Innovating in a Secret World: The Future of National Security and Global Leadership
224
Innovating in a Secret World: The Future of National Security and Global Leadership
224eBook
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Overview
Innovating in a Secret World is a detailed examination of the U.S. government and innovation landscapes and of the current trends in often secret national security–related research and development (R&D). Based on case studies, detailed research, and interviews with executives at Fortune 500s, startup entrepreneurs, and military directors and program managers, this accessible and timely book is a must-read. Tina P. Srivastava evaluates whether the strategy of technology innovation in the world of national security leaves certain innovations behind or unintentionally precludes certain classes of innovators from participating. She identifies the unintended consequences and emergent behaviors of this conflict. This examination unfolds in a complex, dynamic system that includes the legal framework in which technology innovation must exist.
For more than a decade Srivastava has been on the front lines of cutting-edge technology innovation. She suggests focusing on an emerging class of R&D strategy called “open innovation”—a strategy that broadens participation in innovation beyond an individual organization or division traditionally assigned to perform R&D activities. Through compelling stories of commercial and early government applications, she shows how open technology innovation strategies can enable, accelerate, and enhance technology innovation. Successful incorporation of open innovation into the previously closed U.S. government R&D landscape can yield profound benefits to both national security and global leadership.
Product Details
| ISBN-13: | 9781640122086 |
|---|---|
| Publisher: | Potomac Books |
| Publication date: | 07/01/2019 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| Pages: | 224 |
| File size: | 2 MB |
About the Author
Tina P. Srivastava is an innovator, entrepreneur, and technology expert. Her experience spans roles as chief engineer of electronic warfare programs at Raytheon to co-founder of a venture-backed security startup. She is an FAA-certified pilot and instructor of MIT’s Pilot Ground School course. Srivastava earned her PhD in Strategy, Innovation, and Engineering, a masters in System Design and Management, and a bachelors in Aeronautics and Astronautics, all from MIT.
Read an Excerpt
CHAPTER 1
The Emergence of Open Innovation
The commercial sector is successfully leveraging innovation strategies to accelerate technology innovation and enhance business growth. Recent commercial examples of disruptive technology range from smart phones to cloud computing to blockchain to virtual and augmented reality. Given that the commercial sector is often where we find the state of the art in technology innovation, it makes sense to consider whether the innovation strategies employed in that sector can serve as a model for the U.S. government and secure R&D. Among the strategies employed by the commercial sector is an emerging class known as open innovation that touts breakthrough success in achieving technology innovation in terms of the time and cost required to innovate, as well as the diversity and novelty of ideas generated.
Open innovation is about broadening participation in innovation beyond an individual organization or division traditionally assigned to perform specific R&D activities. Henry Chesbrough, credited with coining the term, wrote in 2003, "Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to market, as the firms look to advance their technology."
Chesbrough goes on to explain that an organization, to accelerate internal innovation, should leverage the "purposive inflow" of knowledge from outside the organization. Among the many approaches for establishing such a purposive inflow of knowledge to solve a problem or advance technology, three stand out:
1. Fostering competition
2. Providing a means to share ideas and collaborate
3. Offering incentives to innovators to participate
To understand how these work, consider three brief open technology innovation examples widely regarded as successful.
Three Open Innovation Examples
The first example is one of fostering competition. In 1996 the X Prize Foundation publicly offered $10 million to any nongovernmental organization able to "build and launch a spacecraft capable of carrying three people to 100 kilometers above the Earth's surface, twice within two weeks." It was a lofty goal. (The prize was later renamed the Ansari X Prize, following a multimillion dollar donation to the cause by entrepreneurs Anousheh and Amir Ansari.) In 2004 Mojave Aerospace Ventures (MAV) won the prize. The MAV team, led by Microsoft cofounder Paul Allen and noted aerospace engineer Burt Rutan, successfully achieved the space flight goal. Perhaps even more significant was the fact that their win signaled a dramatic shift in the field of space flight. It opened the door to a new private space industry and commercial space flight.
