analytics: the real-world use of big data

©2012 IBM Corporation

Analytics: The real-world use of big dataHow innovative enterprises extract value from uncertain data

Findings from the research collaboration of IBM Institute for Business Value andSaïd Business School, University of Oxford

©2012 IBM Corporation|

Agenda

2

Key Findings2

Macro Findings1

Recommendations3


Macro findings


IBM Institute for Business Value and the Saïd Business School partnered to benchmark global big data activities

4

Study overview

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

IBM Institute for Business Value

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

http://ibm.co/S55e7d


Big data embodies new data characteristics created by today’s digitized marketplace

Introduction to big data

Characteristics of big data

5


Nearly two out of three respondents reports realizing a competitive advantage from information and analytics

Macro findings

Total respondents n = 11442010 and 2011 datasets © Massachusetts Institute of Technology

Realizing a competitive advantage

Respondents were asked “To what extent does the use of information (including big data) and analytics create a competitive advantage for your organization in your industry or market.” Respondent percentages shown are for those who rated the extent a [4 ] or [5 Significant extent]. The same question has been asked each year.

Competitive advantage enablerA majority of respondents reported analytics and information (including big data) creates a competitive advantage within their market or industry

Represents a 70% increase since 2010

Organizations already active in big data activities were 15% more likely to report a competitive advantage

A higher-than-average percentage of respondents in Latin America, India/SE Asia and ANZ reported realizing a competitive advantage

63%

58%

37%

2012

2011

2010

70%increase

6


Respondents define big data by the opportunities it creates

Introduction to big data

Greater scope of informationIntegration creates cross-enterprise view External data adds depth to internal data

New kinds of data and analysisNew sources of information generated by pervasive devicesComplex analysis simplified through availability of maturing tools

Real-time information streamingDigital feeds from sensors, social and syndicated dataInstant awareness and accelerated decision making

Defining big data

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


Three out of four organizations have big data activities underway; and one in four are either in pilot or production

Macro findings

Total respondents n = 1061Totals do not equal 100% due to rounding

Big data activities

Respondents were asked to describe the state of big data activities within their organization.

Early days of big data eraAlmost half of all organizations surveyed report active discussions about big data plansBig data has moved out of IT and into business discussions

Getting underwayMore than a quarter of organizations have active big data pilots or implementationsTapping into big data is becoming real

Acceleration aheadThe number of active pilots underway suggests big data implementations will rise exponentially in the next few yearsOnce foundational technologies are installed, use spreads quickly across the organization

8


Key findings


Five key findings highlight how organizations are moving forward with big data

Key findings

Big data is dependent upon a scalable and extensible information foundation2

The emerging pattern of big data adoption is focused upon delivering measureable business value5

Customer analytics are driving big data initiatives1

Big data requires strong analytics capabilities4

Initial big data efforts are focused on gaining insights from existing and new sources of internal data3

10


Improving the customer experience by better understanding behaviors drives almost half of all active big data efforts

Key Finding 1: Customer analytics are driving big data initiatives

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

Other functional objectivesThe ability to connect data and expand insights for internally focused efforts was significantly less prevalent in current activities

Big data objectives

Top functional objectives identified by organizations with active big data pilots or implementations. Responses have been weighted and aggregated.

Customer-centric outcomes

Operational optimization

Risk / financial management

New business model

Employee collaboration

11


Customer-centric analytics is the primary functional objective across macro industry groups, as well

50%

11%

21%

16%

2%

42%

26%

13%

13%6%

59%20%

10%

7%5%

51%

19%

16%

10%4%

62%8%

11%

18%1%

32%

30%

27%

6%6%

Consumer Goods Financial Services Healthcare / Life Sciences

Manufacturing Public Sector Telecommunications

Key Finding 1: Customer analytics are driving big data initiatives

Customer-centric outcomes

Operational optimization

Risk / financial management

New business model

Employee collaboration

12


Big data efforts are based on a solid, flexible information management foundation

Key Finding 2: Big data is dependent upon a scalable and extensible information foundation

Solid information foundationIntegrated, secure and governed data is a foundational requirement for big dataMost 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 priorityHigh-capacity warehouses support the variety of data, a close second priorityA significant percentage of organizations are currently piloting Hadoop and NoSQL engines, supporting the notion of exponential growth ahead

Big data infrastructure

13

Respondents with active big data efforts

were asked which platform components were either currently

in pilot or installed within their

organization.


