Creative crowds and wise screen teams are needed to accelerate customer centric innovation

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The major finding of this thesis is thus that desirable capabilities and behaviors of crowd and screen team are highly distinctive but complementary; they are interdependent and indispensable to enable accelerated innovation in the context of Novozymes.
It follows that sustainable use of crowd-sourcing as an innovation accelerator in Novozymes must pay special attention to ensure that innovator crowds stay creative and engaged but also to muster critical, yet open-minded screen teams. The value proposition to these expert teams must be that facing the creative, ‘noisy’ chaos of the crowd can have significant paybacks in the form of new maps of insights which could be much more intriguing than ‘just’ a couple of new good ideas.

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Creative crowds and wise screen teams are needed to accelerate customer centric innovation

  1. 1. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 1 | P a g e Creative crowds and wise screen teams are needed to accelerate customer-centric innovation A case study of an internal online ideation at Novozymes Copenhagen Business School MSc. Management of Innovation & Business Development January - 2014 Christian Brix Tillegreen (021187-2179) - Supervisor: Jörg Claussen Dept. of Innovation and Organizational Economics
  2. 2. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 2 | P a g e Std. Pages: 68 (STUs: 129.430) Executive Summary Development of innovative solutions which meet market needs timely and accurately is becoming more and more critical for companies in order to stay competitive. With the advent of the digital collaboration age crowdsourcing offers a novel approach to conceive and co-develop innovative solution concepts online. The implicit attractiveness of crowdsourcing lies in the expectation of an acceleration effect: while traditional communication of market needs and ensuing solution development involves lengthy, error-prone communication processes, crowdsourcing opens the possibility to engage all critical business functions simultaneously and in a real-time fashion. Thus, market needs could be shared instantaneously across the organization and turned into solutions concepts faster and more accurately through cross-functional concept development. The present thesis investigates certain success factors which need to be in place in order to further strengthen the role of crowdsourcing as an innovation accelerator in the Danish biotech company Novozymes. Earlier research on an internal crowdsourcing campaign in Novozymes had already indicated three key success factors: (1.) diversity of crowd composition, (2.) absorptive capacity and capability of the idea-receiving organization and (3.) a culture permissive to new ideas and innovation (Lauto et al., 2013). The present thesis now focusses on a more recent dataset, recorded from a subsequent internal digital campaign, called ‘New Claims for Detergents’. Here the focus of attention lied with particular capabilities of the crowd and the screen team, respectively. ‘Crowd wisdom’ was investigated as the crowd’s capability to create a sufficiently large number of quality ideas, to co-develop these through cross-functional discussion as well as their collective receptiveness to novelty and to market needs as articulated in the presented ideas. The ‘screen team’s wisdom’, on the other hand, related to the professional scrutiny of this expert group and their cognitive capability of gaining new insights from the presented ideas and their discussion by the crowd.
  3. 3. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 3 | P a g e With regards the crowd’s wisdom it was found that the present crowd of 105 employees was highly engaged in sharing and actively discussing 76 diverse ideas, many of which featured novelty and market needs. Moreover, idea novelty, articulation of market needs and cross-functional discussions where significant predictors of high dot-vote scores as awarded by the crowd. Interestingly, the screen team’s perception of the same ideas and discussions was distinctively different: novelty, market needs and cross-functional discussions were not correlated with the screen team scores. This was interpreted as the result of the team’s critical scrutiny for idea consistency and in particular for supporting evidence. Furthermore, this 5-person team took the ad hoc decision to go beyond their originally stated objective of identifying a couple of trophy ideas (‘idea hunting’) because they became intrigued by emerging idea-connections during their meticulous work with the idea-universe generated by the crowd. They conceived a systematic approach to cluster and organize all ideas which lead to a ‘strategic’ idea map. This was an unintended product of their collective cognitive process and enabled new angles of discussion in their management circles. While it is too early to conclude whether this serendipitously arising cognition process can form the foundation of a new repeatable ‘crowd-strategizing’ protocol, it seems very unlikely that the condensed insights of the screen team would have been possible without the spontaneous, collaborative mass- creativity of the crowd. It is discussed whether it is desirable to push innovation burden from the screen team onto the crowd (e.g. by demanding better idea consistency and evidence), because one has to consider the inherent risk of negatively impacting the very crowd-creativity without which the screen team cannot unfold its potential of insight creation and ‘wisdom’. The major finding of this thesis is thus that desirable capabilities and behaviors of crowd and screen team are highly distinctive but complementary; they are interdependent and indispensable to enable accelerated innovation in the context of Novozymes. It follows that sustainable use of crowd-sourcing as an innovation accelerator in Novozymes must pay special attention to ensure that innovator crowds stay creative and engaged but also to muster critical, yet open-minded screen teams. The value proposition to these expert teams must be that facing the
  4. 4. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 4 | P a g e creative, ‘noisy’ chaos of the crowd can have significant paybacks in the form of new maps of insights which could be much more intriguing than ‘just’ a couple of new good ideas. Table of Content 1. Introduction...................................................................................................................................... 7 1.1 Problem statement ..........................................................................................................................................9 1.2 Research hypotheses.....................................................................................................................................11 1.3 Research relevance .......................................................................................................................................15 1.4 Disposition....................................................................................................................................................16 2. Literature review ........................................................................................................................... 17 2.1 Innovation – in the science-based corporation .............................................................................................18 2.2 Crowdsourcing .............................................................................................................................................19 2.2.1 Assembling the “wise crowd” ................................................................................................ 20 2.2.2 Crowdsourcing in the corporation ......................................................................................... 21 2.3 Collaboration modes.....................................................................................................................................25 3. Company and case description..................................................................................................... 28 3.1 Description of Novozymes ...........................................................................................................................28 3.2 Innovation in Novozymes.............................................................................................................................30 3.3 Innovation processes in Novozymes ............................................................................................................31 3.4 Case: New Claims for Detergent Enzymes ..................................................................................................32 3.4.1 The process of “New Claims for Detergents”........................................................................ 33 3.4.2 Scope and plan........................................................................................................................ 33 3.4.3 Mobilization and composition the crowd ............................................................................... 34 3.4.4 The online ideation phase....................................................................................................... 34 3.4.5 Screening and selection of ideas............................................................................................. 35 4. Methodology................................................................................................................................... 37 4.1 Research approach and design......................................................................................................................37
  5. 5. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 5 | P a g e 4.1.1 Data collection........................................................................................................................ 38 4.1.2 Qualitative data ...................................................................................................................... 39 4.1.3 Quantitative data .................................................................................................................... 40 4.2 Two-fold analysis of crowd versus screen team...........................................................................................43 4.3 Limitations....................................................................................................................................................44 5. Analysis........................................................................................................................................... 45 5.1 Analysis part 1: Descriptive analysis and distribution of ideas...................................................................46 5.1.1 Outcome of “New claims for detergent”................................................................................ 46 5.1.2 Ideas with cross-functional involvement: ............................................................................... 47 5.1.3 Novelty of ideas: ..................................................................................................................... 49 5.1.4 Clustering of the ideas............................................................................................................ 50 5.1.5 Responsiveness to market needs:............................................................................................ 51 5.1.6 Screen team evaluation: ......................................................................................................... 54 5.2 Conclusion of analysis part 1: ......................................................................................................................56 5.3 Analysis part 2..............................................................................................................................................58 5.3.1 Putting the numbers into relation........................................................................................... 58 6. Discussion........................................................................................................................................... 60 6.1. Revisiting the research hypotheses..............................................................................................................60 6.2 The crowd‘s excitement about the presented ideas was not shared by the screen team...............................62 6.2 The screen team’s perspective......................................................................................................................63 6.3 From singular ideas to ‘strategic idea landscapes’ .......................................................................................65 7. Conclusions and Perspectives - Moving from idea-hunting to ‘crowd-strategizing’ .............. 68 7.1 Further Research...........................................................................................................................................71 Bibliography .......................................................................................................................................... 72 Appendices..................................................................................................Error! Bookmark not defined. Appendix 1: ........................................................................................................Error! Bookmark not defined.
