Building Innovation Clusters
Innovation Heatmap
André AndonianMarch 14, 2010
CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited
McKinsey & Company | 2
The emergence and growth of innovation clusters are of tremendous interest for both, governments and companies
SOURCE: McKinsey Innovation Heatmap
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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?
McKinsey & Company | 3
Motivation: Innovation is an unparalleled driver of economic well-being and growth
SOURCE: OECD stat; WEF Executive Opinion Survey 2008/2009, McKinsey Innovation Heatmap
1 For 113 countries around the world for the 12 month period up to Oct 20092 WEF definition, proportion of licensed versus original technology
GNI per capita1, USD
50,000
40,000
30,000
20,000
10,000
0
Capacity for innovation2
6.56.05.55.04.54.03.53.02.50
Innovation and GNI per capita are significantly correlated
R2 : 63%
Innovation is a major driver of growth, economic value creation and popu-lation well-being
McKinsey & Company | 4
Critical Skills
SampleLevers
PossibleProxy
Indicators
• Universities and R&D centers
• Quality of education• Access to global
culture
• IP protection• Access to markets• Distribution channels
• Availability of credit• Local supplier quality• Entrepreneurial culture
• Patents, journal publications, royalties and license fees
• Sector-specific economic value added
• Proportion of economic value added from new products or services
• Value of local brands
• Employment or manufacturing output in innovation intensive/non-commodity sectors
Creative and scientific
Business development, and marketing
Entrepreneurial and engineering
Alignment: Innovation is more than creativity – occurs along a value chain
SOURCE: McKinsey Innovation Heatmap Initiative
Ideation Implementation Commercialization
Basic Research
Applied Research
Initial Market Entry
Commercial Scaling
Business Creation
Engineering/ Development
$$$
McKinsey & Company | 5 SOURCE: McKinsey
Innovation clusters can be in one of five different stages
▪ Dubai, UAE
▪ Fushan, China
▪ Istanbul, Turkey
Nascent Hot Spring
▪ Shanghai, China
▪ Bangalore, India
▪ Shenzen, China
Dynamic Ocean
▪ Silicon Valley, US
▪ San Francisco, US
▪ Taipei, Taiwan
Silent Lake
▪ Seattle, US
▪ Tokyo, Japan
▪ Munich, Germany
Shrinking Pool
▪ Cincinnati, US
▪ Liverpool, UK
▪ Philadelphia, US
▪ 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 broaden their areas of activity as their narrow sectors become less innovation driven and increasingly commoditized
McKinsey & Company | 6
The innovation crown is still the US’s to lose
1 Growth of patents in a cluster per year from 1997 - 20082 Patents' industry and firm diversity in a cluster in 2008
SOURCE: Thomson Reuters; Juan Alcacer (Harvard University); McKinsey
Cluster size
Patents granted, 1997 - 2008
High
Diversity2
High
Momen-tum1
LowLow
0
Bangalore
Shenzhen
Shanghai
Silicon Valley
Tokyo
San Francisco
Taichung
Seattle
Seoul
Chicago
Los Angeles
Hong Kong
Rochester
Newark
Pittsburgh
San Diego
New York
Bristol
SILENT LAKES
DYNAMIC OCEANSHOT SPRINGS
SHRINKING POOLS
NASCENTS
Yokohama
Austin
Taipei
Chicago
Boston
McKinsey & Company | 7
To develop innovation clusters enablers along 5 dimensions need to be addressed
SOURCE: McKinsey Innovation Heatmap
Drivers for enablers
EXEMPLARY
Financial capital
Infrastructure
Local demandSize and type of local demand
Business environmentEfficiency & effectiveness of business pro-cesses and networks
Public & private spend on infrastructure
Customer sophistication
Strategic location
Business laws & regulation
IP laws
Cluster promo-tion
Business sup-port services
Economic & political stability
Human capital
Availability of talent
Social aspect of talent
Soft enablers
▪ Creativity
▪ Risk appetite
▪ Balance of cooperation
▪ Attitude towards wealth accumulation
Local
Demographics
Education system
Social infrastructure
External
Immigration laws
Internationality
Companiesand research
institutes
Equity market
Infrastructure- related laws & regulation
Availability and quality of transportation, Availability
of public and private funding
Credit/loans
FDI
Subsidies
Venture capital
communication and utility infrastructure
McKinsey & Company | 8
Hot Springs develop and reach critical size faster than ever before...
