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Deploying information technologies for organizational innovation: Lessons from case studies
International Journal of Information Management 31 (2011) 183–188
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International Journal of Information Management journal homepage: www.elsevier.com/locate/ijinfomgt
Case study
Deploying information technologies for organizational innovation: Lessons from case studies Jaka Lindiˇc a , Peter Baloh b , Vincent M. Ribière c , Kevin C. Desouza d,∗ a
Faculty of Economics, University of Ljubljana, Kardeljeva ploˇscˇ ad 17, 1000 Ljubljana, Slovenia BISOL, d.o.o., Latkova vas 59A, 3312 Prebold, Slovenia c The Institute for Knowledge and Innovation (IKI-SEA), Bangkok University, Thailand d The Information School, University of Washington, 330D Mary Gates Hall, Box 352840, Seattle, WA 98195, USA b
a r t i c l e
i n f o
Article history: Received 6 December 2010 Accepted 10 December 2010 Available online 15 January 2011 Keywords: Information technologies Innovation Case study Innovation process
a b s t r a c t Organizations must innovate if they are to survive in today’s fiercely competitive marketplace. In this paper, we explore how leading organizations are using emerging technologies to enable novel forms of ideation that can radically increase the sheer volume of ideas they explore. In addition, we outline how organizations use technologies to cost effectively manage this increased volume of ideas by optimizing generation, mobilization, advocacy and screening, experimentation, commercialization, and even the diffusion and implementation of ideas. Critical to this is the management of knowledge during the innovation process. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Organizations must innovate if they are to survive and compete (Chesbrough, 2003; Desouza et al., 2009; Drucker, 1986; Porter, 1990). The ability to innovate, and do so smartly (i.e. effectively and efficiently), is a critical competency that firms have yet to master (Jaruzelski & Dehoff, 2010; Pohle & Chapman, 2006). Consider the case of Google who until recently was a poster child for the most innovative organization. Recently, Google has also fallen on bad times in terms of their ability to innovate successfully. Google labs is a genius way to test innovative ideas and prototypes before their release despite its use, Google’s recent products have not fared well in the marketplace, for e.g. Wave, Buzz, etc. (Cain, 2010; Lakhani, 2010; Pogue, 2010). So if even the most innovative companies fail, there is still a lot to be learned in term of mastering the innovation process. The success of an organization’s ability to innovate is directly linked to their ability to leverage ideas and to manage knowledge, within and across, its midst. Desouza et al. (2009) outline a process for innovation based on a study of over 30 global organizations that traces the evolution of ideas from generation and mobilization, to how they are advocated and screened for, and then how are they experimented with, following this commercialization, diffusion and their implementation in the marketplace. Ideas are
∗ Corresponding author. Tel.: +1 206 616 0880. E-mail addresses: [email protected] (V.M. Ribière), [email protected] (K.C. Desouza). 0268-4012/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2010.12.004
information elements. Ideas are represented as information elements either in textual, aural, or visual formats. Ideas are generated and shared through explicit artifacts (e.g. documents) or tacitly (e.g. through demonstrations). The advocacy and screening of ideas are also information laden – information is shared about the idea and debated leading up to decisions. Moreover, when we experiment with ideas we are gathering, analyzing, and synthesizing data about an idea so as to refine it (or abandon it). If an idea makes it through the experimentation process we can begin the commercialization process, and then diffuse and implement the idea in the marketplace as a product or service. During each of these stages, again, we see the criticality of being able to manage information and knowledge. Consider what might happen if an organization were not able to manage information and knowledge during the implementation and diffusion of a new product/service. Most recently, another poster child of innovation, Apple, faced this very challenge when launching the iPhone 4. During the diffusion and implementation of the product in the marketplace, customers realized that the phone would drop calls due to an issue with the antenna. Apple made one of the rare mistakes in their PR activities as Steve Jobs suggested that users just use cases or avoid holding the phone in a particular way (Sample, 2010). Although Apple is using its brand power to move the fiasco to their benefit by even improving sales of accessories that could help displace this problem (Satariano, 2010), it is clear that this hurts both their sales and image as this issue further delayed the white iPhone 4 launch for antenna redesign (Tofel, 2010). Today, organizations are infusing a wide array of information technologies into their innovation processes (Awazu et al., 2009; Noel, 2009). Information technologies offer great promise for the
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Table 1 Ideation types. Domain
Inside domain (concrete ideas) Outside domain (abstract ideas such as concepts, and models)
Activity Reactive follower
Proactive challenger
I. Inner follower Follow experts, media and organizations from domain II. Outer follower Follow generic topics and authors focus on innovation
III. Inner challenger Challenges inside the domain Swarovski, Shell IV. Outer challenger Challenges outside the domain Netflix, Procter and Gamble
optimal management of ideas and the enablement of new forms of ideation and idea management. Companies like Starbucks, Cisco, Dell and IBM already rely on these new ideation types. For example, Web 2.0 technologies open up opportunities for users and companies to create more content online, to share this more easily with others on Twitter, Facebook, blogs etc. Technologies like semantic search and social intelligence can help companies to spot trends and identify and analyze job-to-be done. NetBases technology for example discovered that long-distance bikers and other endurance athletes purposely drink Coke that had gone flat – giving them the caffeine and sugar to boost stamina but none of the carbonation, which lead to cramps (Flinn, 2010). However, technology is no panacea, and needs to be managed appropriately for business value realization. Opening up innovation process to new mechanisms for ideation based on technologies can lead to a new set of problems. As Cisco discovered “the evaluation process was far more labor-intensive than we’d anticipated; significant investments of time, energy, patience, and imagination are required to discern the gems hidden within rough stones. Anyone attempting to do innovation on the cheap should look elsewhere” (Jouret, 2009). British Petroleum (BP) also used crowd sourcing to get ideas to find Deepwater Horizon Oil Spill Solutions. More than 35,000 suggestions were collected by BP and more suggestions are submitted every day! (Evans, 2010). At this stage, it is not clear how BP used and leveraged all these ideas, but through various articles on the Web we could feel a sense of frustration of the people and companies which contributed ideas regarding the slow or lack of responsiveness. Due to the level of emergency, and the inability for BP to handle in a short manner such a large amount of ideas, numerous organizations and groups created their own way to collect ideas and to test and to implement them on their own (IBM, 2010). As for Cisco, too many ideas can be overwhelming and mechanisms need to be developed to rapidly identify the ideas with the most potentials. As Stata, chairman of Analog Devices puts “The limits of innovation. . . have nothing to do with creativity and nothing to do with technology. They have everything to do with management capability”(Govindarajan & Trimble, 2010). The annual Boston Consulting Group survey on innovation revealed that the top 3 main obstacles of innovation were; Risk adverse culture, Lengthy development time and Difficulty selecting the right ideas to commercialize (Andrew, Manget, Michael, Taylor, & Zablit, 2010). “Speed and discipline are companies’ greatest challenges” The bottom-line being that technology needs to be deployed smartly to enable for selecting and leveraging ideas within the organization. A global CIO survey conducted by Capgemini (2008) focusing on the role of the IT function in business innovation reinforced the need for CIO to take an active role in the business innovation process, even though their role at the time was not perceived as being key. The fast emergence of the use of Web 2.0 technologies to support the innovation process (Ribière & Tuggle, 2010) will allow CIOs to play an important role in providing the right IT infrastructure that will enable efficient and agile innovation processes. In this casestudy paper, we explore how emerging technologies are enabling leading organizations to manage ideas as they move from conceptualization, to commercialization, and finally implementation and
diffusion in the marketplace. The goal of the paper is to outline the potential of information technologies for organizational innovation agendas. The case studies we present below are based on both primary and secondary data collection. Primary data collection included interviews, observations, and even consulting with organizations on infusing technologies into the innovation process. We also conducted an exhaustive search of the business practitioner literature to find examples of technology deployments for innovation. We then, followed up, when possible, to get further information on the details of their technology deployment for innovation.