  6. 6. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 6 | P a g e Appendix 2: ........................................................................................................Error! Bookmark not defined. Appendix 3: ........................................................................................................Error! Bookmark not defined. List of Figures and Tables Figure 1; Disposition of the thesis .......................................................................................................... 16 Figure 2; the layers of crowds................................................................................................................. 22 Figure 3; Modes of Collaboration........................................................................................................... 26 Figure 4; Novozymes organization......................................................................................................... 29 Figure 5; Process of online ideation........................................................................................................ 33 Figure 6; Composition of the Crowd ...................................................................................................... 47 Figure 7; Distribution of new ideas ........................................................................................................ 49 Figure 8; Comprehensive idea map ........................................................................................................ 50 Figure 9; Statistical comparison of screen team scores given on commercial and technical criteria ..... 55 Table 1; Table of hypotheses .................................................................................................................. 11 Table 2; Pros and Cons of Crowdsourcing ............................................................................................. 23 Table 3; Total outcome of the dataset:.................................................................................................... 47 Table 4; Distribution of cross functionally discussed ideas.................................................................... 48 Table 5; Origin of the Top 25 ideas ........................................................................................................ 49 Table 7; Distribution of ideas with market articulation.......................................................................... 54 Table 8; Regression model of the screen team score and the crowd score:............................................ 59 Table 9; Summary of findings and hypotheses acceptance .................................................................... 62
  7. 7. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 7 | P a g e 1. Introduction “…You can’t ask customers what they want and then try to give that to them. By the time you get it built, they’ll want something new…” - This quote by Steve Jobs is a great point of departure for this thesis. The ability to develop new innovations that customers actually want is one of the single hardest things to do for a modern corporation. Especially in times where technology and markets are changing by the day, in relation to Moors law (Moore, 1965), the rapid development in production and new market spaces are forcing companies to innovate faster and to come up with new ideas they can deliver to the market more rapidly than the competitor. One of the greatest challenges for innovation in modern corporations is the organization’s ability to listen to the ‘market needs’ and to develop solutions which meet the customer’s needs accurately, timely and cost competitively. In essence, this capability equals accelerated innovation, which should give companies a substantial competitive advantage. Looking at Danish biotech company Novozymes, the challenge of accelerating innovation is put high on the agenda by top management. In April 2013 the new CEO, Peder Holk Nielsen, addressed this challenge in a press release video about the new strategy in Novozymes in which he focusses on customer-centric innovation as a new ambition for Novozymes: “…The first focus area of the new leadership-team is on growth, it is going to be, bringing innovation quicker, faster, from labs, from our research through business development and to our customers. Get this process to work faster and to get more delivered to our customers, this is focus area number one…” - Peder Holk Nielsen, CEO of Novozymes, interview from Spark TV 02/04/20131 . This thesis is set out to investigate how Novozymes handles this challenge by using digital tools and internal crowdsourcing in their goal to deliver innovation faster to their customer, and more accurate to the market needs. Listening, understanding and responding to the market needs with competitive innovations is difficult because of the organizational complexity: even the most skilled sales representatives and technical 1 http://www.novozymes.tv/video/7631519/peder-holk-nielsens-view-on.
  8. 8. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 8 | P a g e service experts may not understand what the customer really wants and the reports they forward to the other parts of the organization may dilute or even distort the essence of the customer’s need. As a result, R&D more often than not may end up developing the wrong products too late. A partial solution to this challenge lies in establishing multidisciplinary account teams, made up of sales reps, customer service, supply chain and R&D experts. Still, many account teams may find themselves challenged in lacking the necessary diversity of skills and insights – which they naturally will attempt to mitigate by engaging into a dialogue with their cross-functional networks. Undoubtedly, such dialogue increases a given account team’s chances to kick start the right innovation activities but the underlying problem of lacking diversity still lingers because account teams will in most cases try to get their answers and insights from their ‘usual suspects’ – i.e. the expert circles which the habitually consult and collaborate with. Consequently, innovation will follow the established patterns of failures and successes. The advent of collaborative online ideation tools which combine elements of traditional ideation and social media seem to offer a more fundamental solution to the problem of limited diversity. Idea campaigns can be designed in such a way that very large and very diverse crowds are composed of members across all functions of the business system, all markets, segments and hierarchy levels. Naturally, customers can be part of such ideations as well. In a sense, online ideations facilitate a ‘level playing field’ discussion because everybody’s’ ‘voice’ is equal and is being ‘heard’ by everybody else, and everybody’s dot-votes count the same. Thus, differences in hierarchy are – at least partially – abolished. Hence, the anticipation is that in such an arena there is a much higher chance that the actual market needs are being heard in an undistorted fashion and responded to in a meaningful way by a motivated crowd of creative participants. Novozymes has been using collaborative online ideations since 2011 in a successful manner and routinely across business divisions. The first online ideation in Novozymes was studied thoroughly by Lauto et al (2013). The main findings were that online ideations are a potent tool to boost front-end innovation through digital collaboration. The research subject for this thesis is to give a descriptive analysis of one particular Novozymes online ideation campaign called ‘New Claims for Detergent’ and to investigate how the ‘market needs’ are
  9. 9. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 9 | P a g e being perceived in the articulated ideas and in the crowd discussion. One of the most tantalizing questions which this thesis tries to answer is whether there is significant evidence that the crowd responds to market needs with innovative solutions. “…Innovation has nothing to do with how many R&D dollars you have. When Apple came up with the Mac, IBM was spending at least 100 times more on R&D. It's not about money. It's about the people you have, how you're led, and how much you get it…” Steve Jobs quoted in "TIME digital 50" in TIME digital archive (1999) The overall objective of this thesis is not to arrive at general conclusions or validations about crowdsourcing as such rather its aim is a more in-depth investigation of a single case on how internal crowdsourcing can accelerate the innovation process in a global company. By applying newly gained knowledge in the most appropriate way, and thereby pose some unambiguous propositions and managerial recommendations for future acceleration of innovation within Novozymes. 1.1 Problem statement The internal crowdsourcing exercise ‘New Claims for Detergents’ which is the subject of this thesis was novel in Novozymes in the sense that it aimed at create new concepts in response to market needs as articulated in the ideas from Sales and Technical Service participants. This was in contrast to earlier internal crowdsourcing exercises which were mostly conducted within the R&D community exclusively, with no or little representation of customer-facing employees. The crowd of ‘New Claims for Detergents’ thus consisted of employees from Sales, Technical Service, Marketing and R&D, spanning across the entire value creation chain of Novozymes. Participants were partially known experts within the field (enzymes for detergent) and partially ‘unusual suspects’ i.e. people without an expertise in detergent enzymes but with a high potential to contribute with good ideas and energy to the cause. Typically, newcomers with a rising star reputation working in other business divisions were chosen to complement the ‘usual suspects’. Diversity was also present in terms of geographical location and tenure of participants. The dataset used for this thesis represents a digital ideation campaign which lasted approx. 14 days, leading to 74 ideas and over 200 comments, produced by 105 employees from worldwide locations. The limitation however was that the ideation did not involve
  10. 10. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 10 | P a g e customers directly but that representatives from Sales and Tech Service functioned as ‘proxies’. This thesis will investigate the following aspects in order to answer the posted research questions: The presented thesis studies the abilities of online ideation as a tool for idea generation filtering as well as deeper insight creation into idea clusters, which extends beyond identification of singular winner ideas. As argued by a number of scholars and researchers the ability of crowdsourcing to turn ideas into innovations and new products it is difficult to measure or even predict (Poetz and Schreier, 2012). The purpose of this thesis is therefore to contribute to the existing literature with empirical evidence from the case of “New Claims for detergent”. The exploratory nature of the research has led to an investigation of the effects of inventor diversity on the development of ideas. The question examined is thus: Which role does the ‘wisdom’ of the crowd and the screen team play in internal crowdsourcing as a tool to accelerate a corporation’s response to market needs? In order to answer this central research question the analysis will go into investigation of nine different hypotheses as stated below. The examination of these research hypotheses will elucidate the different conditions which need to be fulfilled in order to conduct online ideations successfully – which, in turn, is expected to accelerate customer centric innovation processes. Based upon the results and managerial recommendations will be proposed to aid the company’s ongoing exploration of opportunities within crowdsourcing. It is thus hoped that this study makes a contribution to enhance and to optimize future customer-centric innovation processes.
