Hassannezhad, M., Cassidy, S. and Clarkson, P.J. (2019) Connectivity as the capacity to improve an organization’s decision-making. In: Putnik, G.D., (ed.) 29th CIRP Design Conference 2019. 29th CIRP Design Conference 2019, 08-10 May 2019, Póvoa de Varzim, Portgal. Procedia CIRP, 84 . Elsevier BV , pp. 231-238.
Abstract
This paper describes the development of a new computational model to predict the desirability of decision consequences in an organization, and the development of a prototype tool to enable real-time interaction and decision support when changes occur simultaneously. A tool, called Decision Propagation System, is developed in response to the needs of BT Group plc in understanding the most effective set of interventions in the organization where the high degree of connectivity between system components and the uncertainty in connectivity data are two critical issues. Designed on a case study of the Fields Operations Engineering, this research demonstrates that a knowledge of overlapping decision propagation paths can direct the organizational decisions towards mitigating the risk of unintended consequences.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2019 The Authors. Published by Elsevier B.V. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Complexity; Connectivity; Change propagation; Data-driven engineering design; Decision-making; Multiple domain matrix; Systems engineering |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 21 Apr 2020 10:51 |
Last Modified: | 07 Jul 2020 13:56 |
Status: | Published |
Publisher: | Elsevier BV |
Series Name: | Procedia CIRP |
Refereed: | Yes |
Identification Number: | 10.1016/j.procir.2019.04.222 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159705 |