Decision CAMP 2014 - James Taylor - Decision Management 101

Decision Management 101
Decision CAMP 2014

CEO of Decision Management Solutions
We work with clients to improve their business by identifying and modeling decisions, and applying business rules and analytic technology to automate & improve these decisions.
I have spent the last 12 years championing Decision Management.
Your Instructor – James Taylor
© Decision Management Solutions, 2014
2

The Power of Decision Management
Decision Discovery
Decision Services
Decision Analysis
Getting Started
Agenda
3

The Power of Decision Management

Decision Management
Decision Management allows an organization to control, manage, and automate the repeatable decisions at the heart of its business by effectively applying business rules, analytics, and optimization technology
Decision Management:
Increases accuracy
Increases consistency
Increases agility
Reduces decision latency
Reduces costs
It is a proven framework for implementing Business Rules Management Systems and Predictive Analytics
5

Manage Risk
Personalize communication
Detect fraud
Enforce policies and regulations
What Can Decision Management Do?
And more…
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Strategic Decisions
Tactical
Decisions
Operational
Decisions
Different Kinds of Decisions
7

8
Repeatable decisions
Non trivial decisions
With a measurable business impact
That are candidates for automation
Suitable Decisions for Management

9
Operational Decisions Are Everywhere

Scale For Large Impact
Strategic Decision
Tactical Decision
Operational Decision
10

Straight Through Processing
Processes stop when decisions must be made
Process
Process
Process
Human
Decision
Human
Decision
Automated
Decisions
Straight Through Processing
Manage Rules &
Handle Exceptions
A
B
C
A
B
C
New
11

Maximize Customer Value
1:1 Marketing
Personalization
Next Best Offer
Next Best Action
Micro Segmentation
All ways of saying “Make each decision about a customer uniquely about that customer”
12

Effectively Manage Risk
Risk is not acquired in “big lumps”
Risk is acquired one transaction at a time
Supply chain risk when the wrong supplier is selected
Credit risk when a bad loan is approved
Delivery risk when a commitment is made for stock not available
…
13

14
Many Enterprise Systems …
Report but don’t learn
Wait rather than act
Escalate rather than empower
Mindlessly consistent

15
Automate More Decisions
Complexity
Value
Automated
Decisions
Expert
Decisions
Manual
Decisions

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Decision Management Systems

3 stages to better operational decisions
Delivering Decision Management
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Identify the decisions that are most important to your operational success
Design and build independent decision services to automate these decisions
Create a “closed loop” between operations and analytics to measure results and drive improvement

Decision Discovery

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Repeatable decisions
Non trivial decisions
With a measurable business impact
That are candidates for automation
Suitable Decisions for Management

Business Processes
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Discovering Decisions
Business Intelligence
Brainstorm
KPIs
Micro and hidden Decisions

“… provide a common notation that is readily understandable by all business users... DMN creates a standardized bridge for the gap between the business decision design and decision implementation.”
OMG Specification – a peer to BPMN
Decision Management Solutions, IBM, Oracle, TIBCO, FICO, Escape Velocity, KUL, Model Systems, KPI, Visumpoint
Standard content finalized, approval expected Q4-2014
Use Cases
Modeling Human Decision-making
Modeling Requirements for automated Decision-making
Implementing automated Decision-making
Decision Modeling and Notation (DMN)
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Decision Requirements Diagram
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Information
Knowledge
Decision
Increased Precision

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Decision Modeling
Identify a Decision
Question
Allowed Answers
What is required to make this decision?
Information
Reference Data
Transaction Data
Knowledge
Guidelines, policy
Expertise
Regulations
Analytic Insight
The results of other decisions
Reuse decisions
Identify new decisions

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Questions
Be specific with questions
Subject
Timing
Scope or limitations
Avoid
I, we
Questions that start “How”
Decision
Good question
Bad question
Customer Retention
Which retention offer should the company make this customer when they call to cancel their service?
How can we retain this customer?
Supplier Selection
Which of the company’s approved suppliers should be selected for this specific parts order?
What supplier should we use?
Preventative Action
What is the prioritized list of preventative actions for this quality team on this line today?
What preventative action should the quality team take?