This competition-centric open innovation strategy succeeded in achieving resource leveraging; the winning team's estimated development costs were $25 million, or 2.5 times the prize money. The strategy created reputational incentives beyond the monetary prize that contributed to the winning team's investing far more than the prize money to win. "Over the course of the competition, 26 teams invested over $100 million in aggregate for research and development in suborbital space flight."3Incredible advancements in technology areas such as propulsion and spacecraft reusability were made, not just by the winning team. That is, the entire field of space flight benefitted from the competition.
Systems engineering uses the "iron triangle" to depict the constraints on projects, as figure 2 shows. Open technology innovation challenges can be set up to constrain any of the triangle's dimensions. Some set a limit on the duration of the competition, and the winner is often the best solution achieved within that time frame. The Ansari X Prize had a fixed goal and scope but an unrestricted schedule.
The second example illustrates providing a means to share ideas and collaborate. The start-up company Quirky created a community of innovators and employs a unique intellectual property (IP) incentive structure that helps find the best ideas and then leverages that community to develop those ideas. Quirky has established an environment in which innovators have access to collective knowledge and the ability to share ideas to collaborate.
The Quirky approach involves a three-stage business model. First, the company asks its community to submit ideas. Second, inventors can ask members of the community for help in improving or developing their ideas in exchange for a share of the royalties. Finally, Quirky takes the top product ideas, builds those products, and sells them, sharing some of the revenues with the community according to the IP agreement.
Quirky has also established a structure that incentivizes potential innovators to participate. The company offers royalties to idea contributors, with the goal of increasing access to potentially valuable inventions. The IP and reward policies are tied to the innovation strategy. The approach has paid off: Quirky has been successful in generating a large number of ideas from a diverse population in a short period of time, receiving about a thousand ideas per week.
Like Quirky, the third example also offers incentives to innovators to participate. The idea is that the larger the pool of potential solvers to a problem, the more likely it is that a solution will be found. If we can incentivize more innovators to participate, drawing from an interdisciplinary pool of innovators bringing different skills and experiences, then we may be able to solve previously unsolved problems or decrease the time it takes to reach the solution.
Innocentive is an online platform for organizations to launch prize-based open challenges to solve technology problems. The pharmaceutical company Astra Zeneca, consulting firm Booz Allen Hamilton, and health-care provider Cleveland Clinic have all posted "challenge problems" at Innocentive for anyone in the community to solve.
The Innocentive community of "solvers"— individuals from the community who submit solutions — includes millions of people. The challenge success rate is 85 percent. Innocentive promotes an interdisciplinary perspective because solvers are not necessarily experts in the field of the particular challenge topic.
The potential power of the Innocentive approach can be seen in the experience of Roche Diagnostics, a world leader in in vitro diagnostics, which posted a problem pertaining to product quality control. The company had been working on the problem for fifteen years; the Innocentive responses all came within sixty days. Notably the Innocentive community identified every approach Roche had already tried in addition to identifying a solution.
The Roche example shows that the cost of open innovation can be significantly lower than the use of internal R&D alone. The cost issue is particularly relevant due to the risk factors associated with dedicating resources to an unsolved problem. As the Innocentive model shows, an open innovation strategy can be architected to have comparatively less risk than internalR&D, such as capping the time allocated to solving the problem and leveraging pay-for-performance such that the solution seeker pays only for the winning idea.
All in all, Roche's experience with Innocentive was a success. The high quality of ideas — which included not only what Roche had generated internally, but also a winning solution — enhanced innovation; Innocentive accelerated innovation by generating a large number of ideas in a short time frame; and most important for Roche, this open approach helped solve a problem and thus enabled innovation.
