Formulating optimal business process change decisions using a computational hierarchical change management structure framework: A case study

Abdulrahman Alrabiah (School of Information and Communication Technology, Griffith University Gold Coast Campus, Southport, Australia and Saudi Arabian Monetary Authority, Riyadh, Saudi Arabia)
Steve Drew (Tasmanian Institute of Learning and Teaching, Academic Division, University of Tasmania, Hobart, Australia)

Journal of Systems and Information Technology

ISSN: 1328-7265

Publication date: 14 May 2018



This paper first aims to examine how business process change decisions (BPCDs) were implemented in a government organisation bound by tightly coupled temporal constraints (TTCs). Second, it focuses on how to achieve optimal and efficient BPCDs that require tight compliance with regulators’ temporal constraints. Finally, it formulates a rigorous framework that can facilitate the execution of optimal BPCDs with maximum efficiency and minimal effort, time and cost.


Decision-making biases by individuals or groups in organisations can impede optimal BPC implementation; to demonstrate this, a case study is investigated and the formulated framework is applied to tackle these failings.


The case study analysis shows 76 per cent of the BPCDs implemented were inefficient, mostly because of poor decisions, and these resulted in negative ripple effects. In response, the newly developed hierarchical change management structure (HCMS) framework was used to empower organisations to execute high-velocity BPCDs, enabling them to handle any temporal constraints imposed by regulators or other exogenous factors. The HCMS framework was found to be highly effective, scoring an average improvement of more than 100 per cent when measured using decision quality dimensions. This paper would be of value for business executives and strategic decision makers engaging with BPC.

Research limitations/implications

The HCMS framework has been applied in a single case study as a proof of concept. Future research could extend its application to broader domains that have multi-attribute structures and environments. The evaluation processes of the proposed framework are based on subjective metrics. Causal links from the framework to business process metrics will provide a more complete performance picture.

Practical implications

The outcome of this research assists in formulating a systematic BPCD framework that is otherwise unavailable. The practical use of the proposed framework would potentially impact on quality outcomes for organisations. The model is derived from decision trees and analytical hierarchical processes and is tailored to address this problematic area. The proposed HCMS framework would help organisations to execute efficient BPCDs with minimal time, effort and cost. The HCMS framework contributes to the academic literature on BPCD that leverages diverse stakeholders to engage in BPC initiatives.


The research presents a novel framework –HCMS – that provides a platform for organisations to easily determine and solve hierarchical decision structure problems, thereby allowing them to efficiently automate and institutionalise optimal BPCDs.



Alrabiah, A. and Drew, S. (2018), "Formulating optimal business process change decisions using a computational hierarchical change management structure framework: A case study", Journal of Systems and Information Technology, Vol. 20 No. 2, pp. 207-240.

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