Category: Technology and innovation management

Technology: what do we mean?

In development practice reference is often made to technology as being about hardware (equipment) and software. “Software” is borrowed from information technology to mean the invisible stuff that makes things work, in other words knowledge especially in its coded (tacit) form. This is clumsy. There is a close relationship between innovation and technology, and that is why this confusion matters and should be addressed.

Frequently, innovation is thought of as a new product or hardware artefact, or an improved process made possible by new technology. This error limits technology to hardware, and neglects the other aspects of technology.  It is necessary to understand technology from a much broader perspective.

As alluded to earlier, the narrow definition of technology refers to technical artefacts or hardware (with some supporting documents and instructions). However, complementary factors, without which the employment of technical artefacts makes no sense, are above all qualification, skills and know-how (of the people who work with artefacts), and organisation (i.e. the process of tying artefacts into social contexts and operational sequences). The organization part refers to being able to optimize the way the technology is integrated into other processes, and also how other processes must be changed to exploit the advantages of the new organization.

Meyer-Stamer (1997) formulates three conclusions based on the definition provided above:

(1)    Technology should not be seen in isolation from the environment in which it emerges, or from the organisational structures in which it is used. Technology does not come about in a vacuum; it always develops in concrete social contexts. It is therefore never neutral, and is always developed on the basis of given (economic, social, political) interests.

(2)    Technology often embodies organisational factors. A closed process in the chemical industry or a production line in the metal-processing industry, for instance, consists not only of technical knowledge of individual processing sequences, it also implies organisational knowledge about possible transitions between these sequences.

(3)    Any narrow definition of technology, looking at hardware only, accompanied by the view and approach that go along with it, can thus be tantamount to a guarantee that projects will fail – in development cooperation no less than in many international high-tech corporations.

In the discussion on development policy and the field of development cooperation in recent years, there has been a general acceptance of the broad definition of technology, one that does justice to the problems outlined here. This definition includes four components originally described by Enos (1991:169) illustrated in the image on the right:

(1)    Technical hardware, i.e. a specific configuration of machines and equipment used to produce a good or to provide a service.

(2)    Know-how, i.e. scientific and technical knowledge, formal qualifications and tacit knowledge.

(3)    Organisation, i.e. managerial methods used to link hardware and know-how that includes integrating all the elements into an organization.

(4)    The product, i.e. the good or service as an outcome of the production process.

 

The advantage of the broad definition is that it can help to avoid barren discussions in that it prevents, for instance, any equating of technical artefacts with technology. To this extent it mirrors experience gained, for example, in development cooperation – in view of this definition it is obvious that technology cannot be transferred in package form by for instance combining hardware with manuals and some field training. At the same time it is, against this background, easier to comprehend that technology is involved whenever production goes on – even when seemingly primitive technical artefacts are utilised in the process, for “no country is without technology, not even the most primitive” (Enos, 1991:169). So even a simple manual activity like using a shovel to dig a deep hole involves multiple elements and processes of different technologies. However, the absorptive capacity of countries, regions within countries and between different firms differs vastly.

Practically speaking, this means that practitioners must be careful when describing technology in relation to hardware that they do not neglect the other dimensions. For instance, when trying to understand where ‘new technology’ comes from in a value chain, make sure that respondents are not only identifying equipment suppliers. A second line of enquiry may be to get respondents to consider other kinds of technology related to know-how, or how to configure a specific process or organisation.

If a broader definition of technology is accepted, it becomes clear that there is a close relationship between technology and various forms of knowledge and also between technology and learning.

 

ENOS, J. 1991.  The creation of technological capability in developing countries. New York: Pinter.

MEYER-STAMER, J. & DEUTSCHES INSTITUT FÜR ENTWICKLUNGSPOLITIK. 1997.  Technology, competitiveness and radical policy change : the case of Brazil. London ; Portland, OR: Frank Cass.

 

Identifying firms to work with to induce upgrading of industries

This post was revised in February 2018.

When working on the improvement of innovation systems in developing countries, we have to work with firms. These firms have several roles, and there are three units of analysis:

  1. The firm is an important unit of analysis of innovative practices (product, process, business model).
  2. The firm is also a unit of analysis in terms of cooperation and collaboration, thus its ability to cooperate with rivals is an important consideration when we design interventions.
  3. Working with the right firms also provides an important source of technology and knowledge spillovers. This is where the challenge comes in for development practitioners.

