Technological change cycles

This is the 3rd post that draws from the research and advisory work I am currently busy with to strengthen South Africa’s technological capability to detect and better respond to discontinuous technological change. The citation information for this post is at the bottom of this post, and a link to the research report that I have copied this from is here.

During the 1980s several scholars[1] recognised that technological change follows a cyclical pattern and several models were put forward to explain the phenomena. These models are still in use today and have been found to be active at different levels of technological change. The broad consensus was that a technological change cycle:

  1. Starts with a technological discontinuity or disruption, followed by a period of unstructured and often chaotic innovation when a new idea or concept is made possible (based on preceding developments). This disruption results in a fluid or turbulent development phase during which many ideas are developed, tried and promoted as the next best thing,
  2. That is followed by an era of ferment from which a dominant design emerges; and
  3. This is followed by an era of incremental change during which the dominant design is elaborated.

This can be illustrated with the widely recognised Abernathy and Utterback (1978) model with its three phases of change that are illustrated in Figure 2. The three phases are a fluid phase, a transitional phase, and a specific phase, and is similar to the cyclical pattern described in the bullet list above. Other scholars used slightly different labels, but the characteristics in the different phases are all more or less the same.

Abernathy and Utterback

Figure 2: The Abernathy-Utterback model of technological change

Source: Abernathy and Utterback (1978)

The rate of innovation is highest during the fluid phase, during which a great deal of experimentation with product features and operational characteristics takes place between different competitors[2]. Because of all the changes in the product composition and characteristics, process innovation typically lags. Buyers and users are often confused or overwhelmed during this phase fearing that the benefits are overstated and that the costs of adaptation are uncertain. Only the brave and the innovative engage in finding, adapting and integrating new ideas and concepts.

In the transitional phase, the rate of product innovation slows down and the rate of process innovation increases. At this point, product variety gives way to standard designs that have either proven themselves in the market, or that are shaped by regulations, standards or legal constraints. The pace of innovation of how to produce the product increases. What was done earlier by highly skilled technicians may become automated or developed to a point when low-skilled operators can take over. Or lower-skills jobs are displaced from the production process to other functions like logistics, while the skills intensity on the production line is enhanced. At this point it is easier for bystanders and followers to engage in exploration. The early adopters are already over the horizon, while many early adopters have exited, sold out or moved on.

The final phase, the specific phase, is when the rate of major innovation dwindles for both product and process innovation. In this phase, the focus is on cost, volume, and capacity. Most innovations are very small incremental steps, improvements on what is already known and accepted. Latecomers can now engage with the technology, although it might already be too late.

The description of technological change provided above follows the generic three-step process of technology evolution: a process of variety creation, selection, and then amplification or retention.

  • During the variety creation phase there are many competing designs and no dominant logic. Towards the end of this phase a few dominant designs may emerge, but there is still much competition between ideas. This is not only a technical selection process, there are important social, political and industrial adjustments taking place at the same time.
  • During the selection phase, standards emerge for positively selected ideas, with a few designs dominating. It is a relatively stable process of incremental improvements in features, performance and results. This may be interrupted occasionally by leaps in performance as some designs are substituted by better technologies, or from breakthroughs often coming from other industries or contexts. In general, designs become simpler as a learning process unfolds about how best to design, manufacture, distribute and use a particular technology around dominant designs. This period is characterised by growing interdependence as modules are developed, substituted and standardised. There is a growing exchange and increased competence within and between different communities of practitioners. Often there is industry consolidation during this phase. It is important to note the dominant designs are only visible in retrospect. They reduce variation, and in turn, uncertainty, but within the process it is hard to predict which designs will survive the next set of radical innovations. Once a design becomes an industry standard it becomes hard to dislodge.
  • This leads to an amplification phase, in which the best ideas are not necessarily used as intended, but when technological changes spill over into areas not originally intended. This is a relatively stable process that can continue for long periods, until is it suddenly interrupted by a radically different idea, resulting in the process starting all over again.

Anderson and Tushman (1990) state that, from the perspective of the sociology of technology, technological change can be modelled as evolving through long periods of incremental change punctuated by revolutionary breakthroughs[3]. The innovation activities that take place that lead to these phenomena will be discussed in Chapter 3.

