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Leveraging Analytics to achieve your Customer Experience Objectives


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Presented by Graham Cobb, European Industry Leader for Banking and Financial Markets, Business Analytics at IBM

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Leveraging Analytics to achieve your Customer Experience Objectives

  1. 1. Insurance Event Leveraging Analytics to achieve your Customer Experience Objectives IBM Power Systems © 2011 IBM Corporation
  2. 2. Insurance Event DRAFT V1.0Overview 1. Understand the use of technology as a key enabler of success 2. Apply Consumer Insight and Predictive Analytics to ensure growth 3. Review world class case studies and gain insight into the ROI 2 © 2011 IBM Corporation
  3. 3. Insurance Event DRAFT V1.0The Age of Data is here… Every day, 15 petabytes of new information are being generated. “By 2010, the codified information base of the world is expected to double every 11 hours.” … enterprises today collect more data than ever before on every aspect of their business…… “Today, 80% of new data growth is unstructured content, generated largely by email, with increasing contribution by documents, images, and video and audio” … but they are unable to leverage this into insights and drive business results “Executives are being called upon to make more and faster decisions. Today, 70% of executives believe that poor decision making has degraded their companies’ performance” 3 © 2011 IBM Corporation
  4. 4. Insurance Event DRAFT V1.0Strategic Rationale EBITDA Why? 5-year CAGR, 2004-2008 11.3% A recent study of over 1,900 CFO’s (including from banks and insurers) shows companies excelling in financial Finance Efficiency 3.9% efficiency & business insight significantly outperform the competition in terms of EBITDA over a 5 year period -2.1% -0.1% Only 16% of the participating companies scored themselves in the upper right quadrant. Source: IBM CFO Study, 2010 Source: IBM CFO Study, 2010 Business Insight Analytics Greater sources of data from instrumentation, networking, Data and extraction Why Now? Organisations can create greater insight to New tools make it easier to change their position in the market: Models develop complex models; cheaper processing power makes it faster and cheaper to execute • Explosion of data; • Easier to use modeling tools; • Models that run in real time (versus weeks), Competitive Differentiation / • Dramatic reduction in cost / MIPS Competitive Threat Information / Insight / Intelligence This is either a Threat, or a Weapon depending on your appetite 4 © 2011 IBM Corporation
  5. 5. Insurance Event DRAFT V1.0Analytics seen as critical for driving competitiveness BI/Analytics is #1 investment to improve competitiveness IBM Global CIO Study 2009 Ten Most Important Visionary Plan Elements Interviewed CIOs could select as many as they wantedBusiness Intelligence and Analytics 80% 86% Virtualization 77% 76% Risk Management and Compliance 73% 70% Mobility Solutions 71% 66% Customer and Partner Collaboration 73% 64% Self-Service Portals 71% 63% Application Harmonization 67% 62% Business Process Management 70% 61% High SOA/Web Services 68% 55% growth Unified Communication 63% 57% Low growth “At a time when companies in many industries offer similar products and use comparable technology, high-performance business processes are among the last remaining points of differentiation.” Thomas Davenport, “Competing on Analytics” Source: IBM Global CIO Study 2009; n = 2345 5 © 2011 IBM Corporation
  6. 6. Insurance Event DRAFT V1.0 Analytics involves long-term commitment and an iterative learning process to become a competitive strengthcompetence Stage1: Stage 2: Stage 3: Stage 4: Stage 5: analytical Stages of Analytically Localized Analytical Analytical Analytical Impaired Analytics aspirations companies competitor • Fact-based and test-and-learn Capabilities Maturity of culture • One-off initiatives (no learning) • Gut-based decisions • Analytical processes integrated • Poor quality data across organization • Insights driven by strategic objectives • Enterprise-wise infrastructure Capturing and learning from analytics results from every initiative executed is critical to rapidly progress through competency stages 6 © 2011 IBM Corporation Source: Analytics Competency Framework from ‘Competing on Analytics’ by Thomas Davenport.