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Smart Service Management

Design Guidelines and Best Practices

  • Book
  • © 2020

Overview

  • Presents the main theoretical foundations as well as specific guidelines and practically proven methods on how to design smart services

  • Provides an overview of the possible implementation architectures and shows how smart services can be realized with specific technologies

  • Shows four specific use cases that detail how smart services have been realized in practice and what impact they have within the businesses

  • Written for industry-focused readers from middle management in business development, product management, strategy, and development to Chief Digital Officers

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Table of contents (18 chapters)

  1. Introduction to Smart Services

  2. Smart Service Design

  3. Smart Service Architecture

  4. Smart Service Analytics

  5. Smart Service Use Cases

Keywords

About this book

This book presents the main theoretical foundations behind smart services as well as specific guidelines and practically proven methods on how to design them. Furthermore, it gives an overview of the possible implementation architectures and shows how the designed smart services can be realized with specific technologies. Finally, it provides four specific use cases that show how smart services have been realized in practice and what impact they have within the businesses.

The first part of the book defines the basic concepts and aims to establish a shared understanding of terms, such as smart services, service systems, smart service systems or cyber-physical systems. On this basis, it provides an analysis of existing work and includes insights on how an organization incorporating smart services could enhance and adjust their management and business processes. The second part on the design of smart services elaborates on what constitutes a successful smart service and describes experiences in the area of interdisciplinary teams, strategic partnerships, the overall service systems and the common data basis. In the third part, technical reference architectures are presented in detail, encompassing topics on the design of digital twins in cyber physical systems, the communication between entities and sensors in the age of Industry 4.0 as well as data management and integration. The fourth part then highlights a number of analytical possibilities that can be realized and that can constitute or be part of smart services, including machine learning and artificial intelligence methods. Finally, the applicability of the introduced design and development method is demonstrated by considering specific real-world use cases. These include services in the industrial and mobility sector, which were developed in direct cooperation with industry partners.

The main target audience of this book is industry-focused readers, especially practitioners from industry, who are involved in supporting and managing digital business. These include professionals working in business development, product management, strategy, and development, ranging from middle management to Chief Digital Officers. It conveys all the basics needed for developing smart services and successfully placing them on the market by explaining technical aspects as well as showcasing practical use cases.


Editors and Affiliations

  • University of Bonn, Bonn, Germany

    Maria Maleshkova

  • Karlsruhe Institute of Technology, Karlsruhe, Germany

    Niklas Kühl

  • Schaeffler Monitoring Services GmbH, Herzogenrath, Germany

    Philipp Jussen

About the editors

Maria Maleshkova is an Assistant Professor at the Computer Science Department III of the University of Bonn. She has been working on IoT and service topics for the past 10 years, focusing on semantics-based data integration topics as well as on research in the areas of distributed applications, applied AI-methods, Web APIs and their joint use for developing innovative services. She has led the development and deployment of smart services in production companies and has a strong background in the fundamentals and technologies for implementing smart services.

Niklas Kühl is head of the Applied AI Lab of the Karlsruhe Service Research Institute (KSRI) at the Karlsruhe Institute of Technology (KIT). He has been working on service-related machine learning (ML) and artificial intelligence (AI) for the past 5 years in different domains. He and his team are working on different ML & AI service solutions within healthcare services, industrial services, sales forecasting, production lines or even creativity. Niklas is internationally collaborating in his research efforts with the University of Auckland, the Wharton School of the University of Pennsylvania and the MIT-IBM Watson AI Lab.

Philipp Jussen was responsible for the service management department at FIR at the RWTH Aachen for 4 years and was at the same time managing director for the Center Smart Services at the RWTH Aachen Campus. In addition to numerous benchmarkings and studies, he has extensive implementation and practical knowledge from consulting projects for industrial customers. Together with his team, he developed approaches to smart service engineering and smart service sales for companies in the industrial B2B sector.


 

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