  11. 11. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 11 | P a g e 1.2 Research hypotheses In order to answer the question whether the crowd and the screen team in the present campaign can be considered as ‘wise’ and thus having the potential to accelerate customer centric innovation, nine hypotheses are stated which are clustered in four categories (Table 1). In the context of this thesis a wise crowd is expected to: (1.) Come up with a large proportion of high-quality ideas in relation to the stated challenge (hypotheses 1-3) (2.) Present a substantial proportion of novel ideas which are considered as having a high innovation potential by crowd and screen team alike (hypotheses 4 and 5) (3.) Present a substantial proportion of ideas which trigger cross-functional discussions which serve to develop these ideas in a collaborative fashion. Such ideas are ranked highly by crowd and screen team, respectively (hypotheses 6 and 7) (4.) Propose a substantial fraction of ideas which contain a clear articulation of market needs. Furthermore, such ideas are ranked highly by crowd and screen team alike (hypotheses 8 and 9). Table 1; Table of hypotheses Hypothesis category Hypo- thesis no. Hypothesis text Criteria for acceptance Method of testing Idea quality 1 Ideas of high quality are characterized by a substantial length of text in order to articulate thoughts of a certain complexity. Such ideas represent the majority in the present idea population. 75% of all ideas contain more than 420 characters Descriptive statistics 2 Ideas of high quality draw multiple comments from the crowd and constitute the majority in the present idea population. 75% of all ideas are associated with at least 2 comments Descriptive statistics 3 Ideas of high quality contain supporting references to internal or external sources, which is the case for a substantial fraction of present ideas. 25% of all ideas contain references Descriptive statistics
  12. 12. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 12 | P a g e Idea Novelty 4 Novel ideas represent a substantial fraction of the idea population 25% of all ideas were judged as novel by the screen team Descriptive statistics 5 Novelty is a predictor of high idea ranking. This is expressed by significant correlation of novelty with idea scores, as given by the crowd and the screen team, respectively p<0.05 Regression analysis Idea co- creation 6 Ideas with cross-functional comments constitute a substantial proportion of the entire idea population 25% of all ideas are associated with cross- functional comments Descriptive statistics 7 Co-creation is a predictor of high idea ranking. This is expressed by significant correlation of cross-functional discussion with idea scores from crowd and screen team, respectively. P<0.05 Regression analysis Responsiv eness to market needs 8 Ideas which contain a clear articulation of market needs constitute a substantial proportion of all ideas 25% of all ideas contain market needs articulation Descriptive statistics 9 Ideas with market needs articulation are ranked highly. This is expressed by significant correlation of ‘market need articulation’ with idea scores from crowd and screen team, respectively. P<0.05 Regression analysis The reasoning behind picking the various acceptance criteria for the nine stated hypotheses is explained in the following: arbitrary criteria were used for all hypotheses which were tested by descriptive analysis (hypotheses no. 1-4, 6 and 8). Statistical significance (p>0.05) was the acceptance criterion when testing hypotheses no. 5, 7 and 9. Hypothesis 1: ‘Substantial length’ is arbitrarily set to mean 420 characters of text based on the communication principle in the social medium Twitter: in Twitter a post is limited to 140 characters, but the immense global success of the medium proves empirically and beyond doubt that 140 characters comprise an information ‘package’ or ‘string’ whose length is fully sufficient to express a virtually unlimited number of reasonably complex thoughts. In the context of this thesis it is further inferred that a well-articulated idea consists of at least three such Twitter-length statements (3 x 140 =
  13. 13. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 13 | P a g e 420): first statement pertaining to background or context of the presented idea, second statement embodying the problem at hand and the third statement describing the proposition of its solution. ‘Majority of ideas’ is defined to mean 75% of all ideas posted. Hypothesis 2: It is assumed that the number of comments which an idea triggers is likely to be an indicator of content relevance and thereby of idea quality. It is reasoned that ideas with no comments are most irrelevant since nobody in the crowd was enticed to respond to them. Ideas which drew only one comment are equally likely to have a no or only very low relevance since singular comments may just be an expression of spontaneous (dis)approval. Thus, the minimum number of comments which an idea needs to draw from a crowd to be considered relevant – at least to some extent – is two. Two comments per idea are viewed as a minimum threshold for relevance: an initial idea is sufficiently relevant to trigger somebodies comment and somebody else adds another comment which contributes an additional perspective to the idea or the first comment. One could also say that one idea and two ensuing comments constitute a set of minimum requirements to justify the use of the term ‘idea discussion’. Hypothesis 3: References to internal or external sources are a strong indicator of idea quality since references support ideas with ‘reason to believe’ originating from others than the idea proposer. The crowd of the investigated campaign consisted of 50% participants from R&D. It is therefore argued that since R&D employees (i.e. scientists) are to a high degree used to reference their results and conclusions, it would be fair to expect that at least half of all ideas coming from R&D should contain some kind of reference. This would correspond to a reference incidence of 25%, assuming an equal distribution of idea generation frequency across all business functions involved. Hypothesis 4: Idea novelty is a key feature of innovation and in the present campaign the screen team scored all 74 ideas as being novel or not after the campaign was concluded (Appendix 2). The re- combinatorial nature of ideas, as described by Schumpeter (1939), Nonaka (1994) and others, implies that one can expect novel ideas to constitute a substantial but still minor percentage of all idea posted. In the context of an earlier Novozymes crowdsourcing exercise by Lauto et al, (2013) found that only about 25% of all posted ideas could be considered as novel. Based on this evidence the acceptance criteria for using the term ‘wise crowd’ is equally being set to 25% for the idea population studied here.
  14. 14. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 14 | P a g e Hypothesis 5: Novelty is also expected to be correlated positively with idea ranking. In the present dataset two such rankings exist: the idea ranking of the crowd, as expressed by the sum of dot-votes per idea, and the idea ranking of the screen team, recorded as the summed quantitative scores on six pre-set screening criteria for each idea (appendix 1). Regression analysis was used to answer the question whether there was a statistically significant (p< 0.05) correlation between the crowd and screen team perceptions of idea novelty as expressed. Hypothesis 6: Co-creation and collaboration are argued to be important – if not critical - conditions of innovation since different modules of knowledge and insight are recombined into something new (Keller, 2001). The crowd on ‘New Claims’ was cross-functional in its composition. Participants came from R&D, Sales, Marketing and Technical Service. It is arbitrarily expected that at least 25% of all ideas led to discussions between participants from different business functions. The reason why this threshold was not set higher is the notion that most employees from the implied functions were not used to have collaborative idea discussions with each other – but were faced with such a ‘challenge’ for the first time. Hypothesis 7: Cross-functional discussion is viewed as an indicator of collaboration on a given idea in the framework of the online process. Different perspectives and information are added to the initial idea which is expected to increase the innovation potential of the idea. It is therefore hypothesized that such ideas receive higher scores from crowd and screen team alike. Regression analysis was used to answer this question and significance level was set to be a p-value of p < 0.05. Hypothesis 8: In order to accelerate customer centric innovation, crowds need to be responsive to market needs. In the context of this thesis, market needs are indirectly articulated in the ideas posted by the various participants. A classification scheme was established to score the ‘intensity’ and ‘clarity’ of market need articulation as explained in Analysis 5.1.5. Since 50% of all crowd participants came from customer-facing business functions such as Sales, Technical Service and Marketing it is expected that at least 25% of all ideas are categorized as containing a market need.
  15. 15. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 15 | P a g e Hypothesis 9: It is hypothesized that a ‘wise crowd’ shows a significant (p<0.05) response to ideas with market need articulations, as expressed through high dot-vote scores. It is also expected that the screen team shares this perspective, as expressed through high scores on the pre-set criteria as detailed in Appendix 1. 1.3 Research relevance Since the internet has made it possible to connect individuals in larger groups to interact in online communities, there has been done extensive research in the area of crowdsourcing. In the resent years special focus has been put on the question on the maximal productive size of crowds, and which role crowd diversity plays in the innovation performance, (Soukhoroukova, 2012). However, there seems to be a need for a deeper perspective and analysis of what crowds actually express online and how constructions of new ideas emerge in such campaigns. The current literature seems elusive on this point. Recent work by Poetz and Schreier, (2012) is one of the few articles which c deals with research related to the present thesis. However, the focus in their study was more on the differences between the external versus the internal crowd performance. The research is especially narrowed down to a single company’s internal performance and how the generated ideas are related to the external world. It is also more focused on the screening process by senior experts versus the crowd’s opinion. The analysis of the participant’s ideas is relevant both in terms of strategic implications for the company and for the academic world, since such ‘crowd insights’ or ‘wisdom’ has not been investigated systematically before. The relevance of this thesis lies in its findings around how wise an internal crowd actually is and what unconsciously happens in the aftermath of the screening process. Especially in terms of ‘crowd- strategizing’ a novel cognitive step process was performed by the screen team which according to present search efforts has not been described previously in such form. In the sense of future crowdsourcing exercises in Novozymes, this thesis will be used as a key element in designing new opportunities with this field. The finding conclusion will also be presented to Innovation Management for recommendations in driving customer-centric innovation forward.
