Instigating Innovation: Accelerating Experimentation in industry

When innovation centers, technology transfer centers, applied research platforms and other similar organisations want to help industry with innovation, one way could be to assist companies to experiment with new ideas. I will simply refer to these centers from here onward as innovation and technology support centers. In most of the places where I work these centers are often hosted by or associated with universities, applied research organisations or with technology transfer organisations.

One way to support industry to experiment is through various technology demonstration-like activities, allowing enterprises access to scarce and sophisticated equipment where they can try new ideas. In its simplest form, facilities allow companies to order samples to a certain specification, allowing a company to see whether a particular process can meet a specification or performance criteria. A slightly more intensive form of tech demonstration allows in visitors and a technology and its application is demonstrated (eyes only, no touching!). Very often equipment suppliers play this role, but in many developing countries equipment suppliers behave more like agents and can not really demonstrate equipment.

In Germany I saw demonstration facilities where the pro’s showed the enterprises how things works, and then they stood back allowing teams from a company to try things themselves.

A critical role of innovation support centers is to provide industry with comparative studies of different process equipment. For instance, in an innovation center supporting metal based manufacturers, providing industry with a comparison of the costs and uses of different kinds of CAD systems could be extremely valuable to industry.

Maker labs, Fablabs and similar centers all make it easier for teams that want to create or tinker with an idea to gain access to diverse technologies, reducing the costs of experimenting. However, the range of equipment in these labs are often not so advanced, but it can often be very diversified. In my experience these centers are very helpful to refine early idea formation and prototyping. However, to help manufacturers experiment with different process technologies, different kinds of materials, substitute technologies, etc. is the a binding constraint in many developing countries. The costs of gaining new knowledge is high, and due to high costs of failure, companies do not experiment.

Innovation support centers must be very intentional about reducing the costs of various kinds of experiments if they want manufacturers, emergent enterprises and inventors to try new ideas. These innovation centers can play a role by:

a) assisting companies to internally organize themselves better for experimentation internally

b) assisting many companies to organize themselves better for experimentation collaboratively

c) conducting transparent experiments on behalf of industry collectives

In my experience, graduates from science disciplines often understand how to conduct experiments because their coursework often involve time in a lab. They know basics like isolating variables, managing samples, measuring results, etc. However, engineering graduates often do not have this experience (at least in the countries where I am working most). For many engineering graduates, the closest they will ever get to an experiment is a CAD design, or perhaps a 3D printed prototype.

Therefore, it is necessary for a range of these innovation and technology support centres to assist companies at various hierarchical levels to experiment.

At the functional or operational level, organising for experimentation involves:

  • creating teams from different operational backgrounds,
  • creating multiple teams working on the same problem,
  • getting different teams to pursue different approaches
  • failing in parallel and then comparing results regularly
  • failing faster by using iterations, physical prototypes and mock ups
  • According to Thomke, results should be anticipated and exploited – even before the results are confirmed

At a higher management level, organising for experimentation involves:

  • Changing measurement systems to not only reward success, but to encourage trying new things (thus encouraging learning and not discouraging failure).
  • moving from expert opinion to allow naivety and creativity
  • Preparing for ideas and results that may point to management failures or inefficiencies elsewhere in the firm (e.g. improving a process may be hampered by a company policy from the finance department)

Getting multiple companies and supporting organisations to experiment together is of course a little bit harder. Management of different organisations have many reasons to hide failures, thus undermining collective learning. One way around this could be to use a panel or collective of companies to identify a range of experiments, and then these experiments are conducted at the supporting institution in a transparent way. All the results (success, failures and variable results) are carefully documented and shared with the companies. However, to get the manufacturers to use these new ideas may require some incentives. In my experience, this works much better in a competitive environment, where companies are under pressure to use new ideas to gain an advantage. In industries with poor dynamism and low competition, new ideas are often not leveraged because it simply takes too much effort to be different.

Promising ideas from experiments can be combined and integrated after several iterations to create working prototypes. Here the challenge is to help industries to think small. First get the prototype process to work at a small scale and at lower cost before going to large scale of testing several variables simultanously. An important heuristic is to prototype at as small as possible scale while keeping the key mechanical or scientific properties consistent. More about this in a later post. (Or perhaps some of the people I have helped recently would not mind sharing their experience in the comments?)

