TABLE OF CONTENTS
1 INTRODUCTION 17
1.1 OBJECTIVES OF THE STUDY 17
1.2 MARKET DEFINITION 17
1.3 MARKET SCOPE 18
1.3.1 MARKET SEGMENTATION 18
1.3.2 REGIONS COVERED 18
1.4 YEARS CONSIDERED FOR THE STUDY 19
1.5 CURRENCY CONSIDERED 19
1.6 STAKEHOLDERS 19
2 RESEARCH METHODOLOGY 20
2.1 RESEARCH DATA 20
2.1.1 SECONDARY DATA 21
2.1.2 PRIMARY DATA 21
2.1.2.1 Breakup of primary profiles 21
2.1.2.2 Key industry insights 22
2.2 MARKET BREAKUP AND DATA TRIANGULATION 23
2.3 MARKET SIZE ESTIMATION 23
2.3.1 TOP-DOWN APPROACH 24
2.3.2 BOTTOM-UP APPROACH 24
2.4 MARKET FORECAST 25
2.5 ASSUMPTIONS FOR THE STUDY 26
2.6 LIMITATIONS OF THE STUDY 26
3 EXECUTIVE SUMMARY 27
4 PREMIUM INSIGHTS 32
4.1 ATTRACTIVE MARKET OPPORTUNITIES IN THE PREDICTIVE MAINTENANCE MARKET 32
4.2 PREDICTIVE MAINTENANCE MARKET: TOP 3 VERTICALS 32
4.3 PREDICTIVE MAINTENANCE MARKET: BY REGION 33
4.4 PREDICTIVE MAINTENANCE MARKET IN NORTH AMERICA, BY COMPONENT AND DEPLOYMENT MODE 33
5 MARKET OVERVIEW AND INDUSTRY TRENDS 34
5.1 INTRODUCTION 34
5.2 MARKET DYNAMICS 34
5.2.1 DRIVERS 35
5.2.1.1 Increasing use of emerging technologies to gain valuable insights 35
5.2.1.2 Growing need to reduce maintenance cost and downtime 35
5.2.2 RESTRAINTS 35
5.2.2.1 Lack of skilled workforce 35
5.2.3 OPPORTUNITIES 36
5.2.3.1 Real-time condition monitoring to assist in taking prompt actions 36
5.2.4 CHALLENGES 36
5.2.4.1 Companies’ concern over data security and privacy issues 36
5.2.4.2 Frequent maintenance and upgradation requirement to keep
systems updated 36
5.3 USE CASES 37
5.3.1 INTRODUCTION 37
5.3.1.1 Use case: Scenario 1 37
5.3.1.2 Use case: Scenario 2 38
5.3.1.3 Use case: Scenario 3 38
5.3.1.4 Use case: Scenario 4 39
5.3.1.5 Use case: Scenario 5 39
5.4 REGULATORY IMPLICATIONS 40
5.4.1 INTRODUCTION 40
5.4.2 GENERAL DATA PROTECTION REGULATION 40
5.4.3 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT 40
5.4.4 FEDERAL TRADE COMMISSION 40
5.4.5 FEDERAL COMMUNICATIONS COMMISSION 41
5.4.6 ISO/IEC STANDARDS 41
5.4.6.1 ISO 55000 STANDARDS 41
5.4.6.2 ISO 13374 on condition monitoring and diagnostics of machines 42
5.4.6.3 ISO/ICE JTC 1 42
5.4.6.4 ISO/IEC JTC 1/SC 42 42
5.4.6.5 ISO/IEC JTC1/SC3 1 42
5.4.6.6 ISO/IEC JTC1/SC2 7 43
5.4.7 INDUSTRIAL INTERNET CONSORTIUM REFERENCE ARCHITECTURE 43
5.4.8 CEN/ISO 43
5.4.8.1 CEN/CENELEC 43
5.4.9 NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY 43
5.4.10 EPRIVACY 44
5.4.11 ANSI TAPPI TIP 0305-34:2008 44
5.4.12 MIMOSA 44
6 PREDICTIVE MAINTENANCE MARKET, BY COMPONENT 45
6.1 INTRODUCTION 46
6.2 SOLUTIONS 47
6.2.1 INTEGRATED 48
6.2.1.1 Growing adoption of the integrated solution as it integrates multiple capabilities within a single solution 48
6.2.2 STANDALONE 48
6.2.2.1 Increasing demand for advanced and vertical-focused predictive maintenance capabilities to drive the growth of standalone solutions 48
6.3 SERVICES 49
6.3.1 SYSTEM INTEGRATION 50
6.3.1.1 Predictive maintenance vendors to offer system integration services to overcome system-related issues effectively 50
6.3.2 SUPPORT AND MAINTENANCE 50
6.3.2.1 Growing deployment of predictive maintenance solution to increase the demand for support and maintenance services 50
6.3.3 CONSULTING 50
6.3.3.1 Technicalities involved in implementing predictive maintenance solution to boost the growth of consulting services 50
