Improving business process models using observed behavior

Process-aware information systems (PAISs) can be configured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, simplicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality.

Supporting context-aware process design : learnings from a design science study

Recent studies have started to explore context-awareness as a driver in the design of adaptable business processes. The emerging challenge of identifying and considering contextual drivers in the environment of a business process are well understood, however, typical methods and models for business process design do not yet consider this context. In this paper, we describe our work on the design of a method framework and appropriate models to enable a context-aware process design approach. We report on our ongoing work with an Australian insurance provider and describe the design science we employed to develop innovative and useful artifacts as part of a context-aware method framework. We discuss the utility of these artifacts in an application in the claims handling process at the case organization.

A process-oriented approach to supporting Off-site Manufacture in construction projects

It is well-known that the use of off-site manufacture (OSM) techniques can assist in timely completion of a construction project though the utilisation of such techniques may have other disadvantages. Currently, OSM uptake within the Australian construction industry is limited. To successfully incorporate OSM practices within a construction project, it is crucial to understand the impact of OSM adoption on the processes used during a construction project. This paper presents how a systematic process-oriented approach may be able to support OSM utilisation within a construction project. Process modelling, analysis and automation techniques which are well-known within the Business Process Management (BPM) discipline have been applied to develop a collection of construction process models that represent the end-to-end generic construction value chain. The construction value chain enables researchers to identify key activities, resources, data, and stakeholders involved in construction processes in each defined construction phase. The collection of construction process models is then used as a basis for identification of potential OSM intervention points in collaboration with domain experts from the Australian construction industry. This ensures that the resulting changes reflect the needs of various stakeholders within the construction industry and have relevance in practice. Based on the input from the domain experts, these process models are further refined and operational requirements are taken into account to develop a prototype process automation (workflow) system that can support and coordinate OSM-related process activities. The resulting workflow system also has the potential to integrate with other IT solutions used within the construction industry (e.g., BIM, Acconex). As such, the paper illustrates the role that process-oriented thinking can play in assisting OSM adoption within the industry.

Process model comprehension : the effects of cognitive abilities, learning style, and strategy

Process models are used to convey semantics about business operations that are to be supported by an information system. A wide variety of professionals is targeted to use such models, including people who have little modeling or domain expertise. We identify important user characteristics that influence the comprehension of process models. Through a free simulation experiment, we provide evidence that selected cognitive abilities, learning style, and learning strategy influence the development of process model comprehension. These insights draw attention to the importance of research that views process model comprehension as an emergent learning process rather than as an attribute of the models as objects. Based on our findings, we identify a set of organizational intervention strategies that can lead to more successful process modeling workshops.

Process mining for clinical processes: A comparative analysis of four Australian hospitals

Business process analysis and process mining, particularly within the health care domain, remain under-utilised. Applied research that employs such techniques to routinely collected, health care data enables stakeholders to empirically investigate care as it is delivered by different health providers. However, cross-organisational mining and the comparative analysis of processes present a set of unique challenges in terms of ensuring population and activity comparability, visualising the mined models and interpreting the results. Without addressing these issues, health providers will find it difficult to use process mining insights, and the potential benefits of evidence-based process improvement within health will remain unrealised. In this paper, we present a brief introduction on the nature of health care processes; a review of the process mining in health literature; and a case study conducted to explore and learn how health care data, and cross-organisational comparisons with process mining techniques may be approached. The case study applies process mining techniques to administrative and clinical data for patients who present with chest pain symptoms at one of four public hospitals in South Australia. We demonstrate an approach that provides detailed insights into clinical (quality of patient health) and fiscal (hospital budget) pressures in health care practice. We conclude by discussing the key lessons learned from our experience in conducting business process analysis and process mining based on the data from four different hospitals.

Prioritizing process improvement : an example from the Australian financial services sector

Process improvement has become a number one business priority, and more and more project requests are raised in organizations, seeking approval and resources for process-related projects. Realistically, the total of the requested funds exceeds the allocated budget, the number of projects is higher than the available bandwidth, and only some of these (very often only few) can be supported and most never see any light. Relevant resources are scarce, and correct decisions must be made to make sure that those projects that are of best value are implemented. How can decision makers make the right decision on the following: Which project(s) are to be approved and when to commence work on them? Which projects are most aligned with corporate strategy? How can the project’s value to the business be calculated and explained? How can these decisions be made in a fair, justifiable manner that brings the best results to the company and its stakeholders? This chapter describes a business value scoring (BVS) model that was built, tested, and implemented by a leading financial institution in Australia to address these very questions. The chapter discusses the background and motivations for such an initiative and describes the tool in detail. All components and underlying concepts are explained, together with details on its application. This tool has been successfully implemented in the case organization. The chapter provides practical guidelines for organizations that wish to adopt this approach.

