Delivering customer centricity with decision management
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To deliver customer-centricity, companies must manage customer interaction decisions across channels, platforms and lines of business. Webinar recording is available here: http://decisionmanagement.omnovia.com/archives/60402
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Delivering customer centricity with decision management
- 1. Delivering customer centricity across multiple channels, James Taylor, multiple platforms CEO
- 2. AGENDA 1 2 The challenge of customer centricity Decisions at the center of customer 3 Decision Management centricity 4 5 6 Using Decision Decisions put Wrap and next Management to data to work steps deliver customer centricity
- 3. The one slide you need Customer centricity relies on decision making Particularly on operational “micro” decisions about a single customer Your systems need to take most of these customer- centric decisions Decision Management delivers these decisions to your frontline systems and processes Decision Management can increase loyalty and revenue, improve customer service and agility, and improve time-to-market ©2010-2011 Decision Management Solutions 3
- 5. Customer-centricity Customer centricity refers to the orientation of a company to the changing needs and behaviors of its customers, rather than internal drivers, for mutual profit. It does not mean Always doing exactly what a customer wants Sacrificing profit for customer service Selling or marketing less Only dealing with customer service ©2010-2011 Decision Management Solutions 5
- 6. Why be customer-centric Better results Existing customers are better value Customer-centricity boosts “share of wallet” More loyal Customers treated like a number customers eventually defect Interaction quality is as important as product quality Competitive Only you have your customers’ data differentiation No-one can treat your customers the way you can ©2010-2011 Decision Management Solutions 6
- 7. Challenges include Multiple channels Consistent quality of interactions Learning from all channels Many Products What do customers want, need What will maximize the relationship Change Coping with turnover, Customer needs evolve People Empowering them to act Ensuring best practices Processes Customer-first processes ©2010-2011 Decision Management Solutions 7
- 8. Decisions at the center of customer- centricity
- 9. Questions for customer-centricity What’s the next best action for this customer? What channel should I use to contact them? How do I retain this customer? Can I approve this customer’s request? Is this customer loyal? How valuable is this customer? What’s the best way to handle this problem? How do I tell its time to change my approach? ©2010-2011 Decision Management Solutions 9
- 10. These are all decisions Data is gathered, considered A choice or selection is made That results in a commitment to action ©2010-2011 Decision Management Solutions 10
- 11. Reality check People don’t make Systems do many of the decisions that affect your customers Customer opportunity But operationally, does not come in one transaction, or strategic lumps one customer at a time ©2010-2011 Decision Management Solutions 11
- 12. Operational decisions about customers ©2010-2011 Decision Management Solutions 12
- 13. Micro decisions for customer-centricity Make each decision for each customer Don’t treat everyone the same, treat them uniquely How many decisions are involved in sending a letter to 10,000 customers? Just a few design decisions Or 10,000 micro decisions - one per customer ©2010-2011 Decision Management Solutions 13
- 14. Case study: Telco Example: Analytics enabling an individualized decision about the best plan/upgrade offer to make to each customer ©2010-2011 Decision Management Solutions 14
- 16. Decision Management Improving day to day business results by Supporting Automating and Improving operational decisions A business discipline that builds on existing enterprise applications to put data to work manage uncertainty increase transparency give the business control ©2010-2011 Decision Management Solutions 16
- 17. 5 core principles of decisioning Identify, separate and manage decisions Use business rules to define decisions Analytics to make decisions smarter No answer is static Decision-making is a process ©2010-2011 Decision Management Solutions 17
- 18. Delivering Decision Management 3 stages to better operational decisions Create a “closed loop” between operations and Design and build analytics to independent measure results decision processes and drive to replace decision improvement Identify the points embedded in decisions (usually operational systems about customers) that are most important to your operational success ©2010-2011 Decision Management Solutions 18
- 19. Why manage decisions independently? Faster, easier, independent changes Coordination of decisions across channels Simpler more customer-centric processes Higher employee productivity Apply analytic insights everywhere Continuous improvement Create systems that handle uncertainty ©2010-2011 Decision Management Solutions 19
- 20. Customer decision services ©2010-2011 Decision Management Solutions 20
- 21. Business rules Business rules are, literally, the rules by which you do business Business rules handle Policy Regulations Best practices Internal expertise Customer preferences Business rules increase agility and alignment ©2010-2011 Decision Management Solutions 21