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Allowed Answers
Type
Description
Notes
Yes/No
Yes or No
Or True/False, 1/0 etc
Number
A numeric value
Often constrained to a value in a specific range
Specific Value
One of the values specified in a list
For example Accept / Reject / Refer
Database value
A value stored in a database
Specify how to get the list of options - products, pieces of content etc.
Other
Generally a string or block of text
Such as a custom script or personalized email body
Structure
A set of values each of which is of one the allowed types
Some decisions involve the rolled-up output of their component decisions.
Single Answer
List of Options
Structure with parts
Supporting Information
Messages
Warnings
Notes
Explanations

Decision Requirements Diagram 1
26
Decision

Business Entities
Consider
Reference data
Case or transaction data
Best Practices
Stick to logical “clumps” of information
Business objects not technical ones
Could be one system or database, could be many
Each Input Data object can have a data structure
Input Data
27

28
Information

Decisions Involve Lots of Knowledge
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Decision

This knowledge can be of various types
External regulations
Internal policies
Expertise
Best Practices
Analytic Insight
Business Rules are found in Knowledge Sources
Consider
What tells me what I must do?
What tells me what I should do?
What tells me what I can do?
What tells me what I will probably do?
What would help me do it better?
“If only we knew xyz we could make a more profitable decision”
Knowledge Sources
30

31
Knowledge

32
Finding Dependencies in Decisions
What information do you need to make a decision
Is that information available in the environment
Or must it be determined by making another decision?
Is the decision “atomic” or could someone stop part way through it?
If they could get part way through the decision, what are the logical components of the decision? Where could you stop?
How does someone make the decision?
As someone describes the decision they will likely, naturally, describe it in pieces
Is the decision made differently (or not made) in certain circumstances
Decisions that determine those circumstances are therefore relevant

33
Increased Precision

34

Credit Limit Assignment
Credit Limit
Income
< $40,000
>= $40,000
Card Type
Standard
$1,000
$2,000
Gold
$1,500
$2,500
Applicant Risk
U
Applicant Age
Medical History
Applicant Risk Rating
1
> 60
good
Medium
2
bad
High
3
[25..60]
-
Medium
4
< 25
good
Low
5
bad
Medium
Special Discount
Type of Order
Web
-
Customer Location
US
-
Type of Customer
Wholesaler
Retailer
-
Special Discount %
10
5
0
F
1
2
3
DMN Decision Tables
Rules as rows
Rules as columns
Crosstab or “classic”
35

Simplifying Business Processes
Detailed requirements for business rules
Business understanding for analytic projects
Define Decision Service boundaries
Impact analysis
High level overview of decision-making
Improving Business Intelligence deliverables
Training decision-making staff
…
Multiple uses for Decision Models
36

Decisioning Complicates Processes
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Explicit Decisions Simplify
Separating Decisions simplifies Processes
Modeling Decisions brings clarity

Process and Decision Models
Process Model
Decision Requirements
Decision Logic
Identifies decision tasks
Links tasks to Decision Requirements Models
Specifies Decision Logic or business rules for automated decisions
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With Just a Bucket of Rules
How to manage sources?
How much detail for a given rule?
Who owns which rules?
How and where to document rules?
What are these rules for?
What is the right format for a rule?
How do we find the right metaphor for rules?

Decision requirements models break down complex, redundant, hard to manage rules
Each decision and sub-decision is described with simple, unique business rules
Source of rules and information shown
Dependencies are clear
Logical Modeling Helps Manage Rules
Documented sources
Coherent rule groups
Ownership, volatility
41

Stop Drowning People With Big Data
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Decision
Analytics
Data
Cut Through By Focusing on Decisions
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Link Analytics Explicitly To Action
44
Identify decision to be improved
Uses a non-technical notation
Model can be built by business analysts

45
Define Decision Service Boundaries
Find the top most decision nodes that will be automated
Their sub-tree will be implemented in the decision service
Knowledge sources define the business rules or analytics to be implemented
Most information nodes will be data sources outside the decision services
Multiple phases can be defined

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Impact Analysis

Decision Services

External Data
Big Data
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Building Decision Services
Business Rules
Predictive Analytics