2. Ideation across the innovation process Ideas can come from different sources both inside and outside the company. IBM (2006), in their Global CEO study revealed that for the companies surveyed (765) the top 3 most significant source of business ideas came from employees (42%) followed by business partners (36%) and by customers (35%). While a lot is already known about idea sources inside a company, sources outside the company are less researched. Ideas coming out of these sources are still frequently seen as strike of luck rather than systematic management. But as one of the most known examples of “accidental” innovation – the Penicillin case – the discovery was not a result of a pure luck. Although Fleming did not actively search for antibiotics, the connections still had to be made – he needed knowledge to transform an accident to an idea that he stumbled upon (Ho, 1999). Distinct idea sources result in different ideation types that lead to distinct ideation types and demand different approaches to management of these ideas throughout the innovation process (Table 1). Approaches to ideas generation can be distinguished using two dimensions (domain and activity). The first dimension, Activity, distinguishes among two types of research activity: reactive follower and proactive challenger. The domain dimensiontries to exploit the existing paths of knowledge transfer and use this as an idea source. It does not mean that it is not innovative, but crucial thing is to identify the right innovations when you see it. This type is reactive. The latter – proactive challenger – is proactively asking for development of new innovations. These challenges can be very narrowly defined or put broadly with least defined boundaries. Usually companies use time limits when they create challenges. The domain dimension distinguishes ideas inside from those outside the domain company is currently dealing with. Usually companies have deep knowledge and understanding about the domain in which they operate but they only have broad overview of knowledge outside their knowledge domain. Based on these two dimensions four distinctive ideation types are formed: inner follower, outer follower, inner challenger and outer challenger. Outer follower: companies can learn from other companies even if they are unrelated to their industry. Google and P&G even go so far to swap employees to gain from one another (Byron, 2008). Mr. Garing, CIO and director of strategic planning for the Defense Information Systems Agency visits companies such as Salesforce.com, Google, UPS, FedEx, CitiGroup, Travelocity, Amazon.com to get ideas (Worthen, 2008). But although this approach can be very insightful it is also very resource consuming, rarely pos-
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sible on that level as in described case and one only hopes to find interesting results. Companies can follow databases such as moreinspiration.com that offer databases of innovations. Users can add ideas, vote on ideas, and see related ideas. They can subscribe to get new innovations by e-mail, using RSS feeds or use tools such as Google alerts to follow the most important topics. They can decide to follow people, companies or keywords related to innovations in general. About 19% of all tweets contain links, but usually the Twitter stream moves too quickly to register all the information (Zarela, 2009). Tools such as MicroPlaza uses social filtering to filter out the things that are most relevant for the user. Its filter includes data about what is being tweeted and retweeted but also if it is tweeted by the people you follow. MicroPlaza also enables you to assume the identity of any other Twitter user so you can see what selected individuals follow on twitter. In this way web 2.0 can help companies spot signals quicker as signals can be pushed to the user without his active search. Siemens is experimenting with TweetDeck where you can create interest groups, list of interesting people to follow, but also more efficiently follow topics in real-time with saved searches. The big film studios missed the potential of toy licensing for a long time until Star Wars. With today’s concepts in hand they could learn from Walt Disney Company. Mickey Mouse’s popularity in the 1930s resulted in an explosion of toys, books, and consumer products. None of them were manufactured by the Walt Disney Company. But even in 1977 movies still weren’t considered candidates for a successful toy license (Sansweet, 1999). Another example is Avelle.com which might have found an idea from Netflix. Avelle.com uses similar business model as Netflix (subscription based rental service), but acts in a completely different industry – high fashion industry. Just by following ideas from your industry, Avelle would have missed the opportunity to create, what Kim and Mauborgne call Blue Ocean. Inner follower uses the same approaches as outer follower but focuses more narrowly to subjects related to his domain, e.g. they could follow scientific progress with pushed information about key news, researchers, conferences, journals or keywords related from their domain. The Hospital for Sick Children began using SocialText platform to help clinicians learn; share; and work more effectively together in helping children with impairment in day-to-day functioning due to emotional; behavioral; psychological; psychiatric; or substance use problems. There are now more than 400 experts in the group; with 25% of them actively participating during any given week. These experts can easily track the updates made by the people whom interest them which ensures that knowledge is shared with those who need it; leading to the best possible service to the children in need (SickKids, 2010). Several companies are already using challenges to get ideas from crowds – these crowds can be part their domain or outside it. Inner challenger puts challenge inside the domain where he usually searches for a solution to a very particular problem. For example Swarovski used Design a watch challenge (http://www.enlightened-watch-design-contest.com/) that was directly targeted to a community tightly related to the industry (mostly designers). Participants could use a watch configuration tool or upload a freely created design. Using the former they could design a watch using 24 components and 108 different Swarovski gemstones. 1300 configured designs were submitted. Additionally 700 freely created designs were submitted. In a follow-up contest users could design jewelry. 3000 designs were submitted (Bilgram, Fuller, & Rieder, 2009). In a similar way Shell uses BrightIdeas and GameChanger to search for innovation that could transform the energy industry. At Starbuck’s My Starbucks Idea even managers use the system that was initially intended for its community. For example, user named “store manager at 8955” suggested an idea about saving receipt tape and customer time. Wal-Mart conducted a blogging exercise among their employees on energy conservation.
