Business Architecture Presentations

Extending Business Architecture with Regulatory Architecture using Decisions and DMN

Description

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

Transcript

Extending Business Architecture
with Regulatory Architecture using Decisions and DMN
BUILDING BUSINESS CAPABILITY 2015
LAS VEGAS
Gagan Saxena, VP & Principal Consultant
Decision Management Solutions
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
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
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
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
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
6
Decision-Centric Knowledge Economy
•  Beyond Process Centric
•  But Big Data Centric
•  Predictive Analytics and Optimization Algorithms
•  Taming the Robot Overlords
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
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
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?
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 the head
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 submitters
Decision Model and Notation (DMN)
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
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
Business Process Model
Knowledge Source & Info Source
Automation Boundaries
Decision Table
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
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
21
Common Decision Pattern Identified
•  Decision Requirement Diagrams from multiple Regulators built
•  Common Decision Patterns Identified
•  Common, reusable Decision taken forward for automation
22
Block Trade Size Calculation Decision
•  Automation Boundary established
•  Detailed Decision Requirement Diagrams built
•  Logic requirements captured as Decision Tables
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
24
Results
•  Simplification
•  Consensus
•  Data Requirements
•  Implementation Plans
•  Shared Components
•  Governance and Ownership Structures
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
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
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
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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