Performance
Management
Enterprise Platform
Business
Intelligence
Data
Infrastructure
Application Context
Decision Service
Decision
Analysis
Business Rules
Predictive Analytics
Optimization
Business Process
Management
Event Processing
Enterprise
Application
Predictive
Analytics
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Decision Management In Context

50
Business Decisions Need Rules
Business decisions are rich in business meaning
Business decisions require collaboration
Business decisions are constantly changing

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() > 100000) aCustomer.setSpecialDiscount (0.05); } } }
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Business Rules Can Be Opaque

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Business Rules Management Systems

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Elements of a BRMS
Decision Service
Testing and Debugging
Technical Rule Management
Non-technical Rule Management
Impact Analysis
Data Management
Verification and Validation
Deployment
Rule
Repository

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Insight
Information
Data
Data, Information, Insight

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Usage Scenarios
Confirm or validate expert rules
Automatically discover patterns in data
Identify segments or groups with similar behavior
Predict trends or likely future behavior

Data Management
Data Preparation
Data Visualization & Analysis
Model Monitoring
Model Validation
Modeling
Deployment
Model
Repository
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Elements Of An Analytic Workbench
Rule
Repository
Operational
Data Store
Decision Service

Decision Analysis

58
Four Main Drivers Of Change
New
regulations
or policies
Changes to
business
goals
Changes in
underlying
data
Overall
decision
performance

59
An Environment For Improvement
•
My rules, in context
•
Only allow changes that make sense
•
No unnecessary information
Business User
Rules Management
•
Rapidly see
business
impact of changes
•
Design impact
and
execution impact
•
More than testing
Impact Analysis
•
Swapset
analysis for comparison
•
Simulation and what
-
if analysis
•
Business performance comparison
Alternatives
Assessment
•
Model performance monitoring
•
Self learning models
•
Managed model refresh
Analytic Models
Management

Decision Models link Business Performance to Execution
Improve Business Performance
Improve Cross-Sell
A
Total Number of Orders
Most Recent Order
Total Orders last 12 months
Lifetime Order Total
Customer Status
1
>= 5
< 90 days
> $10,000
-
Gold
2
>=10
< 180 days
> $20,000
-
Gold
3
>= 20
< 360 days
> $40,000
-
Gold
4
-
< 180 days
-
> $1,000,000
Gold
5
-
-
-
> $2,000,000
Gold
Gold Customer Determination
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Getting Started

Identify your decisions
Decisions that matter to customers
Transactional, operational decisions
Decisions that drive your business KPIs
Hidden and micro decisions
Model Decisions
Decision and Process Models help clarify requirements
Decision Requirement Models capture Information and Knowledge
Decision Requirement Models decompose decision-making for clarity
Decisions first, rules second
Model decisions before writing rules
Work top-down to reveal context
Iteratively extend the model, write the rules, develop the analytics, repeat
Key to Success - Focus On Decisions
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Key to Success - Technology Blueprint
Adopt a Business Rules Management System
Approach and technology
Management and governance
Change the relationship between business and IT
Integrate Data Mining and Predictive Analytics
Data Mining for rules
Predictive reporting
Executable analytics
Make Decision Services part of your architectural approach
Performance
Management
Enterprise Platform
Business
Intelligence
Data
Infrastructure
Application Context
Decision Service
Decision
Analysis
Business Rules
Predictive
Analytics
Optimization
Business Process
Management
Event Processing
Enterprise Application
Predictive
Analytics

65
Additional Resources
Technologies Available for Decision Management
Decision Management Overview
BPMN and DMN Modeling
DecisionsFirst Modeler

66
Wrapping Up
Thanks for attending the class
If you have any questions please email us:
james@decisionmanagementsolutions.com
info@decisionmanagementsolutions.com
Lots of additional content on our website, blog, twitter:
decisionmanagementsolutions.com
decisionmanagementsolutions.com/blog
@decisionmgt
More about DecisionsFirst Modeler
decisionmanagementsolutions.com/decisionsfirst-modeler

Decision CAMP 2014 - James Taylor - Decision Management 101

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Decision CAMP 2014 - James Taylor - Decision Management 101