Predicting decision propagation in complex sociotechnical system

作     者：Hassannezhad, Mohammad Cassidy, Steve Clarkson, P. John 

作者机构：Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom Engineering Design Centre Department of Engineering University of Cambridge United Kingdom Future Organizations Lab British Telecommunications Ipswich United Kingdom 

出 版 物：《TechRxiv》 (TechRxiv)

年 卷 期：2021年

核心收录：

主　　题：Decision making 

摘      要：Making informed decisions in today’s ever more connected organizations requires a proactive approach to quantify the desirability of its possible consequences. A prominent problem within this realm is that the consequence of an individual’s decision might propagate far beyond its local impact and globally affect multiple decisions and the entire system, often with amplifying and overlapping sphere of influences. Despite numerous efforts, the algorithmic complexity of overlapping propagation paths in a dense network is not resolved yet. This paper presents the development of a new computational model to tackles this problem from the window of change prediction. The proposed method, called Decision Propagation Method, aims to direct organizational decisions towards the most efficient set of sociotechnical interventions through predicting the risk of concurrent decision propagations. Designed on a case study in the Operations Engineering Group in British Telecom, it is illustrated that the proposed method, supported by an interactive prototype tool, offers a dynamic change prediction at a far less computational complexity and a better reproducibility which also requires less domain Knowledge from the experts. © 2021, CC BY-NC-SA.