Building Innovation Clusters Innovation Heatmap André Andonian March 14, 2010 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of Mc. Kinsey & Company is strictly prohibited
The emergence and growth of innovation clusters are of tremendous interest for both, governments and companies What attributes are critical to establish an innovation cluster? ▪ What are my region's current strengths/weaknesses and ‘bottlenecks’? ▪ Which industries are most suited for the region’s advantages, and how can we attract anchor companies? SOURCE: Mc. Kinsey Innovation Heatmap SUPPLY SIDE ▪ Companies DEMAND SIDE Governments and policy makers ▪ 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? Mc. Kinsey & Company | 1
Motivation: Innovation is an unparalleled driver of economic well-being and growth Innovation and GNI per capita are significantly correlated GNI per capita 1, USD 50, 000 40, 000 30, 000 Innovation is a major driver of growth, economic value creation and population wellbeing R 2 : 63% 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 innovation 2 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, Mc. Kinsey Innovation Heatmap Mc. Kinsey & Company | 2
Alignment: Innovation is more than creativity – occurs along a value chain $$$ Ideation Basic Research Applied Research Implementation Engineering/ Development Business Creation Critical Skills Creative and scientific Entrepreneurial and engineering Sample Levers • Universities and R&D centers • Quality of education • Access to global culture • Availability of credit • Local supplier quality • Entrepreneurial culture Possible Proxy Indicators • Patents, journal publications, royalties and license fees • Employment or manufacturing output in innovation intensive/noncommodity sectors SOURCE: Mc. Kinsey Innovation Heatmap Initiative Commercialization Initial Market Commercial Entry Scaling Business development, and marketing • IP protection • Access to markets • Distribution channels • Sector-specific economic value added • Proportion of economic value added from new products or services • Value of local brands Mc. Kinsey & Company | 3
Innovation clusters can be in one of five different stages Nascent ▪ Regions with limited innovation output Hot Spring ▪ ▪ ▪ Dubai, UAE Fushan, China Istanbul, Turkey SOURCE: Mc. Kinsey ▪ ▪ ▪ Dynamic Ocean 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 ▪ Shanghai, China Bangalore, India Shenzen, China ▪ ▪ ▪ Silent Lake 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 ▪ Silicon Valley, US San Francisco, US Taipei, Taiwan ▪ ▪ ▪ Shrinking Pool 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 ▪ Seattle, US Tokyo, Japan Munich, Germany ▪ ▪ Shrinking innovation ecosystem Unable to broaden their areas of activity as their narrow sectors become less innovation driven and increasingly commoditized Cincinnati, US Liverpool, UK Philadelphia, US Mc. Kinsey & Company | 4
The innovation crown is still the US’s to lose Cluster size Patents granted, 1997 - 2008 High HOT SPRINGS Bangalore Shenzhen DYNAMIC OCEANS Shanghai Hong Kong Seattle Momentum 1 Austin Bristol Taichung Taipei Silicon Valley Seoul San Diego San Francisco Yokohama Chicago Tokyo NASCENTS Pittsburgh 0 Boston New York Rochester Newark Low Los Angeles SILENT LAKES Chicago SHRINKING POOLS Low High Diversity 2 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); Mc. Kinsey & Company | 5
To develop innovation clusters enablers along 5 dimensions need to be addressed Public & private spend on infrastructure Infrastructure. Availability and related quality of transportation, laws & communication and regulation utility infrastructure Venture capital Availability of public and private funding Human capital Availability of talent External Immigration laws Internationality SOURCE: Mc. Kinsey Innovation Heatmap Equity market Financial capital Size and type of local demand Customer sophistication Strategic location Drivers for enablers Subsidies Companies and research institutes Local demand EXEMPLARY Business environment Efficiency & effectiveness of business processes and networks Social aspect of talent Local Demographics Education system Social infrastructure Credit/ loans FDI Business laws & regulation IP laws Cluster promotion Business support services Economic & political stability Soft enablers ▪ Creativity ▪ Risk appetite ▪ Balance of cooperation ▪ Attitude towards wealth accumulation Mc. Kinsey & Company | 6
Hot Springs develop and reach critical size faster than ever before. . . Time taken for clusters to reach critical size 1 1971 1985 Israel 14 years 1994 2000 Singapore 6 years 2002 2006 Bangalore 4 years 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), Mc. Kinsey & Company Mc. Kinsey | 7