- 22. Manageable business rules If customer is GoldCustomer and Home_Equity_Loan_Value is more than $100,000 then college_loan_discount = 0.5% If member has greater than 3 prescriptions and prescription’s renewal_date is less than 30 days in the future then set reminder=“email” If patient’s age is less than 18 and member’s coverage is “standard” and member’s number_of_claims does not exceed 4 then set patient’s coverage to “standard” Smart (Enough) Systems, Prentice Hall June 2007. Fig 4.3 ©2010-2011 Decision Management Solutions 22
- 23. Case Study: International retailer Cross-channel coordination ensures that all relevant offers, including loyalty programs, are combined at the point of sale, with consistent pricing rules applied. ©2010-2011 Decision Management Solutions 23
- 24. Analytics Analytics simplify data to amplify its meaning. Predictive analytics turn uncertainty into usable probability. ©2010-2011 Decision Management Solutions 24
- 25. Different kinds of analytics Business Intelligence Data Mining Predictive Analytics X X X X X X X X X X X X X X X X X X X X X XX X X X X XX X X X X X X XX X X X X X X X XX XX X X X X X X X X X X X XX X X X X X XX X How do I use data to Who are my How are those learn about my best/worst customers likely to customers? What customers? How do behave in the has been happening I turn my data into future? How do they in my business? rules for better react to the myriad decisions? ways I can “touch” them? Knowledge - Description Action - Prescription ©2010-2011 Decision Management Solutions 25
- 26. Insights must drive action * * ** * ** * * * * Predictive models * * * * **** * * * * * ** * don’t DO anything, * * * * ** * * * * * * * * * * ** * they just make * * * ** * * * predictions. ©2010-2011 Decision Management Solutions 26
- 27. Insights must drive action Business Rules make analytics actionable * ** * ** * * * * * * * * * ** * * ** * * * ** * * * * * * * * ** * * * * * * ** * * * * * ** * * * Analytic insights are deployed via a BRMS built in a Decision Service, making them actionable. ©2010-2011 Decision Management Solutions 27
- 28. Case study: Retailer Tailored promotions integrated with loyalty program for consistently compelling offers across channels. Driven by analytic insights from cross- channel data ©2010-2011 Decision Management Solutions 28
- 29. Decision analysis ©2010-2011 Decision Management Solutions 29
- 30. Closed-loop decisioning ©2010-2011 Decision Management Solutions 30
- 31. The evolution of a retention offer Automate Decision Apply rules http://www.f Web Close the Loop Call Center Segment customers Email Adaptive Control Mobile Predict risk, value Optimize decision ©2010-2011 Decision Management Solutions 31
- 32. Using Decision Management to deliver customer-centricity
- 33. Benefits More targeted offers that focus on smaller, tighter segments of your customer base Improved consistency across channels, across representatives and over time Improved agility with externalized decisions that change independent of systems or processes Rapid decision-making enabled by automation reduces call length and wait times Less training, fewer representatives, less time on hold mean lower costs ©2010-2011 Decision Management Solutions 33
- 34. Case Study: European mobile Telco Enabling business experts to manage promotional rules increased flexibility and shortened time-to-market for customer retention programs. ©2010-2011 Decision Management Solutions 34
- 35. Personalization and targeting More than just scripting responses The best response changes in each situation Providing personalization and targeting requires: Analytically derived segments for targeting Rules to implement policies, regulations Customer’s own rules about preferences Predictions of responses Rapid response Continuous evolution ©2010-2011 Decision Management Solutions 35
- 36. Consistency Across Channels Stronger company-level customer relationships More effective use of multiple channels Interaction context intelligently incorporated Customers choose preferred channels Customer value, not channel, drives interaction ©2010-2011 Decision Management Solutions 36
- 37. Empowerment Call Center staff can handle customers better Fewer approvals needed Risk and opportunity integrated into conversation Faster decisions, while the customer waits More response-oriented, less batch-oriented Call Center focus on the interaction, not the decision Complex dialogs handled effectively Next best action not just offers Third parties can act like you not just for you Customers can self-serve more effectively ©2010-2011 Decision Management Solutions 37
- 38. Case Study: Fortune 20 Call Center Making the right decision at the start of the call turns long, costly processes into straightforward, customer-pleasing interactions. ©2010-2011 Decision Management Solutions 38
- 39. Rewarding loyalty Align treatments with behavior Treat consistently with needs Self-service or faster service for a specific customer’s common activities Consistent treatment across channels Better targeting of loyalty offers Show customers that sharing information is valuable ©2010-2011 Decision Management Solutions 39
- 40. And keeping it where you want it The “Mom and Pop” store problem Make staff more visible, personable But who is the customer loyal too? And how does this loyalty persist when staff turnover? Make the systems do the work Remember the customer Recommend the best action Support immediate action without referral Embed best practices ©2010-2011 Decision Management Solutions 40