Arthur (2009:163) contends that change within technological domains is a slow process. He explains technology domains do not develop like individual technologies like a jet engine: focused, concentrated and rational. It is rather more like the development of legal codes: slow, organic and cumulative. With technology domains, what comes into being is not a new device or method, but a new vocabulary for expression, similar to a new language for creating and combining new functionalities.

A current example is the “Internet of things”, where the connectivity of physical devices are spreading from the office and smartphone devices to interconnect household appliances, industrial applications and an endless list of technologies enabling data exchange, control and new functionalities . It could be argued that this is not a new technology, digital sensors have been around for a long time, our cars, smartphones and equipment have contained them for a long time. However, the language, standards, distributed nature of processing, and developments in big data visualisation have all contributed to this technology appearing to arise from obscurity into the limelight of the popular media. A similar argument could be made for artificial intelligence, drone technology and others.

Notes:

[1] The work of Tushman and Anderson (1986), Abernathy and Utterback (1978) are still frequently cited today.

[2] Kuhn (1962) noted that in the early stages of research in a given field, the most that scholars typically can do is to report the phenomena they observe, without a unifying theory or framework to help them categorise or make sense of what they see. As a result, this stage of knowledge accumulation is characterised by confusion and contradiction. Theories are put forward but reports of deviating phenomena accumulate.

[3] This is often referred to as punctuated equilibrium by political scientists.

 

Sources

Abernathy, W.J. and Utterback, J.M. 1978.  Patterns of Industrial Innovation. Technology Review, Vol. 80No. 7 (June/July 1978) pp. 40-47.

Anderson, P. and Tushman, M.L. 1990.  Technological Discontinuities and Dominant Designs: A Cyclical Model of Technological Change. Administrative Science Quarterly, Vol. 35No. 4 (Dec 1990) pp. 604-633.

Arthur, W.B. 2009.  The nature of technology : what it is and how it evolves. New York: Free Press.

Kuhn, T.S. 1962.  The Structure of Scientific Revolutions. Chicago & London: University of Chicago Press.

Tushman, M.L. and Anderson, P. 1986.  Technological Discontinuities and Organizational Environments. Administrative Science Quarterly, Vol. 31No. 3 pp. 439-465.

 

Citation for this text:

(TIPS, 2018:12-13)

TIPS. 2018. Framing the concepts that underpin discontinuous technological change, technological capability and absorptive capacity. Eds, Levin, Saul and Cunningham, Shawn.  1/4, Pretoria: Trade and Industry Policy Strategy (TIPS) and behalf of the Department of Trade and Industry, South Africa.   www.tips.org.za DOWNLOAD

 

 

Shawn in Wonderland

I have not posted anything for the last 3 months. I have been on an amazing adventure which is so similar to Alice in Wonderland that I might be asleep and still dreaming.

It started with a long-pursued opportunity to help a unit in the South African government prepare and think through the consequences of the “fourth industrial revolution” and the fuzzy collection of Industry 4.0 gadgetry that will soon overthrow our lives. By all popular accounts, this revolution will smack us hard, because the narrative in South Africa is that we are behind and falling further behind. The prophets blame all our usual reasons for this impending doom: our poor education system, our unskilled workforce, an unemployable youth, labour unions, capitalist greed, our government policies, inequality, high costs of everything, low public investment, corruption and the easter bunny. (OK, I made up the last one.)

Now don’t get me wrong. I know we are drifting sideways in many respects, maybe even regressing in some areas. For example, our economic complexity is in decline. Our technological capability is dropping. Many of our traditional sectors are uncompetitive. I have been working in the high-tech sectors and I know how hard it is to get to any kind of scale. Our institutions struggle to adapt, are underfunded, and our business people face high uncertainty, as much uncertainty as our public officials.

It is clear to me that the pace and convergence of change is increasing. The amount of information is increasing. We all are drowning in documents, reports, blog posts, emails, journals and correspondence. The demands both on specialists and generalists are increasing. So there is definitely something cooking.

But is it an industrial revolution?

Are revolutions not full of social unrest, upheaval of institutions, overthrowing of  government structures?

