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Business Friendly Data Mining
1) James Taylor is the CEO of Decision Management Solutions and helps clients improve business decisions through analytics. 2) Successful decision management requires clearly defining target decisions, understanding their business impact, and decomposing them to determine data and analytic needs. 3) The key is then deploying analytical decisions into existing business systems and processes to automate and improve targeted decisions.
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- 1. Business Friendly Data Mining 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. Data Mining andPredictive Analytics WORK ©2012 Decision Management Solutions 2
- 4. Success Requires AClear Target ©2012 Decision Management Solutions 3
- 5. Success Requires Deployment ? ? Decision ©2012 Decision Management Solutions 4
- 6. Success Requires Collaboration Business Decision ©2012 Decision Management Solutions 5
- 7. Business-Friendly Data Mining
- 8. Decision Management isthe proven approach used to manage decisions, set goals for predictive analytic efforts, apply and deploy predictive analytics effectively ©2012 Decision Management Solutions 7
- 9. Step 1 Be clearwhich decisions you are improving ©2012 Decision Management Solutions 8
- 10. A Decision A choice or selection Based on facts That ends uncertainty And results in action ©2012 Decision Management Solutions 9
- 11. Discover High ROIDecisions Risk decisions Customer decisions How risky is this deal How profitable might this and what should we do? customer be? Predict risk of a bad Predict response, outcome opportunity, potential Rigorous, regulated Rapidly evolving Fraud decisions How likely is this to be fraudulent? Predict risk of fraud “Black box” ©2012 Decision Management Solutions 10
- 12. Use Questions toDefine Decisions For each decision Name Description Question and a defined set of allowable answers Any other results to be returned with the answer ©2012 Decision Management Solutions 11
- 13. Step 2 Understand howthose decisions impact the business ©2012 Decision Management Solutions 12
- 14. Target Decision-making OnKPIs Strategy defines KPIs KPIs measure operations Operational decisions affect KPIs The link between decisions and KPIs is critical ©2012 Decision Management Solutions 13
- 15. Define The BusinessContext Key Performance Business Processes Indicators What processes does this How is success measured business execute? in this business area? Which business processes How to tell good decisions will need decisions made? from bad ones and the value of focusing on a Business Events decision What key business events trigger business behavior? Organizations When will decisions be What is the basic required and in what organization structure context Teams, departments, Existing Systems groups not individuals What are the core systems Who cares about the for this business area? decisions How will you have to deploy decision making? ©2012 Decision Management Solutions 14
- 16. Put Analytics InContext Processes Know which business Activities require decisions processes will be improved by your analytics Events Trigger decisions Know when your analytics might be Systems calculated Implement decisions Know how you will have Organizational Units to deploy your analytics Make decisions Own decisions Know who cares about Are impacted by decisions your analytics and who will have to believe them ©2012 Decision Management Solutions 15
- 17. Step 3 Decompose decisionsto understand them ©2012 Decision Management Solutions 16
- 18. 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 17
- 19. Case study: Insurer Businesschallenges Solution Benefits Use analytics to Model and Find the decisions improve decompose that could be underwriting decisions impacted and Map decisions to refocused analytic Embed analytics in effort claim processing systems and application organizations Constrained analytic effort to ensure successful implementation
- 20. Decision Models AreRevealing ©2012 Decision Management Solutions 19
- 21. Decision Models AreRevealing 2 ©2012 Decision Management Solutions 20
- 22. Step 4 Deploy analyticaldecisions to the systems and processes that need them ©2012 Decision Management Solutions 21
- 23. Build decision-making components Operational Systems Decision Analytic Systems ©2012 Decision Management Solutions 22
- 24. Create Decision ManagementSystems Agil e Analyti c Adaptiv e ©2012 Decision Management Solutions 23
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- 27. Decision Management Establishesa clear target Enables rapid deployment Creates a collaboration framework Business Decision
- 28. Thank You James Taylor, CEO jtaylor@decisionmanagementsolutions.c om
Editor's Notes
- #4 The power of predictive analytics is their ability to turn uncertainty about the future into usable probability
- #5 Goals and measures of success are clear
- #6 Business, IT and Analytics team can collaborate effectively
- #23 [twitter]#decisionmgt systems link analytic systems to operational systems[/twitter]
- #24 AgileChanging CircumstancesComplianceProcess ImprovementAnalyticManaging RiskReducing FraudTargeting and RetainingFocusing ResourcesAdaptiveFinding New ApproachesTesting and LearningManaging Trade-offs