SlideShare a Scribd company logo
Implementing
Analytics?
You Need
Decision Modeling
and Business Rules
JamesTaylor,
CEO
1 2 3
4 5 6
AGENDA
The power of
analytics
Challenges in
analytics
Introducing
business rules
Integrating
business rules
and analytics
Decision
Management
Wrap Up
©2009-2017 Decision Management Solutions 3
The one slide you need
Analytics have great potential to improve day to
day operations
Challenges include
Business value gap
Engaging the business and IT
Deployment
A business rules management system (BRMS) is
an ideal platform for analytics
Decision Management ties analytics and business
rules together in an effective decision model
framework
The power of analytics
©2009-2017 Decision Management Solutions4
Analytics have power
Customer
Churn
Campaign
Response
Acquisition
Rates
Online
Conversion
Fraud Risk
©2009-2017 Decision Management Solutions 5
©2009-2017 Decision Management Solutions 6
And that power is operational
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 just about “aha” moments
It’s about making better operational decisions
©2009-2017 Decision Management Solutions 7
Operational Decisions Scale For Big Impact
Strategic
Decision
Tactical
Decision
Operational
Decision
©2009-2017 Decision Management Solutions 8
Case: Telco
Example: Analytics enabling an individualized decision about the best
plan/upgrade offer to make to each customer
Challenges
in Analytics
©2009-2017 Decision Management Solutions9
Knowing is not enough
©2009-2017 Decision Management Solutions 10
Those who know first, win
Those who ACT first, win
Provided they act intelligently
Latency in decisions costs you
©2009-2017 Decision Management Solutions 11
Business
event
Action
taken
Decision latency
Operational decisions are at the center
Business
©2009-2017 Decision Management Solutions 12
Monitoring and compliance matter
©2009-2017 Decision Management Solutions 13
Analytics improves operations but…
Power of analytics is in improving operations
Specifically operational decisions
Which means :
Focus on actions not predictions
Minimize the time to impact
Engage analytics, IT, and business teams
Handle monitoring and compliance
©2009-2017 Decision Management Solutions 14
Case: Trade credit insurance
New
countries in
weeks not
months
Ongoing
changes in
hours, not
weeks
Immediate
changes in a
crisis
©2009-2017 Decision Management Solutions 15
Introducing
business rules
What are business rules?
“… a directive intended to influence
behavior.”
“… a formal expression of knowledge or
preference, a guidance system for steering
behavior (a transaction) in a desired
direction.”
“… statements of the actions you should
take when certain business conditions are
true.”
©2009-2017 Decision Management Solutions 17
Business Rules are everywhere
Experienced
Personnel
RegulationsPolicy Manuals
Legacy Systems
Historical Data
©2009-2017 Decision Management Solutions 18
©2009-2017 Decision Management Solutions 19
Business rules drive decisions
Decision
History
Experience
Policy
Regulations
Legacy
Applications
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);
}
}
}
Unmanageable business rules
©2009-2017 Decision Management Solutions 20
Decision
Service
A Business Rules Management System
After Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.6
Design
Tools
Rule
Management
Applications
Rule Engine
Operational
Database
Rule
Repository
Production
Application
Validation and
Verification
Testing
Deployment
©2009-2017 Decision Management Solutions 21
Manageable business rules
Smart (Enough) Systems, Prentice Hall June 2007. Fig 4.3
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=“email”
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”
©2009-2017 Decision Management Solutions 22
©2009-2017 Decision Management Solutions 23
Rule Sheets
Set of rules that share common action(s)
Sequence does not matter
Typically exhaustive and exclusive
Sometimes called a decision table, rule family
Name
Condition
Attribute 1
Condition
Attribute 2
Condition
Attribute 3
Action
Attribute 4
Rule 1 > 2 < 3 =6
Rule 2 <=2 >=3 =12
Rule 3 <=2 <3 True =13
Rule 4 <=2 <3 False =14
Rule 5 >2 >=3 True =10
Rule 6 >2 >=3 False =2
©2009-2017 Decision Management Solutions 24
Decision Table
Set of rules that return a single result
Look up tables, comparing attribute values
Sequence does not matter
Typically exhaustive and exclusive
Attribute 2
Single Family with no
children
Family with
children
Attribute1
< 10 1 2 3
11 – 20 2 4 6
21 – 40 3 5 7
41 – 99 4 6 8
>= 100 5 6 9
©2009-2017 Decision Management Solutions 25
Decision Tree
Set of rules that select a goal from a set
Divides into increasingly fine grained groups
Often a powerful thinking tool
Typically exhaustive and exclusive
Existing
Customer?
Long term
customer?
Grandfather
Issue change
Price quoted
Retract
quote
Issue
warning
Y
N
Y
N
Y
N
©2009-2017 Decision Management Solutions 26
A list of rules representing a rule set
AdjustIncome RuleSet (newApplicant)
Name: Six months or less on the job
if newApplicant’s monthsInCurrentJob is less than or equal to 6
then decrement newApplicant’s income by 5600
Name: About 1 year
if newApplication’s monthsInCurrentJob is between 6 and 13
then increment newApplicant’s income by 1000
Name: Greater than 1 year
if newApplicant’s monthsInCurrentJob is greater than 12
then increment newApplicant’s income by 2500
Name: Computer Total Income
if newApplicant is married
and newApplicant’s spousalIncome is greater than 0
then newApplicant’s totalIncome is equal to newApplicant’s income plus newApplicant’s spousalIncome
else newApplicant’s totalIncome is equal to newApplicant’s income
Name: Minimum Income
if newApplicant’s totalIncome is less than 40000
then newApplicant is not eligible
Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.3
Why manage business rules
Improve Decision Making
• Clear policies and procedures
• Consistently applied across channels, systems
• Increased accuracy from business users participation
Business Agility
• More rapid response to business threats
• Fewer missed opportunities
• Faster time to market
Reduce Costs
• Fewer resources, less time to change decisions
• Lower fines, legal costs from bad decisions
• Reduced IT costs to implement decisions
©2009-2017 Decision Management Solutions 27
Cross-channel
coordination
ensures that all
relevant offers,
including loyalty
programs, are
combined at the
point of sale, with
consistent pricing
rules applied.
©2009-2017 Decision Management Solutions 28
Case: International retailer
Integrating
business rules
and analytics
30
Different kinds of analytics
Data Mining
Who are my
best/worst customers?
How do I turn my
data into rules for
better decisions?
Predictive Analytics
How are those
customers likely to
behave in the future?
How do they react to
the myriad ways I can
“touch” them?
Knowledge - Description Action - Prescription
Business Intelligence
How do I use data to
learn about my
customers?What has
been happening in my
business?
©2009-2017 Decision Management Solutions
*
*
*
*
****
**
*
* **
*
*
*
*
*
* *
* *
* *
*
* *
*
*
*
*
*
*
** *
* ** * *
***
*
* *
**
***
**
*
*
*
*
****
**
*
* **
*
*
*
*
*
* *
* *
* *
*
* *
*
*
*
*
*
*
** *
* ** * *
***
*
* *
**
***
**
Your data is a source of insight
©2009-2017 Decision Management Solutions 31
*
*
*
*
****
**
*
* **
*
*
*
*
*
* *
* *
* *
*
* *
*
*
*
*
*
*
** *
* ** * *
***
*
* *
**
***
**
Insight as presentation is disconnected
©2009-2017 Decision Management Solutions 32
?
*
*
*
*
****
**
*
* **
*
*
*
*
*
* *
* *
* *
*
* *
*
*
*
*
*
*
** *
* ** * *
***
*
* *
**
***
**
Insights as decisions drive action
©2009-2017 Decision Management Solutions 33
Existing
Customer?
Long term
customer?
Grandfather
Issue
change
Price quoted
Retract
quote
Issue
warning
*
*
*
*
*
*
* *
**
*
*
**
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
**
*
*
*
* * *
*
*
*
*
* *
*
*
*
**
**
Low-moderate
income, young
High
Income High income,
low-moderate education
Moderate-high education
low-moderate income
High
Moderate education,
low income, middle-aged
Low education,
low income
Education
High
Descriptive analytics
©2009-2017 Decision Management Solutions 34
Predictive analytics
Attribute 2
Single Family with
no children
Family with
children
Attribute1
< 10 1 2 3
11 – 20 2 4 6
21 – 40 3 5 7
41 – 99 4 6 8
>= 100 5 6 9
©2009-2017 Decision Management Solutions 35
Scorecards are a powerful tool
Years Under Contract
1 0
2 5
More than 2 10
Number of Contract Changes
0 0
1 5
More than 1 10
Value Rating of Current Plan
Poor 0
Good 10
Excellent 20
Score
Smart (Enough) Systems, Prentice Hall June 2007. Fig 5.4
30
©2009-2017 Decision Management Solutions 36
Building Decision Services
Smart (Enough) Systems, Prentice Hall June 2007. Fig 5.1
Production
ProcessData
Warehouse
Operational
Data Store
Business
Rules
Business
Analytics
Decision
Service
Enterprise IT Infrastructure
Adaptive
Control
Events
©2009-2017 Decision Management Solutions 37
Case: Underwriting
Manual reviews Control
Business focus Risk
8 Point Reduction in
Combined Ratio
©2009-2017 Decision Management Solutions 38
Decision Management
Decision Management
Ties analytics and business rules together in
an effective decision model framework
Models decision-making (DMN standard)
Integrates with execution environment
Builds on existing enterprise architecture
©2009-2017 Decision Management Solutions 40
©2009-2017 Decision Management Solutions 41
Delivering Decision Management
3 stages to better operational decisions
Identify the
decisions (usually
about customers)
that are most
important to your
operational success
Design and build
independent decision
services to replace
decision points
embedded in
operational systems
Create a “closed
loop” between
operations and
analytics to
measure results and
drive improvement
Case: State dept of taxation
Business challenges Solution Benefits
Paper tax returns
increased costs and
slowed responses
Information system
silos
Manual fraud
detection and return
review
Single central
taxpayer database
Integrated system
Sophisticated real-
time predictive
analytics
Recovered millions
of dollars from
dubious tax returns
Increased collection
of unpaid taxes
Decreased number
of questionable
returns
Increased customer
satisfaction
©2009-2017 Decision Management Solutions 42
Implementing Analytics Gets Results
Actions not predictions
Minimum time to impact
Engage IT, Business
Handle monitoring , compliance
Decision Management ties analytics and
business rules together in an effective
decision model framework
©2009-2017 Decision Management Solutions 43
Wrap Up
©2009-2017 Decision Management Solutions 45
The one slide you need
Analytics have great potential to improve day to
day operations
Challenges include
Business value gap
Engaging the business and IT
Deployment
A business rules management system (BRMS) is
an ideal platform for analytics
Decision Management ties analytics and business
rules together in an effective decision model
framework
©2009-2017 Decision Management Solutions 46
Action Plan
Identify your decisions
before analytics
Adopt business rules to
implement analytics
Bring business, analytic
and IT people together
Decision Management Solutions
Decision Management Solutions can help you
Focus on the right decisions
Implement a blueprint
Define a strategy
Learn more:
Contact Us
www.decisionmanagementsolutions.com
info@decisionmanagementsolutions.com
©2009-2017 Decision Management Solutions 47
Thank you!
James Taylor, CEO
james@decisionmanagementsolutions.com
www.decisionmangementsolutions.com