Generally, firms that are able to lead the way, or could be good role models, are difficult to involve in development programmes for a variety of reasons. I won’t discuss that right now. What is important to remember is that most firms not only absorb or use technology and knowledge, they are also the main sources of knowledge and technology. This is both from a supply perspective (equipment suppliers, technical or specialist sources of knowledge, etc.) and from a demand perspective (demanding customers, sophisticated demand). Whether firms are aware of their role as disseminators of knowledge of technology is another story!

I will rather focus on how to identify the firms that we can work with to improve innovation and competence in all three units of analysis discussed above. Remember, our objective is to find ways to improve the dynamic in innovation systems that will result in the modernisation and technological upgrading of industries and regions.

More than 25 years ago Bo Carlsson and Gunnar Eliasson described a concept called “economic competence”. At the time they defined economic competence as “the ability to identify, expand and exploit business opportunities” (Carlsson and Eliasson, 1991). This is a useful definition as we have to remember that we cannot innovate on behalf of a broader industry. Somehow we must work with those firms that are able to innovate, imitate, adapt and integrate new knowledge and ideas.

According to Carlsson and Eliasson, economic or business competence has four main components:

  1. Selective (strategic) capability: the ability to make innovative choices of markets, products, technologies and overall organisational structure; to engage in entrepreneurial activity; and especially to select key personnel and acquire key resources, including new competence. This aspect has been amply illustrated in recent years as many companies have struggled to define their corporate identities and strategies as distinct from their competitive strategies in each individual business unit (Porter, 1991).
  2. Organisational (integrative, coordinating) capability: the ability to organise the business units in such a way that there is greater value in the corporate entity as a whole than in the sum of the individual parts.
  3. Technical (functional) ability: this relates to the various functions within the firm, such as production, marketing, engineering, research and development, as well as product-specific capabilities. These are the areas of activity in which firms can compare themselves to their peers or leading competitors.
  4. Learning ability, or the shaping of a corporate culture which encourages continual change in response to changes in the environment.

Economic competence must be present in sufficient quantity and quality on the part of all relevant economic agents, users as well as suppliers, government agents, etc. in order for the technological system to function well. This is both true at a local or regional level, our a national or sectoral level.

If the buyers are not competent to demand or use new technology – or alternatively, if the suppliers are not able or willing to supply it – even a major technical breakthrough has no practical value or may even have negative value if competitors are quicker to take advantage of it.

I think that this business approach of choosing the entrepreneurs that we work with is very relevant to finding the people who can absorb new ideas and make them work in a developing country context. I would also go so far as to state that I do not believe that it is feasible to select “change agents” according to social criteria such as gender, age, etc. – but that we recognise that change within economic systems happens because of the economic competencies of the people who are recognised in the system (regardless of their demographic data). The reality is that you cannot be competent on behalf of other people!

I challenge you to review the firms that you are working with to see if they are economically competent!

Sources:

Carlsson, B. and Eliasson, G. (1991). The nature and importance of economic competence. Working Paper No. 294, The Industrial Institute for Economic and Social Research (IUI).

Porter, M.E. (1991). “Towards a dynamic theory of strategy“, Strategic Management Journal, 12 (Winter Special Issue), pp. 95-117.

The difference between academic and industrial science

One of my favourite authors on the topic of science is the late John Ziman. Ziman played an important role in popularising science and its role in the technological evolution of societies. We have some of his books on our Mesopartner bookstore (You can also click on the images on the right of the screen) .

In his last book, Real Science, he made an important distinction between science in academia, and science in industry. This is relevant to me because I am assisting universities to conduct more relevant scientific research that will benefit industry. At the same time I am assisting industries to intensify their scientific research.

