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Big Data: The next frontier
for innovation, competition,
and productivity



Fujitsu North America Technology Forum
Januar...

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Data storage has grown significantly – shifting markedly from
analog to digital after 2000
Global installed, optimally com...

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Everyone, everything, every interaction generates “exhaust” data

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03 michael chui

Presentation by Michael Chui, Senior Fellow, McKinsey Global Institute. This was presented at our Fujitsu North America Technology Forum 2012, held in Santa Clara, CA on Jan. 25th, 2012. The theme of the event was "From Sensor Networks to Human Networks: Turning Big Data into Actionable Wisdom"

Presentation by Michael Chui, Senior Fellow, McKinsey Global Institute. This was presented at our Fujitsu North America Technology Forum 2012, held in Santa Clara, CA on Jan. 25th, 2012. The theme of the event was "From Sensor Networks to Human Networks: Turning Big Data into Actionable Wisdom"

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03 michael chui

  1. 1. Big Data: The next frontier for innovation, competition, and productivity Fujitsu North America Technology Forum January 25, 2012 CONFIDENTIAL AND PROPRIETARY Any use of this material without specific permission of McKinsey & Company is strictly prohibited
  2. 2. Data storage has grown significantly – shifting markedly from analog to digital after 2000 Global installed, optimally compressed, storage 300 250 200 Data storage, 150 exabytes Digital 100 50 Analog 0 1986 1993 2000 2007 SOURCE: Hilbert and López, “The world’s technological capacity to store, communicate, and compute information,” Science, 2011 McKinsey & Company | 1
  3. 3. Everyone, everything, every interaction generates “exhaust” data Transactions Mobile Social Audio/video Scientific/engineering ‘Internet of things’ McKinsey & Company | 2
  4. 4. Computation capacity has risen sharply Global installed computation to handle information Overall 1012 million instructions per second This computational 6.0 power is equivalent to almost 1.3 billion 5.0 laptops 4.0 3.0 2.0 1.0 0 1986 1993 2000 2007 SOURCE: Hilbert and López, “The world’s technological capacity to store, communicate, and compute information,” Science, 2011 McKinsey & Company | 3
  5. 5. Companies in all sectors have at least 100 terabytes of stored US EXAMPLE data in the United States; many have more than 1 petabyte Average stored data per firm with more than 1,000 employees, 2009, terabytes Securities and Investment Svs. 3,866 Banking 1,931 Communications and Media 1,792 Utilities 1,507 Government 1,312 Discrete Manufacturing 967 Insurance 870 Process Manufacturing 831 Resource Industries 825 Transportation 801 Retail 697 Wholesale 536 Healthcare providers 370 Education 319 Professional Services 278 Construction 231 >500 = WalMart data warehouse in 2004 Consumer and Recreation Svs. 150 235 = Library of Congress collection in 2011 SOURCE: IDC; US Bureau of Labor Statistics; McKinsey Global Institute analysis McKinsey & Company | 4
  6. 6. This data has gone from being highly macro… Americans burn 1,800 calories per day McKinsey & Company | 5
  7. 7. …to very personal He burns She burns He burns burns She She burns 2,133 of calories 1,567 of calories 1,800 calories per day 1,945 of calories Americans burn 1,438 calories calories 1,489 of per day per day per dayper day per day Weekly Overview Typical You 108 Cal 319 Cal 531 Cal 742 Cal 954 Cal 1165 Cal 1377 Cal 1588 Cal 1800 Cal 2011 Cal You burned an average of Your activity level is rated You are in the 1438 cal/day Lightly active 84th percentile from activity this week of all men 25-35 years who are overweight McKinsey & Company | 6
  8. 8. Five ways for big data to create transformational value 1 Create transparency 2 Expose variability and enable experimentation 3 Segment populations to customize actions 4 Replace/support human decision-making with automated algorithms 5 Innovate new business models, products, and services McKinsey & Company | 7
  9. 9. Big Data companies have outperformed their respective Big data leaders markets and have created competitive advantage Other competitors Percent Revenue 1999-2009 EBITDA 1999-2009 (10YR CAGR) (10YR CAGR) 12 11 Grocers 6 3 Online retailers 24 22 -1 -15 Big box retailers 9 10 5 2 Casinos 11 12 5 1 Credit cards 14 9 9 -1 Insurance 9 14 8 5 SOURCE: Bloomberg and Datastream; annual reports; McKinsey analysis McKinsey & Company | 8
  10. 10. Big data is already driving productivity and innovation US health care US retail $300 billion value 60+% increase in net per year margin possible ~0.7 percent annual 0.5–1.0 percent annual productivity growth productivity growth Europe public sector Manufacturing administration Up to 50 percent decrease €250 billion value per in product development, year assembly costs ~0.5 percent annual Up to 7% reduction in productivity growth working capital Global personal location data $100 billion+ revenue for service providers Up to $700 billion value to end users McKinsey & Company | 9
  11. 11. Impact of using big data to drive innovation and productivity is order of magnitude larger than revenue from providing big data services Global personal location data $100 billion $600+ billion in using for fuel to telcos savings, logistics, local targeting Real world healthcare data $10 billion to data $300 billion in shifts profit pool service providers shifts payers, providers, pharma McKinsey & Company | 10
  12. 12. To fully capture this opportunity several major issues must be addressed Description Privacy concerns Data policies Data security issues Intellectual ownership and liability issues Deployment of technologies Technology & techniques Legacy system or inconsistent data formats Ongoing innovation Access to “foreign” data Access to data Integrating with own proprietary data Organizational Shortage of talent change & talent Leadership that understands big data Aligned workflows and incentives McKinsey & Company | 11
  13. 13. Three types of talent are needed to capture value from big data US EXAMPLE Potential gap Talent needed by 2018 Deep analytical Actuaries Mathematicians ~150K Statisticians Big data savvy Business managers ~1.5M Financial analysts Engineers Supporting technology Computer programmers ~300K Computer software engineers Computer system analysts SOURCE: US Bureau of Labor Statistics; McKinsey Global Institute analysis McKinsey & Company | 12
  14. 14. Implications for organization leaders 1 Inventory data assets, proprietary, public and purchased 2 Identify potential value creation opportunities and threats 3 Build internal capabilities to create a data-driven organization 4 Address data policy issues 5 Demonstrate value 5 Architect data-driven transformation McKinsey & Company | 13

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