ANALYTICS FOR ENABLING BUSINESS STRATEGY
PROFESSOR CATHAL BRUGHA, M.B.A, PH.D., FMII
FOUNDER DIRECTOR OF THE ANALYTICS INSTITUTE
PRESIDENT OF THE ANALYTICS SOCIETY OF IRELAND
WHO DO ANALYTICS? TECHI-ANALYSTS
DISTINCT: PARTNERS IN THE PRACTICE OF ANALYTICS
Assessing the Viability of using Open Source Tools
for Marketing Analytics –
Niamh Carroll and Paul Jones, 2008 -2009
 Decision Support System for Credit-Scoring –
Michael Wilson and Simon Shortt: 2009 -2010
 Application of Network Analysis in Insurance Data Sets
in order to highlight potentially Fraudulent Claims Cliona Fleming and Colman Horgan, 2010-2011
 Improving the Accuracy and Efficiency of Predictive
Modelling in Classification and Regression Trees –
Eoin Fitzpatrick and Ciarán Tobin: 2011-2012

Types of Analytics
Quant Approach
Applications
Qual Approach
DECISION ANALYTICS : THEORY BUILT ON PRACTICE

Development of a Muti-Criteria Decision Support System
for Early Diagnosis of Dementia in the Elderly

A Multi-Criteria Approach to the Construction of Team
Performance Indicators in Professional Rugby Union

Cultural Comparisons Between China and Ireland

Reform of the Culture in the Public Service
DEVELOPMENT OF A MUTI-CRITERIA DECISION SUPPORT
SYSTEM FOR EARLY DIAGNOSIS OF
DEMENTIA IN THE ELDERLY
Apostolos Tsakmakis and Muhammad K Hafeez
 Dr. Radu Marinescu and Dr. Léa A Deleris IBM Ireland Research Laboratory
 Professor Mary McCarron –
Dean of the Faculty of Health Sciences,
 Dr Kate Irving - Nursing and Human Sciences
 Dr Allys Guerandel - Integrating E-learning with
Psychiatry teaching,
 Dr. Aurelia Ciblis –
UCD School of Medicine and Medical Science
 Dr. Abdul Rauf - GP in Kilkenny (Software Test)

WHAT IS DEMENTIA?

Definition:
Dementia is the term used to describe a collection of symptoms
caused due to the loss of cognition, behavioural changes and a
decline in social activities in the elderly

Dementia of Alzheimer’s type (AD)
 Mostly in Elderly people age > 60


More than 50% of Dementia in elderly is of AD
41,000 dementia patients and number will be more than 100,000 by 2036
DIAGNOSIS OF DEMENTIA

American Psychiatric Association Diagnostic and
Statistical Manual of Mental Disorders (DSM-IV)

The World Health Organization's International
Classification of Diseases (ICD)
IMPORTANCE OF EARLY DIAGNOSIS
Misdiagnosed/late diagnosis by GPs (35% responsibility)
 Disease can be Managed
 Improved Quality of Life
 Less stress for Family members
 Fewer Patients requiring specialized help
 Fewer referrals to Memory Clinics

Symptoms (Criteria) for Dementia
PSYCHOMOTOR
ACTIVITIES
Memory
Impairment
Sleep
Disturbances
Language
disturbance
Patient’s
Medical History
Personal Care
Orientation
Attention/Thinking/Conciousness
Social Activities/hobbies
Physical Exam
Mood/Behaviour
Instrumental
Activities of
daily living
MOST COMMON DISEASES WITH THE SAME SYMPTOMS
Depression
 Delirium

DEMENTIA DIAGNOSIS A MULTI-CRITERIA DECISIONMAKING (MCDM) PROBLEM

Multiple Diagnostic Criteria

Conflicting Alternatives
STRUCTURING THE CRITERIA TREE
Self

Self
Others
World
Physical
Psychological
Social
Psychomotor

activities
Others

Physical Exam

Medical History

Memory

Personal care
Impairment

IADL
Language

Mood/Behaviour

Social Activities
Disturbance
World

Sleep patterns

Orientation

Attention/thinking/
consciousness
IADL: Instrumental Activities of Daily Living
Convince me they have Dementia: how they relate to Self, Others, the World (structure)
DIAGNOSTIC GUIDELINES
Depression
Criteria
Delirium (DEL)
Dementia (DEM)
(DEP)
Mild
Moderate
Severe
Noticeable
Hypoactive disturbance
Large
No
disturbance
(retardation)
in
movement.
in movement
Movement
Retardation:
Decreased
More
Psychomotor
Prolonged
Activities
restlessness,
Slightly
Hyperactive
little risk
no control in
behaviour,
psychomotor
considerable
activity,
intense
highly
reactions
intense
restless,
occasional
(agitation)
little risk
behaviour
reactions
motivation
Apraxia: Psychomotor
changes
characteristically
Agitation:
agitated
depression
occurring late in the
illness
CRITERIA WEIGHTS AND SCORING OF ALTERNATIVES