That is the big question that I started with. I must admit the empirical and academic evidence is thin on this topic. The only people excited are geeks and suppliers of gadgets. This really bothered me, so I tried to figure out what all the things are that I would have to understand to sense, monitor, track and possibly predict where technologies are changing, how these shifts could affect our institutional structures, industries and jobs.

So I went on the most amazing reading journey. Down the rabbit hole I went.

I started by exploring the literature on how technological change happens, how technology cycles unfold. I could get lost in little forests of papers, books and articles by many of my favorite scholars. I followed ideas down paths (to the 1980’s) and came back again to 2018. Actually, not much has changed since the early writings of Nelson, Pavitt, Lall, Freeman, Edquist, Perez and many others. I admire these scholars because they really grasped the principles at such a fundamental level that not even the arrival of the internet really nullified any of their theories. I then investigated technological evolution and was again inspired by the clear writing of Arthur, Hidalgo, Hausmann and Rodrik (on structural change and industrialisation).

Then I stood back and wondered about all the innovation, tinkering, risk taking and failing that had to happen to lead to the patterns that I found in the chapter on technology. Again, I went into a forest, this time looking at innovation, how it happened, did not happen and why. I was inspired by the work of Dosi, Fagerberg, Malerba, Dodgson, Teece, Utterback, Clark, Henderson and Christensen.

For a week I felt paralysed by these two forests. Are they really two different domains deserving separate chapters, or should they be integrated into one? In the past I have treated them as separate. So, I procrastinated and forged into one of my favorite topics, that of innovation systems and how they change.

It was always my intention to hold back on this walk into the innovation system forest, as I wanted to look at everything here with new eyes. I plunged into my favourite authors, Nelson, Dosi, Freeman, Fagerberg, Srholec, Lundvall, and some more Nelson, and many other authors I admire. I was again struck by the importance of building technological capability, increasing absorption capacity and the importance of social, technical and other meso organisations in all of this.

Towards the end of the innovation system week I ventured into the work of Johan Schot and Frank Geels, Andy Sterling and Ed Steinmuller (the SPRU network), and got lost in the world of socio-technical transformation. I could look at the literature on institutional change and discovered the work of Thelen. I spent a whole day just reading up on Carlota Perez, and the next day I went back to the earlier works of Christopher Freeman (which then lead me down the archives of the SPRU). Perez is one of the few scholars who even mention the word “revolution” and she argues that developing countries must embrace rapid technological change to achieve structural change.

I came out of this forest dazed, confused and inspired. All at the same time. I decided I had to integrate my innovation chapter into the technology chapter. It took me three days to integrate them. I also tried to integrate the socio-technical transformation section into innovation systems.

Then I went away on a weekend in the Bushveld in the Limpopo province in South Africa. Somewhere while breathing fresh air in the country-side I realised that technology and innovation had to be separated, largely because there is a tendency in South Africa to focus on linear innovation (science=>technology application => innovation). I recalled something that my late business partner and friend Jorg Meyer-Stamer repeatedly said.

“Technology is about action, about harnessing natural phenomena to achieve something. Innovation is about a difference, it is about doing something differently”.

For my client to measure and track technological change would not be too difficult. Measuring innovation will be much harder, as a lot of the innovation caused by the “revolution” are about changes in social technologies, organisational culture and strategy.

Four weeks into my study and I was left with one messy section. It involved reconciling my views on innovation systems with the socio-technical transformation and multiple pathways literature. It felt like I was stuck in mud. The common factor between these fields is the importance of adaptive meso institutions, tied with a balanced supply side and demand side interventions. Context matters in both these fields, far more than firm level technological use and innovation practices. What I like about the social technical transformation literature is their focus on developing “niches” based on unique contextual opportunities or challenges, and their recognition of how change unfolds and spills over in time. Too often innovation systems treats the system like a static network of publicly funded organisations.

So that is where I am now. My first draft literature study is complete. I’ve had so much fun during this journey. You would notice that I did not mention economic complexity much. The days that I somehow cannot account for was spent on that, but I really tried not to get sucked in too deep. In the end I decided not to include this in this study.

Stay tuned for a future update about what I discovered.