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Predictive Analytics: From BackOffice to Front OfficeRichard R. Lee, Executive ConsultantThe Speyside Group
Professional Profile  Richard Lee – “Executive Consultant in Business   Informatics & Advanced Analytics”  I Guide & Adv...
What is Predictive Analytics??pre·dic·tive Adjective  • “Relating to or having the effect of predicting an event or    res...
The Evolution of Analytics                                                                                                ...
Predictive Analytics & Big Data(1)           Traditionally, Predictive Analysis was focused on            well-defined da...
Predictive Analytics & Big Data(2)           Creating a “Real-time Predictive Enterprise” is the            goal of every...
Predictive Analytics & Big Data(3)           Critical to the Success of the “Predictive Enterprise”            is the per...
Industry Segments: Banking & Insurance           Banking & Insurance are the most mature segments            in terms of ...
Predictive Insurance                       Broker                                                                         ...
Predictive Claims ProcessingPredictive Analysis:                                    Create:• Customer Behaviours, Linkages...
Other Industry Verticals:            Predictive Analysis has/is becoming pervasive in virtually             all Industry ...
The Democratization of Analytics  How do we “move Predictive Analysis from the Back   Office to Your Office?   • For far ...
Looking Forward  The distant future as seen from 10-years ago has   become manifest already;   • Smart Devices and Embedd...
Summary and Hand-Off  Predictive Analytics is a mature discipline, but   currently confined to an “elite community of ana...
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Zd sap - predictive analytics - 3-26-13 r1

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Zd sap - predictive analytics - 3-26-13 r1