  16. 16. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 16 | P a g e 1.4 Disposition This figure illustrates the deposition which the thesis is built on and gives the reader a better perspective of what is done to answer and conducting the research. Figure 1; Disposition of the thesis
  17. 17. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 17 | P a g e 2. Literature review This chapter will provide a view of some of the recent and most relevant research literature on crowdsourcing and idea management in large corporations. The research, done in this field has been focusing to a large extend on external crowdsourcing (Howe, 2006). In the recent years, quantity has been the main research object, in terms of maximizing the crowd. However, the latest research investigates how to measure and manage the ideas coming in from the crowd (Soukhoroukova, 2012). The object of this part of the thesis is also to identify the how the literature reflects upon theory of assembling and using a crowd to achieve business objectives. The notion of using internal crowdsourcing in a strategic context is not something that has been documented that much, in contrast to a lot of theory regarding large open source and external crowdsourcing (Flynn, et al., 2003). In order to discuss the research hypotheses, it is necessary to create some clarification on how crowdsourcing has been presented and used to generate new ideas and solutions for the past decade. The measurement of a “wise crowd” and “picking the right idea” are two very different things, and seen as two different ways of executing an ideation. A winning idea can easily be a pure technology focused solution, however in this thesis, the theory is focused on the way companies built and structure their crowd in order to use the generated outcome in a strategic matter and identity knowledge and market gaps. The provided starting point is to give an understanding for what types of arguments that can be stated in order to justify online idea campaigns inside companies, and to give a perspective to narrow down some related and specific research. This enables the thesis to draw on some of the relevant theory to answer the research questions around the use of internal crowdsourcing in Novozymes. The following chapter will start with a short explanatory approach of where the need for a collaborative environment has emerged from in science based companies. Then the chapter goes into the core of the literature around crowdsourcing and explains the theoretical benefits and barriers and other implications of crowdsourcing.
  18. 18. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 18 | P a g e 2.1 Innovation – in the science-based corporation In the text “The evolution of Science-based business: innovating on how we innovate” by Gary Pisano from 2010, it is argued that traditionally, science has always been connected to innovation and thereby states that it has its home in the R&D part of the organization. However Pisano explains that in the later 20th century, innovation systems starts to change in the area of the emerging bioscience and biotechnology industry; especially in the way science and business are connected. A shift emerged in the way science moves more efficiently from the laboratory to the commercial market (Pisano, 2010). “…even DuPont, by the 1980s, was asking its research laboratories to focus more on the commercial needs of the existing businesses (Hounshell and Smith, 1989)…” Now, this seemed like a good way to get R&D aligned with the rest of the organization and an easy way to commercialize new innovations fast to the market, but Pisano argues that there is an important attribute that lies in the iterative nature of R&D, “…time horizons to resolve fundamental uncertainty can be quite long. Thus, not only might the financial costs of exploration be high, but critical technical uncertainties may not be easily or quickly resolvable early in the development process.” This is not a new challenge of the science-based business field, it is more a question of the knowledge base that the companies now operates in, which now is changing in an extreme pace. In areas where the underlying science is more mature, knowledge is often modular. That is, with deeper understanding comes knowledge about fundamental “building blocks” and how those interact (Ibid). Collaborative software is an example of how R&D can break down problems into module components, for example in the idea generation phase. In sense there could be different “pieces” but their boundaries are not clearly defined. How one thing affects the other may not be well understood at all (ibid). Pisano calls this “the integration problem” and relates it to the argument made more than 50 years ago by Schumpeter (1939), where he found that breakthrough innovation is the result of recombination and integration of existing bodies of knowledge (Fleming, 2001). Many empirical studies have confirmed that Schumpeter was right in his observations (ibid).
  19. 19. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 19 | P a g e 2.2 Crowdsourcing Crowdsourcing is a recent approach to increase the amount of ideas, solution and turn them into innovations in companies. The ideology behind crowdsourcing is to use the wisdom of many individuals instead of relying on only a few experts (Surowiecki, 2004). The literature uses various terms to describe related phenomena, such as peer production, collaborative systems, community systems, collective intelligence, crowd wisdom and mass collaboration (Flynn, et al. 2003). Other terms often used in the literature include consumer co-creation (Simula, et al. 2012), open innovation (Chesbrough, 2011), user innovation (von Hippel, 2005), collaborative innovation (Soukhoroukova, 2012), customer driven (Schreier, 2011) and used-generated content (Hine and Kapeleris, 2006). In this thesis the use of the term “crowdsourcing” is set to describe idea and innovation generation. Crowdsourcing is still on its raising in the corporate world, however the concept of crowdsourcing is very known in world around, basically it is a way for someone; a person, department, group, government, company, even countries, to source a question, problem, issues or new ideas and get feedback from a wide number of people; the crowd. In history we see a lot of different examples. Boudreau and Lakhani (2011) mention an example from the 15th century where authorities in Florence presented an open invitation for everyone to participate in designing what would be the world’s widest and tallest dome for the city’s new cathedral. One of the largest and most well-known examples of crowdsourcing is Wikipedia.org; this website is used all over the world and is developed by a global crowd to create free access to knowledge. The size of knowledge shared on Wikipedia is a great example of how powerful the internet can be in sharing and generate knowledge (Surowiecki, 2004). In the literature around crowdsourcing, the notion of “wisdom of the crowd” is very often discussed. The wisdom of the crowd refers to “the discovery that the aggregate of a set of proposed solutions from a group of individuals performs better than the majority of individual solutions.” (Yi et al., 2012:452).
  20. 20. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 20 | P a g e 2.2.1 Assembling the “wise crowd” In crowdsourcing the single most important variable that needs to be in place and function correctly if of cause the crowd itself. Surowiecki, 2004 suggest a framework whereas it is necessary to break down the advantages of crowdsourcing into three types of “wisdom of crowds”, which is classified as the following (Surowiecki, 2004): Cognition In order for a crowd to be cognitional, it needs to be highly capable of intellectual thinking and understand the information processing aspect of the problem proposed. Secondly the crowd needs to have some understanding of market judgment, which Surowiecki argues can be much quicker and more reliable, in producing ideas that will succeed in the evaluation process. The crowd is also less subject to political or managerial powers than the discussions of experts or in knowledge heavy committees (ibid). Coordination In order for a crowd to be classified as a coordinating crowd their behavioral approach needs to be clearly focusing around optimizing the utilization of the ideas co-development aspects. Surowiecki uses examples from experimental economics, however it is also takes in the cultural aspect in terms of how common understanding within a culture allows remarkably accurate judgments about specific reactions of other members of the culture (ibid) Cooperation The cooperative aspect of assembling the “wise crowd” refers to how crowds can form networks and connections of trust without a central system controlling their behavior or directly enforcing their compliance. Furthermore Surowiecki argues that, not every crowd is rational and can create wise decisions, (e.g. group of investors in a stock market bubble), so he describe these following four criteria you need to form a wise crowd, in order to create a rational crowd and not end up with an irrational crowd (Surowiecki, 2004).:
  21. 21. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 21 | P a g e Table 2; Criteria of a wise crowd (Source: Surowiecki, 2004) Surowiecki argues however, that failure of crowd intelligence is still a risk. In some cases the crowd can come up with bad judgment. He argues that the crowd cognition or cooperation failed because the participants of the crowd were too conscious of the opinions of others and instead of thinking differently started to emulate and conform each other’s ideas (ibid). He asserts that when the decision making environment is not set up to accept the crowd, then the benefits of individual and private knowledge is lost and not articulated. This can lead to the crowd only being able to be as beneficial as its smartest member, instead of perform better as a crowd (ibid). 2.2.2 Crowdsourcing in the corporation The preceding chapter has defined and discovered which factors are important to secure when using crowdsourcing as a tool. Now it is wanted to give a deeper understanding of crowdsourcing within the corporation, and look at some of the literature around internal crowdsourcing. In the text of Simula et.al, 2012, is it explained that the potential of crowdsourcing in relation to creating new ideas and innovations in a business-to-business environment is starting to get quite popular, because crowdsourcing is lowering the cost and shortening the product development cycles. One of the key value propositions of crowdsourcing is that it enables companies to collect ideas from large groups and manage review them, instead of using time and money on sourcing from few experts (Simula et.al, 2012) . In order to get an understanding of how crowdsourcing can be handled by companies I will use the framework provided by Simula et.al, 2012. This framework consists of four layers of participants, which a company can use when initiating an exercise for crowdsourcing. The framework builds on the traditional stakeholder theory (Freeman et. al. 2004). It is argued that this model can be applied to a
  22. 22. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 22 | P a g e number of industries, but in this thesis the research will mainly be used in the context of internal crowds. Figure 2; the layers of crowds (Scource: Simula et. al., 2012). In the center of the figure (3) are the employees of the company, this is also were most companies begin when using crowdsourcing in the business-to-business sector, however after some practices, proof of concept and success cases, the company can start to move into the external layers, consisted of trusted partner (also known as “value-chain partners”) by Freeman et al., 2004. The next layer consists of a specific crowd, including people with certain skills, knowledge and expertise or other pre- qualifications; it can also refer to a community of like-minded individuals (Simula et. al., 2012). The third and last layer is the general crowd which can consist of everyone, who has an interest in the scope of the campaign, even competitors can participate here. However in this case study it is necessary to return back to the first layer, and focus on the internal crowd, within the boundaries of the company. The other layers are outside the scope of this thesis. According to (Simula et. al., 2012) Companies usually target internal idea ideation at all employees, in order to increase serendipity, which is seen as a good thing. Howe, 2008, argues that the best solutions often emerge from crowds that are the least likely to come up with the right way of solving the raised problem. Internal crowdsourcing has been practiced by many companies. One example is the
  23. 23. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 23 | P a g e pharmaceutical giant Eli Lilly, who have demonstrated the value of harnessing the knowledge of employees to solve problem and idea generate throughout the organization. However Boudreau and Lakhani 2011, points out that company culture can be a major issue in the pursuit of getting a crowd to be innovative thinking, they state that one of the most important motivators is to provide the crowd with the sense that their ideas are valued by management. When designing an online ideation Simula et. al. 2012 argues that it needs to be done in such a way that they can be unambiguously understood by the crowd. In order to engage people in crowdsourcing and to make them contribute, people need to understand the context of the idea and have the right frame of mind (ibid). They argue that feedback also plays a major role in the perception of how the crowd will react to the requested task; “There is also the risk that people may want to develop their ideas by themselves and are not ready to share or that they think their idea is not good enough to post. Another challenge related to engaging users is the importance of feedback: not receiving feedback may have a negative impact on future participation of the contributor. Similarly, the informant in Gamma pointed out that if people think that the internal idea service is meant for R&D people only, there may be less interest in participating.”(Ibid). Simula et. al. 2012 gathers their findings in a table of advantages and benefits and some of consequences and barriers in using internal crowds in crowdsourcing. These thoughts of internal crowdsourcing will be taken into consideration in the discussion part of this thesis. Table 2; Pros and Cons of Crowdsourcing (Source: Simula et. al. 2012.)
