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Models collecting dust? How to transform your results from interesting to impactful
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Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.

Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.

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Models collecting dust? How to transform your results from interesting to impactful Presentation Transcript

  • 1. Models Collecting Dust?James Taylor CEO
  • 2. Your presenter – James Taylor CEO of Decision Management Solutions Works with clients to improve their business by applying analytic technology to automate & improve decisions Spent the last 9 years championing Decision Management and developing Decision Management Systems ©2012 Decision Management Solutions 1
  • 3. ChallengesOr why your models are gathering dust
  • 4. Knowing is not enough Those who know first, win Those who ACT first, win Provided they act intelligently ©2012 Decision Management Solutions 3
  • 5. It’s hard to communicate your value ©2012 Decision Management Solutions 4
  • 6. Time to deploy models matters ©2012 Decision Management Solutions 5
  • 7. Cottage industries don’t scale ©2012 Decision Management Solutions 6
  • 8. Challenges with predictive analytics Actions are needed not just predictions Begin with the decision in mind The business does not understand analytics A business context for analytics Analytic models age quickly Cottage industries don’t scale Industrialize your analytic processes ©2012 Decision Management Solutions 7
  • 9. Begin with thedecision in mind
  • 10. Decision Management is the proven approach used to manage decisions and applypredictive analytics effectively ©2012 Decision Management Solutions 9
  • 11. 3 Steps to Decision Management Discover Build Improve ©2012 Decision Management Solutions 10
  • 12. What is a decision? Data is gathered, considered A choice or selection is made That results in a commitment to action ©2012 Decision Management Solutions 11
  • 13. Different kinds of decisions Strategic Decisions • Few in number, large impact • Should we acquire this company or exit this market? Tactical Decisions • Management and control, moderate impact • Should we re-organize this supply chain, change risk management approach? Operational Decisions • Day-to-day decisions that affect one transaction or customer • Best offer for this customer ?How risky is this loan? Is this claim fraudulent? ©2012 Decision Management Solutions 12
  • 14. Decisions are the focal point for risk Risk is not acquired in “big lumps” but one transaction at a time ©2012 Decision Management Solutions 13
  • 15. Decisions maximize customer value ©2012 Decision Management Solutions 14
  • 16. Three kinds of analytic decisions Risk Fraud Opportunity ©2012 Decision Management Solutions 15
  • 17. Analytics power operational decisions How do I… prevent this customer from churning? convert this visitor? acquire this prospect? make this offer compelling to this person? identify this claim as fraudulent? correctly estimate the risk of this loan? It’s not about “aha” moments It’s about making better operational decisions ©2012 Decision Management Solutions 16
  • 18. Case: RetailerBusiness challenges Solution BenefitsGrocery chains are Tailored promotions Increased revenuebattling for market integrated with Deep knowledge ofshare loyalty program customers acrossCustomer loyalty is Integrated system formatsessential for growth from back office to More effectiveLoyalty to the brand, point of sale promotionalnot a single store Consistently campaignsformat compelling offers across channels ©2012 Decision Management Solutions 17
  • 19. A business context for decision making
  • 20. Candidate decisions Determine if a customer is eligible for a loan Calculate the discount for an order Assess the risk of a transaction Select the terms for a deal Choose which claims to Fast Track These are decision words The system must answer a question each time ©2012 Decision Management Solutions 19
  • 21. Target decision-making on KPIs Strategy defines KPIs KPIs measure operations Operational decisions affect KPIs The link between decisions and KPIs is critical ©2012 Decision Management Solutions 20
  • 22. Decision to KPI mapping KPIs impacted by improvement in decision Customer Customer Losses Retention KPI 5 Churn Service Budget CallsWhat retention offer shouldbe made? ↑ ↑ ↓ ?What initial price should beoffered? ↑ ↑Should an intervention callbe made? ↓ ↓Decision 3 ?… ©2012 Decision Management Solutions 21
  • 23. Decompose the decisioning What is required to make decision? Guidelines, policy documents Human expertise Regulations Existing system logic Data describing the case External reference data Predictive Analytic Models Data Mining Results The results of other decisions ©2012 Decision Management Solutions 22
  • 24. Decisions provide context Processes Know which business Activities require decisions processes will be improved by your analytics Events Know when your analytics Trigger decisions might be calculated Systems Know how you will have to Implement decisions deploy your analytics Organizational Units Know who cares about Make decisions your analytics and who will Own decisions have to believe them Are impacted by decisions ©2012 Decision Management Solutions 23
  • 25. Case study: InsurerBusiness challenges Solution BenefitsUse analytics to Model and Find the decisionsimprove underwriting decompose decisions that could be Map decisions to impacted andEmbed analytics in refocused analyticclaim processing systems and organizations effortapplication Constrained analytic effort to ensure successful implementation
  • 26. Industrialize Analytics
  • 27. Embed Predictive Analytics ? ? Decision ©2012 Decision Management Solutions 26
  • 28. Analytic Insight Management Data Management Data Preparation Data Visualization & Analysis Modeling In-database Modeling Model Validation Deployment and Scoring In-database Scoring Model Monitoring Model Tuning Model Tuning Repository ©2012 Decision Management Solutions 27
  • 29. Build decision-making components Operational Systems Decision Analytic Systems ©2012 Decision Management Solutions 28
  • 30. Case study: Cable TVBusiness challenges Solution Benefits1.2M households Predictive analytics to 13-18% cross-sell hitMany single-product predict churn, cross- rate on averagehouseholds sell Up to 40% cross-sellWhole industry Business rules use analytics and data to success rate for somesuffers from lowloyalty and 20%+ drive dynamic scripts Teams using thecustomer churn Embedded in call scripts have moreIncreasing center application to salescompetition and improve decision making Reduced churn by 20-changing regulations 30% ©2012 Decision Management Solutions 29
  • 31. Some Pitfallsand how to avoid them.
  • 32. Operational decisions are at the center Business Decision ©2012 Decision Management Solutions 31
  • 33. Don’t just create a decision point ©2012 Decision Management Solutions 32
  • 34. Create Continuous improvement ©2012 Decision Management Solutions 33
  • 35. Case: State dept of taxationBusiness challenges Solution BenefitsPaper tax returns Single central Recovered millionsincreased costs and taxpayer database of dollars fromslowed responses Integrated system dubious tax returnsInformation system Sophisticated real- Increased collectionsilos time predictive of unpaid taxesManual fraud analytics Decreased numberdetection and return of questionablereview returns Increased customer satisfaction ©2012 Decision Management Solutions 34
  • 36. Questions?
  • 37. Decision Management Systems What if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Decision Management Systems can do all that and more. This book shows how to integrate operational and analytic technologies to create more agile, analytic, and adaptive systems. Discount Code: TAYLOR4389For more information about this new release, visitwww.decisionmanagementsolutions.com/book ©2012 Decision Management Solutions 36
  • 38. In a Predictive Enterprise, analytics are… Used in every transactionPervasive At the point of contact/delivery In operational decision making From reporting to prediction and forecastingPredictive Data mining Predictive analytics and scoringActionable Decisions being made, actions being taken Decision Management Systems Decision Support Systems ©2012 Decision Management Solutions 37
  • 39. Begin with the Decision in mind Discover Build Improve Find the decisions that matter to your business and model them ©2012 Decision Management Solutions 38
  • 40. Create an Analytic Factory ©2012 Decision Management Solutions 39
  • 41. Thank You James Taylor, CEOjames@decisionmanagementsolutions.com 40