Big Data: The next frontier for innovation, competition, and …assets.en.oreilly.com/1/event/71/Big Data_ The Next... · 2011-09-20 · Big Data: The next frontier for innovation,

Big Data: The next frontier forinnovation, competition, and productivityMcKinsey Global Institute

September 20, 2011Strata Summit

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The amount of data collected and stored has grown exponentially in the last decade

Technology trends have converged – data is personal, everywhere, and increasingly accessible

New possibilities exist to innovate and create significant value out of big data

Big data will have bottom-line implications for companies and far-reaching effects on the economy

There are challenges to address if the value of big data are to be realized

Key findings


Data storage has grown significantly – shifting markedly from analog to digital after 2000

SOURCE: Hilbert and López, “The world’s technological capacity to store, communicate, and compute information,” Science, 2011

Global installed, optimally compressed, storage

Analog

Digital

50

300

250

200

150

100

0

Data storage,

exabytes

2007200019931986


150231278319370

536697

801825831870

9671,312

1,7921,931

1,507

3,866

InsuranceDiscrete Manufacturing

GovernmentUtilities

Communications and MediaBanking

Securities and Investment Svs.

ConstructionProfessional Services

EducationHealthcare providers1

Wholesale

Consumer and Recreation Svs.

RetailTransportation

Resource IndustriesProcess Manufacturing

Companies in all sectors have at least 100 terabytes of storeddata in the United States; many have more than 1 petabyte

Average stored data per firm with more than 1,000 employees, 2009, terabytes

SOURCE: IDC; US Bureau of Labor Statistics; McKinsey Global Institute analysis

>500 = WalMart data warehouse in 2004235 = Library of Congress collection in 2011


This data has gone from being highly macro…

Americans burn 1,800 calories per day


Americans burn 1,800 calories per dayHe burns 2,133of calories per day

She burns 1,489of calories per day

She burns 1,567of calories per day

She burns 1,945of calories per dayHe burns 1,438of calories per day

…to very personal


Even physical objects are generating “exhaust” data


Estimated number of connected nodes, millionsThe number of connected nodes is increasing exponentially

SOURCE: Analyst interviews; McKinsey Global Institute analysis

Utilities

Travel and logistics

RetailIndustrials Energy

Health care

Security

Automotive

2015

72–215

15–45

28–83

4–128–23

2–6 1–3

5–14

10–30

2010

17–50

6–18

2–6 2–62–5 1–2

5–14

SecurityIndustrials

RetailTravel and logistics

AutomotiveUtilities


Computation capacity has risen sharply

SOURCE: Hilbert and López, “The world’s technological capacity to store, communicate, and compute information,” Science, 2011

Global installed computation to handle information

1012 million instructions per second

20072000199319860

1.0

2.0

3.0

4.0

5.0

6.0

Overall

This computational power is equivalent to almost 1.3 billion laptop computers


5 ways for big data to create transformational value

Create transparency

Expose variability and enable experimentation

Segment populations to customize actions

Replace/support human decision-making with automated algorithms

Innovate new business models, products, and services


Big Data companies have outperformed their respective markets and have created competitive advantage

SOURCE: Bloomberg and Datastream; annual reports; McKinsey analysis

Revenue EBITDA

9

14

11

9

24

12

8

9

5

5

-1

6

Insurance

Casinos

Credit cards

Big box retailers

Online retailers

Grocers

14

9

12

10

22

11

5

-1

1

2

-15

3

Other competitorsBig data leader

Percent, 10-year CAGR (1999 – 2009)


Big data can generate significant value across sectors

SOURCE: McKinsey Global Institute analysis

Europe public sector administration▪ €250 billion value per year▪ ~0.5 percent annual productivity

growth

Global personal location data▪ $100 billion+ revenue for

service providers▪ Up to $700 billion value to end

users

Manufacturing▪ Up to 50 percent decrease

in product development, assembly costs

▪ Up to 7% reduction in working capital

US health care▪ $300 billion value

per year▪ ~0.7 percent annual productivity

growth

US retail▪ 60+% increase in net margin

possible▪ 0.5–1.0 percent annual

productivity growth


Consumer surplus: Personal location data will generate 6 times more value for end customers than for service providers


Revenue accrued to service providers Quantifiable value accrued to end customers

▪ Fuel savings▪Reduced

congestion

▪Convenience (e.g., location sharing)


Relative value potential and ease of capture will vary across sectors

Wholesale trade

Utilities

Transportation and Warehousing

Retail trade

Real Estateand Rental

ProfessionalServices

Other Services

Natural resources Manufac-

turing

Management of companies

Information

Health Care Providers

Government

Finance andInsurance

Educational services

Construction

Computer and electronic products

Arts and Entertainment

Admin, Support and Waste Management

Accommodation and Food

Low

High

Low

Big data ease of Captureindex

High

Big data value potential index

Bubble sizes denote relative sizes of GDP



To fully capture this opportunity several major issues must be addressed

Data policies▪ Privacy concerns ▪ Data security issues ▪ Intellectual ownership and liability issues

Technology & techniques▪ Deployment of technologies▪ Legacy system or inconsistent

data formats▪ Ongoing innovation

Organizational change & talent▪ Shortage of talent ▪ Leadership that understands big data▪ Aligned workflows and incentives

Access to data▪ Access to “foreign” data ▪ Integrating with own proprietary data


3 types of talent are needed to capture value from big data

SOURCE: US Bureau of Labor Statistics; McKinsey Global Institute analysis

~1.5M

~300K

~150KDeep analytical

Big data savvy

Supporting technology

▪ Actuaries▪ Mathematicians▪ Statisticians

▪ Business managers▪ Financial analysts▪ Engineers

▪ Computer programmers▪ Computer software engineers ▪ Computer system analysts

Potential gap by 2018Talent needed


Importance of access to data: US health care example


Integration of data poolsrequired for

major opportunities

Pharmaceutical R&D data

Clinical data

Activity (claims) and cost data

Patient behavior and sentiment data

▪ Owner: Pharmaceutical companies, academia

▪ Example datasets: clinical trials, high throughput screening (HTS) libraries

▪ Owners: payors, providers

▪ Example datasets: utilization of care, cost estimates

▪ Owners: providers▪ Example datasets:

electronic medical records, medical images

▪ Owners: various including consumer and stakeholders outside health care (e.g., retail, apparel)

▪ Example data sets: patient behaviors and preferences, retail purchase history, exercise data captured in running shoes

Data pools


Implications for organization leaders

Inventory data assets, proprietary, public and purchased

1

Identify potential value creation opportunities and threats

2

Build internal capabilities to create a data-driven organization

3

Develop enterprise information strategy to implement technology

4

Address data policy issues5


Implications for policy makers

Align incentives to promote data sharing for the greater good

Develop policies that balance the interests of companies wanting to create value from data and citizens wanting to protect their privacy and security

Establish effective intellectual property frameworks to ensure innovation

Address technology barriers and accelerate R&D in targeted areas

Ensure investments in underlying information and communication technology infrastructure

Build human capital for big data123456


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Documents

Big Data: The next frontier for innovation, competition, and …assets.en.oreilly.com/1/event/71/Big Data_ The Next... · 2011-09-20 · Big Data: The next frontier for innovation,