Open Innovation


The term “open innovation” was first introduced in 2003 by Henry Chesbrough, who suggested a new model and outline for obtaining innovations within the industrial context (Chesbrough, 2012). The background for the concept is that vertical models for developing innovations, such as R&D departments, are simply not sufficient enough in this modern hectic business environment. Therefore, ideas and knowledge needs to “open up” in a more freely and available manner. Open innovation as a concept has multiple interpretations and definitions, just as eskimos has many different word for snow, though the most fitting definition is proposed by Chesbrough (2006) hiself “the use of purposive inflows and outflows of knowledge to accelerate internal innovation and expand the markets for external use of innovation”. Chesbrough (2012) further elaborates the concept and introduces two variants of open innovation: outside-in and inside-out.

Open innovation is “the use of purposive inflows and outflows of knowledge to accelerate internal innovation and expand the markets for external use of innovation”



The inside-out open innovation perspective refers to the organisational outflow of unused or underutilized knowledge and innovations. In practice this concept suggest that internal developed knowledge and innovations could be used by other businesses in their business models and activities. This unorthodox flow of free intellectual assets is difficult to both comprehend and implement in practice, therefore this is clearly the vaguer and the least explored form of the two open innovation domains (Chesbrough, 2012).


The outside-in perspective has gained most attention within the academia and in practical applications (Chesbrough, 2012). The basic principle of the concept is that innovation ought to be assimilated and obtained to a company beyond the traditional organisational structure, meaning that the innovation processes are exposes to both external inputs and contributions (Chesbrough, 2012). Thus the outside-in perspective is a horizontal approach, where the innovations potentially emerge or get influences beyond organisations boundaries.


Analysis of old school R&D and Innovation

In the global economy there is an evident trend that points out that industry actors are increasingly consolidating through mergers & acquisition. According to Institute of Mergers, acquisitions and Alliances (2016) the value of M&As has since 2007 been around $4,5 trillion on a yearly basis, two folding the corresponding value observed in the mid-90s, likewise the number of M&A’s has doubled during that same time. Obviously this is partly as a result of a more globalised world, because cross boarder deals have increased from a sixth to 43 percent in 2014 during the same previous time period (Economist, 2014). However, despite the many different reasons and motives behind M&As, the World Economic Forum (2015) argues that this phenomenon is partially a means to an end for companies to outsource ideas and innovations. The argument is that the internal R&D activities are increasingly getting more expensive and that firms simply does not internally have the vast required know-how and resources anymore. Therefore, by buying start-ups, big firms acquire this R&D and talent that they lack. For example, this is one of the main reason why Google acquired Nest in 2014 for $3.2 billion. Hence, the statement proposed by World Economic Forum, that companies are outsourcing innovation and creativity, is fully valid one.

“M&As are a means to an end for companies to outsource ideas and innovations”

Meanwhile, it can be observed that R&D activities are perceived more valuable than ever in a value chain context. This appears clearly in the Figure 1, which illustrates the “smile curve”, where the value added properties in respect to R&D have clearly increased since the 70s. What is also noteworthy is that activities in the very end of the value chain is correspondently seeing the same development, while the production phase is plummeting in the in the respect to generated value.  Naturally, this means that the focus of the value chain is shifting significantly towards the beginning and end of the value chain, thus supporting the previous stated argument.


Figure 1. Comparison between the “smile curves” from the 70s and 00s, which are illustrating the value added activities from a value chain perspective (Productivity Commission, 2016).

The importance and value deriving from R&D activities is further emphasized by the fact that product life cycles are constantly getting shorter. Generally speaking, this means that companies must produce more new offerings at an accelerated pace, while enjoying less revenues. Meanwhile, according to Eurostat (2016) the gross domestic expenditure on R&D (GERD) stood at €272 billion in the EU-28 in 2013, which is 43.8 percent higher than 10 years earlier in 2003. In essential this means that the expenditures are growing and corporations must come up with new more cost efficient and faster methods and structures for performing or obtaining R&D, because the traditional and conservative methods are not sufficient enough.

