Integrating Business Rules and Business Processes

Slide 1: Integrating Business Processes and Business Rules Michael zur Muehlen, Ph.D. Center of Excellence in Business Process Innovation Howe School of Technology Management Stevens Institute of Technology Hoboken NJ Michael.zurMuehlen@stevens.edu 1

Slide 2: Private university, founded 1870 ‣ 1800 undergraduate, 2600 graduate students ‣ Located in Hoboken, NJ (across the Hudson from Manhattan) Four Schools ‣ Technology Management ‣ Engineering ‣ Systems and Enterprises ‣ Arts & Sciences Rankings: ‣ Top 5 technology management program, on par with Stanford, MIT, CMU, Babson (Optimize Magazine) ‣ #1 for best distance learning program (Princeton Review) ‣ Top 25 for most connected Campus (Sloan Foundation) http://www.stevens.edu 2

Slide 3: Offers MBA in Technology Management, Master of Science (IS, Telecom Mgmt, Mgmt, EMTM), Bachelor’s Degree (Business & Technology) Programs taught on campus and off-site in corporate locations Clients: ADP, Avaya, BASF, Bristol-Myers Squibb, Chubb, Citigroup, Deutsche Bank, J&J, Lockheed, Merrill Lynch, PaineWebber, Pearson, Prudential, PSE&G, UBS, UPS, Verizon and others Research centers with focus on ‣ Process Management ‣ Project Management ‣ Product Innovation http://howe.stevens.edu 3

Slide 4: Rules + Processes = Simpler Processes Higher Agility Better Risk Management 4

Slide 5: Why don’t Users like Processes? Abstract Restrictive It’s not Excel 5

Slide 6: Too Abstract Process thinking requires a lateral view of the organization Process thinking requires to generalize from the day-to-day business Process thinking is expressed in (semi-) formal notation 6

Slide 7: Too Restrictive Try modeling the following: Manufacturing can start anytime after the payment from the customer has been received An inventory check, a credit check, and a regulatory check have to be performed - in any order After quotes from 3/4 of the eligible suppliers have been received, or after three days (whichever is earlier) a selection is made Users tend to think in “If-Then” scenarios 7

Slide 8: Example Completed questionnaire ... After 5 days Send Send ... questionnaire reminder 8

Slide 9: It’s not Excel 9

Slide 10: BPM: The Promise of Agility We deployed BPM to achieve three things: “ Shorten Processing Times Increase Revenue Enable Business Users to Change their Processes We have achieved the first two, but failed on the third. Royce (2007) 10

Slide 11: Managing Change Claims processing at major US Insurance company 12 Process Steps >5,000 Business Rules What do you think changes faster? 11

Slide 12: How many rules exactly? >90 product types and their associated product rules >700 data edit rules >70 claim pending rules >200 types of correspondence letters >250 claim processing and payment approval authority rules >70 claim quality review sampling rules >1,000 special client claim handling rules >2,000 federal/state regulatory rules >850 accounting rules >600 published claim processing guidelines 12

Slide 13: Integration Points Control Flow Decisions Assignment Decisions Monitoring of Policies and Exceptions 13

Slide 14: Control Flow Decisions Using Business Rules Engine to make data-based decisions about the sequence of processing steps From Workflow: Workflow-relevant data From BRMS: Branching decision Useful if multi-criteria decisions are needed 14

Slide 15: Manual Decision Making 15

Slide 16: Manual Decision Process Case Type A Review Process Case Application Type B Application received Process Case Type C 16

Slide 17: Multi-Step Decisions 17

Slide 18: Control Flow Decisions 18

Slide 19: Control Flow Decision Straight- >770 through Process 680<=770 Check Credit Manual Score Review Application received <680 Reject 19

Slide 20: Simpler Processes Loos (2007) 20

Slide 21: Decision Rules Sample Applications Customer Contact Scripts Validation of data before processing Complex decision scenarios Mining of rule criteria from runtime data Model process with high fidelity Run process and record audit trail Apply statistical analysis techniques to uncover correlation between process data and process path 21

Slide 22: Assignment Decisions Use BRMS to route work to the most qualified performer From Workflow: Assignment-relevant Data From BRMS: Identifier of qualified resource(s) Useful if assignment decisions are made based on data of the workflow object 22

Slide 23: Assignment Decision >770 Review by Intern 680<=770 Check Credit Review by Score Manager Application received <680 Review by CSR 23