According to Ziman, academic science works towards the Mertonian norms introduced by Robert K Merton in 1942, also known as CUDOS. Merton advanced our understanding of the ethos of the scientific process. I like Ziman’s (2000) discussion of the Mertonian principles. CUDOS is as an acronym that denotes good academic research and stands for:

  • Communalism – fruits of academic science should be public knowledge (belongs to the whole scientific community), and the communication and dissemination of results are as almost as important as the research itself,
  • Universalism – researchers and scientists relate to each other regardless of the rank and experience of the researcher. The norm of universalism requires that scientific findings are evaluated objectively regardless of the status, race, gender, nationalism or any other irrelevant criteria,
  • Disinterestedness – academic scientists have to be humble and disinterested. Work is done in a neutral, impersonal and is often recorded in the passive voice. It disassociates with the personal or social problems, and focus on advancing knowledge or solving a very specific problem in an almost clinical way.
  • Originality – every scientist is expected to contribute something new to the archive, while building on the knowledge of predecessors. Unfortunately this also sometimes constrains how creative academic research can become. “new” could mean new data, questions, methods and insights.
  • Scepticism – This norm triggers important brakes on scientists, as it involves critical scrutiny, debate, peer review and contradiction before being accepted. It is important as it deepens understanding and knowledge from different research perspectives, and should not seen as being completely negative, rather it should be seen as being necessary.

 

Industrial science works towards what Ziman (2000:78-79) calls PLACE:

  • Proprietary – the knowledge is not made public (or at least as little as necessary is made public),
  • Local – it is focused on local technical problems rather than on increasing general understanding,
  • Authoritarian – Industrial researchers act within a hierarchy and must work to please senior management, in other words, it is not serendipitous,
  • Commissioned – it is undertaken to achieve practical goals rather than to just improve knowledge, and
  • Expert – industrial researchers are employed as expert problem solvers, rather than for their personal creativity and writing or teaching skills.

 

Ziman argues that when universities undertake contract research for industry, they somehow cross the boundaries between these two approaches to research. For instance, industry is more interested in solving a specific technological challenge and would prefer that senior researchers work on a problem. In the last 50 years it has increasingly become necessary for universities to raise 3rd stream income, so it a universally accepted practice that universities undertake research for and in cooperation with industry.  However, a university must prioritise the development of interns and junior researchers (and achieve other social goals). Furthermore, industry may not be interested in registering a patent (immediately), otherwise their secrets gets shared with the whole world. Academic researchers on the other hand, are expected to deliver publications when they cannot deliver patents or licenses, thus there is another conflict of their objectives. Perhaps a last comment is that universities are under pressure to solve social problems that are deemed “relevant” by prevailing political pressures, while industry prefer to solve problems that are immediate, relevant and that may even be in contrast with the desires of the prevailing political and social debates. Practically this means that at the moment industry may need to automate to remain competitive, thus incurring job losses, while government and the society may be demanding job creation for people with little or no technical education.

 

Universities must understand this tension, and must operate within and between different modes of conducting research. Current legislation perhaps assumes one standard approach to university research, that always results in something that can be published and or patented (licensed), and it further assumes that the value (and cost) or research is known at the time of start of the research or after completion. Practical experience indicates that this is not always the case. Sometimes the value of research only becomes apparent when it faces market forces.

 

Sources:

ZIMAN, J.M. 2000.  Real Science: what it is, and what it means. Cambridge: Cambridge University Press.

 ZIMAN, J.M. 2003.  Technological Innovation as an Evolutionary Process. Cambridge Cambridge University Press.

Innovation is not linear

You would think that everyone would know this by now.

You are wrong.

Frequently, policy makers, universities and technological supporting institutions erroneously describe innovation according to a linear model that assumes that innovation is applied science. It is assumed to be ‘linear[1]‘ because it is believed that there are a series of well-defined stages that innovations go through, starting with research (science), followed by development and then finally production and marketing. In this linear model scientific research is deemed to be the most important step as it is the first step in the process. Although there are some cases that have followed this route, they are in the minority.

A softer version of the linear process of innovation is where it is assumed that the knowledgeable people are in the academia or business support structures, and that the task of policy makers is to devise ways to transfer the knowledge flows from universities and supporting structures to businesses. The main perceived limitation is the inability of business people to learn by themselves or to absorb knowledge from the system around them.

In the real world, innovation is dynamic and it is complex. It sometimes starts with a clever idea by an entrepreneur about an unmet need in the market. At other times it starts with a customer complaining to a service technician. Often it starts with a problem or obstacles, and in a few cases it is the result of brainstorming. Wherever it starts, innovation is definitely not neat and tidy. In fact, it is quite chaotic.

