Category: Research and development

Using the S-Curve to identify potential disruptions

This is a continuation of my blog posts based on my research into how technological disruptions and change occurs.

A widely publicised model is the S-curve model that enables the evolution of the performance of a technology (Foster, 1986a; Foster, 1986b). In management of technology textbooks, this model is used to make predictions about the evolution of the rate of technological change, to detect possible technological disruptions, or to determine the limits of a particular technology.

In the S-curve model[1], the Y-Axis tracks the performance of a specific technology, while the X-Axis shows effort measured in R&D investment and resources aimed at technology development (see Figure 4).

s-curve

Figure 4: A technology S-curve

Source: Author, based on work by Foster and Christensen

In the beginning of the development cycle of a specific technology, it takes a lot of effort to get performance increases out of a technology (blue line in Figure 4). This phase is often characterised by many different competitors with many different approaches to solving a given technological problem. This is often followed by an exponential improvement curve where the effort pays off with large increases in performance. Typically, improvements to the performance of the technology at this point in time are driven by several incumbent competitors, with many companies if their technologies are not chosen. After a while, the performance increases for every unit of investment (effort) starts to taper and return on investment diminishes. This is where incumbent firms are most vulnerable, as they try to squeeze as much profit from their existing technologies without looking for new investment opportunities even though they are almost completely dominating the market. New entrants find it very difficult to challenge the incumbents in the existing market place, because the incumbents have established a brand reputation, distribution networks and supporting systems.

Clayton Christensen (2000) explains that incumbent firms are often overconfident about the value of their existing technologies and tend to ignore potential new technological approaches. New entrants that are using a different technology aimed at a different market segment might be entering a new steep S-curve (the red line in Figure 4).

The new technology is usually at a lower level of performance than the original technology, and targeting a small, not-so-profitable niche that the incumbent firms are not willing to fight for (as they are benefitting from the scale of their current customer base). The niche market provides the new technology space to innovate in ways to increase in performance, and at some point, the graphs may intersect. This is where whole industries or technologies can be disrupted, as existing customers switch to a new technology that is in an upward performance curve. Christensen and Raynor (2003) explain that incumbents are very often “relieved” to exit small, low-margin markets, and so they constantly upgrade towards higher-margin or higher-volume target markets. This leaves small niche markets for new entrants where demands are not being met. These niche buyers and the new entrants often work together through several development iterations together, until the performance curve of the new technology crosses the incumbent technology in the broader market.

Christensen argues that whether a technology is disruptive or not depends less on how radical it is, but more on its specific effect on the S-curve. If a new development improves performance of an existing technology, then the incumbents are preserved and tend to benefit most as this improvement often suits its current scale of operations. If a technology creates a new S-curve, then it may disrupt existing technology at some point, leading to a disruptive change in industry structure. This implies that radical or incremental performance improvements in most cases benefits incumbents, while disruptive innovation challenges industry structures. In an interesting twist, Christensen argues that incumbents are not ignorant of new technologies and underserved markets. He argues that they are the victims of their own success in making decisions that leverages existing knowledge, networks, markets and capabilities. Ironically, customers may actually communicate that they prefer incremental improvements on existing technologies rather than adjusting to disruptive technology. It is not only the innovator that faces risk and uncertainty, buyers also try to avoid making decisions about technologies that are only emerging, or where performance, results and requirements are vague or uncertain. Decision-making in research and development may also be biased towards the most likely-to-succeed ideas that directs resources away from tinkering or experimenting with fundamentally different ideas.

Existing companies may be able to spot an emerging technology or group of technologies with a potential to disrupt their current market. However, it may still be very difficult to decide when to switch more resources to completely new technologies that may also require different business structures, culture, market and supplier relations (thus switching resources from the blue line to the red line in Figure 4). The performance of the technology is born from the strategy of firms and how they allocate resources to product, process and business model innovation. One way that governments can reduce the costs of incumbents and new innovators to confront, investigate and test new technologies is through technology demonstration and applied technology research, where companies can visit, use or test technologies hosted by public universities. Because companies know that their competitors might be investigating the feasibility of trying a new technology, they themselves are more likely to invest in new skills, in trying the new technology or exploring how this new technology could result in new markets, business models and capabilities.

