Typology for Innovative Organizations

Typology for Organizations: an update

It has been a while since Henry Mintzberg developed his influential work that made us aware of the importance of structures in organization design. To my opinion, Mintzberg’s work was a refreshing change to the world of organization design that until then has been largely influenced by Taylor’s Scientific Management Approach and Henry Ford’s efficiency-based adaptation of that.

As an entrepreneur and lecturer in organization science I find myself still using Mintzberg-related terminology on a regular base: ‘professional organizations’, ‘top management’, ‘middle management’, ‘hierarchy’ or ‘organization charts’. While these terms may be common language in business and as such might be useful in having a common understanding of what we’re talking about, much of it is outdated: organization design has shifted it’s focus over time. Structures are no longer of primary focus in design organizations. In fact, building blocks as ‘middle management’ might only still exist on paper today. Let me show you how the focus of organization design has changed over the years:

Scholar Organization Design in their eyes
Frederick Winslow Taylor (1911) Organization Design encompasses the development of task packages for employees that align with their strengths and competencies. It enhances productivity.
Henry Ford (1913) Ford embraced the idea that not tasks should be optimized, but processes should be optimized and automatized: organization design is the effective and efficient design of processes.
Henry Mintzberg (1979) Mintzberg looked at organization design from a perspective of structures.
Robert Quinn & Kim Cameron (1983) Quinn & Cameron argued that organization can be defined by their cultures and introduced their Competencies Values Framework.
Larry Greiner (1989) Greiner discussed in his work Evolution and Revolution as Organizations Grow that all of the before are true, but change over time for a growing company.
Steve Blank (1995) Steve Blank argued, while coining the term Customer Development, that organization design needs to support the value proposition of organizations.

But times are changing and organizations are emerging, scaling and managed completely differently. New generations, societal change, sustainable goals and disruptive technology require organizations to be much more flexible, self-reinventing organisms that don’t fit above-mentioned design principles. They require openness, transparency, adaptability, co-creation, self-management and responsiveness. While searching for a modern-day typology for innovative organizations – to show our students and what kind of context they most likely would want to work – I found that none was there, so I created a new one.

A Typology for Innovative Organizations

Below you’ll find an overview of the new typologies that I’d like to propose. The model describes organizational typologies based on cultures of innovation. This model is drawn upon a combination of Quinn & Cameron’s values framework (2011) and Nagji and Tuff’s innovation ambition framework (2012). The typology proposes 4 types of organizations. Each type of organization exists in three different levels of innovation. At the centre are the innovation brokers: consultancy firms, education professionals and knowledge brokers who do not directly work with innovation, but accelerate it (Chesbrough, 2007).

On the right-hand side you’ll see a more structured-approach to the new typologies. All of Mintzberg’s types would now be grouped under ‘traditional structures’.

Typology for Innovative Organizations.
Figure 1: Typology for Innovative Organizations. The figure in the middle was initially published in 2018 in the internal document Professional Profile Business Innovation at Avans University of Applied Sciences which I co-authored with the aim of explaining students in what environment they are most likely to find jobs after graduating.

Why this typology: innovation management in organizations

Academic Relevance

Innovation Management focuses on creating and managing sustainable business (Crossan & Apaydin, 2010; Keeley, Walters, Pikkel, & Quinn, 2013).

Romme (2016) argued that we are now far beyong early thinkers as Taylor and Ford and that organizational learning is a key aspect for innovative organizations (drawn from i.e. Garud & Van De Ven, 1992; Romme, 2016; Romme & Endenburg, 2006, Simon, 1991) and for business model innovation (Berends, Smits, Reymen, & Podoynitsyna, 2016; DaSilva & Trkman, 2014). Organizational learning helps innovative organizations to deal with the ever-changing, unsure and unpredictable context of business (Van De Vrande, 2017).

As a result, ‘typologies’ are not as black-and-white as they used to be. Organizations are now ambidextrous by nature: ‘the ability of an organization to both explore and exploit—to compete in mature technologies and markets where efficiency, control, and incremental improvement are prized and to also compete in new technologies and markets where flexibility, autonomy, and experimentation are needed’ (O’Reilly & Tushman, 2013, p. 2) and has been widely studied (i.e. structured ambidexterity; O’Reilly & Tushman, 2008; i.e. contextual ambidexterity; Birkinshaw & Gibson, 2004). As such, a modern-day typology for innovative organizations should deal with ambiguity in organizations.

Ambiguity isn’t new: the ‘Schumpetarian approach’ and the ‘Kirznerian approach’ have widely discussed over the last decades. The Schumpetarian approach argues that organizations try to create something new (De Jong & Marsili, 2010; Schumpeter, 1934), while Kirzner argues that it’s about seizing existing opportunities (Kirzner, 1999). Research has shown that organizations deal with different strategies over time and that organizational design takes a more flexible approach in order to simultaneously deal with both effectuation and causation (Samuelsson & Davidsson, 2009; Johnson, Craig, & Hildebrand, 2006; Shane, 2003; Busenitz, 1996; Walrave, van Oorschot, and Romme, 2011; De Jong & Marsili, 2010; Reymen et al., 2015, Christensen, 2011, Birkinshaw & Gibson, 2004, Kelley, 2005).

