Interview on knowledge for innovation

I had the privilege of being interviewed by Richard Angus (CEO The Finance Team) on the Business Masterclass programme on The topic of the interview was about concepts on knowledge and knowledge management that are relevant for business leaders. Listen to the podcast here.

During this 30 minute interview we talk about several knowledge concepts, like the distinction between tacit knowledge and codified knowledge and why this matters. I explained my favourite concept of how knowledge creation can be enhanced to improve innovation.

This interview is based on the article that I wrote earlier this year for the University of Stellenbosch Business School Executive Education newsletter.


Thank you to Richard and the show host Adriaan Groenewald from the Leadership Platform for this opportunity to talk about a topic that I love so much.




Instigating innovation by enhancing experimentation

“We don’t experiment!”, the operations manager sneered at me. “We know what we are doing. We are experts”. From the shaking of his head I could form my own conclusions. It meant that this business has a very short term focus in terms of innovation, mainly using a consensus based approach to drive incremental improvement. The irony is that the word “expert” implies learning by doing, often over an extended period. The very people that become “experts” through experimentation and trying things become the gatekeepers that promote very narrow paths into the future, thus inhibiting learning in organizations.

The aversion to experimentation and its importance in innovation is institutionalized in management. Many of the textbooks on innovation and technology management does not even have a chapter on experimentation (see below for some exceptions). Many industrial engineers and designers actually narrow the options down so early in a process or product design so that what comes out can hardly be described as an experiment. Approaches such as lean and others make it very hard to experiment as any variation is seen as a risk. In more science based industries, such as pharmaceutics, medicine and health, experimentation is the main approach to innovation.

Most manufacturers do not like the idea of experimentation, despite it being widespread in most companies. If management does not see it (or hear about it) does not mean it is not happening. This is the main problem. Lots of companies (or rather employees) experiment, but the feedback systems into the various levels of management and cross functional coordination are not working. Learning by doing is hard to do in these workplaces. Furthermore, management systems that rewards success or compliance makes learning by doing almost impossible.

Let me first unpack what I mean with experimentation.

Experimentation is a kind of investigation, or an attempt to better understand how something works. It is often associated with trial and error. Sometimes experiments are carefully planned, other times it can be impulsive (like when people press the elevator button repeatedly to see if the machine responds faster). Experiments are sometimes based on a deep insight or research, then it is almost like a authentication or proofing exercise. Other times it is done as a last resort (two attempts to get the machine to work did not work is followed by hitting it with a spanner). This could be naive even a little desperate. (Suddenly the machine works and nobody knows what exactly solved the problem). While experiments can be to prove something, I believe that not enough managers realise that experiments is a powerful way to keep their technical people happy (geeks love tinkering) and a strong way to improve the innovative and knowledge capability of an organisation. What does it matter if this experiment was successful in 1949, why don’t we try it and see if we can figure it out? Remember, innovation is a process of combination and recombination of old, new and often distant capabilities and elements.

Experiments in manufacturers happens at different levels.

  • It happens spontaneously on the work floor, where somebody needs to keep a process going. Ironically often experiments in the work space is the result of resource constraints (like trying to substitute one component/artifact/material/tool for another. A lot of potential innovations are missed by management because feedback doesn’t work, or experimentation is not encouraged or allowed.
  • Experiments could also be directed and a little more formalized. Typically these experiments originate from a functional specialization in the business, like the design office or another function. In these experiments the objective, the measurement and evaluation of the experiment is valuable for management as it could create alternative materials, processes, tools and approaches viable.
  • At a more strategic level experimentation often happens when evaluating investments, for instance making small investments in a particular process or market opportunity. It could also be about experimenting with management structures, technology choices or strategies. Sometimes the workers on the factory floor bear the brunt of these “experiments” which are not explained as experiments but rather as wise and thoroughly through decisions. In companies that manages innovation strategically, decisions at a strategic level could involve deciding how much funds to set aside or invest in tools that enable experimentation, for instance 3D printing, rapid prototyping, computer aided design and simulation, etc.
  • Accidental experimentation occurs when somebody by accident, negligence or ignorance does something in a different way. This occasionally result in breakthroughs (think 3M), and more often in breakdown or injury. Accidental experimentation works in environments where creating options and variety is valued, and where co-workers or good management can notice “experimental results” worth keeping. However, in most of industry accidental experimentation is avoided as far as possible.

The above four kinds of experiments could all occur in a single organizations. At a higher level experimentation can also happen through collaboration beyond the organization, meaning that people from different companies and institutions work together in a structured experiment.

When you want to upgrade industries that have a tendency to under invest in innovation, you can almost be certain that there is very little formal experimentation going on. With formal I mean thought through, managed and measured. Proving one aspect at a time. It is often necessary to help business get this right.

Since this series is about instigating innovation in both firms and their supporting institutions it is important to consider the role of supporting institutions. One important role for supporting institutions is to lower the costs and risks of experimentation for companies. This could be through the establishment of publicly funded prototyping or demonstration facilities. Another approach is for supporting organizations to support collaborative experiments. However, I sometimes find that supporting institutions themselves are not managing their own innovation in a very strategic nor creative way.

