SNACH a new framework to support business process improvement.

Abstract

Business processes are central to any organisation. They coordinate activities, roles, resources, systems and constraints within and across organisational boundaries to achieve predefined business goals. The demand for dynamic business environments, customer satisfaction, global competition, system integration, operational efficiency, innovation and adaptation to market changes necessitates the need for continuous process improvement. In order to adequately respond to these demands, business processes are designed in two approaches: Business Process Re-engineering (BPR) and Business Process Improvement (BPI). This thesis follows the BPI approach which considers existing infrastructure in an organization to improve operational efficiency and achieve organisational goals. Many methodologies have been developed for conducting BPI projects, but they provide little support for the actual act of systematically improving a business process. We adopted case study as the research strategy to examine a collaborative business process, specifically the UK Higher Education Institutions (HEI) admission process. The design science research methodology was used to answer the research questions and satisfy the research objectives. The Map technique was employed to construct the new BPI artefact based on the Mandatory Elements of Method (MEM) from Method Engineering. The new BPI framework comprises of a number of elements to support analysts and practitioners in process improvement activities. We present a novel approach to BPI, the SNACH (Simulation Network Analysis Control flow complexity and Heuristics) framework that supports the actual act of process improvement using a combination of process analysis techniques with integrated quantitative measurable concepts to measure and visualize improvement in four dimensions: cost, cycle time, flexibility and complexity. A simulation technique was employed to analyse the process models in terms of time and cost; and Control Flow Complexity was used to calculate the logical complexity of the process model. A complex network analysis approach was used to provide information about the structural relationship and information exchange between process activities. Using a complex network analysis approach to reduce a process model to a network of nodes and links so that its structural properties are analysed to provide information about the structural complexity and flexibility of the network. To achieve this higher level of abstraction, an algorithm was defined and validated using four disparate process models. The complex network analysis technique is integrated into the SNACH framework and its significance lies in the study of the nature of the individual nodes and the pattern of connections in the network. These characteristics are assessed using network metrics to quantitatively analyse the structure of the network, thereby providing insight into the interaction and behavioural structure of the business process activities. To conclude the design science research process phases, the artefact was evaluated in terms of its effectiveness and efficiency to systematically improve a business process by conducting an experiment using another use case.