I know this is already a long post, but I will add that Dave Snowden promotes Safe2fail probes, where teams are forced to design a range of experiments going in a range of directions even if failure is certain in some instances. In my experience this really works well. It breaks the linear thinking that often dominates the technical and manufacturing industries by acknowledging that while there may be preferred solutions, alternatives and especially naive experiments should be included in the overall portfolio. To make this work it is really important that the teams report back regularly on their learning and results, and that all the teams together decide which solutions worked best within the context.

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


Instigating innovation in traditional industries

The average manufacturer in a developing country grapples with the notion of innovation. That is why they are often called “traditional”, although almost each industry would have one or two outliers. While governments, like South Africa, offers incentives to stimulate innovation, most manufacturers do not identify with the term the way the governments use it. For instance, when governments use the word “innovation” they often mean “invention“, in other words something that can be protected, copyrighted and owned (more about the differences between innovation and invention here). While I understand the argument for patenting and protection I think this narrow definition of innovation is inhibiting many industries from increasing their productivity and competitiveness by copying what works from elsewhere (catching up). It also fails to recognize that in many value chains the manufacturers themselves make components or sub-systems that goes into overarching architectures (defined by standards, compliance, specifications), so their design authority is limited in scope.


Herewith a list of synonyms from for innovation that I have assessed to see how enterprises might understand or respond to these words:

  • Modernization – lots of enterprises dream about this but often do not have the many nor the organizational capability to pull it off (one day, next time)
  • contraption – many innovations and most inventions result in one of these. You can see them standing in the corners in most factories
  • Mutation, addition, alteration, modification – this is what most innovations in traditional industry would look like. They are doing this all the time as their machines gets older, but this behavior is mostly not recognized nor accelerated
  • newness, departure, deviation – the bolder enterprises with more financial and organizational capability might try these, but it takes capital to maintain.

Most people understand innovation as an outcome, but the word itself is a noun that implies change and novelty. It is about a shift, even if it is often incremental. The reason why so many of our enterprises here in South Africa are not deemed to be innovative is because they struggle (or perhaps do not have the organizational capability) to manage several simultaneous change processes. As Tim Kastelle posted some years ago, change is simple but not easy. Although this is often described as a technology problem it is really a management problem (see some older posts here). I would go even further and state that in many industries the margins are so thin that even those enterprises that have a reasonable management structure would struggle to finance many innovations at the same time.

However, in my experience of visiting more than 50 manufacturers every year I am always stunned and awed by how ingenious these companies are. They keep old machines running, often modifying them on the fly. They operate with fluctuating and unreliable electricity, inconsistent water pressure and often hardly any specialist support. What policy makers often do not recognize is that in developing countries it takes a lot of management time and capacity just to keep the throughput going. The time and effort to go explore “change” beyond what is necessary in the short to medium term is very expensive. The costs of evaluation new ideas, new technologies, new markets and better suppliers are all far more expensive in developing countries than elsewhere. Yet, at the heart of innovation is the ability to combine different inputs, different knowledge pools, different supporting capabilities with different market possibilities.

There are two implications for innovation promotion practitioners.

  1. The process of instigating innovation must start with recognizing how companies are innovating NOW. How are they modifying their processes (and products), and how much does it cost? What are the risks that are keeping them from introducing more novelty? Perhaps use the Horizons of Innovation (my next post) to create a portfolio of innovation (change) activities that can be identified at the enterprise or industry levels.
  2. It is hard if not impossible for different manufacturers in most countries to figure out what others are struggling to change at a technological level. Use your ability to move between enterprises to identify opportunities to turn individual company costs into public costs (this is often cheaper). Do not take the innovation away from enterprises, but use your meso level technology institutions to try and accelerate the learning or to reduce the costs of trying various alternatives. Be very open with the results to enable learning and dissemination of ideas.

The process of instigating innovation must start with recognizing where manufacturers are naturally trying to change, just like a change process in an organization must start with understanding current behavior, culture and context. Somehow innovation have become so associated with a contraptions and narrow views on technology that the organizational development body of knowledge and management of change have been left behind.

