Analytic Journeys from Predictive Analytics World


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How do companies move from databases and BI to pervasive, predictive, actionable analytics? This presentation summarizes research conducted with IBM.

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  • Many companies are adopting analytics, with the most sophisticated increasingly pushing predictive analytics to the point of contact, the very tip of their organizations. Based on research conducted with IBM and IBM clients, this presentation will show how companies in a variety of industries have made progress on their analytic journeys. While each industry, each company, is different, this presentation will describe the common steps on the journey to pervasive, actionable, predictive analytics.1. The results of research with IBM clients on how companies adopt analytics in stages2. What the right next step in adopting analytics would be for them3. How analytics can help them transform their business
  • Real-time optimizationContinually optimize in real-time, managing trade-offs and predictionsInstitutional actionCreate an infrastructure that supports differentiated treatment in operationsPredictive actionPredict likely responses to treatment and use this to select and prioritize actionsDifferentiated ActionAnalytically establish what alternative actions can be takenKey targets/segmentsMine data to identify segments or sub-populations and prioritizeData in orderIntegrate, clean and organize data to support decisions
  • Analytic Journeys from Predictive Analytics World

    1. 1. Analytic Journeys<br />James Taylor,<br />CEO<br />
    2. 2. About me<br />Independent consultant working with clients to help automate and improve decisions<br />Researcher and independent analyst in decision management techniques and decisioning technology<br />20 years experience in all aspects of software including time in PeopleSoft R&D and at Ernst & Young<br />Blogger, speaker, writer<br /><br />
    3. 3. The research<br />The end game<br />The journey<br />Critical success factors<br />Related research<br />Next Steps<br />
    4. 4. The One Slide You Need<br />Pervasive, predictive, actionable analytics are the goal of the journey<br />Many companies have BI and predictive analytics on separate tracks<br />There are reasonable steps to take from BI to predictive analytics<br />Build an information platform first but…<br />…keep the decision in mind<br />Don’t forget to operationalize, institutionalize<br />
    5. 5. The research<br />©2009 Decision Management Solutions<br />5<br />
    6. 6. ©2009 Decision Management Solutions<br />6<br />The Research<br />Sponsored by IBM<br />Reviewed case studies and interviewed customers<br />Various industries:<br />Telecommunications (customer retention)<br />Retail (consumer marketing)<br />Healthcare Providers (patient care)<br />K-12 Education (student achievement)<br />Government agencies (operations)<br />Banking (customer centricity)<br />
    7. 7. ©2009 Decision Management Solutions<br />7<br />Publishing as a series of white papers<br />
    8. 8. The end game<br />©2009 Decision Management Solutions<br />8<br />
    9. 9. ©2009 Decision Management Solutions<br />9<br />The end game for analytics<br />Pervasive<br />Used in every transaction<br />At the point of contact/delivery<br />In operational decision making<br />Actionable<br />Decisions being made, actions being taken<br />Action-support not decision-support<br />Predictive<br />From reporting to prediction and forecasting<br />Predictive analytics and scoring<br />
    10. 10. Telecom Provider<br />Business challenge:<br />100M customers and 3Bn calls / day<br />200TB of customer information<br />1.3M Retail partners<br />Rural and urban consumers, large and small companies<br />Solution:<br />Integrated data warehouse across all channels, all products<br />Real-time analytics for micro-segmentation, offer targeting<br />Web, retail, call-center and mobile channels<br />Benefits:<br />Rapid growth with 2-3M new customers/month<br />Growing and accelerating Revenue Market Share<br />
    11. 11. The journey<br />©2009 Decision Management Solutions<br />11<br />
    12. 12. The journey<br />Platform<br />Delivery<br />
    13. 13. Platform - Integration<br />©2009 Decision Management Solutions<br />13<br />Collect and integrate information about <br />Customers<br />Students<br />Products<br />Citizens<br />Have a purpose (Decision) <br />Decision &lt;&gt; original motivation<br />Operational benefits<br />
    14. 14. Platform - Understanding<br />©2009 Decision Management Solutions<br />14<br />Analysis and reporting still central<br />Analyzing at the group level <br />Facility<br />School<br />Program<br />Not management/financial reporting<br />New users<br />