Internal sources of data enable organizations to quickly ramp up big data efforts

Key Finding 3: Initial big data efforts are focused on gaining insights from existing and new sources of internal data

Untapped stores of internal dataSize and scope of some internal data, such as detailed transactions and operational log data, have become too large and varied to manage within traditional systemsNew infrastructure components make them accessible for analysisSome data has been collected, but not analyzed, for years

Focus on customer insightsCustomers – influenced by digital experiences – often expect information provided to an organization will then be “known” during future interactions

Combining disparate internal sources with advanced analytics creates insights into customer behavior and preferences

TransactionsEmailsCall center interaction records

Big data sources

Respondents were asked which data

sources are currently being collected and analyzed as part of

active big data efforts within their organization.

14


Strong analytics capabilities – skills and software – are required to create insights and action from big data

Key Finding 4: Big data requires strong analytics capabilities

Strong skills and software foundationOrganizations start with a strong core of analytics capabilities, such as query and reporting and data mining, designed to address structured dataBig data efforts require advanced data visualization capabilities as datasets are often too large or complex to analyze and interpret with only traditional toolsOptimization models enable organizations to find the right balance of integration, efficiency and effectiveness in processes

Skills gap spans big dataAcquiring and/or developing advanced technical and analytic skills required for big data is a challenge for most organizations with active efforts underwayBoth hardware and software skills are needed for big data technologies; it’s not just a ‘data scientist’ gap

Analytics capabilities

Respondents were asked which analytics

capabilities were currently available within

their organization to analyze big data.

15


Patterns of organizational behavior are consistent across four stages of big data adoption

Key Finding 5: The emerging pattern of big data adoption is focused upon delivering measureable business value

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


Big data leadership shifts from IT to business as organizations move through the adoption stages

Additional Findings

CIOs lead early effortsEarly stages are driven by CIOs once leadership takes hold to drive explorationCIOs drive the development of the vision, strategy and approach to big data within most organizationsGroups of business executives usually guide the transition from strategy to proofs of concept or pilots

Business executives drive actionPilot and implementation stages are driven by business executives – either a function-specific executive such as CMO or CFO, or by the CEOLater stages are more often centered on a single executive rather than a group; a single driving force who can make things happen is critical

Leadership shifts

Respondents were asked which executive is most closely aligned with the mandate to use big data within their organization. Box placement reflects the degree to which each executive is dominant in a given stage.

Total respondents = 1028

17


Challenges evolve as organizations move through the stages, but the business case is a constant hurdle

Additional Findings

State the caseFindings suggest big data activities are being scrutinized for return on investmentA solid business case connects big data technologies to business metrics

Getting startedThe biggest hurdle for those in the early stages is first understanding how to use big data effectively, and then getting management’s attention and supportSkills become a constraint once organizations start pilots, suggesting the need to focus on skills during planningData quality and veracity only surface as an obstacle once roll-out begins, again suggesting the need for earlier attention

Obstacles to big data

Respondents were asked to identify the top obstacles to big data efforts within their organization. Responses were weighted and aggregated. Box placement reflects the degree to which each obstacle is dominant in a given stage.

Total respondents = 973

18


Recommendations


An overarching set of recommendations apply to all organizations focused on creating value from big data

Commit initial efforts to drive business value

Build analytical capabilities based on

business priorities

1Develop

enterprise-wide big data blueprint

Create a business case based on

measurable outcomes

Start with existing data to achieve

near-term results

4

2 3

5

Recommendations

20


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

Getting started

21

Big data: Tapping into new sources of value


www.ibm.com/2012bigdatastudy

Download the study and access additional resources

Listen to a podcast on this study

http://ibm.co/S55e7d

http://ibm.co/QIkSJH


Take the 2013 survey!

http://survey6.spss-asp.com/mrIWeb/mrIweb.dll?I.Project=BAOSURVEY2013V4