“Within the last 10 years the R&D expenditure has almost doubbled. This is unsustainable in the long run”

An example of this is the semiconductor manufacturer ASML who spent on average 78,000 EUR per employee on its R&D expenses in 2009, which was more than what most pharmaceutical and automotive firms correspondingly spent on R&D (Chick et al., 2014). However, the demand required an even more accelerated development pace, and from ASML financial perspective this was extremely unsustainable with its current investment model. The solution to this problem was unorthodoxly solved with a Co-Investment programme. Where ASML’s three largest customers – TSMC, Samsung and Intel – each contributed with financial resources of a total €1.38 billion over the next five years, for developing the next generation of lithography technologies (Chick et al., 2014). By doing this kind of network innovation, ASML was able to increase its development capabilities and meet the market demand. However, it can be argued that this composition structure is very similar to the open innovation paradigm because financials, instead of information, are “openly” shared among competitors for the common greater good of their industry.


Another yet similar example of open innovation paradigm, where the financials are shared instead of knowledge, is GE’s cooperation project with four venture capital firms in 2010.  Together these parties arranged a challenge and pledged $200 million in funds to be invested in the best venture proposals related to renewable energy technologies (Chesbrough, 2012). The challenge received over 3800 venture proposals submission of whom 23 project was invested in. The overwhelming success of this challenge led to application of a similar model within the healthcare space a year later (Chesbrough, 2012)

Besides “openly” sharing pooled financial resources for acquiring financing and outsourcing of innovation projects, there have emerged other solutions on a smaller scale that are perhaps more aligned with the open innovation paradigm. Often these solutions are focused on crowdsourcing, i.e. seeking innovations and ideas from the crowd. For instance, Cisco has since 2007 arranged crowdsourcing challenges, called “I-Prize“, which targets and persuades young innovators to submit and present their ideas. The best winner is offered a financial reward of $250,000 in exchange for intellectual property rights for their idea (Cisco, 2016).

Procter & Gamble embraces a similar crowdsourcing strategy with their “Connect + Development” platform. The vision for this platform initiative was to increase the external ideas used in R&D from 15 percent to 50 percent (Gassmann et al., 2014). The final outcome of the initiative was that it managed to connect the firm’s 9000 researchers with over 1.5 million scientists around the globe. As a result, an enormous external ideation network was formed, that boosted the Procter & Gamble R&D productivity by 60 percent over five years after its release (Chesbrough, 2012; Gassmann et al., 2014).

The pharmaceutical company Eli Lilly takes this crowdsourcing strategy a step further by creating a transaction platform – “Innocentive“– that connects a wide range of high-technological solution seekers with solution proposals from 375,000 top experts in their field (Innocentive, 2016).  The best proposal receives a financial award, while the platform receives its revenues from posting the solution seeker’s challenge and from acquiring the intellectual property rights for the winning idea (Innocentive, 2016).

The Buzz Phenomenon of Hackathons

Another more tangible implementation of open innovation is the use of hackathons. The term originates from the software industry and is a combination of both “hack” and “marathon”, which “implies an intense, uninterrupted, period of programming” (Komssi, 2015). The objective of a hackathon is to build a prototype in a relatively short amount of time, often about three days (Riikkala, 2016). Despite the short time frame, the results are astounding. For example, Juha Pankakoski, the CDO of Konecranes, expressed his overwhelming awe with the words: “it is scary how much can be achieved in such a short amount of time”, while Facebook, who is notorious for its hackathons, created the “like-button” during such a hackathon (Briscoe, 2014; Riikkala, 2016).