Slide 24: Sample Rule If channel equals agency, and plan equals mortgage term or whole life, and region equals Midwest, and age is greater than 18 and less than or equal to 65, and face amount is more than $250,000 and less than $1,000,000, and policy is a conversion from existing policy Then assign to Midwest Level 1 Underwriter Group. No Channel Region Age Face Amount Conversion? Assignment 250,000 Midwest Level 1 Underwriter 1 Agency Midwest 18<=65 <=1,000,000 no Group East Level 2 Underwriter 2 Brokerage East 18<=65 >=1,000,000 yes Group 3 Agency South 18<=65 <250,000 no Underwriter Assistant Group Source: Royce (2007) 24

Slide 25: Original System 4. Underwriting 3. Application is assigned 1. Application is 2. Data is entered Begins to Underwriter during scanned into Into Admin indexing process. FileNet. Systems. Network Workflow FileNet Administrative Image System Systems 5. Workflow and associated route work through the business process based on the kind of policy. Source: Royce (2007) 25

Slide 26: Rule Engine Driven Assignment 1. Application is 2. Data is entered into 3. Applications are distributed based 4. Underwriting scanned into Admin Systems and on availability and skill level Begins FileNet. used by Rule Engine. and Admin Systems Are Updated. Assignment Engine Network FileNet Workflow, Administrative Image System Rule Engine and Robot Systems Source: Royce (2007) 26

Slide 27: Practical Experience “Right before going into production the underwriting department re-organized requiring the change of almost 100 assignment rules. These were all done by the business “ analyst who continues to make changes today.” “The rule engine was also used to “auto-issue” some of the highest volume insurance products. Currently over 20% of the most popular products are issued without a review by an underwriter.” Source: Royce (2007) 27

Slide 28: Moving to Exception Based Underwriting Underwriter reviews APS’s and some complex cases Rule Engine validates Data Entry App is Scanned Application information And Validation and OCR’ed and Issues some policies 24/7 Issue System Admin System Imaging System Workflow and Rule Engine Producer receives policy for delivery. Expanded Rules with Automatic Interface functionality may include: Straight-through processing Intelligent requirement processing Source: Royce (2007) Automated issue Minimized admin system entry 28 Workload Balancing

Slide 29: Cross-Process Policies Use BRMS to coordinate across process instances Example: During labor action, hold all non-critical orders Requires API for process control at the BPMS level 29

Slide 30: Business Operations Control Predictive Historical Real Time Simulation Dashboards Analytics Data Mining Alerts & Event Detection & Actions Optimization Correlation Event Bus EAI ERP BPM ECM Legacy Custom Shapiro (2007) 30

Slide 31: Real Time Actions & Alerts Dashboards Alerts & Rules Actions Engine KPI Evaluation Process Goals Metrics Thresholds Risk Mitigation Email and Cellphone Actions notification Web Service Call or Execute Script Process Event Triggers Action Schedule Shapiro (2007) 31

Slide 32: Managing Risks 32

Slide 33: Compliance Compliance means adherence to rules and regulations Process models provide execution rules Control flow: What happens when? Task allocation: Who is involved? Role models: Who may do what? But what about context? Business object dependencies: Value/Customer Type Environmental dependecies: Season/Off-season processing Regulatory compliance: Documentation/Audit Correlation of multiple processes 33

Slide 34: Managing Risk with BPMS Use formal Process Models to ensure process compliance Process Models can be scripts or maps If Scripts: Use BPMS to automate control flow, task allocation, application/service invocation If Maps: Use collaborative tools to allow execution flexibility BPMS provide risk management services Authorizations / Access Control Enforcement of routings, reviews Audit capability to document compliance 34

Slide 35: Managing Risk with BRMS Use Business Rules to ensure contextual compliance Document process objectives to prevent business rules from turning into process rules Performance Objectives combine BAM with BRMS Decision rules allow context-dependent enforcement of oversight Use Business Rules Management System to enforce compliance Document rules limit the state changes on documents Example: Can’t go from draft to approved without review Customer rules configure case handling 35

Slide 36: Standards? 36

Slide 37: BPMN - Modeling Notation

Slide 38: BPMN 1.1 Mainly cosmetic changes New symbol for Multiple Event and Gateway (used to be star) New Signal Event Separation of “catching” and “throwing” events 38

Slide 39: 0 30 60 90 120 Normal Flow Task End Event Start Event / Event Pool Data-Based XOR Start Message Message Flow Text Annotation Parallel Fork/Join Gateway Lanes Sub-Process (Collapsed) Association Data Object Intermediate Timer End Terminate Intermediate Message Sub-Process (Expanded) End Link Default Flow Inclusive Decision/Merge Activity Looping 'exception' task End Message Start Link End Exception Complex Decision/Merge Event-Based XOR Group Multiple Instance Intermediate Event Transaction Compensation Conditional Flow Practical Use of BPMN Symbols End Cancel Exception Flow Intermediate Compensation Source: Sample of 120 BPMN models Intermediate Link 39 Start Timer End Compensation Intermediate Multiple

