Monetization of technical Data

Press release: Springer-Book “Monetization of technical Data — Innovations from Industry and Academia”

senseering, WZL of RWTH Aachen University and Fraunhofer FIT have sent manuscript to SpringerVieweg

Dieser Artikel ist auch auf Deutsch verfügbar.

Advertisement/Anzeige: The new Springer Book Monetization of Technical Data is now available for order!

The monetization of data is a very new topic per se, and there are only a few
very few case studies. There is a lack of a strategy or a concept, that shows executives the way to monetize data, especially those who have discovered the digital transformation or Industry 4.0 for themselves or are threatened by it. Because machine data is mostly unstructured and cannot be exploited without domain knowledge/metadata, the monetarization of machine data
holds potential that cannot yet be conclusively evaluated.

In order to grasp that potential, senseering, WZL of RWTH Aachen and Fraunhofer FIT have initiated this book, that includes 35 contributions from academia as well as practical examples from industry. On the basis of these examples, readers can already become part of a future data economy. Added values and benefits are described in concrete terms.

Submission completed

After one year of work, the manuscript finally went to Springer on January 15, 2021 and will be in the shelves by the end of the year!

Preface

Dear Readers,

“Elon Musk’s company Tesla is not an electric car manufacturer, Tesla is a software company” is one of my favorite quotes. On the one hand, it shows how multifaceted digitalization is, and on the other hand, how misunderstood it is. While in the eyes of many citizens and entrepreneurs the electric vehicles are Tesla’s actual product, the so-called digital natives in particular see the digital services and features that — just like that — come along as a product. This difference in product and brand interpretation describes very well the different expectations of different customer groups, but also the potential of digital, data-based business models. In the past, product-related value propositions were the focus of economic and social development. People wanted to own something, they paid for the equivalent value of the “thing”. And that was basically a safe bank, too. Accordingly, the competition differentiated itself either through significantly cheaper products or through products of significantly higher quality.

Digitization has now changed the range of products and services offered by companies. Due to the improved accessibility of suppliers and customers via apps, platforms and the like, almost around the clock, it became apparent that the actual needs of most customers do not lie in the possession of a thing, but rather in the use of this very thing. What problem does the thing actually solve? And how can I transform the problem-solving solution into a recurring, digitally automated service? Answering these two questions is something that Anglo-Saxon companies in particular have understood in recent years. For Tesla, the need of drivers is not the need to own a vehicle, but to get from point A to point B. Environmentally friendly and time efficient. The former is realized through the use of electric technology, the latter through the soon-to-be-available Autopilot. After all, that’s what drivers and especially commuters want: to stop wasting time in traffic jams. Autopilot is just one of the many conceivable software services that can be delivered with a Tesla and made available elegantly, without a workshop visit, via over-the-air updates.

In my view, the future holds incredible potential for Tesla-like success stories. By 2025, experts expect that up to 75 billion Internet-of-Things (IoT) devices will be connected to the Internet worldwide. An IoT device can be anything from a smart toaster to an electrified vehicle to a smart manufacturing machine in mechanical engineering, the data from which can be used to develop a digital, data-driven service that makes using the actual thing more convenient for the user. And these data-driven services will dominate the economy. An estimated 175 zettabytes, or 175 billion terabytes, are expected to be generated in 2025. In that context, data must be understood not as singular information, but as fuel that enables the time- and location-dependent, person-specific use of something.

Even though it is not yet known exactly what the economic exploitation of data would look like in such a scenario, it is known that this data will have a potential value of 829 billion euros in 2025. This book, “Monetization of technical Data,” attempts to show how readers and entrepreneurs can leverage the potential of data and monetize it through unique services. The book is not a practical guide that shares established and proven best practices, but rather a collection of innovative impulse contributions from a few pioneers that aims to slowly but surely establish the topic of “monetization of technical data” as an inspiration and door opener. My thanks therefore go to all the authors who have embarked on this journey into the unknown and whose contributions have made the success of this book possible in the first place. Likewise, this book is not a report of results. It is only the beginning of a long journey on which you, the readers, are invited to share your private or professional experiences and results, perhaps even with a contribution in the next edition.

My special thanks go to Marco Becker and his colleagues Mia Kornely, Joachim Stanke, Johannes Mayer, Lucia Ortjohann, Martin Unterberg, Philipp Niemietz and Tobias Kaufmann from the Laboratory for Machine Tools and Production Engineering WZL at RWTH Aachen University, who coordinated and supervised this book, as well as to the co-editors, who supported and made possible this work with important impulses and contributions.

I wish all readers an exciting time and much pleasure in reading these forward-looking contributions. I hope the following pages will provide you with inspiration to make your own data monetization projects successful.

On behalf of the co-editors Thomas Bergs and Wolfgang Prinz

Daniel Trauth

January 2021

Meet the contributors

Unfortunately, this first edition of the book is in German only.

Greetings

Introduction

Chapter 1: Rechtliche Aspekte der Datenmonetarisierung

Chapter 2: Betriebswirtschaftliche Aspekte der Datenmonetarisierung

Chapter 3: Informationstechnische Aspekte der Datenmonetarisierung

Chapter 4: Datenmonetarisierung in der fertigenden Industrie

Chapter 5: Datenmonetarisierung in der Energietechnik

Chapter 6: Datenmonetarisierung in weiteren aufkommenden Anwendungsfeldern

senseering Logo | © senseering

About senseering

The senseering GmbH is a company founded in September 2018 that was awarded the RWTH Aachen University Spin-Off-Award. The core competence of senseering GmbH is the development and implementation of systems for the digitalization and networking of industrial and production facilities. Likewise, senseering GmbH advises on strategic corporate issues, in particular digital transformation, distributed-leger technologies, edge vs. cloud computing architectures for AI-based real-time control of industrial processes, digital business model innovation and the introduction of digital business processes such as home office, Azure or Microsoft365. Senseering is one of the winners of the first and largest AI innovation competition of the BMWi with the project www.spaicer.de.

Daniel Trauth (CEO) | www.senseering.de | E-Mail: mail@senseering.de