71 Innovation Methodologies

A while ago I sat down with Machiel Wetselaar & David van Dinther to create a list of innovation methodologies for a course we’re developing. Up to now we’ve gathered 71 different methodologies for implementing innovation in your organization. We are still looking for ways to categorize them, but for now we’ve based our categorization on the maturity of the organization.

We’re pretty sure there are many more methodologies out there. Please drop a comment if you would like one or more methodologies included in this overview. The list is almost random.

Enjoy!


Innovation Cycle (Avans)

Focus stage: Growth
Published: 2013
source…

The Lean Startup (Ries)

Focus stage: Early-stage
Published: 2010
source…

The Lean Enterprise

Focus stage: Maturity
Published: 2011
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New Product and Development Service Process (Hauser)

Focus stage: Maturity
Published: 1980
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New Product Development Front End (Khurana)

Focus stage: Early-stage
Published: 1997
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Stage-Gates NPD Process (Cooper)

Focus stage: Maturity
Published: 1986
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Revolutionizing Product Development (Wheelwright & Clark)

Focus stage: Maturity
Published: 1992
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PACE NPD Funnel

Focus stage: Maturity
Published: 1992
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MIT CIPD Funnel

Focus stage: Growth
Published: 1995
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New Product Development Funnel (Katz)

Focus stage: Early-stage
Published: 2011
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Open Innovation (Chesbrough)

Focus stage: Maturity
Published: 2005
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Open Innovation Kick-Start Approach (AT Kearney)

Focus stage: Early-stage
Published: 2013
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Open Innovation Requirement Model (AT Kearney)

Focus stage: Growth
Published: 2013
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Experiments Open Innovation (Guinan)

Focus stage: Maturity
Published: 2013
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Human-Centered Design (IDEO)

Focus stage: Seed
Published: 2014
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Updated Model of Design Thinking

Focus stage: Seed
Published: 2013
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Double Diamond (Chu)

Focus stage: Seed
Published: 2014
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Design Thinking Process (Stanford)

Focus stage: Seed
Published: 2012
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Crowdsourcing (Whitla)

Focus stage: Growth
Published: 2009
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Crowdsourcing Process (Geiger)

Focus stage: Early-stage
Published: 2011
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Design Competitions

Focus stage: Early-stage
Published: 2012
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Stage-Gate Model in Crowdsourcing (Saldanha)

Focus stage: Maturity
Published: 2014
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Developing Crowd Capabilities (Prpic)

Focus stage: Maturity
Published: 2014
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Co-Creation (Prahalad)

Focus stage: Growth
Published: 2004
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Co-Creating Value (Ramaswamy)

Focus stage: Maturity
Published: 2008
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Morphology of Co-Creation (Bartl)

Focus stage: Early-stage
Published: 2004
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Taxonomy of Co-Creation (Zwass)

Focus stage: Maturity
Published: 2010
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Open Innovation Customer Integration (Reger)

Focus stage: Maturity
Published: 2009
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External Sources (West)

Focus stage: Maturity
Published: 2011
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Managing Distributed Innovation (Bogers)

Focus stage: Maturity
Published: 2012
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Managing Unsolicited Ideas (Alexey)

Focus stage: Maturity
Published: 2012
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Innovation Circle (Berenschot)

Focus stage: Maturity
Published: 2009
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Chain-Linked Model (Kline)

Focus stage: Growth
Published: 2014
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Delft Product Innovation Model (Buijs)

Focus stage: Maturity
Published: 1980
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Roadmapping

Focus stage: Maturity
Published:
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Design for Six Sigma (Idov)

Focus stage: Maturity
Published:
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Value Engineering (Miles)

Focus stage: Maturity
Published: 1945
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TRIZ (Altshuller)

Focus stage: Seed
Published: 1946
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Systematic Inventive Thinking (Connoly)

Focus stage: Seed
Published: 1993
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Scenario Planning (Stratfor)

Focus stage: Growth
Published: 2015
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Multy-Dimensional Framework for Organization Innovation (Crossan)

Focus stage: Maturity
Published: 2010
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5R Trend Model (Bosma)

Focus stage: Seed
Published: 2012
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Deep Dive (Ideo)

Focus stage: Seed
Published: 2010
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Experience Design Process (Armano)

Focus stage: Seed
Published: 2006
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Business Model Generation (Osterwalder)

Focus stage: Early-stage
Published: 2010
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Value Proposition Design (Osterwalder)

Focus stage: Early-stage
Published: 2014
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Customer Development (Blank)

Focus stage: Early-stage
Published: 1996
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End-to-End Innovation Process (Furr)

Focus stage: Early-stage
Published: 2014
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Hourglass Model (Gaspersz)

Focus stage: Growth
Published: 2006
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Citizen-Drive Innovation (World Bank)

Focus stage: Maturity
Published: 2015
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Innovation Challenge (Herbert)

Focus stage: Maturity
Published: 2015
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FORTH Innovation Method (Wulfen)

Focus stage: Early-stage
Published: 2015
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Productive Thinking (Hurson)

Focus stage: Seed
Published: 2007
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101 Design Methodology (Kumar)

Focus stage: Growth
Published: 2012
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The Art of Thought (Wallas)

Focus stage: Seed
Published: 1926
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Process of Creativity (Gill)

Focus stage: Seed
Published: 2013
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Creative Problem Solving (Isaksen)

Focus stage: Seed
Published: 2005
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IDEAL Cycle (Stein)

Focus stage: Seed
Published: 1984
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Possibility Thinking (Burnard)

Focus stage: Seed
Published: 2006
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QCA Research Process (Ragin)