What are the secrets of successful process modelling? Insights from an Australian case study

L'intérêt suscité par la ré-ingénierie des processus et les technologies de l'information révèle l'émergence du paradigme du management par les processus. Bien que beaucoup d'études aient été publiées sur des outils et techniques alternatives de modélisation de processus, peu d'attention a été portée à l'évaluation post-hoc des activités de modélisation de processus ou à l'établissement de directives sur la façon de conduire efficacement une modélisation de processus. La présente étude a pour objectif de combler ce manque. Nous présentons les résultats d'une étude de cas détaillée, conduite dans une organisation leader australienne dans le but de construire un modèle de réussite de la modélisation des processus.

Industry based rehabilitation and closure knowledge management system : scoping study

The Central Queensland Mine Rehabilitation Group (CQMRG) has hosted mine site rehabilitation inspections combined with technical workshops for more than 20 years. It was recognised at CQMRG's anniversary meeting in April 2013 that the vast body of knowledge held by rehabilitation and closure planning practitioners was being lost as senior rehabilitation experts retire from the industry. It was noted that even more knowledge could be readily lost unless a knowledge management platform was developed to capture, store and enable retrieval of this information. This loss of knowledge results in a significant cost to industry. This project was therefore undertaken to review tools which have the capability to gather the less formal knowledge as well as to make links to existing resources and bibliographic material. This scoping study evaluated eight alternative knowledge management systems to provide guidance on the best method of providing the industry with an up-to-date, good practice, knowledge management system for rehabilitation and closure practices, with capability for information sharing via a portal and discussion forum. This project provides guidance for a larger project which will implement the knowledge management system to meet the requirements of the CQMRG and be transferrable to other regions if applicable. It will also provide the opportunity to identify missing links between existing tools and their application. That is, users may not be aware of how these existing tools can be used to assist with mine rehabilitation planning and implementation and the development of a new platform will help to create those linkages. The outcomes of this project are directed toward providing access to a live repository of rehabilitation practice information which is Central Queensland coal mine-specific, namely: highlighting best practice activities, results of trials and innovative practices; updated legislative requirements; links to practices elsewhere; and informal anecdotal information relevant to particular sites which may be of assistance in the development of rehabilitation of new areas. Solutions to the rehabilitation of challenging spoils/soils will also be provided. The project will also develop a process which can be applied more broadly within the mining sector to other regions and other commodities. Providing a platform for uploading information and holding discussion forums which can be managed by a regional practitioner network enables the new system to be kept alive, driven by users and information needs as they evolve over time. Similar internet-based platforms exist and are managed successfully. The preferred knowledge management system will capture the less formal and more difficult to access knowledge from rehabilitation and mine closure practitioners and stakeholders through the CQMRG and other contributors. It will also provide direct links, and greater accessibility, to more formal sources of knowledge with anticipated cost savings to the industry and improved rehabilitation practices with successful transitioning to closure and post-mining land use.