More Related Content

What's hot

Data Architecture for Solutions.pdf
Data Architecture for Solutions.pdfData Architecture for Solutions.pdf
Data Architecture for Solutions.pdf
Alan McSweeney
 
Data-Ed: Data Governance Strategies
Data-Ed: Data Governance StrategiesData-Ed: Data Governance Strategies
Data-Ed: Data Governance Strategies
Data Blueprint
 
Digital Transformation And Solution Architecture
Digital Transformation And Solution ArchitectureDigital Transformation And Solution Architecture
Digital Transformation And Solution Architecture
Alan McSweeney
 
Business Intelligence: Data Warehouses
Business Intelligence: Data WarehousesBusiness Intelligence: Data Warehouses
Business Intelligence: Data Warehouses
Michael Lamont
 
Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)
DATAVERSITY
 
How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...
Christopher Bradley
 
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDGSAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
July A. M. Rizzo
 
Real-World Data Governance: Data Governance Policy - Components and Content
Real-World Data Governance: Data Governance Policy - Components and ContentReal-World Data Governance: Data Governance Policy - Components and Content
Real-World Data Governance: Data Governance Policy - Components and Content
DATAVERSITY
 
ERP Cloud: Assessing Readiness and Building the Roadmap
ERP Cloud: Assessing Readiness and Building the RoadmapERP Cloud: Assessing Readiness and Building the Roadmap
ERP Cloud: Assessing Readiness and Building the Roadmap
Capgemini
 
Business Drivers Behind Data Governance
Business Drivers Behind Data GovernanceBusiness Drivers Behind Data Governance
Business Drivers Behind Data Governance
Precisely
 
Ecosystem innovation – a new approach to complex supply chain challenges to c...
Ecosystem innovation – a new approach to complex supply chain challenges to c...Ecosystem innovation – a new approach to complex supply chain challenges to c...
Ecosystem innovation – a new approach to complex supply chain challenges to c...
Shaun West
 
Master Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and GovernanceMaster Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and Governance
DATAVERSITY
 
RWDG Slides: Build an Effective Data Governance Framework
RWDG Slides: Build an Effective Data Governance FrameworkRWDG Slides: Build an Effective Data Governance Framework
RWDG Slides: Build an Effective Data Governance Framework
DATAVERSITY
 
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
Mirco Hering
 
Business Value Metrics for Data Governance
Business Value Metrics for Data GovernanceBusiness Value Metrics for Data Governance
Business Value Metrics for Data Governance
DATAVERSITY
 
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
Alan McSweeney
 
Business Intelligence (BI) and Data Management Basics
Business Intelligence (BI) and Data Management  Basics Business Intelligence (BI) and Data Management  Basics
Business Intelligence (BI) and Data Management Basics
amorshed
 
Advanced Analytics Governance - Effective Model Management and Stewardship
Advanced Analytics Governance - Effective Model Management and StewardshipAdvanced Analytics Governance - Effective Model Management and Stewardship
Advanced Analytics Governance - Effective Model Management and Stewardship
DATAVERSITY
 
Pm3
Pm3Pm3
Pm3
natluc
 
Building an Effective Data & Analytics Operating Model A Data Modernization G...
Building an Effective Data & Analytics Operating Model A Data Modernization G...Building an Effective Data & Analytics Operating Model A Data Modernization G...
Building an Effective Data & Analytics Operating Model A Data Modernization G...
Mark Hewitt
 

What's hot (20)

Data Architecture for Solutions.pdf
Data Architecture for Solutions.pdfData Architecture for Solutions.pdf
Data Architecture for Solutions.pdf
 
Data-Ed: Data Governance Strategies
Data-Ed: Data Governance StrategiesData-Ed: Data Governance Strategies
Data-Ed: Data Governance Strategies
 
Digital Transformation And Solution Architecture
Digital Transformation And Solution ArchitectureDigital Transformation And Solution Architecture
Digital Transformation And Solution Architecture
 
Business Intelligence: Data Warehouses
Business Intelligence: Data WarehousesBusiness Intelligence: Data Warehouses
Business Intelligence: Data Warehouses
 
Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)Data Governance Takes a Village (So Why is Everyone Hiding?)
Data Governance Takes a Village (So Why is Everyone Hiding?)
 
How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...How to identify the correct Master Data subject areas & tooling for your MDM...
How to identify the correct Master Data subject areas & tooling for your MDM...
 
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDGSAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
SAP Forum Brasil 2018 - Tire suas dúvidas sobre o SAP MDG
 
Real-World Data Governance: Data Governance Policy - Components and Content
Real-World Data Governance: Data Governance Policy - Components and ContentReal-World Data Governance: Data Governance Policy - Components and Content
Real-World Data Governance: Data Governance Policy - Components and Content
 
ERP Cloud: Assessing Readiness and Building the Roadmap
ERP Cloud: Assessing Readiness and Building the RoadmapERP Cloud: Assessing Readiness and Building the Roadmap
ERP Cloud: Assessing Readiness and Building the Roadmap
 
Business Drivers Behind Data Governance
Business Drivers Behind Data GovernanceBusiness Drivers Behind Data Governance
Business Drivers Behind Data Governance
 
Ecosystem innovation – a new approach to complex supply chain challenges to c...
Ecosystem innovation – a new approach to complex supply chain challenges to c...Ecosystem innovation – a new approach to complex supply chain challenges to c...
Ecosystem innovation – a new approach to complex supply chain challenges to c...
 
