Crowdsourcing & Open Innovation

Most of society's innovation systems – academic science, the patent system, open source, etc. – are “open” in the sense that they are designed to facilitate knowledge disclosure among innovators. An essential difference across innovation systems is whether disclosure is of intermediate progress and solutions or of completed innovations. We theorize and present experimental evidence linking intermediate versus final disclosure to an ‘incentives-versus-reuse’ tradeoff and to a transformation of the innovation search process. We find intermediate disclosure has the advantage of efficiently steering development towards improving existing solution approaches, but also has the effect of limiting experimentation and narrowing technological search. We discuss the comparative advantages of intermediate versus final disclosure policies in fostering innovation.

Tomohiro Ishibashi (Bashi), chief executive officer for B to S, and Julia Foote LeStage, chief innovation officer of Weathernews Inc., were addressing a panel at the HBS Digital Summit on creative uses of big data. They told the summit attendees about how the Sakura (cherry blossoms) Project, where the company asked users in Japan to report about how cherry blossoms were blooming near them day by day, had opened up opportunities for the company's consumer business in Japan. The project ultimately garnered positive publicity and became a foothold to building the company's crowdsourcing weather-forecasting service in Japan. It changed the face of weather forecasting in Japan. Bashi and LeStage wondered whether the experience could be applied to the U.S. market.

Traditionally, human ingenuity has been considered the main source of innovation. However, recent research and the development of new products by firms as diverse as P&G, Speedo and Nike has shown that nature can provide inspiration for new innovative products. The San Diego Zoo, which has established a Center for Bioinspiration, defines bioinspiration as a methodology in which biological systems, processes, and elements are studied to draw analogies that can be applied to human design challenges in a sustainable manner.

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.

We report results of a natural field experiment conducted at a medical organization that sought contribution of public goods (i.e., projects for organizational improvement) from its 1200 employees. Offering a prize for winning submissions boosted participation by 85 percent without affecting the quality of the submissions. The effect was consistent across gender and job type. We posit that the allure of a prize, in combination with mission-oriented preferences, drove participation. Using a simple model, we estimate that these preferences explain about a third of the magnitude of the effect. We also find that these results were sensitive to the solicited person’s gender.

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.

Tournaments are widely used in the economy to organize production and innovation. We study individual data on 2775 contestants in 755 software algorithm development contests with random assignment. The performance response to added contestants varies nonmonotonically across contestants of different abilities, precisely conforming to theoretical predictions. Most participants respond negatively, whereas the highest-skilled contestants respond positively. In counterfactual simulations, we interpret a number of tournament design policies (number of competitors, prize allocation and structure, number of divisions, open entry) and assess their effectiveness in shaping optimal tournament outcomes for a designer.

InnoCentive.com, a firm connecting R&D labs of large organizations to diverse external solvers through innovation contests, has to decide if it will enable collaboration in its community. Case covers the basics of a distributed innovation system works and the advantages of having external R&D. Links how concepts of open source are applied to a non-software setting. Describes the rationale for participation by solvers in innovation contests and the benefits that accrue to firms. Raises the issue if a community can be shifted to collaboration when competition was the basis of prior interaction.

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.

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.)

BACKGROUND: The association of differing genotypes with disease-related phenotypic traits offers great potential to both help identify new therapeutic targets and support stratification of patients who would gain the greatest benefit from specific drug classes. Development of low-cost genotyping and sequencing has made collecting large-scale genotyping data routine in population and therapeutic intervention studies. In addition, a range of new technologies is being used to capture numerous new and complex phenotypic descriptors. As a result, genotype and phenotype datasets have grown exponentially. Genome-wide association studies associate genotypes and phenotypes using methods such as logistic regression. As existing tools for association analysis limit the efficiency by which value can be extracted from increasing volumes of data, there is a pressing need for new software tools that can accelerate association analyses on large genotype-phenotype datasets.

RESULTS: Using open innovation (OI) and contest-based crowdsourcing, the logistic regression analysis in a leading, community-standard genetics software package (PLINK 1.07) was substantially accelerated. OI allowed us to do this in <6 months by providing rapid access to highly skilled programmers with specialized, difficult-to-find skill sets. Through a crowd-based contest a combination of computational, numeric, and algorithmic approaches was identified that accelerated the logistic regression in PLINK 1.07 by 18- to 45-fold. Combining contest-derived logistic regression code with coarse-grained parallelization, multithreading, and associated changes to data initialization code further developed through distributed innovation, we achieved an end-to-end speedup of 591-fold for a data set size of 6678 subjects by 645 863 variants, compared to PLINK 1.07's logistic regression. This represents a reduction in run time from 4.8 hours to 29 seconds. Accelerated logistic regression code developed in this project has been incorporated into the PLINK2 project.

CONCLUSIONS: Using iterative competition-based OI, we have developed a new, faster implementation of logistic regression for genome-wide association studies analysis. We present lessons learned and recommendations on running a successful OI process for bioinformatics.

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.

This paper discusses several challenges in designing field experiments to better understand how organizational and institutional design shapes innovation outcomes and the production of knowledge. We proceed to describe the field experimental research program carried out by our Crowd Innovation Laboratory at Harvard University to clarify how we have attempted to address these research design challenges. This program has simultaneously solved important practical innovation problems for partner organizations, like NASA and Harvard Medical School (HMS), while contributing research advances, particularly in relation to innovation contests and tournaments. We conclude by proceeding to highlight the opportunity for the scholarly community to develop a “science of innovation” that utilized field experiments as means to generate knowledge.

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.

Teaching Note for HBS Cases 614-042 and 614-043.

The first case describes the efforts of Beiersdorf, a worldwide leader in the cosmetics and skin care industries, to generate and commercialize new R&D through open innovation using external crowds and "netnographic" analysis. Beiersdorf, best known for its consumer brand Nivea, has a rigorous R&D process that has led to many successful product launches, but are there areas of customer need that are undervalued by the traditional process? A novel online customer analysis approach suggests untapped opportunities for innovation, but can the company justify a launch based on this new model of research?
The 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 first case, and how the commercial success of the product informed thinking by leaders in R&D for the future.