Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

Log delta analysis: Interpretable differencing of Business process event logs

This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

Barriers, drivers and enablers for transitioning towards innovation in the Australian water sector

The Australian water sector needs to adapt to effectively deal with the impacts of climate change on its systems. Challenges as a result of climate change include increasingly extreme occurrences of weather events including flooding and droughts (Pittock, 2011). In response to such challenges, the National Water Commission in Australia has identified the need for the water sector to transition towards being readily adaptable and able to respond to complex needs for a variety of supply and demand scenarios (National Water Commission, 2013). To successfully make this transition, the sector will need to move away from business as usual, and proactively pursue and adopt innovative approaches and technologies as a means to successfully address the impacts of climate change on the Australian water sector. In order to effectively respond to specific innovation challenges related to the sector, including climate change, it is first necessary to possess a foundational understanding about the key elements related to innovation in the sector. This paper presents this base level understanding, identifying the key barriers, drivers and enablers, and elements for innovative practise in the water sector. After initially inspecting the literature around the challenges stemming from climate change faced by the sector, the paper then examines the findings from the initial two rounds of a modified Delphi study, conducted with experts from the Australian water sector, including participants from research, government and industry backgrounds. The key barriers, drivers and enablers for innovation in the sector identified during the initial phase of the study formed the basis for the remainder of the investigation. Key elements investigated were: barriers – scepticism, regulation systems, inconsistent policy; drivers – influence of policy, resource scarcity, thought leadership; enablers – framing the problem, effective regulations, community acceptance. There is a convincing argument for the water sector transitioning to a more flexible, adaptive and responsive system in the face of challenges resulting from climate change. However, without first understanding the challenges and opportunities around making this transition, the likelihood of success is limited. For that reason, this paper takes the first step in understanding the elements surrounding innovation in the Australian water sector.

Special issue on best papers from the "BPM 2012" workshops

Business Process Management (BPM) (Dumas et al. 2013) investigates how organizations function and can be improved on the basis of their business processes. The starting point for BPM is that organizational performance is a function of process performance. Thus, BPM proposes a set of methods, techniques and tools to discover, analyze, implement, monitor and control business processes, with the ultimate goal of improving these processes. Most importantly, BPM is not just an organizational management discipline. BPM also studies how technology, and particularly information technology, can effectively support the process improvement effort. In the past two decades the field of BPM has been the focus of extensive research, which spans an increasingly growing scope and advances technology in various directions. The main international forum for state-of-the-art research in this field is the International Conference on Business Process Management, or “BPM” for short—an annual meeting of the aca ...

Analysis and improvement of a construction permit approval process: A teaching case for developing business process development capabilities, targeting developing nations

With the increasing competitiveness in global markets, many developing nations are striving to constantly improve their services in search for the next competitive edge. As a result, the demand and need for Business Process Management (BPM) in these regions is seeing a rapid rise. Yet there exists a lack of professional expertise and knowledge to cater to that need. Therefore, the development of well-structured BPM training/ education programs has become an urgent requirement for these industries. Furthermore, the lack of textbooks or other self-educating material, that go beyond the basics of BPM, further ratifies the need for case based teaching and related cases that enable the next generation of professionals in these countries. Teaching cases create an authentic learning environment where complexities and challenges of the ‘real world’ can be presented in a narrative, enabling students to evolve crucial skills such as problem analysis, problem solving, creativity within constraints as well as the application of appropriate tools (BPMN) and techniques (including best practices and benchmarking) within richer and real scenarios. The aim of this paper is to provide a comprehensive teaching case demonstrating the means to tackle any developing nation’s legacy government process undermined by inefficiency and ineffectiveness. The paper also includes thorough teaching notes The article is presented in three main parts: (i) Introduction - that provides a brief background setting the context of this paper, (ii) The Teaching Case, and (iii) Teaching notes.