Limitations in Certain Environments
Today there is no consensus on what defines open technology innovation strategy. Researchers have recognized this gap and, as one wrote, "Open innovation is a young concept that includes several meanings. … Researchers have different definitions and interpretations about open innovation." There has never before been a taxonomy developed to help classify these various strategies so that they can be critically analyzed and their potential applications to different situations evaluated. As a result, many implementations of open technology innovation are "copycat" and often not grounded in academic theory.
The gap in open innovation research widens in the U.S. government context. There have been few studies of open innovation in the government and fewer still in the areas of national security and defense. The U.S. government remains "in the early stages of adoption of open innovation," and academia is still "in the process of understanding relevant issues." Academic researchers of open innovation in the U.S. government have focused almost exclusively on the delivery of public services, not on technology innovation.
Several endemic aspects of secure U.S. government R&Denvironments help explain the dearth of open innovation examples. Chesbrough identified three limitations to the application of open innovation that correspond directly to these aspects. First, he explained that current open innovation strategies do not work well when proprietary or other restrictions prevent a solution seeker from being able to fully define the problem needing to be solved. Organizations seeking solutions to problems sometimes purposely obscure aspects of the problem to avoid tipping off their competitors, but this approach can hinder innovation. Chesbrough advised that providing a complete description of the problem is necessary to elicit helpful innovations. Unfortunately in U.S. government environments, security classification often prevents problems from being fully defined. The "competitors" in this context may be global adversaries.
Second, open technology innovation strategies do not work well when tacit knowledge is required to fully understand the problem. If the problem must be experienced firsthand and cannot be adequately described in words, it does not lend itself to be solved with open innovation. Unfortunately this situation is also characteristic of secure U.S. government R&D.
Third, most open innovation strategies are best suited to point solutions — that is, solving one particular problem without regard to related issues — and do not work well in the context of technical interdependencies. However, as discussed above, the technology needed to advance national security is often complex, interconnected, and dynamic. For certain technology areas critical to national security, innovators require a prerequisite knowledge base of the complex systems and technical interdependencies involved.
To overcome these limitations first requires a broader understanding of what open technology innovation would mean in a U.S. government context. A starting point is the taxonomy I mentioned above, and the remainder of this chapter introduces a taxonomy to further not only research, but also, and more important, the implementation of open innovation in secure U.S. government environments, where it is so desperately needed.
Building a Taxonomy
To begin let's explore the breadth of open technology innovation strategies that have been used in the U.S. commercial sector, affording us an opportunity to see trends and design variables that will drive the analysis of potential opportunities for open innovation in U.S. government programs. In this context the U.S. commercial sector includes the industries and organizations that benefit civilian commercial interests either directly (business-to-consumer, orB2C) or indirectly (business-to-business, or B2B), including both for-profit and nonprofit organizations not owned and operated by the U.S. government and that may be privately or publicly held.
Table 1 shows a variety of open technology innovation strategies used in the commercial sector. The eighteen examples were selected from more than one thousand to illustrate the breadth of the solution space. These examples span industries from software to appliances to retail and others. In some cases these open innovation examples are entities themselves, such as Quirky, Kiva, and Threadless, and other examples are part of a larger company, such as Sandisk Ventures, Cisco Entrepreneur in Residence (EIR), and LEGOIdeas. The list also includes platforms that support multiple open innovation approaches, such as Innocentive.
It should be noted that outcomes associated with many open innovation implementations tend to be documented by the initiators and sponsors themselves rather than in independent, objective assessments. The latter would be indicative of a higher level of maturity in the field of open innovation; the former illustrates that open innovation remains at an early stage.
Based on the list in table 1, the taxonomy of open innovation strategies in figure 3 categorizes those that have been pursued in the U.S. commercial sector in recent decades. Let's look at these in a bit more detail. "Challenge/Contest/Game" and "Innovator Network" correspond to the examples listed above in this chapter. "Challenge/Contest/Game" includes "Grand Challenges" such as the Ansari X Prize, which set a lofty goal and offered prize money as a reward. "Innovator Network" leverages a community of innovators to solve technology challenges, such as in the Quirky and Innocentive examples. The innovators in the community often have varied backgrounds and are not necessarily subject-matter experts, a situation that can lead to interdisciplinary work and generation of ideas that cross knowledge boundaries.
"Venture Capital (VC) Arm" is a twist on traditional funding strategies. VC arms can be "self-directed new venture groups charged with moving the firm into a new market." They often invest in start-ups with a technology focus synergistic with the firm's growth areas and that have potential for merger or acquisition at a later point.
"Crowdfunding," a relatively recent concept, involves posting ideas on a designated online portal and raising money by soliciting contributions from a large number of contributors. Accepting small contributions creates a lower threshold to participate. There are several varieties of crowdfunding. In microfinancing-based crowdfunding, the money contributed is in the form of a loan — as in the example of Kiva, a nonprofit founded in 2005 that connects potential lenders with borrowers in multiple categories. In rewards-based crowdfunding, such as through the increasingly well-known Indiegogo and Kickstarter platforms, the money can be a donation that is rewarded with items such as a T-shirt or even an early version of the product. Finally, in securities-based crowdfunding, money is contributed by what the U.S. Securities and Exchange Commission (SEC) calls "accredited investors" in exchange for equity. Recent SEC rules allow anyone, not just accredited investors, to invest an amount based on the annual income and net worth of the investor.
"Product Platforming" involves opening a firm's base product platform for others to add on features and components, such as apps. Google's partially open source Android operating system is a commonly cited example. Innovations built on the platform are often incremental rather than "disruptive" because they conform to an existing platform. Many of this strategy's benefits tend to be in product adoption and network externalities rather than in the enhancement of innovation capability through a unique strategy or structure.
"User-Centered Innovation" seeks to benefit from loyal product users' experiences by involving them in the product development and redesign process. These users, sometimes called lead users, are often evangelists of a product and proactively customize products to their own needs. These customizations may highlight areas for new feature development. For example, a user of a commercially available snow blower may make innovative modifications to it for increased throughput, using odds and ends such as zip ties rather than professional design and manufacturing tools. Users might be willing to share their innovations with manufacturers for free because they would benefit from their modifications being incorporated professionally into future versions of the product. Like "Product Platforming," this strategy tends to be limited to incremental innovations.
Each strategy's implementation is defined by design variables — for example, whether a financial prize is offered or who retains intellectual property rights. It should be noted that it is possible to change design variables within an open innovation strategy without changing the overarching strategy itself. For example, a monetary prize and some IP protection could be offered in the context of a "Challenge/Contest/Game," as in the case of the Ansari X Prize, or there could be a non-monetary prize and no IP protection, but in both cases it would still be a Challenge/Contest/Game.
Figure 4 illustrates how the choice of design variables affects the implementation of a strategy. Objectives are not typically considered design variables, but they are included here to aid in determining which strategy to pursue. "Recurrence model" refers to whether the approach is a one-time effort, recurring, or tiered (as in the example of FANG, discussed in chapter 3 below). The "Number of winners" matters because it may speak to the nature and complexity of the goal advertised by the sponsors. Is it a contest that is so difficult that no one wins? Is the concept of a winner even applicable? Considering the "Audience (number of participants or number of competitors)" as a design variable may meanmodifying the implementation with respect to marketing efforts, platform capacity, resources allocated, or type of platform.
(Continues…)
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Table of Contents
List of Illustrations List of Tables Acknowledgments Introduction: Maintaining a Technological Edge for National Security 1. The Emergence of Open Innovation 2. The World of Secret U.S. Government R&D 3. Success and Failure in Secret U.S. Government Technology Innovation 4. Practical Consequences and Perverse Incentives 5. Secrecy versus Open Innovation 6. Incentives for Innovation 7. The Path to Long-Term Improvement Notes Bibliography Table of Authorities Index