Innovation systems in Metropolitan Regions of developing countries

During 2015 Frank Waeltring and I were commissioned by the GIZ Sector Project “Sustainable Development of Metropolitan Regions” (on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), Division 312 – Water, Urban Development, Transport) to write a discussion paper about a hands-on approach to innovation systems promotion in metropolitan regions in developing countries. The discussion paper can be found here.

Frank (left) and Shawn (right) in front of the Berlin Wall Memorial

This assignment was a great opportunity for us to reflect on Frank’s experience on structural change in territorial economic development and my experience on industrialization and innovation systems in developing countries. We also had to think hard about some of the challenges of using a bottom up innovation systems logic in developing countries, as such an approach would rely heavily on the ability of local public management to coordinate strategic activities aimed to improve the dynamics between various public and private stakeholders. It was great to reflect on our past Local Economic Development experience and our more recent work on innovation systems, industrial upgrading and complexity thinking.

A key aspect of this discussion document was to think long and hard about where to start. We know many economic development practitioners in cities are often overrun by demands from both politicians and industries for support. We also know that by selecting promising sectors based on past data and assumptions about job and wealth creation often end in little impact and much frustration. We agreed that an innovation systems approach must be aimed at stimulating the innovative use of knowledge, so we decided to not start with a demand focus (assuming the officials are already responding to some of the demand) or with statistics but a knowledge application focus. The use, generation and recombination of knowledge is central to the technological upgrading of regions, industries, institutions and societies. From our experience in promoting innovation systems and our recent research into non-consensus based decision making (this is where you do not select target sectors based on consensus or assumptions about growth potential, but you look at emergent properties in the system) we decided to start with three questions to understand the dynamics of knowledge flows in the region:

  1. Which enterprises, organisations and even individuals are using knowledge in an innovative way? Obviously this question is not simple and can only be answered by reaching out in the local economy to institutions, firms and individuals.
  2. Which stakeholders are actively accumulating knowledge from local or external sources? Again, this is an exploration.
  3. Who are individuals or organisations that know something about unique problems (challenges, demands, constraints) in the region? These could be buyers, supply chain development officials, public officials, engineers or even politicians that are willing to articulate unique demands on the regional economy that might not have been responded on by local (or external) enterprises.

These three questions are treated as an exploration that will most likely be most intensive at the start. In our experience economic development practitioners should constantly be asking themselves these questions when working on any form of private sector upgrading.

A second dimension is about assessing the interplay between institutions and industries and its effect on innovative behavior within regions. Who is working with whom on what? Why? What are the characteristics of the life cycles or maturity of various kinds of stakeholders in the region? Thus we are trying to understand how knowledge “flows” or is disseminated in the region. While some knowledge flows are obvious, perhaps even formal, some knowledge flows could be more tacit and informal. For instance, while knowledge flows from education is quite formal, the informal knowledge exchange that takes place at social events is much more informal, yet very important.

Apart from the identification of the dynamics and interrelations between the industries and the different locations, one other key factor is to identify the drivers of change who want to develop the competitive advantages of the region.

We also present our technological capability upgrading approach as six lines of inquiry, some of which have been covered in earlier posts on this weblog:

  1. The company-level innovation capability and the incentives of firms to innovate, compete, collaborate and improve, in other words the firm-level factors affecting the performance of firms and their net-works of customers and suppliers. These include attempts within firms to become more competitive and also attempts between firms to cooperate on issues such as skills development, R&D, etc.
  2. The macroeconomic, regulatory, political and other framework conditions that shape the incentives of enterprises and institutions to develop technological capability and to be innovative.
  3. Investigation of the technological institutions that disseminate knowledge.
  4. The responsiveness and contribution of training and education organisations in building the capacity of industry, employees and society at large.
  5. Investigation not only of the interaction and dynamics between individual elements in the system, but of the whole system.
  6. Exploring poorly articulated needs or unmet demands that are not visibly pursued by the innovation system.

We, and of course our GIZ colleagues of the Sector Project Sustainable Development of Metropolitan Regions, are very keen to engage with the readers on these ideas? Please post your comments, questions to this weblog so that we can have a discussion.