Diffusion and Implementation
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Generation and Mobilization
Advocacyand screening
Commercialization
Experimentation Fig. 1. The innovation process (based on Desouza et al. (2009)).
They received more than 6000 posts with ideas, and saved millions in energy costs as a result. One employee posted advice to take the unneeded light bulbs out of the drink machines in store stockrooms. As a result, their savings by taking that one light bulb out of the machines was $1 million aggregated across all their locations (McKendrick, 2010). On the other hand, Outer challenger does not limit himself to only members of his domain. P&G, Boeing, and Eli Lilly and Company co-created YourEncore a technical service provider that helps companies accelerate innovation by connecting them with retired scientists and engineers to leverage their expertise. YourEncore Network currently consists of approximately 5000 Experts that have retired from or have prior experience at over 800 companies, universities or other organizations. Any retired and highly experienced individual can enrol in The YourEncore Network and different tools are used to match Expert skills to assignments at the Member Companies is open to enrolment by retired and highly experienced individuals. Given the above classification of ideation, we now explore the major components of the innovation process. We employ the Desouza et al. (2009) process model to this end (see Fig. 1). The first stage of the innovation process – idea generation and mobilization is concerned with the creation of new ideas and the transfer of existing ideas from one domain to the next. The next stage, idea advocacy and screening, involves the garnering organizational support for ideas, making the business case for ideas, and putting ideas through a rigorous screening process. Once we have a short-list of ideas for the organization to pursue, the next stage is to experiment with the idea. Here, the focus is on testing and refining the idea for market introduction. Following this, ideas are put through the stage of commercialization, where in they are moved into the market with the help of adequate pricing, promotion, and packaging. The final stage of the innovation process is the diffusion and implementation of the idea. Here, the focus is on ensuring that the idea reaches its intended audiences, is consumed, and generates value. Moreover, this stage is also vital for the identification of new ideas and concepts that can feed back into the process of idea generation and mobilization. Different ideation types can influence approaches used in all stages of the innovation process. Using reactive follower types for example company can identify potential new partners for experimentation and commercialization phase. While proactive
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challenger types not only enable this but also integrate partners in the innovation process itself. As they participate in the development of the idea it is easier to get good advocacy on the idea and buy-in in the diffusion and implementation phase.
uses the prediction markets to assess the strength of relationships between different teams.
3. Information technologies and innovation
Companies also need buy-in and acceptance for an innovation. As Google Wave examples showed it is not enough for the company to create a product that has a good potential to be life changing for numerous clients, if they cannot clearly communicate and diffuse innovation to any of them. After Google announced they stopped Google Wave as a product a new web site savegooglewave.com surfaced. Google Wave fans started posted their visions on how Wave could help them including ideas about company brainstorming sessions, supporting research work, teacher-student collaboration.
3.1. Generation and mobilization of ideas When it comes to the generation of ideas, an important consideration is how we capture knowledge from sources. These sources can be customers, business partners, an even the firm’s own employees. Consider the case of Swarovski, who used Design a watch challenge (http://www.enlightened-watch-designcontest.com/) that was directly targeted to a community tightly related to the industry (mostly designers). Participants could use a watch configuration tool or upload a freely created design. Using the tool they could design a watch using 24 components and 108 different Swarovski gemstones. 1300 configured designs were submitted. Additionally 700 freely created designs were submitted. In a follow-up contest users could design jewelry. 3000 designs were submitted. Through this exercise Swarovski was able to capture knowledge from customers and external knowledge communities which are vital sources for ideas of innovation. In addition, to simply capturing the knowledge in the form of requirements and specifications, Swarovski was able to go a step further and use technologies to get the knowledge represented in a form that was readily usable for innovation (i.e. in the form of actual watch designs). 3.2. Advocacy and screening Once a company overcomes the idea generation spasm, the issue becomes how to evaluate the ideas generated to decide which ideas will be acted upon. Assessing feasibility and creating technical and commercial superiority are the purpose of this stage. For example Starbucks uses a combination of idea submission/voting system to innovate their products and processes; in example, there have been over 32 ideas and thousands of votes for offering some kind of reward system for customer visits. 3.3. Experimentation Ideas that passed through the screening process move to experimentation and prototype-building. Even if a prototype exists from previous phase, the idea’s applicability to a specific problem, context or production chain must be tested. Netflix uses outside experts to solve their problems. Netflix Prize seeks to substantially improve the accuracy of predictions about how much someone is going to love a movie based on their movie preferences. The prize is 1 million $. Even people from AT&T, and Yahoo! Research work on this challenge. By following concepts and ideas from different industries you can gather insights which could lead to breakthrough innovation. 3.4. Commercialization The key to successful innovation process is not only selecting the right ideas through the screening process but also advocating the ideas that are most promising. Motorola’s employees can submit ideas to ThinkTank. Every idea that gets at least 5 votes are eligible to compete in the prediction market. Winners are judged based on their stock performance, and participants who hold stock in winning ideas get a bonus (Burnham, 2009). Google uses internal prediction markets since April 2005, and runs about 25–30 prediction markets per quarter. Google uses them to forecasts product demand, for internal performance (e.g. will new product releases be on time), and external business environment factors. Google also
3.5. Diffusion and implementation
4. The role of managing knowledge during the innovation process As the various case studies presented in this paper demonstrated, the innovation process is getting more and more open, allowing stakeholders and the crowd to be involved in various phases of the process. Effectively selecting the “right” idea remains a challenge, particularly when the number of ideas becomes overwhelming. Taking a “wining” idea up to the implementation phase requires strong collaboration among the various teams involved as well as proper information and knowledge management. We could think of an idea as a piece of data that evolves/grows/matures all along the innovation process by gaining some more context, feedback, experimentation (information) until it becomes a prototype (knowledge artifact) and finally a product or service or new process or business model. The snow ball effect could be used as an analogy. A snow ball (idea) will grow while rolling down the hillside (innovation process). Some balls might break before they reach the destination and some might reach the bottom of the hill being big and strong and some might make it being big but fragile and might crash (maybe because they arrived too fast (for example, iPhone 4))! Managing knowledge all along the process can help the ball to go down the hill in a much secure/safer way, strengthening the cohesion of the snow particles on the ball so it does not fall apart before reaching the bottom of the hill or at the arrival (market release). The tacit aspect of the knowledge associated with an idea makes it difficult to fully manage it. For instance, capturing/unveiling the hidden requirements or expectations of a customer is a difficult task since very often customers do not exactly know what they want. Experimentation and simulation then become important tools of the process where users can play and discover what will work best for them. The main question remains: how can the knowledge gained through such practical and cognitive activities as well as through the other phases of the innovation processes be captured, structured and organized to fully represent the value, potential and risks associated with an idea? Currently, when possible, portfolio of ideas are used to mitigate such risks but if a better management of internal and external knowledge was performed all along the innovation process we believe that it could strengthen and fasten the innovation process. Technology can play an important role to support and enable the management of knowledge all along the innovation process, particularly when the number of ideas get overwhelming “idea overload”. 