Gathering all the information that is necessary to construct an S-curve requires time and can be costly. It is especially difficult to figure out which performance criteria and measures of effort to use to construct the graph. However, when a portfolio of technologies is tracked this way it shows not only inflection points, but when certain technologies may outperform existing dominant technologies. A key question that must be answered in constructing this model is whether to track performance change at the level of components (modules), sub-systems or architectures. Furthermore, even if the performance lines cross, incumbents may not switch if their sunk investments are too high, or the learning cost of the new technology is too high. That is why newer companies are needed in the economy, as they might have lower sunk investments and more to gain from higher performance. Over time, resources shift from the old technology to the new, but only if the new technology is accepted and is disseminated sufficiently.

A critique of the S-curve model is that while the graph makes sense, it is often hard to construct and project into the future. It often makes sense ex-post to explain why a given technology outperformed a previous dominant technology. Also, a weakness of the narrow focus on technological performance disconnects the technology from the broader technological and social context, such as the organisation capacity and supporting networks and infrastructure that is required to make a given technology work.

Notes:

[1] It is called an S-curve because when the results are graphically illustrated the curve that is usually obtained is a sinusoidal line that resembles an S.

Sources

CHRISTENSEN, C.M. 2000.  The innovator’s dilemma: when new technologies cause great firms to fail. 1st Ed. New York, NY: HarperBusiness.

CHRISTENSEN, C.M. and RAYNOR, M.E. 2003.  The innovator’s solution: creating and sustaining successful growth. Boston, Mass.: Harvard Business School Press.

FOSTER, R. 1986a.  Innovation: the Attackers Advantage. New York: Summit Books.

FOSTER, R.N. 1986b.  Working The S-Curve: Assessing Technological Threats. Research Management, 294 17-20.

Citation for this text:

(TIPS, 2018:23-24)

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

South African Research units and funding scenarios

I have been holding back on this post for a while, because it touches on a very sensitive situation here in South Africa regarding the student protests about university fees (see #feesmustfall). In South Africa, many of our research and technology development units that are publicly funded are hosted by universities. These centres depend on students and particularly post graduate students to deliver services to industry. At the same time these centres depend on industry to commission research, prototypes and to also take up the graduates. With the massive shortage of funding in the education sector, many of these centres and their hosting universities are starved of funding.

In August, I was helping a leadership team think through their industry strategy. I realised that their strategy was dependent on two implicit assumptions. Firstly, that the student unrest about the fees would be contained and short lived, with government miraculously finding funding from somewhere to relieve the pressure in the system. Secondly, they assumed that the private sector would somehow remain keen to invest in R & D, problem solving and prototyping despite the political uncertainty and adverse business conditions that we have in South Africa at the moment.

I helped the team to develop a set of scenarios, and this is what this post is about. It was a spur of the moment idea at the end of a meeting.

A simple way to develop scenarios would be to take the two assumptions (we usually use uncertainties) and to construct a simple 2 x 2 matrix. I know a 2 x 2 matrix has many shortcomings, but this simple matrix was to allow a team to explore several topics they have been hesitant to consider collectively. This was about helping a group make sense so that they could develop some actions together. With the leadership team, we wrote an assumption about the stability at the university on the horizontal axis. On the left we have a stable political environment at the university, with some high uncertainty about how long the peace would last and how much public funding will be available. On the right hand side we wrote that the situation becomes both unstable and uncertain. This axis is all about the stability of the hosting university.

On the vertical axis we wrote at the top that business people remain optimistic and continues to draw on the facilities and the services of the research centres, while at the bottom we formulated the opposite.

This simple matrix gave us four quadrants which we numbered 1 to 4 clockwise.

Scenario_Matrix

The instruction to the team was to think of each of the quadrants in the extreme of the two assumptions of the quadrant if they both played out. I won’t repeat all that was said here, but will just briefly capture some ideas. In quadrant 1, the situation at the university was stable, while business people continued to draw on their resources. The group agreed that this was the preferred quadrant!

Then they consider quadrant two, where the university was in chaos, and industry had to find alternatives for their services, or they were stuck. Trust relations developed with industry over many years were harmed (again).

In the 3rd quadrant, industry is depressed or paralysed, while the university is unstable. Everybody loses. Good graduates can’t find work, good researchers and lecturers lose hope and possibly leave the system, while business slowly but surely falls behind because the instability is very local. Globally competitors are investing, expanding and growing because the world goes on.

In the 4th quadrant the industry is depressed, meaning that demand from industry is possibly suppressed. The stability at the university is uncertain, meaning little investment takes place. The university does not have the resources to build capability or offers that helps industry, while industry does not have the resources to expand their investment. The whole system just hangs there waiting for something to give.

