Crowdsourcing & Open Innovation

This supplementary case follows up on an innovative R&D approach by Beiersdorf,a skin care and cosmetics company. The case relates what happened to the product launched by Beiersdorf, to its Nivea line, following the events of the A case, and how the commercial success of the product informed thinking by leaders in R&D for the future.

This case follows Rodrigo Nino, founder and CEO of commercial real estate development company Prodigy Network, as he develops an equity-based crowdfunding model for small investors to access commercial real estate in Colombia, then tries out the model in the U.S. U.S. regulations, starting with the Securities Act of 1933, effectively barred sponsors from soliciting small investors for large commercial real estate. However, the JOBS Act of 2013 loosened U.S. restrictions on equity crowdfunding. Nino believes that crowdfunding will democratize real estate development by providing a new asset class for small investors, revolutionizing the industry. The case also follows Nino's development of an online platform to crowdsource design for his crowdfunded buildings, maximizing shared value throughout the development process. Nino faces many challenges as he attempts to crowdfund an extended stay hotel in Manhattan, New York. For example, crowdfunded real estate faces resistance from industry leaders, especially in regards to the concern of fraud, and SEC regulations on crowdfunding remain undetermined at the time of the case.

From the late 1990s to 2006/2007, Samsung Electronics moved from one of 170 TV manufacturers to gain dominant TV market share year over year from 2007-2013. As digital technologies increasingly converged in 2013-2014, the industry faced new questions: What was the future of TV? The case considers Samsung Electronics TV Group's product development processes, as the company's mobile and TV offerings increasingly converged and consumer demands and behavior pushed the historically clear boundaries of product, content, engagement and interaction.

Victors & Spoils (V&S), located in Boulder, Colorado, was the first advertising agency built on open innovation and crowdsourcing principles from the ground-up. V&S was co-founded in 2009 by John Winsor, Claudia Batten and Evan Fry, all former members of the advertising agency Crispin Porter + Bogusky (CP+B). V&S crowdsourced creative ideas for its ad campaigns through Agency Machine, its proprietary online platform. CEO John Winsor wanted to change the way that advertising was done, a difficult task in an industry entrenched in traditional models. The case follows Winsor as he prepares to scale his business and must determine the best way to do so. He has an offer from Havas, a leading global advertising company interested in acquiring V&S, which would give V&S access to unprecedented resources. However, Winsor and the V&S team have concerns about how their innovative processes may be affected by partnering with a large, traditional company.

This teaching plan provides an 80 minute class plan for the case Victors & Spoils: "Born Open".

Victors & Spoils (V&S), located in Boulder, Colorado, was the first advertising agency built on open innovation and crowdsourcing principles from the ground-up. V&S was co-founded in 2009 by John Winsor, Claudia Batten and Evan Fry, all former members of the advertising agency Crispin Porter + Bogusky (CP+B). V&S crowdsourced creative ideas for its ad campaigns through Agency Machine, its proprietary online platform. CEO John Winsor wanted to change the way that advertising was done, a difficult task in an industry entrenched in traditional models. The case follows Winsor as he prepares to scale his business and must determine the best way to do so. He has an offer from Havas, a leading global advertising company interested in acquiring V&S, which would give V&S access to unprecedented resources. However, Winsor and the V&S team have concerns about how their innovative processes may be affected by partnering with a large, traditional company.

The “self-organizing” of online crowds — or workers, more generally — into teams is a non-trivial problem of coordination and matching, in a context in which other parties are simultaneously competing for partners. Here, we experimentally investigate the capacity for workers in online crowds to self-organize into teams, within a scientific crowdsourcing contest. We compare matching outcomes and performance to those in a comparison group in which we eliminate the coordination and matching problem altogether (by directly assigning individuals to Pareto efficient teams). Online crowd members do remarkably well relative to the benchmark achieving 13% more functioning teams. Teams also tended to be more effective, by several measures. (We found no evidence these levels depending on the size of the self-organizing pool of workers.) Conditional on having formed, the self-organizing teams also benefit from several advantages in performance.

This chapter contrasts traditional, organization- centered models of innovation with more recent work on open innovation. These fundamentally different and inconsistent innovation logics are associated with contrasting organizational boundaries and organizational designs. We suggest that when critical tasks can be modularized and when problem- solving knowledge is widely distributed and available, open innovation complements traditional innovation logics. We induce these ideas from the literature and with extended examples from Apple, the National Aeronautics and Astronomical Agency (NASA) and LEGO. We suggest that task decomposition and problem- solving knowledge distribution are not deterministic but are strategic choices. If dynamic capabilities are associated with innovation streams, and if different innovation types are rooted in contrasting innovation logics, there are important implications for firm boundaries, design and identity.

