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Building Innovation Clusters

Building Innovation Clusters. Innovation Heatmap. André Andonian March 14, 2010. CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited.

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Building Innovation Clusters

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  1. Building Innovation Clusters Innovation Heatmap André Andonian March 14, 2010 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited

  2. The emergence and growth of innovation clusters are of tremendous interest for both, governments and companies Governments and policy makers Companies • What attributes are critical to establish an innovation cluster? • What are my region'scurrent strengths/weaknesses and ‘bottlenecks’? • Which industries are most suited for the region’s advantages, and how can we attract anchor companies? • Where will I find the talent to develop the next generation of my products? • What regions are emerging as innovation hubs in my industry? • How can we promote the revitalization of clusters where we have our existing R&D locations? DEMAND SIDE SUPPLY SIDE SOURCE: McKinsey Innovation Heatmap

  3. , R2 : 63% Motivation: Innovation is an unparalleled driver of economic well-being and growth Innovation and GNI per capita are significantly correlated GNI per capita1,USD 50,000 40,000 Innovation is a major driver of growth, economic value creation and popu-lation well-being 30,000 20,000 10,000 0 0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 Capacity for innovation2 1 For 113 countries around the world for the 12 month period up to Oct 2009 2 WEF definition, proportion of licensed versus original technology SOURCE: OECD stat; WEF Executive Opinion Survey 2008/2009, McKinsey Innovation Heatmap

  4. Alignment: Innovation is more than creativity – occurs along a value chain $$$ Ideation Implementation Commercialization Basic Research Applied Research Engineering/ Development Business Creation Initial Market Entry Commercial Scaling Critical Skills Creative and scientific Entrepreneurial and engineering Business development, and marketing • Universities and R&D centers • Quality of education • Access to global culture • Availability of credit • Local supplier quality • Entrepreneurial culture • IP protection • Access to markets • Distribution channels Sample Levers • Patents, journal publications, royalties and license fees • Employment or manufacturing output in innovation intensive/non-commodity sectors • Sector-specific economic value added • Proportion of economic value added from new products or services • Value of local brands Possible Proxy Indicators SOURCE: McKinsey Innovation Heatmap Initiative

  5. Innovation clusters can be in one of five different stages Nascent Hot Spring Dynamic Ocean Silent Lake Shrinking Pool • Regions with limited innovation output • Small and fast growing innovation hubs • Strong industry focus and high reliance on a small number of companies • Strong focus rather on business model than on product innovations • Large and vibrant innovation ecosystems • Continuous creation and destruction of new businesses • Leading innovators and primary sectors change as the hub frequently reinvents itself through breakthrough innovations • Low growth innovation ecosystems • Narrow range of very large established companies that operate in a handful of sectors • Frequently the source of a steady stream of "evolutionary" innovations and step-by-step improvements • Shrinking innovation ecosystem • Unable to broadentheir areas of activity as their narrow sectors become less innovation driven and increasingly commoditized • Dubai, UAE • Fushan, China • Istanbul, Turkey • Shanghai, China • Bangalore, India • Shenzen, China • Silicon Valley, US • San Francisco, US • Taipei, Taiwan • Seattle, US • Tokyo, Japan • Munich, Germany • Cincinnati, US • Liverpool, UK • Philadelphia, US SOURCE: McKinsey

  6. The innovation crown is still the US’s to lose Cluster size Patents granted, 1997 - 2008 High Bangalore HOT SPRINGS DYNAMIC OCEANS Shenzhen Shanghai Taichung Hong Kong Taipei Seattle Silicon Valley Momen-tum1 Austin Seoul Bristol San Diego San Francisco Yokohama Chicago Tokyo NASCENTS SILENT LAKES Pittsburgh Boston Los Angeles 0 New York Chicago Rochester Newark SHRINKING POOLS Low Low High Diversity2 1 Growth of patents in a cluster per year from 1997 - 2008 2 Patents' industry and firm diversity in a cluster in 2008 SOURCE: Thomson Reuters; Juan Alcacer (Harvard University); McKinsey

  7. 1 Drivers for enablers To develop innovation clusters enablers along 5 dimensions need to be addressed EXEMPLARY Subsidies Public & private spend on infrastructure Venture capital Equity market Infrastructure Financial capital Credit/loans Infrastructure- related laws & regulation Availability and quality of transportation, Availability of public and private funding communication and utility infrastructure FDI Companies and research institutes Business environment Efficiency & effectiveness of business pro-cesses and networks Business laws & regulation IP laws Cluster promo-tion Business sup-port services Economic & political stability Local demand Size and type of local demand Customer sophistication Strategic location Human capital Availability of talent Social aspect of talent External • Immigration laws • Internationality Local • Demographics • Education system • Social infrastructure • Soft enablers • Creativity • Risk appetite • Balance of cooperation • Attitude towards wealth accumulation SOURCE: McKinsey Innovation Heatmap

  8. 1971 1985 Israel 14 years 1994 2000 Singapore 6 years 2002 2006 Bangalore 4 years Hot Springs develop and reach critical size faster than ever before... Time taken for clusters to reach critical size1 1 Defined as time required to increase from 50 to 200 patents per year SOURCE: USPTO; Strategic Review 2005; India's National Association of Software and Service Companies (NASSCOM), McKinsey