But there are elements of the innovation process that may appear linear, like a product development process (product innovation). But this scarce and mainly happens in professionally run firms. For most of us, innovation is not a structured process.

Again, it is important to understand that innovation in a systemic context often arise due to the interaction between different social actors like enterprises, technical specialists, suppliers, customers and maybe the odd academic.

Notes:

[1] The ‘linear’ innovation process was first criticised by KLINE, S. & ROSENBURG, N. 1986.  An overview of innovation. In The positive sum strategy: harnessing technology for economic growth. Landau, R. & Rosenburg, N. (Eds.), Washington, DC: National Academies Press, pp. 275-305.

The difference between invention and innovation

This post is copied from a chapter in a book that I am working on about the fundamentals of innovation systems. I am responsible for the thematic area of innovation systems within the knowledge consultancy mesopartner that I am a partner of. If you want to stay abreast of the work I am doing on this topic then I urge you to subscribe to my blogsite so that you can receive an e-mail every time I add some content (click on the sign me up button on the top right).

We often find that development practitioners, business people and policy makers are not clear about the distinctions between innovation and invention.

A widely accepted distinction between invention and innovation is provided by Fagerberg et al. (2005:4). According to Fagerberg et al., invention is the first occurrence of an idea for a new product or process (first to the world), while innovation is the first attempt to carry it out in practice within a specific context (by, for instance, introducing a machine from another country into a local manufacturing process). Thus invention and innovation could be closely linked, although in most cases they are separated in time (sometimes decades or centuries), place and organisation. However, the fact that innovation typically emerges within a complex system is often overlooked. For instance, as Schumpeter (1964/1911) explained, the innovator who invented the steam engine still had to wait for others to develop the different aspects of the rail system before it could be commercially viable. The steam engine was initially invented in a completely different context, again illustrating how inventions are dependent on the context in which they arise.

While many innovations can be linked to well-funded research programmes, funding is not a pre-condition for innovation. In fact, in many cases a lack of resources could stimulate people to innovate. Firms usually innovate because they believe there is a commercial benefit to the effort and costs involved in innovating. This commercial benefit could be measured in terms of return on investment or profits, but it could also be about cost saving, resource optimisation, solving a recurring problem or responding to the demands of a customer. Often increased competition, changes in market structure or market demand, or changes in technological performance also affect the innovation process. However, innovation requires taking or at least managing risks. Therefore, firms with low capital or with tied up resources are less likely to innovate.

To turn an invention into an innovation, a firm typically needs to combine several different types of knowledge, capabilities, skills and resources from within the organisation and the external environment (Schumpeter, 1964/1911). The interaction between knowledge and learning will be discussed in more detail in the next section.

The willingness of an individual to tinker and explore better solutions is influenced in part by the organisational context of the innovator, but also by factors such as education, qualifications, meta-level factors such as culture, personal characteristics (such as patience, inquisitiveness or tolerance of failure) and the institutional environment. Other factors such as competitive pressure, problem pressure, or social and economic incentives also play a role. Locations with a more diverse economic and social make-up are more likely to be conducive to innovation, as actors interact with people with similar and different interests. The proximity of other actors and the density of interactions make imitation, cross-pollination of ideas, learning from others and the combination of different ideas into new products and services more viable (and less expensive). This feature could explain why urban areas are often hotbeds of innovation – there are more people with different ideas and perspectives that stimulates and often absorbs new innovations.

Why does this matter? Well, many countries (including South Africa) over emphasize “invention” (even when they say “innovation”). Many financial incentives, loans and support programmes prioritize novelty as opposed to absorption. Absorption is important for innovation, as it indicates how ready firms, industries or societies are to not only learn from their own mistakes (and success), but to also learn from the mistakes and the success of others.

Therefore innovation stimulation is about getting our developing countries ready and willing to absorb insights and ideas from others, as much as it is about getting our entrepreneurs to be creative.

As someone famous once said: “why re-invent the wheel?”. With our small budgets we are highly unlikely to out-invent our international peers on many of the topics that are now seen as “sexy” like climate technology etc.

Our priority should remain to get our entrepreneurs and enterprises to be innovative at product, process and business model level. Only once we improve our absorptive capacity will we be able to become inventive.

Sources:

FAGERBERG, J., MOWERY, D.C. & NELSON, R.R. 2005.  The Oxford handbook of innovation. Oxford ; New York: Oxford University Press.

