Shawn Cunningham: Thinking out loud

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  • 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

     

     

  • Between a rock and a hard place. Sectoral vs. local approaches to private sector development

    I am preparing for a presentation at a conference in May about development programmes shifting from a sectoral to a regional or local perspective. This got me thinking about these shifts in focus and why they appear.

    In economic development, it is often necessary to choose whether to intervene at a sectoral level, or whether it would be better to take a locational or geographic approach. In my experience I have learned that when you start with the one, i.e. with a specific sector or value chain, you often end up with the other, i.e. supporting specialization or addressing specific issues in a certain location. But this is of little consolation to managers of development programmes and Local Economic Development units who are then typically measured by the wrong indicators or that have different incentives due to the design of their programme or institutional mandate.

    During my MBA, the Professor in Organisational Development introduced us to a really elegant tool to assess whether a tension or conflict between different approaches could really be addressed. He introduced us to Polarity Management, a simple instrument developed by Johnson (1992). According to Johnson, many problems that we face today are not really problems to be solved, but polarities to be managed. Johnson argues that we can continually try to solve these problems by shifting our strategies to another mode where we perceive lots of benefits. The trouble is that after a while of some negative aspects emerge, and suddenly the benefits of the other strategy seems to be more attractive.

    Polarity management is an instrument that can be used by change management practitioners to understand these polarities and to manage them. It implies that perhaps these different strategies even depend on each other, like breathing in versus breathing out. We need both, even if they have very different objectives, benefits and downsides. This means that the strengths and the weaknesses of alternatives must be understood, and then managed.

    In development we have many polarities, for example wealth creation versus poverty reduction, or designed interventions versus enabling evolution, project versus process, top down versus bottom up, and many others. It is very expensive and even risky to shift between these, and an organisations current expertise, instruments and orientation may find it very hard to make these shifts effectively. But some try and some even manage to do this.

    This post is for those organisations that are undecided about their strategy and their focus.. A key question then is how do we manage these alternatives, especially if we want the best of both worlds?

    There are 3 steps to better understand a polarity:

    1. Fill in the headings of the two polarities in the matrix
    2. Capture the strengths and the weaknesses of both in the columns
    3. Determine if there is a movement of preference between the polaries, meaning that when the negative consequences of a particular strategy becomes too much, strategy is shifted to the other approach for its apparent strengths. Then over time, the negatives start to weight in on the positives, resulting in a shift to the other approach.

    Below I have quickly written down some of the positives and negatives of both approaches. This is an incomplete list but I think it is sufficient to illustrate the point. The PDF of the graphic below can be found here. For those that cannot read so small, the bottom line is this: there are pluses and minuses to both paradigms. Under each strategy, the benefits of the one approach may outweigh the negatives of that approach, but be aware, these weights are changing and after a while the other strategy may become more desirable!

    Polary table

     

     

     

     

     

     

     

     

     

     

     

     

    The third step in understanding the polarity is to look at whether there is a shift between these polarities. From my experience working in a dozen or so developing countries, development programmes are either designed to be sectoral or geographic, with very few programmes designed to do both. From a local perspective, institutions and programmes are designed and resourced to either be targeted at specific industries and sectors, or they have a locational focus. It is very hard for programmes and institutions to build a case that a strategic shift to the other paradigm may be needed, even if for only a part of the resources to be dedicated to the other approach. This typically happens when the negatives of a current path starts to outweigh the positives, and the benefits of the other approach increasingly looks appealing. The danger is that a compromise is reached, instead of a synergy being developed.

    From a Local Economic Development perspective, growing the technical capability to pursue both strategies simultaneously is important. This does not imply that both are equally important at any given time, as both these approaches have different timescales, resource requirements, and objectives. For example, it would be unwise to leave a dominant sector to its own devices in order to focus on emerging enterprises. At the same time, focusing on the issues of a dominant sector might distract attention from purposefully promoting emergence, diversification and economic resilience. Yet, many programmes and organisations are forced to choose, often too early when not enough is understood about the dynamics of the place or the industries. For me the worst reason to choose an particular approach is because some or other decision maker has attended a training course or conference, or because a particular approach is deemed “best practice”. In fact, most of my time is spent trying to help leaders and decision makers get out of a mess because their programme or institutions was designed based on some ideology or “solution” without enough attention being given to the requirements, trajectories and complexity of the specific context.

    For national governments and international development programmes there seems to be a continuous shift between these two. Almost like a flip-flopping from one to the other. I think that the shifts are counter productive, as the learning from the previous shifts are often lost. If I just think back over my 16 year career how often the value chain or sub sector approaches or alternatively cluster and Local Economic Development have become fashionable again and then losing its appeal after a short time.

