1. Dr. Charles W. Wessner Director, Technology & Innovation The National Academies of Sciences, USA

2. 2 Advisor, US Congress & Executive Agencies Adjunct Professor, George Washington University; University of Nottingham, England; Max Planck Institute, Germany Advisor, OECD Committee on Science and Technology Policy Advisor, Mexican National Council on Science and Technology Advisor, Finland National Technology Agency (Tekes) Advisor, Sweden National Technology Agency (VINNOVA) Member, Norwegian Technology Forum

3. 3 Fostering Knowledge & Innovation An Overview of the United States Innovation System  Innovation & Competitiveness Practitioners Workshop Istanbul, Turkey April 19, 2004 Charles W. Wessner, Ph.D. Director, Technology and Innovation National Research Council

4. 4 The U.S. National Academies NRC Mission: The NRC is the Operating Arm of the National Academies; it includes 1300 Staff and a Budget of $160 Million The NRC Mission is the Advise the Government on Science, Engineering, and Medicine: 270 Reports Each Year National Academy of Sciences National Academy of Engineering Institute of Medicine National Research Council

5. 5 What is a National Innovation System? A network of institutions in the public and private sectors whose activities and interactions initiate, develop, modify, and commercialize new technologies –Increasingly, governments around the world view the development and transformation of such systems as an important way to promote innovation —thus improving the competitiveness of domestic industries and services –Can be better understood as an Eco-system

6. 6 Why National Innovation “Eco-Systems ” ? “Eco-Systems” Because Innovation Systems Grow and Evolve –They are not constructed by an engineering team to reach a fixed point The Good News: New policies and institutional change can help ecosystem to grow in new ways for new needs –Ecosystem characterized by dynamic linkages among multiple sub-systems…

7. 7 National Innovation “Eco-Systems ” Ecosystem strengthened through linkages among a Nation’s –Human Resource base, –Information Infrastructure –Universities and Research Institutes, –A Positive Business Environment –Enabling Government Policies and Programs The Policies drive the System

8. 8 U.S. Innovation Ecosystem Strengths & Weaknesses Strong Aggregate Commitments to R&D Distributed system with multiple paths of Inquiry and Trial Culture of Inquiry & Entrepreneurship Entrepreneurship-friendly Business Environment Distribution of research portfolio can cause gaps & shortfalls, and can reduce the impact of R&D investments Political myths about the primacy of markets inhibit commercialization mechanisms Dominance of Military R&D, Capacity Constraints & Waste lowers return on R&D investments

9. 9 Presentation Topics Trends and Anomalies in US R&D Funding –Strong Aggregate Commitments –But Linkages to Commercial Realization are less robust Myths and Market Realities about the US Innovation System –Myth of Perfect Markets mean that Promising New Ideas are often not adequately funded –The Path to Commercialization is Complex Sustaining Innovation-Led Growth –Fostering an Enabling Business Environment –Government Awards to Spur Growth: The SBIR Model –Innovation Transfer from Universities Concluding Points

10. 10 Trends & Anomalies in U.S. R&D Funding The Good News and the Bad News

11. 11 Strong U.S. Commitment to R&D Shares of Total World R&D, 2001 Total World R&D = $746.7 billion U.S. share = $276 billion EU share = $187 billion Source: OECD Main S&T Indicators, 2004; AAAS, 2004 Calculated using purchasing power parities, Jan 2004

12. 12 Trends in U.S. R&D Funding There is Good News, but… Total R&D is Rising (but Federal R&D Spending is flat )

13. 13 U.S. Industry and Federal R&D: 2000 Industry R&D is More Focused on Development than Basic or Applied Research Source: AAAS Expenditures in Billions of U.S. Dollars

14. 14 More Good News Public Research has Surged in Health: A National Decision to Increase our Bet Source, AAAS, 2003

15. 15 Trends in U.S. R&D Funding The Bad News: An Uneven Record Changes in Federal Research Obligations for All Performers and University/College Performers FY 1993–1999

