A Normative Approach for Identifying Decision Propagation Paths in Complex Systems

Abstract

In real-world, making the right decision at the right time is very challenging. Additional complexity is related to the fact that, a change in one part may propagate across multiple subsystems and therefore, it is very difficult to predict how decisions behave. To respond this need, this paper contributes a conceptual framework to present a novel perspective on modelling decisions, so-called Decision Propagation System -DPS. It is an intelligent approach to reflect how organisational dynamics and information dependencies can affect decision propagations, thus helping make Smart decisions.

Predicting Decision Propagation in Complex Sociotechnical System

“…The outcome was a range of alternative models developed to address the outlined business challenges (in Sec. 3) such as the concepts presented in [8] and [1].…”

“…Therefore, the widely-used Change Prediction Method (CPM) [9] was used to identify the risky components and combined with a real-time System Dynamics model to interactively examine how dynamics of those components affect the key performance indicators. In the latter research, a conceptual decision analysis model was developed, based on the Bayesian chain rule, in that the proportional strength of the connectivity between decisions used to compute the Cumulative Confidence Ratio [1]. A primary case within the BT's Field Engineering Division (FED) was considered to assess the plausibility of the proposed concepts.…”

“…New connectivity technologies (such as knowledge-sharing platforms) have transformed the way individuals communicate and influence one another in a dynamic environment. As the result, an upstream decision might affect several consequences concurrently, while each of which might propagate beyond its local impact and globally affect multiple downstream decisions, sometimes without the influenced decision-makers necessarily taking any control over the situation [1][2]. Anticipating the collective risk of consequences in such situations is extremely difficult, and the knowledge of which can infer many implications across organizations towards a better understanding of the emergent system behavior, for example through constructing an individual feedback mechanism for each role to steer a better system performance.…”

BPMN++ to support managing organisational, multiteam and systems engineering aspects in cyber physical production systems design and operation

“…However, they do not take into account Model-Based Systems Engineering (MBSE) approaches and the required coupled tool support to ease cooperation between teams and disciplines, which is mandatory for our approach. Hassannezhad & Clarkson (2018) focus on decisions made in such networks and address the propagation, especially of management decisions, with consideration of organisational dynamics. They developed a conceptual framework that enables modelling of a decision network in order to understand the criticality and consistency of decisions, but did not consider engineering workflow aspects.…”