Knowledge management challenges in small-and medium-sized enterprises

Background & Research Focus Managing knowledge for innovation and organisational benefit has been extensively investigated in studies of large firms (Smith, Collins & Clark, 2005; Zucker, et al., 2007) and to a large extent there is limited research into studies of small- and medium- sized enterprises (SMEs). There are some investigations in knowledge management research on SMEs, but what remains to be seen in particular is the question of where are the potential challenges for managing knowledge more effectively within these firms? Effective knowledge management (KM) processes and systems lead to improved performance in pursuing distinct capabilities that contribute to firm-level innovation (Nassim 2009; Zucker et al. 2007; Verona and Ravasi 2003). Managing internal and external knowledge in a way that links it closely to the innovation process can assist the creation and implementation of new products and services. KM is particularly important in knowledge intensive firms where the knowledge requirements are highly specialized, diverse and often emergent. However, to a large extent the KM processes of small firms that are often the source of new knowledge and an important element of the value networks of larger companies have not been closely studied. To address this gap which is of increasing importance with the growing number of small firms, we need to further investigate knowledge management processes and the ways that firms find, capture, apply and integrate knowledge from multiple sources for their innovation process. This study builds on the previous literature and applies existing frameworks and takes the process and activity view of knowledge management as a starting point of departure (see among others Kraaijenbrink, Wijnhoven & Groen, 2007; Enberg, Lindkvist, & Tell, 2006; Lu, Wang & Mao, 2007). In this paper, it is attempted to develop a better understanding of the challenges of knowledge management within the innovation process in small knowledge-oriented firms. The paper aims to explore knowledge management processes and practices in firms that are engaged in the new product/service development programs. Consistent with the exploratory character of the study, the research question is: How is knowledge integrated, sourced and recombined from internal and external sources for innovation and new product development? Research Method The research took an exploratory case study approach and developed a theoretical framework to investigate the knowledge situation of knowledge-intensive firms. Equipped with the conceptual foundation, the research adopted a multiple case study method investigating four diverse Australian knowledge-intensive firms from IT, biotechnology, nanotechnology and biochemistry industries. The multiple case study method allowed us to document in some depth the knowledge management experience of the theses firms. Case study data were collected through a review of company published data and semi-structured interviews with managers using an interview guide to ensure uniform coverage of the research themes. This interview guide was developed following development of the framework and a review of the methodologies and issues covered by similar studies in other countries and used some questions common to these studies. It was framed to gather data around knowledge management activity within the business, focusing on the identification, acquisition and utilisation of knowledge, but collecting a range of information about subject as well. The focus of the case studies was on the use of external and internal knowledge to support their knowledge intensive products and services. Key Findings Firstly a conceptual and strategic knowledge management framework has been developed. The knowledge determinants are related to the nature of knowledge, organisational context, and mechanism of the linkages between internal and external knowledge. Overall, a number of key observations derived from this study, which demonstrated the challenges of managing knowledge and how important KM is as a management tool for innovation process in knowledge-oriented firms. To summarise, findings suggest that knowledge management process in these firms is very much project focused and not embedded within the overall organisational routines and mainly based on ad hoc and informal processes. Our findings highlighted lack of formal knowledge management process within our sampled firms. This point to the need for more specialised capabilities in knowledge management for these firms. We observed a need for an effective knowledge transfer support system which is required to facilitate knowledge sharing and particularly capturing and transferring tacit knowledge from one team members to another. In sum, our findings indicate that building effective and adaptive IT systems to manage and share knowledge in the firm is one of the biggest challenges for these small firms. Also, there is little explicit strategy in small knowledge-intensive firms that is targeted at systematic KM either at the strategic or operational level. Therefore, a strategic approach to managing knowledge for innovation as well as leadership and management are essential to achieving effective KM. In particular, research findings demonstrate that gathering tacit knowledge, internal and external to the organization, and applying processes to ensure the availability of knowledge for innovation teams, drives down the risks and cost of innovation. KM activities and tools, such as KM systems, environmental scanning, benchmarking, intranets, firm-wide databases and communities of practice to acquire knowledge and to make it accessible, were elements of KM. Practical Implications The case study method that used in this study provides practical insight into the knowledge management process within Australian knowledge-intensive firms. It also provides useful lessons which can be used by other firms in managing the knowledge more effectively in the innovation process. The findings would be helpful for small firms that may be searching for a practical method for managing and integrating their specialised knowledge. Using the results of this exploratory study and to address the challenges of knowledge management, this study proposes five practices that are discussed in the paper for managing knowledge more efficiently to improve innovation: (1) Knowledge-based firms must be strategic in knowledge management processes for innovation, (2) Leadership and management should encourage various practices for knowledge management, (3) Capturing and sharing tacit knowledge is critical and should be managed, (4)Team knowledge integration practices should be developed, (5) Knowledge management and integration through communication networks, and technology systems should be encouraged and strengthen. In sum, the main managerial contribution of the paper is the recognition of knowledge determinants and processes, and their effects on the effective knowledge management within firm. This may serve as a useful benchmark in the strategic planning of the firm as it utilises new and specialised knowledge.

Exploring location-dependency in process modeling

Purpose – Context-awareness has emerged as an important principle in the design of flexible business processes. The goal of the research is to develop an approach to extend context-aware business process modeling toward location-awareness. The purpose of this paper is to identify and conceptualize location-dependencies in process modeling. Design/methodology/approach – This paper uses a pattern-based approach to identify location-dependency in process models. The authors design specifications for these patterns. The authors present illustrative examples and evaluate the identified patterns through a literature review of published process cases. Findings – This paper introduces location-awareness as a new perspective to extend context-awareness in BPM research, by introducing relevant location concepts such as location-awareness and location-dependencies. The authors identify five basic location-dependent control-flow patterns that can be captured in process models. And the authors identify location-dependencies in several existing case studies of business processes. Research limitations/implications – The authors focus exclusively on the control-flow perspective of process models. Further work needs to extend the research to address location-dependencies in process data or resources. Further empirical work is needed to explore determinants and consequences of the modeling of location-dependencies. Originality/value – As existing literature mostly focusses on the broad context of business process, location in process modeling still is treated as “second class citizen” in theory and in practice. This paper discusses the vital role of location-dependencies within business processes. The proposed five basic location-dependent control-flow patterns are novel and useful to explain location-dependency in business process models. They provide a conceptual basis for further exploration of location-awareness in the management of business processes.

Virtual business role-play : leveraging familiar environments to prime stakeholder memory during process elicitation

Business process models have traditionally been an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach for process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions as they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. Empirical data obtained in this study suggests that this approach may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Noise Filtering of Process Execution Logs based on Outliers Detection

This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

Process visualization techniques for multi-perspective process comparisons

Organizations executing similar business processes need to understand the differences and similarities in activities performed across work environments. Presently, research interest is directed towards the potential of visualization for the display of process models, to support users in their analysis tasks. Although recent literature in process mining and comparison provide several methods and algorithms to perform process and log comparison, few contributions explore novel visualization approaches. This paper analyses process comparison from a design perspective, providing some practical visualization techniques as anal- ysis solutions (/to support process analysis). The design of the visual comparison has been tackled through three different points of view: the general model, the projected model and the side-by-side comparison in order to support the needs of business analysts. A case study is presented showing the application of process mining and visualization techniques to patient treatment across two Australian hospitals.