Imprecise Weights
User is not able to provide a specific importance to one symptom over another.

Verbal Scale

Direct-interactive Structured-Criteria (DISC ) System

Utility Scoring (DISCUS) System

Relative Intensity Measurement (DISCRIM) System
DECISION SUPPORT SYSTEM (DSS) REQUIREMENTS
User friendly interface
 Efficient scoring process
 Accessibility to historical data
 Data protection
 Flexibility
 Integration with other DSS

MCDM IMPLEMENTATION SOFTWARE
Imprecise input requirements
 Additional software requirements (EXCEL)
 User friendliness
 Generic approach

PROTOTYPE SOFTWARE
 Stand-alone
Java based application
 Software Implementation for MCDM model
 Handles Imprecise Inputs
 Data Protection
 Provides functionality for further analysis
CONTRIBUTION TO BUSINESS & SOCIETY
Early Diagnosis can reduce the cost of Dementia care
(approx €442/person in late stages).
 The quality of life of the Person with Dementia can be
improved through therapies in the early stages.
 Reduced number of misdiagnosed patient referrals to
Memory Clinics
 Improved quality of life for Dementia patients
 Correct early clinical diagnosis with no Dementia can
reduce extra cost (MRI, Brain scans etc.)

ACADEMIC CONTRIBUTION
Structuring DSM IV using MCDM
 Imprecise inputs for MCDM model
 Structured criteria combined with diagnostic guidelines
matrix can be used for improvement of dementia
training for GPs