Socio-economic Relevance

An updated version of typologies is useful because it adopts new discussions, for instance about overexploitation (Raworth, 2017), innovation (Coley, 2009) and sustainability (Griggs et al, 2013; Sachs, 2012, United Nations, 2017) and puts them at the heart of organizational typology. As such, education programs and public instances would be more accurate in their teaching – which has a strong influence on future economic developments (Georghiou & Sachwald, 2017, p. 29). It follows up on trends in education to break the shift towards a more entrepreneurial environment into a model of multisided value creation (Manshanden et al, 2014; Zwaan, 2016)

Usage

The model can be used in three different ways:

  • For identification: it helps you in identifying the (most applicable) form of organizational typology for your organization. It helps in explaining differences between organizations and it helps in understanding why some companies mature in innovation and other don’t. It helps students in preparing for business environment and finding types of organizations that suit their wishes. It creates a common language.
  • For analysis: it helps in analyzing the strenghts and weaknesses of every aspect of your organizations. You can create a weighted variant that reveals the nuance in your strategy and company branding.
  • For discussion: it helps in understanding and discussing the strenghts and weaknesses of regional ecosystems, as it may be used to show the importance of certain types of organizations that are under- or over-represented in your area. It helps in organization your partner-network and starting open innovation projects

References

– Berends, H., Jelinek, M., Reymen, I., & Stultiëns, R. (2014). Product innovation processes in small firms: Combining entrepreneurial effectuation and managerial causation. Journal of Product Innovation Management, 31(3), 616–635. doi:10.1111/jpim.12117
– Berends, H., Smits, A., Reymen, I., & Podoynitsyna, K. (2016). Learning while (re)configuring: Business model innovation processes in established firms. Strategic Organization, 14(3), 181–219. doi:10.1177/1476127016632758
– Birkinshaw, J., & Gibson, C. (2004). Building ambidexterity into an organization. MIT Sloan Management Review, (4), 47–55.
– Busenitz, L. W. (1996). Research on entrepreneurial alertness: Sampling, measurement, and theoretical issues. Journal of Small Business Management, 34(4), 35.
– Cameron, K. S., & Quinn, R. E. (2011). Diagnosing and changing organizational culture: Based on the
competing values framework. John Wiley & Sons.
– Chesbrough, H. W. (2007). Why companies should have open business models. MIT Sloan Management Review, 48(2), 22–28.
– Coley, S. (2009). Enduring ideas: The three horizons of growth. McKinsey Quarterly.
– Crossan, M. M., & Apaydin, M. (2010). A multi‐dimensional framework of organizational innovation: A systematic review of the literature. Journal of Management Studies, 47(6), 1154–1191. doi:10.1111/j.1467-6486.2009.00880.x
– DaSilva, C. M., & Trkman, P. (2014). Business model: What it is and what it is not. Long Range Planning, 47(6), 379–389. doi:10.1016/j.lrp.2013.08.004
De Jong, J. P. J., & Marsili, O. (2010). Schumpeter versus Kirzner: An empirical investigation of opportunity types. EIM Business and Policy Research, Scales Research Reports.
– Garud, R., & Van De Ven, A. H. (1992). An empirical evaluation of the internal corporate venturing process. Strategic Management Journal, 13(S1), 93–109. doi:10.1002/smj.4250131008
Georghiou, L., & Sachwald, F. (2017). Europe’s future: Open innovation, open science, open to the world: Reflections of the Research, Innovation and Science Policy Experts (RISE) High Level Group. Retrieved from the EU Publications website: https://publications.europa.eu/en/publication-detail/-/publication/527ea7ce-36fc-11e7-a08e-01aa75ed71a1
– Griggs, D., Stafford-Smith, M., Gaffney, O., Rockström, J., Öhman, M. C., Shyamsundar, P., … Noble, I. (2013). Policy: Sustainable development goals for people and planet. Nature, 495(7441), 305–307. doi:10.1038/495305a
– Keeley, L., Walters, H., Pikkel, R., & Quinn, B. (2013). Ten types of innovation: The discipline of building breakthroughs. Hoboken, NJ: John Wiley & Sons.
– Kirzner, I. M. (1999). Creativity and/or alertness: A reconsideration of the Schumpeterian entrepreneur. Review of Austrian Economics, 11, 5–17. doi:10.1023/A:1007719905868
– Lawrence, K. (2013). Developing leaders in a VUCA environment. UNC Executive Development, 1–15. Retrieved from https://www.emergingrnleader.com/wp-content/uploads/2013/02/developing-leaders-in-a-vuca-environment.pdf
– Manshanden, W., de Heide, M., Koops, O., van der Horst, T., Poliakov, E., Bulasvkaya, T., … Bekkers, F. (2014). De Staat van Nederland Innovatieland: R&D: impuls voor economische groei. Special issue [The State of the Netherlands as an Innovation Country: R&D: Impetus for economic growth]. The Hague Centre for Strategic Studies.
– Meadows, D. H. (2008). Thinking in systems: A primer. London: Chelsea Green Publishing.
– Nagji, B., & Tuff, G. (2012). Managing Your innovation portfolio. Harvard Business Review, 66. Retrieved from https://hbr.org/2012/05/managing-your-innovation-portfolio
– O’Reilly, C. A., III, & Tushman, M. L. (2008). Ambidexterity as a dynamic capability: Resolving the innovator’s dilemma. Research in Organizational Behavior, 28, 185–206. doi:10.1016/j.riob.2008.06.002
– O’Reilly, C. A., III, & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338. doi:10.2139/ssrn.2285704
– Osterwalder, A., & Pigneur, Y. (2010). Business model generation: A handbook for visionaries, game changers, and challengers. Hoboken, NJ: John Wiley & Sons.
– Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design: How to create products and services customers want. Hoboken, NJ: John Wiley & Sons.
– Raworth, K. (2017). Doughnut economics: Seven ways to think like a 21st-century economist. London: Chelsea Green Publishing.
– Reymen, I. M. M. J., Andries, P., Berends, H., Mauer, R., Stephan, U., & Burg, E. (2015). Understanding dynamics of strategic decision making in venture creation: A process study of effectuation and causation. Strategic Entrepreneurship Journal, 9(4), 351–379. doi:10.1002/sej.1201
– Romme, G. (2016). The quest for professionalism: The case of management and entrepreneurship. Oxford, UK: Oxford University Press.
– Sachs, J. D. (2012). From millennium development goals to sustainable development goals. The Lancet, 379(9832), 2206–2211. doi:10.1016/S0140-6736(12)60685-0
– Samuelsson, M., & Davidsson, P. (2009). Does venture opportunity variation matter? Investigating systematic process differences between innovative and imitative new ventures. Small Business Economics, 33(2), 229–255. doi:10.1007/s11187-007-9093-7
– Schumpeter, J. A. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest, and the business cycle (Vol. 55). Piscataway, NJ: Transaction Publishers.
– Shane, S. A. (2003). A general theory of entrepreneurship: The individual-opportunity nexus. Cheltenham, UK: Edward Elgar Publishing.
– Simon, H. A. (1991). Bounded rationality and organizational learning. Organization Science, 2(1), 125–134. doi:10.1287/orsc.2.1.125
– Tushman, M., Lakhani, K., & Lifshitz-Assaf, H. (2012). Open innovation and organization design. Journal of Organization Design, 1(1), 24–27. doi:10.7146/jod.6336
– United Nations. (2017, May 17). Innovators, UN discuss using tech to tackle world’s development challenges. Retrieved from https://news.un.org/en/story/2017/05/557562-innovators-un-discuss-using-tech-tackle-worlds-development-challenges
– Van De Vrande, V. (2017). Collaborative innovation: Creating opportunities in a changing world. ERIM Inaugural Address Series Research in Management. Retrieved from http://hdl.handle.net/1765/100028
– Walrave, B., van Oorschot, K. E., & Romme, A. G. L. (2011). Getting trapped in the suppression of exploration: A simulation model. Journal of Management Studies, 48(8), 1727–1751. doi:10.1111/j.1467-6486.2011.01019.x
– Zwaan, B. van der. (2016). Haalt de universiteit 2040? Een Europees perspectief op wereldwijde kansen en bedreigingen [Will the university reach 2040? A European perspective on worldwide opportunities and threats]. Amsterdam, the Netherlands: Amsterdam University Press.

