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Extending Business Architecture
with Regulatory Architecture using Decisions and DMN
BUILDING BUSINESS CAPABILITY 2015
LAS...
We help organizations plan, design, build and
operate Decision Management Systems.
Automate high-volume operational decisi...
2
Agenda
1.  What is the Problem we are Solving
2.  Why Decisions and DMN were applicable
3.  How does Architecture come i...
Take Away Points from Today
3
•  Business Architecture in Action
•  Central Role of Decisions in pulling Architecture toge...
4
Regulations: Compliance & Traceability
•  Regulations are ‘Knowledge’ that influence how decisions are made
•  But Decis...
5
Regulations = Rules = Policies = Guidelines
•  One decision can consume multiple ‘rules’ (and analytic models)
•  Some f...
6
Decision-Centric Knowledge Economy
•  Beyond Process Centric
•  But Big Data Centric
•  Predictive Analytics and Optimiz...
7
Why Decisions are Important
•  First, Decisions are real, tangible ‘things’ that can be described, managed and
improved
...
DECISION
Information
Knowledge
ACTION
Learnt
Rules
Patterns Predictions
Trade-Offs
Big Data
Business Rules
Data Mining Pre...
ü Guidelines, Policy documents
ü Human Expertise
ü Regulations
ü Data describing the situation
ü External reference d...
Complexity
Value
Automated
Decisions
Expert
Decisions
Manual
Decisions
10
11IMAGE COURTESY: IBM
Can’t keep Decisions in your Head
To build fancy gizmos, we need to first document what is inside th...
12
From Individual to Org Decision Making
•  Capture Organizational Decision Making – Transparent, Reproducible
13
Describing Decisions = DMN
•  Everyone need not describe their decision making in their own words
INDUSTRY STANDARD
FROM
OBJECT MANAGEMENT GROUP
January 2014
14
Decision Management Solutions is one of the original DMN su...
Information
•  What is needed?
•  Where does it come
from?
Knowledge
•  How to make it?
•  How to improve it?
Precision
• ...
FIRST CANDIDATE
FOR AUTOMATION
16
Knowledge
Information
Decision
Manage Automation Boundaries
17
Decisions Connect Business Architecture
18
Key Steps: Regulatory Decision Architecture
Example – Regulation CFTC 43
Decision Catalog
Decision Requirements Model
B...
19
•  Legal Language = Logical and Mathematical, Conditional
•  Rules about *how* to make decisions
•  Discover Decisions ...
20
CFTC Part 43 Decision Requirements
•  Decisions Requirement Diagram for CFTC Part 43
•  Decisions ‘discovered’
•  Knowl...
21
Common Decision Pattern Identified
•  Decision Requirement Diagrams from multiple Regulators built
•  Common Decision P...
22
Block Trade Size Calculation Decision
•  Automation Boundary established
•  Detailed Decision Requirement Diagrams buil...
23
Techniques
•  Prototyping
•  Agile Development
•  Formal Training Classes
•  Informal Check-in and Practical Hands on W...
24
Results
•  Simplification
•  Consensus
•  Data Requirements
•  Implementation Plans
•  Shared Components
•  Governance ...
Agile Decision Requirements
•  Build diagrams quickly, finding and reusing objects or importing
existing information
Conne...
26
Challenges
•  Need to get up to speed on the concept of Decisions
•  Unclear distinction between Rules and Decisions
• ...
27
The Path Forward
•  Beyond Regulations – Most Business Rules can be automated
•  Business Concepts need to be formally ...
Take Away Points from Today
28
•  Business Architecture in Action
•  Central Role of Decisions in pulling Architecture tog...
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Extending Business Architecture with Regulatory Architecture using Decisions and DMN

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As businesses have an increasing obligation to demonstrate compliance with regulations there is a need for a business architecture view that not only tracks regulations impact but also connects seamlessly to diverse, distributed implementations in automated systems and manual procedures. The Decision Model Notation (DMN) has been used to create a decision architecture for regulatory compliance at a leading global financial organization. This Regulatory Architecture includes business decisions impacted by a variety of global financial regulations – the Dodd Frank Act, in particular. This business architecture has been modeled in the form of decision requirement models and aligned with business process and business organization architectures. Presented by Gagan Saxena of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015

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Extending Business Architecture with Regulatory Architecture using Decisions and DMN

