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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
Agenda




        1                      Macro Findings


        2                       Key Findings


        3                     Recommendations




2   | ©2012 IBM Corporation
Macro findings




| ©2012 IBM Corporation
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
Introduction to big data

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


                               Characteristics of big data




 5   | ©2012 IBM Corporation
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
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
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
Key findings




| ©2012 IBM Corporation
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
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
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
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
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
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
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
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
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
Recommendations




| ©2012 IBM Corporation
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
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
Download the study and access additional resources




 www.ibm.com/2012bigdatastudy   Listen to a podcast on this study




| ©2012 IBM Corporation
Analytics: The Real-world Use of Big Data

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Analytics: The Real-world Use of Big Data

  • 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
  • 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