  24. 24. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 24 | P a g e To get a bit deeper into the research related more specific to my study of internal crowdsourcing, I will draw on the recent published article, “The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generation New Product Ideas?” By Poetz and Schreier (2012). They make an analysis of a case company that crowd source ideas for new products, and ask a crowd of 100+ participants. 52 were internal employees and the remaining 51 were customers. The participants where posting ideas through the company website. The ideas were screened and evaluated by the company’s CEO and the Head of R&D, blinded of whether the source of the ideas originally came from inside the company or outside. The study is similar to my research in terms of measuring the ideas and where the ideas come from. Poetz and Schreier set the following research question; how attractive are new product ideas generated by users through a crowdsourcing process compared with new product ideas generated by a firm’s professionals? In this study it is stated that the professional engineers out performed in the creation of feasible ideas, in contrast to the ideas generated outside R&D, in the case the, which the authors conclude to be an indication that the professional crowd is much more focused on deliver ideas that is easier to realize in technical terms, whereas the ideas from costumers are focused on the commercial benefits for the end-user, but lacks of realistic deliverables and timeframes for actual execution to the market. Whereas the authors draw on the theory from Chesbrough (2011), that they need to reinvent the formulated question to a specific problem-solver, crowd or group.
  25. 25. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 25 | P a g e 2.3 Collaboration modes In the article by Pisano and Verganti, 2009, called “Which kind of collaboration is the right on for you?” the authors go through different types of crowdsourcing strategies. They are districting between open and closed networks, and between a hierarchical and a flat governance approach. This very simple framework is effective in order to get an overview of where the strategic decisions should be made when initiating a crowdsourcing exercise. The text especially discusses which types of crowds companies should invite and focusing on who will carry the “Innovation burden”, meaning screening and filtering ideas etc. They argue that the cost of searching and screening ideas increases when a company engages with larger crowds than the internal capacity can carry. However the advantages of having an open network could result in attracting a large number of problem solvers and consequently a huge number of ideas generated. The text argues that in this scenario the company doesn’t have to identify either the best knowledge domain or the most appropriate experts in those domains (Ibid). The company doesn’t even have to know the contributor, but the text argues that it can be dangerous as well, if the knowledge domain is a sensitive business area, where you don’t want to have competitors or others who can use the information provided to other winnings. The authors note that often interesting innovative solutions can emerge from contributors the company never has imagined could come up with good ideas. Open modes, however, have their disadvantages. An interesting notion is that, they are not as effective as closed approaches in identifying and attracting the best participants. Pisano and Verganti argue this is because as the number of participants increases, the likelihood that a participant’s solution will be selected (especially for an ambiguous problem) decreases (ibid). “…Open modes are effective only under certain conditions. First, it must be possible to evaluate proposed solutions at a low cost. Sometimes the screening process is extremely cheap and fast…” “…In other cases, though, the only way to find out whether an idea is worth pursuing is through expensive and time-consuming experiments, and you’ll want to consider fewer (but better) ideas. The only way to do that is to invite contributions from the problem solvers that you think will have the best chance of providing good ideas. That is, to opt for a closed mode…” (ibid)
  26. 26. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 26 | P a g e The figure (4) shows the four basic modes of collaboration: a closed and hierarchical network (an elite circle), an open and hierarchical network (an innovation mall), an open and flat network (an innovation community), and a closed and flat network (a consortium). (Source: Pisano and Verganti, 2009) Figure 3; Modes of Collaboration Elite circle: In this mode one company selects the crowd, the screening process is also made by the company and they define the problem and choose the solution. Pisano and Verganti argue that this mode is appropriate when the company know the knowledge domain and can determine from where the best solution to the problem are likely to emerge from. In this mode the chosen experts play a major role and the company needs to have the capabilities to pick them internally. The owners of the ideation do the evaluation and screening process and only they evaluate the proposed ideas. Innovation Mall: In this scenario there is still one company that posts a problem, but here anyone can propose the solution, and the company chooses the best idea. This mode of collaboration enables the company to get ideas from many parties, and the best ideas can come from unexpected sources. Here Pisano and Verganti suggest that the consequences of missing out on a good idea, as in the elite circle, are limited in this scenario due to the self-selection of participant. Thus if the problem is small or narrow it can be broken down into smaller sessions, to resolve it faster. In this mode the evaluation
  27. 27. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 27 | P a g e process is spread over the different parties involved and thereby enables the company to screen the ideas fairly cheaply. Innovation Community: In this mode anybody can propose problems, suggest solution and decide which solutions are best and put into use. This is the most open approach, this mode is properly most appropriate when the company needs ideas from many different parties. The company can’t own the intellectual property underlying the solutions, and needs to take this into consideration these collaboration modes are therefor often seen in open source software projects e.g. Linux or Apache. Consortium: The authors suggest that this collaboration mode is like a private club, where participants jointly select the problem and co-create the chosen solution and decide together how to conduct the further assessment of the winning ideas. This mode is appropriate when the company, like in the Elite circle, knows the knowledge domain and knows where the best solutions are most likely to emerge. Once again the importance of having the right experts is a key factor in this mode and the company needs to have the capabilities to pick them; however the experts need to have “share power” over the decision making in the selection of winning ideas. Pisano and Verganti also suggest that all the expertise of all participants is needed in this mode in order to harness the true innovation. In this mode there can be different ways of sharing the intellectual property, e.g. a co-owned patent or royalties to the owners of the winning ideas. Choosing a collaboration mode involves more than understanding the trade-offs. A company must take into account its strategy for building and capturing value. And as the strategy evolves, the right mode of collaboration might change, too. (ibid)
  28. 28. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 28 | P a g e 3. Company and case description In this chapter I will give a short presentation of the case company; Novozymes and provide an overview of how the company innovate, more specific how Novozymes handle ideas and how the Innovation Department manage it. In the last part of this chapter I will provide a deeper understanding of the chosen idea campaign; “New Claims for Detergent”. That later will be analyzed. 3.1 Description of Novozymes Novozymes is the world leader in Bioinnovation and Biosolutions. Novozymes' core business is industrial enzymes, microorganisms, and biopharmaceutical ingredients. Their goal is to help their customers (such as P&G, Unilever, Nestle, PepsiCo) to achieve more efficient product and process solutions to save energy, raw materials, and reduce waste. The pursued result is higher quality, lower costs, and a better environment. The biological solutions are used in the production of numerous products such as biofuels, detergents, food, and animal feed. (NZ1) Novozymes has over 6000 employees globally, working in Research and Development (R&D), Production, Sales, Marketing, Technical Service and general administration. The company has a portfolio of over 700 products, used in 130 countries. The company is quoted on NASDAQ OMX Copenhagen A/S (NZ2). The company is performing well financially. Over the past 10 Years, during which the company has been operating separately from its sister company Novo Nordisk, Novozymes has achieved an annual sales CAGR of 8% (NZ1). Due to the rapid development within their fields of technology and the company’s ability to innovate, as well as strong secular trends such as sustainability, chemical replacement, and energy security, Novozymes today aims to increase their business by more than 10% a year. On top of this lies the opportunity within cellulosic biofuels. Turning agricultural waste into sugars for the production of biofuels and other chemicals is a very interesting opportunity for Novozymes. However, due to the uncertainties associated with the timing and scope of this opportunity, it is not yet included in their long-term sales growth ambition (The Novozymes Report 2010). In 2012 Novozymes achieved a turnover of 11 billion DKK, and had a net profit of 1,6 billion DKK. (NZ1)
