The Top 10 Imperatives for Insurers and the role of Decision Management in addressing them
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James Taylor of Decision Management Solutions and Deb Smallwood of Strategy Meets Action present he Top 10 Imperatives for Insurers and the role of Decision Management in addressing them. Webinar recording available at http://decisionmanagement.omnovia.com/archives/64033
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The Top 10 Imperatives for Insurers and the role of Decision Management in addressing them
- 1. The top 10 imperatives for Insurers and the role of Decision Management in addressing them James Taylor, Decision Management Solutions Deb SmallwoodSMA Strategy Meets Action
- 2. ©2010 Decision Management Solutions 2 Your presenters James Taylor CEO, Decision Management Solutions Decision Management Solutions works with clients to improve their business by applying analytics and analytictechnology to automate and improve decisions James spent the last 8 years developing the concept of Decision Management 20 years experience in all aspects of software including time in FICO, PeopleSoft R&D, Ernst & Young Deb Smallwood Founder, Strategy Meets Action SMA is a strategic advisory firm offering a unique blend of advisory, research and consulting services to both insurance companies and solution providers. Deb is well known as a strategic influencer and advisor Leadership roles at TowerGroup, ICW, KPMG and Liberty Mutual Commercial Lines
- 3. The top 10 imperatives The role of analytics and a modern IT architecture Introducing Decision Management Addressing the 10 imperatives with Decision Management Next Steps for Insurers Q&A
- 4. SMA Top 10 Imperatives the “must haves” for charting your course imperative actions for linking strategy to capabilities to technology Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 5. SMA Top 10 Imperatives The list of the top 10 imperatives stems from SMA’s latest research including over 100 hours of interviews with leading executives across the entire insurance ecosystem. Consistently, executives cited these top 10 initiatives as they position for market recovery and prepare to handle the external forces changing insurance and a world in which technology is woven into the fabric of everyday life. Authors Deb Smallwood, Founder dsmallwood@strategymeetsaction.com Mark Breading, Partner mbreading@strategymeetsaction.com Karen Furtado, Partner kfurtado@strategymeetsaction.com Mary Ann Garwood, Partner mgarwood@strategymeetsaction.com www.strategymeetsaction.com/our-research Use of Our Reports The entire content of this Top 10 Imperatives research report is subject to copyright protection, with all rights reserved. Reproduction or distribution of the report, whole or in part, without permission is not allowed. The material and observations contained in this publication have been developed from sources believed to be reliable. SMA shall have no liability for omissions or errors and no obligation to revise or update any data or conclusions should new information become available or future events occur. The opinions expressed in this report are subject to change without notice. Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 6. Key Business Drivers Profitable Growth (sustainable) It would be nice if one could identify the one or two or even three simple things that are sure to drive success for insurers. Unfortunately, our world is complex with challenging economic conditions, unpredictable regulatory environments, and increasingly dynamic customer demands and interfaces. Insurers have more than a few things to consider in laying out their business and IT road maps. There are not just 3 key processes to address or 2 new technologies to install. There is no one-size-fits-all magic top priority. Instead, there are a series of imperatives that every insurer must be addressing right now if they want to stay competitive – actions for linking technology to the business capabilities that will be required for creating value in the coming years. Customer Service (agile) BUSINESS DRIVERS Business Optimization (scalable) Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 7. SMA Top 10 Imperatives for Insurers Make GOVERNANCE Work Chart a Course to PROFITABLE MARKETS Fast Path NEW PRODUCT DEVELOPMENT Benefit from BUSINESS OPTIMIZATION Put the DATA to Work Rethink LEGACY Drive Dynamic DISTRIBUTION Channels Capitalize on Intelligence to manage LOSSES Apply Smarts to UNDERWRITING Claims Analysis Risk Analysis Link CUSTOMER COMMUNICATION Holistically Profitability Analysis Make GOVERNANCE Work Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 8. SMA Top 10 Imperatives for Insurers CHART A COURSE TO PROFITABLE MARKETS… plot a position for growth with market intelligence PUT THE DATA TO WORK … make vision a reality with shared, common, quality data RETHINK LEGACY… use a modern application architecture – choose a best-of-breed, best-of-enterprise, or hybrid set of solutions FAST PATH NEW PRODUCT DEVELOPMENT … remove the technology obstacles DRIVE DYNAMIC DISTRIBUTION CHANNELS … navigate and manage expanding channels APPLY SMARTS TO UNDERWRITING… balance science and art CAPITALIZE ON INTELLIGENCE TO MANAGE LOSSES … sound the alarm early and give great customer service at the same time HOLISTICALLY LINK CUSTOMER COMMUNICATION... integrate voice, data, and paper interactions with channels and processes across the enterprise BENEFIT FROM BUSINESS OPTIMIZATION … stay ahead – improve speed-to-market, reduce costs, enhance service, and position for growth MAKE GOVERNANCE WORK … link business and IT to ensure the right investments – right projects, right time, right technology Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 15. Real-time quotation for all lines
