Business Intelligence for New-Generation Managers (eBook)

Jörg H. Mayer is the head of the Corporate Management Systems Competence Center at University of St. Gallen. In parallel, he is a Partner of Deloitte Consulting GmbH responsible for Business Technology Innovation (BTI). He received his Doctoral Degree in 1999 at Darmstadt University of Technology. His main research interests are executives and their information systems (IS) support, especially mobile business intelligence for managers and environmental scanning systems.Reiner Quick has been Professor and the Chair of Accounting and Auditing at Darmstadt University of Technology since 2004 as well as a part-time Professor of Auditing at the University of Southern Denmark since 2009. He received his Doctoral Degree in 1990 and his Habilitation in 1995 at the University of Mannheim and held full professorships at the University of Essen and the Westfälische Wilhelms-Universität Münster. His main areas of research are auditing, in particular audit methodology, auditor independence and audit markets and management accounting.

Editorial 6
Business Intelligence for New-Generation Managers: Current Avenues of Development 6
References 8
Contents 10
On the Advent of Operational Perspectives in Business Intelligence 11
1 Introduction 11
2 The Understanding of BI in Context of Data and Their Managerial Usage Level 12
3 Method 14
4 Results 14
4.1 Analysis by Application Areas 15
4.2 Analysis by Text Mining 17
4.3 Discussion of Topics on Strategic and Operational BI 20
5 Conclusion 22
References 23
On the Way from a Knowledge Discovery in Databases to a Predictive Analytics 26
1 Introduction 26
2 Practical Implications of a Business Intelligence Based Forecast Process 27
2.1 Forecasts within the Decision Process 28
2.2 Business Intelligence in the Forecast Process 28
2.3 Problem Statement 29
3 Conceptual Modification of the KDD Process to Improve the Forecast Quality 29
3.1 Knowledge Discovery in Databases Process Model 30
3.2 KDD Enhancements in Context of a Predictive Analytics 30
4 Case Study: Customer Relationship Management in a German Saving and Loans 31
5 Conclusions 33
References 34
Design and Implementation of a Performance Measurement System for the German Trade Sector 36
1 Introduction 36
2 Theoretical Background 37
2.1 Determining Managers´ Information Needs 37
2.2 Performance Measurement Systems 38
2.3 Business Intelligence 38
3 Design of a Performance Measurement System for the German Trade Sector 39
3.1 Design Approach for Trade Scorecard 39
3.2 Sector-Specific Success Factors of the German Trade Sector and the Formation of the TSC Perspectives 40
3.3 The Financial Perspective 42
3.4 The Non-financial Perspectives: Key Performance Indicator Hierarchies Exemplified 42
4 Prototypal Implementation in a Business Intelligence Environment 44
5 Conclusion and Outlook 45
References 46
Applicability of Environmental Scanning Systems: A Systematic List Approach to Requirements Criteria 49
1 Introduction 50
2 Current Gaps in Environmental Scanning System Design 50
3 Model Development 51
3.1 Principle of Economic Efficiency 51
3.2 First Level of Specification: Design Criteria 52
3.3 Second Level of Specification: Requirements Criteria 53
4 Discussion 55
5 Outlook and Future Research 55
References 55
Developing Individual IT-Enabled Capabilities for Management Control Systems 58
1 Introduction 58
2 Maturity Models for Management Control Systems 60
3 Method Design 62
3.1 Design Theory 62
3.2 Constructing the Method 64
4 Demonstrating the Method 65
4.1 Research Design 65
4.2 Case Setting, Data Collection and Analysis 66
4.3 Instantiating the Method 66
5 Conclusion, Limitations and Future Research 70
References 71
Towards an Evaluation Framework to Structure Business Intelligence Project Patterns as Enhancement of Business Intelligence Ma... 74
1 Introduction 74
2 State of the Art: Business Intelligence 75
2.1 Conceptual Approach to Business Intelligence 76
2.2 Literature Review 79
3 Framework to Structure Patterns in BI Projects 81
4 Conclusions 82
References 83
Deployment of a Descriptive Big Data Model 84
1 Introduction 84
2 Research Design 85
3 Descriptive Model 88
3.1 Phenomenon 88
3.2 Causal Condition 88
3.3 Context 90
3.4 Strategy 92
3.5 Consequences 94
4 Classification of Academic Publications and Implementations 95
5 Conclusion 100
References 101
Business Intelligence 2.0 103
1 New Opportunities 103
2 Overview of Types of Data and Analysis Methods 104
2.1 Activities 104
2.2 Content 106
2.3 Relations 108
2.4 Experiences 110
3 Mix of Methods in Practical Application 111
4 Conclusion 115
References 116
Self-Service Management Support Systems: Findings from a New-Generation Manager Perspective 118
1 Design Problem 118
2 Requirements Analysis 120
2.1 Literature Review 120
2.2 Set of Requirements 124
3 Developing the Artefact 124
3.1 Survey Design and Sample Characteristics 124
3.2 Multi-Case Study 125
3.3 Develop Design Guidelines 126
Design guideline 1 127
Design guideline 2 128
Design guideline 3 128
Design guideline 4 128
Design guideline 5 129
4 Demonstrate 129
4.1 Project Description 129
4.2 The Corporate Navigator Framework 129
4.3 The Corporate Navigator App 130
5 Evaluation 135
6 Conclusion and Avenues for Future Research 137
References 138