This document discusses how predictive analytics can improve operational decisions and business outcomes. It provides examples of how predictive models can be applied to decisions around customer retention, campaign response, risk assessment, and fraud detection. The key challenges are effectively deploying models and ensuring analytics lead to concrete business actions. Decision management systems aim to address this by separating decision-making processes from operations and creating a closed loop between analytics and measurable results. The document advocates starting with high-impact decisions, engaging both business and IT stakeholders, and moving rapidly from predictions to actions through decision management.

1. Putting predictive analytics to work James Taylor, CEO

2. The ROI of better operational decisions Analytics and operational decisions Challenges in putting predictive analytics to work Decision Management Next Steps

3. The One Slide You Need Better operational decisions yield high ROI Analytics can improve operational decisions You need to Focus on actions Deploy rapidly Engage business and IT Decision Management Focuses on decisions, Combines business rules with analytics Puts predictive analytics to work

4. Better operational decisions offer high ROI

5. ©2009 Decision Management Solutions 5 There are different types of decisions High-value, low-volume decisions Medium-value, medium-volume decisions Low-value, high-volume decisions High ECONOMIC IMPACT Low Low High DECISION VOLUME After Smart (Enough) Systems, Prentice Hall 2007

6. ©2009 Decision Management Solutions 6 Small improvements add up

7. “The essence of strategy is choosing to perform activities differently than rivals do.” Dr. Michael Porter, Harvard Business School

8. Better underwriting decisions

9. Analytics improve operational decisions ©2009 Decision Management Solutions 9

10. Analytics have power in decision making CustomerRetention CampaignResponse AcquisitionRates Online Conversion Fraud Crime WastedSpend Risk

11. ©2009 Decision Management Solutions 11 See through uncertainty with analytics % % % Predictive analytics turn uncertainty into usable probability

12. Challenges in putting predictive analytics to work

13. Knowing is not enough ©2009 Decision Management Solutions 13 Those who know first, win Those who ACT first, win Provided they act intelligently

14. Time is accuracy, accuracy is money

15. Operational decisions at the center

16. Monitoring and compliance

17. Takeaways Better decisions means actions not predictions Time to business impact is critical The only results are business results Analytics requires IT and business engagement Compliance needs concrete execution

18. Case: Premier Bankcard ©2009 Decision Management Solutions 18 Scores deployed Fraud risk Credit risk Customer value Critical Success Factors Analytics must lead Business must support But deployment AND testing require IT engagement Building IT respect takes time

19. Decision Management

20. ©2009 Decision Management Solutions 20 Decision Management is A business discipline that builds on existing enterprise applications to put data to work manage uncertainty increase transparency give the business control

21. ©2009 Decision Management Solutions 21 5 core principles of decisioning Identify, separate and manage decisions Use business rules to define decisions Analytics to make decisions smarter No answer is static Decision-making is a process

22. ©2009 Decision Management Solutions 22 Delivering Decision Management 3 stages to better operational decisions Create a “closed loop” between operations and analytics to measure results and drive improvement Design and build independent decision processes to replace decision points embedded in operational systems Identify the decisions (usually about customers) that are most important to your operational success

23. Addressing our challenges

24. Case: Infinity Insurance Claims Innovation 12,000-13,000 claims/month Recession – lower expenses, 25% fewer staff Claims adjudication with rules, analytics Results 1100% increase in fast track rate Loss adjustment expense from 14% to 11% 33% higher subrogation returns Subrogation recovery up by $10m/year

25. Next Steps

26. Begin with the Decision in Mind

27. Action Plan

28. Blog: www.jtonedm.com