- 16. Customized & personalized sales approach
- 17. Real time negotiation via agent portals
- 20. Severity and frequency management
- 21. Fraud detection, case mgmt
- 22. Personal service Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 23. PUT THE DATA TO WORK …make vision a reality with shared, common, quality data It is no secret that data makes the world go ‘round. It is viewed by some as an insurance company’s most valuable corporate asset. The key is to put the data to work for competitive advantage. First the data must be clean. Second it must be available. And third it must be usable and meaningful. This means that the data must be integrated and shared giving users the intelligence needed to take the right actions and make the right decisions – acumen applied anytime and anywhere. Data is the foundation for out-performing the competition, enhancing client satisfaction, and increasing value. Campaign Management Customer Retention Segmentation Management Customer Management Product Management Product Pricing & Underwriting Advanced BI and Analytic Tools Common Quality Data Risk Management Risk Analysis Profitability Analysis Claims Analysis Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 24. RETHINK LEGACY… use a modern application architecture – choose a best-of-breed, best-of-enterprise, or hybrid set of solutions In spite of years of replacement intentions and efforts, legacy systems live on! Now is the time to capitalize on advanced technologies and new solution offerings that make it easier to apply intelligence and smart data. A new breed of enterprise solution based on modern architecture and a data game plan is worth consideration as a total solution or a foundation for best-of-breed plug-and-play components or a hybrid approach. Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 25. FAST PATH NEW PRODUCT DEVELOPMENT … remove the technology obstacles Staying competitive means delivering insurance products that are designed to meet specific customer needs. The ability to rapidly develop and revise products and manage the product lifecycle is a distinct market advantage. For many insurers, achieving a faster path means that technology obstacles must be removed in a variety of areas including research, prototyping, and deployment. The fact is that all parts of the business need to support the product set using common data. Leverage comes from a central, shared repository of rates, rules, and forms to drive real agility and speed-to-market. Product Customer Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 26. DRIVE DYNAMIC DISTRIBUTION CHANNELS… navigate and manage expanding channels Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 27. APPLY SMARTS TO UNDERWRITING … balance science and art As precision insight becomes not only an advantage but also a weapon, the strategic application of technology becomes increasingly important. The fundamental is the integration of data, tools, and engines to give people and automated processes the business intelligence needed to take the right actions, at the right time, and make the right decisions - acumen applied anytime, anyplace, and anywhere. Underwriting/Enrollment/New Business Flow Quote, Proposal & Bind Risk/Loss Assessment Submission/ Order Entry Application Data, Tools, and Engines Data Validation Base Rating Pricing balancing Art Science Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved. 14
- 28. CAPITALIZE ON INTELLIGENCE TO MANAGE LOSSES … sound the alarm early and give great customer service at the same time Insurers, using knowledge as the foundation for appropriate action, are making giant strides in delivering top quality service while containing costs across all dimensions of the typically fragmented and siloed claims processing area. Integrating and managing the complete claims cycle reduces expenses. With personalized views, adjustable processes, and sharable services, new levels of customer satisfaction are realized. The use of external data, analytics and intelligence enables severity management, improved cycle time, and better claims recovery. Recovery Claims Management Processing 1 Investigate/Evaluate/ Case Work 2 Verification/ Assignment Notification 3 Customer Experience Sharable-Repeatable Services Adjustable-Automated Processes Data, Analytics, Intelligence 5 4 Negotiation/ Settlement Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 29. HOLISTICALLY LINK CUSTOMER COMMUNICATION … integrate voice, data, and paper interactions with channels and processes across the enterprise Customer Communications Management (CCM) plays a critical role in increasing sales and improving retention in the insurance industry. A comprehensive, holistic CCM vision is essential in today’s highly dynamic environment. Customers are making new demands, demographics are shifting, and the devices and channels used by policyholders, agents, and 3rd party partners are expanding. Information flows need to be seamless - capable of incorporating all forms of interaction, integrating both voice and data, and accommodating traditional and ever-changing new channels. Interaction occurs through a variety of Communication Options Interaction results in the creation of a variety of Information Types The blurring of channels, devices and information calls for a different approach to understanding customer communication management Communication and information flows through and enables a defined set of Insurance Processes Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 