7 PREDICTIVE MAINTENANCE MARKET, BY DEPLOYMENT MODE 51
7.1 INTRODUCTION 52
7.2 CLOUD 53
7.2.1 BENEFITS, SUCH AS SCALABILITY AND EASE OF IMPLEMENTATION,
TO BOOST THE GROWTH OF THE CLOUD DEPLOYMENT MODE 53
7.3 ON-PREMISES 53
7.3.1 DATA-SENSITIVE ORGANIZATIONS TO ADOPT THE ON-PREMISES DEPLOYMENT MODE FOR PREDICTIVE MAINTENANCE SOLUTIONS 53
8 PREDICTIVE MAINTENANCE MARKET, BY ORGANIZATION SIZE 54
8.1 INTRODUCTION 55
8.2 LARGE ENTERPRISES 56
8.2.1 LARGE ENTERPRISES TO ADOPT PREDICTIVE MAINTENANCE SOLUTIONS TO OPTIMIZE OPERATIONAL MAINTENANCE PROCESSES 56
8.3 SMALL AND MEDIUM-SIZED ENTERPRISES 56
8.3.1 SMALL AND MEDIUM-SIZED ENTERPRISES TO ADOPT PREDICTIVE MAINTENANCE SOLUTIONS WITH RISING TECHNOLOGICAL ADVANCEMENT 56
9 PREDICTIVE MAINTENANCE MARKET, BY VERTICAL 57
9.1 INTRODUCTION 58
9.2 GOVERNMENT AND DEFENSE 59
9.2.1 GOVERNMENT AND DEFENSE VERTICAL TO ADOPT PREDICTIVE MAINTENANCE SOLUTIONS FOR AUTOMATING THE DEFENSE SYSTEM 59
9.3 MANUFACTURING 60
9.3.1 GROWING NEED TO TRACK, DIAGNOSE, AND MONITOR MACHINES TO FUEL THE GROWTH OF THE PREDICTIVE MAINTENANCE APPLICATION IN THE MANUFACTURING VERTICAL 60
9.4 ENERGY AND UTILITIES 60
9.4.1 THE GROWING DEMAND OF POWER-USAGE ANALYTICS APPLICATIONS FUEL THE GROWTH OF ENERGY AND UTILITIES VERTICAL 60
9.5 TRANSPORTATION AND LOGISTICS 61
9.5.1 INCREASING NEED TO IMPROVE ASSET TRACKING AND PERFORMANCE MANAGEMENT FOR MINIMIZING RISKS LEAD TO GROWTH IN TRANSPORTATION AND LOGISTICS VERTICAL 61
9.6 HEALTHCARE AND LIFE SCIENCES 61
9.6.1 GROWING DEMAND FOR MONITORING PATIENT HEALTH AND PERSONALIZED TREATMENT IN REAL TIME TO FUEL THE GROWTH OF HEALTHCARE AND LIFE SCIENCES VERTICAL 61
9.7 OTHERS 62
10 PREDICTIVE MAINTENANCE MARKET, BY REGION 63
10.1 INTRODUCTION 64
10.2 NORTH AMERICA 66
10.2.1 UNITED STATES 71
10.2.1.1 Need to extract maximum value from smart devices to fuel
the demand for predictive maintenance solutions in the US 71
10.2.2 CANADA 71
10.2.2.1 Increase in investments and research activities to drive predictive maintenance adoption in Canada 71
10.3 EUROPE 72
10.3.1 UNITED KINGDOM 75
10.3.1.1 Government focus on innovation and research to fuel the adoption of predictive maintenance solutions in the UK 75
10.3.2 GERMANY 76
10.3.2.1 Skilled workforce, strong infrastructure, and increase in investments to drive the predictive maintenance adoption in Germany 76
10.3.3 FRANCE 76
10.3.3.1 Focus on R&D and heavy inflow of capital from global players and investors to drive the predictive maintenance market in France 76
10.3.4 ITALY 76
10.3.4.1 Increasing adoption of new technologies and innovations to drive
the predictive maintenance market in Italy 76
10.3.5 REST OF EUROPE 77
10.4 ASIA PACIFIC 78
10.4.1 CHINA 82
10.4.1.1 Increasing focus on integrating AI and deep learning technologies to drive the adoption of predictive maintenance solutions in China 82
10.4.2 JAPAN 83
10.4.2.1 Increasing government initiatives, led to the potential growth for predictive maintenance in Japan 83
10.4.3 REST OF ASIA PACIFIC 83
10.5 MIDDLE EAST AND AFRICA 84
10.5.1 ISRAEL 88
10.5.1.1 Presence of IoT and AI software vendors to lead the adoption of predictive maintenance solutions 88
10.5.2 UAE 88