Focus stage: Early-stage
Published: 2013
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Fast Track Innovation (Deloitte)

Focus stage: Growth
Published: 2012
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Innovation Generation Process (Gopalakrishnan)

Focus stage: Maturity
Published: 1997
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Innovation Audit (Adams)

Focus stage: Maturity
Published: 2006
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Innovation Strategy (Goffin)

Focus stage: Maturity
Published: 1999
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3G Innovation Model (Rothwell)

Focus stage: Maturity
Published: 1992
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Innovation & Entrepreneurship (Bessant)

Focus stage: Growth
Published: 2013
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Development Funnel (Bessant)

Focus stage: Growth
Published: 2013
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 This article was written by Jan Spruijt. Jan Spruijt is a senior lecturer and entrepreneur in Innovation Sciences. Connect with Jan to stay in touch:

 

Remember me? I’m a Silly Valley Serial Entreprenerd Unicorpse. I like to leverage Start-Up Jargon.

Remember me? I’m a Silly Valley serial entreprenerd. I’m well-known for using startup jargon, which I learned from Forbes, Fortune and TechCrunch. Shall I share my story with you? Beware: this small piece of text contains 73 jargon words.

When I was 16 I launched my first B-to-B business. Some FFF helped me to leverage my first MVP and both an incubator and accelerator thought that monetizing the Business Model would disrupt existing markets using our bleeding edge technology and lead to ROI quickly. In the beginning the business was just ramen-profitable, but by pivoting our way through the first months, iterated the profit model to a B-to-C market, we created traction, penetrated new markets and gathered the low hanging fruit.

Some angel investors acknowledged the hockey stick we didn’t know we were and we were suddenly valuated as a My Little Pony. We agreed on a term sheet, with some interesting metrics and cliff details. But more importantly, we co-created with accredited investors to reach the VC Series A round, because we wanted to become a centaur.

Became pretty serious now, we were no longer a cottage business. We started with SaaS, changed to Freemium/strong> with some gamification elements along the way, implemented responsive design and had a good enough runway to scale-up for a while. Yes, we also build a good deck and pitched to a range of capitalists. We promised them boot-strapping, sweet equity and an excellent burn-rate. Our value prop was valued at unicorn-level, we got FMA and a great exit strategy scenario ready.

When I was 16 and a half, my business had the most opium in our space and we were definitely crushing it. We were an excellent example of a lean start-up, growth-hacked ourselves into the Bay Area. We bluffed our way through funding rounds, shouting we were Non-GAAP Profitable, cashflow positive and had 500% growth rates week-over-week. We were market leaders because of our approach to UI/UX and our design-centered organization. Our post-money valuation brought us quickly to decacorn-level.

However, our loss leader pricing strategy didn’t work out and we had to confess to our investors we actually created a lot of vaporware and forgot to register for IP across the border. Our expected churn-rate was enormous, so we were suddenly valuated a unicorpse. We saved our asses by changing to an advertorial-model for a couple of months. We were a failure. We had to fire everybody and got acqui-hired by a real company. End-of-story.

The Lean Scale-Up: Innovation & Entrepreneurship for New Ventures

Traditionally, organization design (OD) is an area of expertise focused on the roles and formal structures of organizations. The main goal of OD would be to design the organization in such a way that it makes it possible for the company to reach its vision and thus facilitates the growth.

    But the world is changing, and the digital era calls for a fresh view on how to design organizations. Organizations are now operating in a globalized, dynamic world and see their workforce change from homogeneous to diverse and educated. Innovation is almost always focused on information, is knowledge-based, complex and customized – which shortens the time to market and increases first mover advantages. All this, calls for more organic, innovative and learning organizations that are lead by strategic leaders (Greiner, 2004).

    As a result, to facilitate the growth of a company, organization design needs process view. In stead of formalizing the structures and architecture, a company that is in the process from start-up to scale-up needs to formalize its processes. Roca wrote a pretty good article about that a while ago: from the sandbox to the hive (Model for Organization Design, Roca).

    Many popular tools are based on this process view on organization design. Think about The Lean Start-Up (Ries), Agile, Business Model Generation (Osterwalder) and Customer Development (Steve Blank). What all these tools have in common is that they suggest an easy to use model that is usually cyclic, includes iteration, is non-lineair and are focused on a way of thinking.

    In my quest to place these tools into perspective, I generated a new integrative model: The Lean Scale-Up – how to get from start-up to scale-up. Below you’ll find an overview of the model. You can download the full infographic nu entering your email address above.

    An abstract from the infographic in more detail:

    The Making Of…

    Of course, the idea originated when I was reading somebody else’s perspective on entrepreneurship – and more specifically on the Lean Startup. It was the Nordstrom Innovation Lab who firstly created the following image on the relation between Design Thinking, Lean and Agile. Simply beautiful. It helped me, and many other to understand the link between the three in more detail.

    The problem of that model is that it ‘stops’ at the lean startup, while scaling-up is one of the most intriguing aspects of Organization Design. During the start-up phase, organizations are very informal (both processes as structures), but in the process of scaling up, companies need to formalize their processes. Dyer and Furr (Harvard) took it one step further. In their model “End-to-End Innovation“, they proposed a cyclic view on innovation that included design thinking, lean thinking, agile, but also business model design and scale-up. It also related Open Innovation to the cycles, but I think they are wrong by placing OI only in the front end of innovation.