Innovation Management Canvas

As part of a simulation game on innovation management we have been running at universities and in corporate training programs for over 4 years now, we have developed an integrative model for dealing with innovation management on a daily basis. Innovation Management is a strategic activity that isn’t necessarily needed to implement throughly for every company. Mostly large companies have included structured processes that include administrative stages to following the (large number of) project that are in progress and to be able to follow-up on them and calculate the effect of innovation management in general. For smaller companies however, that is not general practice: having such a formal process in place simply doesn’t weigh up to cost efficiencies will generate. But for them, innovation management is just as important – but they rather use a toolkit than a formal process. Based on our 8 Types of Innovation Processes model this is a useful canvas design that makes it easy to start working on formalizing your innovation activities and processes in your organization.

Based on three categories – value creation, strategy and operations – you would be able to start improving the activities of your organization.

You can download the full infographic at the website of Innovative Dutch.

33 Routes to Open Innovation

It has been a while since Henry Chesbrough coined the term Open Innovation and formulated it’s definition: “combining internal and external ideas as well as internal and external paths to market to advance the development of new technologies.” (Chesbrough, 2003). In the course of time, the terminology surrounding Open Innovation has evolved alongside developments in management literature and practises. Open Innovation as a paradigm on itself is on its quest to touch base. Rather than taking a (technical) process-oriented approach, Open Innovation is now also about Open Business Models (Chesbrough, 2006), Open Services (Chesbrough, 2010) – both from a more strategic perspective – and practical tools (Vanhaverbeeke, 2017) – more from a tactical or operational point-of-view.

AAEAAQAAAAAAAAyyAAAAJDYyMTNhZmJlLTBmM2EtNDQ2OS1hZjRkLWFmMTVhYTI0MGFlZg.jpg This article was written by Jan Spruijt. Jan Spruijt is an expert in Innovation Sciences. He designs business simulations and academic programs in the field of Open Innovation and AI-enabled Business – also called Cognitive Business or Smart Business. Connect with Jan at jan@openinnovatie.nl for opportunities.

 

While it could be argued if Open Innovation is the best approach to be used as a general framework to put different strategic, tactical and operational activities into perspective, it is useful to try. So that’s what I did below: I used to initial Open Innovation framework, based on the innovation funnel, to describe and position a long, but non-exclusive, list of activities that are related to Open Innovation. Of course, also other frameworks could be used to do so, but this seemed like a solid approach.

The infographic includes 33 routes to Open Innovation, ordened by:

  • the level of involvement of partners (upper half) and clients (lower half): the closer the activity is to the funnel, the more involvement is required to succeed.
  • The size of the circles are partly intuitive, partly evidence-based, and describe to current usage of the phenomenen or in some cases the current impact of the phenomomen.
  • Also note that some of the ‘activities’ are rather ‘systems’ that could be tapped into to use it as a source of innovation in stead of an activity that you’ll have to organize and accelerate yourself.

Tekengebied 1@36x-80.jpg
Click image to download full resolution copy.


The goal of this framework: to give you an idea of all the possibilities that come with Open Innovation, where you could start and in what stage of your internal process it comes in (most) handy.

Partner Activities:

Route 1: In-licensing

The process of sourcing for external knowledge, patents or technology and to formalize the use of that information in your own innovation process. The ‘license’ often include information about the collaborators, how the risks are shared, how the pofits are shared and to what extend the technology or information may or may not be altered or adapted.

Route 2: Co-patenting

The process of collaboration between inventors and joined registration for a patent that may be used for further exploration and exploitation onwards. The effect has been studied by for instance Belderbos and it also an indication of the strength of (inter)regional collaboration, according to OECD.

Route 3: Spin-off

A spin-off is a form of Open Innovation in the sense that a company can ‘spin-off’ a newly developed technology to the public market for further exploitation by the involved engineers or startup team. It thus a technique to split off an early innovation in the hope that, when it leaves it mother’s wings, it will become more successfull on his own.

Route 4: Collaborative Innovation

Collaborative Innovation is a branche within Open Innovation that studies the effect of temporary Open Innovation-projects with a single goal in mind, such as the creation of a new product or the development of a new service. It is as such not a paradigm but a program management method. Vareska van de Vrande was recently appointed as professor of Collaborative Innovation at the Rotterdam School of Business.