10.5.2.1 Complex legal, regulatory, and economic resolutions to compel organizations to adopt predictive maintenance solutions 88
10.5.3 REST OF MIDDLE EAST AND AFRICA 88
10.6 LATIN AMERICA 89
10.6.1 BRAZIL 93
10.6.1.1 Brazil embraces the digital age with a shift toward Industry 4.0 93
10.6.2 MEXICO 93
10.6.2.1 Mexico to witness the highest growth rate in the predictive maintenance market in the coming years 93
10.6.3 REST OF LATIN AMERICA 94
11 COMPETITIVE LANDSCAPE 95
11.1 OVERVIEW 95
11.2 COMPETITIVE LEADERSHIP MAPPING 95
11.2.1 VISIONARIES 95
11.2.2 INNOVATORS 95
11.2.3 DYNAMIC DIFFERENTIATORS 95
11.2.4 EMERGING COMPANIES 95
11.3 STRENGTH OF PRODUCT PORTFOLIO 97
11.4 BUSINESS STRATEGY EXCELLENCE 98
11.5 COMPETITIVE LEADERSHIP MAPPING (START-UPS) 99
11.5.1 PROGRESSIVE COMPANIES 99
11.5.2 RESPONSIVE COMPANIES 99
11.5.3 DYNAMIC COMPANIES 99
11.5.4 STARTING BLOCKS 99
11.6 STRENGTH OF PRODUCT PORTFOLIO (STARTUPS) 101
11.7 BUSINESS STRATEGY EXCELLENCE (STARTUPS) 102
12 COMPANY PROFILES 103
12.1 INTRODUCTION 103
(Business Overview, Products/Services/Platforms Offered, Recent Developments, SWOT Analysis, and MnM View)*
12.2 IBM 103
12.3 MICROSOFT 107
12.4 SAP 110
12.5 GE 113
12.6 SCHNEIDER ELECTRIC 116
12.7 HITACHI 119
12.8 PTC 121
12.9 SOFTWARE AG 124
12.10 SAS 127
12.11 TIBCO 129
* Business Overview, Products/Services/Platforms Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
12.12 C3 IOT 131
12.13 UPTAKE 131
12.14 SOFTWEB SOLUTIONS 132
12.15 ASYSTOM 132
12.16 ECOLIBRIUM ENERGY 133
12.17 FIIX 133
12.18 OPEX GROUP 133
12.19 DINGO 134
12.20 SIGMA INDUSTRIAL PRECISION 134
13 APPENDIX 135
13.1 INDUSTRY EXPERTS 135
13.2 DISCUSSION GUIDE 136
13.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 141
13.4 AVAILABLE CUSTOMIZATIONS 143
13.5 RELATED REPORTS 143
13.6 AUTHOR DETAILS 144
TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2015–2017 19
TABLE 2 FACTOR ANALYSIS 25
TABLE 3 GLOBAL PREDICTIVE MAINTENANCE MARKET SIZE AND GROWTH RATE,
2017–2024 (USD MILLION, Y-O-Y %) 28
TABLE 4 PREDICTIVE MAINTENANCE MARKET SIZE, BY COMPONENT,
2017–2024 (USD MILLION) 46
TABLE 5 SOLUTIONS: PREDICTIVE MAINTENANCE MARKET SIZE, BY TYPE,
2017–2024 (USD MILLION) 47
TABLE 6 SERVICES: PREDICTIVE MAINTENANCE MARKET SIZE, BY TYPE,
2017–2024 (USD MILLION) 49
TABLE 7 PREDICTIVE MAINTENANCE MARKET SIZE, BY DEPLOYMENT MODE,
2017–2024 (USD MILLION) 52
TABLE 8 PREDICTIVE MAINTENANCE MARKET SIZE, BY ORGANIZATION SIZE,
2017–2024 (USD MILLION) 55
TABLE 9 PREDICTIVE MAINTENANCE MARKET SIZE, BY VERTICAL,
2017–2024 (USD MILLION) 58
TABLE 10 PREDICTIVE MAINTENANCE MARKET SIZE, BY REGION, 2017–2024 (USD MILLION) 66
TABLE 11 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY COMPONENT, 2017–2024 (USD MILLION) 68
TABLE 12 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY SOLUTION,
2017–2024 (USD MILLION) 68
TABLE 13 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY SERVICE,
2017–2024 (USD MILLION) 68
TABLE 14 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY DEPLOYMENT MODE, 2017–2024 (USD MILLION) 69
TABLE 15 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET BY ORGANIZATION SIZE, 2017–2024 (USD MILLION) 69
TABLE 16 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY VERTICAL,
2017–2024 (USD MILLION) 70
