Connecting Design Thinking and Startup Ecosystems: An Innographic

This visual framework offers a conceptual link between the iterative processes of Design Thinking (DT) and the customer-driven methodologies embedded in Steve Blank’s Customer Development (CD) model. The intention is to situate startups not as isolated entities but as critical participants within broader, interconnected ecosystems. This narrative aims to clarify how such integrative approaches can foster adaptive innovation processes that align with stakeholder needs, market realities, and systemic complexity.

Conceptualizing the Startup Growth Pipeline

The Startup Growth Pipeline forms the centerpiece of this visual, mapping four phases: Discovery, Define, Develop, and Delivery. This approach underscores the importance of iterative progression and external validation. Within the context of DT, these stages provide a scaffold for ideation, experimentation, and market introduction, while Blank’s CD framework introduces a customer-centric validation process throughout each step.

Deconstructing the Four Phases

  1. Discovery emphasizes an investigative approach wherein startups actively identify and interrogate customer needs and market gaps. This aligns with the Customer Discovery stage in Blank’s methodology, ensuring that ventures are grounded in verifiable demand rather than assumed value. The success of the eco-packaging firm Notpla, which pivots on the viability of seaweed-derived packaging to replace single-use plastics, reflects the necessity of thorough discovery and demand validation.
  2. Define involves translating ambiguous or multifaceted challenges into clearly articulated opportunities for innovation. This phase transitions into Customer Validation, where solutions are rigorously tested against market expectations. Firms such as Tylko, specializing in customizable furniture solutions, exemplify the application of rapid iteration cycles to calibrate their product offerings through continuous customer engagement and feedback.
  3. Develop centers on refining and prototyping solutions through structured experimentation. Drawing upon Lean Startup methodologies, this stage underscores an evidence-based, “Build-Measure-Learn” cycle, prioritizing efficiency and adaptive learning. By embedding iterative loops, startups optimize their prototypes before committing to resource-intensive production.
  4. Delivery marks the transition from MVP to scalable product, encompassing aspects of market entry, company building, and stakeholder alignment. This phase aligns with Customer Creation and subsequent scaling efforts, demanding that firms navigate market complexities and ecosystem dynamics to achieve sustainable growth.

Expanding to an Ecosystem Perspective

Unlike isolated growth models, the framework broadens the lens to emphasize ecosystem dynamics—highlighting how startups engage with networks of collaborators, customers, competitors, and institutional stakeholders. This alignment resonates with Chesbrough’s Open Innovation model, illustrating how partnerships, co-creation, and knowledge exchange enhance innovation trajectories. Such a perspective challenges the view of startups as siloed actors and situates them within relational contexts that profoundly influence their developmental pathways.

Capabilities as Strategic Levers

The upper arches of the infographic denote critical capabilities—Curiosity, Resilience, Creativity, Openness, Collaboration, Authenticity, Adaptability, and Ambition—that influence how startups navigate their growth. These capabilities, informed by Simon Kavanagh’s learning arches, serve as strategic levers in responding to ecosystem complexities and emergent challenges. For example, resilience proved instrumental for firms like Amwell during the COVID-19 crisis, as they pivoted rapidly to meet surging telehealth demand. Such adaptive capacities are not merely desirable but essential for firms operating under conditions of uncertainty.

Evaluating Metrics: A Pragmatic View of Success

To anchor these conceptual pathways, four core metrics are introduced: Identified Needs, Validated Ideas, Prototype Iterations, and Product-Market Fit. These indicators serve as pragmatic measures of progress, offering tangible reference points for evaluating success at each pipeline stage. Drawing on McKinsey’s research into growth-driven innovation, the role of well-defined metrics in steering strategic decision-making cannot be overstated, particularly for nascent ventures facing resource constraints.

Bridging Established Frameworks

Subtle integrations of Osterwalder’s Business Model Canvas and Eric Ries’ Lean Startup methodology provide familiarity and operational context. While these frameworks have achieved broad adoption, the visual aims to foster a more comprehensive understanding of their utility within a dynamically shifting ecosystem context. By situating these methodologies within an overarching narrative, the infographic seeks to promote critical engagement with established tools while encouraging a broader systems-thinking approach.

