Data-Based Stakeholder Identification in Technical Change Management

Fabian Sippl, Renè Magg, Carla Paulina Gil, Steffen Düring, Gunther Reinhart

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

The efficient and effective handling of technical changes in product and production is seen as an important factor for the long-term success of manufacturing companies. Within the associated processes, the engineering and manufacturing change management, the identification and involvement of all relevant stakeholders, i.e., departments and employees, plays an essential role. Overlooking relevant stakeholders can lead to unforeseen impacts, such as production stops or further necessary changes, and can cause unforseen increased costs. In particular, in large companies, this task is complex and error-prone due to the high number of changes and departments involved, as well as the abundant variety of changes that can take place. Therefore, this contribution introduces an approach for stakeholder identification in technical change management, which allows the automated identification of relevant stakeholders at the beginning of the reactive phases of the change management process. The approach describes all necessary steps from data preparation to the evaluation of the obtained classification models. It is based on a text-classification approach and focuses in particular on the additional integration of expert knowledge to increase model quality. The approach has been successfully applied in cooperation with a German automotive company, and the obtained model quality has been compared to an expert-based classification.

Original languageEnglish
Article number8205
JournalApplied Sciences (Switzerland)
Volume12
Issue number16
DOIs
StatePublished - Aug 2022
Externally publishedYes

Keywords

  • change management
  • engineering
  • manufacturing
  • stakeholder identification
  • text classification

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