- 41. Decisions put data to work
- 42. Don’t start by focusing on the data Better Analytic decision insight Derived information Available data ©2010-2011 Decision Management Solutions 42
- 43. Start by focusing on the value Better decision Analytic insight Derived information Available data ©2010-2011 Decision Management Solutions 43
- 44. Use data to improve decisions Classify “good” customers Spot likely churners Identify revenue opportunities Find fraud and abuse Focus acquisition on likely customers Match price and risk ©2010-2011 Decision Management Solutions 44
- 45. Wrap up and next steps
- 46. The one slide you need Customer centricity relies on decision making Particularly on operational “micro” decisions about a single customer Your systems need to take most of these customer- centric decisions Decision Management delivers these decisions to your frontline systems and processes Decision Management can increase loyalty and revenue, improve customer service and agility, and improve time-to-market ©2010-2011 Decision Management Solutions 46
- 47. Critical Success Factors Challenges Critical Success Factors Were the right decisions made for Develop & maintain deep customer the customer and the company? insight Measure customer lifetime value impact Did they enhance the customer’s Target customer experiences experience? Measure treatment effectiveness Were those decisions consistent Integrate across functional Silos across channels and customer segments? Operationalize decisions Reduce time-to-market cycle times Are they keeping up with changing circumstances? Test and learn ©2010-2011 Decision Management Solutions 47
- 48. Action Plan Identify customer treatment decisions Adopt decisioning technology Analyze data decision first ©2010-2011 Decision Management Solutions 48
- 49. Decision Management Solutions Decision Management Solutions can help you Focus on the right decisions Implement a blueprint Define a strategy For assistance, to find out more or if you have questions decisionmanagementsolutions.com ©2010-2011 Decision Management Solutions 49
- 50. Thank you! James Taylor, CEO james@decisionmanagementsolutions.com www.decisionmangementsolutions.com
Editor's Notes
- Organizations have multiple channels for interacting with their customers. Each channel has its own platform for valid technical reasons. And each line of business has its own systems while customer data is spread across multiple databases. To deliver customer centricity, organizations need to connect these elements effectively. At the heart of effective customer interactions are decisions – decisions about offers, about eligibility, about treatments about the actions to take to serve a customer. A focus on these decisions, and on making these decisions customer-centric, is essential if every platform, every line of business, every channel is to be put to work effectively.This webinar will show how decisions are at the heart of customer centricity, how those decisions can be managed independently of the disparate elements of an enterprise architecture and how Decision Management ensures you put a customer-centric strategy to work.
- Organizations have multiple channels for interacting with their customers. Each channel has its own platform for valid technical reasons. And each line of business has its own systems while customer data is spread across multiple databases. To deliver customer centricity, organizations need to connect these elements effectively. At the heart of effective customer interactions are decisions – decisions about offers, about eligibility, about treatments about the actions to take to serve a customer. A focus on these decisions, and on making these decisions customer-centric, is essential if every platform, every line of business, every channel is to be put to work effectively.This webinar will show how decisions are at the heart of customer centricity, how those decisions can be managed independently of the disparate elements of an enterprise architecture and how Decision Management ensures you put a customer-centric strategy to work.
- Multiple ChannelsConsistency, quality of interaction across channelsLearning about customers across all channelsManyProductsUnderstanding what they might want, might needWhat will maximize a customer relationshipChangeApplying changing best practices, policies, regulationsCoping as staff turnover, markets & customers evolvePeopleEmpowering staff to be customer-centricProcessesNeed to be customer centric
- At its heart a decision is a choice, a selection of a course of action. A decision is arrived at after consideration and it ends uncertainty or dispute about something.Decisions are made only after considering various facts or pieces of information about the situation and participants.Decisions select from alternatives, typically to find the one most profitable or appropriate for an organization.Decisions result in an action being taken, not just knowledge being added to what’s knownThe basic decision making process is simple. Data is gathered on which to base the decision. Some analysis of this data is performed and rules derived from company policy, regulations, best practices and experience is applied. A course of action, a selection from the possible options, is then made so that it can be acted on. When considering decisions in operational business processes, the way the decision is made is often constrained such that it can be described and automated effectively in many, even most, cases.