5. Implications The technologies today, especially design tools and user toolkits (von Hippel, 2001) are helping us go beyond capturing knowledge in raw form, but actually capture knowledge in a readily usable
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form such as in design prototypes. One implication that we can draw from this is the fact that we need to go beyond just capturing knowledge for knowledge sake, but look at options on how do we employ technologies to capture knowledge in readily usable formats. Technologies available also enable wider participation using different ideation types. This participation can result in better screening process, ideas can be refined, analyzed, evolved more thoroughly. By including people outside the core domain, feasibility can be screened from different perspectives. This approach can also improve advocacy for the ideas that should move to the following innovation process phases, as there are more people involved and embrace the idea as their own. By making tools and data available to outside entities companies can attract more knowledge outside the company. To do this it can use both proactive challenger types depending on the knowledge required to make the initial idea more robust and ready for the next phase. Using prediction markets companies can reduce the risk involving the commercialization of an innovation as they include more people in the evaluation of idea’s potential. The more radical the idea is the harder it is to clearly define its value proposition and to get the buy-in. By involving different stakeholders (users, partners, employees, suppliers, etc.) in the innovation process it is easier to define how to both clearly define and communicate the value to potential buyers. 6. Conclusion Through a series of mini-case studies, we have analyzed the role that technologies can play in various aspects of the innovation process. Our paper lays the groundwork for several avenues for future research. Firstly, research is needed that explores how we might better engage users in the design of creative technologies to solve local innovation challenges. Most of the technologies that we studied were driven by the organization, and then used by individuals. A great potential exists, especially as users increase their efficacy with technology to engage them in the design of digital solutions for innovation (Clark, 2007). Second, research is needed to systematically evaluate the costs and benefits of technologies as they pertain to innovation. During our research, we found limited empirical research on the business-value of technology for innovation. We have a lot of anecdotal evidence, and individual case studies, in the literature, these while valuable, do not help us assess the true impacts of the technologies on the organizational innovation agenda. Third, research is needed on the actual design process, especially how are emergent technical solutions, to address challenges with managing ideas within the organization. Much of the literature is still focused on studying planned approaches to innovation. In reality, organizations, and the individuals within them, have to contend with a highly emergent and chaotic innovation landscape (Cunha & Gomes, 2003). Research is desperately needed on how technologies are used on the fly, and are designed and implemented as problems and opportunities arise. References Andrew, J. P., Manget, J., Michael, D. C., Taylor, A., & Zablit, H. (2010). Innovation 2010: A return to Prominence – and the emergence of a new world order. Boston, MA, USA: Boston Consulting Group. Awazu, Y., Baloh, P., Desouza, K. C., Wecht, C. H., Kim, J. Y., & Jha, S. (2009). Information-communication technologies open up innovation. ResearchTechnology Management, 52(1), 51–58. Bilgram, V., Fuller, J., & Rieder, B. (2009). How to be successful in CoCreation Research. http://www.slideshare.net/HYVE/how-to-be-successful-incocreation-research
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Order and disorder in product innovation models. Creativity and Innovation Management, 12(3), 174–187. Desouza, K. C., Dombrowski, C., Awazu, Y., Baloh, P., Sangareddy, S. R. P., Jha, S., & Kim, J. Y. (2009). Crafting Organizational Innovation Processes. Innovation: Management, Policy & Practice, 11(1), 6–33. Drucker, P. F. (1986). Innovation and entrepreneurship: practice and principles. New York: Simon and Schuster. Evans, M. J. (2010). Oil Spill Suggestions for Plugging Deepwater Horizon Leak Are Pouring. http://bpoilnews.com/oil-spill-suggestions/xprize-foundation-mayaward-10-million-prize-for-oil-spill-solution/ Flinn, R. (2010). Wanted: Social Media Sifters. http://www.businessweek. com/magazine/content/10 44/b4201020317862.htm Govindarajan, V., & Trimble, C. (2010). The other side of Innovation: solving the execution challenge. Harvard Business Press. Ho, D. (1999). Bacteriologist Alexander Fleming. 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Apple’s White iPhone Delay a Chance for Antenna Redesign. http://www.businessweek.com/technology/content/jul2010/ tc20100723 838305.htm. von Hippel, E. (2001). PERSPECTIVE: User toolkits for innovation. The Journal of Product Innovation Management, 18(4), 247–257. Worthen, B. (2008). Creative Cooperation. WSJ,. http://online.wsj. com/article/SB122227470431471451.html Zarela, D. (2009). The Linguistics of ReTweets. http://danzarrella.com/retweetlinguistics.html# Jaka Lindiˇc works at the Faculty of Economics, University of Ljubljana, Slovenia. He holds an EFMD award winning Ph.D. in innovations. He also founded and manages the largest European network of parenting portals. In addition, he acts as member of the board and consultant to several Slovene high-tech companies. Peter Baloh is a member of the executive board at BISOL – innovative and rapidly growing photovoltaic module producer and solar power plant solution provider. He also holds an assistant professor position at University of Ljubljana, Slovenia. Additionally, he has founded and managed a niche consultancy firm Catch the Knowledge. Vincent M. Ribière, after teaching for 10 years in the United States, first at American University (Washington, DC) and later on at the New York Institute of Technology (NYIT) in New York and in the Kingdom of Bahrain, he joined Bangkok University in 2007 as the Managing Director and co-founder of the Institute for Knowledge and Innovation – Southeast Asia (IKI-SEA). Vincent received his Doctorate of Science in
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Knowledge Management from the George Washington University, and a Ph.D. in Management Sciences from the Paul Cézanne University, in Aix en Province, France. Vincent teaches, conducts research and consults in the area of knowledge management, innovation management and information systems He is a KM columnist for CIO World & Business magazine (Thailand) and he is part of the editorial board of the International Journal of Knowledge Management (IJKM) and of VINE: The Journal of Information and Knowledge Management Systems. He can be contacted at: [email protected]
Kevin C. Desouza is an associate professor at the University of Washington Information School. He holds adjunct appointments in the UW’s College of Engineering and at the Daniel J. Evans School of Public Affairs. He currently serves as the Director of the Institute for Innovation in Information Management (I3M). For more information, please see http://www.kevindesouza.net.