Route 5: Co-engineering

Collaborative engineering: a term mainly used in conventional manufacturing and production industry, with a focus on collaboration between two or more partners in the full process of design, engineering and manufacturing with multidisciplinary teams and supply chain integration.

Route 6: Co-learning

A different approach to open innovation because it is more about HRM and than about the processes itself that become open. Co-learning is about the collaborative learning platforms or trajectories for personnel in order to gain new skills, both on operational level as on more tactical or strategic levels. The knowledge than flows back into the company making the influx of knowledge applicable to business processes. For instance: Faems (2006) and Rowley, Kupiec-Teahan and Leeman (1983)

Route 7: Spin-out

A spin-out differs from a spin-off in the sense that the technology or startup-team is moving to another ‘mothership’ in the form of an acquisition, merger or (most likely, because the former two usually don’t happen at this early stage) a joint venture.

Route 8: Open Innovation-based Business Models

Basically, this is about having a business model in place that exploits the opportunities that arise because of Open Innovation. Businesses with Open Innovation-based Business Models usually are trying to take the place of innovation intermediaries in Open Innovation networks. They can for instance be inventors with the sole purpose of registering and selling intellectual property. Or they can be network brokers. More information in Weiblen (2014) and Chesbrough (2010) when he describes these companies as merchants.

Route 9: Out-licensing

Out-licensing is one of the most important strategies within Outbound Open Innovation. Outbound Open Innovation is a core principle of the Open Innovation Paradigm and includes for instance also spin-offs and spin-outs. Out-licensing explores gainin external rewards for internally developped technologies. More information: Lichtenthaler (2009).

Route 10: Co-design

This approach could also have been placed underneath the funnel: co-design usually happens with both partners and customers and is meant to have a more human-centered design approach in your R&D-funnel. It has become a main topic of research within design thinking. More info: Steen, Manschot & De Koning (2011).

Route 11: Open Business Models

Open Business Models are all-inclusive approaches to Open Innovation: “Open Business Models take a broad perspective of ‘resources’ that are exchanged and shared with the ecosystem. […] It is seen as an ecoystem-aware way of value-creation and capturing. (Weiblen, 2014). As such, firms with an Open Business Model collaborate with its ecoystem by building up partner-networks, platforms. The process of ‘opening up the business model’ is often referred to as Business Model Innovation.

Route 12: Open Business

Although the term is almost the same as the before-mentioned approach, ‘Open Business‘ is something completely different. An Open Business embeds a business model that aims to publicly share all data and information. It is related to open source, freeware and open science.

Route 13: Co-branding

Collaborative branding refers to the fact that a network of organizations join to create a synergetic branding effect. In many case they will create a joint brand that replaces the current product or company brand in order to gain a larger scale effect of the brand. This process is very common in public networks (such as Brainport, the Netherlands, were many companies use the brand Brainport rather than there own branding), but also works out for business-only partnerships, such as the Douwe Egberts and Philips co-brand Senseo. A related term is co-promotion.

Route 14: Co-production

Co-production – or co-manufacturing – is largely the same as co-engineering except from the fact that it focuses only the production part of the process, thus enhancing economies of scale and cost reductions in (mass) production environments.

Route 15: Co-marketing

Co-marketing, like co-branding, is about creating a synergetic effect in the commercialization stage of the innovation process. Collaborative marketing focuses on sharing distribution channels and pricing information. It involves joint teams of marketeers bringing to market different products from differnt companies.

Partner systems:

Route 16: Sectoral Innovation Systems

A sectoral innovation systems describes the complete institutional environment, whose aim is to accelerate innovation and employability in a certain sector. In the EU, sectoral innovation systems have been a main focus point of both international and national programs over the last two decades. It’s effects still have to be proven.

Route 17: Shared Facilities

The availability of facilities that can be used by networks of companies. From an inbound approach, a company could make use of machine labs, printing labs or hubs with design and production lines; from an outbound approach, companies could share their facilities with others. It contributes to Open Innovation because of the fact that when using these shared facilities, often new combinations or ideas arise. An example of a shared facility is the Holst Centre in Eindhoven.

Route 18: Regional Innovation Systems

A regional innovation describes the institional environment, whose aim is to accelerate innovation and employability in a certain (geographically bounded) region. An example is Brainport. I’ve previously written about regional innovation systems.

Route 19: Business Ecosystems

These are ecosystems that are created and driven by businesses. Another term would be clusters. While business ecosystems are more likely to be created because of commercial opportunities (and as thus may be actually quite ‘closed’ and could prevend Open Innovation from happening), they could also be created with the purpose of Open Innovation in mind.

Route 20: National Innovation Systems

Same as regional, but than national 😉

Route 21: Fieldlabs

Field Labs are collaborative working places where businesses and knowledge institutes meet to create and develop new ideas. It’s primarily a place where students can work with professionals to create new products.

Customer activities:

Route 22: Crowdsourcing

The activity of ‘sourcing’ the crowd: gather opinions, ideas, drafts, suggestions and information from the general public, sometimes – but not always – targeted to specific crowds, such as your current customers or users, a group of elite users or targets platforms (such as designers). Crowdsourcing is effective in the early stages of an innovation process because of the fact that it per definition a diverging activity and it results in a wide variety of options to choose from. The technique is not focused enough to be of use later on in the process. Be aware of having enough resourses avaiable when starting a crowdsourcing campaign, as it may go viral and require lots of hours to manage and react. As it is a form of ‘brainstorming’, the general rules of ‘brainstorming’ also apply to crowdsourcing, which includes taking every idea or opinion seriously.

Route 23: Crowdfunding

Based on the popularity of crowdsourcing, crowdfunding was firstly introduced in the beginning of the 21st century in the US. Its principles are the same, but the main ‘source’ you’re looking for is not ideas or opinions, but finance for your project. Crowdfunding platforms, just like crowdsourcing platforms, deal with intellectual property rights, commons and other legal issues that come into play when dealing with using external work for your project. Crowdfunding is a hugely popular technique but has very low success rates, because of the lower entry barrier.

