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Big Data and Role of Information Professional

Webinar for Special Libraries Assn.Insurance & Employee Division (SLA - IEBD) members on Big Data and potential value add and opportunities for information professionals - an under tapped resource for BICCs and Chief Analytic Officers.

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Big Data and Role of Information Professional

  1. 1. SLA – IEBD Webcast Big Data and Role of the Information Professional Pat Saporito, CPCU, Sr. Director, Global COE for Analytics Pat.saporito@sap.com Twitter: @patsaporito
  2. 2. ©2012 SAP AG. All rights reserved. 2 Confidential Agenda Big Data & Disruption Potential Business Value & Challenges Emerging Roles & Stakeholders Culture & Change Management Information Professionals Role
  3. 3. ©2012 SAP AG. All rights reserved. 3 Confidential Internet of Things is disrupting all industries 1 billion Facebook users 4 billion YouTube views per day Data doubles every 18 months 15 billion web-enabled devices 5 billion in emerging middle class
  4. 4. ©2012 SAP AG. All rights reserved. 4 Confidential Drive Better Profit Margins New Strategies and Business Models Operational Efficiencies Value Velocity Volume Variety Mobile CRM Data Planning Opportunities Transactions Customer Sales Order Things Instant Messages Demand Inventory Big Data Matters: 5 Vs Potential to Provide Transformational Business Value Veracity
  5. 5. ©2012 SAP AG. All rights reserved. 5 Confidential 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
  6. 6. ©2012 SAP AG. All rights reserved. 6 Confidential All that Glitters is not Gold All data is not equal •Validate data sources •Validate its fit for purpose •ID alternative data sources
  7. 7. ©2012 SAP AG. All rights reserved. 7 Confidential Selected 3rd Party Data Categories & Sources 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 Categories
  8. 8. ©2012 SAP AG. All rights reserved. 8 Confidential The Mother Load – Data.Gov http://catalog.data.gov 134,000 data sets
  9. 9. ©2012 SAP AG. All rights reserved. 9 Confidential Organizations need to mature their analytics to attain business value Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Agile Visualization Predictive Modeling Optimization What happened? Why did it happen? What will happen? What is the best that could happen? User Engagement Maturity of Analytics Capabilities Self Service BI Generic Predictive Analysis Collective Insight
  10. 10. ©2012 SAP AG. All rights reserved. 10 Confidential Turning new signals into business value Proactive Health/Wellness & Risk Management 360O Customer View 360O Provider View Extraordinary Policy/Contract & Claims Service Customer and Producer Sentiment Underwriting & Pricing, Real Time Predictive Risk Management Fraud Detection, Real Time Telematics / Usage Based Insurance Insider Threats Risk Mitigation, Real-time Asset Optimization Distribution Management :-)
  11. 11. ©2012 SAP AG. All rights reserved. 11 Confidential “World Class Analytics” Often Described, Rarely Achieved
  12. 12. ©2012 SAP AG. All rights reserved. 12 Confidential Big Data Challenges Staffing and Skills Data Quality/ Governance Cost Uncertainty on Value of Big Data Tools & Technogies Connecting people to information, and applying analytics
  13. 13. ©2012 SAP AG. All rights reserved. 13 Confidential Nucleus Research, Gartner, Fortune Magazine Analytic Use Will Skyrocket: 2020 vs. 2014… yet, we’re not using the data we already have 10% 75% Use Analytics Today Need Analytics by 2020 Ability to manage and consume all data is getting harder Not utilizing all the information out there Bottom Line: Not leveraging the power of “collective insight” Missing new insights IT is not agile enough and the business wants to get involved =
  14. 14. ©2012 SAP AG. All rights reserved. 14 Confidential Many New Titles & Roles Data Diva Data Savant Data Super Hero Chief Analytics Officer Analytics Cave Man Not everyone is a Data Scientist… but more people need analytics in their jobs.
  15. 15. ©2012 SAP AG. All rights reserved. 15 Confidential Analytic Value Chain Many Different Types of Users
  16. 16. ©2012 SAP AG. All rights reserved. 16 Confidential 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.
  17. 17. ©2012 SAP AG. All rights reserved. 17 Confidential Insurance Analytics Evolution Where are you today? Where do you want to be? Pricing & Underwriting Traditional Class Rated Portfolio Analysis Household Analysis, Tier Rating Plans Risk Based Pricing, Ad-hoc or On Demand Rate Reviews Data Poor Quality, Silo’d, Inaccessible Data Data Assembled Across Product Lines/Historical Consistent Enterprise View Knowledge/ Data Mining Atomic Detail Data Wisdom/ Predictive Product Development One Product Fits All Unbundled Coverages Cafeteria/ Menu Approach Customer & Profitability Driven Marketing Product Value Customer Segment Value Customer Lifetime Value Dynamic Value Management Accounting & Finance Unit focused claims mgmt. Integrated, but reactive claims mgmt. Driver based historical claims mgmt. Driver based predictive claims mgmt. Metrics Silo’d, Functional, Lagging Metrics SBU-Strategic Objective linked, historical drivers Strategic & Cross-SBU objective linked, predictive drivers Integrated predictive models & metrics Claims Traditional Planning & Budgeting Driver Based Planning & Budgeting Integrated Planning Predictive Planning Less Advanced More Advanced
