Abstract
The purpose of this study is to understand the nature of and the extent to which the type and level of marketing efforts help with the continuation of early-stage innovations. The locus between the phases of Research and Development and New Product Development is defined as the fuzzy front end of innovation, frequently called the “Valley of Death.” This early stage of innovation is typified by high risks and scarcity of project resources. The challenge for a firm as it develops an early-stage innovation is securing adequate financial, human, and physical project resources. For this study, early-stage innovations are represented by the US National Institutes of Health licenses accorded to small- to medium-size firms. The study develops firm profiles that describe combinations of marketing efforts that enable innovation continuation during the fuzzy front end of innovation. Profiles are evident in terms of marketing variables, firm attributes, and project resources. These profiles vary for type of firm and also by the stage in the firm’s life cycle. The contributions of this study are to (a) develop combinations of variables and profiles for describing and predicting early-stage innovation continuation, (b) provide pragmatic information to potential stakeholders about how to identify and foster early-stage innovations, and (c) help small- to medium-size firms understand how to position and promote themselves in order to obtain resources and advance early-stage innovations.
Keywords
Introduction
The biotech industry’s long development cycle and regulatory procedures can be associated with a low-invention-to-commercialized product survival rate. 1 Not only is the survival rate low, but also the process of commercializing new biotech solutions involves many different economic actors. Typically, a small- to medium-size (SME) biotech firm will advance an early-stage innovation toward the new product development (NPD) phase and then, in the later stages, will team up with a large pharmaceutical or biotech company, which offers marketing, sales, and manufacturing resources that smaller firms are unable to replicate or scale.2–4 Ensuring early-stage innovation continuation is critical for increasing the number of biotech solutions that could advance through to later product development stages. The focus of this study is prior to NPD, where SME firms are prevalent developers for early-stage biotech innovations.
One source of innovation is a licensed technology from a government or academic institution. Firms of all sizes, which include SMEs, obtain technology licenses for the purpose of advancing the technology toward commercialization. However, innovations, especially during the initial stage of development, can become stalled and might not come to fruition due to lack of project-level resources, defined as financial, human, or physical. 5 This initial stage is a risky and perilous time for a developing innovation. For example, in the biotech industry, it is estimated that only one in 5,000–10,000 innovations survives to product commercialization. 6
While the prior-reported survival rate could have scientific/technological reasons behind the success or failure, the purpose of this study is to understand the extent to which marketing efforts enable the continuation of early-stage innovations within SMEs. 6 SME biotech firms are studied as they seek to obtain innovation project resources by communicating value propositions about their firms to potential resource stakeholders. In this study, an early-stage innovation is a firm’s technology license granted by an institution. The firm is tasked with developing the licensed technology into a commercial solution.
Many scholars called the early stage of innovation the fuzzy front end of innovation (F2EI), which is characterized by informal processes and many industry-specific conditions.7–12 These F 2 EI characteristics lead to an appearance of chaos and randomness. 13 Survival during F 2 EI, which is used in this study as license continuation, is typically uncharted and difficult and, thus, has been called the “Valley of Death.”14,15 The challenge for a firm as it develops an early-stage innovation is securing adequate financial, human, and physical project resources. Scholars have observed that even firms that achieve some form of growth, i.e. revenue and/or profit, are challenged in finding and securing resources.16–19
This study’s emphasis is on how the firm’s marketing efforts, defined primarily as the promotion of a firm’s attributes, can assist with the acquisition of project resources and extend the survivability of the license during the F2EI.
Methods
Study design
This cross-sectional study uses a Likert-based survey in order to develop licensee profiles that help determine license continuation through the Valley of Death. The variables in the survey were developed from a previous qualitative study. 20 Results from discriminant analysis and cluster-analysis procedures, supported by qualitative comments, are used to develop the profile patterns. At the end of this section, example profiles are discussed to elucidate the license continuation patterns observed during the Valley of Death by the research participants.
Sample
The sample was derived from the population of US National Institutes of Health (NIH) licenses from 2002 to 2012, sourced from NIH Lights Up the World, which is a searchable, public database. In this study, licensed SME firms fit the qualification parameters of the Small Business Administration’s (SBA) definition of small- to medium size. 21 All qualifying licensees were given an equal opportunity to participate in this study. Because the objective was to conduct an interview with an executive, typically, the CEO of the firm, prior to sending an introductory email or making a phone call, background information was collected on the firm and the license. Sources for gathering background information were the firm’s website, the Federal Register, and other publicly available records on the firm. Background information typically included information about the firm’s history, such as the founding date, location, executives, board members, products, press releases, and contact information. Each licensee was contacted at least three times in order to secure a survey interview.