Slide 40: goal is quantified by objective Synonymous Form: objective quantifies goal end channels efforts towards course of action desired result vision supported by quantified by goal objective strategy tactic quantifies Figure 8.3: - Desired Results — Goals and Objectives BMM - Means and Ends A Desired Result is an End that is a state or target that the enterprise intends to maintain or sustain. A Desired Result supported by Courses of Action. Compared to an Objective, a Goal tends to be longer term, qualitative (rather than quantitative), general (rather than specific), and ongoing. Compared to a Goal, an Objective tends to be short term, quantitative (rather than qualitative) specific (rather than general), and not continuing beyond its timeframe (which may be cyclical). 40 Objectives differ from Goals in that Objectives should always be time-targeted and measurable. Goals, in contrast, ar not specific in these ways.

Slide 41: directive is motivated by potential impact Synonymous Form: potential impact provides the impetus for directive means governed by supports governs achievement of course of action directive desired result formulated based on has achievement supported by source of business policy business rule strategy tactic Figure 8.8: - Interrelating Directives with Courses of Action and Ends BMM - Means and Ends As the name suggests, Directives indicate how the Courses of Action should, or should not, be carried out — in other words, they govern Courses of Action. Specifically, a Directive defines or constrains or liberates some aspect of an enterprise. It is intended to assert business structure or to control or influence the behavior of the business, and is stated in declarative form. Directives govern Courses of Action. For example, the Business Rule "Pizzas may not be delivered beyond a radius of 30 miles" governs the Strategy "Deliver pizzas to the location of the customer's choice." This governance applies to Tactics as well. For example, the Tactic "Encourage rental extensions" is governed by the Business Policy "Allow 41 extension of rentals by phone."

Slide 42: SBVR Semantics of Business, Vocabulary and Rules Formally defined taxonomy to describe elementary business operations and rules Meta model expressed in UML Business-level specification aims at enterprises to formally express their operations 42

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Slide 44: Production Rule Representation Exchange format for Business Rules (Production Rules) Defined by Fair Isaac & Co and ILOG Current revision submitted 09/03/2007 PRR Core defines basic meta model PRR OCL defines conditions and actions 44

Slide 45: Initiative), although they are a subclass of Computer Executable Rule rather than Rule t confusion with other uses of “Rule” as a metamodel class. Rule IntegrityRule DerivationRule ProductionRule TransformationRule ReactionRule InferenceRule SQL:1999 SQL:1999 View ECAPRule ECARule ProdeduralRule Assertion {OR} XSL 1.0 Rule SQL:1999 Trigger OCL 2.0 Invariant ILOG JRule BlazeAdvisorRule Oracle 10g XSB 2.6 Prolog MS Outlook 6 Rule Jess 3.4 Rule SQL View Rule PRR Focus Rule classification per Gerd Wagner, RuleML PRR Taxonomy 45

Slide 46: SWRL and RIF Semantic Web Rules Language - Proposal submitted to W3C Rules Interchange Format - Initiative within W3C SWRL combines OWL and RuleML, some use in practice RIF is in very early stages, but keep an eye on it 46

Slide 47: Getting Started Some practical advice 47

Slide 48: Business Rules Business Processes Business Objectives Business Activities govern & prioritize Process Objectives Core Processes govern govern Business Rules Business Processes use govern Operational Rules Work Processes use 48

Slide 49: Identify Business Identify Business Objectives Activities Identify Process Identify Core Objectives Processes Create Rules Model Processes Model Detailed Create Detailed Rules Processes 49

Slide 50: Classifying Change Frequency Hourly Daily Monthly Infrequent Scope Company-wide Multi-Process Process Activity Responsibility LOB Biz Analyst System Analyst Programmer Trigger External Biz Partner Internal Predictability Low Medium High Persistency Instance Days Months Permanent 50

Slide 51: Thank You – Questions? Michael zur Muehlen, Ph.D. Center of Excellence in Business Process Innovation Howe School of Technology Management Stevens Institute of Technology Castle Point on the Hudson Hoboken, NJ 07030 Phone: +1 (201) 216-8293 Fax: +1 (201) 216-5385 E-mail: mzurmuehlen@stevens.edu Web: http://www.cebpi.org 51