Unlocking knowledge in organisations

A favorite topic that I love to talk, think and write about is the knowledge that is lurking around in organisations, often untapped.

Last week, the University of Stellenbosch Business School, where I am a member of faculty in the Executive Development programme, published an article I wrote in its thought leader newsletter. It is titled “Unlocking knowledge in organisations to enable innovation”. What started off as a 1200 word article was reduced to 700 words by Linton Davies, the wordsmith that always helps me to better express my ideas when I write formal publications. I think this article as it stands now must be the most I have ever said in only 700 words!

I am really proud of this article in its current short form. It started off many years ago as a much a more complicated module in my innovation systems training session. Now it is a practical workshop format that I use often in organisations supporting innovation, but increasingly in businesses, government programmes and even NGOs.

It is informed by evolutionary and complexity thinking, and is thus in line with my current research and the principles that I now pursue and value. Of course, a lot of extremely important theory is left out in this form, but by helping managers become more aware of how the inhibit or promote knowledge generation in their organisations is for me already a great start.

 

Instigating Innovation: Tech push fallacy is still alive

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

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

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

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

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

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

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

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

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

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

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

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

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

 

Source:

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

 

 

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.

 

Significance over scale when selecting sectors

When promoting territorial economic development from an innovation systems perspective it is important to find ways of increasing the use of knowledge and innovation in the region. However, in mainstream economic development there is a tendency to target the private sector based on scale. This means that practitioners look at quantitative measures such as jobs, numbers of enterprises, numbers of beneficiaries, etc. when deciding where to do analysis and focus support. This is common practice in value chain promotion, sub sector selection, etc. Many development programmes do this as well prioritizing scale measures such as jobs, women, rural individuals, etc.

From my experience of assisting development organisations to strengthen the economic resilience of regional economies (which means more innovation, more experiments, more diversity, increased use of knowledge, more collaboration between different technological domains), I have found that the scale argument is distracting and too focused on the beneficiaries (whatever is counted) and not focused enough on those indirect public or private agents that are significant and that enable a whole variety of economic activities to take place. With significant I mean that there could even be only one stakeholder or entry point (so the direct scale measure is low) but by addressing an issue it enables a whole variety of economic activities to take place.

Of course, scale is very important when a local politicians need votes. It is also important when you have limited budget and must try to achieve wide spread benefit. For this reason scale is very important for social programmes.

However, when local institutions are trying to strengthen the local innovation system, in other words improve the diversity technological capability of a region, then scale becomes a second priority. The first priority then becomes identifying economic activity that enables diversity or that reduces the costs for enterprises to innovate, use knowledge more productively should be targeted. The reason why this does not happen naturally is that these activities are often much harder to detect. To make it worse, “significance” could also be a matter of opinion (which means you have to actually speak to enterprises and their supporting institutions) while crunching data and making graphs often feel safer and appear to be more rigorous.

My argument is that in regions, the long term evolution and growth of the economy is based on supporting diversification and the creation of options. These options are combined and recombined by entrepreneurs to create new economic value in the region, and in so doing they create more options for others. By focusing exclusively on scale, economic actors and their networks increasingly behave in a homogeneous way. Innovation becomes harder, economic diversity is not really increased. I would go as far as saying that success becomes a trap, because once a recipe is proven it is also harder to change. As the different actors becomes more interdependent and synchronized the system becomes path dependent. Some systems thinkers refer to this phenomena as tightly coupled, meaning a failure in one area quickly spills over into other areas. This explains why whole regions goes into decline when key industries are in decline, the economic system in the region became too tightly coupled.

But I must contradict myself just briefly. When interventions are more generic in nature, meaning they address market failures that affect many different industries and economic activities, then scale is of course important.

The experienced development practitioners manage to develop portfolios where there are some activities that are about scale (for instance, targeting a large number of informal traders) and then some activities that are about significance (for instance ensuring that local conformity testing labs are accessible to local manufacturers).

The real challenge is to figure out what the emergent significant economic activities are that improves the technological capability in the region. New emergent ideas are undermined by market failures and often struggle to gain traction. Many new activities requires a certain minimum economic scale before it can be sustained, but this is a different kind of scale than when practitioners use scale of impact as a selection criteria. Many small but significant economic activities cannot grow if they do not receive public support in the form of promotion, awareness raising or perhaps some carefully designed funding support.

There are a wide range of market failures such as high coordination costs with other actors, high search cost, adverse selection, information asymmetry and public good failures that undermines emergence in local economies. It is exactly for this reason that public sector support at a territorial level (meaning sub national) must be sensitive to these market failures and how they undermine the emergence of new ideas that could be significant to others. The challenge is that often local stakeholders such as local governments have limited influence over public institutions in the region that are funded from other spheres of public administration.

Let me wrap up. My argument is that scale is often the wrong place to start when trying to improve the innovation system in a region. Yes, there are instances where scale is important. But my argument is that some things that could be significant, like the emergence of variety and new ideas often get lost when interventions are selected based on outreach. Furthermore, the focus on large scale impact draws the attention to symptoms of problems and not the the institutional or technological institutions that are supposed to address market failures and support the emergence of novelty.

I will stop writing now, Marcus always complains that my posts are too long!

Let me know if I should expand on the kinds of market failures that prevent local economies from becoming technologically more capable.

 

 

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.

 

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.

Innovation_invention

Herewith a list of synonyms from thesaurus.com 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)

 

 

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