    Distinguishing between the Lean Start-up and Business Model Design isn’t as easy as it looks, but I liked their suggestion that Business Model Design is something that usually comes into place when innovations have been created. A Business Model is only a topic when growing. But of course, as Furr says:

    Naturally, innovation is a messy process and you may find that you start somewhere else on the figure (e.g., you already have a solution or business model innovation in mind), but the figure helps us remember that even in these cases, each element has to be addressed before you try to scale the business—or you are in grave danger of failure.

    Deciding to put the Lean Start-Up process before the creation of a business model was a tough decision. But also Alexander Osterwalder has suggested that the lean start-up focuses on testing, while business models focus on designing the product. He also includes a step in between: the customer development process, developed by Steve Blank in his work The Four Step to Epiphany. He says:

    We already now know how to do this kind of designing and testing for business models: by combining the Business Model Canvas with the Customer Development process. Steve Blank has impressively demonstrated this in his work.

    We can achieve the same for Value Propositions by combining the VP Canvas with the Lean Startup process. This will help us more systematically work towards achieving what the startup movement calls a product-market fit or problem solution fit. In other words, building/offering stuff that customers really want.

    So, in practise, these two are more often combined with each other then followed by each other.

    The research cycle was partially based on ResearchMap.info and Barringers work on New Ventures.

    The last cycle, whick takes up 95% of the actual time that businesses are alive, is based on Greiner’s work on revolutions and evolutions as organizations grow. We have wrote on that before, for example in this post.

    And last but not least, we have included the funding process of businesses in the scheme. Not very detailed, but you’ll get an idea.

    7 Billion Universities: How Simulation Games could disrupt Education

    Over a week ago, I gave a TED talk about the role of simulation games in higher education and how they could disrupt the education system as we know it. Below, you’ll find the video, the slides I used and the full transcript of the text. Are you interested in helping me to make this game ready to enroll in a couple of years?

    Enter your email address to download high resolution PDF:


      Presentation Sheets

       This article was written by Jan Spruijt. Jan Spruijt is a senior lecturer and entrepreneur in Innovation Sciences. Connect with Jan to stay in touch:

       

       

      The Early Bird Gets the Worm, But the Second Mouse Gets the Cheese: Non-Technological Innovation in Creative Industries

      In the most recent edition of the Journal of Creativity and Innovation Management, I ran into an interesting article about being a startup versus being an early adaptor. The article suggests that early adaptors have a higher probability to succeed in the case of non-technological environments than the startups that proceed them.

      The article suggests that startups or pioneers usually focus on Business Model Innovation. They create radical business models, that are designed for a sole purpose and often opportunity driven. Startups tend to focus less on managing and organizing innovation. According to the authors, there way of organizing the business is spontaneous, reactive and loosely-designed.

      On the other hand, the early adaptors have more time and capacity to focus on both business model innovation and managing innovation at the same time. That way, they address business models innovation in a systematic, planned and integral manner. And on top of that, they address the organization of innovation in a way that it is deliberate, complementary to and interplaying with the business model.

      As the authors state: “But there is a question over how early an adapter of innovations may want to engage in innovative business models. When it comes to innovation in small, entrepreneurial firms in CIs, early adopters of organizational innovations are the early birds who get the worm, and close early followers relying on multiple non-technological initiatives may also benefit from being the second mouse and get the cheese. Engagement in BMI can pay off for earlier adopters. An innovative business model is a valuable corporate asset. However, our study suggests that this is perceived to be a risky decision. Only firms with superior organizational capabilities and resources should engage in pioneer BMI. Early followers may be better suited to managing sustained non-technological innovations. Allegedly, by combining BMI and MI, small, entrepreneurial firms in CIs may cope with changes in activity without some of the risks that newcomers face.”

      Read full article: The Early Bird Gets the Worm, But the Second Mouse Gets the Cheese: Non-Technological Innovation in Creative Industries

      Schematic overview to understand the complexity of the Innovation Ecosystem (Infographic)

      The Innovation Ecosystem

      The Innovation Ecosystem is one of the most under-researched topics. One the one hand because policy researchers usually tend to focus more on polls, elections and international collaboration and business researchers usually tend to focus more on organizations and interorganizational collaborations. However, publisher Edward Elgar has repeatedly published interesting works on innovation policy, innovation systems and the like. An ecosystem of innovation could be described as, quoting Wikipedia, the flow of technology and information among people, enterprises and institutions [which] is key to an innovative process. It contains the interaction between actors who are needed in order to turn an idea into a process, product or service on the market. The Innovation Ecosystem is extremely important to the economy and welfare of a country or region. It is one of the main drivers of GDP. Over the past decades more research has been done on the dynamics behind these ecosystems and its subsystems. Below you'll find a schematic overview of the innovation ecosystem. It will take you to the download side of Innovative Dutch, where you can download it in full resolution.

      Enter your email address to download high resolution PDF:


        System Dynamics within the Ecosystem

        The Innovation Ecosystem could be defined as a dynamical system. Dynamical systems are a theory first mentioned by Jay Forrester in the 50s and applied to a wide range of disciplines such as demography, ecology, evolution, economy and sociology. It suggests that systems contain complex feedback loops, causal links, flows, stocks, delays among the agents. Because these agents influence each other with complex logic, mostly non-linear, it is very hard to predict how the system will behave. Usually the basic feedback loops consist of positive loops, that will keep enhancing itself without limitation. However, the system also holds several negative loops, that will discontinue the positive processes. Systems usually continue switching between positive flows and negative flows, making fluctuations very common. For instance, in climate, is it common to have fluctuations per the hour, per the day, per the season, per the year and over long era's. The same holds for the economy or for rabbit populations. Complex dynamical systems can be mathematically programmed. The following example shows how a system with only two actors can even achieve chaos within a few cycles when there are small anomalies in its initial circumstances. This is called the chaos theory: imagine the long-term effect a small change can have. For instance, the effect of a local forest fire on the weather world-wide. Or losing a coin on the local economy.Innovation ecosystems work the same. There are many agents, that are influences by a wide range of actors. Imagine the effect of low-level corruption on a national ecosystem or the effect of a successful start-up on the world-wide ecosystem.