Within the 5 dimensions the importance of single enablers varies depending on the cluster development stage Focus for nascent clusters 75% Average 25% Shrinking Pools Silent Lakes Dynamic Oceans Hot Springs Nascent Shrinking Pools Silent Lakes Availability of VC funds 3 Dynamic Oceans Availability of talent 2 Hot Springs Quality of communication infrastructure 1 Nascent Clusters need to ramp up these enablers in later development stages to transition to the "dynamic ocean" stage passing the typical stalling point Shrinking Pools Clusters need to continuously update these enablers to transition to the next development stage Silent Lakes Clusters need to achieve threshold value in early development stages to transition to next development stages Dynamic Oceans 3 World-class differentiators Hot Springs 2 Proportional enablers Nascent 1 Threshold enablers 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); Mc. Kinsey & Company | 8
There are three forces changing the global distribution of global talent 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 talent due to changing tasks, organizational environments, and generational value shifts SOURCE: Mc. Kinsey Innovation Heatmap Mc. Kinsey & Company | 9
US’ innovativeness benefits strongly from foreign talent US patent applications contributed by foreign ethnics* Percent Electrical Computers Chemicals Drugs Mechanical Other 1975 80 85 90 95 * Based on last name search statistics SOURCE: USPTO; Bill Kerr (Harvard University); Mc. Kinsey & Company 2000 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 2004 Mc. Kinsey & Company | 10
Relative attractiveness for superior talent has deteriorated Foreign students in higher education in host countries, 2001 - 07 Percent 100% = 1, 159 US 47 1, 303 1, 363 1, 431 1, 469 1, 523 1, 560 43 40 38 37 36 45 thousand ▪ 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 Peer. Group * 2001 02 03 * Germany, Australia, UK, Canada SOURCE: Euro monitor; Mc. Kinsey & Company 04 05 06 2007 Mc. Kinsey & Company | 11
BACKUP Mc. Kinsey & Company | 12
Defining innovation: more than just new technology High SUBSTANTIAL ▪ 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 Technology Novelty ▪ Evolutionary extension or improvement of core business, moving up the Scurve ▪ Drives near-term growth of the core with attractive risk/reward Examples – Vanilla Coke, Mercedes S class INCREMENTAL Low BREAKTHROUGH ▪ 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 ▪ 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 TRANSFORMATIONAL 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 Mc. Kinsey & Company | 13
New innovation clusters typically emerge as a result of three processes: Heroic Bet, Irresistible Deal, or Knowledge Oasis Strategy "Heroic Bets" "Irresistible Deals" "Knowledge Oases" Description Example clusters 1 Typical challenges 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) ▪ 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) ▪ 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) ▪ ▪ ▪ Often difficult to identify target sectors top-down Difficult to create non-distorting subsidies Issues with transition from initial support phase Ensuring knowledge transfer to local ecosystem Transitioning the mix of labor skills toward higher value added activities Infrastructure stress due to uncoordinated growth Difficulties crossing the 'implementation chasm' by attracting sufficient capital and world class managerial talent Avoiding the scalability wall as critical technologies mature 1 Cluster strategies are not exclusive - clusters are often developed by pursuing multiple strategies SOURCE: Mc. Kinsey & Company | 14
2. . . in later stages diversification across the value chain and across industries is crucial to make the cluster self-sustainable Absolute number of patents filed Split of technologies of patents granted in California, USA Percent 1970 19* 2005 Industries that are just beyond their peak 59 5, 966 Industries that are shrinking for decades Chemicals, photocopying 14 Status of industry Textiles, heavy industry, printing 8 Industries Optical communications, digital processing systems, molecular biology Growing industries 7 11 Electrical conductor technology, optics Industries that remain constant 6, 946 19, 181 Selfsustainable clusters jump on new industries to compensate for shrinking ones 21 SOURCE: Mc. Kinsey Innovation Heatmap, USPTO Mc. Kinsey & Company | 15
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