Route 24: Open Data

This is more a philosophy than a concrete activity, but at least it is fair to say that the process of opening up your data and tapping into open data is an activity. Increasingly popular in software industry, public institutes and educational institutes, opening up (big) data creates opportunities for organizations that otherwise wouldn’t be able to see and use that data. Searching for and using open data is an effective and efficient Open Innovation tool. Wikipedia states, although it misses a source, that “Some make the case that opening up official information can support technological innovation and economic growth by enabling third parties to develop new kinds of digital applications and services.”

Route 25: Co-creation Labs

Co-creation labs are almost identical to Fieldlabs, except from the fact that co-creation labs are mainly intended for the public to participate (customers, local civilians, et cetera). Co-creation labs are an effective way to gather feedback on newly developed prototypes and get ideas regarding branding and marketing.

Route 26: Co-creation

The term of co-creation is used for a whole lot of different purposes, but in the context of Open Innovation is points to the fact that organizations deliberately seek contact with end customers to test and validate new ideas and prototypes and to gather new ideas for bringing the product to market. Although not intended as such, co-creation, if done right, is also an accepted marketing technique: it engages customers with your product.

Route 27: Community

Communities are groups of highly engaged customers, usually voluntarily involved with your product because of personal interest. Searching for and collaborating with these communities may increase new ideas. Lee et al (2011) argue that communities in the example of Lego, have an automatic filtering, for instance through fora, of ideas and these ideas are as such much more worth looking at than for instance ideas generated by crowdsourcing.

Route 28: E-Participation

Primarily a public or governmental activity, e-participation tries to involve the public in (usually) gathering feedback on delivered services. It also works for companies because gathering feedback helps in validating and incrementally increasing the quality of products.

Route 29: Open Source

Much related to Open Data, Open Source is a philosophy adopted by software engineers to generate sources codes that are freely available. This doesn’t mean that there isn’t any commercial activity involved: while the source code may be open to the public for use, only developers will understand it – and thus commercial activities can be exploited when making the software available for the public. Examples of Open Source projects are Wikipedia and WordPress.

Customer systems:

Route 30: Co-working spaces

Increasingly popular, mainly because of the growing number of freelancers and self-employed personal, co-working spaces are actually an excellent place to start networking and source for new ideas. Because of the diversity of specialists working in those places, you are more likely to gather diverse ideas, which work best in the early stages of the inonvation process. In cities such as Amsterdam co-working spaces pop-up all the time, so it’s worth to search for a space that is as diverse as possible and offers also opportunities to chat and discuss.

Route 31: Collective Intelligence

This is the fundamental construct behind crowdsourcing: the idea is that the ‘collective intelligence’ always outperforms individual intelligence, even of the most awarded geniuses in your expertise. Tapping into the collective intelligence is therefore a useful activity.

Route 32: Smart Cities

The concept of Smart Cities is based around the ICT-perspective on ‘intelligence’: a highly digital, hyperconnected accessible information society in which broadband is present and the main industry focuses on services and online activities. Smart Cities are a cosmopolitan view on the world, but being located in one of them opens up a wide range of opportunities for innovation.

Route 33: User Engagement

The last route to Open Innovation focuses on the end users of your product or service. User engagement is widely researched as a highly effective approach to Open Innovation. This involves (creative) user research (Kumar) and Lead User Involvement (Bogers).

I’m quite sure there are many more techniques. Please feel free to add them and to indicate how to could be included in the graphic and I’ll update it.

 

IMG_4152_Dit_is_hem_120_100.jpg   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:

 

Clarifying Design in Business Sciences: a Design Thinking Taxonomy

images.jpg This article is an extended book review of The Quest for Professionalism of George Romme, a 2016-published book by Oxford University Press. The book is a one-of-a-kind taking a much needed reflective approach to leadership and a critical note towards the level of professionalism that many of us are approaching the science of management and entrepreneurship with. His work is exceptional, because it integrates major scientific perspectives on management from a holistic point-of-view without getting too descriptive. The book chooses a slightly philosophical approach without getting too abstract. The book takes a slightly life-work approach without giving too much self-credit.

So what’s it about? It’s about the way we think of design – in its broadest sense: organization design, strategic design, theory design, business model design, and product design – in business sciences. So why is it good? It shapes clarity in the field of design thinking, because many of us seem to think nowadays that design thinking equals a hipster approach by emphatizing with customers in order to innovate more rapidly. But that is, as this book describes perfectly, not the case at all: design thinking simply equals business science. I’ll explain why.

AAEAAQAAAAAAAAyyAAAAJDYyMTNhZmJlLTBmM2EtNDQ2OS1hZjRkLWFmMTVhYTI0MGFlZg.jpg 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.

 

Design Thinking in Business Sciences

Over the last couple of years, there has been a significant increase in the use of the term ‘Design Thinking’ in the context of management and entrepreneurship. However, the impact of design thinking in business sciences originates from Herbert Simon’s work ‘the Sciences of the Artificial’ for which he has won the Nobel Prize in 1978 – the only Nobel Prize ever awarded to a social scientist. His work focused on the dual approach of management problems: a more fundamental approach, drafting from scientific insights and solving problems ‘top-down’ and more practical approach, reflecting on real creations and validating learnings from them in science, a more design-oriented approach. Romme argues in his work that amongst others also Schon, Krippendorff and Rousseau were bridging the gap between design thinking and management. More recently, many authors have linked ‘organizational learning’ – and thus innovation – with the concept of ‘bounded rationality’- a result of Simon’s dual approach. In other words: design thinking is a necessary approach in order to come to innovation. Or better even: there is no other science in which design thinking is more appropriate than in innovation, for as in innovation sciences the explication of knowledge will always be bounded by human intentionality, environmental continency and therefore asks for a dual approach of discovering and validating. This mechanism happens at all levels, for every type of (research) question one could think of.

Design Thinking Taxonomy

This so-called science-based design approach can be visualized – showing that it can be argued that solving any particular (innovation) problem in business sciences could follow a deliberate approach (roughly the red arrow) and/or an emergent approach (roughly the blue arrow):

researchdesign1.png.