Of the total population (374 firms), 115 licensed firms participated in the survey (31%), 126 did not wish to participate or did not respond to calls and emails (34%), 52 firms were acquired by larger firms (14%), and 81 firms went out of business (21%). Out of the eligible sample, which was 241 firms (374 total minus 52 acquired firms and minus 81 firms that went out of business), a 48% response rate was obtained. The 52 firms that were acquired by larger firms were not able to participate in the survey due to confidentiality reasons and/or loss of key personnel that could have provided a perspective on the license prior to the firm’s acquisition, a circumstance that would qualify as the Valley of Death. These firms do represent a measure of success; however, this type of success, merger/acquisition, cannot be captured in this study. The 81 firms that went out of business were not able to be contacted, as their e-mail addresses and/or phone numbers are no longer operating. These firms are clear examples of failure but because of the lack of access to them, they could not be included in the study.
The firms in this study represent two major biotech groups – development and services. The development group, which holds 132 licenses in total, includes firms that focus on development of therapeutics, diagnostics, and devices. The services group, which holds 68 licenses in total, is represented by firms that developed reagents, models, or are contract research organizations.
Results
Discriminant analysis
Confusion matrix
From the discriminant results, there are six independent variables with differences between the two types. These are firm attributes: executive, board, and technology; marketing: Internet; and project sources of funds: grants and partner. In order to understand these differences, a PROC TTEST procedure in SAS was used to determine the means of the two types and the significance of these differences in means. The results of this procedure are shown in Figure 1. The two types demonstrate different means in three of the four main areas in the model—firm attributes, marketing, and project sources of funds. Three firm attributes—executive, board, and technology—have different means, all of which are significant. In the services type, all three firm attributes and project sources of funds have lower means than the development type. However, Internet marketing has a higher value for the services type and is discussed next.
Mean differences by type. *α ≤ 0.10, **α ≤ 0.05, ***α ≤ 0.01.
Development type
The distribution of licenses is 24% biological materials (non-patent) and 78% patent technologies. As shown in Figure 1, means for the firm attribute variables—executive, board, and technology/IP—are all higher than the services type. Technology/IP and the executives are both extremely important. “You have to have good science and a good business communicator to get critical resources,” said Licensee 93. Means for the sources of funding—grants and partners—are higher than for the services group. “We have been funded entirely by government grants. In addition, by serving on various committees, we have been able to form partnerships with manufacturing and clinical grade research organizations,” stated Licensee 146.
Services type
This type of biotech licensee is distributed fairly equally among the license type, 47% biological materials (non-patent), and 53% patent technologies. Service providers typically acquire revenue from their services and, thus, the means for the group, as shown in Figure 1, indicate less dependence on grants and partners for sources of project funds. Means for the firm attributes – executive, board, and technology/IP – are also lower than the development-type means. This is because firms are marketing service solutions versus pitching firm attributes in order to raise capital. “We don’t raise capital, we are owner and services revenue financed,” stated one CEO (Licensee 194). The mean of the Internet marketing variable, e.g. the firm’s website, is critical for highlighting the firm’s services capabilities and conducting commerce. “Our website is how we promote our services and expertise. The Internet is critical to our company,” explained Licensee 174.
Cluster analysis
The cluster-analysis procedure was used for understanding how firm profiles explain license continuation. In addition to the discriminant analysis, service/development groupings that elucidate different means for certain variables within the two biotech license types, cluster analysis helped determine other combinations of variables that result in license continuation. The SAS software PROC CLUSTER procedure was used to test the marketing interval variables in the model. The marketing variables yield three cluster groupings, which are shown in Figure 2. Each of these clusters demonstrates different means for the marketing variables and, thus, has unique combinations of marketing variables that led to license continuation.
Summary of cluster means.
Upon examination of the observations in each of the clusters, their unique patterns can be labeled by using investment community terminology as follows: seed stage to early-stage start-up; mid- to latter-stage start-up; and established, revenue-generating.22–24 Each of these clusters is explained next.
