Overview of Ideas:
Direct Innovation Factors
Innovation operates within an ecosystem of economic and policy factors as well as institutional actors. It is a complex system involving many such elements, but some are more significant and “direct” than others. The “Direct Innovation Factors” amount to prerequisites for innovation. Direct factors include Robert Solow’s “technological and related innovation” and Paul Romer’s “human capital engaged in research.” In rough shorthand, we could say that these two direct factors require R&D and the talent base to undertake it.
Indirect Innovation Factors
There are also numerous “Indirect Innovation Factors,” less critical for innovation but potentially significant. Strong innovation capacity requires getting as many of these right as possible. Some indirect factors are set by government, others by the private sector. Indirect factors set by government include: fiscal/tax/monetary policy, trade policy, technology standards, technology transfer policies, government procurement (for mission agencies), intellectual property protection, legal/liability systems, regulatory systems (for environment, health, safety, market solvency and market transparency), accounting standards, export controls, etc. Indirect factors set by industry include investment capital (angel, venture, IPOs, equity, lending), markets, management and management organization, talent compensation and rewards, etc.
Innovation Organization – The Third Direct Innovation Factor
Innovation Organization can be viewed as the third direct innovation factor, supplementing Solow’s “technological and related innovation” and Romer’s “human capital engaged in research” factors. This factor entails evaluation of the strength and capacity of the innovation organizations operating in an innovation system – which can be evaluated at regional, national, cross-national or sectoral levels. Innovation organizations include university research, government labs, established firms and startups, as well as the effectiveness of the handoffs of technology advances between them. The strength of the institutional actors and the linkages between them – the innovation organization - will be determinative of the strength of the innovation system.
Innovation at the Institutional and Personal Levels
Innovation must be evaluated at both the institutional level and at the personal level. The first involves the connections and hand-offs between innovation institutions, whether at the industry, university or government research levels. Effective linkages between these innovation actors can be termed “connected science.” However, it is critical to note that people innovate not institutions, so innovation must also be analyzed at the personal level. Innovation (as opposed to invention or discovery) almost invariably involves “great groups,” a concept developed by Bennis and Biederman. Understanding the rulesets for these great groups is thus a key aspect to understanding the innovation, along with the connectedness of innovation institutions.
Above points set out in:
- “The Connected Science Model for Innovation - The DARPA Role”, chapter in the National Academy book 21st Century Innovation Systems for the U.S. and Japan (May 2009), 207-210.
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Elements of the DARPA Model
The DARPA (Defense Advanced Research Projects Agency) innovation model is particularly important because it has operated to consciously to create two capabilities. First, it represents “Connected Science,” fostering linkages between innovation institutions, public and private. Second, it has encouraged the creation of “great groups.” Such groups are capable of breakthrough innovation through deep collaboration, remarkable talent from complementary fields, effective leadership, focus on a major technology challenge, devotion to a mission, adherence to an organizational ruleset and backing from an innovation ecosystem. DARPA’s recurring ability to encompass innovation at both the institutional and personal level has been largely unique among innovation organizations.
DARPA has consistently followed a Challenge-Based Research Model seeking research advances that will result in solution to major technological challenges. Technology Visioning is a process of creating an image of how a technology could develop in the future and what such a successful technology would look like, as an aid to setting goals and motivating present action. This is an essential part (as discussed by Tamara Carleton) of the technology challenge approach practiced by DARPA.
In undertaking these steps, DARPA has also utilized a “Right-Left” Model where its program managers determine the technologies needed from the “right” (outcomes) side of the innovation pipeline, then look for breakthrough science on the “left” side of the pipeline that will get them there, nurturing this research into technologies required for the advances identified.
DARPA is also an example of the Island-Bridge Model of innovation (a term first used by Bennis and Biederman), exemplifying a relatively small, flexible, innovative organization or team which is isolated and protected from bureaucratic influences and controls (placed on an “island”) but retains direct links (a “bridge”) with top decision makers with authority to implement its innovations. DARPA has also made extensive use of the "hybrid model," combining outstanding university researchers with innovative small firms to link these two kinds of innovation capabilities.
Above points set out in:
- “ARPA-E and DARPA: Applying the DARPA model to energy innovation” (with R.VanAtta), Journal of Technology Transfer (Oct. 2011).
- “The Connected Science Model for Innovation - The DARPA Role”, chapter in the National Academy book 21st Century Innovation for the U.S. and Japan (May 2009).
- “The Once and Future DARPA” appeared in the book (Brookings Press, Francis Fukuyama, ed., 2007) (reprinted from The American Interest (2006)).
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Transformative Innovation
Transformative innovation (as opposed to transformative technologies) embarks through a series of five stages. Forming critical innovation institutions requires great talent operating through institutional mechanisms on the front end of the innovation system. capable of moving technology advances from idea toward innovation – in spaces where great research and talent combine. The Island-Bridge model, described above, allows the innovation group protection from bureaucratic pressures, creating the innovation island, but with a bridge back to sympathetic decision makers who can press technologies forward into implementation. Because every innovator stands on the shoulders of others, building a “thinking community” is key – this must become a community of thought to keep enhancing the ideas. Linking technologists to operators brings measures of realism and practical need to the innovation task. Finally, change agents, individual or institutional, are vital to develop and press the technology advance forward into the innovation phase.
Above points set out in:
- Technological Innovation for Legacy Sectors, (with C. Weiss) (Oxford University Press 2015), chapter 12 (in publication).
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Models of the Dynamics of Innovation
Traditional theory ascribes innovation either to a “pipeline model” in which "technology push" results from federally-supported basic research, or to an “induced innovation model” in which new products emerge largely from incremental advances by industry to meet a "market pull." These two traditional categories do not adequately describe the full dynamics of innovation; three new categories of innovation drivers are needed: the “extended pipeline model” in which innovations are nurtured not just from research but all the way from research through market launch, the “manufacturing-led model” for innovations that emerge through highly creative enhancements in engineering and manufacturing processes as a technology approaches and enters the production phase, and the “innovation organization model” in which innovation requires the creation of linkages between innovation institutions and measures to address the structural obstacles that block disruptive innovation in Legacy sectors. This fifth model incorporates and integrates the other four models in order to overcome the technology lock-in imposed by Legacy paradigms (discussed below).
Above points developed in:
- Technological Innovation for Legacy Sectors, (with C. Weiss) (Oxford University Press 2015), chapter 11 (in publication).
- Structuring an Energy Technology Revolution (with C. Weiss) (MIT Press 2009).
- “Complex, Established ‘Legacy’ Sectors: The Technology Revolutions that do Not Happen” (with C. Weiss), Innovations (Spring 2011).
- “Taking Covered Wagons East: A New Innovation Theory for Energy and Other Established Sectors” (with C. Weiss), Innovations (special energy issue Fall 2009).
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New Model Innovation Agencies – Connected Science
There have been four major innovation organization policy moments for the federal government, driven by the demands of politics and technology since World War II: 1) the immediate postwar period where the Cold War helped drive the formation and expansion of a plethora of science agencies organized around basic research, 2) the Sputnik aftermath with the formation of DARPA and NASA and scaled up funding for science, 3) the competitiveness era “valley of death” programs of the 1980’s, and recently, 4) an energy technology shift driven by energy security and climate demands, and 5) new advanced manufacturing programs and policies linking industry, university research and government policy. In that six decade evolution, what lessons have we learned about design of federal innovation organizations? What are the institutional elements in the “new generation” innovation policy programs now developing or under consideration? There was a fundamental divide in the design for federal science agencies, between a “connected” model prevalent in the World War II period where innovation stages and actors were closely linked, and a “disconnected” postwar model, where the federal role focused on one innovation stage, basic research, and lines to the industry development and implementation roles were largely erased. Subsequent decades have seen a series of efforts in new agency design (in periods 2 through 5) to bridge the divide and restore the ”connected science” approach. The focus has been on an evolving the federal agency role, furthering linkages between the actors within innovation pipeline.
The Problem of Political Design in Innovation Agencies
In addition, this structural evolution has been accompanied by a growing realization that the substantive policy design of new and existing innovation agencies must be complemented by a political design to assure the agency’s survival but is consistent with not contradictory to strong substantive policy design. Rules for sound political design can be applied to help ensure sound innovation policy implementation over time.
Above points discussed in:
- “New Model Innovation Agencies – An Overview,” Science and Public Policy (July 2014), v.41 n.4, 425-437.
- “The Problem of Political Design in Federal Innovation Organization”, chapter in the Stanford Univ. Press book The Science of Science Policy (spring 2011).
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Legacy Sectors
The new concept of “Legacy sectors” describes an economic sector that is defended by barriers and market imperfections that favor existing technology and block the development and market launch of disruptive innovations. Because U.S. innovation policy historically has focused on nurturing “the next new thing,” it has missed “the next old thing” – the Legacy sectors. It drives its technology covered wagons west to open new territories, it doesn’t drive those covered wagons east to bring new technology to existing sectors. In other words, because U.S. innovation is organized around innovation in Frontier sectors, it is missing a major potential area for introducing needed disruptive innovations in the Legacy sectors that constitute most of the economy. In this way, it misses a chance to accelerate economic growth and to address pressing environmental problems.
The technological/economic/political/social Paradigm
Understanding Legacy sectors requires a new framework for how they resist disruptive innovation. They form a “technological/economic/political/social paradigm” that locks-in to existing technology and its supporting business model, protected from innovation by economic, political and social support systems organized around protecting the existing technology. There are features common to Legacy sectors – from perverse subsidies and price structures to vested interests, financing systems geared to existing technologies and existing public habits and expectations. There are also market imperfections such as economies of scale, "lumpiness," "non- appropriability" and a lack of collective action. These enable a corresponding set of tools which can be applied for analyzing Legacy sectors, such as energy, the electric grid, construction, auto and air transport, manufacturing, higher education, health care delivery, industrial agriculture and the military.
Steps to address Legacy Sector Challenges
There is a five-step process for addressing the deep policy challenge of bringing innovation to Legacy sectors through the innovation organization model. Successful innovation in Legacy sectors requires a strategic and systems approach to institutions and policies that stimulate research and innovation, as well as policy measures that address the structural obstacles to innovation in these sectors. The stages include strengthening the “front end” of the innovation system (from research through prototyping), identifying launch paths for emerging technologies, matching supporting policies to launch paths, undertaking a gap analysis of the innovation system and filling innovation system gaps. It also requires change agents – actors, institutional and individual, who overcome all obstacles and see the innovation through from idea to implementation, and equally important, an enabling economic, political, legal and cultural innovation context.
Point of Market Launch:
The traditional focus of innovation policy for over theree decades has been on the “Valley of Death” between research and later stage development stages. However, the complexity of the innovation process in Legacy sectors forces an additional policy focus: on the point of Market Launch, the moment at which a technology is introduced into the market. This is the most difficult step in the development and deployment of technologies intended for Legacy sectors, in contrast with the “Valley of Death,” which is the most difficult launch point for technologies that fit the “pipeline model.”
Above points discussed in:
- Technological Innovation for Legacy Sectors, (with C. Weiss) (Oxford University Press 2015), chapters 5,12 (in publication).
- Structuring an Energy Technology Revolution (with C. Weiss) (MIT Press 2009).
- “Legacy sectors: barriers to global innovation in agriculture and energy” (with C. Weiss), Technology Analysis and Strategic Management v. 25, no. 10 (Nov. 2013). 1189-1208.
- “Complex, Established ‘Legacy’ Sectors: The Technology Revolutions that do Not Happen” (with C. Weiss), Innovations (Spring 2011).
- “Taking Covered Wagons East: A New Innovation Theory for Energy and Other Established Sectors” (with C. Weiss), Innovations (special energy issue Fall 2009).
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Advanced Manufacturing
Manufacturing is a major Legacy sector subject to the legacy sector challengers delineated above, but also a critical driver of the innovation process. By failing to consider measures to counter the tendency of U.S.-based companies to send production offshore, particularly measures consistent with the traditional American emphasis on free markets and free trade, the U.S. is giving up important parts of its innovation capacity. Manufacturing must be seen, like the R&D stages, as a part of the innovation process, and critical to the innovation system. A new vocabulary is needed to describe the consequences of the near-exclusive focus on R&D that has been the basis of U.S. innovation policy. “Innovate here, produce here,” which can also be called full-spectrum innovation, in which the U.S. took all the gains of its strong innovation environment at every stage, is being replaced by “innovate here, produce there.” This threatens to create a problem of jobless innovation, and in turn threatens to lead to “produce there, innovate there.”
New production technology paradigms (accompanied by new business and process models) that dramatically increase efficiency and lower costs are required to enable production competition with lower cost and lwer wage economies. These could include “smart” and “network centric” manufacturing, advanced materials and new distribution and energy efficiencies. In addition, new scale-up financing tools are needed to overcome the Mountain of Death: the gap between the 5 to 7 year time horizon of venture capitalists and angel investors in the IT sector, on the one hand, and the 10 plus year time horizon for scale-up in manufacturing and capital goods sectors, on the other.
Above points discussed in:
- Technological Innovation for Legacy Sectors, (with C. Weiss) (Oxford University Press 2015), chapters 4, 6,13 (in publication).
- “Advanced Manufacturing Policies and Paradigms for Innovation”, Science (December 6, 2013).
- “Reinventing American Manufacturing: the Role of Innovation”, Innovations (special manufacturing issue Summer 2012).
[Note - as indicated in the references, many ideas above were developed in close collaboration with co-author Prof. Charles Weiss]