Continuous Integration of Risk Management in a Business Process Reengineering: Towards Optimization through Machine Learning

Abstract

To improve their market position and competitiveness, organizations aim to shorten production times, cut costs, and boost the quality and variety of their products. While Business Process Reengineering (BPR) is a good method to achieve these goals, implementing it can be risky: any change to a task in the initial process directly affects the final process's performance in terms of time, cost, and quality. This article, drawing on design science, a literature review, and a field study with responses from executives and managers of two companies in the aerospace and automotive sectors in Morocco to measure their satisfaction and identify their risk management needs, provides an overview of the BPR method, its implementation frameworks and methodologies, and explains the importance of risk management in such projects. It suggests an improved continuous risk management process for BPR projects that enhances the gathering and use of risk management data through machine learning. Doi: 10.28991/ESJ-2024-08-03-019 Full Text: PDF

Keywords

• bpr
• risk management
• continuous integration
• machine learning.