Conclusion: Reframing Innovation Pathways

The integration of Design Thinking, Customer Development, and systemic perspectives challenges the dominant narrative of linear innovation. By presenting startups as relational actors embedded in networks of mutual influence, this visual framework invites deeper exploration of how capabilities, metrics, and ecosystem interactions coalesce to shape entrepreneurial outcomes. For educators, practitioners, and innovation scholars, this conceptual alignment highlights a path toward a more integrated, reflective, and contextually grounded approach to innovation management.

For further inquiry or to discuss how these models can be applied within practical contexts or educational settings, feel free to reach out for more detailed conversations.

2 Decades of Open Innovation: an infographic

2 Decades of Open Innovation: an infographic

The rise of open innovation has been a long-standing trend in business. In the early 1990s, companies were starting to realize that they could improve their competitive edge by sharing their ideas and innovations with others. This led to the development of the concept of “open source” software, which allows for free exchange of information among developers. Open innovation is a term first coined by professor Henry Chesbrough in his 2003 book “Open Innovation: The New Imperative for Creating and Profiting from Technology”. It describes the process of organizations leveraging external ideas and resources to drive innovation and growth. This can be done through things like open R&D, corporate venturing, collaborative research, etc.

Read more
Inneagram: Stakeholder Collaboration in Innovation Ecosystems

Inneagram: Stakeholder Collaboration in Innovation Ecosystems

The story of this infographic began 16 years ago during a Summer School organized by the University of Cambridge. Not in the City of Perspiring Dreams itself, but on the mystical mountain Uludağ in Turkey, with 15 fellow students in a mountain hut more than 1 hour away from the nearest town with cellphone reception. On this mountain, led by Cambridge professor Jim Platts, we took an ESTIEM traineeship in transformative leadership. Without taking a deep dive into the material of the Summer School, one of the models that we started to work with was the Enneagram. Not only the power of the model itself, but also the history behind it, really intrigued me and so the story began.

Over the years, I’ve read much more about the Enneagram. Mostly used in (business) psychology, the framework is best described as an adaptive approach to recognize your own – and others’- behaviour in interactions with others. So it’s not, as many think, a framework for personality traits, like the Myers-Briggs Type Indicator (MBTI) or the Big-5 personality test. It perhaps holds the middle between these personality tests and the Rose of Leary, a theory of behavioral influence. The theory helps you to find your comfort-spot and from there on explains how your interactions with others happen and could be improved if you learn how to read it. It’s adaptable: it may change under different circumstances, under different preconditions and in different situations.

Read more
tentypesofinnovationteams

When Ten Faces flirt with Ten Types: Ten Types of Innovation Teams

When the book “Ten Types of Innovation” (Keeley et al.), in its most recent format, hit the shelves in 2013 – not only me, but many of my colleagues in higher education, embraced the work because of its clarity and integrality. It offered a much richer approach than the usual – perhaps more scientifically evidenced – approach of 4 types of innovation (product innovation, process innovation, business model innovation, service innovation). The work was, and still is, one of the most influential works used in our Business Innovation program and highly rewarded by both students and partners in the field. The infographic I made in 2014 based on this book has been one of the most downloaded infographics on this blog ever since.

Read more

Do you have an open innovation strategy?

In today’s business environment, where startups play an increasingly important role and disruptions come from unexpected corners of the business arena, embracing external sources of knowledge as part of an open innovation strategy becomes crucial!

Rotterdam School of Management launches a new programme focused on implementing such an open innovation strategy with a particular focus on the role of startups. What is the role of startups in today’s business environment and how can corporates and startups effectively cooperate? During this intensive two-day RSM Executive Education programme, you will discover the latest academic perspectives of corporate venturing and its role in the corporate innovation process. Building on company cases and your own experience, you will learn best practices from experts, and exchange knowledge and experience with your peers.

More info can be found here.

