Development of a knowledge based supply chain risk identification system

Abstract

Supply Chain (SC) nowadays is characterized with vastly intertwined networks which may consist of hundreds of firms and may be located across the continents. SC risks occur as a consequence of lack of understanding of potential disturbances in the business networks which have grown exponentially due to global trading, and also improper risk management. Thus, preventive measures need to be taken by every organisation in the supply chain network to manage and mitigate these risks. Risk identification is the first and crucial step in Supply Chain Risk Management (SCRM) process. However, the complexity of supply chain networks and uncertainty of environment they operate in, makes extremely challenging to identify risks in supply chain. Moreover, the types and number of SC risks also vary across different process strategies used by organizations. Accordingly, it is difficult to manage these risks without a decision-support tool. Such a tool utilizing a Knowledge Based System (KBS) approach can assist decision makers to identify most if not all of these SC risks. Although there are considerable numbers of publications on SCRM and KBS, a decision support tool which could identify majority of critical SC risks and their interrelationships with other risks have not been developed using a KBS approach which is flexible enough to assist several process strategies. This thesis presents the development and validation of a decision support tool called Supply Chain Risk Identification System (SCRIS) in order to: (1) Assist manufacturing organizations in identifying their SC risks by providing potential SC risks based on organizations internal and external SC network environment including the product(s) they design, manufacture and deliver, (2) Recognize most (if not all) of SC risks and the interactions between these risks, (3) Consider several risks inherent in different process strategies, namely: Make to Stock, Make to Order and Engineer to Order. SCRIS are successfully validated in industry at four manufacturing organizations. SCRIS provides a bird's eye view of SC risks inherent in SC networks and between SC partners and assist decision-makers to better manage SC risks. It can be used as a formal/informal documentation tool as well and can be updated to include emerging future risk types.