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Customer Decision Management - 5 Benefits
The document discusses the benefits of customer decision management, emphasizing the need for accurate, real-time, and scalable decision-making processes. It outlines three stages to improve operational decisions and highlights the importance of analytics in driving actionable insights. Additionally, it focuses on achieving competitive differentiation through better customer interactions and personalized marketing strategies.
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Similar to Customer Decision Management - 5 Benefits
Customer Decision Management - 5 Benefits
- 1. 5 Benefits ofCustomer Decision Management James Taylor CEO, Decision Management Solutions
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- 4. James Taylor CEO ofDecision Management Solutions We work with clients to improve their business by applying analytic technology to automate and improve decisions … especially customer decisions © Decision Management Solutions, 2013 4
- 5. Agenda More Accurate More Real-time CustomerDecision Management More Agile More Consistent More Scalable © Decision Management Solutions, 2013 5
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- 7. From presenting data foranalysis …
- 8. … to making decisions withanalytics
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- 11. © Decision ManagementSolutions, 2013 11
- 12. © Decision ManagementSolutions, 2013 12
- 13. 3 stages tobetter operational decisions Decision Discovery Decision Services Decision Analysis
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- 15. 1:1 Marketing Next BestAction Cross-channel Marketing Markets of 1 Personalization © Decision Management Solutions, 2013 15
- 16. Micro Decisions Macro Impact ©Decision Management Solutions, 2013 16
- 17. Up The AnalyticsSpectrum Predictive Analytics Data Mining Business Intelligence X X X X X X X X X XX X X X X XX X XX X X X X X XX X X X X XX X X XXXXXX X X XX X XX X XX XX XX X XX XX X XX X XX X XX © Decision Management Solutions, 2013 17
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- 21. Faster decisions Event Decision latency Action Higher Value ©Decision Management Solutions, 2013 21
- 22. © Decision ManagementSolutions, 2013 22
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- 24. Business Rules Predictive Analytics External Data Big Data ©Decision Management Solutions, 2013 24
- 25. © Decision ManagementSolutions, 2013 25
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- 27. Decision © Decision ManagementSolutions, 2013 27
- 28. The Evolution OfA Retention Offer Automate Decision Policies, best practices ∫ Segment customers Predict value, opport unity Test, learn, op timize © Decision Management Solutions, 2013 28
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- 31. Decisions Are HighChange Components Keep making compliant decisions Track eligibility requirements Competitive discount Change risk assessment Keep the right deal terms © Decision Management Solutions, 2013 31
- 32. Conventional Approach Decision Management OtherSystems CRM System Frequent code changes Programmers CRM System Decision Service Other Systems Infrequent code changes Programmers Frequent policy changes Policy Changes Business users Business users Smart (Enough) Systems, Prentice Hall June 2007. Fig 2.11 © Decision Management Solutions, 2013 32
- 34. Agile, Industrial Analytics ©Decision Management Solutions, 2013 34
- 35. Drive Action withAnalytics Operational Systems Decision Analytic Systems © Decision Management Solutions, 2013 35
- 36. Keeping Costs DownWith Scalable Solutions
- 37. Decision Management SystemsScale Staffing ratios broken Manuals and reports replaced by recommendations and decisions Avoiding the “press 0” problem Always on, powerful self-service © Decision Management Solutions, 2013 37
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- 39. Customer Decision Management BetterResults • Existing customers are better value • Boost “share of wallet” More Loyal Customers • Customers treated like a number eventually defect • Interaction quality is as important as product quality Competitive Differentiation • Only you have your customers’ data • No-one can treat your customers the way you can © Decision Management Solutions, 2013 39
- 40. Begin with theDecision in Mind From Decision To Data… Data Analytic Insight Decision …not the other way around © Decision Management Solutions, 2013 40
- 41. Email: james@decisionmanagementsolutions.com Twitter: @jamet123 PARTNERS Mobile App InfoHub Kiosks teradata-partners.com
Editor's Notes
- #3 From the c-suite Big Data is the latest shiny object – everyone should have oneBut its also costly, or potentially costlyAnd perceived as a blue sky initiative – something for the (distant) future
- #4 What if you were able to use Big Data to drive Improved customer service and marketing in your call centerLower fraud across the boardBetter managed risk for your loan officers
- #6 I am going to introduce customer decision management and show how you can make more accurate, more real-time, more agile and consistent customer treatment decisions and do all this at scale
- #8 CDM is fundamentally about moving from presenting data for analysis
- #9 To making decisions with analytics
- #10 And not just any decisionsThink about the decisions your organization makes:Strategic DecisionsFew in number, large impactShould we acquire this company or exit this market?Tactical DecisionsManagement and control, moderate impactShould we re-organize, change our risk management approach?Operational DecisionsDay-to-day decisions that affect one transaction or customerNext Best offer? How risky is this loan? Is this claim fraudulent?It is operational decisions that are our focus
- #11 And they matter because these decisions are where, how, you focus on your customers
- #13 These little decisions are everywhereWhat offer should we make when this person uses the ATM?Is this credit card fraudulent?How should this loan office treat this applicant?What IVR menus should be played and how should this call be routedAnd on and on….These decisions matter
- #14 CDM uses a three step processDecision DiscoveryIdentify the decisions that are most important to your operational successDecision ServicesDesign and build decision management systems to automate these decisionsDecision AnalysisCreate a “closed loop” between operations and analytics to measure results and drive improvement
- #15 First how do we target our customers more accurately
- #16 All ways to say that we must make consistent, accurate, customer-centric micro decisions about what to do next
- #21 The right time is increasingly in real-time but people are NOT real time
- #23 We must shift from thinking about how to get people to make better decisionsTo how to get computers to make better decisions
- #25 These decision management systems support our existing platformsProviding decision making services to help these systems, and the users of these systems, make better decisionsUsing both explicit business rules and predictive analytics to make sure these decisions are accurate, compliant and analytically preciseAnd this is where the decision analysis piece comes in as we can collect all the operational data from those systems, reflecting how well our decision-making worked out for us, and feed it back into our big data infrastructureWhere, combined with new external big data sources, it drives improved rules and better predictive analytics, closing the loop for continuous improvement.
- #26 Telenor Pakistan story
- #29 It is often helpful to walk through one example here. Let’s take some interaction with a customer – say making a retention offer – and see how it might work.Initially we have different channels and our approach to retention is probably different in each. The first step, then, is to take control of the decision so we can make it consistently across channels. We should also use rules to describe it so that the decision can be automated correctly and managed by business staff, not IT. However not all customers are the same so we should analyze them and segment them so we can retain them differently depending on what is going to work. Segmenting based only on the data we have is interesting but it would be more useful if we could also use predictions as to their risk of leaving, lifetime value of them etc as part of our decision. Back to the data, then, to build predictive insights. Applying adaptive control to continually improve the outcomes and we end up with an optimized decision.As we work our way through the class we will revisit this and discuss.
- #32 Decisions are high change thoughRegulations change, so you have to change to stay compliantPolicies change, so eligibility has toCompetitors change so discounts have toMarkets and consumer behavior change, so risk assessment has toLoyalty shifts so deal terms have to
- #35 And analytics needs to be more agile tooEach model is hand-crafted - Expertise is applied in an automated contextScripts and programming are primary - Graphical analytic tools are primaryModels are one-time efforts - Models are continuously refreshed and updatedProjects are done when the model is done - Projects are done when the business is changed
- #36 In particular CDM makes sure that our analytics actually have an impact quickly, focusing on rapidly deploying analytics to drive operational change
- #41 If we start by understanding our decisions we can focus on the data that will improve those decisions and so avoid the “integrate everything” problem