SCHUMPETER, J. 1964/1911.  Theorie der wirtschaftlichen Entwicklung. Eine Untersuchung über Unternehmergewinn, Kapital, Kredit, Zins und den Konjunkturzyklus. Berlin: Duncker und Humblot.

Rediscovering things I once knew: 4 types of innovation

I am in the process of preparing for an intensive appraisal of several sectoral innovation systems around a University of Technology in South Africa. While reading up on my old notes I discovered something written a long time ago by the late Christopher Freeman in 1987. I thought it a good idea to share this with my readers.

According to Freeman, four types of innovation can be distinguished:

  • everyday, “incremental” technological change in small steps – an improvement in a production process, an improved product, a new service. It is this type of innovation that ensures that the productivity of firms will grow. Yet it does have inherent limits: even continuous improvements were, for instance, unable to prevent the replacement of sailing ships by steam ships;
  • technological breaks due to radical innovations, which alter the course of development of an entire industry – the introduction of the zipper, nuclear technology, or electronic word-processing systems are examples;
  • changes in a technical system that affect more than one industry; one example is the success of plastics;
  • changes in a techno-economic paradigm – new technologies prevail throughout entire societies, new industries emerge, old industries lose significance, conventional organizational patterns are invalidated. This type proceeds from the long-wave theory.

This is an important reminder that I have to design my process to be sensitive to these different kinds of change within technological systems!

 

Responsive but not pro-active innovation in business

During last year I conducted more than 100 interviews at engineering and high-tech firms in South Africa. This fieldwork was part of trying to better understand the innovation systems of which these firms formed part. On reflecting on the interview notes, I am shocked by a pattern that shows that the greater majority of these firms had a mainly responsive strategy to innovation. This means that many firms mainly did development and research work once customers asked for a specific improvement or change in a product. At least they are very responsive, but how to get from responsive to pro-active?

Although there were many firms that had a more pro-active approach to research and development, they were in the minority. Very few firms started from a scientific or technological base, combined with some or other research problem. Even firms that reported formal research and development budgets were mainly busy with incremental improvements on existing products.

From the very small sample that I have I can see that firms that had some kind of official or formal approach to research and development outperformed firms without these systems. It begs the question whether they first performed better and then engaged in product development (based on some research), or whether they first formalised research and then improved their performance. This question leads us nicely to the important point that innovation goes beyond product and process research, and that it also includes business management innovations. My research definitely supports the idea that more innovatively managed firms seems to be more creative in terms of research and development aimed at product or process innovations.

Many firms in South Africa complain that being pro-active requires fast amounts of working capital, as the economies of scale are too low to warrant huge investments. So many firms work from a successful past product. This has two implications. Firstly, that new entrants will struggle to get in at all. Secondly, that firms without a product to build on would be in deep water. But does this also pose an opportunity? Does this mean that if we can find new technological ways to overcome scale dependencies we can create new markets? Secondly, in a country with very demanding and sophisticated customers, should there not be many entry points that are not so scale dependent?

My New Years resolution is to investigate the relationship between science in business and innovation in business. Why are so few firms using a more scientific approach or basis in their business? Can science in business be stimulated? Can we use our technological and scientific base to create completely new markets, thus moving from fast and customised response to pro-active market creation?

PS. With scientific approaches in business I do not necessarily mean having labs full of white coated scientists brooding over bubling concoctions.  More about that in a next post.

How do you think we can deepen the use of science in business?

User-led innovation

Here is another short article that I wrote on the topic of user-led innovation. Many of my clients are asking about this topic. Because we are so far away from the industrialised countries, and because we have such huge geographical spaces to cover, we are faced by sophisticated and sometimes unreasonable demands. Therefore lead firms, lead customers, government and problems solvers are all asking for some very demanding solutions. Many of them are not waiting for new innovations to come from the markets, they are simply innovating to solve their own problems.

In recent years the focus in value chain promotion has increasingly emphasised the importance of systematic and market-based interventions. Within innovation system promotion, markets are important not only as selectors or buyers of successful innovations. Specialised users or unmet local needs could also be used as an impulse to stimulate innovation in a specific part of a value chain. The challenge here is not to ‘import’ technology or ‘solve’ a problem, but to get industry and its supporting structures to respond to this opportunity. This can often be achieved by better articulating unmet needs, or facilitating interaction between innovative producers and user groups.

