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Business Case for Business Intellligence

Business Case for Business Intellligence

Kevin Pledge

June 14, 2012
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  1. SOA Health Meeting - June 2012 Business Case for Business

    Intelligence Kevin Pledge [email protected] 416 949 8920 @kevinpledge http://ca.linkedin.com/in/kevinpledge
  2. Kevin Pledge • CEO and Co-Founder of Insight Decision Solutions

    • Chair of the SOA Entrepreneurial Actuaries Section • Member of working group on Actuaries in Business Analytics [email protected] • 416 949 8920 • @kevinpledge • http://ca.linkedin.com/in/kevinpledge
  3. Agenda Kevin: Examples and case studies of BI at work

    Neil: Developing trends in semantics and big data
  4. What is Business Intelligence? 1) Combination of data management and

    analytics 2) A database managed by IT 3) The ability for an organization to take all its capabilities and convert them into knowledge 4) An oxymoron 5) All of the above
  5. Typical BI Architecture Data Warehouse / OLAP Server Presentation Server

    Users Metadata Data Store Integrated Systems e.g. valuation system ETL ETL Source systems But others are possible….
  6. Reality Check data definitions, data cleansing, aggregations, normalizing, de- normalizing,

    rationalizing, extracts, transformations, translations, data dictionaries, restructuring, conversions, Not worth anything if don’t have a use for it
  7. consistent cleansed data for actuarial Before: Separate data extracts for

    experience studies, valuation, financial reporting schedules Separate rules applied for experience studies, valuation, financial reporting schedules • Date of termination in the future, policy status terminated • Terminated policies with active coverages • Change of primary insured’s gender on joint life plans • Inconsistencies between age, DOB and issue date • System conversion errors $20m reserve for poor quality data
  8. consistent cleansed data for actuarial After: Single extract, single set

    of rules Reduction in head count, but increased number of actuaries No year-end panic Increased work capacity – more frequent reporting, more analysis Increased responsibilities, need to develop new skills Released $20m reserve for poor quality data And… I could never work in a traditional actuarial environment again
  9. Improving Analytics sales reporting salesforce analysis accounts underwriting analysis claim

    analysis inforce demographics valuation analysis valuation data extracts experience studies earnings-by-source actuarial involvement analysis frequency retention analysis customer analysis
  10. Improving Analytics Traditional Approach BI Approach Prepare Model / Calcs

    Apply Data Report Prepare Data Model / Calcs Analysis
  11. Improving Analytics: Real Life Example Medicare Supplement rate increases $1bn

    premium income ~80% of business applied for increases Assuming 6% increase 80% x $1bn x 0.06 x 1/12 = $4m 20% x $1bn x 0.06 = $12m
  12. Marketing Understanding your agents and customers… Coverage Agent Policy Claim

    Group Customer Sales Team Office Coverage Agent Policy Claim Group Customer Sales Service
  13. Underwriting – Predictive Modeling Automate for faster, more consistent decisions

    • Reduce cost, NTU’s • Process to improve • over time
  14. Analytical Competitors 1. Senior executives strongly advocate analytics and fact-based

    decision making 2. Widespread use of descriptive statistics, predictive modeling, and complex optimization techniques 3. Analytics used across multiple business functions 4. Enterprise-wide approach to analytical tools, data, and process
  15. Is there really a magic recipe? Management Support Widespread and

    in multiple business areas But…  Does not need to be complex  Coordinated, not centralize control
  16. Opportunities for Actuaries in Business Analytics As part of the

    SOA's strategic objective to create and promote new areas of practice, this initiative will determine whether significant opportunities exist for actuaries in business analytics and, if so, identify projects the SOA should undertake to explore and develop these opportunities. Session tomorrow Actuaries in Advanced Business Analytics
  17. Summary • Consistent cleansed data • Improve analytics – Accelerated

    – More depth – Lower cost • Extend analytical decision making