Actually, Romme has provided the reader with a long list of research methods/activities that could be followed when dealing with a particular innovation problem. Specific problems ask for (a combination of) specific methods, all within the science-based design method (Romme & Endenburg, 2006):

science-based-design approach.png

Romme, in his work, explains that by plotting the research methods on the design thinking ontology, would create a 3D-version of his model. Romme, however, doesn’t plot this 3D-model because it would become visually complex. I saw that as a challenge and have a created a 3D-model, which I coin the Design Thinking Taxonomy.

designresearchlowres.png

For whom?

This book is, IMHO, a must-read for everyone involved in business sciences: lecturers, curriculum designers, professors, trainers. I’m quite sure that business science will evolve from its current, usually very conservative, scienfific approach, into design-centered programs that are in turn increasing the level of professionalism in management and entrepreneurship.

 

IMG_4152_Dit_is_hem_120_100.jpg   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:

 

50 Research Methods for Innovation

A few weeks ago entrepreneur Valer Pop, CEO of LifeSense Group told his startup story to us at the High Tech Campus. After having a successful career at Holst Centre, Valer decided to start his business with just a small idea: solving unwanted urine loss. He was working on this idea at Holst Centre, but after meeting co-founder Julia Veldhuijzen, Valer and she decided to start up their own business and create specialized medical underwear to help 400 million women worldwide. Early on in the process they gathered an advisor board consisting of 100 women and involved them in the creation process, in both opinion polls and experiments. Right now, LifeSense’s product Carin is an international success. LifeSense’s goal for this year it to be the fastest growing medical company in Europe. Now that’s a goal.

What got to me was the inventive way of using different forms of research in their quest to create their first product. In innovation processes, we usually run into companies that mostly use ‘questionnaires’ and ‘expert interviews’ as part of their ‘research process’. Sometimes, if engineers or psychologists are involved, they use experiments too. Not surprisingly, they found it very hard to get to the real innovation challenge or problem in the market by using these research methods.

Over the years, many different works have been published that deal with creative research methods: there are so many great alternatives for finding that real gap in the market and iterating your product to its final stage. I decided to create an infographic with 50 different research methods. To get to this list I used the following sources:

Download Infographic

Structure

In order to categorise the different research methods, I combined a few sources to create a general ‘research process’. On average we could state that each R&D-trajectory consists of the following steps:

  • Explore
  • Describe
  • Gather
  • Elaborate
  • Experiment
  • Analyse
  • Test
  • Evaluate

Moreover, based on the Research Toolkit from the Methods Lab, I distinguished four different parameters for each research method:

  • Level of Expertise Needed
  • Total Investment Needed
  • Amount of Time Needed
  • Number of Staff Needed

. Based on these parameters, you, as an innovation researcher, could make a elaborated choice on which method to use and why.

50 Research Methods

The following research methods are part of the infographic:

  1. Buzz Mining: keeping track of all the buzz that comes and goes around a certain topic.
  2. Media Scanning: actively scanning media to stay up to date about a certain topic.
  3. Scenarios: using scenario planning methods to forecast different scenario’s.
  4. Trend tracking:
    keeping track of macro-economical and ‘under the iceberg’-technological trends that could impact your business.
  5. Competitive Analysis: systematically comparing products, offerings or methods of competitors and drawing conclusions.
  6. Stakeholder Mapping: draw extremely detailed stakeholder diagrams and explain the connections to the maximum of your understanding.
  7. Literature Review: reviewing existing literature to find all known and unknown information regarding your topic.
  8. Market Research: reviewing market data find all known and unknown insights about the market your in or entering.
  9. Expert Interviews: interviewing experts in the field to gain general insights on your product (category).
  10. Questionnaires: conducting questionnaires among potential users (or a population in general) to find interesting insights.
  11. Sociographics & Pshychgraphics: deeper research into lifestyle, motivational and emotional reasoning of potential users.
  12. Contextual Inquiry: taking ‘live’ questionnaire in specific contexts to compare own observations with user reactions.
  13. Anthropological observation: observing potential customers in their natural behaviour (from a distance).
  14. Indirect observation: using videos (or other tools) to indirectly observe behaviour of potential customers.
  15. User Journey Mapping: finding and observing all touch points of a certain user with your brand or product.
  16. Lead User Engagement: finding and involving important (recurring) users in your research process.
  17. Competitive testing: testing products of competitors to find useful insights.
  18. Role playing: imitating real-life situations in order to see users reactions.
  19. Graffiti Walls: putting large sleets of paper to a wall and ask users to answer certain questions over time.
  20. Crowdsourcing: using the wisdom of the crowd to gain new insights.
  21. Social Media Research: using social media to research reactions or general sense among users.
  22. Opinion polls: using structured opinion polls to test hypotheses.
  23. Focus groups: invite diverse groups of people to discuss the product idea with you.
  24. Brainstorms: using creative techniques with a diverse group of involved stakeholders to gather new ideas.
  25. Bodystorming: more active forms of idea generation.
  26. Rapid prototyping: using rapid, paper, prototypes to sketch and test possible products.
  27. Longitudinal analysis: a research method that follows users over a longer period of time to see how their behaviour or perspective changes over time.
  28. Shadowing: actively shadowing users to immerse yourself into their actions and thinking.
  29. Direct observation: proactively observe consumers when dealing with your product.
  30. Eyetracking: a computer-technique to follow the eye-movements of users when looking at a computer or mobile screen to analyse your product usage.
  31. Burrito Lunch: inviting the ‘man on the street’ for a lunch to discuss a product in detail with them.
  32. In-built tracking: using data analytics built into apps or websites to track user behaviour in detail.
  33. Alpha testing: testing first drafts of your product with small groups of customers; usually for free or without any charge.
  34. Usability testing: detailed test to see how users use your product and its features to their advantage.
  35. Fake Door: creating ‘fake products’ to see if potential are interested (in specific options or add-ons).
  36. Impersonator: faking an artificial intelligence customer service (phone or email) to test if artificial intelligence would be an option for you.
  37. Web analytics: using website and search engine data to optimize the marketing process.
  38. Mapping & Clustering: all different forms of using diagrams to cluster ideas, insights and conclusions in order to come to future suggestions.
  39. Systematic Content Analysis: using systematic approaches to analyse and quantify for instance interview recordings.
  40. Stakeholder Mapping: draw extremely detailed stakeholder diagrams and explain the connections to the maximum of your understanding.
  41. Case studies: a systematic approach that analyses different cases of users or clients that use your product and compare them with each other.
  42. Simulations: create simulations of alternative product usage to test results and effects.
  43. Triangulation: using at least three different research methods for the same question to check if the results are reliable.
  44. SWOT-matrix: plotting the outcomes of previous research in a SWOT-diagram to find future solutions.
  45. Weighted Criteria Matrix: defining criteria and benchmarking results from different research methods to those criteria in order to find possibly successful solutions.
  46. Live Experiments: conducting experiments with your product in real-life situation to test something without users knowledge.
  47. Beta testing: testing a first official version of your product (for regular pricing) to the crowd.
  48. A/B testing: testing two different version of your product at the same time to find differences and usability.
  49. Evaluative Research: using research methods with the specific intention of gather feedback on your product of process.
  50. User interviews: interviewing users to gather feedback about your product and its usage.
  51. Review analysis: analyse online reviews of your product to find new possible solutions.

