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EXPLORATORY MULTIVARIATE STATISTICAL METHODS APPLIED · PDF file EXPLORATORY MULTIVARIATE STATISTICAL METHODS APPLIED TO PHARMACEUTICAL INDUSTRY CRM DATA by Jorge Manuel Santos Freire

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  • 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.....................

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