    15. 15. Platform - Targeting<br />©2009 Decision Management Solutions<br />15<br />Segmentation<br />Group analysis<br />Trends and patterns<br />Analytically focus resources<br />Non-intuitive results <br />
    16. 16. K-12 School District<br />Business challenge:<br />Unable provide effective intervention for at-risk students<br />48% drop-out rate <br />Attendance, test, student data disconnected and out of date <br />Solution:<br />Transform compliance, accountability data into a strategic asset <br />Analytics to identify at risk students <br />Intervene early in time to make a difference<br />Benefits:<br />Proactive alerts when students cross at-risk thresholds <br />Identify which programs are likely to work for each student<br />Reduce costs<br />
    17. 17. Delivery - Operationalization<br />©2009 Decision Management Solutions<br />17<br />Integration with operational systems, processes<br />Increased granularity of treatment<br />Increasingly prescriptive<br />Action support not just decision support<br />Infrastructure for differentiated treatments <br />Business rules management<br />
    18. 18. Delivery - Prediction<br />©2009 Decision Management Solutions<br />18<br />Looking forward<br />Forecast<br />Predict<br />Calculate propensity<br />Fraud detection, targeting, retention<br />Proactive decision-making<br />Micro-segmentation<br />
    19. 19. Delivery - Optimization<br />©2009 Decision Management Solutions<br />19<br />Next Best Action<br />Formal trade-off analysis<br />Personalization, markets of one<br />Pervasive<br />Predictive<br />Actionable<br />
    20. 20. Retailer<br />Business challenge:<br />Grocery chains are battling for market share<br />Customer loyalty is essential for growth<br />Loyalty to the brand, not a single store format<br />Solution:<br />Highly tailored promotions integrated with loyalty program<br />Integrated system from back office to point of sale<br />Consistently compelling offers across channels<br />Benefits:<br />Increased revenue<br />Deep knowledge of customers across formats<br />More effective promotional campaigns<br />
    21. 21. Critical success factors<br />©2009 Decision Management Solutions<br />21<br />
    22. 22. ©2009 Decision Management Solutions<br />22<br />Critical Success Factors<br />
    23. 23. 23<br />Start by focusing on the value<br />Better decision<br />Analytic insight<br />Derived information<br />Available data<br />
    24. 24. 24<br />Start by focusing on the value<br />Better decision<br />Analytic insight<br />Derived information<br />Available data<br />
    25. 25. State department of taxation<br />Business challenge:<br />Paper tax returns increased costs and slowed responses<br />Siloed information systems<br />Manual fraud detection and return review<br />Solution:<br />Single central taxpayer database <br />Sophisticated real-time predictive analytics<br />Benefits:<br />Recovered millions of dollars from questionable tax returns<br />Increased collection of unpaid taxes<br />Decreased number of questionable tax returns<br />Increased customer satisfaction<br />
    26. 26. Related research<br />©2009 Decision Management Solutions<br />26<br />
    27. 27. Some other recent work on analytics<br />Analytics at Work<br />Tom Davenport, Jeanne Harris, Robert Morison<br />Harvard Business School Press<br />More than 100 organizations<br />28 companies in sponsored research<br />Survey on managing analytical talent<br />Breaking away with business analytics and optimization<br />IBM Institute for Business Value<br />400 respondents, mostly business executives<br />Characteristics of high performers<br />
    28. 28. Ladder of analytical applications<br />Analytics at Work: Smarter Decisions, Better ResultsTom Davenport, Jeanne Harris and Robert Morison<br />
    29. 29. Business direction<br />Trusted information<br />2.4x<br />2.5x<br />4.4x<br />2.4x<br />2.0x<br />2.7x<br />Analytical and predictive tools<br />Dashboards and visualization<br />Business rules management<br />Content management<br />Master data management<br />Data integration tools<br />Key: Top performers (i.e., 1st quintile relative to industry peers) <br /> Lower performers (i.e., 4th and 5th quintile relative to industry peers)<br /> Relative difference of top performers to lower performers<br />Source: Breaking Away with Business Analytics and Optimization: New intelligence meets enterprise operations at <br />Some differences of high performers<br />
    30. 30. Next Steps<br />©2009 Decision Management Solutions<br />30<br />
    31. 31. Action Plan<br />
    32. 32. More information<br />White papers<br /><br />Decision Management Solutions<br /><br />Blog<br /><br />©2009 Decision Management Solutions<br />32<br />
    33. 33. Blog:<br />