        Innovation subsystems

        There are many different subsystems of innovation, for instance:

        • National Innovation Systems: 'The network of institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse new technologies' (Freeman, 1987). Another word that is used on a regular basis for NIS is 'Institutional Environment' – which describes the institutionalization of innovation policy in governments, research institutes, advisory boards and educational institutes.
        • Regional Innovation Systems: 'The regional innovation system can be thought of as the institutional infrastructure supporting innovation within the productive system of a region.' (Asheim & Gertler, 2005). While NIS focuses more on the institutional environment of innovation, RIS usually focuses more on soft factors, such as network characteristics, trust, identity, cosmopolitism, quality of life and culture. These factors are often the first things if we think about successful RIS such as Grenoble, Silicon Valley, Helsinki or Brainport.
        • Sectoral Innovation Systems: during the early zero's more attention has come to sectoral innovation systems. In contrary to NIS and RIS, SIS focus on globally active sectors that function independently of the institutional environment. For instance, the Dutch government now prolongs the Top Sector Policy, focusing on different global sectors. NIS and RIS are now mainly supportive to SIS in the Netherlands. The Top Sectors defined are Agri-Food, Chemicals, Creative Industry, Energy, High-Tech, Logistics, Life Sciences & Health, Agriculture and Water. Another institute, the EIT, is also focusing on these sectors (Climate, Digital, Health, Raw Materials and Energy).
        • Education Systems: these are the ecosystems that surround educational institutes, such as universities. This group is often referred to as the economics of education. An well-performing education system usually increases expenses because of increased income, increases in return on investments because of higher (company) incomes and increases in productivity. It enables academic inflation.
        • Macro-economical Systems: this system refers to basic economics: output and income (GDP, GRP), unemployment and inflation and deflation.
        • Start-up Systems: a startup ecosystem is a small-scale system that enables startups to arise. It involves aspects such as ideas, inventions, research, education, startups, entrepreneurs, angel investors, seed investors, mentors, advisors and events and is supported by universities, incubators, accelerators, facilitators, investors, coworking spaces and venture capitalists.
        • Innovation Management Systems: these refer to a cyclical view of turning ideas into innovation; I've wrote a post about that earlier.
        • Cluster or Science Park Systems: In 2000 Porter already wrote: 'Geographic, cultural, and institutional proximity provides companies with special access, closer relationships, better information, powerful incentives, and other advantages that are difficult to tap from a distance. […] Competitive advantage lies increasingly in local things – knowledge, relationships, and motivation – that distant rivals cannot replicate.' (Porter, 2000). Clusters usually go the four phases: emergence, growth, maturity and renewal. The reason why clusters seem to work well is proximity. Cooke et al. (2011) suggest 7 types of proximity, 1) Geographic proximity – referring to the physical distance between actors, 2) cognitive proximity – referring to the closeness in ways of thinking between the actors, 3) communicative proximity – referring to the closeness professional language between the actors, 4) organizational proximity – referring to the arrangements that organizations make to coordinate interactions and collaborate with each other, 5) functional proximity – referring to closeness in expertise in different industries/clusters, 6) cultural proximity – referring to closeness of cultural habits and virtues and 7) social proximity – referring to the intensity of trust-based social relations, such as friendship.

        Crises

        The above-mentioned (sub)systems of innovation are in fact 'positive loops'; meaning that they will positively influence each other in an endless loop. As explained earlier, dynamic, chaotic systems, are almost always also containing negative loops, that break the positive flow. These negative loops can turn around the whole mechanism and cause crises, for instance the economic crisis. In the innovation system there are four main negative loops that create discontinuity:

        • Labour market depletion: innovation not only creates new firms which in turn increase employment, innovation also creates more automated, efficient processes that in turn lead to less employment: labour market depletion. Take a look at the book stores for instance: digital innovation has caused the traditional book stores to adjust their business to the online world, closing down book stores and reducing the amount of employees.
        • Other new (disruptive) technologies: from an industry perspective, other new technologies can cause the whole sector to be superfluous. This term is identified as disruptive innovation. Think about how the mobile phone radically made landlines superfluous.
        • Imitation: rising profits within a sector also attracts new companies to the sector that will try to copy the products – at lower costs and without the initial investment. Especially sectors with low entrance barriers are receptive to this, such as software, app development and low-tech products.
        • Policy failures: a various number of reasons can cause policy to fail. The most common ones are bureaucracy, corruption and short-term thinking.