The 3 Phases of Responsible Innovation

Over the last few month, the phrase “Responsible Innovation” has been booming on scientific social media. It has emerged from Corporate Social Responsibility as a topic that researches the effect and consequences of innovation on the long term. This could be technological effects, antropological effects or ethical effects.

The fundament of this research topic lies in the Collingridge Dilemma:

The Collingridge dilemma is a methodological quandary in which efforts to control technology development face a double-bind problem: an information problem – impacts cannot be easily predicted until the technology is extensively developed and widely used – and a power problem – control or change is difficult when the technology has become entrenched.

The way to start innovating in order to enhance responsible innovation is three-fold:

1. Value-consciousness in design, research and development: this aspect means that design or R&D should start with a clear answer to the ‘why of innovation’. In other words: does this idea or design provide a solution to one of the grand challenges that we are facing in 5, 10 or 30 years? Values are the key to those answers.

2. Ethical Parallel Research: every step of the innovation management funnel  should be taken with the influence of ethical researchers and if possible, also researches from other parallel industries. This way, the impact that the innovation has on the long term can be easily addressed and tackeled early stage.

3. Constructive Technology Assessment: innovation teams shouldn’t be monodisciplinary, but multidisciplinary. That way, early-stage innovation (ideas) can be assessed and tested upon. Multidisciplinary teams form the basis of Open Innovation.

If you are interested in the material, take into account the following material:

Responsible Innovation: Managing the Responsible Emergence of Science and Innovation in Society

Science and innovation have the power to transform our lives and the world we live in – for better or worse – in ways that often transcend borders and generations: from the innovation of complex financial products that played such an important role in the recent financial crisis to current proposals to intentionally engineer our Earth’s climate. The promise of science and innovation brings with it ethical dilemmas and impacts which are often uncertain and unpredictable: it is often only once these have emerged that we feel able to control them. How do we undertake science and innovation responsibly under such conditions, towards not only socially acceptable, but socially desirable goals and in a way that is democratic, equitable and sustainable? Responsible innovation challenges us all to think about our responsibilities for the future, as scientists, innovators and citizens, and to act upon these.

The Importance of Responsible-Innovation and the Necessity of ‘Innovation-Care’

This study deals with responsibility as part of innovation. By nature, innovation gives birth to development for the organization and can only be at the core of any strategy within an ever-increasingly global economic context. However it also raises new questions stemming mostly from the impossibility to forecast the success of the innovations. More precisely, the questions raised by innovation also concern its consequences on society as a whole. Today, the innovator should understand his responsibility, the consequence of each innovation.

Moreover, common acceptance of the word ‘responsibility’ raises some questions about its use and how it should be understood. What does ‘responsibility’ mean? Who is responsible and for what? Through the notion of ‘care’, we aim at providing an evolution of responsible-innovation. The concept of ‘innovation-care’ is centered on people and more precisely focuses on taking care of them. The purpose of innovation-care is indeed to innovate and keep up with the level of productivity necessary to any organization while taking into account the essential interdependence between the status of the innovator and that of the citizen.

Enhancing Socially Responsible Innovation in Industry

This thesis presents a study that aims to explore to what extent corporate researchers in the field of industrial Life Science & Technology (LST) can consider social and ethical aspects of LST innovation to improve their Research and Development (R&D) practices. Innovators, particularly those working in controversial scientific and technology fields such as industrial LST, are encouraged to adopt socially responsible innovation methods. This requires that researchers, who work in such fields, consider the broader social and ethical context of their R&D activities.

The presented study explores first how corporate researchers can integrate such aspects in their daily work and how this could improve their work. Second it investigates whether such integration leads to a quantitatively assessable improvement of the quality of R&D. The results indicate that integration is possible, and leads to a measurable improvement of the quality of R&D work. In addition, researchers see a number of improvements in their R&D work, e.g. in the quality of communication and cooperation, and how to link their own work to corporate strategies and marketing. This thesis can be useful for innovators who wish to enhance socially responsible innovation practices, as it presents a tool for R&D management that allows for the operationalisation of socially responsible innovation and improved R&D performance.

