How the digital transformation is changing businesses

Alexander Arzt, research fellow in the Data Mining and Value Creation project, reports from the Spring Servitization Conference 2019.

Three sentences on the contents of the conference

Due to the digital change and the increasing availability of data, the service landscape in companies is changing.

This facilitates new data-driven services and expanded service offerings, entails changes in business models, the market and competition, and has an impact on organizational requirements and corporate strategies.

Representatives from Scania, SAAB AB, Toyota Material Handling Europe and Electrolux reported on how they are coordinating change in their companies, for example by developing necessary competencies and skills, or by outsourcing certain services to other companies or to value creation networks.

© Alexander Arzt

Not only was the conference itself interesting, the atmosphere was also very pleasant.

Personal conclusion of Alexander Arzt

“The conference gave me a good overview of what topics are currently being discussed in business and science and in which areas there is still a need for research. I was particularly interested in the aspects that play a role in the digital transformation and the establishment of data-driven services in companies, and in the challenges and solutions that result from them. Last but not least, I also benefited from the positive feedback and constructive impulses on our research poster, which I presented at the conference.”

Business Model Innovations for Competing on IoT Platform Battleground

 

The poster describes our research on business models and the development of IoT (Internet of Things) platforms, which we see as a great opportunity but also a challenge for industrial companies.

© Data Mining and Value Creation

The first part of the poster shows the three growth paths we have identified that industrial companies can pursue to overcome the digitalization paradox.

  1. First, companies need to embed digital technologies into their physical products, such as machines and equipment, to enhance the functionality of their products and increase the value proposition to customers.
  2. Companies can use connectivity technologies to network their products over the internet to gain insight, monitor and analyze customer product usage. This enables companies to derive improvement potential for the products, identify new service requirements for the customer or develop usage or performance-based payment models.
  3. The establishment of an IoT platform-based application business is a further growth path that paves the way for the company into the digital service business. Companies use the diverse data available from their networked products and combine them with machine learning or artificial intelligence technologies to analyze and optimize customer processes and solve customer problems. Ultimately, they sell software applications as digital services.
© Data Mining and Value Creation

IoT platforms can seldom be set up on their own and used economically. Instead, they encompass an ecosystem as a value creation network made up of various actors and levels. The second part of the poster illustrates this ecosystem and gives examples for the different actors. Numerous questions are still open in this context and will be investigated within the framework of our research:

  • Will few platforms dominate the market or can many different platforms coexist and even benefit from data exchange?
  • Will certain actors within the ecosystem claim a disproportionate share of the value creation for themselves?
  • How can the ecosystem be regulated?
  • Which business models are conceivable on IoT platforms and which are particularly promising?
© Data Mining and Value Creation

The third part of the poster outlines implications of the IoT platform business for the components of the business model (value proposition, value creation, revenue mechanism). In addition, we try to distinguish and categorize IoT platforms based on the design of the business model. To this end, we list initial ideas for possible categories in which existing IoT platforms should be classified.

Contact

Alexander Arzt

Contact Press / Media

Alexander Arzt

Research Fellow Data Mining and Value Creation

Fraunhofer Center for International Management and Knowledge Economy IMW
Neumarkt 9-19
04109 Leipzig, Germany

Phone +49 341 231039-274

Fax +49 341 231039-9274