  1. 1. Predictive Analytics: From BackOffice to Front OfficeRichard R. Lee, Executive ConsultantThe Speyside Group
  2. 2. Professional Profile  Richard Lee – “Executive Consultant in Business Informatics & Advanced Analytics”  I Guide & Advise Senior Executive Teams in their pursuit of “The Predictive Enterprise”  Worked in many “Information-driven Verticals” over long consulting career; • Banking & Insurance • Utilities • Consumer Goods & Retail • Telecoms • Government • Technology PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  3. 3. What is Predictive Analytics??pre·dic·tive Adjective • “Relating to or having the effect of predicting an event or result”a·nal·y·sis Noun • “Detailed examination of the elements or structure of something, typically as a basis for discussion or interpretation.”Predictive Analytics: “Modeling, machine learning, and data mining thatanalyze current and historical facts to make predictionsabout future, or otherwise unknown, events.”
  4. 4. The Evolution of Analytics 10’s Embedded 00’s Analysis Predictive 90’s Analysis Descriptive Analysis 80’s Statistical Analysis4 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  5. 5. Predictive Analytics & Big Data(1)  Traditionally, Predictive Analysis was focused on well-defined data sets • Customer Churn & Up Sell/Cross Sell • Risk & Fraud • Actuarial (Claims & Underwriting)  Finely Tuned Models were employed • Extensive A/B & Champion Challenger Testing/Development • Maintained by PhD Statisticians, Actuaries and Decision Scientists  Analysis was time consuming and always “after the fact” • Months to Years of Development & Optimization5 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  6. 6. Predictive Analytics & Big Data(2)  Creating a “Real-time Predictive Enterprise” is the goal of every “Analytics Centric” organization today. • Forward Looking pervasive use of all Information aka Big Data • Embedded Real Time Analysis of Customer Behavior, Opportunities & Risks and Sources of Competitive Advantage • Leveraging deep knowledge of the Past and the Present to “Predict” with high accuracy “what will happen next” and to exploit this knowledge in real time to; – Delight the Customer & Win his/her Loyalty – To Mitigate Risks while Maximizing Opportunities – To Clearly Differentiate your Services & Products from the Competition – To Maximize your Operational Efficiencies and Productivity.6 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  7. 7. Predictive Analytics & Big Data(3)  Critical to the Success of the “Predictive Enterprise” is the pervasive use of all Information Resources across your Enterprise by an Analytics-driven Executive Team and Workforce” • Big Data & the deep historical data repositories working in a “collective fashion” to present a 360 view. • Predictive Analytics engines embedded in Enterprise Applications • Analytics Tools are available for everyone to exploit from anywhere. • Deep competencies in Analytics to support Front Line Users and Analysts.  Creating and Driving “A Culture of Analytics” across the Enterprise should be the CEO’s #1 Priority & Responsibility.7 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  8. 8. Industry Segments: Banking & Insurance  Banking & Insurance are the most mature segments in terms of using Predictive Analytics. • Customer Insights & Opportunities • Fraud & Risk Management • Quantitative Finance • Pricing and Claims  Case Study in Detail – North American P&C Insurer • Transformational Approach • Move from “Backwards looking” to “Predictive view” of all aspects of the business. • Goal was “Near Real Time, Holistic Management” • Predictive Analysis embedded in all business functions.8 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  9. 9. Predictive Insurance Broker Strategic P&C Goals Moments of Insurer TheCustomer Truth Analytically-Optimized Improve Business Processes Customer I buy/renew Perception Customer Insights Competitive Pricing I license Improve Predictive Claims Financial Oversight Employee I claim Experience Underwriting Licensing I amend Maintain ERM/Solvency II I cancel Financial Security Analytics- Driven Foresight Retention Customer Attractive and Fraud Best Offers Customer Employee Risk LTV Products Upsell/Cro Mitigation (Claims) Experience Engagement Assessment ss Sell Business Intelligence Advanced Analytics Performance & Risk Mgmt. COE Enterprise Information Subject Areas & Analytical Models Information Delivery Information Foundation Information Integration Information Sources (Structured & Unstructured) 9
  10. 10. Predictive Claims ProcessingPredictive Analysis: Create:• Customer Behaviours, Linkages, etc. • Intelligently scripted/generated questions• Current claims activities • Empower Knowledge Workers• Claims history • Drive Operational Excellence• External data (Partners, MD, BI, Gov. 3rd •Delight the Customerparties, etc.) Service Fast Claims Application Track Environment First Request Notification Predictive Additional of Loss Claims Information (FNOL) Platform (Embedded) SIU Information Infrastructure Suspect PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  11. 11. Other Industry Verticals:  Predictive Analysis has/is becoming pervasive in virtually all Industry Segments; • Fast Moving Consumer Goods & Retail • Healthcare • Government • Energy & Utilities • Transportation • Telecommunications • Entertainment • Publishing • Etc., etc.  Leaders within each of these Verticals have created unique Sources of Competitive Advantage for their organization as they have become “Predictive Enterprises”.11 © 2011 Ziff Davis, Inc. - All Rights Reserved. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  12. 12. The Democratization of Analytics  How do we “move Predictive Analysis from the Back Office to Your Office? • For far too long PA has been the domain of the so-called “data geeks” and “Bayesians”. – We need to make PA more pervasive by moving it to everyone’s “Work Platform” e.g. Desktop, Laptop, Tablet, Smart Device, etc. – We must bootstrap everyone’s skills and knowledge to be “Analytics Literate” • We must “unleash the power of all of our sources of Information” to create unique and actionable insights for everyone to leverage. – We must move away from “batch driven & IT-lead “ to a “real-time & Business-lead” Operational Model for delivering Information- based, Analytics-driven Outcomes. – We must build Governance into all Analytics endeavors as we have done with our Information-related ones, using a holistic approach. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  13. 13. Looking Forward  The distant future as seen from 10-years ago has become manifest already; • Smart Devices and Embedded Applications have accelerated the “inflection point” for creating massive streams of Information (aka Big Data) and the Pervasive use of Analytics to drive decision making.  Predictive Analysis will be embedded in all Enterprise Applications and Services going forward. • Decision Making at the Point of Contact is paramount. • An integrated view of the Customer is essential to “Delighting him or her” • Windows of Opportunity are shrinking to zero.  Creating a “Culture of Analysis” along with Delivering “Analytics as a Service” to Everyone is the Critical Path • A, integrated, long-range Analytics Strategy is the key to driving a successful outcome to this Top Down Vision. PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase
  14. 14. Summary and Hand-Off  Predictive Analytics is a mature discipline, but currently confined to an “elite community of analysts” in most, if not all Enterprises.  The so-called “Democratization of Analytics” will remove these barriers to broad Enterprise Adoption.  A long-range, business driven Analytics Strategy (aligned with the Organization’s overall strategy) is required to insure a successful “Transformation into a Predictive Enterprise” • People, Process, Technology & Culture  A critical first step in this transformational journey is “To Move PA from the Back Office to Your Office” PCMag.com • ExtremeTech • Geek.com • LogicBUY • BuyerBase

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