As innovation becomes more democratic, many of the best ideas for new products and services no longer originate in well-financed corporate and government laboratories. Instead, they come from almost anywhere and anyone.¹ How can companies tap into this distributed knowledge and these diverse skills? Increasingly, organizations are considering using an open-innovation process, but many are finding that making open innovation work can be more complicated than it looks. PepsiCo, the food and beverage giant, for example, created controversy in 2011 when an open-sourced entry into its Super Bowl ad contest that was posted online featured Doritos tortilla chips being used in place of sacramental wafers during Holy Communion. Similarly, Kraft Foods Australia ran into challenges when it launched a new Vegemite-based cheese snack in conjunction with a public naming contest. The name Kraft initially chose from the submissions, iSnack 2.0, encountered widespread ridicule, and Kraft abandoned it. (The company instead asked consumers to choose among six other names. The company ultimately picked the most popular choice among those six, Vegemite Cheesybite.) Reports of such problems have fed uncertainty among managers about how and when to open their innovation processes. Managers tell us that they need a means of categorizing different types of open innovation and a list of key success factors and common problems for each type. Over the last decade, we have worked to create such a guide by studying and researching the emergence of open-innovation systems in numerous sectors of the economy, by working closely with many organizations that have launched open-innovation programs and by running our own experiments.² This research has allowed us to gain a unique perspective on the opportunities and problems of implementing open-innovation programs. (See “About the Research.”) In every organization and industry, executives were faced with the same decisions. Specifically, they had to determine (1) whether to open the idea-generation process; (2) whether to open the idea-selection process; or (3) whether to open both. These choices led to a number of managerial challenges, and the practices the companies implemented were a major factor in whether the innovation efforts succeeded or failed.

From Apple to Merck to Wikipedia, more and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious. It seems risky and even unnatural to push problems out to vast groups of strangers distributed around the world, particularly for companies built on a history of internal innovation. How can intellectual property be protected? How can a crowdsourced solution be integrated into corporate operations? What about the costs? These concerns are all reasonable, the authors write, but excluding crowdsourcing from the corporate innovation tool kit means losing an opportunity. After a decade of study, they have identified when crowds tend to outperform internal organizations (or not). They outline four ways to tap into crowd-powered problem solving — contests, collaborative communities, complementors, and labor markets — and offer a system for picking the best one in a given situation. Contests, for example, are suited to highly challenging technical, analytical, and scientific problems; design problems; and creative or aesthetic projects. They are akin to running a series of independent experiments that generate multiple solutions—and if those solutions cluster at some extreme, a company can gain insight into where a problem’s “technical frontier” lies. (Internal R&D may generate far less information.)

This chapter reports on an actual field experiment that tests for the influence of “sorting” on innovator effort. The focus is on the potential heterogeneity among innovators and whether they prefer a more cooperative versus competitive research environment. The focus of the field experiment is a real-world multiday software coding exercise in which participants are able to express a preference for being sorted into a cooperative or competitive environment—that is, incentives in the cooperative environment are team based, while those in the competitive environment are individualized and depend on relative performance. Half of the participants are indeed sorted on the basis of their preferences, while the other half are assigned to the two modes on a random basis.

Following its 2011 win of the Broad Prize, the most prestigious award available for urban school districts, Charlotte-Mecklenburg Schools must hire a new superintendent. This case examines the context of a large urban public school district and how its Board of Education and superintendent were able to create an environment that successfully fostered innovation, using a variety of tools including policy, structure, tools, and culture. It explores the particular constraints and barriers of public education and how the district leadership navigated them. Covers issues such as the resistance to innovation in the public sector, the importance of leadership in building a culture of innovation, the use of autonomy and accountability to encourage individual creativity, the difficulty of managing multiple stakeholders, and the challenge of sustaining improvements over changes in leadership.

In this paper, I study the effect of adding large numbers of producers of application software programs (“apps”) to leading handheld computer platforms, from 1999 to 2004. To isolate causal effects, I exploit changes in the software labor market. Consistent with past theory, I find a tight link between the number of producers on platform and the number of software varieties that were generated. The patterns indicate the link is closely related to the diversity and distinct specializations of producers. Also highlighting the role of heterogeneity and nonrandom entry and sorting, later cohorts generated less compelling software than earlier cohorts. Adding producers to a platform also shaped investment incentives in ways that were consistent with a tension between network effects and competitive crowding, alternately increasing or decreasing innovation incentives depending on whether apps were differentiated or close substitutes. The crowding of similar apps dominated in this case; the average effect of adding producers on innovation incentives was negative. Overall, adding large numbers of producers led innovation to become more dependent on population-level diversity, variation, and experimentation —while drawing less on the heroic efforts of any one individual innovator.

The case describes OpenIDEO, an online offshoot of IDEO, one of the world's leading product design firms. OpenIDEO leverages IDEO's innovative design process and an online community to create solutions for social issues. Emphasis is placed on comparing the IDEO and OpenIDEO processes using real-world project examples. For IDEO this includes the redesign of Air New Zealand's long haul flights. For OpenIDEO this includes increasing bone marrow donor registrations and improving personal sanitation in Ghana. In addition, the importance of fostering a collaborative online environment is explored.