  29. 29. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 29 | P a g e Business areas Novozymes’ business consists of two segments: Enzyme Business and BioBusiness. Enzyme Business is engaged in development, production and distribution of enzymes, this currently accounts for more than 90% of sales, while BioBusiness generates the remaining 10%. Detergent enzymes These enzymes are used in laundry and dishwashing detergents. In the process of washing clothes, certain enzymes break down water-insoluble stains into water-soluble molecules that can be rinsed away by the wash water. Technical enzymes Technical enzymes are used, among other things, in the transformation of starch into different kinds of sugars. This functionality is used in the starch and fuel industries. By 2014 the company expects that the enzymes will make it possible to produce advanced biofuel from certain agricultural residues in large-scale production. Technical enzymes are also used for many other applications, for example leather and textile treatment and forest product industries. Food enzymes Enzymes enhance quality or production efficiency in the production of food products such as bread, wine, juice, beer, noodles, alcohol, and pasta. Figure 4; Novozymes organization
  30. 30. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 30 | P a g e Feed enzymes Adding enzymes to animal feed increases the nutritional value of the feed and improves phosphorus absorption in the animals. This leads to faster growth of the animals and improves the environment as less phosphorus is released via manure. (NZ2) Microorganisms Novozymes’ beneficial microorganisms are used in industrial and municipal wastewater treatment, as well as in the cleaning of surfaces such as carpet, concrete, drain lines, and septic tanks in industrial and household applications. Beneficial microorganisms are also at work in aquaculture and agricultural applications. Biopharmaceutical ingredients Biopharmaceutical ingredients are proteins and other biological substances used in the pharmaceutical industry. The proteins replace proteins from humans and animals that have traditionally been used and have posed the risk of transferring disease. The industrial proteins do not pose this risk and offer further advantages such as cost savings, process performance, consistency, and compliance. (NZ2) 3.2 Innovation in Novozymes Innovation plays an important role for Novozymes as a business. In the industry of biotechnology, it is vital to stay ahead of competition all the time through new innovations, and to protect technologies and business areas’ extensive use of patents (NZ1). Novozymes currently holds over 6000 patents, and is filing about 150 new patents per year (NZ1). In comparison, Novozymes’ largest competitor, the Danish company DANISCO (now acquired by DuPont) holds about 2500 patents and is filing about 50-70 per year. This is why Novozymes can call themselves the world leader of bio-innovation. Novozymes puts a lot of focus on R&D. In 2010, 14 % of turnover was invested in their research and development department, which is located at 8 different sites around the world and employs 800 researchers. Within this department a great amount of attention is directed at promoting collaboration across geographical boarders, and the sharing of knowledge through both face-to-face contact and databases (NZ1). Innovation by Novozymes typically takes place in close collaboration with their customers. Partnerships play an important role in Novozymes’ business model. While developing a new biological solution, Novozymes works closely with their partner in order to optimize their
  31. 31. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 31 | P a g e technology’s functionality for application in the customers’ products or processes (NZ1). When it comes to commercialization, Novozymes role is generally to deliver the technology, while their partners take it to the market. Because of this, Novozymes is extremely dependent on strong partnerships (NZ1) 3.3 Innovation processes in Novozymes Face-to-face ideation is a common and fairly used tool within the company to brainstorm on new concepts and to come up with new ideas on specific topic. These workshops a usually administered and facilitated by the Innovation Office and has been focusing a lot on technical solution and are mainly exercised in the R&D community. Since R&D are located around the world these face-to-face ideation are heavily costly to arrange and typically scientist are flown in from different destinations, which means the budget goes mostly to travelling expenses. Another tool idea generation tool is the Idea Web (an idea suggestion box on the companies Intranet), which is also administered by the Innovation Office. This idea box is open to all members of R&D and Business Development. The Idea Web is open 24/7 all year around. The Innovation Office is responsible for screening and forwards the posted ideas to an expert within the field. If the idea is good the idea will be taking into further assessment in R&D. However the screening process is not optimal and can often lead to very little feedback to the idea submitter. On the positive side it can be argued that the Idea Web is good place to showcase your idea to senior experts, especially if the submitter is new in Novozymes or perhaps located far away from Head Quarters in Denmark. For maturing ideas and concepts, is the initiative called RIC (Radical Innovation Catalyst) which goal is to mature and initiate good ideas coming out i.e. Ideations and turn them into projects. The RIC community is built on volunteer allocations, to make sure that employees are choosing the projects they really believe in. The Innovation Office is responsible to gather the ideas and run a website where employees can read about the new projects and decide if they would like to get involved. With a need for more and faster acceleration of innovation processes and a more customer-centric approach, demanded from Senior Management, the Online Ideation tool is set out to be the right process to fulfill the wanted goal of new projects delivered faster to customer. The Innovation Office is thereby on a journey to test out internal crowdsourcing as the right method to achieve this goal. The R&D Management initiated this strategy in late 2011, and has now slow but steady grown into a
  32. 32. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 32 | P a g e concept, that today is a well-known tool for idea management in all of Novozymes. Since 2011 Novozymes has performed 17 online ideation campaigns, most of them with a technology and product innovation focus, thus drawing heavily on R&D crowds. The parameters of success for internal crowdsourcing were analyzed and described by Lauto et al (2013). Diversity, absorptive capacity and a culture permissive to innovation were the most important ones. 3.4 Case: New Claims for Detergent Enzymes The overall goal of the online Ideation; “New Claims for Detergent“ was to identify new ideas that could boost the growing area and core business of enzymes for detergents and solutions that could lead to new claims for Novozymes’ customers. In the term of “new claims”, it is meant that customers can use the provided technology as sustainable “green” claim of e.g. washing powder without harsh chemicals or claiming ‘whiter than white, or ‘total stain removal at 45C’ and similar Some of the largest detergent manufactures and marketers are customers at Novozymes (e.g. Procter & Gamble and Unilever) today. In order to keep sales growing to these customers, Novozymes needed to come up with more ideas on creating enzymatic solutions that they can be used to sell consumer products and use “green” claims. By applying an internal online idea generation tool, it became possible to crowd- source ideas from around the organization, in that way the tool combined the classical ideation process with an online community, with selected employees from around the world. The online platform was provided by an external consultancy firm NOSCO2 , who has been offering the online platform to Novozymes for a little over a year at this point. The collaborative online ideation process was designed together with the Innovation Office at Novozymes and consultants from NOSCO. 2 Website: nos.co
  33. 33. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 33 | P a g e 3.4.1 The process of “New Claims for Detergents” The process was divided into different phases to make sure that the ideas would make it through the whole campaign and at the same time to mobilize the crowd in order to get the most out of their creativity. Figure 5; Process of online ideation 3.4.2 Scope and plan The online ideation aimed at identifying problematic stains and possible solutions with focus on Americas and EMEA markets. The division called Household Care, who is responsible for developing the detergent business within Novozymes, was the main sponsor of the campaign. Household Care had just developed a new strategy called “Triple 20”, with the goal of triple the turnover within Household Care by 2020, one of the way of succeeding this was to identify, develop and launch 5 new laundry claim enzymes similar to the very successful Mannaway3 , which sells for close to 250 million DKK a year. Basically the challenge was formulated to find “the next big thing” within the detergent business area. This meant also that this online ideation had a very high priority in Novozymes and participants were allowed to spent time on the online platform. 3 A big blockbuster Novozymes product within detergent - Problem statement - Source / Solve? - Admin Team - Process template, - Communication plan - Timeline - Screen team - Crowd Execute communication plan: - Purpose - Expectations - Process - Timing - Incentives - Feedback - Support Posting & discussing by crowd Screen team 5 ideas /solutions 1 week 1 week 1 week 2 weeks 2 days 1-3 months Assessment of winning ideas
  34. 34. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 34 | P a g e 3.4.3 Mobilization and composition the crowd Assembling and construction of the crowd was steered by the Innovation Office in close collaboration with the Household Care group, and started to handpick the different scientist who was specialized within enzymes for detergent, and the unusual scientist how could possibly come with a creative angle on ideas. The campaign was also the first cross-functional online ideation done in Novozymes. 50% of the crowd was origin in R&D and the other 50% was coming from departments of Marketing, Sales and Technical Service. This was done in order to get a more diverse and a more customer oriented approach to the ideas, and not only conceive ideas heavily focused on technological propositions. 3.4.4 The online ideation phase The online phase was planned to run for 2 weeks and the 105 invited participants was able to submit an unlimited amount of ideas and comments. The online ideation was kicked off with a conference call where the participants were briefed by Nosco’s consultant and the scope was clarified and questions from the crowd would be answered. The participants were given profile with name and picture on the platform delivered from Nosco, the profile was typical profile as seen on social media. The platforms had a few features, where participants could follow, share, vote, and comment on ideas. The platform was designed to give a simple overview of the idea flow and showcase which ideas were most popular at the given moment. When posting an idea the crowd was kindly asked to write the idea with a short description and attach documents and other relevant items. The participants was presented by a short summary of what the screen team was looking for in an “good” idea and what types of criteria an idea needed to contain and address in order to succeed in the evaluation process. These were the criteria set up by the screen team;  A stain which is problematic for many consumers  Future stains based on market trends within food compositions  An enzyme which there is reason to believe will be able to remove the problematic stain(s)  Completely new idea for an enzyme  An enzyme solution with high technical probability
