Implementing data-based services: a socio-technical model
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Authors
Author (Corporation)
Publication date
21.07.2022
Typ of student thesis
Course of study
Type
04B - Conference paper
Editors
Leitner, Christine
Ganz, Walter
Bassano, Clara
Satterfield, Debra
Editor (Corporation)
Supervisor
Parent work
The Human Side of Service Engineering
Special issue
DOI of the original publication
Link
Series
AHFE International
Series number
62
Volume
Issue / Number
Pages / Duration
262-270
Patent number
Publisher / Publishing institution
AHFE Open Access
Place of publication / Event location
New York City
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
The trend towards digitalization requires equipment manufacturers to complement their products with data-based services. Successfully implementing appropriate processes into existing organizational structures poses several challenges, which we address in this research. Based on two in-depth case studies together with Swiss industrial companies we developed a sociotechnical model that supports the successful implementation of data-based services. Following, the challenges as well as the model and its application are briefly described. Challenges: Adding data-based services to existing products requires not only new skills, such as the ability to collect valid data or to apply the latest algorithms of data analytics. If needed, such methodological abilities can be obtained on the labor market. Rather, it is a matter of identifying the right indicators on which to base data-driven services, or interpreting the results of analysis in a way that adds value for customers. Consequently, novel methodological abilities need to be combined with in-depth domain expertise. However, the required expertise is usually distributed throughout an organization. This is because, industrial companies over the years optimize their organizational processes and structures regarding the production, commissioning and maintenance of their traditional products. Therefore, experiences and knowledge are gained by different organizational units. Combining this distributed expertise to create synergies in the analysis and interpretation of data can be a major challenge. It becomes even more difficult, when part of the expertise is tacit or when its relevance is not obvious but requires the linking of seemingly unimportant information. Hence, organizational processes and structures must be found that enable co-production and hence the knowledge synergies required for the data-based services. The sociotechnical model: Based on an extended literature review and the needs of our industrial partners we developed a sociotechnical model. It provides operationalized criteria for designing and evaluating organizational processes and structures, which enable knowledge-oriented collaboration. The model is onion-like structured with different spheres. The data-based service to be implemented builds the core of the model. It is surrounded by spheres of technology, knowledge, human workforce, and organizational structures. For each sphere as well as for interfaces between spheres operationalized criteria are provided, which represent preconditions of successful knowledge-oriented collaboration. Examples for the criteria are: process transparency, perceived self-efficacy or mutual trust. Furthermore, the upper hemisphere of the model represents the service provider, whereas its lower hemisphere represents the customer. It is very important to have both included as the targeted synergies require boundary-spanning collaboration between the two. Model application: The model and its criteria are applied when designing the collaboration of everyone required for service delivery. As long as a company still mainly manufactures its traditional mechanical industrial products, it cannot radically reorganize. In this case, the model supports the design of processes and structures of collaboration across organizational boundaries based on defined roles and networking. In periodical meetings the collaboration within these networks is evaluated and optimized by means of the model's criteria. The model as well as its application will be presented in the paper.
Keywords
Subject (DDC)
Event
13th International Conference on Applied Human Factors and Ergonomics
Exhibition start date
Exhibition end date
Conference start date
24.07.2022
Conference end date
28.07.2022
Date of the last check
ISBN
978-1-958651-38-4
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Expert editing/editorial review
Open access category
Gold
License
Citation
Campos, A., Wäfler, T., Havelka, A., & Deflorin, P. (2022). Implementing data-based services: a socio-technical model. In C. Leitner, W. Ganz, C. Bassano, & D. Satterfield (Eds.), The Human Side of Service Engineering (pp. 262–270). AHFE Open Access. https://doi.org/10.54941/ahfe1002566