A Bayesian model of source monitoring

The Source Monitoring Framework is a promising model of constructive memory, yet fails because it is connectionist and does not allow content tagging. The Dual-Process Signal Detection Model is an improvement because it reduces mnemic qualia to a single memory signal (or degree of belief), but still commits itself to non-discrete representation. By supposing that ‘tagging’ means the assignment of propositional attitudes to aggregates of anemic characteristics informed inductively, then a discrete model becomes plausible. A Bayesian model of source monitoring accounts for the continuous variation of inputs and assignment of prior probabilities to memory content. A modified version of the High-Threshold Dual-Process model is recommended to further source monitoring research.

Linking business goals to process models in semantic business process modeling

Broad knowledge is required when a business process is modeled by a business analyst. We argue that existing Business Process Management methodologies do not consider business goals at the appropriate level. In this paper we present an approach to integrate business goals and business process models. We design a Business Goal Ontology for modeling business goals. Furthermore, we devise a modeling pattern for linking the goals to process models and show how the ontology can be used in query answering. In this way, we integrate the intentional perspective into our business process ontology framework, enriching the process description and enabling new types of business process analysis. © 2008 IEEE.

Mining process risks and resource profiles

This research contributes novel techniques for identifying and evaluating business process risks and analysing human resource behaviour. The developed techniques use predefined indicators to identify process risks in individual process instances, evaluate overall process risk, predict process outcomes and analyse human resource behaviour based on the analysis of information about process executions recorded in event logs by information systems. The results of this research can help managers to more accurately evaluate the risk exposure of their business processes, to more objectively evaluate the performance of their employees, and to identify opportunities for improvement of resource and process performance.

Genome-wide association study using extreme truncate selection identifies novel genes affecting bone mineral density and fracture risk

Osteoporotic fracture is a major cause of morbidity and mortality worldwide. Low bone mineral density (BMD) is a major predisposing factor to fracture and is known to be highly heritable. Site-, gender-, and age-specific genetic effects on BMD are thought to be significant, but have largely not been considered in the design of genome-wide association studies (GWAS) of BMD to date. We report here a GWAS using a novel study design focusing on women of a specific age (postmenopausal women, age 55-85 years), with either extreme high or low hip BMD (age- and gender-adjusted BMD z-scores of +1.5 to +4.0, n = 1055, or -4.0 to -1.5, n = 900), with replication in cohorts of women drawn from the general population (n = 20,898). The study replicates 21 of 26 known BMD-associated genes. Additionally, we report suggestive association of a further six new genetic associations in or around the genes CLCN7, GALNT3, IBSP, LTBP3, RSPO3, and SOX4, with replication in two independent datasets. A novel mouse model with a loss-of-function mutation in GALNT3 is also reported, which has high bone mass, supporting the involvement of this gene in BMD determination. In addition to identifying further genes associated with BMD, this study confirms the efficiency of extreme-truncate selection designs for quantitative trait association studies. © 2011 Duncan et al.

Evidence-based recommendations for the monitoring and treatment of ankylosing spondylitis: Results from the Australian 3E initiative in rheumatology

Aim: To develop a set of Australian recommendations for the monitoring and treatment of ankylosing spondylitis (AS) through systematic literature review combined with the opinion of practicing rheumatologists. Methods: A set of eight questions, four in each domain of monitoring and treatment, were formulated by voting and the Delphi method. The results of a systematic literature review addressing each question were presented to the 23 participants of the Australian 3E meeting. All participants were clinical rheumatologists experienced in the daily management of AS. Results: After three rounds of breakout sessions to discuss the findings of the literature review, a set of recommendations was finalized after discussion and voting. The category of evidence and strength of recommendation were determined for each proposal. The level of agreement among participants was excellent (mean 84%, range 64-100%). Conclusions: The 12 recommendations developed from evidence and expert opinion provide guidance for the daily management of AS patients. For most recommendations, we found a paucity of supportive evidence in the literature highlighting the need for additional clinical studies.

