UPDATE: Register now to participate in the 2013 survey: http://ibm.com/2013bigdatasurvey IBM’s Institute for Business Value (IBV) and the University of Oxford released their information-rich and insightful report “Analytics: The real-world use of big data.” Based on a survey of over 1000 professionals from 100 countries across 25+ industries, the report provides insights into organizations’ top business objectives, where they are in their big data journey, and how they are advancing their big data efforts. It also provides a pragmatic set of recommendations to organizations as they proceed down the path of big data. For additional information, including links to a podcast with one of the lead researchers and a link to download the full report, visit http://ibm.co/RB14V0

1. Findings from the research collaboration of
IBM Institute for Business Value and
Saïd Business School, University of Oxford
Analytics:
The real-world use of big data
How innovative enterprises extract value from uncertain data
©2012 IBM Corporation

2. Agenda
1 Macro Findings
2 Key Findings
3 Recommendations
2 | ©2012 IBM Corporation

3. Macro findings
| ©2012 IBM Corporation

4. Study overview
IBM Institute for Business Value and the Saïd Business
School partnered to benchmark global big data activities
IBM
Institute for Business Value
IBM Global Business Services, through the IBM
Institute for Business Value, develops fact-based
strategies and insights for senior executives
around critical public and private sector issues.
Saïd Business School
University of Oxford
The Saïd Business School is one of the leading
business schools in the UK. The School is
establishing a new model for business education
by being deeply embedded in the University of
Oxford, a world-class university, and tackling
some of the challenges the world is encountering.
www.ibm.com/2012bigdatastudy
4 | ©2012 IBM Corporation

5. Introduction to big data
Big data embodies new data characteristics created by
today’s digitized marketplace
Characteristics of big data
5 | ©2012 IBM Corporation

6. Macro findings
Nearly two out of three respondents reports realizing a
competitive advantage from information and analytics
Realizing a competitive advantage
Competitive advantage enabler
A majority of respondents
reported analytics and information
(including big data) creates a 2012
competitive advantage within their 63%
market or industry
Represents a 70% increase 2011
since 2010
58% 70%
increase
Organizations already active in
big data activities were 15%
2010
37%
more likely to report a
competitive advantage
Respondents were asked “To what extent does the use of information (including big
A higher-than-average percentage data) and analytics create a competitive advantage for your organization in your
of respondents in Latin America, industry or market.” Respondent percentages shown are for those who rated the
India/SE Asia and ANZ reported extent a [4 ] or [5 Significant extent]. The same question has been asked each year.
realizing a competitive advantage 2010 and 2011 datasets © Massachusetts Institute of Technology Total respondents n = 1144
6 | ©2012 IBM Corporation

7. Introduction to big data
Respondents define big data by the opportunities it creates
Defining big data
Greater scope of information
Integration creates cross-enterprise view
External data adds depth to internal data
New kinds of data and analysis
New sources of information generated
by pervasive devices
Complex analysis simplified through
availability of maturing tools
Real-time information streaming
Digital feeds from sensors, social and
syndicated data
Instant awareness and accelerated
decision making Respondents were asked to choose up to two descriptions about how their
organizations view big data from choices above. Choices have been abbreviated,
and selections have been normalized to equal 100%.
7 | ©2012 IBM Corporation

8. Macro findings
Three out of four organizations have big data activities
underway; and one in four are either in pilot or production
Big data activities
Early days of big data era
Almost half of all organizations surveyed
report active discussions about big data plans
Big data has moved out of IT and into
business discussions
Getting underway
More than a quarter of organizations have
active big data pilots or implementations
Tapping into big data is becoming real
Acceleration ahead
The number of active pilots underway
suggests big data implementations will rise
exponentially in the next few years
Once foundational technologies are installed, Respondents were asked to describe the state
use spreads quickly across the organization of big data activities within their organization.
Total respondents n = 1061
Totals do not equal 100% due to rounding
8 | ©2012 IBM Corporation

9. Key findings
| ©2012 IBM Corporation

10. Key findings
Five key findings highlight how organizations are moving
forward with big data
1 Customer analytics are driving big data initiatives
Big data is dependent upon a scalable and extensible
2 information foundation
Initial big data efforts are focused on gaining insights
3 from existing and new sources of internal data
4 Big data requires strong analytics capabilities
The emerging pattern of big data adoption is
5 focused upon delivering measureable business value
10 | ©2012 IBM Corporation

11. Key Finding 1: Customer analytics are driving big data initiatives
Improving the customer experience by better understanding
behaviors drives almost half of all active big data efforts
Big data objectives
Customer-centric outcomes
Digital connections have enabled
customers to be more vocal
about expectations and
outcomes
Integrating data increases the
ability to create a complete
picture of today’s ‘empowered
consumer’
Understanding behavior patterns
and preferences provides
organizations with new ways to
engage customers
Customer-centric outcomes New business model
Other functional objectives Operational optimization Employee collaboration
The ability to connect data and Risk / financial management
expand insights for internally
Top functional objectives identified by organizations with active big data pilots
focused efforts was significantly or implementations. Responses have been weighted and aggregated.
less prevalent in current activities
11 | ©2012 IBM Corporation

12. Key Finding 1: Customer analytics are driving big data initiatives
Customer-centric analytics is the primary functional
objective across macro industry groups, as well
Healthcare /
Consumer Goods Financial Services
Life Sciences
5% 2%
4%
7% 16% 10%
10%
50% 16% Customer-
51% centric
21%
20% 59% outcomes
11% 19% Operational
optimization
Risk / financial
Manufacturing Public Sector management
Telecommunications
1% New business
6% 6%
6% model
13% 18%
32%
Employee
42%
collaboration
13% 27% 11%
62%
8%
26% 30%
12 | ©2012 IBM Corporation