  35. 35. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 35 | P a g e In order to get the crowd motivated and get started on posting good ideas, the Innovation office and screen team announced that they would nominate the most novel idea and the author(s) would then be awarded with prizes. The winner would also be appraised as an innovator within Novozymes. In order get ideas flowing fast, was the most active person also awarded, the person with the best arguments for choice of a given stain (to develop an enzyme to remove) and the best team/department (most active and best argues) would also be awarded. This should generate internal competition and help the idea flow, since it is critical to get the first few ideas posted on the platform. 3.4.5 Screening and selection of ideas The phase after the idea generation had ended the phase of screening and selection of the winning ideas started. The online ideation had generated 74 ideas, and had over 200 comments from the 105 participants. Furthermore the crowd had been voting on the ideas, they believe the most in. The screen team was now set out to identify the ideas that had the most potential and which ones should go into further assessment in R&D. The screen team was a diverse group with senior managers and directors from R&D, Marketing and Business Development. Title Department Tenure with Novozymes Tenure with NZ Detergents Senior Director Innovation Office 15 years none Senior Manager Detergent Marketing 12 years 5 Senior Manager Business Development 7 years 7 Dept. Manager Detergent R&D 10 years 10 Senior Manger Technical Service 8 years none The point is to show the diversity of the screen team, its high level of knowledge as expressed by tenure but also to illustrate that none of these people had direct decision or resource power in detergents as such their findings to Management in Detergents were on a pure recommendation for discussion and decision basis.
  36. 36. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 36 | P a g e The screening process was conducted over 2 days where the team reviewed all of the ideas and gave them ratings in the different criteria’s chosen for this campaign. Each of the screen team members need to score the idea within 6 overall criteria from a score of 1-5, where 5 was the highest score. Following meetings was held where the screen team would present their scores and discuss which ideas they liked the most. The first three criteria’s was related to the commercial/market needs in the idea, and the last three criteria were related to technical probability. The screen team did extended background check on the idea both with internal and external databases, and could only score the ideas high if there were found written evidence that the idea could be realized. (For a closer look at the specific criteria please see Appendix 1) Once the screen team had previewed all of the ideas and scored them, the top 5 ideas was picked and presented to the crowd as the winning ideas. The ideas would then go into further assessment and matured for development in R&D. The description above of “New claims for detergent” has provided an overview of the process and designs the idea campaign. The following chapter will present the methodological approach to the research in this thesis.
  37. 37. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 37 | P a g e 4. Methodology In the pursuit to answer the research questions that have been proposed in this thesis, the research is set in the perspective of social constructivism in order to address the exploratory and explanatory findings and thereby put it in an abductive 4 design to seek evidence and conclusions. Since this thesis is a single case study of an online ideation within Novozymes, the investigation and research have been focusing around a number of data sources, mainly quantitative data have been collected and analyzed, but also qualitative data have been collected to reach a point of in-depth and understanding in the process around the investigated online ideation. In the following section, it will be explained how the different data sources have been collected and made it possible to create a foundation for the research approach and develop new knowledge regarding internal crowdsourcing as a tool for creating new ideas. 4.1 Research approach and design In line with the structure described above the method applied in this case study will approach the conduction of the case study method proposed by Yin (1994). According to Yin (1994) a “case study is an empirical inquiry that - Investigates a contemporary phenomenon within its real-life context, especially when - The boundaries between phenomenon and context are not clearly evident” (Yin, 1994; 13). Further the “case study inquiry: - Copes with the technically distinctive situation in which there will be many more variables of interest than data points, and as one result relies on multiple sources of evidence, with data needing to converge in a triangulating fashion, and as another result. 4 Abduction is a form of logical inference that goes from observation to a hypothesis that accounts for the reliable data (observation) and seeks to explain relevant evidence.
  38. 38. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 38 | P a g e - Benefits from the prior development of theoretical propositions to guide data collection and analysis.” (ibid.). The analysis includes internal sources from Novozymes, in order to come up with a conclusion followed by managerial recommendations. The case study approach fulfills the characteristics above and the empirical data does as well since it is chosen to base the analysis on both qualitative and quantitative data, which is recognized as evidence in this approach (Yin, 1994). There are certain areas where the case study deviates from the method proposed by Yin (1994). The data is conducting on an embedded single case study due to the fact that it is analyzed as a subunit that contributes to Novozymes overall innovation strategy; e.g. the industry trends, competitors, core competencies and different resources has not been analyzed due to the scope of the thesis. Analyzing an embedded unit as an online ideation require that the analysis of the embedded unit contribute to the “major interest of the study”, which the analysis does by going in-depth with internal factors to get a broader picture of how Novozymes internal resources could be used in a future approach of crowdsourcing exercises (Yin, 1994; 120). 4.1.1 Data collection The gathering of information and data has been extensive. As explained above, the exploratory approach of the research has led to a process where the data has been collected from different sources, and continually been revisited and made it possible to get new insight. Since the online ideation was held in October 2012, and the data for this thesis have been collected in April/May 2013, it has been important to read through all the ideas and do semi-constructed interviews with members of the screen team and some face-to-face meetings, in order to get a understanding of what the organizational conditions was at the time for the campaign and to understand how the screen team evaluated and researched the ideas submitted. This has enabled the study to retrieve both qualitative and quantitative date, which has led to an in- depth understanding of the research inquiry. The method for collecting the data, has been through exported excel spreadsheets from the Nosco platform, secondly the screen team evaluation documents has been collected and analyzed, questions and clarifying of the documents has been asked to the
  39. 39. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 39 | P a g e screen team, this has been done through semi-constructed interviews. The last data source has been the employee database at Novozymes, in order to get the job titles and departments of the participants of the online ideation and thereby classify and label them to the ideas they were involved in. The analysis in this thesis are mainly focused around the quantitative data collection; although it is held that without the qualitative data collection, the development of hypotheses and the subsequent development of discussions and conclusions could not have been completed. The specific data collections – qualitative and quantitative – will be presented in the following sections. 4.1.2 Qualitative data As presented in the Chapter 3 – Company and Case description the qualitative data collection is primarily conducted in explanatory manner to get an understanding of what happened in the idea campaign. This made it possible to get a deeper understanding of what the process ideation was and to figure out the reflections behind the “New claims for detergents” was, here were a number of qualitative collections applied. This included observations of the full idea campaign process, thoroughly read-through of all the ideas and exploratory interviews with some of the screen team members. A transcript of the specific arguments of the ideas from the screen team, has also been collected, to identify what kind of background research the screen team had conducted when scoring the ideas from there different parameters. The deliberations and assumptions in this thesis were built on a method of triangulation drawing on (i) theory, (ii) qualitative and (iii) quantitative data. “Triangulation refers to the use of different data collection techniques within one study in Order to ensure that the data are telling you what you think they are telling you.” (Saunders et al, 2007:139). The qualitative data collections are therefore important in the methodological considerations although the quantitative data are the dominant in this thesis’ analysis.
