Author
Listed:
- Thomas B. Ladinig
- Krishna S. Dhir
- Gyula Vastag
Abstract
Production management teams often face unfamiliar situations where each team member must understand new phenomena individually before the team can make mutually understandable and acceptable decisions. Contradicting subjective judgments can distort the group’s decision-making process because team members understand situations differently and are generally prone to behavioural biases. This paper presents the development of a sensemaking support system (S3,S cube) for selecting improvement projects in a complex,small-volume batch production system of a premium car manufacturer. All phases of the sensemaking process are facilitated by making various sources of information available to a team of managers and experts to reduce conflicts regarding the selection of improvement projects. S3 is based on a lens model which combines judgments of the management team with discrete event simulation and provides visual representations of the differences and misjudgements related to various improvement options. The results – that can easily be generalised to many similar settings – indicate different understanding and lack of coherence within the management team which prevents them from defining mutually acceptable actions. This is countered with the creation of an action proposal,summarising and visualising causal relationships,and connecting them to improvement options to improve performance of the production system.
Suggested Citation
Thomas B. Ladinig & Krishna S. Dhir & Gyula Vastag, 2021.
"Sensemaking support system (S3) for manufacturing process improvement,"
International Journal of Production Research, Taylor & Francis Journals, vol. 59(8), pages 2406-2425, April.
Handle:
RePEc:taf:tprsxx:v:59:y:2021:i:8:p:2406-2425
DOI: 10.1080/00207543.2020.1733700
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