13. Key Finding 2: Big data is dependent upon a scalable and extensible information foundation
Big data efforts are based on a solid, flexible information
management foundation
Solid information foundation
Big data infrastructure
Integrated, secure and governed
data is a foundational requirement
for big data
Most organizations that have not
started big data efforts lack
integrated information stores,
security and governance
Scalable and extensible
Scalable storage infrastructures
enable larger workloads; adoption
levels indicate volume is the first big
data priority
High-capacity warehouses support
Respondents with
the variety of data, a close second active big data efforts
priority were asked which
platform components
A significant percentage of were either currently
organizations are currently piloting in pilot or installed
Hadoop and NoSQL engines, within their
organization.
supporting the notion of exponential
growth ahead
13 | ©2012 IBM Corporation

14. Key Finding 3: Initial big data efforts are focused on gaining insights from existing and new
sources of internal data
Internal sources of data enable organizations to quickly
ramp up big data efforts
Big data sources
Untapped stores of internal data
Size and scope of some internal data, such
as detailed transactions and operational log
data, have become too large and varied to
manage within traditional systems
New infrastructure components make them
accessible for analysis
Some data has been collected, but not
analyzed, for years
Focus on customer insights
Customers – influenced by digital
experiences – often expect information
provided to an organization will then be
“known” during future interactions Respondents were
asked which data
Combining disparate internal sources with sources are currently
advanced analytics creates insights into being collected and
analyzed as part of
customer behavior and preferences active big data efforts
Transactions within their organization.
Emails
Call center interaction records
14 | ©2012 IBM Corporation

15. Key Finding 4: Big data requires strong analytics capabilities
Strong analytics capabilities – skills and software – are
required to create insights and action from big data
Analytics capabilities
Strong skills and software foundation
Organizations start with a strong core of
analytics capabilities, such as query and
reporting and data mining, designed to
address structured data
Big data efforts require advanced data
visualization capabilities as datasets are
often too large or complex to analyze and
interpret with only traditional tools
Optimization models enable organizations
to find the right balance of integration,
efficiency and effectiveness in processes
Skills gap spans big data
Acquiring and/or developing advanced
technical and analytic skills required for
Respondents were
big data is a challenge for most asked which analytics
organizations with active efforts underway capabilities were
currently available within
Both hardware and software skills are their organization to
needed for big data technologies; it’s not analyze big data.
just a ‘data scientist’ gap
15 | ©2012 IBM Corporation

16. Key Finding 5: The emerging pattern of big data adoption is focused upon delivering
measureable business value
Patterns of organizational behavior are consistent
across four stages of big data adoption
Big data adoption
When segmented into four groups based on current levels of big data activity, respondents showed significant consistency in
organizational behaviors Total respondents = 1061
Totals do not equal 100% due to rounding
16 | ©2012 IBM Corporation

17. Additional Findings
Big data leadership shifts from IT to business as
organizations move through the adoption stages
CIOs lead early efforts Leadership shifts
Early stages are driven by CIOs once
leadership takes hold to drive
exploration
CIOs drive the development of the
vision, strategy and approach to big
data within most organizations
Groups of business executives usually
guide the transition from strategy to
proofs of concept or pilots
Business executives drive action
Pilot and implementation stages are
driven by business executives – either
a function-specific executive such as
CMO or CFO, or by the CEO Respondents were asked which executive is most closely aligned with
Later stages are more often centered the mandate to use big data within their organization. Box placement
reflects the degree to which each executive is dominant in a given stage.
on a single executive rather than a
group; a single driving force who can Total respondents = 1028
make things happen is critical
17 | ©2012 IBM Corporation

18. Additional Findings
Challenges evolve as organizations move through the
stages, but the business case is a constant hurdle
Obstacles to big data
State the case
Findings suggest big data activities are
being scrutinized for return on
investment
A solid business case connects big data
technologies to business metrics
Getting started
The biggest hurdle for those in the early
stages is first understanding how to use
big data effectively, and then getting
management’s attention and support
Skills become a constraint once
organizations start pilots, suggesting the
need to focus on skills during planning
Data quality and veracity only surface Respondents were asked to identify the top obstacles to big data efforts
as an obstacle once roll-out begins, within their organization. Responses were weighted and aggregated. Box
placement reflects the degree to which each obstacle is dominant in a
again suggesting the need for earlier given stage.
attention Total respondents = 973
18 | ©2012 IBM Corporation

19. Recommendations
| ©2012 IBM Corporation

20. Recommendations
An overarching set of recommendations apply to all
organizations focused on creating value from big data
1 2 3
Commit initial Develop Start with existing
efforts to drive enterprise-wide data to achieve
business value big data blueprint near-term results
4 5
Build analytical Create a business
capabilities based on case based on
business priorities measurable outcomes
20 | ©2012 IBM Corporation

21. Getting started
Big data creates the opportunity for real-world
organizations to extract value from untapped digital assets
Focus on measurable business outcomes
Take a pragmatic approach, beginning with
existing data, tools/technologies, and skills
Expand your big data capabilities and efforts
across the enterprise
Big data: Tapping into new sources of value
21 | ©2012 IBM Corporation

22. Download the study and access additional resources
www.ibm.com/2012bigdatastudy Listen to a podcast on this study
| ©2012 IBM Corporation