First annual conference Responsible Innovation

Top 10 Best Articles on Open Innovation in 2013

Based on the rankings of the SSRN database, we are able to create a ranking of the best – most downloaded – Open Innovation and related topics articles that have been published in 2013 so far. Therefore, this is a list of brand new theories, recent case studies, preliminary results and pioneering research.

  1. The Theory of Crowd Capital; Prpic, J., & Shukla, P.
    Abstract: We are seeing more and more organizations undertaking activities to engage dispersed populations through Information Systems (IS). Using the knowledge-based view of the organization, this work conceptualizes a theory of Crowd Capital to explain this phenomenon. Crowd Capital is a heterogeneous knowledge resource generated by an organization, through its use of Crowd Capability, which is defined by the structure, content, and process by which an organization engages with the dispersed knowledge of individuals – the Crowd. Our work draws upon a diverse literature and builds upon numerous examples of practitioner implementations to support our theorizing. We present a model of Crowd Capital generation in organizations and discuss the implications of Crowd Capital on organizational boundary and on IS research.
  2. Leveraging External Sources of Innovation: A Review of Research on Open Innovation, West, J. & Bogers, M.
    Abstract: This article reviews research on open innovation that considers how and why firms commercialize external sources of innovations. It examines both the “outside-in” and “coupled” modes of Enkel et al. (2009). From an analysis of prior research on how firms leverage external sources of innovation, it suggests a four-phase model in which a linear process — (1) obtaining, (2) integrating and (3) commercializing external innovations — is combined with (4) interaction between the firm and its collaborators. This model is used to classify papers taken from the top 25 innovation journals identified by Linton and Thongpapan (2004), complemented by highly cited work beyond those journals. A review of 291 open innovation-related publications from these sources shows that the majority of these articles indeed address elements of this inbound open innovation process model. Specifically, it finds that researchers have front-loaded their examination of the leveraging process, with an emphasis on obtaining innovations from external sources. However, there is a relative dearth of research related to integrating and commercializing these innovations.
    Research on obtaining innovations includes searching, enabling, filtering, and acquiring — each category with its own specific set of mechanisms and conditions. Integrating innovations has been mostly studied from an absorptive capacity perspective, with less attention given to the impact of competencies and culture (including not-invented-here). Commercializing innovations puts the most emphasis on how external innovations create value rather than how firms capture value from those innovations. Finally, the interaction phase considers both feedback for the linear process and reciprocal innovation processes such as co-creation, network collaboration and community innovation.
    This review and synthesis suggests several gaps in prior research. One is a tendency to ignore the importance of business models, despite their central role in distinguishing open innovation from earlier research on inter-organizational collaboration in innovation. Another gap is a tendency in open innovation to use “innovation” in a way inconsistent with earlier definitions in innovation management. The article concludes with recommendations for future research that include examining the end-to-end innovation commercialization process, and studying the moderators and limits of leveraging external sources of innovation.
  3. The Golden Circle of Innovation: What Companies Can Learn from NGOs When It Comes to Innovation, Spruijt, J.P., Spanjaard, T.G.S. & Demouge, K.
    Abstract: This paper examines the lessons that companies can learn from NGOs when it comes to the why, the how and the what of innovation. It explains innovation from the inside out: why is it important and what are the grand challenges? Followed by the how: in what way can innovation be managed and how does the innovation process look like in a modern economy?
    This introduction is elaborated on with two case studies within NGOs in The Netherlands, Fair2 and Liliane Foundation. It leads to several conclusions and hypotheses for further research.
  4. Sustainability-Oriented Innovation, Hansen, E.G. & Grosse-Dunker, F.
    Abstract: Sustainability-oriented innovation (SOI): the commercial introduction of a new (or improved) product (service), product-service system, or pure service which – based on a traceable (qualitative or quantitative) comparative analysis – leads to environmental and (or) social benefits over the prior version’s physical life-cycle (‘from cradle to grave’).
  5. Open Innovation and Organization DesignTushman, M., Lakhani, K. & Lifshitz-Assaf, L.
    Abstract: Abernathy’s (1978) empirical work on the automotive industry investigated relationships among an organization’s boundary (all manufacturing plants), its organizational design (fluid vs. specific), and its ability to execute product and/or process innovations. Abernathy’s ideas of dominant designs and the locus of innovation have been central to scholars of innovation, R&D, and strategic management. Similarly, building on March and Simon’s (1958) concept of organizations as decision making systems, Woodward (1965), Burns and Stalker (1966), and Lawrence and Lorsch (1967) examined relationships among organizational boundaries, organization structure, and innovation in a set of industries that varied by technology and environmental uncertainty. These and other early empirical works have led a diverse group of scholars to develop theories about firm boundaries, organization design, and the ability to innovate.
  6. Managing Crowd Innovation in Public Administration, Collm, A. & Schedler, K.