Helping industries to improve how to conduct experiments need not be expensive and does not necessarily involve consulting services (many institutions are not organized for this). For universities there are some interventions that align with their mandates. For instance, exposing engineering students to formal experiments with strong evaluation elements (such as chemistry students have to go through) can also make it more likely that a next generation of engineering graduates are able to also plan and execute more formal experiments. Or creating a service where industry can experiment with technology within a public institution. Or arranging tours or factory visits to places where certain kinds of experiments are done, or can be done.

Lastly, not all experimentation needs a physical embodiment. Design software, prototyping technology, simulation software and 3D printing makes are all tools that enable experimentation and that reduces the costs and risks of experiments. Furthermore, experiments need not be expensive, but they should be thought through. I often find that companies want to create large experiments when a much smaller experiment focused on perhaps one or a few elements of the whole system would suffice. Here it is important to consider the science behind the experiment (at a certain smaller scale certain materials and process characteristics are no longer reliable or representative). The experiment must be just big enough to prove the point, or to offer measurement and comparison or functionality, nothing more.

I will close with a little story. I once visited a stainless steel foundry. These businesses are often not known to be innovative, but I was in for a surprise. The CEO of the foundry had a list of official experiments that were going on. Often each experiment had a small cross functional team involved, supported by a senior management champion. The aim was not to succeed at all costs, but to figure things out, develop alternatives AND increase the companies knowledge of what is possible. Everybody in the different sections of the business knew when experiments were taking place, and everybody was briefed on the results. Even though this is a very traditional industry, this company had managed to get their whole workforce to be excited about finding things out.

I promise I will get to the how in a future post in this series.


My favorite text books on experimentation in innovation are:

DODGSON, M., GANN, D. & SALTER, A.J. 2005.  Think, play, do : technology, innovation, and organization. Oxford: Oxford University Press. (I think this one is now out of print)

VON HIPPEL, E. 1988.  The sources of innovation. New York, NY: Oxford University Press. (Despite being an old book this is really inspiring)

THOMKE, S.H. 2003.  Experimentation Matters: Unlocking the Potential of New Technologies for Innovation. Harvard Business Press.

HARVARD. 2001.  Harvard Business Review on Innovation. Harvard Business School Press.

If you know of a book more recent then please let me know.


Post 4: Technological Institutions that disseminate knowledge

This is the fourth post in this series about building technological capability.

In 2011 I explained how we define technology in a broad way. This definition looks beyond hardware to include knowledge and organization of the different elements. For instance, if a company decides to achieve a new standard of compliance, that is seen as a technology. This technology involves the way processes are organized, the knowledge of how to achieve and maintain this new standard, and the physical and knowledge infrastructure involved in the enterprise.

Firms depend on a variety of public and private technology institutions in order to compete, innovate and grow. Examples range from access to basic research all the way to access to technical problem solving. The measurement, standards, testing and quality assurance (MSTQ) of a country is also assessed from this perspective. The density of interaction between various technology institutions, as well as the interaction between the firms and the technology institutions, is an important factor in the innovation trends in a sector. Various kinds of technical services such as knowledge-intensive business services play an important role in knowledge spill-overs between different firms.

We call all these carriers of technological knowledge “technological institutions”. While some of these institutions are publicly funded (like a research centre, national standards organization or an start-up incubator), some could also be privately funded (like a supply chain development office at a multinational, a specialized equipment provider that provides training and technical support, etc). Specialist and technical service providers, management consultants, researchers and manufacturing extension experts all fall under this broad category. Some charge full service, others provide public goods, but all disseminate knowledge to enterprises.

An organization like a Technology Transfer Centre hosted by a University is located between an Education Institution (post 3 in this series) and a Technological Institution, and often it behaves like both. The Technology Stations Programme in South Africa is an example of an institution designed to fit the space between technological intermediaries, universities and enterprises.

It is noticeable that in many developing countries, the technological institutions that disseminate technological knowledge and that makes scarce technology available to industry are weak or missing. While some stronger enterprises may require and be able to absorb more technological knowledge, the domestic institutions often provide generic services that do not meet the expectations of these leading enterprises. In middle income countries, leading enterprises may simply disengage from the domestic technological institutions and engage with service provided in other countries, further reducing the scale of knowledge dissemination and weakening the system further. This leads to a situation where most enterprises in the country only have access to generic and low-value services, while leading companies and multinationals connect with global sources of knowledge and technology.

You may be surprised to find out which organizations are identified by enterprises if you asked them where they receive technological and specialized knowledge from. I typically ask “who do you turn to when you get stuck?”. In most cases, equipment suppliers, engineers employed by larger companies, or a junior lecturer with high levels of enthusiasm are identified as the most important sources of knowledge or technological advice. I have found this same pattern in many countries, the most important carriers of knowledge are not formal organizations, but individuals.

The result is that the cost of finding knowledge, or gaining access to scarce technology is high, and that those with broader networks are most likely able to gain access to this important resource while those that depend on public goods or generally available information are unable to access the necessary information.

I will explain in a future post how we can diagnose and improve the domain of technological institutions in order to improve the technological capability of enterprises.

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.


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.


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.

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