S-Curve Technology Analysis
Match your questions to a technology’s position on the adoption curve
- Difficulty
- Moderate
- Time to result
- ~weeks to results
- Steps
- 5
- Confidence
- 95%
Begin by locating a technology on its adoption S-curve: below the radar, rapidly scaling, or flattening into maturity. The position determines the useful questions. During rapid adoption, investigate competitors, survival, timing, and whether growth will flatten. Before adoption, avoid pretending that day-to-day market data exists; instead compare plausible structures such as winner-take-all platforms versus interchangeable components. Once a platform matures, shift attention to what can be built on top of it and to the next emerging curves. Finally, look beyond the obvious product toward second- and third-order changes in industries, behavior, infrastructure, and economics. The output is not a precise forecast but a disciplined map of uncertainties and consequential questions.
Origin
Benedict Evans described this approach on Masters in Business while explaining how the useful questions around mobile changed as its adoption curve matured and new curves emerged.
Core principles
- 01A technology’s maturity determines which questions matter
- 02Early markets require structural questions rather than tactical forecasts
- 03Mature platforms create opportunities in the layers built above them
- 04Second- and third-order consequences often hold more value than the obvious product
How to run it
- 1
Locate the curve
Decide whether adoption is nascent, accelerating, or approaching saturation. Use that position to establish what evidence should reasonably exist.
Pro tip Treat apparent inactivity in an early market as possible foundational work rather than proof that nothing is happening.
Watch out Do not impose mature-market metrics on a technology that has barely entered production.
- 2
Separate old and new curves
Identify the established platform that has already scaled and the emerging technologies developing around or after it.
Pro tip Ask what becomes newly possible once the established platform is ubiquitous.
Watch out Do not keep debating settled platform questions after the market has resolved them.
- 3
Frame structural alternatives
Formulate opposing market structures, such as concentrated versus fragmented or platform-controlled versus componentized. Explore the mechanism and implications of each alternative.
Pro tip Use historical analogies to generate alternatives, not to declare an identical outcome.
Watch out A binary framing should clarify uncertainty rather than conceal other plausible structures.
- 4
Trace downstream consequences
Ask how widespread adoption could alter adjacent industries, behavior, infrastructure, and business models. Continue beyond the first obvious effect.
Pro tip Look for the future equivalents of Walmart or drive-through ATMs: outcomes enabled by a technology but not visible in the original product.
Watch out Distinguish mechanisms supported by the technology from speculative details.
- 5
Update the question set
As adoption and evidence change, replace structural questions with competitive and operational ones. Continue revising the analysis rather than defending an obsolete forecast.
Pro tip Record which uncertainty each new data point resolves.
Watch out Do not confuse a correct broad direction with a correct prediction of who captures the value.
In the wild
Instead of forecasting next quarter’s autonomous-car sales, compare whether autonomy will become a concentrated operating platform or a standardized capability bought by many manufacturers. Then trace downstream effects on parking, road pricing, retail locations, commuting, and vehicle design.
→ The analysis exposes investable ecosystem questions without relying on nonexistent mature-market data.
Once smartphone adoption and the iOS-versus-Android contest are substantially resolved, stop treating mobile as the emerging question. Examine what ubiquitous smartphones enable, while locating machine learning, mixed reality, and cryptocurrency on their own earlier curves.
→ Strategic attention moves from settled platform competition to new layers of opportunity.
Common mistakes
Forecasting before data exists
Detailed numerical projections can create false precision when the technology has no functioning market or stable business model.
Stopping at the obvious product
Predicting the core technology while missing its ecosystem and behavioral consequences can miss where value ultimately accrues.
Using history as a script
Historical patterns should reveal mechanisms and questions, not imply that the same companies or outcomes must recur.
Is it for you?
Best for
It is best for investors, founders, and strategists evaluating emerging technologies or the opportunities created by mature platforms.
Not ideal for
It is not ideal for short-term trading decisions that depend primarily on current financial results.
From the transcript
“the character of the question changes because we're at a different point in the S curve.”
“there's like what are the topics and then how do we work out what the kind of the useful questions to talk about might be…”
“Those second and third auto consequences will flow out of this stuff.”
From the episode
Benedict Evans Talks About the Tech Bubble
Benedict Evans