New publication: Knowledge, Technologies and Innovation for Development in the Agenda 2030: Revisiting Germany’s Contribution

The discussion paper I co-authored with Frank Waeltring recently for the GIZ and the BMZ is now available online. The name of the paper is “Knowledge, Technologies and Innovation for Development in the Agenda 2030: Revisiting Germany’s Contribution“. The paper was commissioned by the GIZ Sector project “Development Orientated Trade and Investment Policy and Promotion” on behalf of the BMZ.

Here is the foreword of the paper. It explains in a nutshell what this document is about.

It was a great privilege to be asked by the GIZ on behalf of BMZ to write a discussion paper on Germany’s contribution towards the Agenda 2030 from a knowledge, technology and innovation perspective as well as a great responsibility. Much deliberation and reflection has taken place in the last six years around this topic, but this work has by no means reached a conclusion as there is much more that can yet be done.

We support the view that a broader understanding of the role of science, technology and innovation is needed, and that building the capacity and capability of innovation systems in developing countries is vital. This is precisely what the Agenda 2030 and the Addis Ababa Action Agenda are demanding from the international development community and developing countries. The long-overdue global consensus on the role of science, technology and innovation as a cross- cutting theme is an exciting development, one which requires a re-think of traditional sectoral or topical development programmes and how they can benefit from this theme.

Our work in this field has made us well aware of Germany’s long-standing track record as a development partner in science, technology, knowledge and innovation support for develop- ing countries. This has been occurring not only on the of cial public policy level, but also on
a broader level where universities, science and technology organisations, economic development programmes and private companies are interacting, sharing, learning and exploring with counterparts in developing countries. The sheer diversity, depth and scale of the options that Germany can now offer may even appear to developing countries to be overwhelming and hard to navigate.

Although many elements of the German Innovation System are plainly visible and well known, beneath the surface there are elements that even our German counterparts sometimes overlook or take for granted. The German Innovation System is a complex one that is still evolving. It has a long history, and many of the current system features were shaped by intentional and unintentional decisions made long ago. Developing countries need help to fathom which ideas can be transferred and learned from, and which ideas are not suitable to their particular context. Furthermore, there are many factors that are not so obvious, which makes it harder to learn from or transfer ideas from Germany to developing contexts. In this respect we should always be aware that Germany’s science and technology activities are organised on a highly decentralised way, whereas in many developing countries science and technology decisions are often more centralised.

As Mesopartner we often work both on the side of the developing country and on the German side to broker relations, build networks, enable exchange and support knowledge and technology transfer. We have seen the extent to which German technology, support and expertise have made a difference in the countries in which we work, even when science, technology and innovation are not the main issues being dealt with. But we have also seen the shortcomings of too great a focus on hardware, training, patents and blueprints and too little emphasis on human capacity, partnerships, networks and adaptation to the local context.

 

We would love to hear your feedback on this discussion paper. It provided us with an opportunity to rework much of our previous work on innovation systems promotion in developing countries. There is also a chapter about the evolution of the German Innovation System.

You are welcome to also visit the publications page on this website where several of the other papers that I have contributed to are listed.

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: 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.

 

Teaching on innovation systems – afterthought

The post about how I teach on the topic of innovation systems two weeks ago really elicited a much bigger response than I expected. The tips, ideas, confirmations and questions received inspired me to think how I can share more practical training advice. I have a lot to share, simply because I love teaching on a wide range of topics. True to my mental construct of an innovator, I constantly develop small modules that can be combined, re-arranged, shortened or expanded to meet the requirements of the teams I support and coach.

For instance, the innovation systems outline that I explained in this previous posts consists of two parts: Part 1 is made up of modules on innovation and technology:

  • Innovation, invention and different kinds of innovation,
  • Knowledge generation in enterprises,
  • What is technology? Definitions, applications and implications of various definitions,
  • Different kinds of competition and its effect on the innovative behavior of enterprises,
  • Knowledge generation in enterprises and organisations

Part 2 then builds on this foundation with topics central to the promotion of innovation systems, with modules on:

  • Knowledge generation, co-generations and assimilation in societies,
  • Defining innovation systems,
  • Role of different kinds of economic and social institutions in innovation systems,
  • The importance and dynamic of building technological capability,
  • Systemic competitiveness as a way of focusing meso level institutions on persistent market failure,

If needed it is easy to bring in many other topics such as:

  • Technological change, social change, economic change (based on the excellent work by Eric Beinhoecker),
  • Assisting stakeholders to embrace sophisticated demand as a stimulus,
  • Diagnosing value chains,
  • Technology transfer, demonstration and extension, and so on

Yesterday I was reflecting with Frank Waeltring about the order of these sessions, why in my experience Part 1 goes before Part 2 and how difficult it is to present part 2 without the basics of part 1 in place. We reflected on why it is easier to start with foundation topics on innovation and technology management, and thereafter moving to the more abstract content of innovation systems.

