Understanding the behavior of workshop facilitators in systems analysis and design projects: Developing theory from process modeling projects

Organizational and technological systems analysis and design practices such as process modeling have received much attention in recent years. However, while knowledge about related artifacts such as models, tools, or grammars has substantially matured, little is known about the actual tasks and interaction activities that are conducted as part of analysis and design acts. In particular, key role of the facilitator has not been researched extensively to date. In this paper, we propose a new conceptual framework that can be used to examine facilitation behaviors in process modeling projects. The framework distinguishes four behavioral styles in facilitation (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that a facilitator can adopt. To distinguish between the four styles, we provide a set of ten behavioral anchors that underpin facilitation behaviors. We also report on a preliminary empirical exploration of our framework through interviews with experienced analysts in six modeling cases. Our research provides a conceptual foundation for an emerging theory for describing and explaining different behaviors associated with process modeling facilitation, provides first preliminary empirical results about facilitation in modeling projects, and provides a fertile basis for examining facilitation in other conceptual modeling activities.

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.

Evidence-based business process management: Using digital opportunities to drive organizational innovation

Process improvement and innovation are risky endeavors, like swimming in unknown waters. In this chapter, I will discuss how process innovation through BPM can benefit from Research-as-a-Service, that is, from the application of research concepts in the processes of BPM projects. A further subject will be how innovations can be converted from confidence-based to evidence-based models due to affordances of digital infrastructures such as large-scale enterprise soft-ware or social media. I will introduce the relevant concepts, provide illustrations for digital capabilities that allow for innovation, and share a number of key takeaway lessons for how organizations can innovate on the basis of digital opportunities and principles of evidence-based BPM: the foundation of all process decisions in facts rather than fiction.

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.

Three-dimensional printing in the construction industry: A review

3D printing (3Dp) has long been used in the manufacturing sector as a way to automate, accelerate production and reduce waste materials. It is able to build a wide variety of objects if the necessary specifications are provided to the printer and no problems are presented by the limited range of materials available. With 3Dp becoming cheaper, more reliable and, as a result, more prevalent in the world at large, it may soon make inroads into the construction industry. Little is known however, of 3Dp in current use the construction industry and its potential for the future and this paper seeks to rectify this situation by providing a review of the relevant literature. In doing this, the three main 3Dp methods of contour crafting, concrete printing and D-shape 3Dp are described which, as opposed to the traditional construction method of cutting materials down to size, deliver only what is needed for completion, vastly reducing waste. Also identified is 3Dp’s potential to enable buildings to be constructed many times faster and with significantly reduced labour costs. In addition, it is clear that construction 3Dp can allow the further inclusion of Building Information Modelling into the construction process - streamlining and improving the scheduling requirements of a project. However, current 3Dp processes are known to be costly, unsuited to large-scale products and conventional design approaches, and have a very limited range of materials that can be used. Moreover, the only successful examples of construction in action to date have occurred in controlled laboratory environments and, as real world trials have yet to be completed, it is yet to be seen whether it can be it equally proficient in practical situations. Key Words: 3D Printing; Contour Crafting; Concrete Printing; D-shape; Building Automation.

Liquid Business Process Model Collections

Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Nursing and medical perceptions of a hospital rapid response system: New process but same old game?

Perhaps no other patient safety intervention depends so acutely on effective interprofessional teamwork for patient survival than the hospital rapid response system (RRS). Yet little is known about nurse-physician relationships when rescuing at-risk patients. This study compared nursing and medical staff perceptions of a mature RRS at a large tertiary hospital. Findings indicate the RRS may be failing to address a hierarchical culture and systems-level barriers to early recognition and response to patient deterioration.