    Abstract: Governments all over the world have discovered the world of social media, for better or for worse. Whereas some of them are making every effort to prevent the unhierarchical and therefore uncontrollable (dissident) opinion-forming process in Web 2.0, others are looking for ways of putting the potentialities of this new opening-up of communication to use. One approach that is increasingly being tried out is opening up innovation processes in government. However, this opening-up of innovation processes is anything but trivial. It requires a thoroughly thought-out strategy and thus confronts government systems with extensive challenges if it is not to suffer the same fate as other unsuccessful attempts at reform in the past. In our essay, we reflect on the consequences of these challenges for public managers.
  7. Adopting Open Innovation to Stimulate Frugal Innovation and Reverse Innovation, Hossain, M.
    Abstract: Frugal innovation and reverse innovation have very recently emerged as interesting concepts. Frugal innovation is based on cost constraints to serve low-income customers in developing countries. When frugal innovation comes to developed countries and becomes commercially successful it is considered as reverse innovation. Recently, many companies, such as GE, Siemens, Procter and Gamble, etc. have engaged heavily in frugal innovation and in reverse innovation. Open innovation, on the other hand, has not been considered in the context of low-income customers in developing countries. We argue that using open innovation concept in developing countries may boast frugal innovation and reverse innovation. Consequently, quality product with low-income will be widely available not only in developing countries but also in developed countries. Hence, western companies need to change their long hold business strategies and reshape their business models. This study aims to illustrate why western companies need to be aware of and take step to become successful in the turbulent business world.
  8. The Impact of Visibility in Innovation Tournaments: Evidence from Field Experiments, Wooten, J.O. & Ulrich, K.T.
    Abstract: Contests have a long history of driving innovation, and web-based information technology has opened up new possibilities for managing tournaments. One such possibility is the visibility of entries – some web-based platforms now allow participants to observe others’ submissions while the contest is live. Seeing other entries could broaden or limit idea exploration, redirect or anchor searches, or inspire or stifle creativity. Using a unique data set from a series of field experiments, we examine whether entry visibility helps or hurts innovation contest outcomes. Our eight contests resulted in 665 contest entries for which we have 11,380 quality ratings. Based on analysis of this data set, we provide evidence that entry visibility influences the outcome of tournaments via two pathways: (1) changing the likelihood of entry from an agent and (2) shifting the quality characteristics of entries. For the first, we show that entry visibility generates more entries by increasing the number of participants. For the second, we find the effect of entry visibility depends on the setting. Seeing other entries results in more similar submissions early in a contest. For single-entry participants, entry quality “ratchets up” with the best entry submitted by other contestants previously if that entry is visible, while moving in the opposite direction if it’s not. However, for participants who submit more than once, those with better prior submissions improve more when they can not see the work of others. The variance in quality of entries also increases when entries are not visible, usually a desirable property of tournament submissions.
  9. Digital Scholarship: Exploration of Strategies and Skills for Knowledge Creation and Dissemination, Cobo, C. & Naval, C.
    Abstract: Widespread access to digital technologies has enabled digital scholars to access, create, share, and disseminate academic contents in innovative and diversified ways. Today academic teams in different places can collaborate in virtual environments by conducting scholarly work on the Internet. Two relevant dimensions that have been deeply affected by the emergence of digital scholarship are new facets of knowledge generation (wikis, e-science, online education, distributed R&D, open innovation, open science, peer-based production, online encyclopedias, user generated content) and new models of knowledge circulation and distribution (e-journals, open repositories, open licenses, academic podcasting initiatives, etc.). Despite the potential transformation of these novel practices and mechanisms of knowledge production and distribution, some authors suggest that digital scholarship can only be of significance if it marks a radical break in scholarship practices brought about through the possibilities enabled in new technologies. This paper address some of the key challenges and raise a set of recommendations to foster the development of key skills, new models of collaboration and cross-disciplinary cooperation between digital scholars.
  10. Dissenting State Patent Regimes, Hrdy, C.A.
    Abstract: Inventors who believe in open innovation should start applying for state patents instead of U.S. patents. Patenting at the state level prevents rivals from obtaining U.S. patents and generates valuable innovation spillovers in other states where the patent has no legal effect. It also creates a unique opportunity to force patent law reform from the bottom up. In exchange for filing fees, inventors can demand patents based on rules that support open innovation, like shorter terms in fast-moving industries, stricter disclosure requirements, or new restrictions on patenting by non-practicing entities. The lobbyists who stymie reform at the national level will have a much harder time blocking reform in all fifty states. Meanwhile, patent law’s dissenters need only one state to start granting patents in order to get courts, the media, and eventually Congress to pay attention.
The Golden Circle of Innovation