Now I know that this little scenario exercise was done very fast (we spent an hour on this), and yes, I know it does not address the fundamental issues that the university and government (and politicians) have to sort out. But the leaders quickly realised that their whole strategy was based on a quadrant 1 scenario. In fact, the very academics that always complains about the short term focus of the private sector were now trapped in a short term survival mode themselves. No industry or society can increase its wealth, prospects or competitiveness by waiting, especially when global competitors are at the door, looking for opportunities! This quick exercise helped the team to realise they needed to expand their offerings to be ready for the very likely other quadrants. They also realised that they had to think of ways of adapting their strategy so that the small steps they could take with their existing resources would lay “platforms” or stepping stones for an as diverse as possible range of future alternatives. For instance, one of the technology centres decided to shift its focus from a product development to a process enhancement focus, because there was a strong interest from industry to find ways of improving operations, cutting costs and improving flexibility.

The scenario dialogue enabled several follow up meetings  where the team could draw in more people and together re-imagine their future alternatives. Everybody was relieved that they had some options, where before this meeting they felt trapped without many options.

What I tried to illustrate in this post is that a simple scenario exercise could be a great instrument to help a team realise that despite almost certain disruptions, they could still think in the short term and the longer term. They had some options, they could even create more. By anticipating the future they also felt more ready for the disruptions that we are all waiting for.

For me it was also important to see how this team realised that their clients (industry) also faced huge uncertainties, and that if the research centre could offer services that reduce risks and costs while at the same time creating alternatives for market and technological development. Somehow shifting the focus from their own survival (and fears) towards the needs of industry and graduates looking to complete their research helped them move forward. Thus I could help the team consider how they could ensure their clients continue to innovate, which in turn helped the leadership to better understand how they themselves then have to be innovative.

Innovation was instigated!

 

 

 

Instigating Innovation: Tech push fallacy is still alive

Let me continue with the Instigating Innovation series. I will slowly shift my attention to the technology intermediaries, research centres and technology transfer organisations that exist in many countries to overcome persistent market failures in the private sector. Yes, I know it is a shock for some, but these centres do not really exist to promote the technical careers or the of these people in these centres, nor to promote a specific technology in itself. From a systemic perspective, these kinds of technological institutions exist because they are supposed to overcome pervasive causes of under investment in technology (and skills development) and patterns of poor performance of enterprises. Economists describe the last two phenomena as the result of market failures, mainly caused by information asymmetries, a lack of public goods, high coordination costs, economies of scale and a myriad of other challenges faced by enterprises (hierarchies), markets and networks.

The challenge is that very often the technology these intermediaries promote become an objective in itself. The technology, embodied in equipment, processes and codified knowledge, becomes the main focus. So now we see technology centres being created to promote Industry 4.0, or 3D printing, or environmentally friendly technology. While I am the first to admit that I am helping many of my clients come to grips with industry 4.0, additive manufacturing or environmentally friendly technology, we must not confuse means with ends.

About 20 years ago, my late business partner Jorg Meyer-Stamer and his colleagues at the German Development Institute developed the Systemic Competitiveness framework. Many of my posts on technological capability and innovation systems are based on this Systemic Competitiveness, but I wont go into this right now (perhaps I can do that in a later post), but will only state this this model has greatly influenced my thinking of how technological capability can be developed in order to upgrade, improve or stimulate the competitiveness and innovative behavior of enterprises and state institutions. In one of my current research contracts I had to retrace the evolutionary economics origins of this framework and I found the following paragraph in one of the early publications:

“A further fallacy also played a role in the past: the establishment of technology institutions was based on the technology-push model, according to which breakthroughs in basic research provide impulses to
applied research, which these in turn pass on to product development. In fact, however, research and development is for the most part an interactive process; and it is frequently not scientific breakthroughs
that impel technological progress, but, on the contrary, technological breakthroughs that induce scientific research, which then seeks to interpret the essence and foundations of a technology already in use.”

What struck me was the past tense in the first sentence. So many of the technology institutions I am working with are still established on these same grounds. A technology push model. Actually, much of economic development has the same mindset, a solution-push model. It implies that clever solutions are developed in a clinical and carefully managed environment, and then is made relevant to business people (as Jorg often said “stupid business people”) through iterations of “simplification” and “adaptation”. Don’t get me wrong. I am the first to promote scientific discovery. But this has its place. Modernisation of industry must start from the demand side:

  • where is the system now?
  • What is preventing companies from competing regionally and internationally?
  • What kind of failures, both in business models but also in markets are repeating over and over again?
  • What kind of positive externality can we create?
  • How can we reduce the costs for many enterprises to innovate and become more competitive?

