Big Data and Role of the Information Professional
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1 Big Data and Role of the Information Professional SLA IEBD Webcast Pat Saporito, CPCU, Sr. Director, Global COE for Analytics
2 Agenda Big Data & Disruption Potential Business Value & Challenges Emerging Roles & Stakeholders Culture & Change Management Information Professionals Role 2012 SAP AG. All rights reserved. Confidential 2
3 Internet of Things is disrupting all industries 1 billion Facebook users Data doubles every 18 months 5 billion in emerging middle class 4 billion YouTube views per day 15 billion web-enabled devices 2012 SAP AG. All rights reserved. Confidential 3
4 Big Data Matters: 5 Vs Potential to Provide Transformational Business Value Drive Better Profit Margins Velocity Instant Messages CRM Data Mobile Customer Value Demand Things Sales Order Operational Efficiencies New Strategies and Business Models Transactions Planning Volume Inventory Opportunities Variety Veracity 2012 SAP AG. All rights reserved. Confidential 4
5 Data (Big & Small) - Its Uses 1:1 Marketing Amazon.com, Gamification/ Game Design Angry Birds, CastleVille Group/Collective Buying Groupon, Living Social Social Networking Facebook, Linked In Inbound Marketing Retargeting, remarketing Travelocity Location Based Marketing Google Places Video YouTube, Hulu User Generated Content Facebook, Linked In, Twitter Mobile Technologies Smartphones, ipads/tablets 2012 SAP AG. All rights reserved. Confidential 5
6 All that Glitters is not Gold All data is not equal Validate data sources Validate its fit for purpose ID alternative data sources 2012 SAP AG. All rights reserved. Confidential 6
7 Selected 3 rd Party Data Categories & Sources Categories Sources: Acxiom AM Best AMA American Housing Survey American Tort Reform Foundation Bureau of Labor Statistics Cap Index Carfax Census Point Choicepoint Corporate Research Board Directory of US Hospitals Dun & Bradstreet EASI Analytics Equifax ESRI Experian Insurance Institute for Highway Safety Internal Revenue Service State Licensing Data (Attys, CPAs, MDs, etc.) Martindale/Hubble Attorney Listing MRI Purchasing Propensities NFIRS National Fire Reporting NHTSA OSHA US Census US Geological Surveys Warranties 2012 SAP AG. All rights reserved. Confidential 7
8 The Mother Load Data.Gov 134,000 data sets 2012 SAP AG. All rights reserved. Confidential 8
9 User Engagement Collective Insight Organizations need to mature their analytics to attain business value Optimization Predictive Modeling What is the best that could happen? Generic Predictive Analysis Agile Visualization Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Self Service BI Why did it happen? What will happen? What happened? Maturity of Analytics Capabilities 2012 SAP AG. All rights reserved. Confidential 9
10 Turning new signals into business value :-) Proactive Health/Wellness & Risk Management Predictive Risk Management Telematics / Usage Based Insurance Insider Threats Asset Optimization Distribution Management Extraordinary Policy/Contract & Claims Service Risk Mitigation, Real-time Customer and Producer Sentiment Underwriting & Pricing, Real Time 360 O Customer View 360 O Provider View Fraud Detection, Real Time 2012 SAP AG. All rights reserved. Confidential 10
11 World Class Analytics Often Described, Rarely Achieved 2012 SAP AG. All rights reserved. Confidential 11
12 Big Data Challenges Staffing and Skills Data Quality/ Governance Tools & Technogies Cost Uncertainty on Value of Big Data Connecting people to information, and applying analytics 2012 SAP AG. All rights reserved. Confidential 12
13 Analytic Use Will Skyrocket: 2020 vs yet, we re not using the data we already have Use Analytics 10% Today Missing new insights Not utilizing all the information out there IT is not agile enough and the business wants to get involved Ability to manage and consume all data is getting harder 75% Need Analytics by 2020 = Bottom Line: Not leveraging the power of collective insight Nucleus Research, Gartner, Fortune Magazine 2012 SAP AG. All rights reserved. Confidential 13
14 Many New Titles & Roles Data Super Hero Data Diva Analytics Cave Man Chief Analytics Officer Not everyone is a Data Scientist but more people need analytics in their jobs. Data Savant 2012 SAP AG. All rights reserved. Confidential 14
15 Analytic Value Chain Many Different Types of Users 2012 SAP AG. All rights reserved. Confidential 15
16 How Information Professionals Can Help Content: Identify external data sources Information Governance: Validate data quality, suitability Access: Help develop text mining taxonomies Tools: Help evaluate tools Research: Develop a bibliography on analytics, big data, analytic leaders, analytic competitors, analytics educational programs. Advocacy: Work with BI Competency Centers SAP AG. All rights reserved. Confidential 16
17 Insurance Analytics Evolution Where are you today? Where do you want to be? Marketing Product Value Customer Segment Value Customer Lifetime Value Dynamic Value Management Product Development One Product Fits All Unbundled Coverages Cafeteria/ Menu Approach Customer & Profitability Driven Pricing & Underwriting Traditional Class Rated Portfolio Analysis Household Analysis, Tier Rating Plans Risk Based Pricing, Ad-hoc or On Demand Rate Reviews Claims Unit focused claims mgmt. Integrated, but reactive claims mgmt. Driver based historical claims mgmt. Driver based predictive claims mgmt. Accounting & Finance Traditional Planning & Budgeting Driver Based Planning & Budgeting Integrated Planning Predictive Planning Metrics Silo d, Functional, Lagging Metrics SBU-Strategic Objective linked, historical drivers Strategic & Cross-SBU objective linked, predictive drivers Integrated predictive models & metrics Data Poor Quality, Silo d, Inaccessible Data Data Assembled Across Product Lines/Historical Consistent Enterprise View Knowledge/ Data Mining Atomic Detail Data Wisdom/ Predictive Less Advanced More Advanced 2012 SAP AG. All rights reserved. Confidential 17