TABLE 17 NORTH AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY COUNTRY,
2017–2024 (USD MILLION) 70
TABLE 18 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY COMPONENT,
2017–2024 (USD MILLION) 72
TABLE 19 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY SOLUTION,
2017–2024 (USD MILLION) 73
TABLE 20 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY SERVICE,
2017–2024 (USD MILLION) 73
TABLE 21 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY DEPLOYMENT MODE, 2017–2024 (USD MILLION) 74
TABLE 22 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY ORGANIZATION SIZE, 2017–2024 (USD MILLION) 74
TABLE 23 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY VERTICAL,
2017–2024 (USD MILLION) 74
TABLE 24 EUROPE: PREDICTIVE MAINTENANCE MARKET SIZE, BY COUNTRY,
2017–2024 (USD MILLION) 75
TABLE 25 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY COMPONENT,
2017–2024 (USD MILLION) 79
TABLE 26 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY SOLUTION,
2017–2024 (USD MILLION) 79
TABLE 27 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY SERVICE,
2017–2024 (USD MILLION) 80
TABLE 28 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY DEPLOYMENT MODE, 2017–2024 (USD MILLION) 80
TABLE 29 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY ORGANIZATION SIZE, 2017–2024 (USD MILLION) 81
TABLE 30 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY VERTICAL,
2017–2024 (USD MILLION) 81
TABLE 31 ASIA PACIFIC: PREDICTIVE MAINTENANCE MARKET SIZE, BY COUNTRY,
2017–2024 (USD MILLION) 82
TABLE 32 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY COMPONENT, 2017–2024 (USD MILLION) 84
TABLE 33 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY SOLUTION, 2017–2024 (USD MILLION) 85
TABLE 34 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY SERVICE, 2017–2024 (USD MILLION) 85
TABLE 35 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY DEPLOYMENT MODE, 2017–2024 (USD MILLION) 86
TABLE 36 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY ORGANIZATION SIZE, 2017–2024 (USD MILLION) 86
TABLE 37 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY VERTICAL, 2017–2024 (USD MILLION) 87
TABLE 38 MIDDLE EAST AND AFRICA: PREDICTIVE MAINTENANCE MARKET SIZE,
BY COUNTRY, 2017–2024 (USD MILLION) 87
TABLE 39 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY COMPONENT, 2017–2024 (USD MILLION) 90
TABLE 40 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY SOLUTION,
2017–2024 (USD MILLION) 90
TABLE 41 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY SERVICE,
2017–2024 (USD MILLION) 90
TABLE 42 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY DEPLOYMENT MODE, 2017–2024 (USD MILLION) 91
TABLE 43 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY ORGANIZATION SIZE, 2017–2024 (USD MILLION) 91
TABLE 44 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY VERTICAL,
2017–2024 (USD MILLION) 92
TABLE 45 LATIN AMERICA: PREDICTIVE MAINTENANCE MARKET SIZE, BY COUNTRY,
2017–2024 (USD MILLION) 92
LIST OF FIGURES
FIGURE 1 GLOBAL PREDICTIVE MAINTENANCE MARKET: RESEARCH DESIGN 20
FIGURE 2 PREDICTIVE MAINTENANCE MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES 24
FIGURE 3 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY COMPONENT 28