Contests are a historically important and increasingly popular mechanism for encouraging innovation. A central concern in designing innovation contests is how many competitors to admit. Using a unique data set of 9,661 software contests, we provide evidence of two coexisting and opposing forces that operate when the number of competitors increases. Greater rivalry reduces the incentives of all competitors in a contest to exert effort and make investments. At the same time, adding competitors increases the likelihood that at least one competitor will find an extreme-value solution. We show that the effort-reducing effect of greater rivalry dominates for less uncertain problems, whereas the effect on the extreme value prevails for more uncertain problems. Adding competitors thus systematically increases overall contest performance for high-uncertainty problems. We also find that higher uncertainty reduces the negative effect of added competitors on incentives. Thus, uncertainty and the nature of the problem should be explicitly considered in the design of innovation tournaments. We explore the implications of our findings for the theory and practice of innovation contests.

InnoCentive.com enables clients to tap into internal and external solver networks to address various business issues. This case focuses on the outcome of InnoCentive's decision to post challenges related to environmental issues created by the Gulf Oil Spill. It reviews lessons learned from this experience and asks students to consider whether InnoCentive should post challenges in response to the nuclear crises resulting from the 2011 Japanese earthquake and tsunami.

Innovation requires sources of novelty, but the challenge is that not all sources lead to innovation, so its value needs to be determined. However, since ways of determining value stem from existing knowledge, this often creates barriers to innovation. To understand how people address the challenge of novelty, we develop a conceptual and an empirical framework to explain how this challenge is addressed in a software and scientific context. What is shown is that the process of innovation is a cycle where actors develop a novel course of action and, based on the consequences identified, confirm what knowledge is necessary to transform and develop the next course of action. The performance of the process of innovation is constrained by the capacities of the artifacts and the ability of the actors to create and use artifacts to drive this cycle. By focusing on the challenge of novelty, a problem that cuts across all contexts of innovation, our goal is to develop a more generalized account of what drives the process of innovation.

Teaching Note for HBS Case 610-074.

This case presents the Myelin Repair Foundation's accelerated research collaboration model for drug discovery. It highlights the challenges of building a multi-disciplinary and multi-institutional research collaboration that is attempting to create a treatment for multiple sclerosis based on a novel scientific approach. The case provides details on how norms of academic research and intellectual property had to be updated to enable collaboration. The current dilemma facing the CEO and COO of the foundation relates to setting strategic priorities for research so that a treatment for MS can be ready in the next ten years. The strategic choices need to account for the complexities of drug discovery, the uncertainty of commercial partners' interest in the therapeutic approach and the constrained donor-based fundraising environment.

Teaching Note for HBS Case 610-032.

TopCoder's crowdsourcing-based business model, in which software is developed through online tournaments, is presented. The case highlights how TopCoder has created a unique two-sided innovation platform consisting of a global community of over 225,000 developers who compete to write software modules for its over 40 clients. Provides details of a unique innovation platform where complex software is developed through ongoing online competitions. By outlining the company's evolution, the challenges of building a community and refining a web-based competition platform are illustrated. Experiences and perspectives from TopCoder community members and clients help show what it means to work from within or in cooperation with an online community. In the case, the use of distributed innovation and its potential merits as a corporate problem solving mechanism is discussed. Issues related to TopCoder's scalability, profitability, and growth are also explored.

Metrology plays a key role in the manufacture of mechanical components. Traditionally it is used extensively in a pre-process stage where a manufacturer does process planning, design, and ramp-up, and in post-process off-line inspection to establish proof of quality. The area that is seeing a lot of growth is the in-process stage of volume manufacturing, where feedback control can help ensure that parts are made to specification. The Industrial Metrology Group at Carl Zeiss AG had its traditional strength in high precision coordinate measuring machines, a universal measuring tool that had been widely used since its introduction in the mid-1970s. The market faced a complex diversification of competition as metrology manufacturers introduced new sensor and measurement technologies, and as some of their customers moved towards a different style of measurement mandating speed and integration with production systems. The case discusses the threat of new in-line metrology systems to the core business as well as the arising new opportunities.

We examine who the winners are in science problem-solving contests characterized by open broadcast of problem information, self-selection of external solvers to discrete problems from the laboratories of large R&D intensive companies, and blind review of solution submissions. We find that technical and social marginality, being a source of different perspectives and heuristics, plays an important role in explaining individual success in problem solving. The provision of a winning solution was positively related to increasing distance between the solver's field of technical expertise and the focal field of the problem. Female solvers—known to be in the "outer circle" of the scientific establishment—performed significantly better than men in developing successful solutions. Our findings contribute to the emerging literature on open and distributed innovation by demonstrating the value of openness, at least narrowly defined by disclosing problems, in removing barriers to entry to non-obvious individuals. We also contribute to the knowledge-based theory of the firm by showing the effectiveness of a market mechanism to draw out knowledge from diverse external sources to solve internal problems.