30. BENEFIT FROM BUSINESS OPTIMIZATION … stay ahead – improve speed-to-market, reduce costs, enhance service, and position for growth The mindset in the insurance industry has long been geared to sequential processes which are often driven by technology rather than a current business strategy. Shift to a business view. Rethink how capabilities align to expected outcomes. Drive operations from the viewpoint of the customer to create a more dynamic and responsive business model. Look at each individual activity to determine if it can be eliminated, automated, or delegated. Then apply the right level of technology to drive both top and bottom-line growth. The result – improved speed, reduced cost, and much better service. The Customer Vision Strategy, Goals & Outcomes Required Business Capabilities SMA’s Business Capability Model Underwriting/ New Business Policy Servicing Distribution Management/ Sales Billing and Collections Claims/ Payout Reinsurance Asset / Investment Management Enterprise Services Marketing and Product Development Market & Product Develop Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 31. MAKE GOVERNANCE WORK … link business and IT to ensure the right investments - right projects, right time, right technology Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 33. Decision Management An approach or business discipline for automating and improving decision-making It improves day to day business results by Supporting Automating and Improving operational decisions It builds on existing enterprise applications to put data to work manage uncertainty increase transparency give the business control
- 34. ©2010 Decision Management Solutions 21 What is a decision? Data is gathered, considered A choice or selection is made That results in a commitment to action
- 35. 22 ©2009 Decision Management Solutions “Most discussions of decision making assume that only senior executives make decisions or that only senior executives’ decisions matter. This is a dangerous mistake.” Peter Drucker
- 36. Different kinds of decisions matter Type Strategy Tactics Operations Economic impact Low High 23 ©2010 Decision Management Solutions
- 37. ©2009 Decision Management Solutions 24 Delivering Decision Management 3 stages to better operational decisions Create a “closed loop” between operations and analytics to measure results and drive improvement Design and build independent decision processes to replace decision points embedded in operational systems Identify the decisions (usually about customers) that are most important to your operational success
- 38. ©2009 Decision Management Solutions 25 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
- 39. ©2009 Decision Management Solutions 26 Business rules drive decisions Decision Policy Regulations History Experience Legacy Applications
- 40. ©2010 Decision Management Solutions 27 Different kinds of analytics X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X DataMining PredictiveAnalytics BusinessIntelligence Knowledge - Description Action - Prescription
- 41. The role of Decision Management in addressing the 10 imperatives 28 ©2009 Decision Management Solutions
- 42. The top 10 imperatives Chart a course to profitable markets Put the data to work Rethink legacy Fast path new product development Drive dynamic distribution channels Apply smarts to underwriting Capitalize on intelligence to manage losses Holistically link customer communication Benefit from business optimization Make governance work
- 43. ©2010 Decision Management Solutions 30 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 Fast path new product development Drive dynamic distribution channels Holistically link customer communication Benefit from business optimization Put data to work Capitalize on intelligence to manage losses Apply smarts to underwriting
- 44. ©2009 Decision Management Solutions 31 Avoid the insight-t0-action gap 2. Put the data to work
- 45. ©2009 Decision Management Solutions 32 Modernizing with decision services Database User Interface Browser Process Decision BPM Data 3. Rethink legacy
- 46. Multi-channel decision making ExternalData Business Analytics HistoricalData Ask a question about a customer Decision Service BusinessRules Give an answer about a customer 33 ©2010 Decision Management Solutions 5. Drive dynamic distribution channels 8. Holistically link customer communication
- 47. Decision management and underwriting 6. Apply smarts to underwriting
- 48. Decision Management and claims Claims Innovation 12,000-13,000 claims/month Recession – lower expenses, 25% fewer staff Claims adjudication with rules, analytics Results 1100% increase in fast track rate Loss adjustment expense from 14% to 11% 33% higher subrogation returns Subrogation recovery up by $10m/year 7. Capitalize on intelligence to manage losses
- 49. Operational decisions at the center 10. Make governance work
- 50. Next steps for Insurers ©2009 Decision Management Solutions 37
- 52. OPTIMIZATION
- 54. Execution
- 55. Investments
- 57. Optimization
- 60. Governance
- 61. Data Standards Source: 2010 SMA Research © 2010 Smallwood Maike & Associates, Inc. USA. May not be reproduced by any means without express permission. All rights reserved.
- 62. ©2009 Decision Management Solutions 39 Action Plan
- 63. 3/9/2010 ©2010 Decision Management Solutions 40 Don’t start by focusing on the data Better decision Analytic insight Derived information Available data
- 64. 3/9/2010 ©2010 Decision Management Solutions 41 Start by focusing on the value Better decision Analytic insight Analytic insight Derived information Derived information Available data Available data
- 65. Questions?