  1. 1. Extending Business Architecture with Regulatory Architecture using Decisions and DMN BUILDING BUSINESS CAPABILITY 2015 LAS VEGAS Gagan Saxena, VP & Principal Consultant Decision Management Solutions
  2. 2. We help organizations plan, design, build and operate Decision Management Systems. Automate high-volume operational decisions using Big Data Analytics, Business Rules and Optimization Algorithms. 1 Decision Management Solutions
  3. 3. 2 Agenda 1.  What is the Problem we are Solving 2.  Why Decisions and DMN were applicable 3.  How does Architecture come into play 4.  How was the Decision Architecture built and deployed 5.  What were the Results 6.  Challenges along the way 7.  The Path Forward
  4. 4. Take Away Points from Today 3 •  Business Architecture in Action •  Central Role of Decisions in pulling Architecture together •  Regulations and Laws can be managed and automated •  Regulations = Rules = Policies = Guidelines
  5. 5. 4 Regulations: Compliance & Traceability •  Regulations are ‘Knowledge’ that influence how decisions are made •  But Decisions have never been formally described •  Several layers of Legal Interpretation •  Long lead times in 'programming' regulations •  Implementing Business Rules was almost as bad as programming, since •  No traceability or organizing structure
  6. 6. 5 Regulations = Rules = Policies = Guidelines •  One decision can consume multiple ‘rules’ (and analytic models) •  Some from regulators and others internal to the business •  A coherent and consistent set of rules improves decision making
  7. 7. 6 Decision-Centric Knowledge Economy •  Beyond Process Centric •  But Big Data Centric •  Predictive Analytics and Optimization Algorithms •  Taming the Robot Overlords
  8. 8. 7 Why Decisions are Important •  First, Decisions are real, tangible ‘things’ that can be described, managed and improved •  Decisions inject knowledge (rules, analytics, algorithms) into Processes •  Decisions consume Information or Data •  Decisions can be automated and automation boundaries established for clarity •  Decisions Requirements drive Business Rules Implementation •  Decision Requirement direct Project Portfolio Management and Prioritization
  9. 9. DECISION Information Knowledge ACTION Learnt Rules Patterns Predictions Trade-Offs Big Data Business Rules Data Mining Predictive Analytics Optimization Information Knowledge DECISION MANAGEMENT TECHNOLOGY DECISIONCONSIDER FIRST DECISION ✔ 8 Harnessing New Technologies
  10. 10. ü Guidelines, Policy documents ü Human Expertise ü Regulations ü Data describing the situation ü External reference data ü Predictive Analytic Models ü Data Mining Results ü The results of other Decisions 9 What is required to make a Decision?
  11. 11. Complexity Value Automated Decisions Expert Decisions Manual Decisions 10
  12. 12. 11IMAGE COURTESY: IBM Can’t keep Decisions in your Head To build fancy gizmos, we need to first document what is inside the head
  13. 13. 12 From Individual to Org Decision Making •  Capture Organizational Decision Making – Transparent, Reproducible
  14. 14. 13 Describing Decisions = DMN •  Everyone need not describe their decision making in their own words
  15. 15. INDUSTRY STANDARD FROM OBJECT MANAGEMENT GROUP January 2014 14 Decision Management Solutions is one of the original DMN submitters Decision Model and Notation (DMN)
  16. 16. Information •  What is needed? •  Where does it come from? Knowledge •  How to make it? •  How to improve it? Precision •  Exactly how? •  Specificity without technical details Context •  Application •  Organization •  Business Goals 15 Need to Describe Decisions Formally
  17. 17. FIRST CANDIDATE FOR AUTOMATION 16 Knowledge Information Decision Manage Automation Boundaries
  18. 18. 17 Decisions Connect Business Architecture
  19. 19. 18 Key Steps: Regulatory Decision Architecture Example – Regulation CFTC 43 Decision Catalog Decision Requirements Model Business Process Model Knowledge Source & Info Source Automation Boundaries Decision Table
  20. 20. 19 •  Legal Language = Logical and Mathematical, Conditional •  Rules about *how* to make decisions •  Discover Decisions by framing Questions the Rule wants to consider •  Definitions, Threshold Values = Knowledge •  Entities under consideration = Information Sources Analyzing the Regulations
  21. 21. 20 CFTC Part 43 Decision Requirements •  Decisions Requirement Diagram for CFTC Part 43 •  Decisions ‘discovered’ •  Knowledge Sources identified •  Information Sources identified •  Overall dependencies and structure captured
  22. 22. 21 Common Decision Pattern Identified •  Decision Requirement Diagrams from multiple Regulators built •  Common Decision Patterns Identified •  Common, reusable Decision taken forward for automation
  23. 23. 22 Block Trade Size Calculation Decision •  Automation Boundary established •  Detailed Decision Requirement Diagrams built •  Logic requirements captured as Decision Tables
  24. 24. 23 Techniques •  Prototyping •  Agile Development •  Formal Training Classes •  Informal Check-in and Practical Hands on Work •  Coaching and Guidance •  Executive sponsorship and ownership •  Constantly collect and share learning
  25. 25. 24 Results •  Simplification •  Consensus •  Data Requirements •  Implementation Plans •  Shared Components •  Governance and Ownership Structures
  26. 26. Agile Decision Requirements •  Build diagrams quickly, finding and reusing objects or importing existing information Connect Decisions, Processes, Systems, Orgs •  Put decisions into context, linking them to process, systems and organizations. Collaborate across silos •  Accessible from anywhere, a social powered and collaborative environment supports multiple perspectives Integrate with your Approach •  Define your own completeness levels and link to your BRMS, Analytics and Optimization 25 Decision Modeling Imperatives
  27. 27. 26 Challenges •  Need to get up to speed on the concept of Decisions •  Unclear distinction between Rules and Decisions •  Limited or no skills in Decision Management •  Need to demonstrate reuse and sharing of components •  Constantly evolving process context; unclear workflows •  Common Data Model evolving •  Multiple technologies and systems, owned by multiple, independent tech teams
  28. 28. 27 The Path Forward •  Beyond Regulations – Most Business Rules can be automated •  Business Concepts need to be formally defined •  Decision Centric Culture drives Process Simplification, Elimination •  Decisions inject Big Data and Predictive Analytics into Processes •  Decision Centric Culture key for ‘manual’ Decision-Making too
  29. 29. Take Away Points from Today 28 •  Business Architecture in Action •  Central Role of Decisions in pulling Architecture together •  Regulations and Laws can be managed and automated •  Regulations = Rules = Policies = Guidelines More at DecisionManagementSolutions.com

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