18 Information Culture Connecting People to Data Use information as a strategic asset in decisions Build and tell fact-based stories Maximize business performance with effective use of information (apply the analytics) The stone age was marked by man's clever use of crude tools; the information age, to date, has been marked by man's crude use of clever tools. Anon 2012 SAP AG. All rights reserved. Confidential 18
19 Practical Guidance Applied Insurance Analytics Free download of Chapter 1 (Overview) 2012 SAP AG. All rights reserved. Confidential 19
20 Free desktop visualization tool SAP Lumira SAP AG. All rights reserved. Confidential 20
21 Shifting to an Enterprise Analytics Mindset Analytics is at the core of an intelligent business Be ready for continuous disruption We all emit data, lots of it! Data needs to be front and Center, no matter how big or small Intelligence and Analytics are universal, "Big Data isn't Create an Information driven culture Analytics is not just for power users - it's for everyone 2012 SAP AG. All rights reserved. Confidential 21
22 Next Steps Volunteer for Analytics projects Expand your peer network especially with: Chief Analytics Officer; let them know your value-add BI Competency Center Enlarge your user base Role: Data scientists Function: Actuarial, marketing, claims, Expand your skills Learn about big data Try new tools especially new visualization and text mining tools Lead by Example Use infographics in fulfilling/presenting info requests 2012 SAP AG. All rights reserved. Confidential 22
23 Become a Trusted Data Advisor Help incorporate analytics into your company s DNA Explore Monitor Act Decision Maker IT Developer Design Plan PEOPLE Data Advisor Govern DATA Enrich Explain Analyst Operational Strategic Engage Enterprisewide BI Visualize Exploration & Visualization Predict Advanced Analytics 2012 SAP AG. All rights reserved. Confidential 23
24 Thank You! Pat Saporito, CPCU Sr. Director, BI Global COE for Analytics (201) LinkedIn: SAP Decision Factor Blog SAP Collaboration Network
25 Analytics Bibliography: Books Analytics at Work: Smarter Decisions, Better Results. Thomas H. Davenport, Jeanne G. Harris, Robert Morison. Harvard Business School Publishing Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies and Tools. Patricia Saporito. Pearson FT Press, Big Data: A Revolution That Will Transform How we Live, Work and Think. Viktor Mayer-Schönberger and Kenneth Cukier. Houghton Mifflin Harcourt, Big Data@Work. Dispelling the Myths, Uncovering the Opportunities. Tom Davenport. Harvard Business School Publishing, Business Intelligence in Plain Language: A practical guide to Data Mining and Business Analytics. Jeremy Kolb. Applied Data Labs, Inc Business Intelligence Competency Centers: A Team Approach to Maximizing Competitive Advantage. Gloria J. Miller, Stephanie V. Gerlach and Dagmar Brautigam. John A. Wiley & Sons Mining the Talk: Unlocking the Business Value in Unstructured Information. Scott Spangler and Jeffrey Kreulen. IBM Press/Pearson, plc Predictive Analytics: The Power to Predict who Will Click, Buy, Lie or Die. Eric Siegel. John Wiley & Sons The Visual Display of Quantitative Information. Edward Tufte (A classic reference work; the original bible of visualization. Also see: Envisioning Information and Visual Explanations, by Tufte SAP AG. All rights reserved. Confidential 25
26 Analytics Bibliography: Trade & Professional Assns. International Institute for Analytics (IIA). An independent research firm co-founded Jack Phillips and Research Director Thomas H. Davenport. Works with organizations to build strong and competitive analytics programs. INFORMS (Institute for Operations Research & Management Sciences) Professional organization for cross industry operations research and management professionals. Sponsors the CAP (Certified Analytic Professional) professional designation. TDWI (The Data Warehouse Institute) A leading educational and research organization for BI and Data Warehousing. TDWI produces an annual BI Benchmark Report SAP AG. All rights reserved. Confidential 26
27 Analytics Bibliography: Articles, Studies, White Papers Benchmarking Analytic Talent. Talent Analytics Corp. December A research study on analytics professionals. Big Data: The next frontier for innovation, competition, and productivity. May McKinsey Research Institute. One of the key studies on Big Data. Business Intelligence and Performance Management; Key Initiative Overview. Gartner Group (Research Brief) Data and Analytics in Insurance: P&C Insurer Strategic Priorities and Operational Plans for 2014 and Beyond. Mark Breading and Denise Garth. June Strategy Meets Action. The Data-Driven Organization. Marcia W. Blenko, Michael C. Mankins, Paul Rogers. Harvard Business Review. June Disruptive Technologies: Advances that will transform life, business, and the global economy. May McKinsey Research Institute. Insights into Machine to Machine (M2M), Internet of Things (IoT), and other technologies. The way forward. Insurance in an age of customer intimacy and Internet of Things. Economist Intelligence Unit; sponsored by SAP. June Global survey of P&C and Life insurance executives on the future of insurance. Key findings include important role of data and analytics SAP AG. All rights reserved. Confidential 27
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