The Golden Circle of Innovation

Recently, a new article about the “The Golden Circle of Innovation” has been published in the SSRN. It provides an interesting way of combining Simon Sinek’s Golden Circle and some traditional literature on innovation science into the ‘Golden Circle of Innovation’.

Important notice: the full article can be downloaded freely from the SSRN database: The Golden Circle of Innovation: what companies can learn from NGOs when it comes to innovation.

Sinek’s Golden Circle

In his work he explains why everything starts with answering the why-question. And that also means innovation, as he states it: “Knowing your why is not the only way to be successful, but it is the only way to maintain a lasting success and have a greater blend of innovation and flexibility. When a why goes fuzzy, it becomes much more difficult to maintain growth, loyalty and inspiration that helped drive the original success” (Sinek, 2009).

Literature review of Innovation Science

Though not focusing on the why, how and what, Crossan and Apaydin have generated an overview of all relevant theories on innovation, resulting in a framework for innovation, as depicted below.

They mention two ‘dimensions of innovation’, both focusing on innovation itself and they mention several ‘determinants of innovation’, focusing on the way that innovation is accelerated and managed within organizations.

 

Golden Circle of Innovation

In attempt to combine both models with each other, we created a new framework: the golden circle for innovation.

The why of innovation: grand challenges, trends and mission statements

The why of innovation not only consists of leadership aspects; it also consists of embracing a mission that fulfills a more general need and therefore rectifies the necessity of innovation.

As Einstein once stated “If you always do what you always did, you will always get what you always got”, change is a prime economic driver. “It is practically impossible to do things identically” (Hansen & Wakonen, 1997) which “makes any change an innovation per definition” (Crossan & Apaydin, 2009).

But to what extend? Innovation drives economic growth and economic growth is a necessity because of the grand challenges that this world is facing, such as keeping up with international competition in a globalizing world – which in turn increases the need for higher productivity rates through both product innovation and process innovation (Parisi, Schiantarelli, & Sembenelli, 2006) – and megatrends such as climate change, social problems and the experience economy (Brainport, 2007; Sistermans, Maas, & Soete, 2005).