  9. 75% Focus for nascent clusters Average 25% Silent Lakes Silent Lakes Silent Lakes Hot Springs Hot Springs Hot Springs Dynamic Oceans Dynamic Oceans Dynamic Oceans Shrinking Pools Shrinking Pools Shrinking Pools Nascent Nascent Nascent Within the 5 dimensions the importance of single enablers varies depending on the cluster development stage 1 2 3 Threshold enablers Proportional enablers World-class differentiators Clusters need to achieve threshold value in early development stages to transition to next development stages Clusters need to continuously update these enablers to transition to the next development stage Clusters need to ramp up these enablers in later development stages to transition to the "dynamic ocean" stage passing the typical stalling point Quality of communication infrastructure1 Availability of talent2 Availability of VC funds3 1 Broadband subscribers per 1,000 people 2 Population with bachelors and higher, percent 3 Active VC funds per 1 million people SOURCE: Prequin; Shanghai University; Mastercard; Worldwide Centers of Commerce Index; US Census Bureau; Statistics of US Business (SUSB); McKinsey & Company

  10. Reverse talent flows with high short term mobility but lower stay ratio in the mid term Demographic shifts diminishing traditional population pools while new countries emerge with excess supply New talent paradigm New breed of talentdue to changing tasks, organizational environ-ments, and generational value shifts There are three forces changing the global distribution of global talent SOURCE: McKinsey Innovation Heatmap

  11. US’ innovativeness benefits strongly from foreign talent US patent applications contributed by foreign ethnics* Percent Electrical Computers While foreign-born account for just over 10% of the US working population, they represent 25% of the US science and engineering (SE) workforce and nearly 50% of those with doctorates Chemicals Drugs Mechanical Other 1975 80 85 90 95 2000 2004 * Based on last name search statistics SOURCE: USPTO; Bill Kerr (Harvard University); McKinsey & Company

  12. The US are still the leading country in terms of attracting foreign students • However, the dominant position is gradually changing and diverged to other countries Relative attractiveness for superior talent has deteriorated Foreign students in higher education in host countries, 2001 - 07Percent 100% = 1,159 1,303 1,363 1,431 1,469 1,523 1,560 thousand 36 37 38 40 43 45 US 47 Peer Group* 2001 02 03 04 05 06 2007 * Germany, Australia, UK, Canada SOURCE: Euro monitor; McKinsey & Company

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  14. SUBSTANTIAL TRANSFORMATIONAL INCREMENTAL BREAKTHROUGH Defining innovation: more than just new technology High • High investment in the next technology, S-curve to improve product or productivity • Drives long-term growth of core business • Examples – Flat-screen TVs, Intel Pentium processor, Google search • Creates a new market by offering new technology-enabled benefits • Also involves new value chains and business models, typically unattractive to incumbents • Examples – Telephone, automobiles, CAD, cell phones, airplanes, copiers Technology Novelty • New business model or set of practices, often with lower cost structure, offers other benefits to low-end consumers • Often pursued by attackers, ignored by incumbents ("innovator's dilemma"), requires new approach • Examples – Dell computer, Southwest Airlines, Wal-Mart • Evolutionary extension or improvement of core business, moving up the S-curve • Drives near-term growth of the core with attractive risk/reward • Examples – Vanilla Coke, Mercedes S class Low Low High Market Novelty Existing customers • Offers improvement along the existing basis of competition (usually performance) • Existing business models with current margins or better New customers • Changes the basis of competition by offering either new dimensions of performance or new benefits such as customization and convenience • New business models with lower cost structures and margins and different value networks Source: Adapted from C. Christensen's "The Innovator's Dilemma", team analysis

  15. Strategy Description Example clusters1 Typical challenges "Heroic Bets" Regions that are developed through large, government-led, targeted investment efforts (e.g., subsidies, tax holidays, direct investments) that focus on a specific promising sector and provide substantial initial support • Hsinchu Science Park (Taiwan) • Singapore • Dresden (Germany) • Often difficult to identify target sectors top-down • Difficult to create non-distorting subsidies • Issues with transition from initial support phase "Irresistible Deals" Regions that were able to attract established companies to capitalize on a significant local advantage (e.g., low cost of qualified labor, access to local markets) and then migrate up the value chain • Bangalore/ Hyderabad (India) • Penang (Malaysia) • Seoul (South Korea) • Ensuring knowledge transfer to local ecosystem • Transitioning the mix of labor skills toward higher value added activities • Infrastructure stress due to uncoordinated growth "Knowledge Oases" Regions with a critical mass of highly specialized talent (for instance, large research universities or government R&D lab) • "Route 128" (Massachusetts, US) • "Silicon Fen" (Cambridge, UK) • "Research Triangle" (North Carolina, US) • Difficulties crossing the 'implementation chasm' by attracting sufficient capital and world class managerial talent • Avoiding the scalability wall as critical technologies mature New innovation clusters typically emerge as a result of three processes: Heroic Bet, Irresistible Deal, or Knowledge Oasis 1 Cluster strategies are not exclusive - clusters are often developed by pursuing multiple strategies SOURCE: McKinsey

  16. 1 Absolute number of patents filed ... in later stages diversification across the value chain and across industries is crucial to make the cluster self-sustainable 2 Split of technologies of patents granted in California, USA Percent Industries Status of industry 1970 1990 2005 Textiles, heavy industry, printing Industries that are shrinking for decades Chemicals, photocopying Industries that are just beyond their peak Self-sustainable clusters jump on new indus-tries to com-pensate for shrinking ones Optical communi-cations, digital processing systems, molecular biology 59 Growing industries 8 21 Electrical conductor technology, optics Industries that remain constant 14 11 7 5,966 6,946 19,181 SOURCE: McKinsey Innovation Heatmap, USPTO

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