Master Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and GovernanceMaster Data Management - Aligning Data, Process, and Governance
Master Data Management - Aligning Data, Process, and Governance
 
RWDG Slides: Build an Effective Data Governance Framework
RWDG Slides: Build an Effective Data Governance FrameworkRWDG Slides: Build an Effective Data Governance Framework
RWDG Slides: Build an Effective Data Governance Framework
 
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
Next Generation IT Delivery - What it means to deliver atthe speed of the Dig...
 
Business Value Metrics for Data Governance
Business Value Metrics for Data GovernanceBusiness Value Metrics for Data Governance
Business Value Metrics for Data Governance
 
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
Data Integration, Access, Flow, Exchange, Transfer, Load And Extract Architec...
 
Business Intelligence (BI) and Data Management Basics
Business Intelligence (BI) and Data Management  Basics Business Intelligence (BI) and Data Management  Basics
Business Intelligence (BI) and Data Management Basics
 
Advanced Analytics Governance - Effective Model Management and Stewardship
Advanced Analytics Governance - Effective Model Management and StewardshipAdvanced Analytics Governance - Effective Model Management and Stewardship
Advanced Analytics Governance - Effective Model Management and Stewardship
 
Pm3
Pm3Pm3
Pm3
 
Building an Effective Data & Analytics Operating Model A Data Modernization G...
Building an Effective Data & Analytics Operating Model A Data Modernization G...Building an Effective Data & Analytics Operating Model A Data Modernization G...
Building an Effective Data & Analytics Operating Model A Data Modernization G...
 

Viewers also liked

Implementing a Successful, Scalable, Governed BI Program
Implementing a Successful, Scalable, Governed BI ProgramImplementing a Successful, Scalable, Governed BI Program
Implementing a Successful, Scalable, Governed BI Program
Pyramid Analytics
 
Integrating Business Rules and Business Processes
Integrating Business Rules and Business ProcessesIntegrating Business Rules and Business Processes
Integrating Business Rules and Business Processes
Michael zur Muehlen
 
Analytics Teams: 5 Things You Need to Know Before You Deploy Your Model
Analytics Teams: 5 Things You Need to Know Before You Deploy Your ModelAnalytics Teams: 5 Things You Need to Know Before You Deploy Your Model
Analytics Teams: 5 Things You Need to Know Before You Deploy Your Model
Decision Management Solutions
 
The Value of Predictive Analytics and Decision Modeling
The Value of Predictive Analytics and Decision ModelingThe Value of Predictive Analytics and Decision Modeling
The Value of Predictive Analytics and Decision Modeling
Decision Management Solutions
 
Avola Decision Platform - Flyer ENG
Avola Decision Platform - Flyer ENGAvola Decision Platform - Flyer ENG
Avola Decision Platform - Flyer ENG
Marc Gelissen
 
Automated loan processing
Automated loan processingAutomated loan processing
Automated loan processing
Newgen Software Technologies Limited
 
Transforming Business with Smarter Analytics
Transforming Business with Smarter AnalyticsTransforming Business with Smarter Analytics
Transforming Business with Smarter Analytics
CTI Group
 
Decision CAMP 2014 - James Taylor - Decision Management 101
Decision CAMP 2014 - James Taylor - Decision Management 101Decision CAMP 2014 - James Taylor - Decision Management 101
Decision CAMP 2014 - James Taylor - Decision Management 101
Decision CAMP
 
Audiences webinar 10.22.2014
Audiences webinar 10.22.2014Audiences webinar 10.22.2014
Audiences webinar 10.22.2014
Optimizely
 
The Decision Table Template For Geospatial Business Rules
The Decision Table Template For Geospatial Business RulesThe Decision Table Template For Geospatial Business Rules
The Decision Table Template For Geospatial Business Rules
Jacob Feldman
 
Testing begins with requirements - Presentation to BCS SIGiST jun15
Testing begins with requirements - Presentation to BCS SIGiST jun15Testing begins with requirements - Presentation to BCS SIGiST jun15
Testing begins with requirements - Presentation to BCS SIGiST jun15
Paul Vincent
 
Practical Techniques for Resolving Conflicts among Business Rules
Practical Techniques for Resolving Conflicts among Business RulesPractical Techniques for Resolving Conflicts among Business Rules
Practical Techniques for Resolving Conflicts among Business Rules
Jacob Feldman
 
Impact 2012 1640 - BPM Design considerations when optimizing business process...
Impact 2012 1640 - BPM Design considerations when optimizing business process...Impact 2012 1640 - BPM Design considerations when optimizing business process...
Impact 2012 1640 - BPM Design considerations when optimizing business process...
Brian Petrini
 
A New Approach to Defining BI Requirements
A New Approach to Defining BI RequirementsA New Approach to Defining BI Requirements
A New Approach to Defining BI Requirements
Decision Management Solutions
 
User requirements for complex search strategies
User requirements for complex search strategiesUser requirements for complex search strategies
User requirements for complex search strategies
Tony Russell-Rose
 
Decision Management Fundamentals: Dutch Version
Decision Management Fundamentals: Dutch VersionDecision Management Fundamentals: Dutch Version
Decision Management Fundamentals: Dutch Version
Martijn Zoet
 
Feature Engineering on Forest Cover Type Data with Decision Trees
Feature Engineering on Forest Cover Type Data with Decision TreesFeature Engineering on Forest Cover Type Data with Decision Trees
Feature Engineering on Forest Cover Type Data with Decision Trees
Chandana T L
 
Next Steps In Your Digital Transformation
Next Steps In Your Digital TransformationNext Steps In Your Digital Transformation
Next Steps In Your Digital Transformation
VMware Tanzu
 
Role of Data in Digital Transformation
Role of Data in Digital TransformationRole of Data in Digital Transformation
Role of Data in Digital Transformation
VMware Tanzu
 
Getting started with decision discovery
Getting started with decision discoveryGetting started with decision discovery
Getting started with decision discovery
Decision Management Solutions
 

Viewers also liked (20)

Implementing a Successful, Scalable, Governed BI Program
Implementing a Successful, Scalable, Governed BI ProgramImplementing a Successful, Scalable, Governed BI Program
Implementing a Successful, Scalable, Governed BI Program
 
Integrating Business Rules and Business Processes
Integrating Business Rules and Business ProcessesIntegrating Business Rules and Business Processes
Integrating Business Rules and Business Processes
 
Analytics Teams: 5 Things You Need to Know Before You Deploy Your Model
Analytics Teams: 5 Things You Need to Know Before You Deploy Your ModelAnalytics Teams: 5 Things You Need to Know Before You Deploy Your Model
Analytics Teams: 5 Things You Need to Know Before You Deploy Your Model
 
The Value of Predictive Analytics and Decision Modeling
The Value of Predictive Analytics and Decision ModelingThe Value of Predictive Analytics and Decision Modeling
The Value of Predictive Analytics and Decision Modeling
 
Avola Decision Platform - Flyer ENG
Avola Decision Platform - Flyer ENGAvola Decision Platform - Flyer ENG
Avola Decision Platform - Flyer ENG
 
Automated loan processing
Automated loan processingAutomated loan processing
Automated loan processing
 
Transforming Business with Smarter Analytics
Transforming Business with Smarter AnalyticsTransforming Business with Smarter Analytics
Transforming Business with Smarter Analytics
 
Decision CAMP 2014 - James Taylor - Decision Management 101
Decision CAMP 2014 - James Taylor - Decision Management 101Decision CAMP 2014 - James Taylor - Decision Management 101
Decision CAMP 2014 - James Taylor - Decision Management 101
 
Audiences webinar 10.22.2014
Audiences webinar 10.22.2014Audiences webinar 10.22.2014
Audiences webinar 10.22.2014
 
The Decision Table Template For Geospatial Business Rules
The Decision Table Template For Geospatial Business RulesThe Decision Table Template For Geospatial Business Rules
The Decision Table Template For Geospatial Business Rules
 
Testing begins with requirements - Presentation to BCS SIGiST jun15
Testing begins with requirements - Presentation to BCS SIGiST jun15Testing begins with requirements - Presentation to BCS SIGiST jun15
Testing begins with requirements - Presentation to BCS SIGiST jun15
 
Practical Techniques for Resolving Conflicts among Business Rules
Practical Techniques for Resolving Conflicts among Business RulesPractical Techniques for Resolving Conflicts among Business Rules
Practical Techniques for Resolving Conflicts among Business Rules
 
Impact 2012 1640 - BPM Design considerations when optimizing business process...
Impact 2012 1640 - BPM Design considerations when optimizing business process...Impact 2012 1640 - BPM Design considerations when optimizing business process...
Impact 2012 1640 - BPM Design considerations when optimizing business process...
 