Best wishes, Shawn and Frank (Mesopartner)



New series: Instigating Innovation

I have been developing a new capacity building method and training approach that brings together my work in innovation systems promotion  and my work on improving technology and innovation management. I call it “Instigating Innovation”.

I chose “instigating” because it has a more positive ring to it than provocation or incitement. While it is a noun with mainly a positive tone, it is a bit more aggressive than support, enable or encourage or even stimulating. I have been referred to in my past as an instigator of change so I thought this was a good idea.

Why was this effort firstly necessary and secondary so rewarding?

My work on innovation systems is mainly aimed at assisting meso-organizations such as technology transfer centres, research centres and universities to be more responsive to the needs of the private sector. While it only takes a few interviews by a senior decision maker from one of these institutions to a few leading enterprises to get the organization to improve its offering to the private sector, it does not solve the problem that these institutions often needs a continuous process of innovation itself. So while they can respond to the needs of the enterprises (for instance by launching a new service, or making a key technology available, etc), they often are not able to innovate constantly in order to anticipate what they private sector might need in the future.

With my other hat on, working in the private sector to improve the management of technology and innovation is focused on helping individual and on rare occasions, groups or networks of enterprises to formalize or improve their management of innovation. Here my challenge is that most enterprises innovate by accident, or have elements of an innovation management approach in place without knowing it. But it is not systematic nor is it consistent.

So both supporting institutions and enterprises lack some very basic frameworks to focus their existing development and learning processes to ensure not only short term results (new products & services, process improvements, cost reduction, etc) but to also ensure longer term success (playing in the right markets, selecting the right technologies, investing in the right kind of knowledge, partnering with the right people, etc). Furthermore, most enterprises and supporting institutions have something else in common: they often face resource constraints with the most versatile of their staff being involved in problem solving and not thinking about the future and what may be possible sometime down the line.

I set aside most of March and had great fun reading through my collection of articles, books, reports of past missions, and speaking to entrepreneurs and development practitioners I trust. Based on this investigation I decided on the following criteria for instruments to include in the Instigating Innovation module:

  1. Each instrument or concept must be relevant to both enterprises and meso-level organizations05 building innovative capacity small
  2. Each instrument must provide a very simple framework that can be illustrated on a flipchart
  3. The simple framework must be usable as a workshop format that allows people to reorganize or explore their current and future practices
  4. The frameworks must be scalable, both in depth (allowing pointers for a deep dive into an issue) and in width (useable for a product, issue, portfolio or the strategy of the organization as a whole).
  5. Lastly, I did not want to be the consultant with a project, I want to be the facilitator that enables change and that builds long term sustainability into the organizations that I work with.

This was a very rewarding exercise. Not only do I love reading about innovation, change and technology, I love finding better ways to explain these concepts. It was also great to find a way to connect my work on innovation systems, which often seems abstract, with the tough decisions that the enterprises that I work with must confront and address. I tend to work in the more technical domains dominated by academics, engineers, scientists and manufacturers, so finding a simple yet convincing way to add value to what these clever people do was important.

I will in the next few posts reveal a little bit more of the tools I selected and how it can be used.

Thank you for the EDA team in Bosnia and Herzegovina who motivated me to turn this idea into a capacity building format and who agreed that I try “Instigating Innovation” on their team during my visit to Banja Luka in May 2015!

Instigating Innovation in Banja Luka with the team from EDA

Instigating Innovation in Banja Luka with the team from EDA

Industry development under conditions of complexity

Most economic development projects have a tendency to separate analysis from intervention or implementation. This follows on an engineering approach where you must first understand a problem or issue before you can design interventions which is then logically followed by implementation and later on evaluation. I will not now go off on why this logic is questionable as I have written about this before and we have dedicated the website to this topic.

But complexity thinking is challenging this norm of separating analysis and intervention.