“Combine marthons with hack and Hackathons are formed”

Despite the impressive “shock therapy” that these hackathons have, the fact is that observations show that the effects are only temporal and will run off if exercised too often (Komssi et. al., 2015). Therefore, new long term aspects need to be distinguished and emphasised. One of these are that hackathons are an excellent opportunity for companies to acquire new talent and employees. For instance, Both Helvar and F-secure have hired new employees based on their accomplishments and performance in a hackathon that they respectively arranged (Kallonen, 2016; Komssi et. al., 2015). Therefore, it is conceivable to expect that hackathons will partly take over some of the human resource tasks or that human resource will take full responsibility for arranging these hackathons. Riikkala (2016), co-founder of Industryhack, is also playing with this idea of making hackathons into a company platform for acquiring new talent. For the time being, hackathons have proven to be an interesting concept of testing and harnessing external input, or outside-in knowledge, on a small scale.

We are open, but not to others!

A study conducted by Chesbroug and Brunswicker (2014) shows that 78 percent of large firms report that they exercise open innovation concepts, however, the main complication with the open innovation concept is that it is most often one-sided. This means that companies only focuses on the principle of outside-in flow of knowledge, while the inside-out perspective is considered as redundant; illogical; and even perceived as a threat. This despite the fact that many company patents and innovations never see the day light. For instance, P&G uses less than 10 percent of all their patents (Chesbrough, 2012).  Likewise, other conducted studies show this pattern and estimates that about 70-90 percent of all patents are not used (Chesbrough, 2012). One explanation for this occurrence is that these innovations are simply not aligned with the company’s strategy or core competencies. But if this holds true, why cannot a third party harness this knowledge instead of being unused? Xerox for instance, challenged this norm and decided to encourage their employees of 35 different project, that didn’t get internal funding anymore, to take the ideas to the external market (Chesbrough, 2012). As it turned out most of these the projects failed, but a few succeeded and even became publicly traded companies. However, the astounding part is that the combined market value of these spin-offs now exceed that of Xerox (Chesbrough, 2012).

” 70-90 percent of all patents are never used”

Thus, it is clear that there is a lot of unused valuable knowledge and innovations, within companies, that aren’t being leveraged at all. However, the protectionism of companies makes sense, because why would companies share their heavily invested knowledge and resources for other to use, if there is no clear business logic involved? P&G have solved this problem by licensing innovations that go external, although this solution often only gives revenues on a rather minuscule level (Chesbrough, 2012). Hence, it is understandable that companies aren’t keen on releasing their ideas, because the risk-return relationship may not seem favourable when comparing the R&D sunk costs involved.

Patent lawyer Wert (2016) is of a different opinion and believes that patents are often misunderstood and should instead be perceived as business tool and a mean for stimulating innovation. This aims towards the tendencies that patents are to be used in negotiations and that competition drives to find new solutions to the same issue. Wert (2016) further states that patens instead play a central role of the “risk assessment” processes of a firm. This essentially refers to the idea that some patents should be considered a violation, but only if the risks involved are first evaluated and analysed. For example, when Google was developing their android operative system, parts of the Java API code were copied and consciously used without Oracle’s consent. However, the actual source code is not considered as an intellectual property, although the involving pseudo code is, thus, Google deleted the involving pseudo code – a strong argument for why Google was not facing criminal charges in the court (Wert, 2016). Therefore, Google’s conscious risk assessment and risk-taking were factors for their fortunate outcome and success. However, the other side of the coin is that firm’s have to, correspondingly, poses patent portfolios in order to have the upper hand in these negotiations or issues. Therefore, unused patents may serve a hidden purpose, or value, that is not taken into account.

Universities are Open Innovation Platforms

Clearly a successful open innovation strategy is all about implementation and aligned motives. For instance, from a theoretical viewpoint it could be argued that universities are originally designed to be ideal open innovation platforms. This is because at universities both inflow and outflow of knowledge take place on a large-scale, e.g. the education of students; inflow of external data sets and the release of scientific publications etc. Yet somehow this idealisation is not always aligned with the observed reality. It is well known that universities develop both advanced knowledge and make scientific breakthroughs on a constant basis, but the issue and problem remains in how to infuse this generated knowledge beyond the university boundaries. Therefore, universities become isolated and unleveraged R&D and knowledge entities, very similar to unused patents and innovations observed within companies.

“Universities are at times unleveraged open innovation platforms, very similar to the unused patents within companies”

According to Bergmark (2015), CEO at “Manufacturing Guide“, this trend was one of the main reasons for the starting the “Manufacturing Guide” initiative, which essentially is a “knowledge platform” whose mission is to mediate university knowledge with the manufacturing industry. A similar agenda and initiative is presented the biomedical research platform “eagle-i“, which is a “discovery tool built to facilitate translational science research” (eagle-i, 2016). The fundamental idea is to share scientific resources that else would appear “invisible beyond the laboratories or universities where they were developed” (eagle-i, 2016). Also the Finnish “PoDoCo” programme strives for integrating and reconciling young academic doctors and researches with the industry programme that last one or two years (Baiyere, 2016; PoDoCo, 2016). The programme itself is a collaboration initiative between universities, industries and foundations; whom together finance the salary expense (Baiyere, 2016). Therefore, there are many different initiatives that are encompassing to improve the open innovation tendencies of universities.

Are universities then harnessed and exploited by big players? According to Kalliokoski (2016) many of Technical Research Centre of Finland (VTT) projects have mainly receiving finance from large international multi-billion dollar companies, instead of national and local companies. This statement suggests that large corporations receive high quality R&D relatively cost efficiently through universities, and this of course happens often without sharing any mutual knowledge with the universities. Another example of this is the Brazilian cosmetic manufacturer Natura, who has an internal R&D team of about 250 employees, a pretty modest number for a company with 3.4-billion-dollars in sales, however, Natura makes up for this shortage by leveraging its sophisticated university network, which constitutes of 25 different universities worldwide (Keeley et al., 2013). Therefore, it could be argued that the knowledge flow between universities and large corporations is one-sided and that they, the large firms, exploit unleveraged government and publicly financed R&D sources and infrastructure to their advantage.

“Large firms exploit one-sidedly (outside-in open innovation) govenrment financed R&D sources and infrastructure to their advantage”

Irrespective of standpoint, it is clear that universities will play an important and central role for companies, who realise that their internal research is not sufficient enough and are looking for new R&D practices and possibilities. Especially in an open innovation context, universities show promising and convincing results. This appears clearly from results in Table 1, which is generated by company called “fimecc” (nowadays renamed “Dimecc“). In short, Dimecc is a Finnish company focusing on co-creation and cooperation between companies and universities, thus, creating and coordinating a true open innovation platform, where the different parties can together develop new innovations and ideas (Kulmala, 2016). The result form Table 1 clearly indicates that fimecc has had a significant impact on the companies involved, when compared to other companies who have not taken part in the programme. Of course some of the numbers are a bit misleading. For eample, 1823% increase in profits over a time period after 2008, mankind’s worst economic depression. Despite this distortion, the facts evidently point out that the programme participants are outperforming in every single category.

The True Power of Open Innovation

According to Kulmala (2016) a key factor to the success it that innovations are to be developed on a “generic level”, so that all encompassing parties can make use of the newly generated knowledge in their own way. In addition, the Finnish mentality and culture is very well suited for open innovation paradigms and concepts. This statement refers to the fact that a flat hierarchal structure in a norm in Finland and that the people are very honest, frank, and open about even confidential matters. This occurrence is very well illustrated by a quotation from a Finnish industry leader Stig Gustafsson: “Finland is not a country, it is a club”. Essentially this means that the dynamic and behaviour in Finland business and industry environment is similar to a community of some sorts. Evidence supporting this statement appears in industry collaboration rankings (Table 2), where one can clearly see that two of Finland’s top technological institutes reach high ranks. Therefore, it appears that open innovation paradigms in Finland have enormous embedded potential. Additionally, one must notice that the Finnish universities are not bound or obliged to specific industry, such as the petroleum industry. Thus, if these “married” universities were excluded, then the Finnish institutes would peak the rankings.

blog2Table 1. Results of companies participating in fimecc’s open innovation programmes compared to random technology companies who do not participate 


Table 2. Industry collaboration rakings. The ranking provides an idea of how much companies are involved in and invest time in the active research of the institution (Times Higher Education, 2016)


All in all, it is obvious that traditional, closed, and internal R&D practices will increasingly become more of a challenge for companies in the future. Cost is the major issue, but also the speed, time-to-market, of which new ideas and innovations are introduced will be a more crucial factor for the survival of firms. There are many observed alternative solutions for companies to enrich themselves through an outside-in flow of ideas and innovations, however, these solutions are only partly aligned with the open innovation concept. It is clear that under the right circumstances, true open innovation paradigms are not an utopia and hypocrisy. Instead the concept can be extremely useful and valuable source of new ideas, as it was observed with Dimecc. Hence, open business model logics have huge unknown potential that needs to be further exploited.




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Chesbrough, H., 2013. Open business models: How to thrive in the new innovation landscape. Harvard Business Press.
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Kallonen, A., 2016. Interviewed on 4th May. 09:00.

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Komssi, M., Pichlis, D., Raatikainen, M., Kindström, K. and Järvinen, J., 2015. What are hackathons for?. IEEE Software, 32(5), pp.60-67.

Kulmala, H., 2016. Interviewed on August 9th. 13:30

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The Business Model Fuzz?!

In everything you do, you need to have a clear understanding of “why” you are doing the things you do. In other words, have a plan. Not having one is planning to fail. Period. Having a plan is the same as having a clear vision and a mission.

By the way what is the difference between vision and mission? A vision is the ideal state you want to be in the long future, a roadmap of sorts. On the contrary, the mission is far more shortsighted and defines clear objectives, when the operating context and environment is taken into account. Still confusing, eh? What helps me to distinguish these concepts from each other is to compared them with the concepts of tactics and strategy in the following manner:

Tactics is winning a battle, while strategy is winning the war

Knowing this, so what is a business model then?

Orgins of Business model

The term “business model” was first time used in academic literature in 1957, but has since early 2000s gained more attention because of the emerging digital economy and therefore is a relatively young phenomenon and concept (Osterwalder, Pigneur, & Tucci, 2005). According to Fielt (2013) the concept is criticized often for being vague, fuzzy and not clearly defined. Also Slavik, and Bednar (2014) agree with this view, but establish that the different definitions can be separated into two categories: a purely economic view and an extended view, where the creation of value is considered. A purely economic business model definition is presented by Chesbrough (2006a) as “a useful framework to link ideas and technologies to economic outcomes “. By comparison, Osterwalder’s and Pigneur’s (2010) definition of a business model takes the value creation and capturing approach, which is illustrated as:

“the rationale of how an organization creates, delivers, and captures value”.

In any case, it is clear that a general definition of business model is still out of sight within the academic context, though it seems that the focus is shifting towards the value generating and capturing perspective (Fleit, 2013). Therefore, the most complete conceptual definition so far is presented by Fleit (2013), who share similar elements with Osterwalder and Pineur, where a business model:

“describes the value logic of an organization in terms of how it creates and captures customer value”.

The best tool for visualizing the business model is the business model canvas, which I will  explain in the next section.

The Business Model Canvas

The business model canvas is a visual strategic management tool initially proposed by Alexander Osterwalder in late 2000s. According to Osterwalder (2012) the business model canvas framework is capable of both discovering all new business models and designing and describing existing ones. The model itself constitutes of nine fundamental building blocks, which are: customer segments, value proposition, channels, customer relationships, revenue streams, key resources, key activities, key partnerships and cost structure. In Osterwalder’s reference model (2012) the nine blocks or modules are placed in a prestructured order which in turn forms a rectangular entity or image (Figure 1) that is the final canvas.

The first block, customer segments, can be found in the upper right corner of the canvas (Figure 1). This conceptual block aims to identify the different groups of people and organisations that the enterprise wants to reach and serve. The customer segments are separated into groups based on: their specific needs; relationship requirements; profitability, their willingness to pay for different aspects of the offering; and how the distribution reaches them (Osterwalder & Pigneur, 2010). Examples of different customer segments are mass market and niche market.


Figure 1. The business model canvas with its different modules (Osterwalder & Pigneur, 2010).

The second block, value proposition, is found at the heart of the business model canvas. This module involves a mix of various different elements catering to the customer segment’s needs (Osterwalder & Pigneur, 2010). Osterwalder and Pigneur (2010) also recognizes elements and features that contribute to value creation which are newness, price, performance, customisation, design, brand/status, cost reduction, risk reduction, “getting the job done”, accessibility, and convenience/usability. All these elements are self-explanatory, except for “getting things done” which refers to the service aspect of helping the customer to achieve her desired results. For example, Rolls-Royce and GE sell operative hours of their machinery instead of the actual product (Wharton, 2007). Finally, all of these value generating elements can be divided into two major categories: qualitative and quantitative values (Osterwalder & Pigneur, 2010).

The third module, channels, is found in the middle-right part of the canvas (Figure 1). Channels are defined as the touch points of the customer, thus it plays a very central and important role regarding the customer experience. In addition, Ostwalder and Pigneur (2010) argues that channels serve important and crucial functions, such as: raising awareness of a company’s products and services; helping customers to evaluate the value proposition; take part in the actual delivering of the value proposition; and providing post-purchase support. Thus the channel process can be divided into five chronological phases, which are called awareness, evaluation, purchase, delivery and after sales (Osterwalder & Pigneur, 2010).

Customer relationship module, the block located above the channels block in Figure 1, portrays the type of relationship a company endeavour to establish with its customer segment (Osterwalder, 2012). Osterwalder and Pigneur (2010) further elaborates this concept by presenting various categories in regards of customer relationships. The first is personal assistance, which encompasses real human interaction and cooperation. This relationship can further be refined into a separated category called “dedicated personal assistance”, which represents the deepest and most intimate possible relationship. Obviously, these kind of relationships takes a lot of time and effort to develop and realise. The third category is self-service, where the customer helps themselves and has no direct relationship with the company. Self-service can further be evolved into “automated services”, the fourth category, that is a more advanced concept, where sophisticated automation is embedded into the self-service processes. The fifth category is the utilisation and involvement of user communities. The rationale is that communities can exchange valuable knowledge and experience with a company’s customers. However, generally this concept face issues related to establishing this crowd sourcing platform with enough contributing parties and customers, who form these valuable network effects (Kemper, 2010). The last category is co-creation, which is a relationship where customers and vendor co-create value together, such as using influences from both parties to make the final product. It can thus finally be concluded that the motivation for all customer relationships are either customer acquisition, customer retention and boosting sales (Osterwalder & Pigneur, 2010).

The importance of Revenue Streams, the block in the lower right corner (Figure 1), is well expressed and formulated by Ostwalder’s and Pigneur’s (2010) citation: “if customers comprise the heart of the business model, Revenue Streams are its arteries”. Revenue streams thus refers to the money that the company generates through its activities and operations. Revenues Streams can further be divided into two groups: transaction revenues from one-time customers and recurring revenues that result from on-going payments (Osterwalder & Pigneur, 2010). Revenue streams are obtained through several ways, such as asset sale, usage fee, licensing, lending/renting/leasing, subscription fees, advertising and brokerage fees.

The sixth block, key resources, can be found in the middle of the left half of the business canvas (figure 1). Key resources constitute of the most important assets of company and forms the core for a successful working business model (Osterwalder, 2012). Key resources can be divided into the following unique categories of physical, financial, intellectual and human assets.

The seventh, key activities, block is located on the left side of the value proposition block (Figure 1) and represents all the most important and crucial operations that a company carries out in order to make its business model work. Key activities can be organised in three categories: production, problem solving and platform/network (Osterwalder & Pigneur, 2010). The production term consists of elements related to designing, producing, and delivering a product or good of a superior quality, therefore this group is often represented by manufacturing companies. The problem solving category differs in the sense that it tries to solve the problems of a customer and is often executed and realised by various different service concepts, thus this group is dominated by service specialised organisations. The last group, platform/network, concerns with matchmaking, networking, and software activities. Additionally, it must be mentioned that even some brands, such as Loui Vuitton, can also function as a platform, which expands the concept remarkably (Osterwalder & Pigneur, 2010).

In the upper left corner (Figure 1) one can find the eight block, key partnerships. Partnerships are a necessity in the modern business environment, where the focus on one’s core competencies and the ability to leverage these are often the deciding factor for a firm’s survival and profitability. Therefore, partnerships are sometimes the cornerstone of many business models (Osterwalder & Pigneur, 2010). The motivation for seeking a partnership can be elaborated into three alternative synergy endeavours, which are optimization and economy of scale; reduction of risk and uncertainties and acquisition of a particular resource and activity (Osterwalder & Pigneur, 2010). Ostwalder and Pigneur (2010) also suggest that partnerships can be distinguished into four differ types, which are strategic alliances between non-competitors, coopetition, joint ventures and buyer-supplier relationships. Where coopetition means that a strategic alliance between competitors are being formed, for example LinkedIn works intimately with competing headhunters (Cabrera, 2014). While Joint venture is per definition a business agreement, for a finite time, between parties to develop a new entity and new assets by contributing equity. The most famous joint venture setup was between Nokia and Siemens, who formed Nokia Networks (Ernst & Kim, 2002).

The last block, cost structure, is found in the lower left corner of the canvas (Figure 1) and illustrates all costs that arise from implementing the business model (Osterwalder & Pigneur, 2010). There are two board extreme classes of cost structure, which are cost-driven and value driven. Most businesses apply a hybrid version of these two classes. Regardless of classification, the cost structure has four characteristics: fixed cost, variable costs, economies of scope and economies of scale (Osterwalder & Pigneur, 2010). Where the “economies of scope” is the cost advantage that arises from producing many distinct goods, while “economies of scale” is the cost advantage arising from an enterprises size, output or scale of operations (Gilligan, Smirlock, & Marshall, 1984).

Final Evaluation of the Framework

The final business model canvas framework is a powerful tool for understanding and implementing business model innovation (Osterwalder & Pigneur, 2010). The real strength of the framework lies in its simplicity, practice orientation and its principle of “Plug- and Play” i.e. ability to start over with the remodelling process (Hong & Fauvel, 2013). However, the greatest short coming of the canvas framework is that it does not take into account the competition of the investigated object (Hong & Fauvel, 2013).

Finally, the importance of the business model is very well expressed by Chesbrough (2010), who illustrates that “the same idea or technology taken to market through two different business models will yield two different economic outcomes”. Therefore, a well-designed business model architecture is a necessity for running a business like a well-oiled machine.

In my opinion, a business model is thus a map for achieving the vision, but the map itself is stuctured based on the mission. Summa summarum, the business model is a concrete and detailed illustration of how to implement you mission (and the vision in the long term).





Chesbrough, H. (2010). Business Model Innovation: Opportunities and Barriers. Long Range Planning, 43(2-3), 354-363.

Chesbrough, H.W., 2006a. Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.

Ernst, D. and Kim, L., 2002. Global production networks, knowledge diffusion, and local capability formation. Research policy, 31(8), pp.1417-1429.

Fielt, E., 2013. Conceptualising business models: Definitions, frameworks and classifications. Journal of Business Models, 1(1), pp. 85-105

Osterwalder, A., 2012. Alexander Osterwalder: The Business Model Canvas. [Online Video]. Available from:

Osterwalder, A., & Pigneur, Y., 2010. Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers, Wiley, Hoboken, US.

Osterwalder, A., Pigneur, Y. and Tucci, C.L., 2005. Clarifying business models: Origins, present, and future of the concept. Communications of the association for Information Systems, 16(1), p.1.