    My conclusion is that while there is a tension between these approaches, the shifting between the strategies are not taking place at an institutional or programmatic level. Decisions about these strategies are made at higher levels of government and development cooperation with little regard for the challenges faced at sub national level in developing countries to build and grow “the right” institutions that can ensure long term economic evolution and development.

    At the implementation level, regional development programmes should do both:

    • Sectoral programmes that ignores the impact of their sector on the geographic areas they are working in are most likely creating negative externalities, even with the best intentions in mind and even when they achieve their objectives of inclusiveness, job creation or export promotion. The negative externalities could be about the environment (mono economy, mono culture), or about increasing the coordination cost of every economic activity not related to the priority sectors (institutional or locational lock-in to particular paths and trajectories). Sectoral programmes that ignore opportunities for regional nuances to develop in their targeted sectors miss important opportunities to enable diversification and emergence of unique regional capabilities.
    • Location development programmes that do not collaborate with other locations to build sufficient scale in particular sectors to justify investing in particular regionally significant institutions will forever remain trapped in low value add, or perpetual dependence on the priorities and mood shifts of national governments. While trying to help every kind of economic activity in a region, you have to at some point also start promoting specific industries and sectors in order to try and reach some leverage or scale.

    But most importantly, the economic activity, available institutional capabilities and the regional context prescribes where to start. And when you have started down a chosen path, be sensitive to when it may be necessary to foster additional organisational or collaborate with other institutions with different more adequate capabilities to enable the benefits of the other strategy to be leveraged. A key challenge in developing countries is that we do not have a rich layer of supporting institutions pursuing different strategies. Everyone seem to be trying more or less the same approaches, or chasing the same politically set targets.

    In our capacity building sessions in Mesopartner we always elaborate on the importance of value chains and sectors to Local Economic Development practitioners, and the importance of regional competence development for value chain and sector development specialists. Actually, the process of diagnosing industries and regions are very similiar, even if you would give slightly more attention to different issues and perspectives.

    In the end, from a bottom up perspective, supporting specific industries allows for scale and focused public investment, but caution must be taken to not create path dependence or institutional lock in. At the same time, a regional approach is critical as it allows for emergence of new kinds of economic activity and for diversity to emerge. I think we need to development of synergies for both, but it depends on the context what your priority should be. Simply being aware that there are pluses and negatives to either strategy is already a good start! This makes it much easier to collaborate with other organisations and programmes that have different objectives and priorities.

    Now I have some questions to my readers:

    1. What is your current approach in your programme or organisation? Sectoral or locational?
    2. Have you even been through a shift from the one to the other in your programme, or do you cater for both?
    3. How did making the shift work out? Did you have the networks, resources and expertise to make this shift?
    4. What would you do differently next time?
    5. Please share your thoughts by commenting below, or send me an email if I can paste your comments unanimously if you are afraid to upset somebody higher up the chain.

    References:

    JOHNSON, B. 1992.  Polarity management : identifying and managing unsolvable problems. Amherst, Mass: HRD Press.

     

  • Instigating Innovation: Accelerating Experimentation in industry

    Originally published Feb 2016, revised March 2018

    When innovation centres, technology transfer centres, applied research platforms and other similar organisations wish to help industry with innovation, one way could be to assist companies to experiment with new ideas. I will simply refer to these centres from now on as innovation and technology support centres. In most of the places where I work these centres are often hosted by or associated with universities, applied research organisations or 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 out new ideas. In its simplest form, a facility allows a company to order samples to a certain specification so that the company can see whether a particular process will be able to meet a particular specification or performance criterion. A slightly more intensive form of technology demonstration allows visitors in 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 act more as agents and cannot really demonstrate equipment.

    In Germany I saw demonstration facilities where the pro’s showed the enterprises how things work, and then they stood back to allow teams from companies to try things out themselves.

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

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

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

    a) assisting companies to 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 course work often involves time in a lab. They know basics such as isolating variables, managing samples, measuring results, etc. However, engineering graduates often do not have this experience (at least in the countries where I have mostly been working). The closest many engineering graduates 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 regularly comparing results
    • 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 not only to reward success, but to encourage the trying of 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 more difficult. Management of different organisations have many reasons to conceal 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 to have these experiments conducted at the supporting institution in a transparent way. All the results (successes, 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 on a small scale and at lower cost before going to large scale of testing several variables simultaneously. An important heuristic is to prototype on as small a scale as possible 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 section?)

    I know that this is already a long post, but I should like to add that Dave Snowden promotes Safe2fail probes, where teams are forced to design a range of experiments going in a variety 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.

     

    Source:

    THOMKE, S.H. 2003.  Experimentation matters: Unlocking the potential of new technologies for innovation. Harvard Business Press.

