Crowdsourcing & Open Innovation

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.

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.

Most United States Patent and Trademark Office (USPTO) patent documents contain drawing pages which describe inventions graphically. By convention and by rule, these drawings contain figures and parts that are annotated with numbered labels but not with text. As a result, readers must scan the document to find the description of a given part label. To make progress toward automatic creation of ‘tool-tips’ and hyperlinks from part labels to their associated descriptions, the USPTO hosted a monthlong online competition in which participants developed algorithms to detect figures and diagram part labels. The challenge drew 232 teams of two, of which 70 teams (30 %) submitted solutions. An unusual feature was that each patent was represented by a 300-dpi page scan along with an HTML file containing patent text, allowing integration of text processing and graphics recognition in participant algorithms. The design and performance of the top-5 systems are presented along with a system developed after the competition, illustrating that the winning teams produced near state-of-the-art results under strict time and computation constraints. The first place system used the provided HTML text, obtaining a harmonic mean of recall and precision (F-measure) of 88.57 % for figure region detection, 78.81 % for figure regions with correctly recognized figure titles, and 70.98 % for part label detection and recognition. Data and source code for the top-5 systems are available through the online UCI Machine Learning Repository to support follow-on work by others in the document recognition community.

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.

We investigate the factors driving workers’ decisions to generate public goods inside an organization through a randomized solicitation of workplace improvement proposals in a medical center with 1200 employees. We find that pecuniary incentives, such as winning a prize, generate a threefold increase in participation compared to non-pecuniary incentives alone, such as prestige or recognition. Participation is also increased by a solicitation appealing to improving the workplace. However, emphasizing the patient mission of the organization led to countervailing effects on participation. Overall, these results are consistent with workers having multiple underlying motivations to contribute to public goods inside the organization consisting of a combination of pecuniary and altruistic incentives associated with the mission of the organization.

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.

The last two decades have witnessed an extraordinary growth of new models of managing and organizing the innovation process, which emphasize users over producers. Large parts of the knowledge economy now routinely rely on users, communities, and open innovation approaches to solve important technological and organizational problems. This view of innovation, pioneered by the economist Eric von Hippel, counters the dominant paradigm, which casts the profit-seeking incentives of firms as the main driver of technical change. In a series of influential writings, von Hippel and colleagues found empirical evidence that flatly contradicted the producer-centered model of innovation. Since then, the study of user-driven innovation has continued and expanded, with further empirical exploration of a distributed model of innovation that includes communities and platforms in a variety of contexts and with the development of theory to explain the economic underpinnings of this still emerging paradigm. This volume provides a comprehensive and multidisciplinary view of the field of user and open innovation, reflecting advances in the field over the last several decades.

The contributors—including many colleagues of Eric von Hippel—offer both theoretical and empirical perspectives from such diverse fields as economics, the history of science and technology, law, management, and policy. The empirical contexts for their studies range from household goods to financial services. After discussing the fundamentals of user innovation, the contributors cover communities and innovation; legal aspects of user and community innovation; new roles for user innovators; user interactions with firms; and user innovation in practice, describing experiments, toolkits, and crowdsourcing and crowdfunding.

Teaching Note for HBS Case 615-702.

As of 2013, Havas was the 6th largest global advertising, digital, and communications group in the world. Headquartered in Paris, France, the group was highly decentralized, with semi-independent agencies in more than 100 countries offering a variety of services. The largest unit of Havas was Havas Worldwide, an integrated marketing communications agency headquartered in New York, NY. CEO David Jones was determined to make Havas Worldwide the most future-focused agency in the industry by becoming a leader in digital innovation. The case explores the tensions within the company as David Jones attempts to change the company to compete in an industry undergoing digital transformation. The case uses the example of the acquisition of Victors & Spoils, a crowdsourcing advertising agency, to examine internal reactions.

This note outlines the structure and content of a seven-session module that is designed to introduce students to the fundamentals of innovating with the "crowd." The module has been taught in a second year elective course at the Harvard Business School on "Digital Innovation and Transformation" and is aimed at students that already have an understanding of how to structure an innovation process inside of a company. The module expands the students' innovation toolkit by exposing them to the theory and practice of extending the innovation process to external participants.

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.

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.

Teaching Note for HBS Case 612-066.

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.

Teaching Note for HBS Case 614-064.

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.

Platforms have evolved beyond just being organized as multi-sided markets with complementors selling to users. Complementors are often unpaid, working outside of a price system and driven by heterogeneous sources of motivation—which should affect how they respond to platform growth. Does reliance on network effects and strategies to attract large numbers of complementors remain advisable in such contexts? We test hypotheses related to these issues using data from 85 online multi-player game platforms with unpaid complementors. We find that complementor development responds to platform growth even without sales incentives, but that attracting complementors has a net zero effect on on-going development and fails to stimulate network effects. We discuss conditions under which a strategy of using unpaid crowd complementors remains advantageous.

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.

As of 2013, Havas was the 6th largest global advertising, digital, and communications group in the world. Headquartered in Paris, France, the group was highly decentralized, with semi-independent agencies in more than 100 countries offering a variety of services. The largest unit of Havas was Havas Worldwide, an integrated marketing communications agency headquartered in New York, NY. CEO David Jones was determined to make Havas Worldwide the most future-focused agency in the industry by becoming a leader in digital innovation. The case explores the tensions within the company as David Jones attempts to change the company to compete in an industry undergoing digital transformation. The case uses the example of the acquisition of Victors & Spoils, a crowdsourcing advertising agency, to examine internal reactions.