In my experience, development practitioners and policy makers often believe the link between the subjects of innovation/technology management and innovation systems promotion is the concept of “innovation”. Almost as if innovation happens in enterprises, and innovation systems is then the public sectors way to make innovation happen in enterprises. This logic is an important stumbling block that many people I have supported struggle with. In my book on the promotion of innovation systems I created the following table to explain the difference.

Difference between innovation/technology management and innovation systems promotion

The connector between these two domains is not innovation (despite it being common two the names of the two domains). It is knowledge. Not necessarily formal knowledge (more engineers & phds = more innovation kind of over simplistic logic), but various forms of knowledge. Tacit knowledge. Knowing of who to speak to. Being exposed to other people from different knowledge and social domains. The costs and ease of getting information from somebody you know or don’t know. Learning from your own mistakes and the attempts of others.

Some places, countries and industries get this right, others struggle. Trust is central. This dynamic takes time to develop. You can sense its presence way before you can figure out how to measure it. While many of these issues can be addressed at a strategic level in an organisation like a company (or a publicly funded institution), many of these kinds of knowledge flows are inter-dependent and can be accelerated by taking an innovation system(ic) perspective.

The conclusion is a real tongue twister: The connection between the body of knowledge of innovation/technology management and the body of knowledge about innovation systems development is the body of knowledge on knowledge and how it emerges, gets assimilated, absorbed and further developed.

That is why knowledge generation, learning by doing fits in so well with part 1, but why it is not complete if not also addressed in part 2, especially the systemic elements of knowledge dissemination and absorption. It is the bridge.

 

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.

 

 

How I teach the topic of innovation systems

IMG_2533One of my favorite subjects to teach is about the promotion of innovation systems. I love it because it combines abstract elements that most people grasp, and practical elements that most people enjoy. Most academic literature on innovation systems are quite abstract, and our approach to identifying ways to improve an innovation system from its current state is quite pragmatic. The literature on managing innovation is very broad and contains millions of tips, theories, myths – actually it is overwhelming for practitioners wanting to support industries, firms and organizations to become more innovative. Therefore I try to explain the principles of both innovation systems and innovation management so that people can re-organize and use what they already know, and know where to relate new knowledge that they may encounter along the way.

SC_in_action

Trying to explain how to get exploration and safe 2 fail experiments to work

I typically start by laying some foundations, often using puppets, props or cartoons to make it slightly less serious (I use sheep characters, don’t ask why):

While most people intuitively understand that there are different kinds of innovation, most practitioners are surprised by how different product innovation, process innovation and business model innovation are. A great discussion usually takes place when people reflect on why business model innovation (Tim Kastelle states that it is easy but really hard) is really what hampers growth and productivity improvements, but how most industrial and innovation policies typically targets mostly product and process improvements.

Now that the foundation is in place, I typically move on to the more abstract issue of innovation systems. After explaining the definition (see the bottom of the post) that I like most, it is necessary to explain the importance of the dynamic between the different elements. It is natural to create checklists of institutions and actors and tend to forget that even in economic development weaker actors that interact more dynamically can trump first class institutions that are not accessible to most people that need support.

The importance of building the technological capability beyond the leading firms is important. I have written many posts about this so will not repeat this here, but for me the systemic nature of innovation and knowledge accumulation is critical. But typically we use 6 lines of inquiry to investigate how the dynamism in the system can be improved. There are four really important aspects which include:6 Four lines of inquiry_web

 

The agenda concludes with different ways practitioners and policy makers can intervene in the innovation system to improve the dynamics, the flow of information, the exchange of knowledge and the increased innovation appetite of entrepreneurs.

Duration

To present this agenda can take anything from 2.5 hours to three days. When the participants are experienced in diagnosing enterprises and public institutions, the exercises tend to be more meaningful and fun. When nobody in the room knows anything about the problems companies face on a day to day basis this kind of training is much harder. When I have more time then topics such as mapping formal knowledge flows, detecting unmet sophisticated demand, collaborating for research and development, etc can be included.

I have been presenting this session is various formats at international training events like our Annual Summer Academy in Germany, at different academic departments in universities. I frequently present this in some form to science, technology and industry government officials. In other occasions I have presented this to practitioners, development staff and even to the management of a university wanting to become more innovative itself.

The definition I work from:

The definition of innovation systems that I work from is the one of the earliest definitions on this subject. Freeman (1987:1) defined an innovation system as “the network of institutions in the public and private sectors whose activities and interactions initiate, import and diffuse new technologies.The emphasis is mainly on the dynamics, process and transformation of knowledge and learning into desired outputs within an adaptive and complex economic system.

The textbooks I teach from:

My favourite textbook that I use when teaching at universities remains FAGERBERG, J., MOWERY, D.C. & NELSON, R.R. 2005.  The Oxford handbook of innovation. Oxford ; New York: Oxford University Press.

If I have more of a business management audience, then I prefer to use a book with more innovation and technology management tools in it such as DODGSON, M., GANN, D. & SALTER, A. 2008.  The Management of Technological Innovation. Oxford University Press.

Of course, this agenda follows the logic of my own book on the promotion of innovation systems that I have published!

 

 

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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