- First, decisions. When we wrote the book this was an area where we wrote a lot more than we had expected – when you think about decisions all the time you get used to identifying them and focusing on them but it is challenging initially.We are not talking about strategic decisions here – should we do business in Alaska, say – but on the decisions that relate to specific individuals, customers, members. These customer treatment decisions can and should be identified, externalized and managed.There are a number of different ways to find these decisions and the four most common are:Micro decisionsOrganizations do not realize how many they makeEvery strategic decision has many operational consequencesEach customer interaction can be many decisionsManual decisionsHidden under manual processesDecisions that are being taken every day by front-line staffConflicting decisionsDifferent parts of your organization treat customers differentlyA longer time horizon might drive a different decisionDecisions are made inconsistentlyMissing or default decisionsDecisions that you do not think you can take and so you do the same thing every timeThe policy was set a long time ago and was never updatedFred has a great example of this with the AmEx website which you will see later
- How many decisions are involved in sending a letter to a some customers?One view says a couple of decisionsWhat to put in the letter and who receives itA more complete view says that you have also made a decision for each customer to receive or not receive the letter. If you sent a letter to 10,000 customers, you just made 10,000 micro decisionsAdding a new option to your IVR system means deciding that everyone who calls will hear the option. changing your website means deciding that every visitor will see something new…Many strategic decisions can only be implemented if many supporting micro decisions are also made.
- Applying analytics to acquire, retain and grow 100M customersBusiness challenge:100M customers and 3Bn calls / day200TB of customer information1.3M Retail partnersRural and urban consumers, large and small companiesSolution:Integrated data warehouse across all channels, all productsReal-time analytics for micro-segmentation, offer targetingWeb, retail, call-center and mobile channelsBenefits:Rapid growth with 2-3M new customers/monthGrowing and accelerating Revenue Market Share
- Little decisions add up so focus on operational or front-line decision makingThe purpose of information is to decide so put your data and analytics to workYou cannot afford to lock up your logic so externalize it as business rulesNo answer, no matter how good, is static so experiment, challenge, simulate, learnDecision Making is a process to be managed
- Why manage decisions independently of process? What’s the advantage? There are several…Faster, easier, independent changes to decision logicCoordination of decisions across channels and productsSimpler processes that are much easier to manage Higher employee productivity and resource utilization Analytic insights for making better decisionsContinuous improvement of decisions and results
- All these pieces contribute to ever-more sophisticated decision services that support your business processes.Decision Services externalize and manage the decisions production processes and systems needBusiness rules allow business users to collaborate in the declarative definition of decisionsAnalytics can create better more data-driven business rulesAnd ultimately additional predictive analyticsAdaptive control allows test and learn to become part of a continuous improvement loop
- Faster, easier, independent changes to decision logic Coordination of decisions across channels and products Higher employee productivity and resource utilization a leading French retailer of cosmetics, faced the challenge of multiple channels and overlapping marketing and loyalty offers. A customer might be eligible for a loyalty offer, have downloaded a web coupon and heard a “discount word” on the radio. This made it hard for retail staff to ensure the price was handled correctly at the point of sale. In addition, they needed a better way to get loyalty offers to the customer. Yves Rocher replaced their POS devices with Linux-based terminals and developed a rules-based system that allowed all the pricing rules to be defined by the marketing department and then downloaded into the terminals. All relevant offers are correctly combined at the point of sale. This system also takes the customer’s loyalty card and applies loyalty offers. Using purchases and loyalty history, it prints an incentive offer designed to bring the customer back to the store on the card itself—the cards are re-printable so the customer sees the offer that will be made when they return.
- Faster, easier, independent changes to decision logic Coordination of decisions across channels and products Harness the power of analytics to make better decisionsAllow continuous improvement of decisions and results Churn minimzedBrand loyalty growsRepeat customA leading European retailer had a vision of delivering compelling promotional offers based on each consumer’s unique profile that was integrated with existing loyalty programs. As a first step, they brought all data together across retail formats and across channels to reveal customer purchasing patterns. By tracking transaction history, the company can obtain analytic insights on not only which products customers buy, but which promotions they are most likely to respond to, who its most profitable customers are, what products they buy now, and what products they would be willing to buy if the incentive was right
- 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.
