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The Innovation Continuum: Moving Promising Technologies off the Shelf Genome Canada GPS Policy Brief Canadian Science Policy Conference Calgary, November.

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Presentation on theme: "The Innovation Continuum: Moving Promising Technologies off the Shelf Genome Canada GPS Policy Brief Canadian Science Policy Conference Calgary, November."— Presentation transcript:

1 The Innovation Continuum: Moving Promising Technologies off the Shelf Genome Canada GPS Policy Brief Canadian Science Policy Conference Calgary, November 5, 2012 Professor Jeremy Hall Beedie School of Business Simon Fraser University Editor-in-Chief Journal of Engineering and Technology Management Professor Jonathan Linton Power Corp Professor for the Management of Technological Enterprises, Institute for Science, Society and Policy, University of Ottawa Editor-in-Chief Technovation: the Journal of Technological Innovation, Entrepreneurship and Technology Management 1

2 Context Increased emphasis on publically funded research for invention, leading to commercialization for societal benefits – How can new scientific endeavours be commercialized to provide societal benefits? – How can we get promising technologies from public research off the shelf? Science-based innovation is a complex process involving different individuals throughout cycle, where individuals variously enter and exit (Langford et al, 2006) High heterogeneity in knowledge; heuristics to exploit opportunity (Hall and Martin, 2005) 2

3 Context Scientific/technical knowledge migrate across institutional boundaries through (Reamer et al, 2003) – Cooperative research and development – Licensing or sale of intellectual property (IP) and spin-offs – Technical assistance – Information exchanges – Hiring skilled people Idiosyncratic, context dependent Currently available indicators for university research outcomes ‘blurs’ the idiosyncrasies and unique path dependencies (Langford et al, 2006) 3

4 Context: Genome Canada Research Increasingly moving beyond discovery research towards “translation of discoveries” for the global bioeconomy (Halliwell and Smith, 2011) – Not just medical but also industrial applications – including: manufacturing, chemicals, bioremediation, biomonitoring tools and biofuels (Sheppard et al, 2011) – More integrated GE3LS research Consistent with recent discourse on more reflexive, interactive approach to innovation rather than linear “technology push” (Nightingale, 2004; Guena et al, 2003) Costs of greater integration? 4

5 Key issue: A need to understand heterogeneous, idiosyncratic features of innovation Heuristics, incentives differ among key technology developers, users, other stakeholders – Insights from wide range of stakeholders needed, but… – Adds complexity; ambiguity, e.g. difficult to identify salient stakeholders, their interests, heuristics (Matos and Hall, 2007. Industrial setting plays key role in whether a public technology will be sought out and commercialized by firms – Some actively monitor, engage with university researchers (e.g. pharmaceuticals), most industries more passive Are technology transfer offices, scientists, early developers adequately prepared to manage relationships with passive industry players? 5

6 Theoretical Underpinnings The Challenges of New Product Development Clark and Wheelwright Number of new ideas ConceptCommercialisation 6

7 The Challenges of New Product Development Clark and Wheelwright Number of new ideas ConceptCommercialisation Ability to influence outcome 7

8 The Challenges of New Product Development Clark and Wheelwright Number of new ideas ConceptCommercialisation Ability to influence outcome Actual management activity 8

9 ‘Contemporary’ Development Funnel Clark and Wheelwright Technology Assessment & Forecasting Market Assessment & Forecasting Development goals & objectives Aggregate project plan Project mgmt & execution Post-project learning & improvement Technology Strategy Product/Market Strategy 9

10 Technological Uncertainties Development goals & objectives Aggregate project plan Project management & execution Post-project learning & improvement Commercial Uncertainties Organizational Uncertainties Social Uncertainties Exogenous technological developments, market trends, global financial conditions, etc. that affect cognitive legitimization processes Social trends, legal issues, controversies etc. that affect socio-political legitimization processes TCOS Framework 10

11 Typology of Innovative Uncertainties Hall and Martin, 2005; Matos and Hall, 2007; Hall et al, 2011 1.Technological uncertainty: Does it work? Domain of scientists, engineers 2.Commercial uncertainty Is it commercially viable? Domain of marketing, business analysts 3.Organisational uncertainty Will your organisation accept/adopt the technology and appropriate the benefits? Domain of the strategists, business development experts 4.Social Uncertainty Is it acceptable to civil society? Domain of ?? 11

12 The TCOS Framework (Hall et al, 2011) Paradigmatic issues Kuhn, 1962  Creative destruction (Schumpeter, 1934, 1942)  Changes in selection environments; breaking org. routines & heuristics (Nelson & Winter, 1982)  Competency-enhancing vs. destroying innovation (Abernathy & Clark, 85; Henderson & Clark, 1990)  Impact on innovation value-added chain (Afuah, 1998) ↓ Impact/Influence TCOS Uncertainties Hall & Martin, 2005 TechnologicalCommercialOrganizational Social Risk Characteristics Knight, 1921; Simon, 1959 Variables & interactions can be identified, probabilities estimated More variables (complexity), some not easily identified (ambiguity) Type of Legitimacy Aldrich and Fiol, 1994 CognitiveSocio-political Heuristics Popper, 1945, 1959 Conjecture – refutation Piece-meal social engineering 12

13 Organizational and Social Uncertainty Organizational uncertainty: can organization appropriate the benefits of the technology (e.g. Teece & Teece et al): –Org. capabilities, complementary assets, legal/institutional settings for IP protection (appropriability regime) determines who profits from the innovation Social uncertainty: how diverse secondary stakeholders may affect, or be affected by technology development –Differ from TCO uncertainties: more interacting variables (more stakeholders beyond value chain, some which may be difficult to identify - complexity and ambiguity) –Require different heuristics 13

14 TAIGA Forest Health: Forest Pathogen Detection and Monitoring Early detection/prevention best strategy for managing forest health, using new genomics-enhanced pathogen detection & monitoring tools for rusts, cankers leaf spots, root diseases Reg. agencies rely on visual inspection for known pathogens; proposed technology faster, more accurate Nurseries another potential market Potential market size unknown; certification regulations in flux While good for industry and society (socio-political legitimacy), may be resisted by individual stakeholders – Some firms may be proactive; others reactive 14

15 Forest biomass can replace petroleum through lignin-based polymers for aromatics, resins, carbon fibers, biofuels – Renewable; can reduce env. impacts – May affect forestry, chemicals, energy industries More efficient lignocellulose degradation via genomic/metagenomic approaches such as manipulating naturally occurring metabolic diversity of forest soil communities But… “You can make anything from lignin except money” – Regulatory pressures, increased concerns over non-renewable feedstocks provide socio-political legitimacy Promising products include lignin-based vanillin and resins Biocatalyst Lignin Transformation Technology 15

16 TCOS Uncertainty Analysis 16

17 TCOS Uncertainty Analysis 17

18 Implications Early Scanning Key for innovative success: early scanning of industry features and market dynamics, firm capabilities and appropriability issues, and potential social/env. impacts. Gatekeepers’ link between research team & environment: Technological gatekeepers Market gatekeepers Stakeholder gatekeeper The Role of Technology Transfer Offices: Passive versus active role, depending on industry Must move beyond medical (active) if translational model is to engage the bio-economy Training for heterogeneous skills? 18

19 Implications Opportunity Identification Early interaction reduces risks, plus identifies opportunities Enroll unanticipated users for future applications, identify opportunities otherwise beyond scope of initial project The role of the ‘gate-opener’ Temporary project structure/ short term funding, versus long term potential applications needed for translational model Learning Levers for Legitimization: New technologies compete against well established incumbents with scale economies (cognitive legitimacy) Effect of learning (Linton and Walsh, 2004) Social/env. attributes as lever - different value proposition based on social legitimacy, which can provide developers with time to improve technological and commercial attributes. 19

20 Implications The Cost of Translation While benefits are promising, there are also costs: – Increased transaction costs (finding industry partners, potential customers, consultations with more stakeholders) – IPM legal & admin costs – Increasingly demanding accountability/research ethics Individually all provide utility, but also time-consuming, requires skills, heuristics peripheral to lead researchers Schumpeterian vs. Kirznerian entrepreneurship - researchers creating new knowledge expected to take on larger share of the risks, admin under translational research, but currently not clear if rewards go to them or others Are we expecting too much from our scientists? 20

21 Acknowledgements TCOS Lab Contributors Senior Researchers (and co-authors of this brief): Drs. Stelvia Matos; Vern Bachor & Robin Downey Adjuncts: Dr. Mike Martin (retired); Dr. Bruno Silvestre (UofW) Students: Deb Farias; John Prpic Research Projects Genome Canada and Genome BC Studies Genomics-based forest health diagnostic and monitoring (PI: Richard Hamelin, UBC) Harnessing microbial diversity for sustainable use of forest biomass resources (PIs: Lindsay Eltis and Bill Mohn, UBC) SSHRC & others: Brazil studies on innovation & entrepreneurship in poor communities We would also like to acknowledge our colleagues Professors Edna Einsiedel and Cooper Langford, and special thanks to Karine Morin for organizing this session 21

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