Contents lists available at ScienceDirect
International Journal of Information Management journal homepage: www.elsevier.com/locate/ijinfomgt
Case study
Deploying information technologies for organizational innovation: Lessons from case studies Jaka Lindiˇc a , Peter Baloh b , Vincent M. Ribière c , Kevin C. Desouza d,∗ a
Faculty of Economics, University of Ljubljana, Kardeljeva ploˇscˇ ad 17, 1000 Ljubljana, Slovenia BISOL, d.o.o., Latkova vas 59A, 3312 Prebold, Slovenia c The Institute for Knowledge and Innovation (IKI-SEA), Bangkok University, Thailand d The Information School, University of Washington, 330D Mary Gates Hall, Box 352840, Seattle, WA 98195, USA b
a r t i c l e
i n f o
Article history: Received 6 December 2010 Accepted 10 December 2010 Available online 15 January 2011 Keywords: Information technologies Innovation Case study Innovation process
a b s t r a c t Organizations must innovate if they are to survive in today’s fiercely competitive marketplace. In this paper, we explore how leading organizations are using emerging technologies to enable novel forms of ideation that can radically increase the sheer volume of ideas they explore. In addition, we outline how organizations use technologies to cost effectively manage this increased volume of ideas by optimizing generation, mobilization, advocacy and screening, experimentation, commercialization, and even the diffusion and implementation of ideas. Critical to this is the management of knowledge during the innovation process. © 2010 Elsevier Ltd. All rights reserved.
1. Introduction Organizations must innovate if they are to survive and compete (Chesbrough, 2003; Desouza et al., 2009; Drucker, 1986; Porter, 1990). The ability to innovate, and do so smartly (i.e. effectively and efficiently), is a critical competency that firms have yet to master (Jaruzelski & Dehoff, 2010; Pohle & Chapman, 2006). Consider the case of Google who until recently was a poster child for the most innovative organization. Recently, Google has also fallen on bad times in terms of their ability to innovate successfully. Google labs is a genius way to test innovative ideas and prototypes before their release despite its use, Google’s recent products have not fared well in the marketplace, for e.g. Wave, Buzz, etc. (Cain, 2010; Lakhani, 2010; Pogue, 2010). So if even the most innovative companies fail, there is still a lot to be learned in term of mastering the innovation process. The success of an organization’s ability to innovate is directly linked to their ability to leverage ideas and to manage knowledge, within and across, its midst. Desouza et al. (2009) outline a process for innovation based on a study of over 30 global organizations that traces the evolution of ideas from generation and mobilization, to how they are advocated and screened for, and then how are they experimented with, following this commercialization, diffusion and their implementation in the marketplace. Ideas are
∗ Corresponding author. Tel.: +1 206 616 0880. E-mail addresses: [email protected] (V.M. Ribière), [email protected] (K.C. Desouza). 0268-4012/$ – see front matter © 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.ijinfomgt.2010.12.004
information elements. Ideas are represented as information elements either in textual, aural, or visual formats. Ideas are generated and shared through explicit artifacts (e.g. documents) or tacitly (e.g. through demonstrations). The advocacy and screening of ideas are also information laden – information is shared about the idea and debated leading up to decisions. Moreover, when we experiment with ideas we are gathering, analyzing, and synthesizing data about an idea so as to refine it (or abandon it). If an idea makes it through the experimentation process we can begin the commercialization process, and then diffuse and implement the idea in the marketplace as a product or service. During each of these stages, again, we see the criticality of being able to manage information and knowledge. Consider what might happen if an organization were not able to manage information and knowledge during the implementation and diffusion of a new product/service. Most recently, another poster child of innovation, Apple, faced this very challenge when launching the iPhone 4. During the diffusion and implementation of the product in the marketplace, customers realized that the phone would drop calls due to an issue with the antenna. Apple made one of the rare mistakes in their PR activities as Steve Jobs suggested that users just use cases or avoid holding the phone in a particular way (Sample, 2010). Although Apple is using its brand power to move the fiasco to their benefit by even improving sales of accessories that could help displace this problem (Satariano, 2010), it is clear that this hurts both their sales and image as this issue further delayed the white iPhone 4 launch for antenna redesign (Tofel, 2010). Today, organizations are infusing a wide array of information technologies into their innovation processes (Awazu et al., 2009; Noel, 2009). Information technologies offer great promise for the
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Table 1 Ideation types. Domain
Inside domain (concrete ideas) Outside domain (abstract ideas such as concepts, and models)
Activity Reactive follower
Proactive challenger
I. Inner follower Follow experts, media and organizations from domain II. Outer follower Follow generic topics and authors focus on innovation
III. Inner challenger Challenges inside the domain Swarovski, Shell IV. Outer challenger Challenges outside the domain Netflix, Procter and Gamble
optimal management of ideas and the enablement of new forms of ideation and idea management. Companies like Starbucks, Cisco, Dell and IBM already rely on these new ideation types. For example, Web 2.0 technologies open up opportunities for users and companies to create more content online, to share this more easily with others on Twitter, Facebook, blogs etc. Technologies like semantic search and social intelligence can help companies to spot trends and identify and analyze job-to-be done. NetBases technology for example discovered that long-distance bikers and other endurance athletes purposely drink Coke that had gone flat – giving them the caffeine and sugar to boost stamina but none of the carbonation, which lead to cramps (Flinn, 2010). However, technology is no panacea, and needs to be managed appropriately for business value realization. Opening up innovation process to new mechanisms for ideation based on technologies can lead to a new set of problems. As Cisco discovered “the evaluation process was far more labor-intensive than we’d anticipated; significant investments of time, energy, patience, and imagination are required to discern the gems hidden within rough stones. Anyone attempting to do innovation on the cheap should look elsewhere” (Jouret, 2009). British Petroleum (BP) also used crowd sourcing to get ideas to find Deepwater Horizon Oil Spill Solutions. More than 35,000 suggestions were collected by BP and more suggestions are submitted every day! (Evans, 2010). At this stage, it is not clear how BP used and leveraged all these ideas, but through various articles on the Web we could feel a sense of frustration of the people and companies which contributed ideas regarding the slow or lack of responsiveness. Due to the level of emergency, and the inability for BP to handle in a short manner such a large amount of ideas, numerous organizations and groups created their own way to collect ideas and to test and to implement them on their own (IBM, 2010). As for Cisco, too many ideas can be overwhelming and mechanisms need to be developed to rapidly identify the ideas with the most potentials. As Stata, chairman of Analog Devices puts “The limits of innovation. . . have nothing to do with creativity and nothing to do with technology. They have everything to do with management capability”(Govindarajan & Trimble, 2010). The annual Boston Consulting Group survey on innovation revealed that the top 3 main obstacles of innovation were; Risk adverse culture, Lengthy development time and Difficulty selecting the right ideas to commercialize (Andrew, Manget, Michael, Taylor, & Zablit, 2010). “Speed and discipline are companies’ greatest challenges” The bottom-line being that technology needs to be deployed smartly to enable for selecting and leveraging ideas within the organization. A global CIO survey conducted by Capgemini (2008) focusing on the role of the IT function in business innovation reinforced the need for CIO to take an active role in the business innovation process, even though their role at the time was not perceived as being key. The fast emergence of the use of Web 2.0 technologies to support the innovation process (Ribière & Tuggle, 2010) will allow CIOs to play an important role in providing the right IT infrastructure that will enable efficient and agile innovation processes. In this casestudy paper, we explore how emerging technologies are enabling leading organizations to manage ideas as they move from conceptualization, to commercialization, and finally implementation and