- Faster, easier, independent changes to decision logic Coordination of decisions across channels and products Vodafone Spain relies heavily on promotions to drive growth and loyalty management programs to reduce churn. With promotions hard-coded into multiple systems, it was hard and expensive to keep promotions consistent and up to date. Vodafone Spain extracted critical promotion decisions and implemented a business rules management system so that marketing, who understood the segmentation, could manage the promotion rules themselves. With real-time monitoring of promotion performance, these same teams can make immediate adjustments to ensure continuous differentiation.
- Simpler processes that are much easier to manage Higher employee productivity and resource utilization International travel wizardBillingTech support and troubleshooting
- There are many views of loyalty but one of the most prevalent and compelling is the idea that large, multi-national, multi-channel organizations must generate the same feelings as local stores, local branches do. The sense that the people with whom you deal know you, value your business, tailor their response to you. Jim Berkowitz in Customer Loyalty and Profitability said “To grow truly loyal customers … what’s needed is the ‘Mom & Pop Store’ factor”. Richard Hackathorn wrote a great article on the same topic called Forward to the Past in which he said “As we fast forward into our global economy, realize that we often direct our technology to achieve the common things of the past”. One way to do this is to try and give your customers personal contacts, named staff, who become familiar faces and voices and, by virtue of dealing with the same customers over and over again, knowledgeable about their needs. This might work, and EDM can certainly help you with it, but what happens if that employee leaves? Especially if that employee leaves and joins a competitor? Will you find that your customer is loyal not to your brand or your products but to your employee? Instead of trying to build loyalty to individuals you need to create loyalty to the store or bank or brand. To do this, to have an ongoing process of building and sustaining loyalty without transferring it to a specific employee, requires EDM without a shadow of a doubt. Think about what makes someone loyal to a small store or branch, or to a specific employee. Perhaps that person got something done for them or perhaps the local store made them a really compelling offer based on what they have bought in the past. Perhaps that person knew the customer well and so dealt with them appropriately. Maybe the rewards being offered were just what the customer valued. Certainly there was not a lot of referring to management or generic scripting of responses going on. What these situations have in common is a focus on the decisions that customers want made (pricing, refunds, shipping prices and times, offers, loyalty rewards) as well as those you want to make about them (cross-sell, up-sell, retention). Because EDM focuses on and automates and improves these decisions, EDM can deliver on organizational loyalty. Think about it: By automating decisions you can ensure that customers are not referred around the organization unnecessarily. The first person they speak to can act immediately because the system can deliver the answer without having to get a supervisor on the line. They won’t become loyal to the individual who can “work the system” if the system empowers everyone.By embedding best practices rules in a decision, every call center representative can respond like the most successful. The difference between the best and the worst customer service representative will be smaller making it less likely that one particular representative will become a customer’s favorite.Using predictive analytics and statistically significant segmentation rules, customers can be treated more appropriately and in a more targeted fashion – you can align your treatment with their behavior. Their wants and likes can be more accurately included in decisions made about how to treat them. Automation of this means that everyone can see the trends in the behavior and value of a customer and know what action to take. Trying to use dashboards and reports means that only the most analytically sophisticated representatives can do this, risking the transference of loyalty to them not the company.Automation means that the same decision can be delivered through any channel – at the store, on the web, in the call center. Consistency of treatment builds loyalty (assuming the treatment is not obnoxious) and knowing that you can get the same treatment from anyone keeps that loyalty linked to the company not to an individual. Instead of always coming to the branch to see a particular person they will know that they can use any channel and still get great service.By targeting loyalty program offers you can use those loyalty program dollars more effectively – not just to reward but also to change behavior. Making a proactive offer to those who are on the cusp of becoming loyal customers, for instance, might be more effective than rewarding those who become loyal. An EDM approach is not going to help with friendliness or surprising customers from time to time but I do believe that higher volume, more self-serve oriented businesses must adopt this approach to really deliver customer loyalty. Using business rules management systems to implement a decisioning backbone for consistency while retaining the agility to respond to changes and injecting insight using predictive analytics let’s you recreate the corner store feel and benefits while still delivering the transaction throughput and response times a modern business often needs.
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- Decision Management Solutions can help youFind the right decisions to apply business rules, analyticsImplement a decision management blueprintDefine a strategy for business rule or analytic adoptionYou are welcome to email me directly, james at decision management solutions.com or you can go to decision management solutions.com / learn more. There you’ll find links to contact me, check out the blog and find more resources for learning about Decision Management.