A New Approach to Defining BI Requirements
A New Approach to Defining BI RequirementsA New Approach to Defining BI Requirements
A New Approach to Defining BI Requirements
 
User requirements for complex search strategies
User requirements for complex search strategiesUser requirements for complex search strategies
User requirements for complex search strategies
 
Decision Management Fundamentals: Dutch Version
Decision Management Fundamentals: Dutch VersionDecision Management Fundamentals: Dutch Version
Decision Management Fundamentals: Dutch Version
 
Feature Engineering on Forest Cover Type Data with Decision Trees
Feature Engineering on Forest Cover Type Data with Decision TreesFeature Engineering on Forest Cover Type Data with Decision Trees
Feature Engineering on Forest Cover Type Data with Decision Trees
 
Next Steps In Your Digital Transformation
Next Steps In Your Digital TransformationNext Steps In Your Digital Transformation
Next Steps In Your Digital Transformation
 
Role of Data in Digital Transformation
Role of Data in Digital TransformationRole of Data in Digital Transformation
Role of Data in Digital Transformation
 
Getting started with decision discovery
Getting started with decision discoveryGetting started with decision discovery
Getting started with decision discovery
 

Similar to Implementing analytics? You need decision modeling and business rules

Accelerating Sourcing to Reduce Costs & Capture New Benefits
Accelerating Sourcing to Reduce Costs & Capture New BenefitsAccelerating Sourcing to Reduce Costs & Capture New Benefits
Accelerating Sourcing to Reduce Costs & Capture New Benefits
Atul Vashistha
 
3 Critical Elements of a Digital Business Platform
3 Critical Elements of a Digital Business Platform3 Critical Elements of a Digital Business Platform
3 Critical Elements of a Digital Business Platform
Decision Management Solutions
 
Putting Predictive Analytics To Work
Putting Predictive Analytics To WorkPutting Predictive Analytics To Work
Putting Predictive Analytics To Work
Decision Management Solutions
 
Creating a Business Case for Global Payroll - APA Fall Forum
Creating a Business Case for Global Payroll - APA Fall ForumCreating a Business Case for Global Payroll - APA Fall Forum
Creating a Business Case for Global Payroll - APA Fall Forum
Catriona Keevans
 
Delivering the Business Value of Analytics
Delivering the Business Value of Analytics Delivering the Business Value of Analytics
Delivering the Business Value of Analytics
Decision Management Solutions
 
Building a bullet proof business case
Building a bullet proof business caseBuilding a bullet proof business case
Building a bullet proof business case
Jonathan L'Ecuyer
 
Customer Decision Management - 5 Benefits
Customer Decision Management - 5 BenefitsCustomer Decision Management - 5 Benefits
Customer Decision Management - 5 Benefits
Decision Management Solutions
 
six-sigma2040.ppt
six-sigma2040.pptsix-sigma2040.ppt
six-sigma2040.ppt
OnurUyar6
 
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
Michelle Caldwell, PSM, SSGB
 
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptxSPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
Michelle Caldwell, PSM, SSGB
 
Creating a Business Case for Big Data
Creating a Business Case for Big DataCreating a Business Case for Big Data
Creating a Business Case for Big Data
Perficient, Inc.
 
Simplify BPM with Decision Management
Simplify BPM with Decision ManagementSimplify BPM with Decision Management
Simplify BPM with Decision Management
Decision Management Solutions
 
3 Secrets to Becoming a Predictive Enterprise
3 Secrets to Becoming a Predictive Enterprise3 Secrets to Becoming a Predictive Enterprise
3 Secrets to Becoming a Predictive Enterprise
Decision Management Solutions
 
Importance of decisions OMG
Importance of decisions OMGImportance of decisions OMG
Importance of decisions OMG
Decision Management Solutions
 
Decision analytics: More than BI and Web Analytics
Decision analytics: More than BI and Web AnalyticsDecision analytics: More than BI and Web Analytics
Decision analytics: More than BI and Web Analytics
Decision Management Solutions
 
5 tips als je nu wilt starten met digital marketing analytics
5 tips als je nu wilt starten met digital marketing analytics5 tips als je nu wilt starten met digital marketing analytics
5 tips als je nu wilt starten met digital marketing analytics
Avanade Nederland
 
6 sigma what is it
6 sigma what is it6 sigma what is it
6 sigma what is it
Kingsley Nwagu
 
Upmc tpdev6
Upmc tpdev6Upmc tpdev6
Upmc tpdev6
Jean-Yves Rigolet
 
What is analytics
What is analyticsWhat is analytics
What is analytics
shweta saxena
 
Business Intelligence Industry Perspective Session I
Business Intelligence   Industry Perspective Session IBusiness Intelligence   Industry Perspective Session I
Business Intelligence Industry Perspective Session I
Prithwis Mukerjee
 

Similar to Implementing analytics? You need decision modeling and business rules (20)

Accelerating Sourcing to Reduce Costs & Capture New Benefits
Accelerating Sourcing to Reduce Costs & Capture New BenefitsAccelerating Sourcing to Reduce Costs & Capture New Benefits
Accelerating Sourcing to Reduce Costs & Capture New Benefits
 
3 Critical Elements of a Digital Business Platform
3 Critical Elements of a Digital Business Platform3 Critical Elements of a Digital Business Platform
3 Critical Elements of a Digital Business Platform
 
Putting Predictive Analytics To Work
Putting Predictive Analytics To WorkPutting Predictive Analytics To Work
Putting Predictive Analytics To Work
 
Creating a Business Case for Global Payroll - APA Fall Forum
Creating a Business Case for Global Payroll - APA Fall ForumCreating a Business Case for Global Payroll - APA Fall Forum
Creating a Business Case for Global Payroll - APA Fall Forum
 
Delivering the Business Value of Analytics
Delivering the Business Value of Analytics Delivering the Business Value of Analytics
Delivering the Business Value of Analytics
 
Building a bullet proof business case
Building a bullet proof business caseBuilding a bullet proof business case
Building a bullet proof business case
 
Customer Decision Management - 5 Benefits
Customer Decision Management - 5 BenefitsCustomer Decision Management - 5 Benefits
Customer Decision Management - 5 Benefits
 
six-sigma2040.ppt
six-sigma2040.pptsix-sigma2040.ppt
six-sigma2040.ppt
 
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
Planning Your Digital Workplace Transformation SharePoint Fest Denver 2017
 
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptxSPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
SPT200-Planning Your Digital Workplace Transformation-DenverFest-2017.pptx
 
Creating a Business Case for Big Data
Creating a Business Case for Big DataCreating a Business Case for Big Data
Creating a Business Case for Big Data
 
Simplify BPM with Decision Management
Simplify BPM with Decision ManagementSimplify BPM with Decision Management
Simplify BPM with Decision Management
 
3 Secrets to Becoming a Predictive Enterprise
3 Secrets to Becoming a Predictive Enterprise3 Secrets to Becoming a Predictive Enterprise
3 Secrets to Becoming a Predictive Enterprise
 
Importance of decisions OMG
Importance of decisions OMGImportance of decisions OMG
Importance of decisions OMG
 
Decision analytics: More than BI and Web Analytics
Decision analytics: More than BI and Web AnalyticsDecision analytics: More than BI and Web Analytics
Decision analytics: More than BI and Web Analytics
 