A MULTI-CRITERIA APPROACH TO THE
CONSTRUCTION OF TEAM PERFORMANCE INDICATORS
IN PROFESSIONAL RUGBY UNION
Alan Freeman and Declan Treanor
Opta Sports
CURRENT RUGBY UNION & TEAM PERFORMANCE METRICS
•
•
Current methods used to objectively depict team
performance leave it up to the expert user to make sense of
them, using technical and qualitative analysis
High Level information flow looks like this:
Match Event
Data
Performance
Metrics
Expert User
Input
Post Match
Analysis
QUESTION: RUGBY UNION & TEAM PERFORMANCE METRICS
•
Can we use Business Analytics to introduce expert user
knowledge earlier in the process so as to produce a team
metric that offers a more meaningful description of
performance?
Match Event
Data
Performance
Metrics
Expert User
Input
Post Match
Analysis
INTRODUCTION: RUGBY UNION & TEAM PERFORMANCE METRICS
•
Can we use Business Analytics to introduce expert user
knowledge earlier in the process so as to produce a team
metric that offers a more meaningful description of
performance?
Match Event
Data
Expert User
Input
Performance
Metrics
Post Match
Analysis
RUGBY UNION & TEAM PERFORMANCE METRICS
•
•
•
•
•
Hot Performance Indicators constructed using existing Multi
Criteria Decision Making tools
Expert Users brought through steps so as to be convinced of
good performance.
Actions need to be executed well technically in any given
context (depending on opposition) and improve the team’s
situation , e.g. gives some advantage – field position or on the
score board
Can be used to analyse comparative team performance by
highlighting imbalances within underlying adjusting structure
Also, provide a basis for match outcome prediction, using a
simple Time Series Forecasting method
RESEARCH QUESTION & SUCCESS CRITERIA
•
•
•
Can the factors that contribute to team performance in Rugby
Union be considered to follow an underlying adjusting
structure?
Using this underlying structure, can a new team performance
metric be created that will lend itself well to comparative
analysis of teams and match outcome prediction?
Success = Successful proof of concept
•
Derived initial criteria relating to possession, set-pieces,
distribution, general execution (Hughes and Bartlett, 2002)
•
Criteria: possession, set-pieces, distribution, general execution
Came from soccer – experts extended them to eight for rugby
•
We consider the sub-criteria for each of the eight criteria, for
example Tackles
•
•
•
•
Sought to convince expert users by looking at different
aspects.
Ensure technique, appropriate to opposition and gives team a
game advantage
Example for Execution>>Tackles
Able to identify
relevant
Match Events for
construction of
HPI metrics
Should be convincing:
Technically
in the particular Context
in the actual Situation
•
Base Scores
•
•
83 match event
outcomes given
scores, positive &
negative outcomes
Score Modifiers
Positional clusters
(James et al. (2005))
• Quality of
Opposition ((Taylor
et al., 2008))
• Location on Pitch
• Home Advantage /
Away Disadvantage
(Nevill et al., 2007))
•
•
Base Scores
•
•
83 match event
outcomes given
scores (positive &
negative outcomes
Score Modifiers
Positional clusters
(James et al.
(2005))
• Quality of
Opposition ((Taylor
et al., 2008))
• Location on Pitch
• Home Advantage /
Away
Disadvantage
(Nevill et al., 2007))
•
METHODOLOGY: DATA & SOFTWARE USED
•
•
•
•
•
Data Provided by Opta
Sports
893 Extensible Markup
Language (XML) Files
(2008 – 2011 data)
Only used data between
2009 – 2011 – data quality
issues
XML included fixture
data, player data and
match event data
Software used: MySQL,
Java
Snippet of XML provided
ENTITY RELATIONSHIP DIAGRAM
BUSINESS CONTRIBUTION
•
•
•
•
Metric shows
difference in
performance / form
over time.
Example, Celtic
League 2011
Munster, Leinster
finished top, Aironi
finished bottom.
See HPI over season
Can be used to
highlight strengths /
weaknesses viz a viz
opposition teams
BUSINESS CONTRIBUTION
•
•
•
•
Well structured teams
should show balance
among the factors
contributing to their
performance
Methodology
highlights imbalance
Metrics form basis for
prediction of match
outcomes (win or loss)
Useful for coaches,
sports management,
bookmakers
Actual HPI vs Match Outcome
SUCCESS CRITERIA
•
Can a new team
performance metric be
created that will lend itself
well to comparative analysis
of teams and match
outcome prediction?
View the Imbalance –
Top vs Bottom of League
Competition
# Fixtures
# Correct
% Correct
Heineken 2010
75
54
72.0%
Heineken 2011
78
60
76.9%
Heineken 2012
72
53
73.6%
Magners 2010
81
50
61.7%
Magners 2011
134
106
79.1%
Rabo 2012
112
73
65.2%
Overall
552
396
71.7%
Predicted HPI vs Match Outcome
Competition
# Fixtures
# Correct
% Correct
Heineken 2010
63
44
69.8%
Heineken 2011
66
38
57.6%
Heineken 2012
60
38
63.3%
Magners 2010
75
41
54.7%
Magners 2011
128
80
62.5%
Rabo 2012
106
66
62.3%
Overall
498
307
61.6%
•
•
•
•
•
Academic Contribution – Novel application of MCDM
