Process Mining in Action (eBook)

Principles, Use Cases and Outlook

Lars Reinkemeyer (Herausgeber)

eBook Download: PDF

2020 | 1st ed. 2020
XXII, 207 Seiten
Springer International Publishing (Verlag)
978-3-030-40172-6 (ISBN)

Infos

This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment.

The book is divided into three parts: Part I provides an introduction to the topic from fundamental principles to key success factors, and an overview of operational use cases. As a holistic description of process mining in a business environment, this part is particularly useful for readers not yet familiar with the topic. Part II presents detailed use cases written by contributors from a variety of functions and industries. Lastly, Part III provides a brief overview of the future of process mining, both from academic and operational perspectives.

Based on a solid academic foundation, process mining has received increasing interest from operational businesses, with many companies already reaping the benefits. As the first book to present an overview of successful industrial applications, it is of particular interest to professionals who want to learn more about the possibilities and opportunities this new technology offers. It is also a valuable resource for researchers looking for empirical results when considering requirements for enhancements and further developments.

Lars Reinkemeyer is a visiting scholar at the University of California, Santa Barbara and senior executive of Siemens AG. Since 2014 he leveraged Process Mining technology in close collaboration with Siemens' functional departments like sales, logistics, procurement, accounting and has established a global community in excess of 6.000 active users around the world, supporting the company's digital transformation. As head of the Global Process Mining Services at Siemens Corporate IT he has built a team of experts located in Germany, Portugal and India providing cross-functional Process Mining services.

Lars Reinkemeyer joined Siemens AG in 1994, right after he earned a Master degree in Business Administration and a PhD from the University of Cologne, from which he graduated summa cum laude. He joined Siemens as Product- and Regional Manager and was delegated to Siemens Australia as International Account Manager in 1996. In 1998, he signed on as General Manager at Oztrak Europe GmbH, gaining some hands-on start-up experiences. In 2000, he joined Atoss Software AG as a Director of International Sales. Dr. Reinkemeyer rejoined Siemens AG in 2001, where he held various international leadership positions in strategy, compliance and IT. He is a guest speaker at Stanford Graduate School of Business and regular speaker on international conferences.