  40. 40. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 40 | P a g e 4.1.3 Quantitative data The quantitative data is the dominating part of the analysis in this thesis. The data has been collected from multiple sources. The exported data from the idea platform, delivered by Nosco has mainly been the primarily source of data. The export options in Nosco’ platform was either a PDF file or an Excel spreadsheet, the PDF file is a full extracts of all the ideas posted in the campaign, whereas the Excel Spreadsheet contained the following information; (i) ideas ID; (ii) number of comments; (iii) number of crowd votes and thereby the crowd score; and (iv) submitters name. However, these data points doesn’t completely fulfill the wanted data to answer the developed hypotheses, it was important to create even more data point in order to provide the regression models to identify if there were any correlations and statistical evidence. The following variables were thereby developed; (v) functional involvement in the idea; (vi) idea depth; (vii) comments depth; (viii) market needs articulated in idea; (ix) cross-functional involvement. The functional involvement in an idea (v) includes the functions or department that commented or submitted a specific idea, divided into Sales, Marketing, Technical Service and R&D. The idea depth (vii) and comments depth (viii) was measured from calculating the characters written in the ideas, in order to see if the ideas with many words were rated higher than the ones with short descriptions. The market needs articulation was measured out from a reading through the ideas, this variable was score from a scale of 1-3, 3 being the highest in terms of market needs articulation, this meant that the ideas was classified to see if the crowd was responsive to the market. The cross-functional (ix) variable was measured out from a binomial setting, if more than one department was involved in the idea, the idea was scored with the number of 1, and if only one department was involved it was scored with a 0. . The second source of data was collected from the screen team, who had ranked all the 74 ideas after the online ideation had ended. It was thereby possible to use the screen team spreadsheets to develop further variables; (STi5 ) screen team total idea score; (STii) novelty of idea; (STiii) commercial probability; and (STiv) technical probability. All of these multiple collections of quantitative data enabled the analyses in this thesis. The statistical measurements of data involve calculations of means 5 ST= Screen Team
  41. 41. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 41 | P a g e and standard deviations. Furthermore, it will be presented as contingency tables of various variables to test for statistical significance using simple regression models tested in the software program called STATA6 . The dependent and independent variables will examined in the analysis, and will be explained in the following sections. 4.1.3.1 Dependent variables The regression models provided in the analysis contains two different dependent variables; the regression models have been calculated with the same independent variables in order to see if there was any significant evidence and relations between the two dependent variables. The first dependent variable is the final screen team score; this variable is set as the dependent variable to identify how the screen team interpreted the ideas. The - screen team score is therefor set up to be the indicator for how the ideas performed throughout the online ideation. The second dependent variable was the - crowd score, this variable is set up to be an indicator for how the crowd interpreted the ideas and makes is possible to identify the “wisdom of the crowd”. The crowd rated the ideas from 1-5 stars, this shows clearly which ideas the crowd believed the most in. The indicator in the statistical analyses is therefore the screen team score and the crowd score. The mission of the indicator, as described by De Solla Price (1978), is to find the simplest pattern in the data at hand, and then look for more complex patterns, which modify the first. The more complex patterns in the dataset are thus the correlation between the crowd and the screen team, and will enable to identify if the “wisdom of the crowd” is present in this ideation. The independent variables will be explained in the following section. 6 http://www.stata.com/
  42. 42. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 42 | P a g e 4.1.3.2 Independent variables In the regression models provided, the independent variables are based on the different department’s performance in the online ideation and on which type of ideas posted, in terms of novelty and market articulation. In order to answer the developed hypotheses and to investigate if there are any correlations between the crowd choices and the screen team choices on the quality of ideas. The chosen independent variables were: (i) New idea to Novozymes; (ii) market articulation; (iii) cross-functional involvement; and (iv) origin of ideas (Divided of the departments, Marketing, Sales, Technical Service and R&D). (i) The New idea to Novozymes variable refers to how new ideas posted in the ideation are correlated to the depended variables, this variable is discovered from analyzing the ideas and is put into a binary score of 1 or 0, when it was ranked as a new ideas. (ii) The market articulation variable refers to how strong the market or customer needs are articulated in the ideas. This variable is used to get a perspective of how the market is interpreted in the online ideation, and will be used as a parameter to figure out how the clear the market is represented. The variable is created by an read through of the all the ideas, and is score every time a sign of market is articulated inside the idea or in the discussion affiliated to the idea. (iii) The cross-functional variable refers to the combinations of participant involved in the ideas. This is measured by looking at how and from which departments the ideas and its comments are represented from. The variable is also made as a binary, whereas 1 if there are more than one department involved in the idea, and 0 if it is only one department posting and discussing the idea. This variable is used to give a perspective on how collaborative the crowd was, and how the different departments interacted in developing new concepts and to see if they could understand their different professional languages. (iv) The origin of ideas variable is created to track where the ideas are coming from, this variable is developed by tracking from which department the idea submitter is, and thereby figure out from where the ideas origin from. The four departments are divided into there each own variable to be able to run regression model on them. This variable is used to figure out how the Crowd and Screen Team looks at ideas coming from the different eras of Novozymes, and to test if the strength of quality in the departments in there submission of ideas in the campaign. To test the hypotheses these variables are put in to the analyses to gain the insights on how the different conditions had any relevance in developing, evaluation and choosing the winning top-5 ideas.
  43. 43. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 43 | P a g e 4.2 Two-fold analysis of crowd versus screen team Since the analysis is created by qualitative and quantitative data, the following analysis will be two- folded. By two-folded it is meant that the data received from the screen team is generated in a descripted way and gives a clear insight on how the ideas were evaluated together with the semi- constructed interviews. The screen team, spreadsheet has also provided a deep insight to what the 5 members were focusing on, and gives a clear perspective of what the more in-depth knowledge has provided in the final evaluation. The quantitative data has been retrieved and modeled in a way that gives insight on how the crowd and the screen team acted purely based on data during the ideation. The regression models provided in the analysis are thereby made only to give a perspective of how the different ideas were conceived and how they were generated and evaluated. The analysis will therefore be based on the different types of information, and in order to answer the research question, the final conclusion will be based on some of the assumptions made on top of the findings from the two-fold investigation of data. The way the analysis is created is based on the relevant findings from the data and later put into discussion to give a more accurate answer on how Novozymes can use crowdsourcing in their pursuit of customer-centric innovation. The two-folded approach, enables the thesis to get a more realistic outcome, and makes it possible to generate some more executable managerial recommendations. However, a single case thesis will also have its limitations; the following section will explain the different limitations will come into play, and argue why this thesis not can be used as a general objective case study.
  44. 44. Christian Brix Tillegreen MSc. Management of Innovation & Business Development Copenhagen Business School Confidential 2013 44 | P a g e 4.3 Limitations Conducting a single case study requires that it is a critical case, extreme or unique case, or a revelatory case in order to be able to generalize from (Yin, 1994; 39). The case study does not test directly any specific theory, nor is it an extreme or unique case and the type of case has not been inaccessible to prior studies. This means that the analysis cannot be used for any generalization or base precedence for other biotech companies with the same challenges. The analysis, conclusion and recommendations are aimed at Novozymes’ specific strategy and the output of this case study is only valid when used by Novozymes. However in light of the strategic managerial recommendations it is in some sense, possible to apply to other similar companies if the internal setup is ready and mature for online idea generation. The single case study has it limitation especially when it comes to objectivity and generalization conclusions. A huge limitation, when investigating an internal crowdsourcing exercise, focused on the market needs, is of cause that there have been no external parties involved at all. It would have been a lot easier to answer the research question, if a customer or a partner had been involved in the online ideation. The empirical data consists of both qualitative and quantitative data however the dominant use of quantitative data in the analyses has its implications. The quantitative data is used to simplify the answer to the research question. The Analysis is arguably limited by the use of quantitative data in that it fails to capture the complex nature of the situation. The case for quantitative data analyses is, however, that it reduces the interpretative and subjective elements in the research inquiry. Through the use of quantitative data, it is possible to support the found assumptions by testing of hypotheses to a greater extent than with qualitative data. The information available in the data set has inevitably guided the research. That is to say, the limitations of data have resulted in the chosen variables; other variables could have been examined had different data been available. The four chosen independent variables, however, are consistent with the suggestions from theory presented in the Literature Review and it is therefore believed that they are important diversity dimensions in relation to the scope of this thesis.

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