Auwhere to gothors such as Snowden argues that under conditions of complexity, the best approach is to diagnose through intervention, which means that there is no real separation between diagnosis and intervention. Practically, you might have to spend some days and a little bit of effort to analyze who is interested in a particular issue so that you know where to start, but you have to recognize that even asking some simple questions is in itself already an intervention. Furthermore, the objective of working under conditions of complexity is to introduce more variety so that different approaches to overcoming constraints can be tried out simultaneously. This means that small portfolios of experiments must be developed and supported, trying many different ways to solve a problem. Many of these are guaranteed to fail, but new novelty will also arise. The health of a system depends on more options being proven viable. Strong alignment of interests, priorities and interventions are actually unhealthy for a system in the long run.

I’ve had this discussion many times with fellow practitioners in the last years and usually at some point somebody would say “but not everything is complex”. I agree. They would argue that there are definite casual relations between for instance education and economic development. Well, this may be true in some places. However, whenever a government (or a donor) decides that a particular sector or industry requires support it should assume that the issue is much more complex than it may appear, otherwise the industry actors and supporting organizations and demanding clients would have sorted things out by themselves.

The idea that diagnosis takes place during intervention has many detractors, despite the fact that many strong economic development organizations intuitively follows this process logic of working with diverse stakeholders in an ongoing process. Here is a short list of some of the detractors and their main reason for resisting such a process approach:

  • Large consulting firms: They would fight this approach as processes are much more difficult to quote and manage than a clearly defined project. Furthermore, this kind of approach depends on more expensive multidisciplinary experts that require a combination of technical, facilitation, change and business skills. The number of people that can support such a process are few and far in between.
  • The public sector: To overcome constraints created by complexity requires that dissent be nurtured and premature alignment be avoided. This is also risky for the public sector as things may not be so neat nor supportive of past policies and decisions. Furthermore, when more options are created it is not certain which firms will really take up the solutions – meaning that in a country like South Africa with strong benefit bias this is too risky, as preferred candidates might not be the beneficiaries of public support.
  • Donors and development organizations: Simple cause and effect interventions that depends on controlling certain inputs in order to benefit specific target groups still dominate the logic of donors. Therefore a process that is not specific, and that explores different alternatives may not be appealing to donors. Furthermore, donors are expected to be able to very precisely report not only in inputs, but also on impact. A process that has multiple shifting goal posts makes planning and resource management very difficult. However, many examples exist of donor supported projects that are very open to this approach, but this is mainly the prerogative of the programme managers deployed into the field – it is not systemic.
  • The private sector: Yes, even firms may resist an open ended and exploratory approach. One reason is that firms try to push the problems experienced in the private sector back onto the public sector (blame and responsibility shifting). An exploratory approach puts much more onus on the private sector to not only contribute, but to be open for alternatives and to then actively pursue opportunities that arise. Secondly, the incumbents in the private sector sometimes profits from a disorderly system. Many existing firms will resist newcomers trying different things and trying to create new markets, as this disrupts the way things are done at the moment. In a complexity sensitive approach we have to on purpose introduce novelty into the existing structures, and this means challenging some of the dominant views and agreements about what is going on, what must be done and why nothing has changed. This is very unsettling for the existing actors.
  • Top management in an organization: Management science in itself assumes many casual relations. For instance, strategy development typically starts with defining a vision and objectives, and then making sure that everyone is aligned and committed to these goals. As one of my favorite strategy David Maister argued  “strategy means saying no”. This means that resources are dedicated to a few specific areas in the belief that addressing these would have predictable and desirable effects.

Now I must state that in more ordered domains, where there is less complexity, many of the arguments outlined above are valid. In a small organization with limited resources priorities must be set. Governments cannot help everyone, so somehow a selection must be made. However, I believe that industry development is in many cases complex also because it is so hard to see how unpredictable effects will affect an industry.

I am grateful that I work with organizations that are willing to embark on industry development or institutional development processes that are more complexity sensitive. I believe that such an approach is particularly important for innovation systems promotion and for industrial policy. I am surprised at how many manufacturers and universities have agreed to embrace a more complexity sensitive approach to development, strategy formation and developing new services/products. All involved have been amazed at the early results this far, as these processes typically unleash a lot of energy and creativity by different stakeholders that in the past were more than willing to just observe from a distance what was going on.