16. 16 The Really Bad News Random Disinvestment: Real Declines for Research in Physics, Chemistry, & Engineering Risk a Lag Effect FY 1993–1999; constant 1999 dollars

17. 17 Anomalies in R&D Funding in U.S. Innovation System R&D Investments in IT-Related Disciplines Dropped in Real Terms in the 1990s –Yet, IT Innovation is the Main Driver of U.S. Productivity Surge Investments in Biomedicine are Up –But complementary IT investments are needed to capitalize on biomedical progress Super Computers needed for DNA Analysis Imaging Technologies and Diagnostics rely on IT advances Multi-disciplinary Approaches, e.g., Bioinformatics are required

18. 18 Criticisms of the U.S. Innovation System Overall R&D Spending is Inadequate –Insufficient R&D investment in the future –2% in the 1960’s—now 0.8% of GDP Too Much Concentration on Military R&D – 52% –Low-utility for civilian economy –Slow or No spin-out for most R&D investments Too Much Focus on Health Research at NIH and Not Enough on the Necessary Information Technologies –Surge in Bio-terrorism funding faces capacity constraints Inadequate Commercialization Mechanisms –Ideological/political blockages for effective programs –U.S. myths about perfect markets and role of venture capital prevent effective policy making –U.S. programs are too few and under-funded

19. 19 Policy Myths & Market Realities The Myth of Linear Innovation The Myth of Military Spin-Offs The Myth of Perfect Markets The Myth of the Venture Capital Solution

20. 20 Reality: Innovation is a Complex Process –Major overlap between Basic and Applied Research, as well as between Development and Commercialization –Principal Investigators and/or Patents and Processes are Mobile, i.e., not firm-dependent –Many Unexpected Outcomes –Technological breakthroughs may precede, as well as stem from, basic research The Myth of the Linear Model of Innovation Basic Research Applied Research Development Commercialization Myth: Innovation is a Linear Process

21. 21 Basic Research Applied Research Development Commercial- ization Quest for Basic Understanding New Knowledge Fundamental Ideas Potential Use Application of Knowledge to a Specific Subject “Prototypicalization” Development of Products Goods and Services Feedback: Market Signals/ Technical Challenge Desired Product Alterations or New Characteristics Cost/design trade-off Feedback: Applied Research needed to design new product characteristics Feedback: Basic Research needed for discovery Search for new ideas and solutions to solve longer-term issues New Unanticipated Applications Non-Linear Model of Innovation

22. 22 The Myth of Military Spin-Offs Euro Myth: “U.S. Defense Research/Procurement Directly Funds Civilian Technologies” Reality: “Very few technologies proceeded effortlessly from defense conception to commercial application.” –Secrecy, military specs, and long lead times slow diffusion of new defense technologies Billions for Stealth Technologies: What civilian market ? –Even efforts to use low-cost civilian technologies for defense use, i.e., “spin-ins,” are often blocked by complicated military procurement system Beyond Spin-off, John Alic, Lewis Branscomb, et al.

23. 23 The Myth of Military Spin-Offs Defense Industry Contracted Sharply in Ten Years after End of Cold War –Major American Contractors dropped from 15 to 5 –Industry is detached from mainstream U.S. economy –Dedicated programs with limited spin-off now compounded by long-term, slow moving contracts Defense R&D Funds Concentrated on Small Number of Engineers with Strong Applied Focus –Issue of scale: Intel at $100 Billion value vs. top three defense groups combined is $50 Billion Spin-Off of Platform Technologies is Diffused –Semiconductors and Internet applied widely –Engines and Airframe: Spillovers are substantial

24. 24 The Myth of Perfect Markets Strong U.S. Myth: “If it is a good idea, the market will fund it.” Reality: –Potential Investors have less than perfect knowledge, especially about innovative new ideas –“Asymmetric Information” leads to suboptimal investments This means that it is hard for small firms to obtain funding for new ideas

25. 25 Federally Funded Basic Research Creates New Ideas Applied Research & Innovation Capital to Develop Ideas No Capital Reality: The Valley of Death Early-Stage Funding Gap To Innovation

26. 26 The Valley of Death A Series of Gaps –Gap in Available Cash Necessary to develop technology to Proof of Principle, Prototype, and/or Product –Gaps in Information between Entrepreneur and potential Investor and Partner about Technology—What is it? Potential of Technology—What can it do? Business Opportunity—What size market?