  18. 18. ©2012 SAP AG. All rights reserved. 18 Confidential 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
  19. 19. ©2012 SAP AG. All rights reserved. 19 Confidential Practical Guidance Applied Insurance Analytics Free download of Chapter 1 (Overview)
  20. 20. ©2012 SAP AG. All rights reserved. 20 Confidential Free desktop visualization tool SAP Lumira http://saplumira.com/
  21. 21. ©2012 SAP AG. All rights reserved. 21 Confidential Be ready for continuous disruption Create an Information driven culture Intelligence and Analytics are universal, "Big Data“ isn't We all emit data, lots of it! Data needs to be front and Center, no matter how big or small Analytics is at the core of an intelligent business Shifting to an Enterprise Analytics Mindset Analytics is not just for power users - it's for everyone
  22. 22. ©2012 SAP AG. All rights reserved. 22 Confidential 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
  23. 23. ©2012 SAP AG. All rights reserved. 23 Confidential Plan Explore Enrich Explain Monitor Design Govern DATA PEOPLE Analyst IT Developer Decision Maker Visualize Exploration & Visualization Predict Advanced Analytics Operational Strategic Become a Trusted Data Advisor Help incorporate analytics into your company’s DNA Engage Enterprise- wide BI Act Data Advisor
  24. 24. Thank You! Pat Saporito, CPCU Sr. Director, BI Global COE for Analytics Pat.saporito@sap.com (201) 681-9671 Twitter: @Pat.Saporito LinkedIn: www.linkedin/in/patriciasaporito SAP Collaboration Network http://scn.sap.com/ SAP Decision Factor Blog http://www.the-decisionfactor.com/home/
  25. 25. ©2012 SAP AG. All rights reserved. 25 Confidential Analytics Bibliography: Books Analytics at Work: Smarter Decisions, Better Results. Thomas H. Davenport, Jeanne G. Harris, Robert Morison. Harvard Business School Publishing. 2010. Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies and Tools. Patricia Saporito. Pearson FT Press, 2014. Big Data: A Revolution That Will Transform How we Live, Work and Think. Viktor Mayer-Schönberger and Kenneth Cukier. Houghton Mifflin Harcourt, 2013. Big Data@Work. Dispelling the Myths, Uncovering the Opportunities. Tom Davenport. Harvard Business School Publishing, 2014. Business Intelligence in Plain Language: A practical guide to Data Mining and Business Analytics. Jeremy Kolb. Applied Data Labs, Inc. 2012. Business Intelligence Competency Centers: A Team Approach to Maximizing Competitive Advantage. Gloria J. Miller, Stephanie V. Gerlach and Dagmar Brautigam. John A. Wiley & Sons. 2006 Mining the Talk: Unlocking the Business Value in Unstructured Information. Scott Spangler and Jeffrey Kreulen. IBM Press/Pearson, plc. 2008. Predictive Analytics: The Power to Predict who Will Click, Buy, Lie or Die. Eric Siegel. John Wiley & Sons. 2013. The Visual Display of Quantitative Information. Edward Tufte. 2001. (A classic reference work; the original “bible” of visualization. Also see: Envisioning Information and Visual Explanations, by Tufte.
  26. 26. ©2012 SAP AG. All rights reserved. 26 Confidential Analytics Bibliography: Trade & Professional Assns. International Institute for Analytics (IIA). www.iianalytics.com 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) www.informs.org Professional organization for cross industry operations research and management professionals. Sponsors the CAP (Certified Analytic Professional) professional designation. TDWI (The Data Warehouse Institute) www.tdwi.org A leading educational and research organization for BI and Data Warehousing. TDWI produces an annual BI Benchmark Report.
  27. 27. ©2012 SAP AG. All rights reserved. 27 Confidential Analytics Bibliography: Articles, Studies, White Papers Benchmarking Analytic Talent. Talent Analytics Corp. December 2012. A research study on analytics professionals. Big Data: The next frontier for innovation, competition, and productivity. May 2011. McKinsey Research Institute. One of the key studies on Big Data. Business Intelligence and Performance Management; Key Initiative Overview. Gartner Group. 2013. (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 2014. Strategy Meets Action. The Data-Driven Organization. Marcia W. Blenko, Michael C. Mankins, Paul Rogers. Harvard Business Review. June 2010. Disruptive Technologies: Advances that will transform life, business, and the global economy. May 2013. 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 2014. Global survey of P&C and Life insurance executives on the future of insurance. Key findings include important role of data and analytics.

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