- 66. We can help Decision Management Solutions can help you Focus on the right decisions Implement a technology blueprint Build decisioning systems james@decisionmanagementsolutios.com SMA Strategy Meets Action can help you ©2009 Decision Management Solutions 43
Editor's Notes
- As Insurers position for market recovery and deal with the forces reshaping the insurance business, SMA’s industry research has identified 10 critical imperatives that will deliver sustainable profitable growth, agile customer service and scalable business optimization. At the core of these initiatives is putting your data to work, and putting it to work across channels in day-to-day, front-line operations. This webinar will:Introduce the top 10 imperativesShow how analytics and a roadmap to a modern IT architecture are essentialIntroduce decision management as a framework for applying analytics in operational systemsIdentify next steps for insurers
- The day to day decisions that drive operational behavior, customer interactions, transactional systems are more important than the big, strategic decisions beloved of management consultants. Each one seems unimportant but they happen so often that their total value swamps anything else you do. If you get these decisions wrong it won’t matter what you get right.
- 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.
- As we are talking about decisions it is worth remembering that all decisions matter, as Peter Drucker noted. Not just the big, strategic decisions of your executives but the day to day decisions that drive your business.After all, people react to your organization’s decisions, especially decisions made by front-line systems and staff, as though they are both personal and deliberateYou should make sure they are
- 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
- Before we talk about decision services, let’s take a step backIn the “old” days applications were monolithicOver time we have recognized the value of decomposing applications and storing the components in a more declarative, reusable form.
- 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
- Here’s another example, this time of an insurance company with about 750,000 policies that implemented a risk-based underwriting decision service for use across its systems. In the first year an eight-point reduction in combined ratio – a big deal for an insurance companyThey got this improvement from all the areas I see when clients apply decision managementThey reduced costs by eliminating many manual reviews and by putting underwriters and actuaries in charge of the rules behind the decision – they eliminated or reduced many of their IT costs.They boosted revenue, the second major area, by improving risk management (far more tiers and more fine grained decisioning) and by focusing their staff on the book of business and helping agents improve it rather than on transactional approvalsThe third area does not show up in the specifics but when I talked to them it was clearly the most powerful aspect of the whole thing. They gained true strategic control over their underwriting decisions.
- Infinity Insurance is a $1Bn writer of insurance for classic cars, commercial auto and personal auto. The claims department at Infinity signed up with predictive analytics software from SPSS Inc. in 2007 to target process change in a couple of areas – fraud and subrogation. The Fraud Investigation Unit had an old process for flagging potentially fraudulent claims, involving adjustors manually applying some simple rules. This needed to be replaced with a more transparent system to identify risky claims. In Subrogation, the process of finding other companies who might be liable for some of a claim, Infinity had spent millions of dollars for outside consultants to come in and check for subrogation opportunities. This had yielded $12M – $16M in actual recoveries so it was clear that a better process was possible.Subrogation turned out to be the quickest payoff, with analytically-derived rules being deployed in about 9 months. The new subrogation decision had 33% higher returns – it found subrogation opportunities in many more claims than before - and paid off the analytic software investment in just 3 months. Previously Infinity had about 15% of its claims come in to the subrogation department for review and now over 22% come in. As a result recovery from has gone from $1.2m/mo to $2m/mo!While Infinity was adopting analytic decision making the industry entered a deep recession. Without the analytically enhanced decision-making they were adopting this would have had far more effect on their business than it did. They had to layoff 25% (some 300 staff) and trim expenses. With 12,000-13,000 new claims a month they had to get cases out to field staff quicker, improve customer service and reduce people all at once. The automated identification of fast track claims helped them decouple the number of adjustors from the amount of business being written.To achieve this they started “Right tracking” claims using Risk Control Builder to assign claims to fast track adjustors. This was a new approach, created to take advantage of the new analytic decision making using a combination of business rules, predictive models, and information gathered from customer interactions. These fast track adjustors were people in the business units who went from simply reporting losses to handling some claims. This created a group who could process the claims “once and done” – no hand off to field adjustors. This allows them to open, appraise and pay some claims within 10 days or so. The analytically enhanced decision increased the old fast track rate of 2% to 22% in just a year of operation. The 100 fast track adjustors now handle more than 2,500 claims a month without referral to a field adjustor. This represents a huge cost saving for the field, helps decouple business growth from the number of field adjustors and has reduced their loss adjustment expenses from 14% to around 11%. Infinity uses PASW Modeler data mining workbench to create predictive models and Risk Control Builder to deploy them. Starting originally with external consultants, Infinity has been transitioning to having more of its own staff use the tools. The resulting decisions are a mix of rules specification and