        Innovation Policy

        The innovation policy regarding RIS and NIS involves many different aspects. One way or another, the institutional environment tries to (positively) influence the main industrial innovation system. A few of the soft factor that policy usually to focus on are:

        • Smart infrastructure: this characteristic is about all kind of infrastructures that the region has to offer. This includes hard infrastructures, soft infrastructures and technological infrastructures.
        • Quality of life: according to Sternberg and Arndt (2001) the quality of life is created by: labour quality, housing amenities, and leisure amenities. All of these factors attract highly qualified people to the region, but moreover, they also make people stay in the region.
        • Cosmopolitanism: this aspect refers to any form of feeling that is evoked by the region. The characteristics of this factor are for example attractiveness for highly educated personnel, a world-wide reputation, a good atmosphere, a shared purpose, and highly motivated people (Whitley, 2002).
        • Talented human capital: Micheals et al. (2001) describe that attracting talent, educating talent, and keeping talent is of high importance to the region. They focus on managerial talent, but they explain that technological, engineering and business talent also must be part of a regional strategy to win the war for talent.
        • Creative cultural environment: a well-developed entrepreneurial climate is attracting and exploiting personal talent and is reinforcing the strong culture of the community. Hofstede, more than 25 years ago, received worldwide praise for constructing four – although years later a fifth one was added – dimensions to characterize cultures of different nations: power distance, uncertainty avoidance, individualism, and femininity (Hofstede, 1980).
        • Trust: there is considerable evidence that a trusting relationship creates greater knowledge sharing. In a trust-based relationship, people are more willing to share useful knowledge. Trust promotes social and emotional ties on the one hand and promotes professional collaboration on the other hand, both facilitators of knowledge sharing (Chowdhury, 2005; Tsai & Ghoshal, 1998; Mayer, Davis, & Schoorman, 1995).
        • Identity: scientists claim that knowledge is more effectively generated, combined and transferred by individuals who identify with a larger collective goal. The individual members then share a sense of purpose with the collective. Ultimately, this will lead to lower network costs, and more trust and commitment (Kogut & Zander, 2003; Dyer & Nobeoka, 2000; Orr, 1990)
        • Diversity: this characteristic of knowledge refers to the extent to which a variety of knowledge, know-how, and expertise is available in a network. New opportunities and resources will be discovered more quickly with access to diverse knowledge and knowledge diversity therefore directly stimulates creativity and innovativeness of the actor in the network. (Galunic & Rodan, 2004; Galunic & Rodan, 2002; Rodan, 2002).

        Triple Helix

        Over the last decade we've heard a lot about the triple helix. More recently also the quadruple and quintuple helix have been introduced. Moreover, also Open Innovation and Co-creation have been growing over the years. What they have in common is that these theories try to integrate the different actors in the traditional dynamical view of ecosystems with each other. In that case, it won't be a 'flow' and it will therefore reduce the time delays within the flow. Simply said: deep integration between goverments and industry could result in quicker innovation. As does deep integration between education and industry; or different industries with each other, et cetera. The triple helix is a modern, 3D, view on system dynamics in the innovation ecosystem.

        Games: simulation of complex dynamical systems

        Games are a very common way to let actors in the network know how complex dynamics works. These games let you play with a few of the 'agents' in the ecosystem to experiment with the effects to better understand long-term behavior of ecosystems. Innovative Dutch creates these kinds of strategic simulation games for governments, companies and higher education; they created this infographic for their newest game; please take a look at their website.

        15 Best Open Innovation Articles of 2015

        2015’s Innovation Management conference (ISPIM) was all about Open Innovation. In fact, it was one of the most keywords – and definitely the most specific one – used amongst all 233 papers presented during the conference. Although the articles are not completely available yet (if you’re not a member), I have used it to draw up a list of the 15 best articles presented on the conference on Open Innovation of 2015 so far. I have added elements of the abstracts here, but following the links you can download the full papers from the ISPIM website.

         

         This article was written by Jan Spruijt. Jan Spruijt is an expert in Innovation Sciences. He designs business simulations, academic programs, masterclasses, courses, keynotes and learning material in the field of strategic design, organization design and (open) innovation. Connect with Jan at jan@openinnovatie.nl for opportunities.

         

        Update October 8, 2015: the links to the pdf’s are not working anymore. Please try to download the papers by searching for them on the SSRN or scholar.google.com.

        1. Paradoxical tensions in Living Labs – Seppo Leminen
          This study focuses on three main classes of tensions that characterize open innovation in living labs: management, users, and the way of working. The suggested categorization of tensions into paradoxes is based on a theory review and an empirical analysis of 26 living labs in four countries. This paper proposes that living labs foster emergence of paradoxical tensions and act as a mechanism to reorganize paradoxical tensions.
        2. Open Innovation in Phoenix Industries: Towards a Multinational Study – Marcin Baron
          The intervention is focused on the way innovation is managed in so called Phoenix Industries (clusters of small and medium-sized businesses working with broadly similar technologies that have sprung up in former industrial areas). The issue of open innovation in PIs emerge as a new research concept.
        3. Do SMEs Perform Better When Using Open Innovation Methods? – Tibor Döry
          Our conclusions are pretty much in line with the growing number of publications that indicate it is worthwhile and profitable for the SMEs to use open innovation methods. This is verified by the higher turnover, exports and patenting activity of the SMEs actively involved in open innovation.
        4. Profiting from Open Innovation: an Exploratory Research – Paula Anzola
          This paper aims to answer the following question: how do companies take advantage of coupled innovation practices? For this purpose, three case studies are discussed by means of applying a conceptual framework that structures the coupled innovation process in three areas of relevance: development, integration and commercialization of the innovation.
        5. Sustainable open innovation and its influence on economic/sustainability innovation performance – Elke Perl-Vorbach
          Open innovation and sustainability are contested, but widely used concepts, both in business practice as well as in management science. Based on the results of a quantitative study with cross-industry sampling, this paper explores the correlation between sustainable open innovation and a company’s economic and sustainable innovation performance.
        6. The Role of Organizational Culture in OI Process: Theoretical Framework – Simone Franzò
          Despite within the extant literature the role of “soft aspects” such as Organizational Culture (OC) with respect to the firms’ innovative behaviour have been deeply analysed, with empirical and quantitative studies as well, the role of OC for a successful implementation of OI have been poorly investigated. This paper aims to bring to light which are the capabilities that a firms has to possess for successfully implement all the stages of the OI process, and which is the impact of a firm’s OC in the development and implementation of such capabilities, distingiushing between the different organizational modes through which OI can be implemented.

