Andrzej Stefan Ceglowski

Formalizing process-based risk with Value-Focused Process Engineering

Following calls to advance the integration of risk and business process modeling paradigms, this paper formalizes the process of incorporating risk into business process models through the principles of Value-Focused Process Engineering (VFPE). In doing so, the paper aims to extend the existing VFPE modeling notation to reflect a set of necessary constructs required to adequately represent risk in goal-oriented business-process models. The extended set of constructs is proposed to support a formal systems view of process-based risk. Process-based risk is formalized on the one hand, as a product of complex interactions between activity-based elements, and on the other hand, as a natural component of the value creation mechanism of an elementary function or a complex process. The proposed risk-aware VFPE formalism also formulates rules for decomposing risk in process models according to the organizational values, thereby enabling better risk visibility, reducing process complexity, and ensuring continuity of business processes.

Analysis of SCOR’s approach to supply chain risk management

Purpose – SCOR 10.0, released in late 2010, is the second version of the supply chain operations reference model (SCOR) to incorporate risk management processes, metrics and best practices. Given the paucity of studies that have explored the coverage and integration of supply chain risk management (SCRM) within SCOR, the analysis and suggested improvements for SCRM are designed to enhance SCOR’s collaborative and coordinated management of supply chain (SC) risks. The paper aims to dicsuss these issues. Design/methodology/approach – Critical analysis was used to analyse the coverage and integration of SCRM within SCOR 10.0. Findings – Discrepancies were identified in how SCRM has been incorporated into SCOR, including issues with the hierarchical representation of SCRM processes, metrics, best practices and skills. These may potentially propagate into difficulties in embedding risk management processes within other SC processes, visualizing risk metrics in a SC’s value hierarchy and reconciling SCOR’s SCRM...

A framework for an intelligent decision support system: A case in pathology test ordering

Decision context, knowledge management, decision makers, and decision strategy are fundamental components for understanding decision support systems (DSSs). This paper describes the specific case of designing a framework for an intelligent DSS in the context of pathology test ordering by general practitioners (GPs). In doing so it illustrates the processes of discovering practical and relevant knowledge from pathology request data generated and stored in a professional pathology company, investigates and understands the decision makers (GPs) through a survey about their current practices in test ordering and their requirements for decision support, and finally proposes an intelligent decision support framework as the decision strategy to support GPs in ordering pathology tests more effectively and appropriately. The process and framework developed through this case contributes effective guidance for practitioners and theoretical understanding concerning intelligent decision support in a complex environment.

Using Self Organising Feature Maps to Unravel Process Complexity in a Hospital Emergency Department: A Decision Support Perspective

Summary. In systems that are complex and have ill-defined inputs and outputs, and in situations where insufficient data is gathered to permit exhaustive analysis of activity pathways, it is difficult to get at process descriptions. The complexity conceals patterns of activity, even to experts, and the system is resistant to statistical modelling because of its high dimensionality. Such is the situation in hospital emergency departments, as borne out by the paucity of process models for them despite the continued and vociferous efforts of experts over many years. In such complex and ill-defined situations, it may be possible to access fairly complete records of activities that have taken place. This is the case in many hospital emergency departments, where records are routinely kept of procedures that patients undergo. Extracting process definitions from these records by self organized clustering is neither a pure technical analysis, nor a completely social one, but rather somewhere between these extremes. This chapter describe use of Self Organised Feature Maps to reveal general treatment processes – actual work practices – that may be monitored, measured and managed.

Prototyping an Online Elective Surgery Waitlist Management System

Excessive waiting time for elective surgery and a lack of information regarding patients status in the waiting list have left the patients upset and unsatisfied while waiting for their turn to receive the treatment. The situation was made worse by inefficient waitlist management that possibly results in unexpected delay and negative impacts on the health condition of the patients. In this paper, we investigate current waitlist management systems implemented in Australias five states and suggest a design prototype that could better address patient needs and empower them by providing personalised information about their waitlist status and decision support on implications of changing their preferences.

Towards process-of-care aware emergency department information systems: A clustering approach to activity views elicitation

The critical role of emergency departments (EDs) as the first point of contact for ill and injured patients has presented significant challenges for the elicitation of detailed process models. Patient complexity has limited the ability of ED information systems (EDIS) in prediction of patient treatment and patient movement. This article formulates a novel approach to building EDIS Activity Views that paves the way for EDIS that can predict patient workflow. The resulting Activity View pertains to “what is being done,†rather than “what experts think is being done.†The approach is based on analysis of data that is routinely recorded during patient treatment. The practical significance of the proposed approach is clinically acceptable, verifiable, and statistically valid process-oriented clusters of ED activities that can be used for targeted process elicitation, thus informing the design of EDIS. Its theoretical significance is in providing the new “middle ground†between existing “soft†and “computational†process elicitation methods.