Deploying Analytics with a Rules-Based Infrastructure. James Taylor, CEO

Transcription

1 Deploying Analytics with a Rules-Based Infrastructure James Taylor, CEO

2 2011 Decision Management Solutions 2 Your presenter CEO of Decision Management Solutions Decision Management Solutions works with clients to improve their business by applying analytics and analytic technology to automate and improve decisions 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

3 AGENDA Zero value analytics are easy Operational analytics are hard(er) Introducing business rules Deploying analytics with business rules Decision Management Wrap Up

4 2011 Decision Management Solutions 4 The one slide you need It is easy to have analytic success without creating business value It is especially easy to fail to deliver business value when focused on operational analytics Business rules and a business rules management system provide an ideal platform for analytics Decision Management ties analytics and business rules together in an effective framework

5 Zero value analytics are easy 2011 Decision Management Solutions 5

6 2011 Decision Management Solutions 6 The operation was a success But the patient died

7 2011 Decision Management Solutions 7 Making information more readily available is important, but making better decisions based on information is what pays the bills.

8 2011 Decision Management Solutions 8 What is a decision? Data is gathered, considered, analyzed A choice or selection is made That results in a commitment to action

9 Operational analytics are hard(er)

10 2011 Decision Management Solutions 10 Different kinds of decisions Type Strategy Tactics Operations Low Economic impact High

11 2011 Decision Management Solutions 11 Analytic power in operational decisions How do I prevent this customer from churning? convert this visitor? acquire this prospect? make this offer compelling to this person? identify this claim as fraudulent? correctly estimate the risk of this loan? It s not about aha moments It s about making better operational decisions

12 After Smart (Enough) Systems, Prentice Hall Decision Management Solutions 12 Operational decisions are different High Volume Low Latency High Variability Ensure Compliance Personalize Manage Risk Unattended Operation Self-Service Straight Through Processing

13 2011 Decision Management Solutions 13 Insights must drive action * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *?

14 Time to deploy models matters 2011 Decision Management Solutions 14

15 2011 Decision Management Solutions 15 The three legged stool Business

16 2011 Decision Management Solutions 16 Case: Varolii Personalized, automated consumer communication SaaS Challenge: apply advanced analytics Analyze past behavior of consumers Drive recommendations to their clients Actionable and automatic Solution Identify key decisions Analytically derive new rules based on past success Integrate client rules with analytic rules

17 Introducing business rules

18 2011 Decision Management Solutions 18 What are business rules? statements of the actions you should take when certain business conditions are true.

19 Business rules drive decisions Policy Decision Regulations History Legacy Applications Experience 2011 Decision Management Solutions 19

20 2011 Decision Management Solutions 20 Unmanageable business rules public class Application { private Customer customers[]; private Customer goldcustomers[];... public void checkorder() { for (int i = 0; i < numcustomers; i++) { Customer acustomer = customers[i]; if (acustomer.checkifgold()) { numgoldcustomers++; goldcustomers[numgoldcustomers] = acustomer; if (acustomer.getcurrentorder().getamount() > ) acustomer.setspecialdiscount (0.05); } } }

21 2011 Decision Management Solutions 21 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= 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 Fig 4.3

22 2011 Decision Management Solutions 22 A Business Rules Management System Validation and Verification Testing Rule Repository Deployment Decision Service Rule Engine Production Application Design Tools Rule Management Applications Operational Database After Smart (Enough) Systems, Prentice Hall June Fig 6.6

23 2011 Decision Management Solutions 23 Case: Health Management Personalized health recommendations Challenge: multiple sources of tailoring Medical research Data mining of participant and outcome information Best practices in personal health Solution Replace Java code with JBoss Drools Implement best practices as decision tables Decision trees from analytic results, medical research Implement as additional decision tables

24 Deploying analytics with business rules

25 2011 Decision Management Solutions 25 Business rules and analytics Broader set of data for business rules to act on Association rules as business rules Decision trees as business rules Predictive (risk) scorecards as business rules

26 2011 Decision Management Solutions 26 Integrate operational and analytic Operational Systems Business Rules Analytic Systems Predictive Analytics

27 Association rules speak for themselves If basket contains Hats AND basket contains Socks THEN offer category is Active Accessories Screenshots courtesy of KXEN 2011 Decision Management Solutions 27

28 Deploying a decision tree Screenshots courtesy of IBM 2011 Decision Management Solutions 28

29 Scorecards are a powerful tool Years Under Contract More than 2 10 Number of Contract Changes More than 1 10 Value Rating of Current Plan Poor 0 Good 10 Excellent 20 Score 30 Reason Codes Explaining results Transparency It is really clear how a score card got its result Compliance Easy to enforce rules about use of specific attributes Simplicity Easy to use and explain Easy to implement Although not necessarily easy to build 2011 Decision Management Solutions 29

30 Deploying a scorecard Screenshots courtesy of FICO 2011 Decision Management Solutions 30

31 2011 Decision Management Solutions 31 The power of business rules Visible, business friendly analytic implementation Avoiding the mistrust of a black box Platform for all three groups to share All three legs can participate and collaborate Time to deploy A BRMS handles much of the complexity Support for defining actions Wrap into decisions

32 Integration options Native model execution Generate code or SQL Let the rules call the models when they need them Models as rules Manual or automatic import of models Create rules and rule artifacts that are executable Database scoring Traditional Separate services Let the rules call scoring services 2011 Decision Management Solutions 32

33 2011 Decision Management Solutions 33 Cautions PMML variations still exist Make sure you understand limitations and issues Variable creation and PMML PMML 4.0 supports variable creation Most tools do not export variable definitions Matching data Operational and analytic data are not always the same From a flat analytic data set to object models Once a model is in rules it can be edited.

34 2011 Decision Management Solutions 34 Case: Major medical insurer Dental Claims Processing Challenge: operationalize fraud models Legacy claims system uses fixed business logic Analytics models predict provider fraud Only currently applied after the fact pay and chase Solution Add a rules-based decision service to review claims Add rules to define new variables Make analytics visible and reviewable by experts Easily add judgment as well as analytics

35 From analytics to decision management

36 2011 Decision Management Solutions 36 Don t start by focusing on the data Analytic insight Better decision Derived information Available data

37 2011 Decision Management Solutions 37 Start by focusing on the decision Better decision Available data Derived information Analytic insight

38 2011 Decision Management Solutions 38 Business Process Legacy System Website Enterprise Application Cloud Mobile Decision Discovery Ask for a decision Get an action Decision Services Decision Service Policy Regulation Best Practices Know-how Business Rules Predictive Analytics Segmentation Clustering Risk Propensity Decision Analysis New approaches Refinements Data External Data

39 2011 Decision Management Solutions 39 Case: Fiserv Core banking systems for mid-sized banks Challenge: create value-add analytic offering Core functionality perceived as commodity Analytics delivers unique value Customers value (but don t understand) analytics Solution Identify key decisions Build rules-based, cross-channel decision services Automate analytic model creation and deployment Empower customers to own these decisions

40 Wrap Up

41 2011 Decision Management Solutions 41 The one slide you need It is easy to have analytic success without creating business value It is especially easy to fail to deliver business value when focused on operational analytics Business rules and a business rules management system provide an ideal platform for analytics Decision Management ties analytics and business rules together in an effective framework

42 2011 Decision Management Solutions 42 Action Plan Identify your decisions before analytics Adopt business rules to implement analytics Bring business, analytic and IT people together

43 Thank you! James Taylor, CEO