diffusion in the marketplace. The goal of the paper is to outline the potential of information technologies for organizational innovation agendas. The case studies we present below are based on both primary and secondary data collection. Primary data collection included interviews, observations, and even consulting with organizations on infusing technologies into the innovation process. We also conducted an exhaustive search of the business practitioner literature to find examples of technology deployments for innovation. We then, followed up, when possible, to get further information on the details of their technology deployment for innovation.
2. Ideation across the innovation process Ideas can come from different sources both inside and outside the company. IBM (2006), in their Global CEO study revealed that for the companies surveyed (765) the top 3 most significant source of business ideas came from employees (42%) followed by business partners (36%) and by customers (35%). While a lot is already known about idea sources inside a company, sources outside the company are less researched. Ideas coming out of these sources are still frequently seen as strike of luck rather than systematic management. But as one of the most known examples of “accidental” innovation – the Penicillin case – the discovery was not a result of a pure luck. Although Fleming did not actively search for antibiotics, the connections still had to be made – he needed knowledge to transform an accident to an idea that he stumbled upon (Ho, 1999). Distinct idea sources result in different ideation types that lead to distinct ideation types and demand different approaches to management of these ideas throughout the innovation process (Table 1). Approaches to ideas generation can be distinguished using two dimensions (domain and activity). The first dimension, Activity, distinguishes among two types of research activity: reactive follower and proactive challenger. The domain dimensiontries to exploit the existing paths of knowledge transfer and use this as an idea source. It does not mean that it is not innovative, but crucial thing is to identify the right innovations when you see it. This type is reactive. The latter – proactive challenger – is proactively asking for development of new innovations. These challenges can be very narrowly defined or put broadly with least defined boundaries. Usually companies use time limits when they create challenges. The domain dimension distinguishes ideas inside from those outside the domain company is currently dealing with. Usually companies have deep knowledge and understanding about the domain in which they operate but they only have broad overview of knowledge outside their knowledge domain. Based on these two dimensions four distinctive ideation types are formed: inner follower, outer follower, inner challenger and outer challenger. Outer follower: companies can learn from other companies even if they are unrelated to their industry. Google and P&G even go so far to swap employees to gain from one another (Byron, 2008). Mr. Garing, CIO and director of strategic planning for the Defense Information Systems Agency visits companies such as Salesforce.com, Google, UPS, FedEx, CitiGroup, Travelocity, Amazon.com to get ideas (Worthen, 2008). But although this approach can be very insightful it is also very resource consuming, rarely pos-
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sible on that level as in described case and one only hopes to find interesting results. Companies can follow databases such as moreinspiration.com that offer databases of innovations. Users can add ideas, vote on ideas, and see related ideas. They can subscribe to get new innovations by e-mail, using RSS feeds or use tools such as Google alerts to follow the most important topics. They can decide to follow people, companies or keywords related to innovations in general. About 19% of all tweets contain links, but usually the Twitter stream moves too quickly to register all the information (Zarela, 2009). Tools such as MicroPlaza uses social filtering to filter out the things that are most relevant for the user. Its filter includes data about what is being tweeted and retweeted but also if it is tweeted by the people you follow. MicroPlaza also enables you to assume the identity of any other Twitter user so you can see what selected individuals follow on twitter. In this way web 2.0 can help companies spot signals quicker as signals can be pushed to the user without his active search. Siemens is experimenting with TweetDeck where you can create interest groups, list of interesting people to follow, but also more efficiently follow topics in real-time with saved searches. The big film studios missed the potential of toy licensing for a long time until Star Wars. With today’s concepts in hand they could learn from Walt Disney Company. Mickey Mouse’s popularity in the 1930s resulted in an explosion of toys, books, and consumer products. None of them were manufactured by the Walt Disney Company. But even in 1977 movies still weren’t considered candidates for a successful toy license (Sansweet, 1999). Another example is Avelle.com which might have found an idea from Netflix. Avelle.com uses similar business model as Netflix (subscription based rental service), but acts in a completely different industry – high fashion industry. Just by following ideas from your industry, Avelle would have missed the opportunity to create, what Kim and Mauborgne call Blue Ocean. Inner follower uses the same approaches as outer follower but focuses more narrowly to subjects related to his domain, e.g. they could follow scientific progress with pushed information about key news, researchers, conferences, journals or keywords related from their domain. The Hospital for Sick Children began using SocialText platform to help clinicians learn; share; and work more effectively together in helping children with impairment in day-to-day functioning due to emotional; behavioral; psychological; psychiatric; or substance use problems. There are now more than 400 experts in the group; with 25% of them actively participating during any given week. These experts can easily track the updates made by the people whom interest them which ensures that knowledge is shared with those who need it; leading to the best possible service to the children in need (SickKids, 2010). Several companies are already using challenges to get ideas from crowds – these crowds can be part their domain or outside it. Inner challenger puts challenge inside the domain where he usually searches for a solution to a very particular problem. For example Swarovski used Design a watch challenge (http://www.enlightened-watch-design-contest.com/) that was directly targeted to a community tightly related to the industry (mostly designers). Participants could use a watch configuration tool or upload a freely created design. Using the former they could design a watch using 24 components and 108 different Swarovski gemstones. 1300 configured designs were submitted. Additionally 700 freely created designs were submitted. In a follow-up contest users could design jewelry. 3000 designs were submitted (Bilgram, Fuller, & Rieder, 2009). In a similar way Shell uses BrightIdeas and GameChanger to search for innovation that could transform the energy industry. At Starbuck’s My Starbucks Idea even managers use the system that was initially intended for its community. For example, user named “store manager at 8955” suggested an idea about saving receipt tape and customer time. Wal-Mart conducted a blogging exercise among their employees on energy conservation.