FIGURE 4 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY SOLUTION 29
FIGURE 5 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY SERVICE 29
FIGURE 6 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY DEPLOYMENT MODE 30
FIGURE 7 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY ORGANIZATION SIZE 30
FIGURE 8 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY VERTICAL 31
FIGURE 9 PREDICTIVE MAINTENANCE MARKET SNAPSHOT, BY REGION 31
FIGURE 10 REAL-TIME CONDITIONING MONITORING TO TAKE PROMPT ACTION IS ONE OF
THE MAJOR FACTORS DRIVING THE OVERALL GROWTH OF THE PREDICTIVE MAINTENANCE MARKET DURING THE FORECAST PERIOD 32
FIGURE 11 ENERGY AND UTILITIES VERTICAL TO GROW AT THE HIGHEST CAGR DURING
THE FORECAST PERIOD 32
FIGURE 12 NORTH AMERICA TO HOLD THE HIGHEST MARKET SHARE IN 2019 33
FIGURE 13 SOLUTIONS COMPONENT AND ON-PREMISES DEPLOYMENT MODE IN
NORTH AMERICA ACCOUNTED FOR THE HIGHEST SHARES IN THE PREDICTIVE MAINTENANCE MARKET IN 2019 33
FIGURE 14 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES:
PREDICTIVE MAINTENANCE MARKET 34
FIGURE 15 SERVICES SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 46
FIGURE 16 STANDALONE SOLUTION SEGMENT TO GROW AT A HIGHER CAGR DURING
THE FORECAST PERIOD 47
FIGURE 17 SUPPORT AND MAINTENANCE SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 49
FIGURE 18 CLOUD SEGMENT TO WITNESS A HIGHER CAGR DURING THE FORECAST PERIOD 52
FIGURE 19 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO REGISTER A HIGHER CAGR DURING THE FORECAST PERIOD 55
FIGURE 20 ENERGY AND UTILITIES VERTICAL TO WITNESS THE HIGHEST CAGR DURING
THE FORECAST PERIOD 58
FIGURE 21 NORTH AMERICA TO HOLD THE LARGEST MARKET SIZE DURING
THE FORECAST PERIOD 64
FIGURE 22 JAPAN TO HOLD THE HIGHEST CAGR DURING THE FORECAST PERIOD 65
FIGURE 23 ASIA PACIFIC TO HOLD THE HIGHEST CAGR DURING THE FORECAST PERIOD 65
FIGURE 24 NORTH AMERICA: MARKET SNAPSHOT 67
FIGURE 25 ENERGY AND UTILITIES TO GROW AT THE HIGHEST CAGR DURING
THE FORECAST PERIOD 67
FIGURE 26 ENERGY AND UTILITIES VERTICAL TO GROW AT THE HIGHEST CAGR DURING
THE FORECAST PERIOD IN EUROPE 72
FIGURE 27 ASIA PACIFIC: MARKET SNAPSHOT 78
FIGURE 28 ENERGY AND UTILITIES VERTICAL TO GROW AT THE HIGHEST CAGR DURING
THE FORECAST PERIOD IN ASIA PACIFIC 79
FIGURE 29 ENERGY AND UTILITIES VERTICAL TO GROW AT THE HIGHEST CAGR DURING
THE FORECAST PERIOD IN MIDDLE EAST AND AFRICA 84
FIGURE 30 ENERGY AND UTILITIES VERTICAL TO GROW AT HIGHEST CAGR DURING
THE FORECAST PERIOD IN LATIN AMERICA 89
FIGURE 31 PREDICTIVE MAINTENANCE MARKET (GLOBAL), COMPETITIVE LEADERSHIP MAPPING, 2018 96
FIGURE 32 KEY PLAYERS OF THE PREDICTIVE MAINTENANCE MARKET, 2018 99
FIGURE 33 PREDICTIVE MAINTENANCE MARKET (GLOBAL), COMPETITIVE LEADERSHIP MAPPING, FOR STARTUPS, 2018 100
FIGURE 34 IBM: COMPANY SNAPSHOT 104
FIGURE 35 SWOT ANALYSIS: IBM 106
FIGURE 36 MICROSOFT: COMPANY SNAPSHOT 107
FIGURE 37 SWOT ANALYSIS: MICROSOFT 109
FIGURE 38 SAP: COMPANY SNAPSHOT 110
FIGURE 39 SWOT ANALYSIS: SAP 112
FIGURE 40 GE: COMPANY SNAPSHOT 113
FIGURE 41 SWOT ANALYSIS: GE 115
FIGURE 42 SCHNEIDER ELECTRIC: COMPANY SNAPSHOT 116
FIGURE 43 SWOT ANALYSIS: SCHNEIDER ELECTRIC 118
FIGURE 44 HITACHI: COMPANY SNAPSHOT 119
FIGURE 45 PTC: COMPANY SNAPSHOT 121
FIGURE 46 SOFTWARE AG: COMPANY SNAPSHOT 124