Business Contribution – new ways to analyse comparative
performance and predict future performance
Learning: How to deal with Professionals / Organisation outside
our normal comfort zone (usually IT / Finance).
Successful in terms of research questions. Married quantitative
with qualitative approach
Further research
• Refinement of scores and modifiers
• Improve scoring methodology (e.g. team rankings, referees)
• Expand scope – better forecasting method (e.g. Artificial
Intelligence
BUSINESS CONTRIBUTION
•
•
•
•
Metric shows
difference in
performance / form
over time.
Example, Celtic
League 2011
Munster, Leinster
finished top, Aironi
finished bottom.
See HPI over season
Can be used to
highlight strengths /
weakness viz a viz
opposition teams
ACADEMIC CONTRIBUTION
•
•
•
•
Novel application
of business analytics
to a real world
problem
Viewed sport as an
Adjusting Process
and showed link to
existing structures
Practise based
approach to
evaluating team
performance
Usable in other
contexts (different
sports, different
decision problems)
SUBJECTIVE COMPARISONS BETWEEN CHINA AND IRELAND ©C
ATHAL
Introverted
Development Committing Phases
Extroverted Development - Convincing Stages
Tech – Self
India - Ireland
x
x
x
x
Somatic – Need –
Thinking – Fear
Analysis – Abduce
Psychic – Prefer –
Feeling – Anxiety
Design – Deduce
Pneumatic – Value –
Knowing – Resent
Implement – Adduce
M BRUGHA
1.
xx
x x
xx
Physical /
Intuiting /
Affection
Contextual –
Others - China
x
x
x
x
xx
x x
xx
Situational –
World - U.S.
x
x
x
x
x
xx
xx
x
2. Political /
Recognizing /
Comradeship
3. Economic /
Believing /
Partnership
6. Emotional /
Trusting /
Empathy
Finding
5. Cultural /
Learning /
Friendship
Filling
4. Social /
Sensing /
Sexual
Fitting
7. Artistic /
Experiencing /
Collaboration
8. Religious /
Understanding /
Communion
9. Mystical /
Realising /
Charity
OBJECTIVE COMPARISONS BETWEEN CHINA AND IRELAND ©C
ATHAL M BRUGHA
OBJECTIVE COMPARISONS BETWEEN CHINA AND IRELAND ©C
ATHAL M BRUGHA
OBJECTIVE COMPARISONS BETWEEN CHINA AND IRELAND ©C
ATHAL M BRUGHA
Introverted
Development Committing Phases
Reforming the Culture in the
Public Service, which came
from 19th Century Britain that
protected corporate entities,
and feared individuals and
representative groups
Extroverted Development - Convincing Stages
Individual
Self - Technical
Representative
Corporate –
Others - Contextual World - Situational
No individuals with
given roles other than
ministers and some
ombudsmen, Governor
of Central Bank,
regulators, etc.
Some external boards:
c. 400 state authorities,
little internal lateral or
mainly unconnected, de
vertical coordination.
facto independent.
Little oversight of
Can postpone, ignore,
authorities. Councils little
sideline suggestions,
power over officials
pass the “hot potato”
Somatic – Need –
Thinking – Fear
Analysis - Abduce
1.
Psychic – Prefer –
Feeling – Anxiety
Design – Deduce
Pneumatic – Value –
Knowing – Resent
Implement – Adduce
Physical /
Intuiting /
Survey
2. Political /
Recognizing /
Study
3. Economic /
Believing /
Define
6. Emotional /
Trusting /
Acquire
Finding
5. Cultural /
Learning /
Design
Filling
4. Social /
Sensing /
Select
Fitting
7. Artistic /
Experiencing /
Construct
8. Religious /
Understanding /
Deliver
9. Mystical /
Realising /
Maintain
Introverted
Development Committing Phases
Reforming the Culture in the
Public Service, which came
from 19th Century Britain that
protected corporate entities,
and feared individuals and
representative groups
Extroverted Development - Convincing Stages
Individual
Self - Technical
Representative
Corporate –
Others - Contextual World - Situational
No individuals with
given roles other than
ministers and some
ombudsmen, Governor
of Central Bank,
regulators, etc.
Some external boards:
c. 400 state authorities,
little internal lateral or
mainly unconnected, de
vertical coordination.
facto independent.
Little oversight of
Can postpone, ignore,
authorities. Councils little
sideline suggestions,
power over officials
pass the “hot potato”
Somatic – Need –
Thinking – Fear
Analysis - Abduce
1.
Psychic – Prefer –
Feeling – Anxiety
Design – Deduce
Pneumatic – Value –
Knowing – Resent
Implement – Adduce
Physical /
Intuiting /
Survey
2. Political /
Recognizing /
Study
3. Economic /
Believing /
Define
6. Emotional /
Trusting /
Acquire
Finding
5. Cultural /
Learning /
Design
Filling
4. Social /
Sensing /
Select
Fitting
7. Artistic /
Experiencing /
Construct
8. Religious /
Understanding /
Deliver
9. Mystical /
Realising /
Maintain
Reform of the Culture in the Public Service ©Cathal M Brugha
ANALYTICS FOR ENABLING BUSINESS STRATEGY
PROFESSOR CATHAL BRUGHA, M.B.A, PH.D., FMII
FOUNDER DIRECTOR OF THE ANALYTICS INSTITUTE
PRESIDENT OF THE ANALYTICS SOCIETY OF IRELAND
WHO DO ANALYTICS? TECHI-ANALYSTS
ANALYTICS HAS MANY APPLICATIONS
COMBINED SUBJECTIVE / OBJECTIVE COMPARISONS ©C
ATHAL M BRUGHA