5 tips als je nu wilt starten met digital marketing analytics
5 tips als je nu wilt starten met digital marketing analytics5 tips als je nu wilt starten met digital marketing analytics
5 tips als je nu wilt starten met digital marketing analytics
 
6 sigma what is it
6 sigma what is it6 sigma what is it
6 sigma what is it
 
Upmc tpdev6
Upmc tpdev6Upmc tpdev6
Upmc tpdev6
 
What is analytics
What is analyticsWhat is analytics
What is analytics
 
Business Intelligence Industry Perspective Session I
Business Intelligence   Industry Perspective Session IBusiness Intelligence   Industry Perspective Session I
Business Intelligence Industry Perspective Session I
 

More from Decision Management Solutions

Customer digitaldecisioningfinal
Customer digitaldecisioningfinalCustomer digitaldecisioningfinal
Customer digitaldecisioningfinal
Decision Management Solutions
 
Introduction to Digital Decisioning
Introduction to Digital DecisioningIntroduction to Digital Decisioning
Introduction to Digital Decisioning
Decision Management Solutions
 
Introduction to Digital Decisioning
Introduction to Digital DecisioningIntroduction to Digital Decisioning
Introduction to Digital Decisioning
Decision Management Solutions
 
Increasing Productivity in Insurance Operations with Digital Decisioning
Increasing Productivity in Insurance Operations with Digital DecisioningIncreasing Productivity in Insurance Operations with Digital Decisioning
Increasing Productivity in Insurance Operations with Digital Decisioning
Decision Management Solutions
 
Backward Engineering: Plan Machine Learning Deployment in Reverse
Backward Engineering: Plan Machine Learning Deployment in ReverseBackward Engineering: Plan Machine Learning Deployment in Reverse
Backward Engineering: Plan Machine Learning Deployment in Reverse
Decision Management Solutions
 
Five Reasons to Fire Your Rules Consultant
Five Reasons to Fire Your Rules ConsultantFive Reasons to Fire Your Rules Consultant
Five Reasons to Fire Your Rules Consultant
Decision Management Solutions
 
What is a claims handling pilot?
What is a claims handling pilot?What is a claims handling pilot?
What is a claims handling pilot?
Decision Management Solutions
 
Simplifying Complex Processes with Decision Management
Simplifying Complex Processes with Decision ManagementSimplifying Complex Processes with Decision Management
Simplifying Complex Processes with Decision Management
Decision Management Solutions
 
The role of decision models in analytic excellence
The role of decision models in analytic excellenceThe role of decision models in analytic excellence
The role of decision models in analytic excellence
Decision Management Solutions
 
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World ExperienceMind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Decision Management Solutions
 
Bringing clarity to analytics projects with decision modeling: a leading prac...
Bringing clarity to analytics projects with decision modeling: a leading prac...Bringing clarity to analytics projects with decision modeling: a leading prac...
Bringing clarity to analytics projects with decision modeling: a leading prac...
Decision Management Solutions
 
3 Reasons to Adopt Decision Modeling in your BRMS Program
3 Reasons to Adopt Decision Modeling in your BRMS Program3 Reasons to Adopt Decision Modeling in your BRMS Program
3 Reasons to Adopt Decision Modeling in your BRMS Program
Decision Management Solutions
 
4 Reasons to Start with Decision Modeling on Your First BRMS Project
4 Reasons to Start with Decision Modeling on Your First BRMS Project4 Reasons to Start with Decision Modeling on Your First BRMS Project
4 Reasons to Start with Decision Modeling on Your First BRMS Project
Decision Management Solutions
 
DecisionsFrst Modeler and Red Hat JBoss BRMS
DecisionsFrst Modeler and Red Hat JBoss BRMSDecisionsFrst Modeler and Red Hat JBoss BRMS
DecisionsFrst Modeler and Red Hat JBoss BRMS
Decision Management Solutions
 
DecisionsFirst Modeler and IBM ODM Demonstration
DecisionsFirst Modeler and IBM ODM Demonstration DecisionsFirst Modeler and IBM ODM Demonstration
DecisionsFirst Modeler and IBM ODM Demonstration
Decision Management Solutions
 
How to Innovate Risk Management and Customer Centricity
How to Innovate Risk Management and Customer CentricityHow to Innovate Risk Management and Customer Centricity
How to Innovate Risk Management and Customer Centricity
Decision Management Solutions
 
Lessons Learned from the Real-life Deployment of Decision Management at Scale
Lessons Learned from the Real-life Deployment of Decision Management at ScaleLessons Learned from the Real-life Deployment of Decision Management at Scale
Lessons Learned from the Real-life Deployment of Decision Management at Scale
Decision Management Solutions
 
Extending Business Architecture with Regulatory Architecture using Decisions ...
Extending Business Architecture with Regulatory Architecture using Decisions ...Extending Business Architecture with Regulatory Architecture using Decisions ...
Extending Business Architecture with Regulatory Architecture using Decisions ...
Decision Management Solutions
 
Good Old UServ Product Derby in the Brave New World of Decision Management
Good Old UServ Product Derby in the Brave New World of Decision Management Good Old UServ Product Derby in the Brave New World of Decision Management
Good Old UServ Product Derby in the Brave New World of Decision Management
Decision Management Solutions
 
How to succeed with advanced analytics at scale
How to succeed with advanced analytics at scaleHow to succeed with advanced analytics at scale
How to succeed with advanced analytics at scale
Decision Management Solutions
 

More from Decision Management Solutions (20)

Customer digitaldecisioningfinal
Customer digitaldecisioningfinalCustomer digitaldecisioningfinal
Customer digitaldecisioningfinal
 
Introduction to Digital Decisioning
Introduction to Digital DecisioningIntroduction to Digital Decisioning
Introduction to Digital Decisioning
 
Introduction to Digital Decisioning
Introduction to Digital DecisioningIntroduction to Digital Decisioning
Introduction to Digital Decisioning
 
Increasing Productivity in Insurance Operations with Digital Decisioning
Increasing Productivity in Insurance Operations with Digital DecisioningIncreasing Productivity in Insurance Operations with Digital Decisioning
Increasing Productivity in Insurance Operations with Digital Decisioning
 
Backward Engineering: Plan Machine Learning Deployment in Reverse
Backward Engineering: Plan Machine Learning Deployment in ReverseBackward Engineering: Plan Machine Learning Deployment in Reverse
Backward Engineering: Plan Machine Learning Deployment in Reverse
 
Five Reasons to Fire Your Rules Consultant
Five Reasons to Fire Your Rules ConsultantFive Reasons to Fire Your Rules Consultant
Five Reasons to Fire Your Rules Consultant
 
What is a claims handling pilot?
What is a claims handling pilot?What is a claims handling pilot?
What is a claims handling pilot?
 
Simplifying Complex Processes with Decision Management
Simplifying Complex Processes with Decision ManagementSimplifying Complex Processes with Decision Management
Simplifying Complex Processes with Decision Management
 
The role of decision models in analytic excellence
The role of decision models in analytic excellenceThe role of decision models in analytic excellence
The role of decision models in analytic excellence
 
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World ExperienceMind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
Mind The Gap - Refinements to DMN 1.1 Suggested by Real-World Experience
 
Bringing clarity to analytics projects with decision modeling: a leading prac...
Bringing clarity to analytics projects with decision modeling: a leading prac...Bringing clarity to analytics projects with decision modeling: a leading prac...
Bringing clarity to analytics projects with decision modeling: a leading prac...
 
