TECHNICAL ISSUES RELATED TO INTEGRATING MODELLING OF BUSINESS PROCESSES, IS AND COMPUTER NETWORKS Alan Serrano, George M. Giaglis, Ray J. Paul, Department of Information Systems and Computing, Brunel University Abstract Information Systems (IS) and Computer Networks (CN) aim at assisting organisations in realising their business objectives in a more effective and efficient manner. To achieve this goal, Business Processes (BP) and their corresponding systems and networks must be aligned. Simulation modelling in both domains (BP and IS/CN) is widely used to analyse existing operations and propose improvements. However, although it is clear that these organisational facets should be aligned, there is no direct path that bridges them in the simulation domain. This paper investigates approaches to integrating BP and CN simulation environments using IS as the link. 1 INTRODUCTION Since it has been realised that organisations can be studied and analysed according to the business processes they perform, process-based organisational analysis has become a prominent matter of study in both the management science and Information Systems fields (Ould 1995). Processes within an organisation are not static, but they undergo changes in the same direction that the organisation moves towards achieving its objectives. Business Process Reengineering (BPR) is the management area that is concerned with the study of the behaviour of the current processes and how they affect the organisation, as well as studying the organisational environment and proposing changes on those processes that are not aligned with the organisational goals. Business process changes can be classified as radical or soft (Kettinger et al 1997) and may cause disruptions to the organisation activities and may possibly involve significant investments in order to be realised. One way that a proposed process change can be tested without causing disruptions in the real business environment and without requiring significant investments is through modelling and simulation. Simulation can be used to predict, observe and diagnose the behaviour of a phenomenon in order to predict the