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Course module: JM2000-M-6
JM2000-M-6
Servitization and Data-Driven Innovation
Course info
Course moduleJM2000-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Economics and Management; TISEM Other;
Is part of
M Data Science and Entrepreneurship (joint degree)
Lecturer(s)
Lecturer
F.C.A. van Leeuwen
Other course modules lecturer
Lecturer
Y.K. Leung
Other course modules lecturer
Academic year2020
Starting block
SM 2
Course mode
Full-time
Remarks-
Registration openfrom 19/01/2021 up to and including 20/08/2021
Content
What is Servitization?
Servitization is the process of integrating products and services to add value for customers (Vandermerwe & Rada, 1988). An increasing number of manufacturers are considering servitization for a number of reasons: to remain strategically relevant in times of commoditization, to offer an alternative to low-cost competitors, to address higher customer expectations, and to make better use of constant technological innovation (Baines et al., 2007; Matthyssens & Vandenbempt, 2008; Vandermerwe & Rada, 1988). Well-known examples of servitization include Rolls-Royce Aero Space, which provides Power-by-the-Hour service to airline companies instead of aircraft engines. Another example is Philips, which provides light as a service instead of a product to Schiphol Airport.

What is the role of data science in servitization?
Unlike the supply chain of a traditional manufacturer, servitization requires a responsive system powered by real-time information (Johnson & Mena, 2008). As such, there is increasing interest in using new technology, such as the Internet of Things, built-in sensors, 5G technology, for servitization, which is known as digital servitization (Paschou et al., 2017; Vendrell-Herrero & Wilson, 2017). Digital servitization provides a huge potential to increase the competitive advantages of a company in different ways, such as optimizing the maintenance efficiency and effectiveness of the product, creating new revenue streams, creating new ways for increased interaction, and connectivity with customers to name a few (Coreynen, Matthyssens, & Van Bockhaven, 2017; Lilien, 2016).


Aim
Enabled by new technology and the availability of data, suppliers and buyers in the agricultural sector have been changing their business models to cope with the opportunities and threats that arise from new technology and an increasing amount of data. In this course, you will learn and understand servitization in the agri-food domain through multiple perspectives. These include:
  1. Academic perspectives: To understand the concept of servitization, types of services, organizational levers to upscale services, digital pathways for servitization, financial benefits and risks, and failure of servitization.
  2. Data science perspectives: To apply data science methods to generate insights from real-world sensor data to inform decision-making strategy.
  3. Business perspectives: To learn from the experience of existing companies that apply servitization to deliver value to their customers.
  4. Entrepreneurship perspectives: To gain hands-on experience of starting a business with servitization by developing a business model.
Learning objectives
Upon successful completion of this course, you will:
  • Understand the meaning and complexity of servitization, its opportunities and pitfalls for product-oriented companies, and also other organizations.
  • Be able to prepare, analyze, and interpret data to facilitate decision-making and servitization. 
  • Have acquired a real-world perspective from companies on how servitization is applied in practice and what motivates them to choose a service-oriented business model.
  • Be able to develop business models for companies and examine their profitability.
Type of instructions
Lectures, workshops, presentations. Most of the class activities will be arranged online via Zoom. Offline sessions will be arranged at the Mariënburg campus in Den Bosch (JADS).

Type of assessments
Individual assignment, individual presentation, group assignment, group presentation, and in-class participation and engagement.

Contact person
Y.K. Leung (y.k.leung@tilburguniversity.edu)

Specifics
The courses from the Data Science and Entrepreneurship program require specific prior knowledge. It is only possible to participate in this course if approved by the admission committee and if you are enrolled for the program. Please note that this course will be taught in Mariënburg, ‘s-Hertogenbosch (JADS). For more information, contact the Program Coordinator (via education.support@jads.nl).
Contact person
Y.K. Leung
Timetable information
Servitization and Data-Driven Innovation
Required materials
-
Recommended materials
-
Tests
Final grade

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