Diffusion and Implementation
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Generation and Mobilization
Advocacyand screening
Commercialization
Experimentation Fig. 1. The innovation process (based on Desouza et al. (2009)).
They received more than 6000 posts with ideas, and saved millions in energy costs as a result. One employee posted advice to take the unneeded light bulbs out of the drink machines in store stockrooms. As a result, their savings by taking that one light bulb out of the machines was $1 million aggregated across all their locations (McKendrick, 2010). On the other hand, Outer challenger does not limit himself to only members of his domain. P&G, Boeing, and Eli Lilly and Company co-created YourEncore a technical service provider that helps companies accelerate innovation by connecting them with retired scientists and engineers to leverage their expertise. YourEncore Network currently consists of approximately 5000 Experts that have retired from or have prior experience at over 800 companies, universities or other organizations. Any retired and highly experienced individual can enrol in The YourEncore Network and different tools are used to match Expert skills to assignments at the Member Companies is open to enrolment by retired and highly experienced individuals. Given the above classification of ideation, we now explore the major components of the innovation process. We employ the Desouza et al. (2009) process model to this end (see Fig. 1). The first stage of the innovation process – idea generation and mobilization is concerned with the creation of new ideas and the transfer of existing ideas from one domain to the next. The next stage, idea advocacy and screening, involves the garnering organizational support for ideas, making the business case for ideas, and putting ideas through a rigorous screening process. Once we have a short-list of ideas for the organization to pursue, the next stage is to experiment with the idea. Here, the focus is on testing and refining the idea for market introduction. Following this, ideas are put through the stage of commercialization, where in they are moved into the market with the help of adequate pricing, promotion, and packaging. The final stage of the innovation process is the diffusion and implementation of the idea. Here, the focus is on ensuring that the idea reaches its intended audiences, is consumed, and generates value. Moreover, this stage is also vital for the identification of new ideas and concepts that can feed back into the process of idea generation and mobilization. Different ideation types can influence approaches used in all stages of the innovation process. Using reactive follower types for example company can identify potential new partners for experimentation and commercialization phase. While proactive
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challenger types not only enable this but also integrate partners in the innovation process itself. As they participate in the development of the idea it is easier to get good advocacy on the idea and buy-in in the diffusion and implementation phase.
uses the prediction markets to assess the strength of relationships between different teams.
3. Information technologies and innovation
Companies also need buy-in and acceptance for an innovation. As Google Wave examples showed it is not enough for the company to create a product that has a good potential to be life changing for numerous clients, if they cannot clearly communicate and diffuse innovation to any of them. After Google announced they stopped Google Wave as a product a new web site savegooglewave.com surfaced. Google Wave fans started posted their visions on how Wave could help them including ideas about company brainstorming sessions, supporting research work, teacher-student collaboration.
3.1. Generation and mobilization of ideas When it comes to the generation of ideas, an important consideration is how we capture knowledge from sources. These sources can be customers, business partners, an even the firm’s own employees. Consider the case of Swarovski, who used Design a watch challenge (http://www.enlightened-watch-designcontest.com/) that was directly targeted to a community tightly related to the industry (mostly designers). Participants could use a watch configuration tool or upload a freely created design. Using the tool they could design a watch using 24 components and 108 different Swarovski gemstones. 1300 configured designs were submitted. Additionally 700 freely created designs were submitted. In a follow-up contest users could design jewelry. 3000 designs were submitted. Through this exercise Swarovski was able to capture knowledge from customers and external knowledge communities which are vital sources for ideas of innovation. In addition, to simply capturing the knowledge in the form of requirements and specifications, Swarovski was able to go a step further and use technologies to get the knowledge represented in a form that was readily usable for innovation (i.e. in the form of actual watch designs). 3.2. Advocacy and screening Once a company overcomes the idea generation spasm, the issue becomes how to evaluate the ideas generated to decide which ideas will be acted upon. Assessing feasibility and creating technical and commercial superiority are the purpose of this stage. For example Starbucks uses a combination of idea submission/voting system to innovate their products and processes; in example, there have been over 32 ideas and thousands of votes for offering some kind of reward system for customer visits. 3.3. Experimentation Ideas that passed through the screening process move to experimentation and prototype-building. Even if a prototype exists from previous phase, the idea’s applicability to a specific problem, context or production chain must be tested. Netflix uses outside experts to solve their problems. Netflix Prize seeks to substantially improve the accuracy of predictions about how much someone is going to love a movie based on their movie preferences. The prize is 1 million $. Even people from AT&T, and Yahoo! Research work on this challenge. By following concepts and ideas from different industries you can gather insights which could lead to breakthrough innovation. 3.4. Commercialization The key to successful innovation process is not only selecting the right ideas through the screening process but also advocating the ideas that are most promising. Motorola’s employees can submit ideas to ThinkTank. Every idea that gets at least 5 votes are eligible to compete in the prediction market. Winners are judged based on their stock performance, and participants who hold stock in winning ideas get a bonus (Burnham, 2009). Google uses internal prediction markets since April 2005, and runs about 25–30 prediction markets per quarter. Google uses them to forecasts product demand, for internal performance (e.g. will new product releases be on time), and external business environment factors. Google also
3.5. Diffusion and implementation