3 Reasons to Adopt Decision Modeling in your BRMS Program
3 Reasons to Adopt Decision Modeling in your BRMS Program3 Reasons to Adopt Decision Modeling in your BRMS Program
3 Reasons to Adopt Decision Modeling in your BRMS Program
 
4 Reasons to Start with Decision Modeling on Your First BRMS Project
4 Reasons to Start with Decision Modeling on Your First BRMS Project4 Reasons to Start with Decision Modeling on Your First BRMS Project
4 Reasons to Start with Decision Modeling on Your First BRMS Project
 
DecisionsFrst Modeler and Red Hat JBoss BRMS
DecisionsFrst Modeler and Red Hat JBoss BRMSDecisionsFrst Modeler and Red Hat JBoss BRMS
DecisionsFrst Modeler and Red Hat JBoss BRMS
 
DecisionsFirst Modeler and IBM ODM Demonstration
DecisionsFirst Modeler and IBM ODM Demonstration DecisionsFirst Modeler and IBM ODM Demonstration
DecisionsFirst Modeler and IBM ODM Demonstration
 
How to Innovate Risk Management and Customer Centricity
How to Innovate Risk Management and Customer CentricityHow to Innovate Risk Management and Customer Centricity
How to Innovate Risk Management and Customer Centricity
 
Lessons Learned from the Real-life Deployment of Decision Management at Scale
Lessons Learned from the Real-life Deployment of Decision Management at ScaleLessons Learned from the Real-life Deployment of Decision Management at Scale
Lessons Learned from the Real-life Deployment of Decision Management at Scale
 
Extending Business Architecture with Regulatory Architecture using Decisions ...
Extending Business Architecture with Regulatory Architecture using Decisions ...Extending Business Architecture with Regulatory Architecture using Decisions ...
Extending Business Architecture with Regulatory Architecture using Decisions ...
 
Good Old UServ Product Derby in the Brave New World of Decision Management
Good Old UServ Product Derby in the Brave New World of Decision Management Good Old UServ Product Derby in the Brave New World of Decision Management
Good Old UServ Product Derby in the Brave New World of Decision Management
 
How to succeed with advanced analytics at scale
How to succeed with advanced analytics at scaleHow to succeed with advanced analytics at scale
How to succeed with advanced analytics at scale
 

Recently uploaded

Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Pitangent Analytics & Technology Solutions Pvt. Ltd
 
A Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's ArchitectureA Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's Architecture
ScyllaDB
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
saastr
 
Demystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through StorytellingDemystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through Storytelling
Enterprise Knowledge
 
Christine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptxChristine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptx
christinelarrosa
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
Edge AI and Vision Alliance
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
Jason Packer
 
Y-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PPY-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PP
c5vrf27qcz
 
What is an RPA CoE? Session 1 – CoE Vision
What is an RPA CoE?  Session 1 – CoE VisionWhat is an RPA CoE?  Session 1 – CoE Vision
What is an RPA CoE? Session 1 – CoE Vision
DianaGray10
 
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
"Scaling RAG Applications to serve millions of users",  Kevin Goedecke"Scaling RAG Applications to serve millions of users",  Kevin Goedecke
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
Fwdays
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
Ajin Abraham
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
Hiroshi SHIBATA
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
DianaGray10
 
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
Chart Kalyan
 
Leveraging the Graph for Clinical Trials and Standards
Leveraging the Graph for Clinical Trials and StandardsLeveraging the Graph for Clinical Trials and Standards
Leveraging the Graph for Clinical Trials and Standards
Neo4j
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
Antonios Katsarakis
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
DanBrown980551
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
akankshawande
 
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge GraphGraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
Neo4j
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
Tatiana Kojar
 

Recently uploaded (20)

Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
Crafting Excellence: A Comprehensive Guide to iOS Mobile App Development Serv...
 
A Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's ArchitectureA Deep Dive into ScyllaDB's Architecture
A Deep Dive into ScyllaDB's Architecture
 
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
9 CEO's who hit $100m ARR Share Their Top Growth Tactics Nathan Latka, Founde...
 
Demystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through StorytellingDemystifying Knowledge Management through Storytelling
Demystifying Knowledge Management through Storytelling
 
Christine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptxChristine's Supplier Sourcing Presentaion.pptx
Christine's Supplier Sourcing Presentaion.pptx
 
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
 
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays - June 2024
 
Y-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PPY-Combinator seed pitch deck template PP
Y-Combinator seed pitch deck template PP
 
What is an RPA CoE? Session 1 – CoE Vision
What is an RPA CoE?  Session 1 – CoE VisionWhat is an RPA CoE?  Session 1 – CoE Vision
What is an RPA CoE? Session 1 – CoE Vision
 
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
"Scaling RAG Applications to serve millions of users",  Kevin Goedecke"Scaling RAG Applications to serve millions of users",  Kevin Goedecke
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
 
AppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSFAppSec PNW: Android and iOS Application Security with MobSF
AppSec PNW: Android and iOS Application Security with MobSF
 
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS  at Code Europe 2024Introduction of Cybersecurity with OSS  at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
 
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsConnector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
 
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfHow to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
 
Leveraging the Graph for Clinical Trials and Standards
Leveraging the Graph for Clinical Trials and StandardsLeveraging the Graph for Clinical Trials and Standards
Leveraging the Graph for Clinical Trials and Standards
 
Dandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity serverDandelion Hashtable: beyond billion requests per second on a commodity server
Dandelion Hashtable: beyond billion requests per second on a commodity server
 
5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides5th LF Energy Power Grid Model Meet-up Slides
5th LF Energy Power Grid Model Meet-up Slides
 
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development ProvidersYour One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
 
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge GraphGraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph
 
Skybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoptionSkybuffer SAM4U tool for SAP license adoption
Skybuffer SAM4U tool for SAP license adoption
 