Seed to early-stage start-up cluster
This grouping is seeking seed funding or other forms of early-stage funding, e.g. grants, and is composed of development firms.25,26 As shown in Figure 2, firms in this cluster have the second-highest networking mean. As one CEO (Licensee 6) explained, “I use my personal network to gain access to resources, which are 99 percent of the time, investments.” Another senior executive (Licensee 58) explained, “My network is based upon the university and attorneys that are helping me get access to investors.” Several firms, e.g. Licensees 58, 61, and 62, are able to network through incubators, which are intermediaries. Incubators are typically able to provide access to business networks along with providing start-up infrastructure, e.g. low-cost rental space, lab equipment, and administrative services.
Three of the marketing variables – conferences/events, Internet, and publications – have the lowest mean of the three clusters. Conferences are often used strategically. “We are selective about which conferences we attend. While they can be good networking events, they also can consume valuable time and resources,” explained Licensee 76. The Internet, i.e. a website, reflects the need for the website to function as a form of credibility, which provides basic company information and is not used to conduct e-commerce. “Since we are a relatively young company, we use the website to feature the technology, and executive and scientific talent,” said Licensee 61. The low value for publications is usually caused by the development stage of the biotech innovation. Scientific, peer-reviewed publications signal credibility, but due to the transparency, are done on protected IP. “We don’t publish until we have a product that is closer to clinical trials,” explained Licensee 27.
In summary, these licensees in this cluster are in the development type and are at the earliest stage of firm formation. They seek funding to help sustain the licensed technology’s development and rely on their network to find and obtain resources.
Mid- to latter-stage start-up cluster
This grouping of licensees is further along the start-up continuum, which is defined as having a history of funding, either through investors or alternative funding sources, e.g. grants.27,28 As shown in Figure 2, marketing effectiveness of the Internet and networking is slightly higher than the seed/early-stage start-up cluster. “Over the past 10 years, we have built a network of over 4500 contacts all over the world. The network is critical to our success in this well-connected industry,” said Licensee 186. The conferences variable mean is the highest of all three clusters. “Because we are fairly well-known in the biotech community, we are positioned favorably at the conferences. This comes in the form of speaking at sessions and also, networking appointments. We have had some successes at conferences and are willing to invest in them,” explained Licensee 15. Publications had the largest mean difference. “We publish because that is how the research institutions found out about our biotech innovations,” stated Licensee 18.
Established, revenue-generating cluster
This cluster, which is shown in Figure 2, includes representation of both the services group (75%) and the development group (25%). While this cluster is predominantly services firms, the development firms are generally larger, ranging from 50 to 500 employees. This cluster demonstrates the service licensee attributes that are also found in the discriminant analysis—specifically, a higher Internet marketing variable mean. “Our website is where we conduct our business. It features our customers, our products, and how to order,” said Licensee 36.
Conferences also have a higher mean when compared with the other two clusters. “We participate in the major investment conferences and industry conferences as part of our marketing strategy,” explained Licensee 79. Publications mean is in the middle of the other two clusters. The networking mean is the lowest of the three clusters. “We have a reputation in the industry, so word of mouth is important to our firm,” stated Licensee 120.
Discussion
Firm profiles were developed by first, using discriminant analysis and cluster analysis. Discriminant analysis was supportive of the differences between two biotech licensee types (development and services) and their key variables from firm attributes (executive, board, and technology/IP), marketing (Internet), and project resources (grants and partner funding). The firm attributes’ variables support the halo effect or institutional prestige.29–31 The halo effect in this case is the NIH licensed technology as well as executive/board members. The linkage to license continuation is that the halo effect signals reduced technology ambiguity for potential investors and other forms of project resources. The marketing variable—Internet—helps support the value of information search as complementary to networking, which was found to be a critical factor for firms. 32 This can be explained by the various licensee life-cycle phases. The Internet is more valuable as a licensee advances the biotech solutions toward commercialization. Project resources are also further explained by partner funding, which was supported by other studies.33,34
Cluster analysis was able to further elucidate three different groupings for marketing efforts. These groupings focus on licensee life cycles and how they deploy marketing efforts during the F2EI. This demonstrates support for the adaptability required by firms depending on the context, as was concluded by other scholars as well.35–39
Based upon the discriminant analysis and cluster analysis, three different types of profiles are illustrated, using individual licensees as examples. Each of the profiles describes and tests the model’s variables.