Improving factory performance using an integrated sugar factory model

A whole of factory model of a raw sugar factory was developed in SysCAD software to assess and improve factory operations. The integrated sugar factory model ‘Sugar-SysCAD’ includes individual models for milling, heating and clarification, evaporation, crystallisation, steam cycle, sugar dryer and process and injection water circuits. These individual unit operation models can be either used as standalone models to optimise the unit operation or in the integrated mode to provide more accurate prediction of the effects of changes in any part of the process on the outputs of the whole factory process. Using the integrated sugar factory model, the effect of specific process operations can be understood and practical solutions can be determined to address process problems. The paper presents two factory scenarios to show the capabilities of the whole of factory model.

BPMN process views construction

Process view technology is catching more attentions in modern business process management, as it enables the customisation of business process representation. This capability helps improve the privacy protection, authority control, flexible display, etc., in business process modelling. One of approaches to generate process views is to allow users to construct an aggregate on their underlying processes. However, most aggregation approaches stick to a strong assumption that business processes are always well-structured, which is over strict to BPMN. Aiming to build process views for non-well-structured BPMN processes, this paper investigates the characteristics of BPMN structures, tasks, events, gateways, etc., and proposes a formal process view aggregation approach to facilitate BPMN process view creation. A set of consistency rules and construction rules are defined to regulate the aggregation and guarantee the order preservation, structural and behaviour correctness and a novel aggregation technique, called EP-Fragment, is developed to tackle non-well-structured BPMN processes.

Designing innovative business models with a framework that promotes experimentation

Purpose – Business models to date have remained the creation of management, however, it is the belief of the authors that designers should be critically approaching, challenging and creating new business models as part of their practice. This belief portrays a new era where business model constructs become the new design brief of the future and fuel design and innovation to work together at the strategic level of an organisation. Design/methodology/approach – The purpose of this paper is to explore and investigate business model design. The research followed a deductive structured qualitative content analysis approach utilizing a predetermined categorization matrix. The analysis of forty business cases uncovered commonalities of key strategic drivers behind these innovative business models. Findings – Five business model typologies were derived from this content analysis, from which quick prototypes of new business models can be created. Research limitations/implications – Implications from this research suggest there is no “one right” model, but rather through experimentation, the generation of many unique and diverse concepts can result in greater possibilities for future innovation and sustained competitive advantage. Originality/value – This paper builds upon the emerging research and exploration into the importance and relevance of dynamic, design-driven approaches to the creation of innovative business models. These models aim to synthesize knowledge gained from real world examples into a tangible, accessible and provoking framework that provide new prototyping templates to aid the process of business model experimentation.

Evaluation of hospital preparedness for public health emergencies in Sichuan (China)

The aim of this research was to develop a set of reliable, valid preparedness metrics, built around a comprehensive framework for assessing hospital preparedness. This research used a combination of qualitative and quantitative methods which included interview and a Delphi study as well as a survey of hospitals in the Sichuan Province of China. The resultant framework is constructed around the stages of disaster management and includes nine key elements. Factor Analysis identified four contributing factors. The comparison of hospitals' preparedness using these four factors, revealed that tertiary-grade, teaching and general hospitals performed better than secondary-grade, non-teaching and non-general hospitals.

Business process performance mining with staged process flows

Existing process mining techniques provide summary views of the overall process performance over a period of time, allowing analysts to identify bottlenecks and associated performance issues. However, these tools are not de- signed to help analysts understand how bottlenecks form and dissolve over time nor how the formation and dissolution of bottlenecks – and associated fluctua- tions in demand and capacity – affect the overall process performance. This paper presents an approach to analyze the evolution of process performance via a notion of Staged Process Flow (SPF). An SPF abstracts a business process as a series of queues corresponding to stages. The paper defines a number of stage character- istics and visualizations that collectively allow process performance evolution to be analyzed from multiple perspectives. The approach has been implemented in the ProM process mining framework. The paper demonstrates the advantages of the SPF approach over state-of-the-art process performance mining tools using two real-life event logs publicly available.