        7. Open for Business: Universities, Entrepreneurial Academics and Open Innovation – Allen Alexander
          The emergence of open innovation theory and practice, alongside the evolution to a quadruple helix system of innovation, has led to a need for universities to rethink their models of engagement with industry and wider society. One important element in this system is the entrepreneurial academics; however there is a lack of research considering the motivations of entrepreneurial academics, who differ from academic entrepreneurs, to engage in knowledge transfer in line with open innovation policy.
        8. What Skills and Competences are required to Implement Open Innovation? – Daria Podmetina
          Once companies open up their innovation process, the internal structures change, the new tasks and challenges emerge, and employees are no longer expected to have technical-scientific or managerial expertise only but in addition, they should possess certain specific competences and skills. However, the description of these required capabilities often remains vague.
        9. Identifying Open Innovation Capabilities: A Critical Literature Review – Colin Cheng
          The initial results of the literature review show that various capabilities are considered to be important for implementing open innovation. This insight is necessary for managers who intend to increase the openness of their innovation strategies, or who aim for increasing the effectiveness of their current open innovation activities.
        10. Solving Complex Problems with Open Innovation and Collaboration – Christophe Deutsch
          Governments, Institutions, Research centers and companies are facing always more complex problems. This complexity emerges from several outside factors: rarefication of resources, environmental aspects, legal aspects, time constraints, globalization or technological complexity. These problems cannot be solved with a traditional way of thinking.

        11. Knowledge Flows Management: Open Innovation + Triple/Quadruple/Quintuple/N-tuple Helix – Marcelo Amaral
          Innovation is the result of a knowledge creation/application to solve real problems. Open Innovation (OI) and Triple Helix (H3) and its variations (quadruple, quintuple, n-tuple) are models to deal with knowledge flows that enable innovation management in a knowledge based economy. These models allows us to analyze player’ behavior and propose strategies (to firms) and policies (to government and academy) to promote innovation and consequent economic development. Together, TH+OI can be understood as a macro/microeconomics of innovation.
        12. Systematic selection of suitable Open Innovation methods – Mattias Guertler
          The performance of Open Innovation (OI) is closely linked to the selection of suitable OI-methods, such as idea-contests, toolkits or cross-industry-innovations. It directly influences the quantity and quality of gained knowledge as well as appropriate incentives. As studies showed, selecting suitable OI-methods is still a challenge for companies, especially when unexperienced with OI.
        13. Governance of open innovation networks with national vs. international scope – Thomas Clauss
          As firms need to create new products or services continuously, particularly small and midsized enterprises are required to collaborate with different stakeholders in networks in order to share relevant knowledge, distribute risks and improve frequency and performance of new product developments.
        14. Challenges Adopting Open Innovation Practices in a Public Research Institute – Thomas van Lancker
          The preliminary analysis shows challenges linked to team composition such as lack of T-shaped researcher, absorptive capacity and relational capacity, issues related to project design, e.g. tension between innovation development and PhD-research, inefficient steering committees and unclear definition of roles and tasks, and problematic organizational characteristics such as culture causing an unconducive climate for open innovation activities.
        15. Exploring New Aspects of Inbound Open Innovation: the Consolidation Index – Marco Greco
          This article studies an unexplored third approach to inbound open innovation: using the firm’s external sources at the highest degree of intensity. To this aim, it introduces a novel measure of inbound open innovation, the consolidation index. Using a large sample of European firms, this article describes how the consolidation index varies with the firm size, with the innovativeness of the firm’s home country and with the innovativeness of its sector. Finally, it describes its interaction with other inbound open innovation measures and explores its impact on innovation performance.

         

        Trending Topics in Innovation Management

        Last week, 233 papers have been presented at the ISPIM conference. Although not proceeded yet, the papers and abstracts are already available for ISPIM members. Being a member, I was able to scan all the abstracts, titles and keywords for trending topics. After a few manual adjustments, such as combining words and ignoring research-related terminology I could come up with the following wordcloud. It identifies the main topics that are currently trending in innovation management.

        So what can we conclude:

        Trending Topics

        The top 10 of trending topics definitely are (leaving some that don’t mean anything without context):

        1. Technology
        2. Business
        3. Processes
        4. Open Innovation
        5. New Product
        6. Development
        7. Services
        8. Performance
        9. Market
        10. Entrepreneurship

        Question Marks

        Question marks to me are the topics that haven’t been mentioned quite often in recent research, but from which we could expect that they would be studied a bit more (because they are hot or because they have been studied widely in the past). The infamous list of question marks would be as followed:

        1. Society
        2. End-users
        3. Education
        4. Culture
        5. Consumers
        6. Incubators
        7. Co-Creation
        8. Tools
        9. Diversity
        10. Networks

        To me it seems interesting that many terms in this list refer to co-creation (end-users, consumers, co-creation, networks – although it must be said that words as collaboration and customers end up higher in the word cloud). This topic has been researched widely over the last few years, but seems to gain less interest this year. Also the cultural aspects get less attention then would be expected (knowing that innovation management basically is all about changing behaviour).

        5 Most Powerfull Insights on Innovation Management gained at the ISPIM Conference

        “If you go from Moscow to Budapest, you think you are in Paris. And if you go from Paris to Budapest, you think you are in Moscow,” as Gyorgy Ligeti very sharply noticed, perfectly describes the location of the XXVI ISPIM Conference in Budapest. ISPIM, short for International Society for Professional Innovation Management, organized this worldwide event once a year. A place to be for everyone involved in Innovation Management, both practitioners and scholars.

