Understanding the Four Critical Stages of Technology Growth

August 8, 2016

Sigmoid1Last week (“Ignore the Sigmoid Curve as Your Peril”) I described the Sigmoid curve, also known as the technology assimilation curve and the “S-curve.”

It depicts the way many new technologies, new products, and new ideas grow in the marketplace; they begin slowly, and then if successful reach what Malcolm Gladwell dubbed the Tipping Point, followed by rapid, almost out-of-control growth. Inevitably, however, even the most successful products/ideas eventually experience slowing growth, which is often followed by decline as even newer technologies and products begin their own new growth curves:

 

 

SigmoidTransformation

I first became exposed to this phenomenon as a young consultant working with IT organizations in the early 1980’s. That was a time of dramatic growth and change as almost everyone was investing heavily in mainframe computer systems and new software applications. At the same time, they were scrambling to hire and train new staff and to build management systems for controlling their growing budgets, projects, and data centers.

My mentors in that exciting time were Richard Nolan and Chuck Gibson, both former Harvard Business School professors who had collaborated to write the now-classic Harvard Business Review article “Managing the Four Stages of EDP Growth” (January, 1974).

[“EDP” stood for Electronic Data Processing,” the term then used to describe the function that has since become known simply as “IT”]

Gibson and Nolan’s application of the Sigmoid curve to IT and IT management was powerful partly because virtually the entire industry was experiencing the same technical and management challenges at the same time.

As a Principal with Dick Nolan’s firm, Nolan, Norton & Co, I was deeply involved in building the basic idea into an entire management consulting framework – a model for understanding and managing change in technology organizations. The model lasted for several decades until the world of IT management became too complex to rely on a single model.

As the original article suggested, there are at least four critical stages along the growth curve:

Stage 1: Learning and experimentation
Stage 2: Rapid (and often uncontrollable) growth
Stage 3: Maturation (slowing of growth, often turning into decline)
Stage 4: Transition (the death of an old technology, accompanied by the adoption of a new one)

Stage 1:  Learning and Experimentation

This is the beginning, where the technology is unproven, and where many early efforts fail. In many cases, people apply inappropriate techniques to design the product or to introduce it into the marketplace.

The most dangerous aspect of Stage 1 is that the organization becomes accustomed to slow rates of improvement and a low return on its effort. Often a new idea dies before it becomes successful, not because it’s a bad idea but because it is smothered by inappropriate monitoring systems, or because it simply takes too much effort to achieve visible success.

Stage 2: Rapid Growth

But when things do succeed, and you reach Gladwell’s Tipping Point, the pace of change turns “north” quickly, and everything gets crazy. The ability to manage rapid growth often can’t keep up with the demand. You are scrambling to hire staff and to find the supplies and suppliers you need to meet that demand; things get frantic as you launch one project after another to leverage the opportunity or fix a problem. Often budgets become almost irrelevant; success breeds both arrogance and carelessness, and it feels as if the sky is literally the limit.

Stage 3: Maturation

Stage 2 can be frantic, but it’s also energizing and fun. However, inevitably, reality sets in.

The product saturates the marketplace, or it produces lots of competition. Growth slows down. Suddenly you have excess inventory, or your distributors start returning unsold products. Profits disappear. Headcount has to be cut, or at least it stops growing so fast.

If there isn’t a new technology sneaking up on you, Stage 3 can actually last for many years. However, it’s a much more stable, slow-growth period of time. Management systems settle down, but they often become ossified and bureaucratic. You need a different kind of staff and different managerial skills in Stage 3; where Stage 2 is typically filled with younger, high-energy, entrepreneurial types, Stage 3 requires more formally-trained managers who understand metrics and are focused on efficiency – on milking every last ounce of profit out of that mature product.

Stage 4: Transition

I once consulted with a chief information officer who told me his financial analysts had used capital budgeting procedures designed for reviewing $10 million mainframe decisions to justify funding for a $10,000 minicomputer. He claimed the company had spent over $100,000 deciding whether to purchase that minicomputer.

That’s a perfect example of the transition challenge. It’s as much a mindset issue as anything else; I recall another CIO client who told me his own project managers were actively discouraging their staff from trying out personal computers (that was a long time ago!) because “real programmers use mainframes.”

The best source of insights around technology transitions comes from Harvard Business School professor Clayton Christensen’s outstanding book The Innovator’s Dilemma, where he focused on the competitive challenges surrounding technology evolution. The dilemma stems from the risk of listening too closely to your existing customers, who are typically tied so closely to the mature technologies that they, like your own organization, may dismiss new generations of technology as unimportant and unimpressive (which they often are, since they are in their own Stage 1 period of pre-Tipping Point learning and experimentation).

As I suggested last week, ignore the Sigmoid curve at your peril. It’s a powerful way to understand and anticipate the inevitable changes we face with increasing frequency and impact every day.


The Sigmoid curve has been understood for decades, but its impact on strategic planning remains minimal. Call me at +1 510.558.1434 for a free initial conversation about how you can inject Sigmoid thinking into your executive team’s strategic planning processes.


Check out my latest book, Making Meetings Matter: How Smart Leaders Orchestrate Powerful Conversations in the Digital Age (link is to the book website). Chapter 7 describes six different tested approaches for designing extraordinary meetings that enable leadership teams to anticipate an uncertain future with confidence.

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