Putting Analytics To Work

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    Page Building effective analytic models is a tough job. But even when the models are ready there is more to do. Business processes and information systems must be changed to put those models to work if you are to gain maximum value from your analytic efforts. This presentation will offer best practices suggestions to address some of the common problems faced by organizations when attempting to implement analytics into their business practices. I am not going to focus today on analytics techniques or on the use of Xeno but on the why and how of putting analytic models to work in information systems. One aside – I will talk about “analytics” and about “models” and I mean both in a very broad way. A model could be a scorecard, a decision tree or a neural net from my perspective. Hopefully it will be clear from the context as we go but, if it is not, ask away.

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    Putting Analytics To Work - Presentation Transcript

    1. Putting Analytics to Work Overcoming the challenges of putting analytics to work in information systems James Taylor Principal Smart (enough) Systems LLC September 2008
    2. Agenda
      • Getting value by impacting systems
      • Decisions, decisions, decisions
      • Challenges
      • Recommendations
    3. Why Smarter Systems? Decision-Making Well-Defined Increasingly Complex Timeliness Days Real-time Objectives Local and clear Complex Trade-Offs Regulations National and simple Complex and global Changes to Strategy Every 3-5 Years Constant Operational Volume Low High
    4. So What IS A Smarter System
      • Operational
      • Real-Time
      • Rapidly evolving - agile
      • Learning
      • Demonstrably Compliant
      • Cost-Effective
      • Business-Driven
    5. Smarter Systems Make More Decisions People Not Made Embedded People Embedded Not Made New Before After Larger boxes represent more decisions, by volume
    6. Different kinds of decisions Low High High ECONOMIC IMPACT OF INDIVIDUAL DECISION Low DECISION VOLUME High-value, low-volume decisions Medium-value, medium-volume decisions Low-value, high-volume decisions
    7. Decisions, Decisions, Decisions
    8. Analytics put the “smarts” in smarter systems
      • Automate Decision
      • Apply policies, regulations
      • Segment customers
      • Predict risk, value
      • Optimize decision
      Web http://www.f Email Call Center Mobile
    9. Putting Analytics To Work – More Examples Process Automation Analytics Commercial Loans Capture and validate data Apply policies and regulations Order additional reports Manage worklists Dispatch outcomes Turn historical payment data into an assessment of this prospect’s credit risk Segment prospects based on statistically significant factors Sales Capture sales order Calculate pricing, discounts Display cross-sell offer Capture payment information Process order Display delivery estimate Dispatch goods Optimize price to maximize value Identify the cross-sell offer most likely to be successful Predict likelihood of on-time delivery Returns Capture return Validate that return does not violate policy Make exception if appropriate Process refund or store credit Calculate risk of fraudulent return Calculate likely future value of customer when considering exception
    10. Challenges
      • Predictions into actions
      • Time to deploy
      • The business
      • IT
      • Impact analysis
      • Monitoring
      • Compliance
    11. Turning predictions into actions Those who know first, win Those who ACT first, win Provided they act intelligently
    12. Takeaways
      • Better decisions require actions, outcomes, not just predictions
    13. Time to deploy models
    14. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
    15. The Business
    16. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
      • Only business users can truly decide if one approach is better than another. Teach them adaptive control, give them simple interfaces, project business results
    17. IT Attribute Data Design Application Database Historical Data
    18. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
      • Only business users can truly decide if one approach is better than another. Teach them adaptive control, give them simple interfaces, project business results
      • Broad adoption of analytics in operational systems requires analysts to reach out and educate IT
    19. Impact analysis for changes, new data
    20. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
      • Only business users can truly decide if one approach is better than another. Teach them adaptive control, give them simple interfaces, project business results
      • Broad adoption of analytics in operational systems requires analysts to reach out and educate IT
      • Work with IT to develop a common impact analysis approach so that data changes don’t break models
    21. Monitoring
    22. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
      • Only business users can truly decide if one approach is better than another. Teach them adaptive control, give them simple interfaces, project business results
      • Broad adoption of analytics in operational systems requires analysts to reach out and educate IT
      • Work with IT to develop a common impact analysis approach so that data changes don’t break models
      • Monitor decisions closely and be part of improving them
    23. Compliance
    24. Takeaways
      • Better decisions require actions, outcomes, not just predictions
      • Consider your analytics “done” only once they are impacting the business
      • Only business users can truly decide if one approach is better than another. Teach them adaptive control, give them simple interfaces, project business results
      • Broad adoption of analytics in operational systems requires analysts to reach out and educate IT
      • Work with IT to develop a common impact analysis approach so that data changes don’t break models
      • Monitor decisions closely and be part of improving them
      • When compliance is an issue, focus on models with concrete execution and rules that can be logged
    25. Action Items Decisions Education Architecture Rules / Execution Constant Improvement
    26. Decisions are at the heart of three groups
    27. Smart (Enough) Systems – The Book
      • How key business trends impact the decision-making process
      • Why organizations need systems smart enough to cope with these trends
      • How decision automation can make their systems smart enough
      • How to translate decisions into a corporate asset and competitive advantage
      • The ROI and business impact of better decisions and smarter systems
      • The core concepts and technologies needed and how they work together
      The book is full of insightful examples of problems solved by applying Enterprise Decision Management across various industries and outlines a practical and incremental method for implementing the technology.
    28. Thank You James Taylor [email_address] http://www.smartenoughsystems.com Blog: http://www.smartenoughsystems.com/wp

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