     

     

  • Blunders, boo-boos and silly mistakes made on the fly

    I am acutely aware that I often make grammar and spelling mistakes in my blogs. I do apologize about these.  I feel silly when I realize I made a mistake. I have no excuses. As my favorite cartoonist Hugh Macleod @gapingvoid put it, excuses are a disease.

    excuses are a disease

    The intention of my blog is not to write perfectly composed articles, but to share my thinking with a broader audience than just the small group of clients, collaborators and friends in my network that I get to work with on a frequent basis. Ask me about those perfect articles and books and I can tell you which ones to buy. I collect them.

    Just like the practitioners and decision makers that I support have to confront clients, decisions and complexities without always having time to perfectly prepare; so I capture conversations, arguments or ideas developed with my clients – on the fly. The point is that in the field knowledge and ideas are not always perfectly described, neatly organised, thoroughly prepared. Sometimes the best explanations happen on napkins, flipcharts or a piece of paper.

    brave as those who need us

    The purpose of my blog site is to help the people I work with to explain some of these concepts on the fly. Hopefully they can do it shorter than it sometimes takes me, or maybe they can even do it more eloquent. Every time these concepts or thoughts are explained it becomes easier and easier.

    I found it works best to write at my client sites, on the way home (on the plane, not while driving – yet), or between meetings – and then to post these articles before I start doubting the relevance of my ideas or the insight gained by explaining something to somebody (yes, most of my posts are based on real conversations with clients out there facing complex situations). I have a huge collection of articles written in the safety of my office, far from the coalface, that I have never published because they suddenly seem less than perfect or even insignificant. It is easy to feel challenged when I sit in my office surrounded by books written by articulate scholars. I wish I could say these scholars always inspire me to write, but that would not be honest. Sometimes they do. Especially when I can connect the different kinds of literature that I have collected over time. However, often this collection makes me feel discouraged. I just have to look at the amazing content my late friend Jorg Meyer-Stamer wrote on a wide range of topics to feel like I should rather not commit anything to the official record.

    I assure my readers that when the text on these blogs make it into other publication forms I usually first get an editor to fix all those pesty grammar mistakes. 

    I thank those of you that read regularly, those that share your ideas with me – even if you don’t agree with everything I post. Thank you for pointing out the mistakes, the inconsistencies or your disagreements with what I post. I especially want to thank those that also take the risk of sharing their comments on Linkedin or directly as a comment to this blog, because you also take the risk of making mistakes or feeling exposed. Please don’t stop. I won’t. 

    Honest feedback

    I have often considered stopping blogging, just like I often wanted to quit co-producing the LEDCast (more than 1,000,000 downloads now!!) on many occasions, also due to my challenges to say ‘s’ or ‘r’ when my tongue gets tied. Somehow the workarounds when I speak have made its way into my writing.

    So as long as I receive your ideas, comments, notes, emails, tweets and calls I will keep on blogging.

     

     

  • 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.

     

     

  • 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.

     

  • How I teach the topic of innovation systems

    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!

     

     

  • Instigating innovation in traditional industries

    Originally published in January 2016, revised in March 2018

    The average manufacturer in a developing country often grapples with the notion of innovation. That is why such industries are often called “traditional“, although almost all industries will have one or two outliers. While governments, such as the South African government, offer incentives to stimulate innovation, most manufacturers do not identify with the term “innovation” the way 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 (see 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 elsewhere (this is just a process of catching up). It also fails to recognize that in many value chains the manufacturers themselves make components or sub-systems that go into overarching architectures (defined by standards, compliance, specifications), so their design authority is limited in scope.

    Innovation_invention

    Here is a list of synonyms from thesaurus.com for innovation that I have assessed to see how enterprises might understand or react to these words:

    • Modernization – many enterprises dream about this but often do not have the financial means nor the organizational capability to pull it off (one day, some other time)
    • Contraption – many innovations and most inventions result in one of these. You can see them standing in  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 get older, but this behaviour is mostly not recognized nor speeded up.
    • 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 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 in South Africa are not regarded as 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 narrow 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 having visited more than 50 manufacturers every year since 2009, I am always stunned and awed by how ingenious these companies can be. They keep old machines running, often modifying them on the fly. They operate with a fluctuating and unreliable electricity supply, inconsistent water pressure and often hardly any technical support. What policy makers often do not realize 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 and explore “change” beyond what is necessary in the short to medium term is very costly. The costs of evaluating new ideas, new technologies, new markets and better suppliers are all far greater in developing countries than in developed countries. Yet at the heart of innovation is the ability to combine different inputs, different knowledge pools, and 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 they could use the Horizons of Innovation 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 as a change process in an organization must start with understanding current behaviour, culture and context. Somehow innovation has become so associated with contraptions and narrow views of technology that the body of knowledge of organizational development 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)