So how are great leaders capable of embracing this necessity for innovation and embed it into their vision for the company? Dyer, Christensen and Gregerson (Dyer, Gregersen, & Christensen, 2009) undertook “a six-year study into the origins of creative – and often disruptive – business strategies in innovative companies”. They found evidence that these leaders are visionary and much more facilitating the innovation process than actually coming up with innovations themselves. They are drivers of the process. Their study results in five ‘discovery skills’ that these inspirational leaders do 50% better than their non-creative counterparts:

  • Associating
  • Questioning
  • Observing
  • Experimenting
  • Networking

Concluding this paragraph, we can state that an effective answer the why of innovation consists of both a motivational mission statement that embraces one or more grand challenges that is functioning as the beating heart of the organization and inspirational leaders that are effective in the five before-mentioned discovery skills.

The how of innovation: innovation history, management and processes

Innovation has a basis in the product life cycle. Literature on this topic goes back centuries, but was first scientifically mentioned by Levitt (Levitt, 1965). In several revising studies, Perreault has elaborated on this model (Perreault, McCarthy, Parkinson, & Stewart, 2000). The model consists of the four phases a product or service are subject to: market introduction, market growth, market stability and decline. From an innovation perspective, Rogers has created a model that characterized final consumers to the extend in which they adopt to new technologies: The Diffusion of Innovation and Adopter Categories (Rogers, 2002).

In recent decades, a lot of research has been performed into innovation processes and the steps that regularly seem to reoccur in these processes. Literature reviews show there is little consensus about the number of phases and types of phases that should be part of a regular innovation cycle (Adams, Bessant, & Phelps, 2006; Gopalakrishnan & Damanpour, 1997).

De Brentani and Reid further elaborate on this model (Reid & De Brentani, 2004). They state that incremental, structured innovations are mostly the result of explicit and structured innovation processes and organizational processes. On the other hand, unstructured innovation processes (especially in the first one or two phases) often lead to disruptive or radical innovations. This is also called the ‘fuzzy front end’ of innovation (Brentani & Reid, 2012). Structure and organisation in later phases of innovation processes is always a pro for the success rate of innovation. In what way does the fuzzy front end of innovation differ with structured innovation?

  • There is continuous unstructured problem identification and unstructured opportunity recognition, whereas more structured innovation processes mostly use problem structuring and opportunity structuring and the early phases of the process (Hauser, Urban, & Weinberg, 1993; Leifer, O’Connor, & Rice, 2001).
  • Information collection and information exploration is generally outside-in oriented, whereas these steps are often inside-out oriented in structured processes.

This theory is further elaborated on by Mance, Murdock and Puccio, who have generated the following model (Puccio, Mance, & Murdock, 2010).
At this point, we have tried to deduce a model that comprises all before-mentioned models and consequently consists of four phases that each have the form of diverging-converging, but also as a total has to form of diverging-converging.
Similar like organizations growth models, the area of innovation management has been undergoing several improvements over the years. Rothwell has stated that market changes have contributed to these improvements and he distinguishes five different generations of innovation:

  • 1st generation: technology push
  • 2nd generation: market pull
  • 3rd generation: coupled innovation
  • 4th generation: integrated innovation
  • 5th generation: open innovation

Concluding this paragraph, we can state that as part of the how of innovation the processes should be oriented at following a pragmatic approach – such as problem finding, ideation, concepting and implementation – and should consist of both a structured inside-out approach and a more chaotic outside-in approach and that the management should be oriented at successful implementation and embedding new approaches to innovation management, such as open innovation.

The what of innovation: innovation as a process and as an outcome

There are various definitions of innovation. In an earlier article, we have used the following, fairly narrow defined, definition of Schilling: “Innovation is the act of introducing a new device, method or material for application to commercial or practical objectives” (M.A. Schilling, 2005; Spruijt, 2012). Crossan & Apaydin recently published a literature review on innovation literature, stating: “An unrestricted search of academic publications using the keyword innovation produces tens of thousands of articles, yet reviews and meta-analyses are rare and narrowly focused, either around the level of analysis (individual, group, firm, industry, consumer group, region, and nation) or the type of innovation (product, process, and business model)” (Crossan & Apaydin, 2009). To be specific, a current search on the keyword “innovation” results in 2.5 million articles on Google Scholar and thousands of articles using the keyword combination “definition of innovation”. Clearly, there isn’t a specific definition that is correct and many perspectives should be taken into account when defining innovation.

