Konferenzbeitrag

Framework for indicator-based, sociotechnical project risk monitoring

Purpose: Many Industry 4.0 projects fail because impending sociotechnical risks are managed insufficiently. An indicator-based, sociotechnical risk monitoring can help to overcome this challenge. However, its effectiveness depends significantly on selecting appropriate risk indicators. This paper outlines a framework that helps decision-makers with the necessary structuring, allowing for subsequent indicator definition. Methodology: Indicators must be embedded in specific contexts to be meaningful. The design of indicator-based monitoring systems, therefore, first requires an appropriate framework. For this purpose, specific requirements related to digitization projects are derived from both literature and practitioners' needs. Findings: Risks in the context of Industry 4.0 projects are systemic risks. For efficient monitoring, new approaches are needed that can manage this high complexity. Systems theory is found suitable to develop a new framework for indicator-based, sociotechnical project risk monitoring. The framework considers the characteristics of projects and enterprises as complex, open, and sociotechnical systems. Originality: Especially in complex projects like those of Industry 4.0, situational risk awareness can contribute crucially to project success. However, achieving this awareness always requires tailored approaches addressing the unique project characteristics. To help solve this challenge for digitization projects, the proposed framework sets both a science-based and practitioner-relevant foundation for subsequent derivation of sociotechnical risk indicators.

Language
Englisch

Bibliographic citation
hdl:10419/249608

Classification
Management
Subject
Advanced Manufacturing
Industry 4.0

Event
Geistige Schöpfung
(who)
Gauß, Philipp
Parlings, Matthias
Event
Veröffentlichung
(who)
epubli GmbH
(where)
Berlin
(when)
2021

DOI
doi:10.15480/882.3968
Handle
URN
urn:nbn:de:gbv:830-882.0161805
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Konferenzbeitrag

Associated

  • Gauß, Philipp
  • Parlings, Matthias
  • epubli GmbH

Time of origin

  • 2021

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