Only then do you start asking what kind of technological solutions, combinations, coordination effort or demonstration is needed. Perhaps no new equipment or applied research is needed, maybe something else must first happen. Some non technical things that I have seen work are:

  • mobilising a group of enterprises into a discovery process of common constraints and issues
  • arranging exchange between researchers, academics and business people at management and operational levels
  • hosting interesting events that provides technical or strategic inspiration to the private sector
  • helping companies overcome coordination costs
  • making existing technology that is not widely used available to industry so that they can try it
  • placing interns at enterprises that have different skills than the enterprise use at the moment
  • arranging visits to successful enterprises; and many more.

The truth of the matter is that the innovative culture of the technology institution, and its openness to learn from the industries it is working with are much better predictors of whether the industries around them will be innovative. If the technology institutions are bureaucratic, stale or rigid, nobody in industry will be inspired by them to try new ideas, new technologies, explore applying technology into new markets, etc. Just like we can sense when we arrive (or contact) a succesful enterprise, so we can all sense when we have arrived at an innovative technology institution. It looks different, there is a vibe. It is information rich, everywhere you look you can see ideas being played with, things being tried, carcasses of past experiments can be seen in the corner.

I can already hear some of my customers leading technology centres reminding me that I must consider their “funding mandate from government” and their “institutional context in universities” as creating limitations in how creative they can be, and just how much demand orientation they can risk taking. Yes. I know this. In the end, leaders must also create some space between the expectations of their funders (masters?), their teams and their target industries. In fact, how leaders balance these demands and what is needed by their clients, students and staff can probably be described as business model innovation. If you cannot get funding from government for what you believe is required, just how creative are you to raise this funding through other (legal) means?

We have seen over and over again that it is not the shiny new piece of equipment in the technology centre that inspires industry; but the culture of the technology centre, the vibe, the willingness to try crazy ideas to make even old stuff work better or combining old and new. Ok, I agree, the shiny equipment excites geeks like me, but this is not all that matters.

My main point is this. Technology Institutions should focus on understanding the patterns of performance or under-performance in the industries and technology domains they are working in, and should then devise innovative products, services and business models to respond to these. This means working back from the constraint to what is possible, often through technology. To be effective in helping entrepreneurs overcome the issues they are facing would require that these technology institutions are innovative to the core. Not just using innovative technology, or offering some innovative services, but also in how these institutions are managed, how they discover what is needed and in how the collaborate with other institutions and the private sector.

To instigate innovation in the private sector, publicly funded technology institutions need to be innovative themselves.

 

Source:

ESSER, K., HILLEBRAND, W., MESSNER, D. & MEYER-STAMER, J. 1995.  Systemic competitiveness. New patterns for industrial development. London: Frank Cas. Page 69

 

 

Preparing for a different manufacturing future

In Africa, we face the challenge of a manufacturing sector that often manufactures products in low volumes. In a country like South Africa, we manufacture a wide range of products but often at low scale. Even our manufacturers that manufacture in larger volumes are still small compared to European or Asian competitors. In some parts of Africa we are further challenged by not having very sophisticated domestic demand in many sectors. When demanding customers are far away it becomes much more difficult to be innovative and well informed of what is possible and what can be done to exceed or at least meet the demands of customers.

But I can sense an important change taking place. I am frequently visiting manufacturers that are becoming much more knowledge intensive. They are smaller and more flexible than their more established competitors, and they combine different skills sets, technology platforms and knowledge bases.

In a forthcoming paper [1] that I co-authored with Garth Williams of the Department of Science and Technology and Prof. Deon de Beer (Vaal University of Technology), we offered the following definition of Advanced Manufacturing.

Advanced manufacturing is an approach that

  • Depends on the use and integration of information, knowledge, state of the art equipment, precision tooling, automation, computation, software, modelling and simulation, sensing and networking;
  • Makes use of cutting edge materials, new industrial platform technologies [2], emerging physical or biological scientific capabilities [3] and green manufacturing philosophies; and/or
  • Uses a high degree of design and highly skilled people (including scientific skills) from different disciplines and in a multidisciplinary manner.

We also argue that Advanced Manufacturing includes a combination of the following.