Recognizing competing hypothesis as complex

In order to improve the economic performance of an industry or a territory, it is important to recognize the current Status Quo of the economy. This is basically to understand “what is?”, but to also understand “what is possible next?”. You may think that local stakeholders, firms and public officials will know the answer to “what is going on now?”, but every time I have done such an assessment I have discovered new suppliers, new innovations, new demands and many new connections between different actors.

The benefit of being a facilitator, process consultant or development expert, is that we can move between different actors, observe certain trends, recognize gaps and form an overall picture of what we think is going on. It is very difficult for enterprises to form such a picture as they can only observe other firms from a distance.

The main challenge is about figuring out what can be done to improve certain gaps or to change the patterns that we observe. These are answers to “What is possible next?” questions . As Mesopartner, we always insist that any process to diagnose an industry or a region starts with the formulation of various hypothesis. This hypothesis formulation before we commence is not only about revealing our bias, nor only about figuring out what exactly we want to find out. It also helps us to figure out what kind of process is needed, the scope of the analysis and what different actors expect from the process.

Unlike in academic or scientific research, hypothesis formulation does not only happen in the early stages of a diagnostic or improvement process, it should be constantly reflected upon and expanded as we go on during the process of meeting stakeholders and analyzing data. This is where the importance of recognizing competing hypothesis within our team and between different stakeholders are important.This process is not about convergence, but about revealing what different actors and the investigator believes is going on.

Economic development practice is full of competing hypothesis that all seem to be very plausible. In a recent training event with Dave Snowden the consequences of not recognizing or revealing these competing hypothesis struck me. According to Dave, competing hypothesis that plausibly explains the same phenomena indicates that we are most likely dealing with a complex issue. For instance, in South Africa we have competing hypothesis about the role of small firms in the economy. One hypothesis is that small firms are engines of growth and innovation, therefore they deserve support. A competing hypothesis is that large firms invest more in innovation and growth, and that they are better drivers of economic growth. Both hypotheses are plausible – the issue is complex. Recognizing this complexity is very important, as the cause and effect relations are not easy to identify and they might even be changing – the situation is non-linear. (Marcus Jenal and I wrote a working paper on complexity in development). This simply means that to get a specific outcome, the path will most likely be indirect or oblique – cause and effect is not linear.

Why is it important to recognize competing hypothesis, or to know when some patterns in the economy or complex? The answer is that it is almost impossible to analyze a complex issue with normal diagnostic instruments. Complex patterns can only be understood by engagement, that is, through experimentation. Again, according to Dave Snowden, you have to probe a complex issue by trying several different possible fixes simultaneously, then observe (sense) what seems to work best under the current circumstances. The bottom line is that you analyze a complex issue by experimenting with it, not by observing or analyzing it.

The implication of this insight in my own work has been huge. By recognizing that many issues that I am dealing with are complex (due to competing hypothesis that are very plausible) and can only be addressed through direct engagement has saved me and my customers a lot of resources that was previously spent on seemingly circular analysis. I now use the hypothesis formation with my clients to try and see if we have competing hypothesis of “what is” and “what must be done”. Where the hypothesis seems to be straight forward, we can define a research process to reveal what is going on and what can be done to improve the situation. But when we have different competing hypothesis of what is going on, we have to immediately devise several simultaneous experiments to try and find an upgrading path. I thought my customers would not like the idea of experiments, but I was wrong.

The conditions are that you must take steps to ensure that there are many different experiments that are all very small, and that by design take different approaches to try and solve the same problem. This takes learning by doing to a new level – because now failure is as important as success as it helps us to find the paths to better performance by reducing alternatives and finding the factors in the context that makes progress possible. The biggest surprise for me is that this process of purposeful small experiments to see what is possible under current conditions (context) has unlocked my own and my customers creativity.

Perhaps a topic for a separate blog is that to really uncover these competing hypothesis we have to make sure that we do not converge too soon about what we think is going on. Maintaining divergence and variety is key – this is another challenge for me as a facilitator that is used to helping minds meet!

Linking: Change: simple, but not easy by Tim Kastelle

I am humbled that Tim Kastelle has quoted a paragraph from a recent blog I wrote in an article he just published on Change and why it is simple but not easy.

For my students and online learners, I recommend that you also subscribe to Tim’s blog as he deals with many issues relating to innovation and especially business model innovation.


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