27. 27 The Cash Flow Valley of Death Technology Creation Technology Development Early Commercialization Cash Flow Federal Agencies, Universities, States Entrepreneur & Seed/Angel Investors IPO Time Cash Flow Valley of Death Successful Moderately Successful Unsuccessful Typical Primary Investors Venture Capitalists SBIR & ATP Adapted from: L.M. Murphy & P. L. Edwards, Bridging the Valley of Death—Transitioning from Public to Private Sector Financing, Golden CO: National Renewable Energy Laboratory, May 2003

28. 28 The Myth of U.S.Venture Capital Markets Myth: “U.S. VC Markets are broad & deep, thus there is no role for government awards” Reality: Venture Capitalists have –Limited information on new firms –Prone to herding tendencies –Focus on later stages of technology development –Most VC investors seek early exit Large U.S. Venture Capital Market is Not Focused on Early-Stage Firms

29. 29 Sustaining Science-Based Growth Firm Creation & Job Growth

30. 30 Basic Research and Small Companies Drive Science-Based Growth Basic Research is Key in Supplying a Steady Stream of “Fresh and New” Ideas –Ideas, if Effectively Transferred to the Private Sector, can become Innovations Basic research is Essential, but not Enough –Innovations can become Commercial Products driving Growth—with the Right Policy Support Developing Incentives to spur Innovative Ideas for New Products is a Central Policy Challenge –Small Companies are Key Players

31. 31 Importance of Small Businesses to the U.S. Economy Small Businesses are a Key Driver of the U.S. Knowledge-Based Economy –Generating 60% to 80% of Net New Jobs Annually 2.5 million of the 3.4 million Total Jobs—1999- 2000 Employs 39% of High-Tech Workers—Scientists, Engineers, Computer Workers –Producing 14 times more Patents per Employee than Large Patenting Firms Patents are of High Quality Twice as Likely to be Cited

32. 32 Small Businesses… Grow Jobs Generate Taxable Wealth Create Welfare-Enhancing Technologies Transform the Composition of the Economy, Developing Products to Ensure our Well-Being and Productivity in the Future This is Why we Punish Them!

33. 33 Challenges Facing Small Firms in the United States: Regulation & Finance SME’s Face High Regulatory Burdens –Very small firms (less than 20 employees) spend 60% more per employee than large firms to comply with federal regulations New Firms Struggle for Adequate Financing –Start-Up funds from “Friends, Family, and Fools” –Over 80% of small firms in U.S. rely on credit but banks hesitate to lend

34. 34 VC Markets More Risk Averse Source: PriceWaterhouseCoopers/Venture Economics/National Venture Capital Association Money Tree Survey, 2004

35. 35 Breakdown of U.S. Venture Capital by Stage of Development-2001 $799 million Source: PricewaterCoopers, Venture Economics, National Venture Capital Association, 2003 Total= $41.284 billion

36. 36 Breakdown of U.S. Venture Capital by Stage of Development-2003 Startup/Seed $354.3 million Total = $18.2 billion

37. 37 Why Do Funding Gaps Matter? Because Equity-Financed Small Firms are a Leading Source of Growth in Employment in the United States Equity-Financed Small Firms are One of the Most Effective Mechanisms for Capitalizing on New Ideas and Bringing Them to the Market –Audretsch and Acs

38. 38 Significance of Pubic Support for Early-Stage Technology Development Collapse in Venture Funding Revealed Importance of Other Sources of Early-Stage Finance

39. 39 New Research: U.S. Funding Sources for Early- Stage Technology Development Branscomb & Auerswald, Between Invention and Innovation An Analysis of Funding for Early-Stage Technology Development, NIST, 2002 Multiple Actors * Multiple Sources of Finance Focused on Different Stages * Government Role is Significant

40. 40 Surprising Role of U.S. Government in Early-Stage Technology Development Markets for Allocating Risk Capital to Early- Stage Technology Ventures are not Efficient Most Early-Stage Funding comes from –Individual “Angel” investors, –Corporations, and –Federal Government –Not Venture Capitalists! Federal Technology Development funds Complement Private Funds –More important than we thought

41. 41 U.S. Entrepreneurial Environment A Key to Knowledge-Based Growth Sources and Limitations  Drive for Ownership: High Rates of Business Formation –High Social Value placed on business success –Low penalties for failure: Gentle Bankruptcy Laws  Low Regulatory barriers for entry –Ease of company formation –Access to early-stage financing—very important –Pace of activity increases the effective value of capital

42. 42 U.S. Policy Framework Strong but Uneven R&D Commitment Spending Helps: Record funding for federal R&D: FY 2005 R&D=$131.9billion –DoD R&D up 6.7% to $69.9 Billion But funding for basic research remains flat –NIH has doubled over five years to $28.8 Billion –NSF to increase to $5.7 Billion –DOE to increase to $8.9 Billion –DHS rapidly expanding to $1.2 Billion Problems with expenditure Large increases in R&D funding for weapons development and homeland defense, but flat or declining funding for the rest of the R&D portfolio Focus on military development misstates figures and reduces return on R&D portfolio

43. 43 Positive Policy Framework: Microeconomic Incentives Positive Incentives for Entrepreneurs –Strong Intellectual Property Regime: Personal Incentive for Invention –Tax Policy: Potential High Returns are the Best Incentive for High Risks –Regulatory Policy: Low Regulation for New Entrants = Lower Cost, Faster to Market –Labor Flexibility: Hire and Fire as Needed Firms that Can’t Fire, Will not Hire (or Invest ) Good Goals do not Guarantee Good Policy

44. 44 Positive Policy Framework : Intermediating Institutions Public-Private Partnerships Innovation Awards —SBIR, ATP S&T Parks University-Industry Clusters Industry Consortia

45. 45 U.S. Policies for Innovation-Led Growth Government Awards to Spur Innovation-Led Growth: SBIR

46. 46 Programs to Bridge the Valley of Death Total Allocated Resources Uncertainty and Distance to Market Prototype Product development Commercialisation Strategic research Curiosity research Applied research Capital Allocation Curve The Financial “Valley of Death” The Focus of SBIR and ATP Seed: Angel Investors Expansion 1st Round VC 2nd Round VC Business development Investment Startup: Friends, Families & Fools Need for Supportive Policy Framework SBIR  Procurement ATP Pre 2002

47. 47 U.S. Innovation Curve Total Allocated Resources Uncertainty and Distance to Market Prototype Product development Commercialisation Curiosity research Strategic research Applied research Capital Allocation Curve The Financial “Valley of Death” The Focus of SBIR and ATP Seed: Angel Backers Expansion 1st Round VC 2nd Round VC Business development Investment Startup: Friends, Families & Fools Need for Supportive Policy Framework SBIR  Procurement and ATP are More Important Post 2002

48. 48 The SBIR Program Created in 1982, Renewed in 1992 & 2001 Participation by all federal agencies with an annual extramural R&D budget of greater than $100 million is mandatory –Agencies must set aside 2.5% of their extramural R&D budgets for small business awards Currently a $2 billion per year program –Largest U.S. Partnership Program

49. 49 SBIR: Critical Source of Predictable Funding for Early-Stage Finance SBIR—Main Source of Federal Funding for Early-Stage Technology Development SBIR over 85% of Federal Financial Support for Early- Stage Development SBIR over 20% of Funding for Early- Stage Development from all sources *Estimate of Federal Government Funding Flows to Early-Stage Technology Development—Based on total funding for ATP, SBIR & STTR programs by Branscomb and Auerswald 2002 * SBIR

50. 50 SBIR Model PHASE I Feasibility Research PHASE III Product Development for Gov’t or Commercial Market Private Sector Investment Tax Revenue Federal Investment PHASE II Research towards Prototype Social and Government Needs $750K$100K R&D Investment

51. 51 SBIR: Goals Vary Among Agencies Multiple Program Goals –Commercialization and Research Multiple Agency Goals –NIH Research Tools, Medical Devices, Drug Development, and Audio-Visual Health Materials –DOD Special Forces Equipment Neural Network Processors for remotely piloted jets Wireless Communications for Divers Low-cost, High-performance Drones

52. 52 SBIR Differs Among Agencies Multiple Administrative Systems –Each agency typically has its own manner of choosing awardees and screening applications –Different metrics reflecting unique agency missions and needs –Different Metrics by industrial sector, e.g., software vs. drug development vs. weapon components Commendable Flexibility & Diversity Not Harmonization!

53. 53 SBIR’s Attraction to Policy Makers Catalyzes the Development of New Ideas and New Technologies Capitalizes on Substantial R&D Investments No Budget Line —stable program Addresses Gaps in Early-Stage Funding for Promising Technologies Attractive to Small Firms —political support Certification Effect —government endorsement of technical quality

54. 54 SBIR’s Attraction to Entrepreneurs Features that Make SBIR Grants Attractive include: –No dilution of ownership –No repayment required –Grant recipients retain rights to IP developed using SBIR funds –No royalties are owed to government –Certification effect for technology/firm

55. 55 Contributions of SBIR to the Nation Provides a Bridge between Small Companies and the Agencies, especially for Procurement Contributes New Methods and New Technologies to Government Missions Provides a Bridge between Universities and the Marketplace Encourages Local and Regional Growth, increasingly through the University connection Creates jobs and justifies R&D investments to the general public

56. 56 Contributions of SBIR Concept Catalyzes the Development of New Ideas and New Technologies Capitalizes on Substantial U.S. R&D Investments Addresses Gaps in Early-Stage Funding for Promising Technologies Certification Effect—Government Endorsement of Technical Quality

57. 57 The Enabling Role of Universities A Major U.S. Asset

58. 58 University-Industry Cooperation is Key Cooperative Research –University research draws ideas from commercial trends more than ever before –Feedback loops from industry to universities are important –Major contribution to training for real jobs Regional Growth –Regional economies need their research universities more than ever before Firm Formation –University innovation + early government funding have been key to the growth of many successful technology companies Supportive University Culture & Incentives are crucial

59. 59 How Ideas are Commercialized Transferring University Technology to Firms RESEARCH $$ INVESTMENT $$ SALES $$ UNIVERSITY COMMERCIAL COMPANY NEW PRODUCTS & PROCESSES INNOVATION License Agreement or Equity Licensing to existing companies – brings royalty $ New company formation – brings royalties and/or equity Other, less direct, contributions to regional economic activity – 5,000 Good New Jobs in Pittsburgh Area ROYALTIES or EQUITY PAYOUT SBIR Drawn from C. Gabriel, Carnegie Mellon University

60. 60 The Benefits of University-Industry Cooperation: SBIR Role SBIR Innovation Awards Directly Cause Researchers to create New Firms –Jobs and Regional Growth –Cooperation creates High-Tech Jobs Universities help diversify and grow the job base –Increasingly universities are the largest regional employer for all types of employment Cooperation validates Research Funding –Returns to Society in Health, Wealth, & Taxes –SBIR is a proven mechanism in an uncertain game

61. 61 Changing Role of Universities Their Role is Important and Changing Universities’ Economic Contributions –Idea Creation: Basic & Applied Research Effective University Leadership and Supportive Policies Make Universities –Poles for Growth of High-Tech Clusters –Centers for Employment of All Types

62. 62 To Make the University a Nexus of Growth Requires Real Changes in –Culture and Values: This requires new leadership and new incentives –Status of Professors: permissive environment to encourage innovations, collaboration with industry, and pursuit of innovation awards and wealth –Institutional Practices: Parallel research institutes with self-select mechanism

63. 63 Incentives and Impacts in the U.S. University Model Structure –Multiple sources of funding –Different Types of Institutions for different needs –High cost tuition for private schools; State schools $3,500 to $6,000 per year –Significant Student funding of studies –Many needs-based scholarships provided –Licensing obstacles to technology transfer Characteristics –Curriculum responsive to market needs—ie, industry –Adaptable, Differentiated programs for students –High range of student choice –High percentage of class attendance & participation –High percentage of college-age cohort attending –Globally high returns to R&D investments, but –Analytically suboptimal returns to public investments in university research

64. 64 Incentives in the European University Model Structure –Centrally managed University budgets –Faculty are Civil Servants –Student fees paid by the State –Centralized State funding –No University Endowments Characteristics –Curriculum not responsive to market needs nor scientific opportunity –Faculty job security means little incentive to innovate –Low levels of Student engagement; don’t seek ‘money’s worth’ –Lack of financial autonomy limits Universities’ flexibility, adaptability & accountability –Fewer new initiatives

65. 65 Consequences of the U.S. Model The US system is more demand driven, and therefore more adaptable –Multiple private participants, not state controlled No single model for higher education –Transfers allows upward mobility across institutions for bright students from different socio-economic backgrounds Research is often focused on problem-solving rather than pure theory Tax laws encourage cooperation with industry –Donations of building and endowments

66. 66 Characteristics of Successful University-Industry Partnerships University-Industry Cooperation involves: –Complementary Objectives, Mutual Respect –Active, Routine Communication for Cross-pollination of ideas Growing Perception of University as Major Regional Economic Player –SBIR brings Research out to the Market –SBIR links Universities, Small Companies, and Large Companies

67. 67 Concluding Points

68. 68 Understanding Innovation Ecosystems National Innovation Systems are Different in Scale and Flexibility –Flexibility is a differentiator –It is less how much is spent but how well All Systems Have Common Challenges –Need to justify R&D expenditures by creating new jobs & new wealth –Need to reform institutions (or invent new ones) –Need to recognize that project failure does not equal program failure Linkages strengthen Innovation Ecosystems –E.g., SBIR draws together small businesses, universities, and government agencies

69. 69 Lessons from the US Innovation System The US Innovation System is one of the most productive in the world –Its first lesson is its diversity of approaches; there is no one right answer and no one right model What we do know is that centrally planned and funded technology development programs and University systems work less well –Uniformity of approach is not equality of opportunity User driven systems are more responsive –Therefore students & industry should be involved in decisions and share costs in the cooperative efforts of education and innovation

70. 70 Lessons from the US Innovation System What does this mean in practice? –Universities should be allowed to differentiate to meet different market needs in training, education & cooperation with industry –To do this, universities need financial autonomy, incentives to cooperate with industry, and strong local rewards –Awards to industry (and universities) should be competitive, limited in size and duration, and be performance based

71. 71 Lessons from the US Innovation System Most important, a powerful institutional mechanism, e.g., a Science, Technology, and Innovation Council, is often needed to adjust the innovation system to new needs, and new opportunities, while drawing on best practice and encouraging diversity. Mechanisms like SBIR can change behavior in Universities & Labs while addressing the Early Stage Funding Gap Close cooperation with strong innovation systems, e.g., the U.S. and European nation states, should be pursued to acquire resources & network advantages

72. 72 THANK YOU Charles W. Wessner, Ph.D. Board on Science, Technology, & Economic Policy National Research Council 500 Fifth Street NW Washington, D.C. 20001 cwessner@nas.edu Tel: 202 334 3801 http://www.nationalacademies.org/step