        It was my first time at the conference, had the opportunity to meet lots of friends from around the globe on the one hand and meet a wide variety of new people in the field. The conference is a nice combination of scientific presentations – on the edge research in the field of innovation management, 233 presentations in total -, workshops – often organized by practitioners -, keynote sessions and a very well-done social program.

        With the aim of sharing what you have missed and giving you the opportunity to learn what we have learned, I will now provide you with 5 key insights I gained from the ISPIM conference. I think I can state that these insights are currently trending within the field of Innovation Management.

        1. Idea Management

        While this topic, as a stream within Innovation Management theory, has been studied long before, it seems to get new life during recent years. In the past Idea Management could just have been another name for Innovation Management, but nowadays it starts focusing more on the (fuzzy) front end of innovation and questions how to generate, capture and select ideas that can then turn into interesting business cases. A few articles discuss the impact of this topic. For instance, Olga Kokshagina proposed that idea absorption is an issue: “Still, the absorption of isolated novel ideas in OI initiatives remains as an issue. […] We find that the intermediary platform can incorporate functions to automatize the absorptive capacity and facilitate further diffusion of ideas.” Or within the world of startups, where capturing ideas can be difficult: “Start-ups are suffering from white spots bringing their business idea to a successful market entry.” (Hubert Preisinger). Some of the presentations also discussed the wide variety of tools dealing with ‘idea management’. One of them Peter Robbins, who argues that design thinking can help: “They used ethnographic research; involved customers, tour operators, historians, community activists and artists, and used them to develop a portfolio of novel ideas implementation,” and TaeWan Kim who explained so-called idea camps in Korea: “In this paper, we introduced the methodology for implementing creative ideas to products or services within two or three years by presenting the idea camp case in Korea.”

        While there is still a lack of a definition of Idea Management, we’ll probably run into more elaborated literature reviews and structured research on this topic in the near future.

        2. Games: strategy simulation games and gamification

        While serious games are already capturing business (and education) for a few years, the topic has still been underdeveloped in research. During the conference we had to opportunity to actually play a few games, such as the Foresights Cards – a card game about taking strategic decision making – and the Innovation Management Game – a business simulation game about the paradoxes of Innovation Management. Moreover, there were a few presentations about case studies on the use of serious games in a business environment. Roalt Aalmoes discussed that “serious games have the potential to become a serious tool to facilitate change processes. This research contributes to our understanding of serious gaming for change in two ways. First, it shows how serious games can be used to support change processes. Second, it provides insights how stakeholders can be made aware of introducing technological innovations using a serious game.”. Moreover, a “Multidisciplinary approach on developing innovative ideas was mixed with gamification elements, and flow experience can help break down barriers towards economics in non-business students and open their mind to such innovation,” according to Maria Bodone Harsanyi. Edward Faber proposed a model for analysing edutainment applications: “By following action research principles this study develops a comprehensive framework that enables more systematical data collection on the design and impact of edutainment applications, in particular serious games and gamification, from learning and learner’s points of view.”

        While serious games are widely studies, their implication for innovation management (and education in innovation management) has been underdeveloped in research. There is a need of much more quantitative research on this topic, because it will definitely create a disruption in innovation management.

        3. User Involvement

        A long-time favorite in Innovation Management, the involvement of users in the innovation process is again growing interest among innovation professionals. This year a wide variety of tools and paradigms for user involvement have been discussed. One of them being “innovation mining”: “Innovation mining is a modern social media analysis technology specifically focusing on innovation related topics. Whereas common social media monitoring techniques are mainly used to gather insights about brand perception or media impact, innovation mining aims to match technologies and product attributes with relevant user-centred applications,” according Michael Bartl. Or the so-called Living Labs method: “Within recent years it has become more important to involve end-users during innovation development processes. One approach in which end-users are involved intensively is the Living Lab approach, in which end-users are studied in their natural, real-life context,” as proposed by Annabel Georges. The Award-winning paper of Seppo Leminen also discusses Living Labs: “This paper examines the tensions, and paradoxes related to open innovation taking place in living labs. […] This study focuses on three main classes of tensions that characterize open innovation in living labs: management, users, and the way of working. Another approach that seemed very interesting is the innovation lab: “The promise of collaboration has for long been holding the attention of the academics, practitioners and policy makers alike as open innovation, user-led innovation or open source have steadily gained in prominence. Yet, meeting the grand challenges of tomorrow will require a far more extreme approach – one that enables true interaction to encourage radical innovation, crossing the previously uncrossable boundaries and leveraging technologies to tap into collaborative, rather than just collective, creativity. We propose to investigate ‘innovation labs’, an emergent form of collaborative innovation aiming to do just that.” (Anne-Laure Mention). One more presentation I’d like to mention, is about co-innovation: “To explicate customers’ behaviours and competence in co-innovation, this research will employ ‘user-innovators’ as the main body of knowledge and examine them in all stages of NPD process.” (Mai Khanh Tran).

        While this topic is high flying within innovation management, one question from the public towards the presenting scholars triggered me: “Did you yourself actually used tools of user involvement in your research.” A question that still is unanswered, saying it all: disappointingly, many scholars still don’t approach (enough) their final customers in their research. A few of them mentioned that the academic world is their main target group (which it isn’t), but none of them actually collaborated (which is not the same as interviewing) practitioners, companies, users and civilians in their research.

