S-Curve Theory 1

Patterns of Technological Innovation John Callahan (2007)

The S-curve or lifecycle model (Foster 1986) remains a widely used tool for thinking about

technological innovation and competition. The basic idea is that any technology with commercial

potential passes through a lifecycle. During the early stages of the commercialization process,

progress is slow as fundamental technical issues are addressed. The rate of progress increases,

as these issues are resolved. As the technology ages, performance approaches upper limits –

often based on fundamental constraints such as the speed of light. Diagram P1 shows a typical

S-curve for a technology. The horizontal axis is the amount of R&D effort expended – cumulative

amount of R&D expenditures over time, for example. Often, time is used as a proxy variable for

this effort. The vertical axis is some single performance measure critical to the technology’s

commercial performance.

The replacement of one technology by another is frequently modeled using S-curves. In the

diagram P2, the performance improvement in technology T1 is slowing. The performance of a

newer technology, T2, while inferior is actually improving at a faster rate. In fact, it does overtake

T1, the old technology, in terms of performance.

© John Callahan, 2008

Thinking like this using the S-curve helps managers to ask what if questions and to make

forecasting decisions. Because the S-curve is also a very simple idea that is easily captured in a

diagram, it also facilitates communication and discussion.1

On the other hand, the use of S-curves has been severely criticized by Sood and Tellis (2005).2

They tested four hypotheses:

1. Technological progress on a primary dimension follows a single S-shaped growth curve.

2. When a new technology is introduced, its performance is lower than that of the old

technology.

3. When a new technology reaches maturity, its performance is higher than that of the old

technology.

4. The performance path of a pair of successive technologies intersects once when the new

technology surpasses the old technology in performance.

These 4 hypotheses form the basis for the use of the S-curve in technology strategy. Sood and

Tellis tested these hypotheses using data from four categories of technology: data transfer, 1 This is an important characteristic of any theory or model. 2 Sood, Ashish and Gerald J. Tellis (2005) “Technological Evolution and Radical Innovation”, Journal of Marketing, 69, July, 152-168.


computer memory, desktop printers and display monitors. The primary dimensions of

technological progress that they used in each category are provided in table P1:

Table P1: Metrics of Primary Dimensions in Each Category

Category Primary Dimensions Metric

Desktop memory Storage capacity Bytes per square inch

Display monitors Screen resolution Dots per square inch

Desktop printers Print resolution Pixels per square inch

Data transfer Speed of data transmission Megabits per second

Sood and Tellis (2005) found no evidence to support any of the 4 hypotheses! What they did find

was that “technological evolution seems to follow a step function, with sharp improvements in

performance following long periods of no improvement” and that “paths of rival technologies may

cross more than once or not at all.” They counsel that using S-curves to predict the performance

of a technology is risky and may be misleading.

The next major step in thinking about the progress of technology was taken by Abernathy and

Utterback.3 Based on their observations of a wide variety of technological innovations, they

proposed a lifecycle model that includes both product and process innovation. The model is

outlined in diagram P3.

At time 0, a radical innovation enters the marketplace in a new product. The product provides

functionality not provided until that point. A good example is the personal computer made

possible by the development of new off-the-shelf microprocessors (and related chip sets) in the

1970s.

This introduction if followed by a period of intense product innovation as companies seek the best

way to use the new technology for product advantage. Abernathy and Utterback (1978) call this

the fluid phase. This intense product innovation begins to fall off once a dominant design is

arrived at. A dominant design is a design that comes to be adopted by a majority of the market.

Again, the personal computer provides an instructive example. Up until the introduction of the

IBM PC, many companies were producing a wide variety of significantly incompatible personal

computers – think of names like Commodore, Osborne and Kaypro. With the IBM PC, the market

3 Abernathy, William J. and James M. Utterback (1978) “Patterns of Innovation in Industry,” Technology Review, 80(7), June-July, 40-47.


coalesced and “IBM compatible” became part of marketing slogans. The IBM PC became a

“dominant design.”4

The theory is that during a transitional phase, a dominant design is arrived at and the rate of

product innovation decreases. This is also a phase of increasing process innovation – that is,

innovation in the processes required to deliver the product to customers: manufacturing, logistics,

shipping, and business models. The innovation questions switch from what to make to how to

make and deliver it more efficiently and effectively. As process issues of product quality, cost and

timeliness of delivery come to dominate, the process enters the specific phase during which

incremental innovation is the norm and the number of suppliers contracts through competitive

attrition.