  • Product innovation: Making new products emerging out of new advanced technologies (including processing technologies).
  • Process innovation: New methods of making existing products (goods or services).
  • Organizational innovation or business model innovation: Combining new or old knowledge and technologies with traditional factors of production [4] in non-traditional fields or disciplines in unique configurations.

I am very proud that our definition of advanced manufacturing was also taken up by the Department of Trade and Industry in their next Industrial Policy Action Plan (IPAP) 2014/15-2016/2017.

The implication is that our technology development, technology transfer and education programmes need to change in order to be better able to equip and support manufacturers. Manufacturers increasingly need to be able to manage multidisciplinary teams using different technologies. These manufacturers must not only be able to learn fast from the market around them, they must be harness and pro-actively develop new combinations of knowledge within their enterprise. Existing or potential manufacturers must also think differently about manufacturing. Smaller factories, using more modern equipment in a flexible way is now a competitive advantage. The entry costs for starting a small manufacturing enterprise has never been so low. For instance, the cost of an automated electronics surface mount production line has come down by more than 70% in less than 10 years. Additive manufacturing allows tooling and products to be developed in parallel, but also makes it possible to develop new products very fast.

Where do South Africa enterprises learn to become more knowledge intensive at the moment? The answer is: At European Trade Shows. If you are a manufacturer or a potential entrepreneur, start saving up. There are many excellent trade shows throughout the year.

Which Meso-organisations offers the best examples, technology demonstration and training on this? Again, European Universities, Technology Transfer centres and universities. (The US and Canada also provide brilliant services, but it is much harder to access for us). If you cannot find a local expert or academics to help you, reach up to Europe.

What do we have to do? Think of ways to get as many of our entrepreneurs curious or interested in the newer technologies available, and learn from our (larger) competitors. Also, we have to get our universities to be more involved in technology adaptation and participating in new research areas. The academia should focus less on publishing in journals and get involved in real research collaboration that gives our industries (exporting) opportunities and that at the same time address unique needs in our domestic markets.

Oh, and by the way. Start reading up on the “internet of things”. Maybe my next post should focus on that.

 

Notes:

[1]  Our paper will be presented at the International Conference on Manufacturing-Led Growth for Employment and Equality in Johannesburg on the 20th and 21st of May. The paper is titled “Advanced Manufacturing and Jobs in South Africa: An Examination of Perceptions and Trends”.

[2] Such platforms have multiple commercial applications, e.g. composite materials, and exhibit high spill-over effects.

[3] E.g. nanotechnology, biotechnology, chemistry and biology.

[4] Labour, materials, capital goods, energy, etc.

 

Assisting firms to improve their Research and Development activities

In my daily work I deal with two kinds of manufacturers: those who have formal or informal research and development activities, and those who don’t. While there are certain tendencies for some industries to be more R & D intensive than others, I found some very innovative firms even in traditional sectors.

The first step to assist firms to improve firms to depend their R & D activities is to disconnect R & D from product development that responds to complaints, suggestions or requests from customers. While in some firms product development is the result of R & D, in most, product development is not purposeful, pro-active or inventive. I am always surprised to realize how dependent many firms are on their customers for specifications, product or ideas, especially in more traditional industries.

So if you disconnect R & D from responding to customers product demands then what do you connect it to?
From my experience, I found that establishing a cross functional team within the organization that has a mandate to question anything, any process, any routine, or that can investigate any problem is a good start. Thus I try to connect R & D firstly with reducing internal costs, solving internal products, mastering existing technology and knowledge domains. The key is to get very different people together, not based on their rank, but based on their curiosity and different expertise.

Next step is to then start thinking about the science behind current products, processes and core assumptions in the firm. Are therw substitute materials, solutions or processes for what is used now in the firm? Can we create some experiments, or can we explore alternative ways to achieve the same results? The purpose here is not to successfully develop new products, but rather to broaden the knowledge used within the firm not only about is core processes, but also about alternative markets, applications and production approaches. If you are lucky enough to have a great team together, then you can even play with questions such as “what else can we make with what we have?” or “if we partnered with a firm nearby, what crazy stuff could we make together?” But, I am sad to acknowledge, this does not happen often.

Only when we have a core team in the manufacturer curious about different ways of doing things, different ways solutions are used, alternative ways of creating solutions – only then do we look at new ways of pleasing current and existing customers with innovative new products. At this point the firm is inquisitive enough to value conducting research into new ways of doing things. We are ready to consider how a more formal Research and Development approach might look.