EXPLORATORY MULTIVARIATE STATISTICAL METHODS
APPLIED TO PHARMACEUTICAL
INDUSTRY CRM DATA
by
Jorge Manuel Santos Freire Tavares
Dissertation submitted in partial fulfilment of the requirements for the degree of
Mestre em Estatística e Gestão de Informação
[Master of Statistics and Information Management]
Instituto Superior de Estatística e Gestão de Informação
da
Universidade Nova de Lisboa
II
EXPLORATORY MULTIVARIATE STATISTICAL METHODS
APPLIED TO PHARMACEUTICAL
INDUSTRY CRM DATA
Dissertation supervised by
Professor Doutor Fernando Lucas Bação
Professor Doutor Pedro Simões Coelho
November 2007
III
Acknowledgements
To Professor Fernando Lucas Bação and Professor Pedro Simões Coelho for their orientation
and support during the execution of this work.
To my friends and family, because of my needed absences to do this work, thank you very much
for the support and understanding.
IV
ABSTRACT
An analysis of the current CRM systems in the Pharmaceutical Industry, the way the
pharmaceutical companies developed them and a comparison between Europe and United States
was done in this study. Overall the CRM in the pharmaceutical industry is far-behind, when
compared with other business areas, like consumer goods, finance (banking) or insurance
companies, being pharmaceutical CRM specifically less developed in Europe when compared to
United States.
One of the big obstacles for the success of CRM in the pharmaceutical industry is the poor
analytics applied to the current CRM programs. Improving Sales and Marketing Effectiveness
by apllying, multivariate exploratory statistical methods, specifically Factor Analysis and
Clustering into pharmaceutical CRM data from a Portuguese pharmaceutical company was the
main goal of this thesis. Their overall usefulness when applied to the business was
demonstrated, and specifically in relation to the cluster methods, SOMs outperformed the
hierarchical methods by producing a more meaningful business solution.
RESUMO
Neste estudo, foi feita uma análise dos sistemas de CRM actualmente utilizados na indústria
farmacêutica, a maneira como as empresas farmacêuticas os desenvolvem, fazendo uma
comparação entre a Europa e os Estados Unidos da América. Na sua globalidade o CRM na
indústria farmacêutica está menos desenvolvido quando comparado com outras áreas de
negócio, tais como o grande consumo, banca ou seguradoras, sendo ainda menos desenvolvido
o CRM farmacêutico na Europa quando comparado com os Estados Unidos.
Um dos grandes obstáculos para o sucesso do CRM na indústria farmacêutica é a fraca análise
de dados feita nos actuais programas de CRM. Melhorar a eficiência nos processos associados
ao marketing e ás vendas, usando métodos exploratórios de análise multivariada,
especificamente Análise Factorial e Análise de Clusters, aplicados a um conjunto de dados
proveniente de uma empresa farmacêutica Portuguesa, é o principal objectivo desta tese. A
utilidade destes métodos quando aplicados no contexto da área de negócio em estudo
demonstrou a sua utilidade e especificamente em relação á análise de clusters, globalmente os
métodos hierárquicos foram inferiores na produção de uma solução válida para a área de
negócio em questão quando comparados com os SOMs.
V
Key Words
Customer Relatationship Management
Pharmaceutical Industry
Exploratory Multivariate Statistical Methods
Factor Analysis
Hierarchical Cluster analysis
Self- Organizing Map
Palavras- Chave.
Gestão de Relacionamento do Cliente
Indústria Farmacêutica
Analise de Dados Exploratória Multivariada
Análise Factorial
Análise Hierárquica de Clusters
Mapa Auto Organizável de Kohonen.
VI
Abbreviations
BMU Best Matching Unit
CLTV Customer Life Time Value
CRM Customer Relationship Management
DTC Direct to Consumer Advertising
ERP Enterprise Resourse Planing
HMO Health Maintainance Organization
IMS International Marketing Services
PAF Principal Axis Factoring
PCF Principal Components Factoring
PhRMA Pharmaceutical Research and Manufacturers of America
qe Average quantization error
SFA Sales Force Automation
SOM Self- Organizing Map
te Topographic error
U-Matrix Unified Matrix
U.S. United States
VII
Table of contents
1. INTRODUCTION..................................................................................................................... 1
1.1. Context............................................................................................................................... 1
1.2. Motivation.......................................................................................................................... 2
1.3. Objectives .......................................................................................................................... 3
1.4. Structure of the dissertation ............................................................................................... 4
2. LITERATURE ANALYSIS................................................................................................. 5
2.1. CURRENT PHARMACEUTICAL ENVIRONMENT..................................................... 7
2.1.1 Characteristics of the United States of America Pharmaceutical Market.................... 7
2.1.2 Characteristics of the European Pharmaceutical Market............................................. 7
2.1.3 Direct-To-Consumer advertising United States of America versus Europe and the
changing dynamics of promoting pharmaceutical drugs ...................................................... 8
2.2. ANALYSIS OF THE CURRENT CRM PROGRAMS IN THE PHARMACEUTICAL
INDUSTRY. ........................................................................................................................... 11
2.2.1 General Overview of CRM Programs in the Pharmaceutical Industry ..................... 11
2.2.2 Sales Force Automation Systems in Pharmaceutical Industry .................................. 14
2.2.3 CRM Programs focusing in online strategies and communication technologies ...... 19
2.2.4 CRM focusing in Supply Chain and Demand Management Integration ................... 22
2.2.5 Differences between the current CRM programs in Europe and United States ........ 23
3. METHODOLOGY.................................................................................................................. 25
3.1 BUSINESS PURPOSE OF APPLIYING MULTIVARIATE TECHNIQUES IN
PHARMACEUTICAL CRM.................................................................................................. 25
3.2 DESCRIPTION OF THE CRM DATA FILE USED. ...................................................... 26
3.3 FACTOR ANALYSIS ...................................................................................................... 28
3.3.1 Factor Model ............................................................................................................. 28
3.3.2 Factor Indeterminacy................................................................................................. 30
3.3.3 Factor Rotations......................................................................................................... 31
3.3.4 Data Matrix................................................................................................................ 37
3.3.5 Factor Extraction Methods ........................................................................................ 37
3.3.6 Methods to evaluate if data is appropriate for factor analysis ................................... 40
3.3.7 Determining the number of factors............................................................................ 41
3.3.8 Factor Solution Quality ............................................................................................. 44
3.3.9 Factor Scores ............................................................................................................. 45
3.3.10 Factor Analysis versus Principal Components Analysis ......................................... 46
3.3.11 Exploratory versus Confirmatory Factor Analysis .................................................. 47
3.4 HIERARCHICAL CLUSTERING................................................................................... 48
VIII
3.4.1 Introduction ............................................................................................................... 48
3.4.2 Agglomerative Methods ............................................................................................ 48
3.4.3 Distance Measures.....................