Implementing analytics? You need decision modeling and business rules

  • 2. 1 2 3 4 5 6 AGENDA The power of analytics Challenges in analytics Introducing business rules Integrating business rules and analytics Decision Management Wrap Up
  • 3. ©2009-2017 Decision Management Solutions 3 The one slide you need Analytics have great potential to improve day to day operations Challenges include Business value gap Engaging the business and IT Deployment A business rules management system (BRMS) is an ideal platform for analytics Decision Management ties analytics and business rules together in an effective decision model framework
  • 4. The power of analytics ©2009-2017 Decision Management Solutions4
  • 6. ©2009-2017 Decision Management Solutions 6 And that power is operational 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 just about “aha” moments It’s about making better operational decisions
  • 7. ©2009-2017 Decision Management Solutions 7 Operational Decisions Scale For Big Impact Strategic Decision Tactical Decision Operational Decision
  • 8. ©2009-2017 Decision Management Solutions 8 Case: Telco Example: Analytics enabling an individualized decision about the best plan/upgrade offer to make to each customer
  • 10. Knowing is not enough ©2009-2017 Decision Management Solutions 10 Those who know first, win Those who ACT first, win Provided they act intelligently
  • 11. Latency in decisions costs you ©2009-2017 Decision Management Solutions 11 Business event Action taken Decision latency
  • 12. Operational decisions are at the center Business ©2009-2017 Decision Management Solutions 12
  • 13. Monitoring and compliance matter ©2009-2017 Decision Management Solutions 13
  • 14. Analytics improves operations but… Power of analytics is in improving operations Specifically operational decisions Which means : Focus on actions not predictions Minimize the time to impact Engage analytics, IT, and business teams Handle monitoring and compliance ©2009-2017 Decision Management Solutions 14
  • 15. Case: Trade credit insurance New countries in weeks not months Ongoing changes in hours, not weeks Immediate changes in a crisis ©2009-2017 Decision Management Solutions 15
  • 17. What are business rules? “… a directive intended to influence behavior.” “… a formal expression of knowledge or preference, a guidance system for steering behavior (a transaction) in a desired direction.” “… statements of the actions you should take when certain business conditions are true.” ©2009-2017 Decision Management Solutions 17
  • 18. Business Rules are everywhere Experienced Personnel RegulationsPolicy Manuals Legacy Systems Historical Data ©2009-2017 Decision Management Solutions 18
  • 19. ©2009-2017 Decision Management Solutions 19 Business rules drive decisions Decision History Experience Policy Regulations Legacy Applications
  • 20. 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); } } } Unmanageable business rules ©2009-2017 Decision Management Solutions 20
  • 21. Decision Service A Business Rules Management System After Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.6 Design Tools Rule Management Applications Rule Engine Operational Database Rule Repository Production Application Validation and Verification Testing Deployment ©2009-2017 Decision Management Solutions 21
  • 22. Manageable business rules Smart (Enough) Systems, Prentice Hall June 2007. Fig 4.3 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=“email” 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” ©2009-2017 Decision Management Solutions 22
  • 23. ©2009-2017 Decision Management Solutions 23 Rule Sheets Set of rules that share common action(s) Sequence does not matter Typically exhaustive and exclusive Sometimes called a decision table, rule family Name Condition Attribute 1 Condition Attribute 2 Condition Attribute 3 Action Attribute 4 Rule 1 > 2 < 3 =6 Rule 2 <=2 >=3 =12 Rule 3 <=2 <3 True =13 Rule 4 <=2 <3 False =14 Rule 5 >2 >=3 True =10 Rule 6 >2 >=3 False =2
  • 24. ©2009-2017 Decision Management Solutions 24 Decision Table Set of rules that return a single result Look up tables, comparing attribute values Sequence does not matter Typically exhaustive and exclusive Attribute 2 Single Family with no children Family with children Attribute1 < 10 1 2 3 11 – 20 2 4 6 21 – 40 3 5 7 41 – 99 4 6 8 >= 100 5 6 9
  • 25. ©2009-2017 Decision Management Solutions 25 Decision Tree Set of rules that select a goal from a set Divides into increasingly fine grained groups Often a powerful thinking tool Typically exhaustive and exclusive Existing Customer? Long term customer? Grandfather Issue change Price quoted Retract quote Issue warning Y N Y N Y N
  • 26. ©2009-2017 Decision Management Solutions 26 A list of rules representing a rule set AdjustIncome RuleSet (newApplicant) Name: Six months or less on the job if newApplicant’s monthsInCurrentJob is less than or equal to 6 then decrement newApplicant’s income by 5600 Name: About 1 year if newApplication’s monthsInCurrentJob is between 6 and 13 then increment newApplicant’s income by 1000 Name: Greater than 1 year if newApplicant’s monthsInCurrentJob is greater than 12 then increment newApplicant’s income by 2500 Name: Computer Total Income if newApplicant is married and newApplicant’s spousalIncome is greater than 0 then newApplicant’s totalIncome is equal to newApplicant’s income plus newApplicant’s spousalIncome else newApplicant’s totalIncome is equal to newApplicant’s income Name: Minimum Income if newApplicant’s totalIncome is less than 40000 then newApplicant is not eligible Smart (Enough) Systems, Prentice Hall June 2007. Fig 6.3
  • 27. Why manage business rules Improve Decision Making • Clear policies and procedures • Consistently applied across channels, systems • Increased accuracy from business users participation Business Agility • More rapid response to business threats • Fewer missed opportunities • Faster time to market Reduce Costs • Fewer resources, less time to change decisions • Lower fines, legal costs from bad decisions • Reduced IT costs to implement decisions ©2009-2017 Decision Management Solutions 27
  • 28. Cross-channel coordination ensures that all relevant offers, including loyalty programs, are combined at the point of sale, with consistent pricing rules applied. ©2009-2017 Decision Management Solutions 28 Case: International retailer
  • 30. 30 Different kinds of analytics Data Mining Who are my best/worst customers? How do I turn my data into rules for better decisions? Predictive Analytics How are those customers likely to behave in the future? How do they react to the myriad ways I can “touch” them? Knowledge - Description Action - Prescription Business Intelligence How do I use data to learn about my customers?What has been happening in my business? ©2009-2017 Decision Management Solutions * * * * **** ** * * ** * * * * * * * * * * * * * * * * * * * * ** * * ** * * *** * * * ** *** **
  • 31. * * * * **** ** * * ** * * * * * * * * * * * * * * * * * * * * ** * * ** * * *** * * * ** *** ** Your data is a source of insight ©2009-2017 Decision Management Solutions 31
  • 32. * * * * **** ** * * ** * * * * * * * * * * * * * * * * * * * * ** * * ** * * *** * * * ** *** ** Insight as presentation is disconnected ©2009-2017 Decision Management Solutions 32 ?
  • 33. * * * * **** ** * * ** * * * * * * * * * * * * * * * * * * * * ** * * ** * * *** * * * ** *** ** Insights as decisions drive action ©2009-2017 Decision Management Solutions 33
  • 34. Existing Customer? Long term customer? Grandfather Issue change Price quoted Retract quote Issue warning * * * * * * * * ** * * ** * * * * * * * * * * * * * * * * * * * * ** * * * * * * * * * * * * * * * ** ** Low-moderate income, young High Income High income, low-moderate education Moderate-high education low-moderate income High Moderate education, low income, middle-aged Low education, low income Education High Descriptive analytics ©2009-2017 Decision Management Solutions 34
  • 35. Predictive analytics Attribute 2 Single Family with no children Family with children Attribute1 < 10 1 2 3 11 – 20 2 4 6 21 – 40 3 5 7 41 – 99 4 6 8 >= 100 5 6 9 ©2009-2017 Decision Management Solutions 35
  • 36. Scorecards are a powerful tool Years Under Contract 1 0 2 5 More than 2 10 Number of Contract Changes 0 0 1 5 More than 1 10 Value Rating of Current Plan Poor 0 Good 10 Excellent 20 Score Smart (Enough) Systems, Prentice Hall June 2007. Fig 5.4 30 ©2009-2017 Decision Management Solutions 36
  • 37. Building Decision Services Smart (Enough) Systems, Prentice Hall June 2007. Fig 5.1 Production ProcessData Warehouse Operational Data Store Business Rules Business Analytics Decision Service Enterprise IT Infrastructure Adaptive Control Events ©2009-2017 Decision Management Solutions 37
  • 38. Case: Underwriting Manual reviews Control Business focus Risk 8 Point Reduction in Combined Ratio ©2009-2017 Decision Management Solutions 38
  • 40. Decision Management Ties analytics and business rules together in an effective decision model framework Models decision-making (DMN standard) Integrates with execution environment Builds on existing enterprise architecture ©2009-2017 Decision Management Solutions 40
  • 41. ©2009-2017 Decision Management Solutions 41 Delivering Decision Management 3 stages to better operational decisions Identify the decisions (usually about customers) that are most important to your operational success Design and build independent decision services to replace decision points embedded in operational systems Create a “closed loop” between operations and analytics to measure results and drive improvement
  • 42. Case: State dept of taxation Business challenges Solution Benefits Paper tax returns increased costs and slowed responses Information system silos Manual fraud detection and return review Single central taxpayer database Integrated system Sophisticated real- time predictive analytics Recovered millions of dollars from dubious tax returns Increased collection of unpaid taxes Decreased number of questionable returns Increased customer satisfaction ©2009-2017 Decision Management Solutions 42
  • 43. Implementing Analytics Gets Results Actions not predictions Minimum time to impact Engage IT, Business Handle monitoring , compliance Decision Management ties analytics and business rules together in an effective decision model framework ©2009-2017 Decision Management Solutions 43
  • 45. ©2009-2017 Decision Management Solutions 45 The one slide you need Analytics have great potential to improve day to day operations Challenges include Business value gap Engaging the business and IT Deployment A business rules management system (BRMS) is an ideal platform for analytics Decision Management ties analytics and business rules together in an effective decision model framework
  • 46. ©2009-2017 Decision Management Solutions 46 Action Plan Identify your decisions before analytics Adopt business rules to implement analytics Bring business, analytic and IT people together
  • 47. Decision Management Solutions Decision Management Solutions can help you Focus on the right decisions Implement a blueprint Define a strategy Learn more: Contact Us www.decisionmanagementsolutions.com info@decisionmanagementsolutions.com ©2009-2017 Decision Management Solutions 47
  • 48. Thank you! James Taylor, CEO james@decisionmanagementsolutions.com www.decisionmangementsolutions.com