Crossan and Apaydin (2009) have identified different forms of innovation and grouped them around certain dimensions, some of them related to innovation as a process, some of them to innovation as an outcome. These dimensions are:

Innovation as a process:

  • drivers of innovation
  • levels of innovation
  • direction of innovation
  • source of innovation
  • locus of innovation

Innovation as an outcome:

  • forms of innovation
  • magnitude of innovation
  • referent of innovation
  • type of innovation

Golden Circle of Innovation

This leads to a more detailed model of the one we presented earlier:

 

Example case of NGOs

During the studies we followed the Liliane Foundation in an innovation project aiming to create more awareness amongst high school students about the problems in third world countries. They collaborated with a group of students from Avans University in order to identify the problems. These students are high school dropouts and were able to address the problem very efficiently. In a next step, the Liliane Foundation gathered a group of high school teachers to further develop ideas and alternative programs for awareness. In a third step, they collaborated with high school executives and university executives in order to create a platform for the implementation of the alternative programs and to find financial contribution. In the last phase, the implementation, they collaborated with all parties and included some external partners, mostly sponsors, in the roll out. The whole project was successfully launched within a year.

So what did they do? They used their why to find partners that were willing to help them executing the how. They found a way of ‘open innovation’ that is rarely seen in the corporate world, as depicted in the following figure.

Important notice: the full article can be downloaded freely from the SSRN database: The Golden Circle of Innovation: what companies can learn from NGOs when it comes to innovation.

Shell wants to invest in Open Innovation

Shell indicates to be willing to invest hundreds of millions of dollars in technology-oriented companies for the next 6 to 8 years. according to belegger.nl. The website has published to following text (translated):

This step helps Shell to enable the use of innovations on new projects, according to the company.

Shell refers (amongst others) to the technology that enables the company to apply their resources more thoughtfully and smarter in their quest for oil and gas and in the improvement of the process of obtaining gas and oil. The investments are categorized under Shell Technology Ventures. ,,Ideas from outside our organisation are of great importance in the exploitation of R&D.. We want to be enable the brightest to develop plans and let them take advantage of our expertise and global impact of our company in order to use these technologies as quickly as possible on our projects”, according to the chief technology officer Gerald Schotman.

Besides investing in promising technological companies, Shell wants to focus on so-called spin-outs, organisational assets that become independent and on funds of venture capitalists.

As such a great example of Open Innovation in practise.

Serious games effective in teaching (open) innovation & management

Serious games effective in teaching (open) innovation & management

Recently, an article about the effect of serious games on teaching and learning the essentials of (open) innovation and innovation management has been published on the ssrn. The authors have researched a group of students from different nationalities playing a game in the context of an education course. By playing the game, they had the following goals:

  • Creating a shared experience of social dynamics and the paradox of co-opetition for the students;
  • Enable critical reflection on social dynamics of co-opetition based on this experience;
  • Experience-based learning — enable the students to apply what they learned from their reflection and experience through iteration;
  • Create deeper understanding of open innovation;
The study uses a series of plays and discussions and compares the results of these sessions with game theory. They round up with several interesting conclusions:
  • We argued that play can be a source of creativity, imagination and fun in a teaching setting (cf. Kolb & Kolb, 2010).
  • We found evidence that playful games can help to create such an experience through interactive experience and simple simulation — thereby helping the students to better understand the theory behind open collaborative innovation (Bogers, 2012; Chesbrough, 2003; Chesbrough et al., 2006; Dahlander & Gann, 2010; Nalebuff & Brandenburger, 1997).
  • Moreover, playful games allow understanding open innovation as interplay of complex processes of relating, social capital, and institutions (Adler & Kwon, 2002; Nahapiet & Ghoshal, 1998; Rolfstam, 2009; Searle, 2005; Stacey & Griffin, 2005).
  • They thus allow us to get a more holistic understanding of the complex social dynamics that emerge when people have to deal with novelty. (Bogers & Sproedt, 2012).
Two of the most used innovation games in teaching (professionals) and higher education are: