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 ID: 139212
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The Innovation Continuum: Moving Promising Technologies off the ShelfGenome Canada GPS Policy BriefCanadian Science Policy Conference Calgary, November 5, 2012
Professor Jeremy HallBeedie School of Business Simon Fraser UniversityEditor-in-Chief Journal of Engineering and Technology Management
Professor Jonathan LintonPower Corp Professor for the Management of Technological Enterprises, Institute for Science, Society and Policy, University of OttawaEditor-in-ChiefTechnovation: the Journal of Technological Innovation, Entrepreneurship and Technology Management
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ContextIncreased emphasis on publically funded research for invention, leading to commercialization for societal benefitsHow 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) 2Slide3
ContextScientific/technical knowledge migrate across institutional boundaries through (Reamer et al, 2003)Cooperative research and developmentLicensing or sale of intellectual property (IP) and spin-offsTechnical assistance
Information exchangesHiring skilled people Idiosyncratic, context dependentCurrently available indicators for university research outcomes ‘blurs’ the idiosyncrasies and unique path dependencies (Langford et al, 2006)3Slide4
Context: Genome Canada ResearchIncreasingly 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 researchConsistent 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? 4Slide5
Key issue: A need to understand heterogeneous, idiosyncratic features of innovation Heuristics, incentives differ among key technology developers, users, other stakeholdersInsights 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 firmsSome actively monitor, engage with university researchers (e.g. pharmaceuticals), most industries more passiveAre technology transfer offices, scientists, early developers adequately prepared to manage relationships with passive industry players? 5Slide6
Theoretical UnderpinningsThe Challenges of New Product DevelopmentClark and Wheelwright
Number of new ideas
Concept
Commercialisation
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The Challenges of New Product DevelopmentClark and Wheelwright
Number of new ideas
Concept
Commercialisation
Ability to influence outcome
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The Challenges of New Product DevelopmentClark and Wheelwright
Number of new ideas
Concept
Commercialisation
Ability to influence outcome
Actual management activity
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‘Contemporary’ Development Funnel Clark and Wheelwright
Technology Assessment & ForecastingMarket Assessment & Forecasting
Development goals & objectives
Aggregate project plan
Project
mgmt
& execution
Post-project learning & improvement
Technology Strategy
Product/Market Strategy
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Technological Uncertainties
Development goals & objectives
Aggregate project planProject 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
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Typology of Innovative UncertaintiesHall and Martin, 2005; Matos and Hall, 2007; Hall et al, 2011Technological uncertainty:
Does it work? Domain of scientists, engineersCommercial uncertaintyIs it commercially viable? Domain of marketing, business analystsOrganisational uncertaintyWill your organisation accept/adopt the technology and appropriate the benefits? Domain of the strategists, business development expertsSocial UncertaintyIs it acceptable to civil society? Domain of ??11Slide12
The TCOS Framework (Hall et al, 2011)
Paradigmatic issues Kuhn, 1962Creative 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
Technological
Commercial
Organizational
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
Cognitive
Socio-political
Heuristics
Popper
, 1945, 1959
Conjecture – refutation
Piece-meal social engineering
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Organizational and Social UncertaintyOrganizational 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 innovationSocial uncertainty: how diverse secondary stakeholders may affect, or be affected by technology developmentDiffer from TCO uncertainties: more interacting variables (more stakeholders beyond value chain, some which may be difficult to identify - complexity and ambiguity)Require different heuristics13Slide14
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 diseasesReg. agencies rely on visual inspection for known pathogens; proposed technology faster, more accurateNurseries another potential marketPotential market size unknown; certification regulations in fluxWhile good for industry and society (socio-political legitimacy), may be resisted by individual stakeholdersSome firms may be proactive; others reactive14Slide15
Forest biomass can replace petroleum through
lignin-based polymers for aromatics, resins, carbon fibers, biofuels Renewable; can reduce env. impactsMay affect forestry, chemicals, energy industriesMore efficient lignocellulose degradation via genomic/metagenomic approaches such as manipulating naturally occurring metabolic diversity of forest soil communitiesBut… “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 resinsBiocatalyst Lignin Transformation Technology 15Slide16
TCOS Uncertainty Analysis
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TCOS Uncertainty Analysis
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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 gatekeeperThe Role of Technology Transfer Offices: Passive versus active role, depending on industryMust move beyond medical (active) if translational model is to engage the bio-economy Training for heterogeneous skills? 18Slide19
Implications
Opportunity IdentificationEarly interaction reduces risks, plus identifies opportunities Enroll unanticipated users for future applications, identify opportunities otherwise beyond scope of initial projectThe 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. 19Slide20
ImplicationsThe Cost of TranslationWhile benefits are promising, there are also costs: Increased transaction costs (finding industry partners, potential customers, consultations with more stakeholders)
IPM legal & admin costsIncreasingly demanding accountability/research ethics Individually all provide utility, but also time-consuming, requires skills, heuristics peripheral to lead researchersSchumpeterian 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? 20Slide21
Acknowledgements
TCOS Lab ContributorsSenior 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 ProjectsGenome Canada and Genome BC StudiesGenomics-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 communitiesWe would also like to acknowledge our colleagues Professors Edna Einsiedel and Cooper Langford, and special thanks to Karine Morin for organizing this session 21