Process quality indicators targeting cognitive impairment to support quality of care for older people with cognitive impairment in emergency departments

Objectives The objective of this study was to develop process quality indicators (PQIs) to support the improvement of care services for older people with cognitive impairment in emergency departments (ED). Methods A structured research approach was taken for the development of PQIs for the care of older people with cognitive impairment in EDs, including combining available evidence with expert opinion (phase 1), a field study (phase 2), and formal voting (phase 3). A systematic review of the literature identified ED processes targeting the specific care needs of older people with cognitive impairment. Existing relevant PQIs were also included. By integrating the scientific evidence and clinical expertise, new PQIs were drafted and, along with the existing PQIs, extensively discussed by an advisory panel. These indicators were field tested in eight hospitals using a cohort of older persons aged 70 years and older. After analysis of the field study data (indicator prevalence, variability across sites), in a second meeting, the advisory panel further defined the PQIs. The advisory panel formally voted for selection of those PQIs that were most appropriate for care evaluation. Results In addition to seven previously published PQIs relevant to the care of older persons, 15 new indicators were created. These 22 PQIs were then field tested. PQIs designed specifically for the older ED population with cognitive impairment were only scored for patients with identified cognitive impairment. Following formal voting, a total of 11 PQIs were included in the set. These PQIs targeted cognitive screening, delirium screening, delirium risk assessment, evaluation of acute change in mental status, delirium etiology, proxy notification, collateral history, involvement of a nominated support person, pain assessment, postdischarge follow-up, and ED length of stay. Conclusions This article presents a set of PQIs for the evaluation of the care for older people with cognitive impairment in EDs. The variation in indicator triggering across different ED sites suggests that there are opportunities for quality improvement in care for this vulnerable group. Applied PQIs will identify an emergency services' implementation of care strategies for cognitively impaired older ED patients. Awareness of the PQI triggers at an ED level enables implementation of targeted interventions to improve any suboptimal processes of care. Further validation and utility of the indicators in a wider population is now indicated.

Effect and process evaluations of an early childhood obesity prevention intervention

The thesis develops a summative evaluation framework of the NOURISH Randomised Controlled Trial, and applies this to a selection of maternal feeding choice outcomes of the programme. The research is based on an ecological model of the complex set of factors that need to be acted upon to address childhood obesity. The novel approach extends the standard RCT effect evaluation, while also conducting an in-depth evaluation of the process of programme development and implementation. Research findings identify adaptations of intervention delivery that could improve its effectiveness and translatability, in a new cycle of the programme.

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.

Technology adoption as a multi-stage process

This study proposes that technology adoption be considered as a multi-stage process constituting several distinct stages. Using the Theory of Planned Behaviour (TPB), Ettlie’s adoption stages and by employing data gathered from 162 owners of Small and Medium-sized Enterprises (SMEs), our findings show that the determinants of the intention to adopt packaged software fluctuate significantly across adoption stages.

Design process

Christina Waterson interviews Queensland interior designer Marisha McAuliffe about her PhD research into process, and why some people are drawn to create.

Are there generalizable trends in the release of airborne synthetic clay nanoparticles from a jet milling process?

Despite recent efforts to assess the release of nanoparticles to the workplace during different nanotechnology activities, the existence of a generalizable trend in the particle release has yet to be identified. This study aimed to characterize the release of synthetic clay nanoparticles from a laboratory-based jet milling process by quantifying the variations arising from primary particle size and surface treatment of the material used, as well as the feed rate of the machine. A broad range of materials were used in this study, and the emitted particles mass (PM2.5) and number concentrations (PNC) were measured at the release source. Analysis of variance, followed by linear mixed-effects modeling, was applied to quantify the variations in PM2.5 and PNC of the released particles caused by the abovementioned factors. The results confirmed that using materials of different primary size and surface treatment affects the release of the particles from the same process by causing statistically-significant variations in PM2.5 and PNC. The interaction of these two factors should also be taken into account as it resulted in variations in the measured particles release properties. Furthermore, the feed rate of the milling machine was confirmed to be another influencing parameter. Although this research does not identify a specific pattern in the release of synthetic clay nanoparticles from the jet milling process generalizable to other similar settings, it emphasizes that each tested case should be handled individually in terms of exposure considerations.