Authors such as Von Hippel (2005, 1988) have over the years made a strong case for recognition of the innovations introduced by users, especially lead users. For instance, Von Hippel argues that customers (markets) often know what design criteria they have, and if a producer can capture this knowledge then new products could be created. Other authors, most notably Michael Porter, has in several publications indicated that the force of market demand not only shapes the design of products and technologies or strategies of firms (i.e. 5 Forces analysis), but that it could affect industry structure (i.e. the Diamond of Competitiveness). In his work Porter also emphasises the role of sophisticated or demanding customers in the innovativeness of firms.

Lead users may also provide unique opportunities for firms to innovate by customising or combining existing elements of technologies to respond to the needs of a potential customer group. For instance, many medical devices originate from the US or Europe. But surgeons and operating theatre staff working in distant locations may have unique functional requirements for these instruments, and if approached or observed in their working environments may provide important clues or insights on how instruments can be customised to improve their functionality. While firms in developing countries may be far from large markets, they are often close to specialised or niche users that may then create opportunities for innovators.

The risk of an emphasis on user-led innovation is that path dependence may occur and that blindness to rival technologies may result in a marketplace being disrupted by a rival technology. Path dependence occurs when producers respond to the demands of a certain kind of customer through investment choices that do not allow the producer to switch to a different technology or market. These customers may in turn be exposed to other market forces or technological change processes that may affect their continued demand for a given technology. The risk of the strong governance of strong buyers in the chain may then lead to a tunnel view that does not consider the upgrading potentials and requirements of the whole innovation system in the sector or region, but a too-narrow perspective on companies and their need to upgrade according to the demands of the main buyers and final customers[1]. The insights as well as interventions may be too narrow and may not lead to more proactive knowledge loops but to a reactive orientation that does not encourage new ways of doing things in the system.

Experienced value chain practitioners will be able to identify the opportunities and the risks of working with lead users as sources of innovation, as in value chains lead customers often emerge who can be used to better position certain actors in a chain. Although this usually works to the benefit of certain kinds of chain actors, it could also be argued that it deepens the dependence on specific kinds of customers (resulting in path dependence).

Sources:

VON HIPPEL, E. (1988) The sources of innovation, New York, NY, Oxford University Press.

VON HIPPEL, E. (2005) Democratizing innovation, Cambridge, MA, MIT Press.

[1] For instance, the IDS has published several papers on this and related topics which can be found at http://www.ids.ac.uk/go/idsproject/clusters-in-the-global-economy

Connecting innovation systems with local and regional economies

Many of you have asked me how I connect my current focus on innovation systems and technological upgrading with industries with my past experiences of local and regional economic development. I thank you for repeatedly asking this question, and apologise for not providing you with an answer. The reason for my silence was that I was also not exactly sure how to connect these topics. But I think I am now starting to understand how these topics relate to each other.

Let me try to explain this.

Before I continue I need to make sure that you understand that an innovation system is far more than one or two innovative firms.  Freeman (1987:1) defined an innovation system as “the network of institutions in the public and private sectors whose activities and interactions initiate, import and diffuse new technologies.” The emphasis is mainly on the dynamics, process and transformation of knowledge and learning into desired outputs within an adaptive and complex economic system.

So how does innovation systems work within regions or places? Well, it is often affected by issues such as trust, social and informal networks, formal relationships, common customers or common inputs and other factors. You will notice that it sounds very similar to the characteristics of a cluster in its early days. The main characteristic of a local or regional innovation system is that it is mainly focused on a specific geographic space and on the specific knowledge spill-overs that occur around certain firms, industries or institutions unique to that space.

You will immediately notice that innovation thus favours places with more people and more firms. You are right, a close relationship exist between density of interactions between people (provided for by towns and cities, nightlife, and frequent social exchanges) and the innovation system. It does not mean that innovations are limited to these spaces, but simply that they emerge faster or with more success in these spaces. This is largely caused by the increasing importance of knowledge exchange and interaction between firms, knowledge service providers and technological and educational infrastructure. But more about that in a seperate post.

I want to leave you with 3 questions that I have found to be useful to better understand the relationship between places and innovation systems. I use it frequently at the start of an assessment into an innovation system, or to stimulate thinking of public and private leadership.