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
Israel
14 years
1971 1985
Singapore
6 years
1994 2000
Bangalore
4 years
2002 2006
Time taken for clusters to reach critical size1
McKinsey & Company | 9 N
asc
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Dyn
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Oce
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La
kes
Sh
rinki
ng
Po
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0
20
40
60
80
100
SOURCE: Prequin; Shanghai University; Mastercard; Worldwide Centers of Commerce Index; US Census Bureau; Statistics of US Business (SUSB); McKinsey & Company
Focus for nascent clusters
Threshold enablers1
Clusters need to achieve threshold value in early development stages to transition to next development stages
World-class differentiators3
Clusters need to ramp up these enablers in later development stages to transition to the "dynamic ocean" stage passing the typical stalling point
Proportional enablers2
Clusters need to continuously update these enablers to transition to the next development stage
10
20
30
40
50
0
20
40
60
80
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1 Broadband subscribers per 1,000 people2 Population with bachelors and higher, percent3 Active VC funds per 1 million people
Within the 5 dimensions the importance of single enablers varies depending on the cluster development stage
Quality of communication infrastructure1 Availability of VC funds3Availability of talent2
75%
25%
Average
McKinsey & Company | 10
New talent paradigm
Demographic shiftsdiminishing traditional population pools while new countries emerge with excess supply
New breed of talent due to changing tasks, organizational environ-ments, and generational value shifts
Reverse talent flowswith high short term mobility but lower stay ratio in the mid term
There are three forces changing the global distribution of global talent
SOURCE: McKinsey Innovation Heatmap
McKinsey & Company | 11
US’ innovativeness benefits strongly from foreign talent
10
15
20
25
30
35
40
Percent
Mechanical
Other
Computers
Electrical
Chemicals
Drugs
US patent applications contributed by foreign ethnics*
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
1975 80 85 90 95 2000 2004
* Based on last name search statisticsSOURCE: USPTO; Bill Kerr (Harvard University); McKinsey & Company
McKinsey & Company | 12
Relative attractiveness for superior talent has deteriorated
Foreign students in higher education in host countries, 2001 - 07Percent
▪ 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
53 55 57 60 62 63 64
1,560
36
06
1,523
37
05
1,469
38
04
1,431
40
03
1,363
43
02
1,303100% =
Peer
Group*
US
2007
45
2001
1,159
47
thousand
* Germany, Australia, UK, CanadaSOURCE: Euro monitor; McKinsey & Company
McKinsey & Company | 14
Defining innovation: more than just new technology
Existing customers▪ Offers improvement along the existing basis
of competition (usually performance) ▪ Existing business models with current
margins or better
Technology Novelty
High
Low
Market Novelty
Low 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
▪ 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
▪ 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
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
INCREMENTAL TRANSFORMATIONAL
SUBSTANTIAL BREAKTHROUGH
Source:Adapted from C. Christensen's "The Innovator's Dilemma", team analysis
McKinsey & Company | 15
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
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
Regions with a critical mass of highly specialized talent (for instance, large research universities or government R&D lab)
"Knowledge Oases"
▪ "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
McKinsey & Company | 16
... in later stages diversification across the value chain and across industries is crucial to make the cluster self-sustainable
Absolute number of patents filed
SOURCE: McKinsey Innovation Heatmap, USPTO
5,966 6,946 19,181
200519901970
Textiles, heavy industry, printing
Chemicals, photocopying
Optical communi-cations, digital processing systems, molecular biology
Electrical conductor technology, optics
Industries Status of industry
Industries that are shrinking for decades
Industries that are just beyond their peak
Growing industries
Industries that remain constant
Split of technologies of patents granted in California, USAPercent
Self-sustainable clusters jump on new indus-tries to com-pensate for shrinking ones
2
25
41
1853
12
31
11
59
7
21
14
8