 

IMG_4152_Dit_is_hem_120_100.jpg   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:

 

99 Mental Barriers for Innovation

Many of our students work on innovation projects for SME. When asked to organize an ‘open innovation session’, students enthousiastically start to read details about open innovation, open sessions and different ways of creating an open innovation-mindset within SME. We usually point them to the excellent work of Lee et al (2010), an article that points out that SME usually prefer to be open in the exploitative stage of an innovation process (rather then the explorative stage of innovation) and that they prefer sharing risks with strong ties such as competitors, clients and suppliers.

Surprisingly, the SME owners act positive when the students introduce them to the idea of open innovation in the explorative stage, for instance by offering to organize a shared brainstorm session for them, but they close down when it actually comes to planning it. Although appreciating the idea itself, they don’t see the direct benefit for it themselves. It seems they fell prone to the prisoner’s dilemma.

Non-zero-sum Game in Open Innovation

The Prisoner’s Dilemma is a so-called non-zero-sum game, which in economic terms represents a situation in which the collaborative total gain could be larger the individual gains. Simply said: 1+1 could be more than 2. The Prisoner’s Dilemma however sketches the situation in which the individual is aware of the fact that the total gain may be larger, but still prefers their personal gain over the group gain for any number of reason. They don’t collaborate, because they think personal benefit is more important than mutual benefit. Click here for an explanation of the Prisoner’s Dilemma.

In business, this dilemma is very common: not collaborating gives a higher reward on the short-term. The example of our students, and many examples alike, are caused by small fallacies in our way of thinking. Fallacies that were necessary in prehistoric times and are so deeply rooted in our behaviour that we often don’t even recognize when we behave like that. But quite often, these fallacies are not very rational and certainly not effective for business. The dilemma is summarized in the quotation: “If you want to go fast, go alone; if you want to go further, go together.”

99 Mental Barriers for Innovation

In 2012 Rolf Dobelli published his book ‘The Art of Thinking Clearly‘, which contains 98 missers in our brain when it comes to business and marketing (and innovation if you like). In the work, all of these 98 missers are linked to each other, which brought me to the idea of creating a network infographic with all 98 missers showing how they are related to each other. Below you’ll find the infographic and an explanation of a few fallacies that are most common in innovation processes.

Download Infographic

99 Mental Barriers for Innovation

Example 1: The Not-Invented-Here-Syndrome

A well-known example, the Not-Invented-Here-Syndrome is a stance adopted by social, corporate, or institutional cultures that avoid using or buying already existing products, research, standards, or knowledge because of their external origins and costs, such as royalties. It prevents companies from collaborating effectively.

Example 2: Sunk Cost Fallacy

The Sunk Cost Fallacy refers to the justification of increased investment of money, time, lives, etc. in a decision, based on the cumulative prior investment (“sunk costs”); despite new evidence suggesting that the cost, beginning immediately, of continuing the decision outweighs the expected benefit. In open innovation projects it usually comes down to the fact that there is no clear stage-gate-model in place and a ‘go’ is given rather than a ‘no-go’ for the fact that all parties have already invested time and money in trusting each other and building the prototype.

Example 3: Social Loading

Quite surprisingly, it is proven that the more horses draw a horsecar, the less horsepower they produce individually. Ringelman, an engineer, tested this behaviour on humans and saw that when two men have to carry a weight, they only use 93% of their effort. If 3 men carry a weight, they use only 85% and if 8 man carry a weight they only use 49% of their effort. This behaviour is present in collaborations as well: working in trusted alliance will make us ‘carry the weight’ to a lesser extend. We extend responsibility to other partners in the network for instance.

Example 4: Association Bias

Our minds are highly associative. We even associate things that are not to be associated (also see: clustering illusion, for instance when we see certain shapes in clouds). For this reason we also use prior experiences and knowledge to present situation, causing mistakes in our thinking. Not all past experiences are representative for current situations, such as collaborations or failures on product development.

Example 5: Alternative Blindness

Alternative Blindness means that we systematically refuse to compare outcomes to the next best alternative. We tend to compare it to the worst alternative – to make a stronger argument for the current outcome. In collaborative production this means that alternative options, solutions, prototypes and concepts are often overseen because we ‘believe’ in the success of the current alternative.

Example 6: Neomania

Neomania is the irrational behaviour associated with early adaptors. Okay, we need them to test our products, but please don’t be one yourself. In innovation, neomania refers to the fact that we irrationally want to create new things, new partnerships, new trials, new tools, even though we haven’t yet brought to market the last invention. Be aware of neomaniacs in your partnership.