1) Why are people innovating in this specific location (and not on another space)?

2) How does this space or place support innovation, and more specifically, how does it reduce the costs of innovation?

3) How do innovations in firms affect this space?

Bear in mind that with innovation I mean product, process as well as organisational or business model innovations.

Ask these questions and let me know what you find. I am sure that you will find that many places do not actively support innovation (unless you have some really determined or stubborn innovators there). Nor do they make it cheaper for people to innovate, exchange knowledge or stimulate joint problem solving (or opportunity exploitation). To me it also seems increasingly obvious that the role of cities and towns in Africa are not fully exploited in national economic development as spaces for innovation.

In South Africa, innovation happens mainly in 9 major and about a dozen secondary urban spaces. No amount of public policy will break this pattern until settlement patterns change, or until smaller places start to attract skilled people that can afford to innovate from cities.

So how can we support innovation systems in each and every town? How can we built regional and local institutions that reduce the cost and risk of innovation. Again, I dont mean only product development as an innovation. I mean process and business model innovation as well.

Until we can build our own local technological and educational institutions using local priorities and local resources from the bottom up the trend of urbanisation and migration to the major centres will continue. This is great in terms of reducing the costs of innovation, but it makes us very dependent on national policy, and only a few good local administrations. I would prefer a situation where we can build our local institutions around local issues, this giving firms in for example a mining region a head start in innovating around problems or opportunities related to mining.  For instance, in the Mpumalanga  province (South Africa) we have a lot of coal mining with its associated problems. Why is it so difficult to create a small but focused research institute or technological institute in a town that will focus on applied research and knowledge generation around environmental technology related to coal mining? Could this not be an impulse with environmental solutions as well as innovation as outcomes? I could imagine that such an institute could create positive externalities in a space that would lead to innovation that our both cutting edge and relevant to our society.

Now if you think about it, then Africa is rich with millions of ideas (also known as opportunities, challenges and obstacles) that could serve as impulses to create, stimulate or grow local innovation systems around relevant issues. Dont get me wrong, I dont mean that the public sector must do the research, and then the private sector must commercialise the research (although a little of this certainly helps). I mean that public funds or public private partnerships could be used to establish local institutions that create positive advantages for firms to innovate within regions through reducing the costs of finding relevant information (about a problem, opportunity or technology) and by highligthing opportunities for application of new ideas (by better articulating demand or applications). But there must be sufficient scale of infrastructure to allow the people with the right knowledge, experience and perhaps financial resources to settle in the region to exploit (or address) the opportunities through innovation.

Let me know what you find when you ask these questions.

PS. I know I will receive hundreds of angry e-mails that I am implying that rural areas are doomed.  Re-read my post before hitting ‘send’.

UNU-MERIT: How firms innovate: R&D, non-R&D, and technology adoption

You may be interested in the following paper from UNU-MERIT by C. Huang, A. Arundel & H. Hollanders

The official abstract is below.

Non-R&D innovation is a common economic phenomenon, though R&D has been the central focus of policy making and scholarly research in the field of innovation. An analysis of the third European Community Innovation
Survey (CIS-3) results for 15 countries finds that almost half of innovative European firms did not perform R&D in-house. Firms with weak in-house innovative capabilities and which source information from suppliers and competitors tend to innovate through non-R&D activities.
In contrast, firms that engage in product innovation, find clients, universities and research institutions an important information source for innovation, or apply for patents or use other appropriation methods are more likely to perform R&D. However, non-R&D performers do not form a consistent block, with several notable differences between firms that use three different methods of innovating without performing R&D. Many of these determinants also influence the share of total innovation expenditures that are spent on non-R&D innovation activities. Furthermore, an analysis of the determinants of the share of each firm’s total innovation expenditures for non-R&D activities shows that the
factors that influence how innovation expenditures are distributed is generally consistent across sectors and European countries.
What I find interesting is that these empirical findings are very similar to what I have found in my interviews with South African firms. Many firms do a lot of innovation without spending any money on R & D. A large number of firms use specialised product developers (or freelance experts) to do research on their behalf. Or they depend on universities or technology stations for research. Amazingly, the majority of the firms doing product development (as their area of specialisation) are small firms.

I wish we had this kind of data in Africa…..