In the PC market, Dell typifies the increased importance of process innovation during the specific

phase. Dell computers were and are similar to the existing dominant design. Dell’s direct sales

processes, however, were distinctly different from those that existed when Dell entered the

4 Note that the establishment of a dominant design in a market does not mean that no other designs survive. The continued survival of the Apple in the PC market is a good example of this. Srinivasan et al. (2006) investigate both the probability that a dominant design will emerge in a product market and the time taken for a dominant design to emerge if it does.


market and began to be successful. Of course, since then other companies like HP have copied

Dell’s process innovations and Dell’s dominance in the market has been blunted.

Tushman and Anderson5 took the AU model a step further by looking at successive innovation

cycles.6 They asked the questions: Under what conditions do industry incumbent companies

survive and thrive through a radical technological innovation” and Under what conditions are new

entrants successful? Their answer, based on data gathered in the cement, airline and mini-

computer industries was that it depended on whether the radical innovation was “competence

enhancing” or “competence destroying.”

For an incumbent company in an industry, a radical innovation is “competence destroying” if the

incumbent company’s technology base is less able to provide the company with competitive

advantage because of the radical innovation. A standard example of this is the development of

the transistor. For those companies that produced vacuum tubes, the transistor was a

“competence destroying” technological innovation. When a competence destroying technological

innovation occurs in an industry, Tushman and Anderson theorized that industry incumbents

would not do well through the transition. Their data backed up their contention.

On the other hand, if the innovation is “competence enhancing”, incumbents do well and even

consolidate their presence in the market. An example of this is the development of large-scale

integrated circuits (VLSI). Those companies that had been producing simpler transistor based

chips were more able than any to adopt VLSI. The new technology provided these companies

even more competitive advantage from their competencies with transistors. When a competence

enhancing radical technology enters a market, Tushman and Anderson theorized that incumbents

consolidate their competitive positions. Again, data backed up their contention.

Christensen took the next step.7 He constructed another very telling critique of the standard use

of S-curves to describe the replacement of an older technology by a new one as shown above in

diagram P2.8 He made the point that the key measures of performance of the two technologies

5 Tushman, M.L. and P. Anderson (1986) "Technological discontinuities and organizational environments", Administrative Science Quarterly, 31, 439-65. 6 Note that the model of incremental innovation punctuated by radical innovation used by both Abernathy and Utterback and by Tushman and Anderson has a lot of similarities to the results found more recently by Sood and Tellis (2005) radical innovation and then more incremental 7 Christensen, Clayton M. (1997) The Innovator’s Dilemma, Harvard Business School Press; Christensen, C.M. and M.E. Raynor (2003) The Innovator's Solution: Creating and Sustaining Successful Growth. Harvard Business School Press. 8 Christensen, C.M. (1992) “Exploring the Limits of the Technology S-Curve. Part I: Component Technologies”, Production and Operations Management, 4(Fall), 334-357; Christensen, C.M.


can be very different. Often the new technology, T2, satisfices on the performance dimensions of

the old technology, T1, while providing a new dimension of performance on which it is much

superior to the old technology and that allows it to provide superior value in use. Even more

important, the new technology is often architectural in nature. That is, the new technology

changes the overall design of the product rather than just the components of the product, and is

targeted initially at sectors of the market historically regarded as unimportant by industry

incumbents. The situation is as shown in the following diagram:

Christensen further developed this idea as disruptive innovation. He identified three critical

elements of disruption. First, in every market there is a rate of technology driven improvement in

a product class that customers can utilize or absorb. Second, the pace of technological progress

almost always outstrips the ability of any given tier of the market to use it. These first two

elements, taken together, mean that the lower tiers of a product market often become overserved

by the products of the incumbent companies in the industry.

The third element is the distinction between sustaining and disruptive innovation. Sustaining

innovation is directed by industry incumbents at the upper, most demanding, tiers of the market –

(1992) “Exploring the Limits of the Technology S-Curve. Part 2: Architectural Technologies”, Production and Operations Management, 4(Fall), 358-366.


at those customers who value product functionality the most. Disruptive innovation, on the other

hand, is directed at those customers already overserved. Products driven by disruptive

innovation are “good enough” for these customers. More importantly, they are often cheaper and

easier to use.

Disruptive innovation is particularly dangerous for industry incumbents because an asymmetry of

motivation that exists between them and disruptive new entrants. The incumbents stay close to

their important and most demanding upper-tier customers, and give them what they want – more

functionality. These companies are not particularly interested in the overserved lower tiers of the

market because, almost by definition, these tiers of the market feature cheaper, low margin

products. The incumbents, in looking to the upper tiers of the market, are organized to profit from

high margin products. Their business models are not designed to make money in a price

conscious, low margin environment. For companies like this, going down margin to respond to

disruptive threats is very difficult. For managers, there is no incentive because there is higher

margin business available at the top of the market. It is also very hard to take overhead out of a

business model.

Disruptive new entrants come to the overserved segments of the market with enthusiasm and

business models designed to profit from low margin products. When successful, disruptive new

entrants are eager to move up market and take on the incumbents in the low end of their product

range. And technological progress often facilitates this as it moves faster than customer adoption

as pointed out above.

Christensen pictures the situation as follows:


A classic example of a market being over served was provided by the spring 2007 upgrade of

Adobe Photoshop.9 Photoshop had been a standard photo-processing tool for all serious

photographers. The new Photoshop had more power and functionality than ever. It’s new power

and functionality, however, was only really utilized by professional photographers. With the

decline in digital camera prices, the number of digital photography enthusiasts was growing fast.

But these enthusiasts seldom printed their photographs – preferring to upload and share them on

web sites like Flickr and Photobucket. The full print processing functionality of Photoshop was

not required for photos going directly to the web without being printed. This meant that

Photoshop over served a growing number of digital photographers. Heading the advice of

Christensen, Adobe brought out lighter weight products like Lightroom to address this demand

and protect the bottom end of its market.

So-whats for tech based startups

1. Lots of managers and entrepreneurs think about technological change using S-curves.

This is inappropriate.

9 Gilbertson, Scott (2007) "Major Photoshop Upgrade Is Overkill for the Flickr Crowd", Wired, March 27, http://www.wired.com/software/softwarereviews/news/2007/03/pshop_cs0327 (accessed April 15, 2007).



2. As a technology-based market matures, innovation and competitive advantage switches

from product design innovation to process innovation – product cost, quality, and delivery

effectiveness become more important. That is, your business models must change.

3. This switch is marked by the emergence of a dominant design for the product.

4. A startup can do well against established competitors if it avoids direct confrontation with

what the incumbents regard as the most attractive parts of a market, but rather if it

provides new types of functionality in inexpensive and easy to use products to over-

served or un-served customers.

References

Anderson, Philip and Michael L. Tushman (1991) “Dominant Design”, Research-Technology

Management, May/June, 26-31.

Anderson, Philip and Michael L. Tushman (1990) “Technological Discontinuities and Dominant

Designs: A cyclical model of technological change”, Administrative Science Quarterly, 35, 604-

633.

Christensen, Clayton M. (1997) The Innovator’s Dilemma, Harvard Business School Press

Christensen, C.M. (1992) “Exploring the Limits of the Technology S-Curve. Part I: Component

Technologies”, Production and Operations Management, 4(Fall), 334-357.

Christensen, C.M. (1992) “Exploring the Limits of the Technology S-Curve. Part 2: Architectural

Technologies”, Production and Operations Management, 4(Fall), 358-366.

Christensen, C.M. and M.E. Raynor (2003) The Innovator's Solution: Creating and Sustaining

Successful Growth. Harvard Business School Press.

Foster, R. (1986) "The S curve: A New Forecasting Tool." Chapter 4 in Innovation, The Attacker's

Advantage, Summit Books, Simon and Schuster, New York, 88-111.

Gilbertson, Scott (2007) "Major Photoshop Upgrade Is Overkill for the Flickr Crowd", Wired,

March 27, http://www.wired.com/software/softwarereviews/news/2007/03/pshop_cs0327

(accessed April 15, 2007).

Tushman, M.L. and P. Anderson (1986) "Technological discontinuities and organizational

environments", Administrative Science Quarterly, 31, 439-65.

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S-Curve Theory 1