        4. Crisis-driven Innovation

        This topic was brought up by only one scholar during the conference: John Bessant, famous saxophone player in the ISPIM-band and publisher of many innovation books. As noted in his abstract: “Crises, whether natural or man-made, require rapid problem solving if agencies and aid workers are to avoid the huge negative impacts of such disasters. That makes consideration of how innovation takes place in this sector an urgent challenge. Our paper summarizes the nature of the challenge and reviews experience so far in humanitarian innovation (HI). There is a second issue which we also explore. Arguably crisis conditions provide a ‘laboratory’ for exploring alternative approaches and generating novel innovation trajectories which might diffuse more widely – the concept of ‘reverse innovation’.”

        A very interesting topic which I’d definitely like to hear more about in the future.

        5. Networking

        In Chesbrough’s 2006 book, Simard and West proposed the model of wide vs. deep ties. For Open Innovation it has long been argued that wide ties are very important. They create a source pool for knowledge and new ideas. Not surprisingly, this is probably the most important aspect of the ISPIM conference: the social program. The opening drink, the pauses, the lunch breaks, the walks through Budapest, the luxury diner at the Opera, the drink before – and after – the diner, the classical music, the bars, the boat trip, the drinks before – and after – the boat trip, the ISPIM-band, the wedding proposal during the boat trip, it all contributes to creating a lot of new wide ties. Connections that make the conference an awesome thing to be at and that will be of much more importance in the future than we could ever imagine.

        Thanks to the organisers, Iain Bitran, Steffen Conn, David Farell and the many workshop leaders for this wonderful event.

         

         

        A 5-Dimensional Model for Managing Innovation through Organizational Change

        I’m in the lucky position to run into quite a few business owners, corporate directors and leaders on a daily occasion. And when talking to them about innovation – and their ambitions – it almost always comes down to one simple question: “How can we implement innovation in our organization?”. A question which seems easy to ask, but needs a complicated answer.

        In the consulting projects that follow, a range of interviews usually indicate the complexity of the question. Leaders on strategic positions indicate they require business model innovation, marketing personnel indicates they need consumer innovation, tactic level manager indicate they need product innovation, business analysts indicate they need process optimization. Everybody more or less indicates they need a culture change. Stakeholders indicate they would like to see the organization collaborate more. And the truth is: they are all important for organizational change.

        With years of experience, and lots of projects to test it on, I’ve created a 5-dimensional model for managing innovation through organizational change: a model that will help answering the question that everybody asks: “How can we implement innovation in our organization?”.

        The 5-Dimension model of Innovation through Organizational Change looks as followed:

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          Click to download a high-resolution version. We also have created specialized versions for i.e. education, healthcare and industry.

          So, how did I create this framework? Let’s explain step by step:

          Change
          First of all, I started by finding a perfect tool for change. The most important factor of change is: the implementation. Because change will only be change when it will be embedded in the daily routine of the organization. A model that is widely used is the PDCA-cycle of Deming: focusing on process change and quality. This will be the basis for our model.

          Organizational Change
          However, I wasn’t looking for a change as such, but for a model for organizational change. And in the field of innovation, these organizations are so-called ‘learning organizations’: they are open to continuous improvement and change. The best model for that use is the OADI-model, an adaption to the PDCA accredited to MIT Sloan professor Kofman. OADI stands for:

          • Observe
          • Assess
          • Design
          • Implement

          This qualitative-research-based and design-oriented approach works well for innovative organizations. Moreover, I combined the model with the learning loop, creating a layered model of redesigning organizations.

          Innovation
          There are a wide number of different definitions of innovation. Earlier, I have elaborated on the Ten Types of Innovation model. However, in practice, not all Ten Types are of the same importance to organizational change. In fact, I suggest only 5 different types are to be innovated when starting with a organizational change project. In chronological order.

          1. Innovation of the why (the mission, vision and goals. This one is not in the Ten Types model).
          2. Innovation the business and profit model
          3. Innovation of the (primary) processes
          4. Innovation of the product and product systems
          5. Innovation of the customer experience

          These 5 dimensions are chronologically ordered. So, it’s best to start with the first. Moreover, they are also ordered in length: they all follow their own OADI-cycle. Innovation of the why takes much longer than innovation of the customer experience.

          However, to start changing these 5 dimensions, innovation needs to be integrated in the preconditions. There are three types of preconditions in innovation:

          • Innovation of the network
          • Innovation of the structure

          The first one is often referred to as Open Innovation. The second one, innovation of the structure, is relatively under-exposed in the Ten Types model. In the world of Sociotechnical Organization Design, authors often refer to for aspect of ‘structure’:

          • Innovation of the (formal) structure
          • Innovation of the culture
          • Innovation of the (informal and communication) systems
          • Innovation of the people

          These factors can be divided into ‘slow factors’ and ‘fast factors’. For instance: structure, systems and the skills of people are refered to as ‘fast factors’ and the culture, attitude, shared values and stakeholder management are seen as ‘slow factors’ (Camp Matrix).
          So, in order to go for innovation through organizational change: both the preconditions and the 5 dimensions need to be taken into account. But there is more.

          Managing innovation

          Up to now I didn’t talk about ‘managing’ this innovation process. This requires a set of special skills. The model out there is the OECD-model for a creative attitude towards innovation, which includes challenging assumptions, wondering, questioning, exploring, investigating, sticking with difficulty, daring to be different, collaborating, sharing, reflecting, crafting, making connections and using intuition. Not a usual set of skills for a change manager, but definitely the best one for managing innovation through organizational change.

           This article was written by Jan Spruijt. Jan Spruijt is a senior lecturer and entrepreneur in Innovation Sciences. Connect with Jan to stay in touch: