delivery as templates, tooling and trained staff accumulate.
Can a competitor break my experience curve advantage?
Yes, most often by adopting a different technology or process that starts a fresh curve, which is why incumbents with deep cost advantages still get displaced.
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