Development licensee—Seed/early-stage start-up example
This early-stage start-up firm (Licensee 61) is part of the development group. The licensee means deviated from the model means in several areas (see Figure 3). The CEO is a serial entrepreneur and, thus, has a vast business network. Instead of sourcing funds from grants and partners, the CEO was able to raise seed and Series A venture capital funding. This supports the findings by other scholars, where serial entrepreneurs were able to obtain multiple sources of financial capital.
40
The firm’s board is composed of investors, which is fairly typical of early-stage companies. Thus, the board has a higher value in terms of helping secure financial resources through networking. The marketing variables—Internet and publications—are lower than the respective means due to the status of the biotech innovation development.
Licensee comparison with seed/early-stage development means.
Development licensee—Mid- to latter-stage start-up example
Licensee 179 exhibits means close to the marketing variables, with the exception of conferences (shown in Figure 4). The CEO explained that his firm only engages in conferences that are strategic to his firm. His network is where he is able to obtain resources the firm needs to develop biotech innovations. In addition to grants, his firm was able to raise an initial round of venture capital funding. Future project funding will come from innovations that will be released to the market in the future. The CEO also expects to secure future partner project funding with latter-stage innovations.
Licensee comparison of mid-/latter-stage development means.
Services licensee example
Licensee 120 delivers services to the biotech industry. The company collaborates with other companies and institutions in order to develop service solutions for its biotech customers. When comparing the firm’s individual licensee ratings with the services group means and the services cluster means (shown in Figure 5), the means for the marketing variables do not deviate from the conferences and publications means, but do deviate more for the Internet and networking variables. This can be explained by the collaborative nature of the firm. It relies on its network more than the Internet for customers.
Licensee comparison with service means.
The discriminant means do not differ for the firm attribute variable—board and Internet. However, the firm attributes—executive and technology/IP—are higher than the mean. Additionally, the means for project resources—funding from grants and partners—are higher. All of these can be explained by the firm’s collaborative model.
Conclusion
Biotech innovations, defined as government-developed technology licenses transferred to SME firms during the F2EI, face Valley of Death survival challenges. The nature of the challenges requires an understanding of the firm’s strengths and weaknesses, coupled with the ability to dynamically adjust to the context, both of which are found among this study’s biotech licensees. Scholars have found that entrepreneurs have a talent for resource construction through entrepreneurial bricolage, which is making do with what is available to the firm. 41
This study focuses on a firm’s resources and how these resources are related to the continuation of the technology license. The objective of the licensees is to market their firm attributes as indicators of minimizing ambiguity to potential financial, human, and infrastructure sources of capital during the license development phase. These sources of capital are invested in project resources that are deployed with the development of a biotech innovation during the F2EI. The entrepreneur may play an important role in terms of reconfiguring existing firm resources and/or acquiring new resources in order to advance the transferred technology license. As is this case in this study, the participants, i.e. biotech license survivors (licensees), demonstrate different pathways through the F2EI.
The study provides new insights about marketing efforts that enable early-stage innovation survival, i.e. license continuation. In particular, having several contextual profiles set the foundation for future research efforts to find order within the chaotic nature of early-stage innovation. Researchers can build upon and test profiles in different industries as well as from different sources of technology transfer.
The practical contributions to industry associations, such as National Business Incubator Association, Association of University Technology Managers, and government and academic institutions, such as NIH, SBA, and Small Business Innovation Research programs, that transfer the technology or support the firm’s development of the transferred technology are many. The transferring agency will have profiles to help guide matching of licenses to prospective licensees. Post-transfer support and resource allocation have the potential to be more effectively applied and achieve innovation development toward commercialization. From a policy perspective, government institutions have additional mechanisms to evaluate the criticality and importance of supporting these biotech innovations with grants and other support services as the licensees advance through the Valley of Death.
Other actors, such as partners and investors, may use the profiles as guides to understanding where firms might need alliances and funds. More important, based on the profiles, the uncertainty can potentially be reduced. Firms will be able to use these profiles to communicate their own value proposition, which can assist efforts to secure resources, such as partners and funds. This study found that networking was an important marketing variable that helped obtain critical resources during early-stage development of a biotech innovation. This, at a minimum, is an important contributor to license continuation.
Footnotes
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
Conflict of interest
None declared.