4. The role of managing knowledge during the innovation process As the various case studies presented in this paper demonstrated, the innovation process is getting more and more open, allowing stakeholders and the crowd to be involved in various phases of the process. Effectively selecting the “right” idea remains a challenge, particularly when the number of ideas becomes overwhelming. Taking a “wining” idea up to the implementation phase requires strong collaboration among the various teams involved as well as proper information and knowledge management. We could think of an idea as a piece of data that evolves/grows/matures all along the innovation process by gaining some more context, feedback, experimentation (information) until it becomes a prototype (knowledge artifact) and finally a product or service or new process or business model. The snow ball effect could be used as an analogy. A snow ball (idea) will grow while rolling down the hillside (innovation process). Some balls might break before they reach the destination and some might reach the bottom of the hill being big and strong and some might make it being big but fragile and might crash (maybe because they arrived too fast (for example, iPhone 4))! Managing knowledge all along the process can help the ball to go down the hill in a much secure/safer way, strengthening the cohesion of the snow particles on the ball so it does not fall apart before reaching the bottom of the hill or at the arrival (market release). The tacit aspect of the knowledge associated with an idea makes it difficult to fully manage it. For instance, capturing/unveiling the hidden requirements or expectations of a customer is a difficult task since very often customers do not exactly know what they want. Experimentation and simulation then become important tools of the process where users can play and discover what will work best for them. The main question remains: how can the knowledge gained through such practical and cognitive activities as well as through the other phases of the innovation processes be captured, structured and organized to fully represent the value, potential and risks associated with an idea? Currently, when possible, portfolio of ideas are used to mitigate such risks but if a better management of internal and external knowledge was performed all along the innovation process we believe that it could strengthen and fasten the innovation process. Technology can play an important role to support and enable the management of knowledge all along the innovation process, particularly when the number of ideas get overwhelming “idea overload”. 5. Implications The technologies today, especially design tools and user toolkits (von Hippel, 2001) are helping us go beyond capturing knowledge in raw form, but actually capture knowledge in a readily usable
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form such as in design prototypes. One implication that we can draw from this is the fact that we need to go beyond just capturing knowledge for knowledge sake, but look at options on how do we employ technologies to capture knowledge in readily usable formats. Technologies available also enable wider participation using different ideation types. This participation can result in better screening process, ideas can be refined, analyzed, evolved more thoroughly. By including people outside the core domain, feasibility can be screened from different perspectives. This approach can also improve advocacy for the ideas that should move to the following innovation process phases, as there are more people involved and embrace the idea as their own. By making tools and data available to outside entities companies can attract more knowledge outside the company. To do this it can use both proactive challenger types depending on the knowledge required to make the initial idea more robust and ready for the next phase. Using prediction markets companies can reduce the risk involving the commercialization of an innovation as they include more people in the evaluation of idea’s potential. The more radical the idea is the harder it is to clearly define its value proposition and to get the buy-in. By involving different stakeholders (users, partners, employees, suppliers, etc.) in the innovation process it is easier to define how to both clearly define and communicate the value to potential buyers. 6. Conclusion Through a series of mini-case studies, we have analyzed the role that technologies can play in various aspects of the innovation process. Our paper lays the groundwork for several avenues for future research. Firstly, research is needed that explores how we might better engage users in the design of creative technologies to solve local innovation challenges. Most of the technologies that we studied were driven by the organization, and then used by individuals. A great potential exists, especially as users increase their efficacy with technology to engage them in the design of digital solutions for innovation (Clark, 2007). Second, research is needed to systematically evaluate the costs and benefits of technologies as they pertain to innovation. During our research, we found limited empirical research on the business-value of technology for innovation. We have a lot of anecdotal evidence, and individual case studies, in the literature, these while valuable, do not help us assess the true impacts of the technologies on the organizational innovation agenda. Third, research is needed on the actual design process, especially how are emergent technical solutions, to address challenges with managing ideas within the organization. Much of the literature is still focused on studying planned approaches to innovation. In reality, organizations, and the individuals within them, have to contend with a highly emergent and chaotic innovation landscape (Cunha & Gomes, 2003). Research is desperately needed on how technologies are used on the fly, and are designed and implemented as problems and opportunities arise. References Andrew, J. P., Manget, J., Michael, D. C., Taylor, A., & Zablit, H. (2010). Innovation 2010: A return to Prominence – and the emergence of a new world order. Boston, MA, USA: Boston Consulting Group. Awazu, Y., Baloh, P., Desouza, K. C., Wecht, C. H., Kim, J. Y., & Jha, S. (2009). Information-communication technologies open up innovation. ResearchTechnology Management, 52(1), 51–58. Bilgram, V., Fuller, J., & Rieder, B. (2009). How to be successful in CoCreation Research. http://www.slideshare.net/HYVE/how-to-be-successful-incocreation-research
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Apple’s White iPhone Delay a Chance for Antenna Redesign. http://www.businessweek.com/technology/content/jul2010/ tc20100723 838305.htm. von Hippel, E. (2001). PERSPECTIVE: User toolkits for innovation. The Journal of Product Innovation Management, 18(4), 247–257. Worthen, B. (2008). Creative Cooperation. WSJ,. http://online.wsj. com/article/SB122227470431471451.html Zarela, D. (2009). The Linguistics of ReTweets. http://danzarrella.com/retweetlinguistics.html# Jaka Lindiˇc works at the Faculty of Economics, University of Ljubljana, Slovenia. He holds an EFMD award winning Ph.D. in innovations. He also founded and manages the largest European network of parenting portals. In addition, he acts as member of the board and consultant to several Slovene high-tech companies. Peter Baloh is a member of the executive board at BISOL – innovative and rapidly growing photovoltaic module producer and solar power plant solution provider. He also holds an assistant professor position at University of Ljubljana, Slovenia. Additionally, he has founded and managed a niche consultancy firm Catch the Knowledge. Vincent M. Ribière, after teaching for 10 years in the United States, first at American University (Washington, DC) and later on at the New York Institute of Technology (NYIT) in New York and in the Kingdom of Bahrain, he joined Bangkok University in 2007 as the Managing Director and co-founder of the Institute for Knowledge and Innovation – Southeast Asia (IKI-SEA). Vincent received his Doctorate of Science in
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Knowledge Management from the George Washington University, and a Ph.D. in Management Sciences from the Paul Cézanne University, in Aix en Province, France. Vincent teaches, conducts research and consults in the area of knowledge management, innovation management and information systems He is a KM columnist for CIO World & Business magazine (Thailand) and he is part of the editorial board of the International Journal of Knowledge Management (IJKM) and of VINE: The Journal of Information and Knowledge Management Systems. He can be contacted at: [email protected]
Kevin C. Desouza is an associate professor at the University of Washington Information School. He holds adjunct appointments in the UW’s College of Engineering and at the Daniel J. Evans School of Public Affairs. He currently serves as the Director of the Institute for Innovation in Information Management (I3M). For more information, please see http://www.kevindesouza.net.