Analytics: The real-world use of big data

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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 Tom Inman, Vice President, IBM Software Group

2 Introduction to big data Big data is a business priority inspiring new models and processes for organizations, and even entire industries Analytics is expanding from enterprise data to big data Volume Velocity Variety 12 terabytes of Tweets create daily s million trade events per second from surveillance cameras video feeds Analyze product sentiment Identify potential fraud Monitor events of interest billion meter readings per annum billion call detail records per hour 80% data growth are images, video, documents Predict power consumption Prevent customer churn Improve customer satisfaction

3 Introduction to big data Big data is a business priority inspiring new models and processes for organizations, and even entire industries 3

4 Introduction to big data Big data embodies new data characteristics created by today s digitized marketplace Characteristics of big data 4

5 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. 5

6 Macro findings Three out of four organizations have big data activities underway; and one in four are either in pilot or production 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 Big data activities 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, use spreads quickly across the organization Respondents were asked to describe the state of big data activities within their organization. Total respondents n = 1061 Totals do not equal 100% due to rounding 6

7 Macro findings Organizations are gaining value from working with IBM Grow, retain and satisfy customers Increase operational efficiency Transform financial processes Manage risk, fraud & regulatory compliance 60% Improvement in billed revenue retention rate 50% Increase in inventory turns 50% Reduction in planning cycle times 70% Trading decisions improved with 70% of counterparties

8 Key findings Five key findings highlight how organizations are moving forward with big data Customer analytics are driving big data initiatives Big data is dependent upon a scalable and extensible information foundation Initial big data efforts are focused on gaining insights from existing and new sources of internal data Big data requires strong analytics capabilities The emerging pattern of big data adoption is focused upon delivering measureable business value 8

9 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 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 Big data objectives 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 Total respondents n =

10 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 A holistic and integrated approach to analytics and big data Solutions An approach that enable organizations to: Discover and integrate relevant information Analyze patterns and predict outcomes Enterprise Healthcare Next Best Social Media Fraud Analytics Action Analytics Analytics and Decision Management Predictive Content Decision Visualization Analytics Analytics Management & Discovery Visualize and explore for answers Take action and automate processes Optimize analytical performance and IT costs Content Management Big Data Platform Hadoop Data System Warehouse Stream Computing Manage, Govern and Secure Information Information Integration and Governance Big Data Infrastructure: Systems, Storage and Cloud

11 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 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 Combining disparate internal sources with advanced analytics creates insights into customer behavior and preferences Transactions s Call 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. 11

12 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 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 big data is a challenge for most organizations with active efforts underway Both 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. 12

13 Key Recommendation 5: Create a business case based on measurable outcomes Business cases must include explicit forecasts of how technology investments will impact the bottom line Business case details Articulating the case Many organizations are basing their business cases on the following benefits that can be derived from big data: Smarter decisions Leverage new sources of data to improve the quality of decision making Faster decisions Enable more real-time data capture and analysis to support decision making at the point of impact Decisions that make a difference Focus big data efforts toward areas that provide true differentiation Secure executive support An important principle underlies each of these recommendations: business and IT professionals must work together throughout the big data journey Active involvement and sponsorship from one or more business executives throughout this process is needed to advocate for investments I believe big data will force companies to re-think their structures and business divisions to focus more on those areas that are most relevant to the accomplishment of the strategy and corporate goals, and not just financial, but also in terms of customer satisfaction, product development, research, etc. Insurance industry executive Mexico 13

14 Create a business case based on measurable outcomes Key Business Benefits Business Areas 1. Sales & Marketing Effectiveness 2. Advanced Data Expansion 3. Network Optimization Dealer incentives, Pricing, District based approach Targeted marketing and increased cross-sell / up-sell Reduction in subscriber churn through advanced subscriber analytics Filling capacity, Sachet approach on pricing Freemium approach, 4. Finance Improve network utilization Optimize network capital investments Optimize network operating investments Benchmarking, Spend smart, Financial analysis, post mortem Product Profitability Analysis COMPANY CONFIDENTIAL

15 Recommendations An overarching set of recommendations apply to all organizations focused on creating value from big data 1 Commit initial efforts to drive business value 2 3 Develop enterprise-wide big data blueprint Start with existing data to achieve near-term results 4 Build analytical capabilities based on business priorities 5 Create a business case based on measurable outcomes 15

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