Inhalt

Foreword 6
Foreword 8
Process Mining in a Volatile World 8
Preface 11
Outline of the Book 12
Acknowledgments 15
Contents 16
Abbreviations 18
Part I: Principles and Value of Process Mining 20
1: Process Mining in a Nutshell 21
2: How to Get Started 29
3: Purpose: Identifying the Right Use Cases 33
4: People: The Human Factor 44
5: Processtraces: Technology 48
6: Challenges, Pitfalls, and Failures 53
7: Process Mining, RPA, BPM, and DTO 57
8: Key Learnings 61
Part II: Best Practice Use Cases 63
9: Siemens: Driving Global Change with the Digital Fit Rate in Order2Cash 64
Challenge 64
Use Case 65
Impact 68
Technology 69
Lessons Learned 70
Outlook 71
Links 72
10: Uber: Process Mining to Optimize Customer Experience and Business Performance 73
Challenge 73
Use Case 74
Impact 75
Technology 75
Lessons Learned 75
Outlook 76
11: BMW: Process Mining @ Production 78
Challenge 78
Use Case 80
Impact and Technology 81
Lessons Learned 82
Outlook 85
Links and Further Reading 86
12: Siemens: Process Mining for Operational Efficiency in Purchase2Pay 87
Challenge 87
Segregation of Duty Versus e2e Transparency 88
Cornerstones and Definitions for P2P Process Mining Cases 89
Use Cases 91
P2P Direct Material Focus Areas and Data Models 91
P2P Overview: Direct Material 92
Rework: Direct Material 93
P2P Indirect Material Focus Areas (SRM) 94
Payment Terms 98
EDI Rate Versus Rework Rate 99
Robotic Process Automation 101
Impact: Potential Business Benefits and Savings 103
Benefits of Increasing Operational Efficiency 104
Benefits of Reducing Throughput Times 104
Benefits of Optimizing Working Capital 105
Benefits of Increasing Digitalization 105
Technological Concepts of Process Mining P2P 106
Technological Prerequisites 106
P2P Data Model Configuration Template 107
Lessons Learned and Outlook 108
13: athenahealth: Process Mining for Service Integrity in Healthcare 109
Challenge 109
Why Process Mining? 110
Use Cases 110
Use Case #1 111
Use Case #2 111
Implementation of Use Case #1 111
Implementation of Use Case #2 113
Technology 115
Impact 115
Lessons Learned 116
Macro 117
Micro 118
Key Takeaways 118
Outlook 119
Links and Background Information 119
14: EDP Comercial: Sales and Service Digitization 121
Challenge 121
Use Case 122
Impact 123
Medium- and Long-Term Impacts: Accelerating the Positive Impact on Climate Change 124
Customer Care Insights 124
How Process Mining Is Contributing to Break Silos? 126
Analyzing Within the Processes 126
Technology 127
Lessons Learned 127
About People 127
About Processes 128
How to Engage? 128
Outlook 128
The Main Role of Process Mining 128
Public Sector Benefits 129
Process Mining Requires New Skills 129
Technological Context 129
Organic Context 129
Is the Global Market Mature? 129
Links (Fig. 14.4) 130
15: ABB: From Mining Processes Towards Driving Processes 131
Challenge 131
Use Case 133
Impact 134
Technology 136
Lessons Learned 138
16: Bosch: Process Mining-A Corporate Consulting Perspective 141
Challenge 141
Use Case 142
Impact 143
Technology 144
Lessons Learned 144
Outlook 145
17: Schukat: Process Mining Enables Schukat Electronic to Reinvent Itself 146
Challenge 146
Use Case 147
Bottom-Up-Analyze First 147
Top-Down-Design First 148
Loop 149
Trigger Live Action 149
Impact 150
Technology 150
Lessons Learned 150
Outlook 151
Links 153
18: Siemens Healthineers: Process Mining as an Innovation Driver in Product Management 154
Challenge 154
Use Case 156
Impact 158
Process Mining Enhanced by New Types of Visualizations 161
Exam Throughput per Hour 161
Trending of Examination Times 161
Visualization of Individual System Settings 162
Technology 163
Event Log and Data Architecture 163
Process Mining App 164
Hosting 164
Self-Service Process Mining 165
Lessons Learned 165
Challenge of Gathering Data 166
Structural and Organizational Challenges 166
Outlook 166
Links and Further Reading 167
19: Bayer: Process Mining Supports Digital Transformation in Internal Audit 169
Challenge 169
Use Cases 171
Impact 174
Technology 174
Lessons Learned 175
Outlook 177
Links 178
URLs 178
20: Telekom: Process Mining in Shared Services 179
Challenge 179
Use Case 181
Step 1: The First Implementations 182
Step 2: Center of Excellence 182
Step 3: Integration 183
Step 4: Machine Learning 184
Impact 184
Technology 185
Lessons Learned 186
Outlook 188
Links 188
Part III: Outlook: Future of Process Mining 189
21: Academic View: Development of the Process Mining Discipline 190
Adoption of Traditional Process Mining Techniques 191
Expanding the Scope of Process Mining 192
An Inconvenient Truth 195
Novel Challenges 200
Process Hygiene 204
References 204
22: Business View: Towards a Digital Enabled Organization 206
Present Trends 207
Near Future 208
Midterm Future 212
Long-Term Future 213
Vision of a Digital Enabled Organization 214
About the Editor 216

Produkt-Details

• Erscheint lt. Verlag: 14.3.2020
• Zusatzinfo: XXII, 207 p. 87 illus., 79 illus. in color.
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Datenbanken
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Wirtschaftsinformatik
• Schlagworte: Big Data • business process management • Computer Applications • data analytics • Empirical Studies • Process Mining • Use Cases
• ISBN-10: 3-030-40172-3 / 3030401723
• ISBN-13: 978-3-030-40172-6 / 9783030401726