Editor's Notes

  1. Putting business analytics to work is top of mind for organizations like yours. Business agility and operational responsiveness are more important than ever. There is a real opportunity to use analytics – especially predictive analytics – to seek out increasingly small margins and understand your customers, products, channels, partners and more. But predictive analytics is only part of the solution – you must put these analytic insights to work making better decisions every day. Business rules offer the agile, business-centric platform you need to manage decisions and effectively deploy predictive analytics. Putting them together requires a new conceptual framework – Decision Management.
  2. Applying analytics to acquire, retain and grow 100M customersBusiness challenge:100M customers and 3Bn calls / day200TB of customer information1.3M Retail partnersRural and urban consumers, large and small companiesSolution:Integrated data warehouse across all channels, all productsReal-time analytics for micro-segmentation, offer targetingWeb, retail, call-center and mobile channelsBenefits:Rapid growth with 2-3M new customers/monthGrowing and accelerating Revenue Market Share
  3. Models make predictions but predictions alone will not help much – you must ACT based on those predictions.When you are thinking about smarter systems, taking action means having the system take action in a way that uses the predictions you made. You need to make a decision based on those predictions and this means combining the models with rules about how and when to act.Let’s take our retention example from earlier. Knowing that a customer is a retention risk is interesting, acting appropriately and in time to prevent them leaving is usefulGrovel index story
  4. Remember – decisions are where the business, analytics and IT all come together
  5. Once deployed analytics cannot be a “black box”, we must understand analytic performanceObviously you need a &apos;hold out sample&apos; or business as usual random group to compare to.You need to understand what&apos;s working and what&apos;s the next challenge – which segments are being retained, for instanceYou must understand operational negation.You need to track input variables, scores, decisions or actions taken (classic example is in collections where a strategy may dictate a &apos;do nothing&apos; strategy, but the collections manager overrides the decision and puts the accounts into a calling queue) and operational data that fed the decisionBoth analysts and business users must think about what they can do to improve decision making, which is the foundation of adaptive controlIn our retention example I need to have some customers I don’t attempt to retain or that I don’t spend any money retaining. I have to capture what the call center representative ACTUALLY offered and what was actually accepted (if anything), not just what SHOULD have been offered and I have to be able to show the results to my business users in terms they understand.
  6. Actions not predictions - Business rules add actions to analytic insightTime to impact - Externalized decisions, rapid deploymentBusiness results - Decisions impact KPIs, implement strategyEngage IT, Business - Rules for the business, Decision services for ITMonitoring , compliance - Rules and explicit models expose decision making
  7. Sometimes the ROI is discussed in terms of keeping a company in business, eliminating those company killing risks.This company offered trade credit insurance and a decision service provides trade credit calculations, combining business rules and algorithms developed by using predictive analytic techniques. Business experts interact directly with trade credit rules by using rule templates to ensure that rules match the underlying object model, without business users having to understand the object model’s technicalities.They got some classic BRE ROI:A country can be added in a few weeks rather than months, so the organization went from 2 to 16 covered countries in just 3 months.Ongoing changes can be made in hours rather than weeks.Most importantly though the system allows immediate changes to rules in a crisis, preventing the possibility of liability or other legal exposure for the organization.
  8. So making decisions correctly will be hard unless we can pull all these rules together.Given this is how rules often look to start with, this is clearly going to be hard.But rules also change…Because your business policies doBecause your competitors doBecause the law doesBecause stock levels doBecause your services and products doBecause your customers doBecause your customers’ needs doSo we need something that will let us collect, manage and update the business rules that drive our decisions
  9. The most basic representation is a list of rules or a rule set. These are simple atomic rules grouped into a logical set for execution and storage. Rule sets are often shared between decisions.
  10. A big part of the benefit companies get from managing rules comes from putting the business in charge more directly. Having business users manage business rules reduces costs by eliminating a step – that of having the business tell IT what they want so that IT can do code it – and improves accuracy by eliminating the impedance of this step. It also increases business agility by making it easier for a company to respond to changes – after all the business folks notice the changes firstIn my experience, the use of business rules and a BRMS to manage high-volume, operational decisions have a proven track record in reducing application development costs and application maintenance. It takes fewer developers and less time to specify how a system or service should behave using a BRMS thanks to the increased expressive power of business rules and the improved verification and testing offered by BRMS. Maintenance of these rules is easier, often dramatically easier, than the maintenance of the equivalent code. Not only are can the business rules be changed independently and safely; business users can participate directly in the maintenance process for the first time. Domain expertise is applied more directly and less time and money are spent making changes.
  11. Faster, easier, independent changes to decision logic Coordination of decisions across channels and products Higher employee productivity and resource utilization a leading French retailer of cosmetics, faced the challenge of multiple channels and overlapping marketing and loyalty offers. A customer might be eligible for a loyalty offer, have downloaded a web coupon and heard a “discount word” on the radio. This made it hard for retail staff to ensure the price was handled correctly at the point of sale. In addition, they needed a better way to get loyalty offers to the customer. Yves Rocher replaced their POS devices with Linux-based terminals and developed a rules-based system that allowed all the pricing rules to be defined by the marketing department and then downloaded into the terminals. All relevant offers are correctly combined at the point of sale. This system also takes the customer’s loyalty card and applies loyalty offers. Using purchases and loyalty history, it prints an incentive offer designed to bring the customer back to the store on the card itself—the cards are re-printable so the customer sees the offer that will be made when they return.
  12. the classic sources of rules – policies, regulations, best practices, expertise. Many, most, of your rules will come from these sources. But your data is also rich source of rulesYou can analyze the data you have to find exactly which thresholds you should use in your rules – is it really customers above 21 years old or would 20 or 19 be a more meaningful cut off?You can use data mining techniques to actually find the rules – association rules such as if someone is buying this product try and sell them that product or segmentation rules – using your historical data to find out what were the most successful rules in the pastYou can use this historical data to create new insights into customers – predicting things about them that extend the data you can work with and against which you can write rules.
  13. Descriptive analytics can be used to categorize customers into different categories – to find the relationships between customers - which can be useful in setting strategies and targeting treatment. But this analysis must be delivered not just to your analysts, also to your systems. Analysis is generally done offline, but the results can be used in automated decisions – such as offering a given product to a specific customer – often by developing rules that embody the analytics.For instance a decision tree can be created where each branch, each end node, identifies the segment for a particular member.Data mining can also create rules with less effort and with a quicker time to market in certain circumstances
  14. Predictive analytics often rank-order individuals. For example, rank-order members by their likelihood of renewing – the higher the score, the more “completers” for every “non-completer”. The risk or opportunity is assessed in the context of a single customer or transaction and these models are not an overall pattern, even if they are predictive. Models are called by a business rules engine to “score” an individual or transaction, often in real time, though the analysis is done offline.These models are often represented by a scorecard where each characteristic of a member adds to the score and where the total score can then be returned.
  15. All these pieces contribute to ever-more sophisticated decision services that support your business processes.Decision Services externalize and manage the decisions production processes and systems needBusiness rules allow business users to collaborate in the declarative definition of decisionsAnalytics can create better more data-driven business rulesAnd ultimately additional predictive analyticsAdaptive control allows test and learn to become part of a continuous improvement loop
  16. Here’s another example, this time of an insurance company with about 750,000 policies that implemented a risk-based underwriting decision service for use across its systems. In the first year an eight-point reduction in combined ratio – a big deal for an insurance companyThey got this improvement from all the areas I see when clients apply decision managementThey reduced costs by eliminating many manual reviews and by putting underwriters and actuaries in charge of the rules behind the decision – they eliminated or reduced many of their IT costs.They boosted revenue, the second major area, by improving risk management (far more tiers and more fine grained decisioning) and by focusing their staff on the book of business and helping agents improve it rather than on transactional approvalsThe third area does not show up in the specifics but when I talked to them it was clearly the most powerful aspect of the whole thing. They gained true strategic control over their underwriting decisions.
  17. Actions not predictions - Business rules add actions to analytic insightTime to impact - Externalized decisions, rapid deploymentBusiness results - Decisions impact KPIs, implement strategyEngage IT, Business - Rules for the business, Decision services for ITMonitoring , compliance - Rules and explicit models expose decision making
  18. Little decisions add up so focus on operational or front-line decision makingThe purpose of information is to decide so put your data and analytics to workYou cannot afford to lock up your logic so externalize it as business rulesNo answer, no matter how good, is static so experiment, challenge, simulate, learnDecision Making is a process to be managed
  19. Begin!Identify your decisionsHidden decisions, transactional decisions, customer decisionsDecisions buried in complex processesDecisions that are the difference between two processesConsiderWho takes them nowWhat drives changes in themAssess Change ReadinessConsider Organizational changeAdopt decisioning technologyAdopt business rules approach and technologyInvestigate data mining and predictive analyticsThink about adaptive control
  20. Decision Management Solutions can help youFind the right decisions to apply business rules, analyticsImplement a decision management blueprintDefine a strategy for business rule or analytic adoptionYou are welcome to email me directly, james at decision management solutions.com or you can go to decision management solutions.com / learn more. There you’ll find links to contact me, check out the blog and find more resources for learning about Decision Management.