analytics work and Infinity has been identifying people who have real claims experience and getting them involved in managing the rules themselves as analysts. This enables new rules, new models to be deployed without going through IT and this is important as IT has been a challenge.Initially IT was skeptical about the approach and was not all that supportive – the business had to get past a “this sounds like star wars” mindset. The business needed their support but IT was getting cut back and so appropriate teams were not always available. Over time the business has reduced its demands on IT as claims personnel have become able to add rules. With weekly changes to the rules and models this ability to make their own changes has been critical to delivering the agility and responsiveness they needed.The different decisions are each handled in slightly different ways. In the Fraud Investigation Unit the analytic models and rules are used to create a credit-score like ranking. The decision is to determine the fraud risk score for a particular claim. This score is then used by the team to rank order claims so that those with the highest risk of fraud are investigated first. The decision as to whether or not a claim is suitable for fast tracking is similar, with the score being used to send the most appropriate claims to fast track. The subrogation decision is a little different with the rules and analytics being used to identify those claims where no subrogation has been identified but where it is considered likely. Infinity is building a new claims system with some self-service options and an ability to support mobile devices and automated claims payment. This new system is being developed with hooks to the analytic decision making process to allow for no-handle claims.Infinity found that board members can be hard to convince when it comes to claims as numbers for things like fraud are often imprecise. Subrogation was easier to “sell” in part because the numbers are easy to see – claims handed off to others to pay are very concrete. Successful adoption requires finding the pain points of executives and showing how the technology, the approach, can address those pains.
- Because operational decisions are high volume, transactional decisions IT is involved (systems)Business people are involved in decision makingAnd we want to bring analytics to bearThree groups not always that good at working togetherBusiness does not understand code nor does it understand the mathAnalytics people are not familiar with IT nor do all analytics folks think about IT when they are building modelsIT people think of data as something to be stored and reported on, not something to be usedThe business – and what they know and don’t know – represents a whole other class of problemBusiness people understand their business and they know what results they want, want will count as a successDo they understand the math in your models? NoDo they understand the statistics in adaptive control and model performance? NoDo they understand programming code that represents the actions they need taken? NoTo succeed long term you must engage the business in the comparison of ideas, of different approaches, in the results of analysis and in the actions being taken. This means providing them with an environment that lets them collaborate with you without having to become LIKE you.In retention terms this means showing them the effect of different retention strategies on customer segments named the way they name them and in terms they understand – not statistical measures but business measures, the KPIs they use every day. It means letting them specify the retention offers in a simple, declarative format they understand (rules, say).Another challenge is the lack of awareness of analytics and data mining, their power and how to apply them among IT professionals.For instance imagine a conversation:A business user realizes it would make it much easier for our call center to handle customers if we knew this about them. If they ask IT they will prompt an IT-centric response – who knows it and could enter it? Which application(s) do they use? What table structure can we use to store it? How about backup, security, recovery…… If they ask someone with an analytics background they will get a different one – I wonder how we could derive that from what we know about our customers….When systems are developed or modified, a need for attributes, about a customer say, results in a data design along with an application to capture the data and, in the end, a database containing the information. It’s a one way street – from need to data in a database.Analytics can close that loop – taking the historical data being created and deriving new, useful attributes from it.Of course this only works if the IT people know to ask and it’s a lot simpler if IT is cleaning, storing and making available the data that analysts will actually need (not some aggregation of it suitable only for reporting).In our example if the business users tell their IT folks that they need to include the retention risk and long term profit potential of a customer in the retention offer logic the result may be a project to capture this information and store it in the database. It is unlikely to result in an analytic project to derive it.When IT does impact analysis they don’t consider modelsWhen the business does impact analysis they don’t eitherModels are part of a complex ecosystem so impact analysis is a problemIf I change the KPIs for the customer managers that changes their definition of good results and thus of a good model. Would such a change ripple through to the analytics team? If the IT team implements a change to the customer database design that will change the historical data available from that point on – will that ripple through?
- Begin!Identify your decisionsHidden decisions, transactional decisions, customer decisionsDecisions buried in complex processesDecisions that are the difference between two processesConsiderWho takes them nowWhat drives changes in themAssess Change ReadinessConsider Organizational changeAdopt decisioning technologyAdopt business rules approach and technologyInvestigate data mining and predictive analyticsThink about adaptive control
- 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.