Example 7: Ambiguity Aversion

There is a large difference between risk and uncertainty. In Open Innovation you’ll have to deal with both. If the likelihood of a certain event to happen is known, we can take risk. If the likelihood of a certain event to happen is unknown, the outcome is uncertain. It is proven that we rather take calculated risk than follow an uncertain path, thus the term ‘ambiguity aversion’. In business there will be many occasions where we can’t calculate or take risk, because the probabilities are unknown and in those cases we have to tolerate uncertainty.

Example 8: Déformation Professionelle

This terminology refers to the fact that we can only look at problems from our own perspective. Mark Twain once said: “If your only tool is a hammer, all your problems will be nails.”. Especially within Open Innovation contexts it is necessary to accept and overcome Déformation Professionelle, by striving for a diverse, wide network.

 

IMG_4152_Dit_is_hem_120_100.jpg   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 University in 2040: 6 trends & an infographic.

On November 23, I had the honor of giving a talk at the NRC Live event for Education. I was scheduled immediately after Bert van der Zwaan, rector magnificus at the University of Utrecht. Van der Zwaan launched his book that day: the result of sabbatical he and his wife took in 2015. During that sabbatical they traveled the world and tried to speak with as many educational visionaries as possible. It led to the work: The University in 2040, does it still exist?

In his work, Van der Zwaan introduces 6 worldwide trends in education that will have significant impact on how we learn in the future. The book was published under a creative commons license (free for you to download in Dutch) and I decided that a ‘summary’ of the most important topics covered in the form on an infographic would be a great contribution for the reader of this blog.

6 trends in higher education

  • Global Innovation Hubs: Through urbanisation universities move into the era of the global campus, a university that focuses on innovation and entrepreneurship and is the center of a regional ecosystem and knowledge valorisation.
  • Digitalization: IT will change the landscape of educat ion forever. Online learning and blended learning are just the first signs of a remarkeable shift in education. The future will behold exponential learning through big data, open science and serious games.
  • Debundling: Debundling is the trend towards more personalized, modular education. This trends will mark a shift towards a more global talent pool, accessible education SPOCs, shared intellectual commons and global commons.
  • Lifelong learning: Lifelong learning will solve the continuing mismatch between education and the labour market. Universities will start to offer more customized and problem-solving education and turn into the engaged university.
  • Economic Shift: In the near future governments worldwide will reduce investments in tertiary education and universities will become more privatized. Globally there are huge differences in labour market needs for employees with a higher education degree.
  • Civic University: The main function of the university of the future is unsure. Will the university a) focus on developing talent b) focus on applying research for entrepreneurship or c) focus on fundamental research for dealing with social challenges?

Infographic: the University of 2040

We have created an infographic on the future of education based on the work of Bert van der Zwaan. Click the link to download a full resolution copy:

Schermafbeelding-2017-01-23-om-20.57.48.png

 

IMG_4152_Dit_is_hem_120_100.jpg   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:

 

8 Types of Innovation Processes

As part of a simulation game on innovation management we have been running at universities and in corporate training programs for over 4 years now, we have developed an integrative model for dealing with innovation management on a daily basis. Innovation Management is a strategic activity that isn’t necessarily needed to implement throughly for every company. Mostly large companies have included structured processes that include administrative stages to following the (large number of) project that are in progress and to be able to follow-up on them and calculate the effect of innovation management in general. For smaller companies however, that is not general practice: having such a formal process in place simply doesn’t weigh up to cost efficiencies will generate. But for them, innovation management is just as important – but they rather use a toolkit than a formal process. Our 8 Types of Innovation Processes model is a simple design that makes it easy to bridge the gap between a formal process and the tools available.

Based on a visionary criteria – radical or incremental? product leadership or operational excellence? – you would be able to select approximately 2 or 3 types of processes that should be of interest to you. Scroll down to the tactics and start working on them tomorrow.

You can download the full infographic at the website of Innovative Dutch.

8 Types of Innovation Processes

  • Marketing & Branding: innovating the customer experience.
  • Ideation: innovating the product idea & concept.
  • Technology: innovating the product functionality.
  • Co-creation: innovating the customer involvement.
  • Social Innovation: innovating the corporate culture.
  • Entrepreneurship: innovating through entrepreneurial thinking.
  • Open Innovation: innovating with stakeholders.
  • Business Model Innovation: innovating the purpose and strategy.
  •  

    IMG_4152_Dit_is_hem_120_100.jpg   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:

     

Innovation Thinking Methods by Hashmi

A few weeks ago, a friend brought the book “Innovation Thinking Methods: disciplines of thought that can help you rethink industries and unlock 10x better solutions” from Osama A. Hashmi to my attention. I ordered it, read it and was impressed by the both the power and simplicity of the work.

The book is thin and comprehensible. In fact, it read like a weblog post enriched with interesting personal thoughts of the author and beautiful examples from his own perspective. What I most liked is the fact that it takes another approach then we’re used to see: the book is a random list of thinking methods that could be used when dealing with innovation as an entrepreneur. The list is not categorized, nor is there a structured process that guides you through the book, nor an analysis or an advice. And therefore it is mostly an inspirational book and a homage to disruptive, non-incremental or structured thinking; the fuzzy front-end of innovation. A non-methodological list of methods. Both an obeisance for the entrepreneurial-minded free-thinkers and experienced managers looking for a solution to create passion and change in an innovation team.

However, I do like analysis and created an infographic that groups the thinking methods into one model, with 4 typical innovation team assets on the vertical axis: Experience, Knowledge, Skills and Attitude. I have ranked each innovation thinking method on those 4 assets, making it possible to ‘rank’ and categorize your own team – in order to see where there are opportunities for growth and new perspectives.

Download Infographic


Innovation Thinking Methods

 

IMG_4152_Dit_is_hem_120_100.jpg   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 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.

An abstract from the infographic in more detail:
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.
Nordstrom Innovation Lab

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.

Osterwalder

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.

 

IMG_4152_Dit_is_hem_120_100.jpg   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: