10 types of Innovation

Innovation is defined by Oxford English Dictionary as “make a change in something established“ or “introduction of something new”, such as a method, idea or device. A similar but a more sophisticated definition is presented by Abernathy and Clark (1985), who illustrate it as:

”an innovation is the initial market introduction of a new product or process whose design departs radically from past practice. It is derived from advances in science, and its introduction makes existing knowledge in that application obsolete. It creates new markets, supports freshly articulated user needs in the new functions it offers, and in practice demands new channels of distribution and aftermarket support. In its wake it leaves obsolete firms, practices, and factors of production, while creating a new industry”.

Thus, this view clearly focuses on entering new unexplored domains and markets.

The Periodical system for Innovation

Keeley et al. (2013, here is the link to the book. I highly recommend if for anybody that is working with innovation) introduces an innovation framework, which is inspired by the periodical system from chemistry, that consists of three different main segments: configuration, offering, and experience. The first segment, the configuration aspect, focuses on the innermost workings of an enterprise and its business system. The second segment, the “offering category”, concerns with the core products and services of an enterprise, or a collection of these. Finally, the experience category focuses on the elements that the customers face in the regards to the enterprise and its business system.

 

All these three segments are also horizontally ordered as from left to right, according to its internal to its external impact and influences of the enterprise. In addition, the whole framework constitutes of further ten category types, which is grouped into the aforementioned three main segments (Figure 1).
The first type in the configuration segment is the “profit model”, which essentially involves how to convert “firm’s offerings and other sources of value into cash”. Hence fore, the focus in on having a deep understanding of what the customers cherish and aspire, in order to discover new revenue and pricing opportunities. It should be noted and clarified that a profit model differs significantly from a business model, mainly because a profit model only concerns with catching value and is not involved in the value creation process.

 
The second innovation type is “network”, which represents the opportunities that lies in both leveraging on one’s core competences and harnessing other firm’s strengths and assets to one’s advantage. This innovation type is thus closely associated with various co-creation and business ecology concepts, which will increase in an ever more connected global environment.

 
The third innovation type is “structure”, which focuses on how the company’s assets are organised in order to generate value. In other words, these innovations encompass the alignment and nature of company capabilities and assets, so that the configuration and management of these are structured and leveraged in the best possible manner.
The process unit refers to the primary activities and operations that are associated with producing the offerings of a company. Innovating in this division requires fundamental changes from “business as usual”, although the outcome, that is the offering, remains the same and unchanged.

 
The first innovation type in the offering segment is “product performance” which addresses the “value, features and quality of a company’s offering”. Often the traditional understanding of innovation is associated with this type, a goods-dominant logic perspective on innovation. The thumb of rule states that these innovations most often are easily copied by industry competitors, or reverse engineered, and therefore provide with only a temporary advantage.

 
The “product system” division refers to the bundling and connecting effects between products and services. The foundation for fostering these effects lies in interoperability, modularity and integration between otherwise distinct and separate offerings. Therefore, product systems are the blueprints for building valuable and protected and differentiated product offering entities, that strives for establishing ecosystem-like synergies within the company’s reach and boundary.

 
The first innovation type in the experience category is “service”. This division refers to the innovations that “ensure and enhance the utility, performance, and apparent value of an offering”. Thus, services function as a supporting element that improves the customer journey and reveals new overlooked value capabilities for the users.

 

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Figure 1. Illustration of the innovation type framework with the three segments distinguished in different colours. The innovation types are ordered from left to right, according to its internal to its external impact and influences of the enterprise (from Keeley et al., 2013).

The channel division involves all the conceptual innovations associated with connecting the value offerings with the customers and users of a company. In short, channel innovations are various new infrastructure solution concepts that conveys the final products or services to the end users.

 
The “brand” innovations helps the customers to remember, recognize and prefer the offerings of a company over other similar substitutes. The goal is to seduce and attract the customer with a conveyed promise that will make the offerings distinctive and unique. By doing this the offerings gain an immaterial advantage over its competitors that gives rise to new exploitable value dimensions.

 
The “customer engagement” is the final innovation type, and strives for designing and implementing a deep relationship between the enterprise and its users that symbolises meaningfulness and endeavours aspirations beyond the original commercial incitements. This means that the paradigm encompasses and stimulates an emotional dimension to the offerings of a firm, which give rise to a symbiosis effect between the company and its users.

 

Periodical tables might change…

It is clear that the 10 types of innovation is a pragmatic model for classifying different innovations. However, innovations are obviously not as straightforward as the model suggests. The chategories may develop over time or new ones might be introduced etc., just like new elements are found and added into the periodical table, when new scientific breakthroughs are made . But the great value in this model is that it will help you seeing things from a different perspective. That in itself is a innovation! 

/Drill

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”

Chesbrough

Inside-out

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).

Outside-in

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.

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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 

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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.

/Drill

 

References:

Bergmark, H,, 2015. Interview. April 16th. 11:30

Chesbrough, H.W., 2006a. Open innovation: The new imperative for creating and profiting from technology. Harvard Business Press.
Chesbrough, H. ,2006b. Open Business Models: How to Thrive in the New Innovation Landscape. Boston: Harvard Business School Press.
Chesbrough, H. (2010). Business Model Innovation: Opportunities and Barriers. Long Range Planning, 43(2-3), 354-363.
Chesbrough, H., 2012. Open innovation: Where we’ve been and where we’re going.Research-Technology Management, 55(4), pp.20-27.
Chesbrough, H., 2013. Open business models: How to thrive in the new innovation landscape. Harvard Business Press.
Chesbrough, H. and Brunswicker, S., 2014. A fad or a phenomenon?. The adoption of open innovation practices in large firms. Research-Technology
Management, 57(2), pp.16-25.

Cisco, 2016. What is the Cisco I-Prize?. [Online] Available from: https://www.cisco.com/web/solutions/iprize/info.html#ov1%5BAccessed 19 August 2016].

imaa, 2016. M&A Statistics. [Online] Available from: https://imaa-institute.org/statis tics-mergers-acquisitions/ [Accessed 14 August 2016].

Innocentive, 2016. About Us. [Online] Available from:
https://www.innocentive.com/about-us/ [Accessed 14 August 2016].

Kallonen, A., 2016. Interviewed on 4th May. 09:00.

Keeley, L., Walters, H., Pikkel, R. and Quinn, B., 2013. Ten types of innovation: The discipline of building breakthroughs. John Wiley & Sons.

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

Times Higher Education, 2016. Alliances in Science: Innovation Indicators.

Productivity Commission, 2016. Digital Disruption: What do governments need to do?. Australian Government Productivity Commission Research Paper. June 2016. [Online] Available from:http://www.pc.gov.au/research/com pleted/digital-disruption/digital-disruption-research-paper.pdf
[Accessed 14 August 2016].

Wert, J., 2016. Interviewed on 15th September. 09:25

World Economic Forum, 2015. Industrial Internet of Things: Unleashing the Potential of Connected Products and Services.

Seven Laws of Information – A Foundation for “Digital Wisdom”

186721518Information is increasingly being perceived as a valuable asset in today’s modern society, de facto that in some occurrences information is by far the most valuable asset of a business and its activities. This tendency is refered often with the quote: “data is the new oil”.

What is problematic about Information is that it has an intangible character embedded to it, which makes it very hard to evaluate its real actual nominal value. Moody and Walsh (1999) recognizes this issue and introduces seven laws or postulates associated with the natures of information in order to understand its underlying value and how information differs from regular assets. I believe that by understanding the very nature of information (combined with the DIKW – hierarchy, which was my second blog post), one is able to become more wise, but also able to obtain a new form and dimension of  wisdom, which I would like to call it “digital-wisdom”.

1. Infinitely shareable

The first law states that information is infinitely shareable. Essentially this means that information has the unique ability of being shared among numerous parties, “without consequent loss of value to each party” (Moody & Walsh, 1999). The fact that information can be unlimitedly replicated and shared, with no real additional costs, makes it possible for many parties to use it at the same time. However, the duplication of information does not mean an increase of financial value of the information set (Uckelmann et. al., 2011). In contrast, information is very different from regular assets because assets are appropriable, i.e. you either have it or you do not (Moody & Walsh).

2. The value increases with use

The second law is that the value of information increases with use. This is intriguing because usually resources deprecate with use. In spite of this statement, it is important to point out that information does not provide any value if it is not used at all (Uckelmann et. al., 2011). Thus Moody and Walsh (1999) concludes that information in itself “has no real value on its own” and is in it unused form seen rather as a liability.

3. Perishability

The third law indicates that information is perishable. In practice this means that information depreciates over time and can thus be compared to any other asset (Moody & Walsh, 1999). The useful lifetime of information is therefore often relatively short, though it can be extended to a certain point when used for decision-making (Moody & Walsh, 1999).

4. Accuracy

The fourth law postulates that the value of information increases with accuracy. It is apparent that the more accurate information, the more valuable it beholds. However, 100 percent accuracy is rarely required in a business context, while a 100 percent accuracy is a must in some cases, such as maintenance or data banking records (Uckelmann et.al., 2011). In regards of decision-making, the level of “accuracy of information is as important as having accurate information”, because the margins for errors can be incorporated into the context (Haebich, 1997). For this reason, the view extends itself to the fifth law.

5. Synergies of combined pieces of information

The fifth law establishes that the value of information increases when combined with other information. Practically this states that integration or comparison of information generates new additional value. Therefore, it is evident that even a slight standardization of this information integration process will accumulate with high benefits. The inclusion of both identifiers and coding schemes are facilitating computing tools for achieving these benefits (Uckelmann et.al., 2011). Often the integration process is a great hurdle for many organisations, thus it is suggested that the focus ought to be aligned with the pareto principle, or the 80/20 rule, where the idea is that most of output is generated from the 20 percent effort or input (Moody & Walsh, 1999).

6. The more, ain’t better

The sixth law states that more information is not necessary better. Nevertheless, increasing amounts of information do result in more value to a certain extent, however crossing the information overload point causes significant problems and issues (Uckelmann et.al, 2011). Moody and Walsh (1999) points out an interesting empirical paradox related to information and decision-making, which is that the perceived value of information continue to increase even after the information overload point has been reached. The reason for this delusion is most likely related to the misconception that more information helps to avoid mistakes and reduces the uncertainty involved (Moody & Walsh, 1999).

7. Not depletable

The seventh and last law appoints that information is not depletable. At heart this refers to the fact that information is self-generating – the more one use it, the more one obtains of it (Uckelmann et.al, 2011). This differs greatly from traditional assets and resources, who cease to exist the more it is used (Moody & Walsh, 1999).

Summary

By understanding the very nature of information, it is evident that it is a very misunderstood and poorly managed asset, especially in terms of duplication; lack of standardisation; and lack of attention to its quality (Moody & Walsh, 1999). If other assets were managed in a similar manner as information (e.g. financials or people) then firms would most likely go out of business. Therefore, in order to manage information properly, one needs to understand its many unique features and facets (Alberts et.al, 2001).

The “digital wisdom”, as a concept, is in its very early stages and needs to be futher clarified. For now it will answer to the simple question: “know-why?“, when associated with digital and other heavily data oriented technologies. And evidently, the seven laws of information helps to clarify this matter to some extent, though there is still a long way to go. Finally, my future belief is that new regulations, such as GDPR, will empahsize the importance of “digital wisdoms” for both consumers and firms. This because “digital wisdom” also comprises both ethics and foresight within the context of digital data, which clearly is needed in the future.

/Drill

References:

Alberts, D.S., Garstka, J.J., Hayes, R.E. and Signori, D.A., 2001. Understanding infor mation age warfare. ASSISTANT SECRETARY OF DEFENSE C3I/COMMAND CONTROL RESEARCH PROGRAM  WASHINGTON DC, pp. 9-17.

Moody, D.L. and Walsh, P., 1999. Measuring the Value of Information – An Asset Valuation Approach. ECIS (pp. 496-512).

Uckelmann, D., Harrison, M. and Michahelles, F., 2011. An architectural approach towards the future internet of things (pp. 260-263). Springer Berlin Heidelberg.

Effectual Reasoning – A piece of Wisdom for both Startups and Life

As we all know, lately there is a lot of hype – “fuzz an buzz” – related to the subject of entrepreneurship. Damn, nowadays it seems like everybody is working with or starting their own startups. Me being a notorious Devil’s advocate and a supporter of long-term thinking, have a somewhat of a critical standpoint toward this phonomenon of just striking gold and doing it fast. In my opinion, beautiful visions and mision are worth far more than their weight in gold.

The other day I was discussing with a very inspiring professor of Entrepreneurship. To challenge him and this academical subject, I decided to ask the professor for the most intresting and appealing idea wihtin his field that he have come accross. My expectations was to yet again to see emperor’s new clothes. Though as it turned out, I couldn’t have been more wrong.

So what did the professor give me? It was a paper on the philosophy of “Effectual reasoning”.

What is Effectual Reasoning?

Effectual vs. Causal Thinking

As the word “effectual” is inverse of “causal” and originates from the science of entrepreneurship. Causal rationality, or predictive reasoning, “begins with a pre-determined goal and a given set of means, and seeks to identify the optimal – fastest, cheapest, most efficient, etc. – alternative to achieve the given goal” and is often applied in strategic thinking (Sarasvathy, 2001). Thus the underlying logic is that the future is both predictable and controllable.

Causal thinkers are like great generals seeking to conquer fertile lands (Genghis Khan conquering two thirds of the known world)

 

However, effectual reasoning differs in the sense that it does not begin with a specific goal and that the future is unpredictable, but controllable and still to be made (Sarasvathy, 2001). According to Sarasvathy (2001) effectual reasoning begins with a given set of means and allows goals to emerge contingently over time from the varied imagination and diverse aspirations of the founders and the people they interact with”. Thereby effectual reasoning adjusts and adapts goals according to the surrounding contingencies and unfolding unexpected events.

“Effectual thinkers are like explorers setting out on voyages into uncharted waters (Columbus discovering the new world)”

It is clear that effectual reasoning is “inherently creative” philosophical approach that breaths execution and thus demands something more beyond the regular and domains specific skills and abilities, such as imagination; spontaneity, risk-taking and salesmanship (Sarasvathy, 2001). These features can be compiled into five conceptual principles.

The Five priciples of Effectual Reasoning

The first principle goes by the name “bird-in-hand” and refers to the process where the individual inspect their own means. In general, the means are divided into three categories that involves the audit of: “who they are” – their abilities and traits; “what they know” – experiences and knowledge; and, “whom they know” – social and professional networks (Effectuation, 2011; Sarasvathy, 2001).

The second principle is “affordable loss” which essentially is an evaluation of the potential downside risk for the overall project, if the worst case scenario would occur (Effectuation, 2011). The idea with the affordable loss principle is that it pre-established. That is how much resources is allowed and affordable to lose for a given project. If the pre-determined limit is reached, then the project is automatically rejected.

The third principle is called “lemonade” and revolves around the element of surprise (Effectuation, 2011). This means that contingencies and surprises are the norm for all projects and therefore ought to be welcomed and leveraged, instead of perceived as a misfortune.

The fourth principle is named “patchwork quilt” principle and is about building and establishing strategic partnerships (Effectuation, 2011). Thus, this principle encompasses trust and how to leverage this through collaboration.

The final principle is “pilot-in-the-plane” and is the combination of the previous four principles into an entity that forms “the belief that the future is neither found nor predicted, but rather made” (Effectuation, 2011). In a nutshell, the effectuation as philosophy is about iterating and leveraging competences and means in the most effective and adaptive way.

Thus, the priciples can be summarised in the following picture:

FivePriciples

Serendipities – The Core of Effectual Reasoning

The element of surprise is generally perceived as an undesirable and avoided state for any human-being and situation. This Despite the overlooked and powerful opportunities that serendipities potentially can provide with. A serendipity is defined by oxford dictionary as “the occurrence and development of events by chance in a happy or beneficial way”. In other words, serendipities is an actual word for unpredictable occurances and situations that provide with the most insightful knowledge, wisdom, and happiness for us all. Thus, serendipities are the core of effectual reasoning. (To read more about it, check this blog post).

Serendipities are the occurrence and development of events by chance in a happy or beneficial way”.

On that note, embrace surprises and unpredictive event. These might be the things/opportunities you are actually looking for. And apply the philosophy of effectual reason to make and form your future. Do it. Do it now.

/Drill

 

References:

Effectuation, 2011. Principles of Effectuation. [Online] Available at: http://www.effectuation.org

Sarasvathy, S.D., 2001. What makes entrepreneurs entrepreneurial?.