Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modeling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modeling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.     

Syntax highlighting in business process models

Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax highlighting to workflow nets, a modeling technique that is frequently used for business process modeling. Our contribution is three-fold. First, we establish a theoretical argument to what extent highlighting could improve comprehension. Second, we formalize a concept for syntax highlighting in workflow nets and present a prototypical implementation with the WoPeD modeling tool. Third, we report on the results of an experiment that tests the hypothetical benefits of highlighting for comprehension. Our work can easily be transferred to other process modeling tools and other process modeling techniques.     

From inter-organizational business process models to service-oriented architecture models

Today’s business processes become increasingly complex and often cross the boundaries of the organizations. On the one hand, to support their business processes, modern organizations use enterprise information systems that need to be aware of the organizations’ processes and contexts. Such systems are called Process-Aware Information System (PAIS). On the other hand, the service-oriented architecture (SOA) is a fast emerging architectural style that has been widely adopted by modern organizations to design and implement PAIS that support their business processes. This paper aims to bridge the gap between inter-organizational business processes and SOA-based PAISs that support them. It proposes a novel model-driven design method that generates SOA models expressed in SoaML taking the specification of collaborative business processes expressed in BPMN as input. We present the principles underlying the approach, the state of an ongoing implementation, and the results of two studies conducted to empirically validate the method in the context of ERP key processes.     

Quality indicators for business process models from a gateway complexity perspective

ContextQuality assurance of business process models has been recognized as an important factor for modeling success at an enterprise level. Since quality of models might be subject to different interpretations, it should be addressed in the most objective way, by the application of measures. That said, however, assessment of measurement results is not a straightforward task: it requires the identification of relevant threshold values, which are able to distinguish different levels of process model quality.ObjectiveSince there is no consensual technique for obtaining these values, this paper proposes the definition of thresholds for gateway complexity measures based on the application of statistical techniques on empirical data.MethodTo this end, we conducted a controlled experiment that evaluates quality characteristics of understandability and modifiability of process models in two different runs. The thresholds obtained were validated in a replication of the experiment.ResultsThe thresholds for gateway complexity measures are instrumental as guidelines for novice modelers. A tool for supporting business process model measurement and improvement is described, based on the automatic application of measurement, and assessment as well as derivation of advice about how to improve the quality of the model.ConclusionIt is concluded that thresholds classified business process models in the specific level of understandability and modifiability, so these thresholds were good and useful for decision-making.     

Extensible ontology-based views for business process models

Knowledge and Information Systems - A business process model may be used as both a communication artefact for gathering and sharing knowledge of a business practice among stakeholders and as a...     

Using GXL for exchanging business process models

The graph exchange language (GXL) is an XML-based standard exchange language for sharing graph data between tools. GXL can be customized to exchange application specific types of graphs. This is done by exchanging both, the instance graph, representing the data itself, and the schema, representing the graph structure. Business process models are usually depicted in a graph-like form. This paper describes a novel application of GXL to the exchange of business process models. It is shown, how to customize GXL to exchange business process models depicted as Event-driven Process Chains and Workflow nets as examples for the control flow part of business process models. Each level of modeling is exemplarily demonstrated from the metaschemas down to instances of graphs.     

Comprehending object and process models: an empirical study

We report the results of an empirical study comparing user comprehension of object oriented (OO) and process oriented (PO) models. The fundamental difference is that while OO models tend to focus on structure, PO models tend to emphasize behaviour or processes. Proponents of the OO modeling approach argue that it lends itself naturally to the way humans think. However, evidence from research in cognitive psychology and human factors suggests that human problem solving is innately procedural. Given these conflicting viewpoints, we investigate empirically if OO models are in fact easier to understand than PO models. But, as suggested by the theory of cognitive fit, model comprehension may be influenced by task-specific characteristics. We therefore compare OO and PO models based on whether the comprehension activity involves: 1) only structural aspects, 2) only behavioral aspects, or 3) a combination of structural and behavioral aspects. We measure comprehension through subjects' responses to questions designed along these three dimensions. Results show that for most of the simple questions, no significant difference was observed insofar as model comprehension is concerned. For most of the complex questions, however, the PO model was found to be easier to understand than the OO model. In addition to describing the process and the outcomes of the experiments, we present the experimental method employed as a viable approach for conducting research into various phenomena related to the efficacy of alternative systems analysis and design methods. We also identify areas where future research is necessary, along with a recommendation of appropriate research methods for empirical examination     

Profiting from business process outsourcing

Companies have successfully used outsourcing for decades to generate savings and allow greater focus on core (essential) business. Outsourcing traditionally noncore (nonessential) yet critical functions to larger service providers is one of the fastest-growing changes in the market today. We refer to this process as business process outsourcing (BPO). Two significant market forces are driving this practice: a growing low-cost white-collar labor pool and automation and codification of best practices. Although the BPO market has been around for more than 40 years, it is only now reaching many companies' radar screens because of the better service levels and cost-savings promise. The two opportunities behind the recent growth of this sector - process modules and offshoring - show enormous promise, and companies musty use them in conjunction to show sustainable savings and, hence, long-term profitability. Future work in this area would involve understanding the definitions, costs, benefits, and risks associated with various service delivery models that service providers deploy, such as a global services delivery model that uses on-site, on-shore and offshore locations and a pure offshore services delivery model.     

Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curve method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.     

Similarity of business process models: Metrics and evaluation

It is common for large organizations to maintain repositories of business process models in order to document and to continuously improve their operations. Given such a repository, this paper deals with the problem of retrieving those models in the repository that most closely resemble a given process model or fragment thereof. Up to now, there is a notable research gap on comparing different approaches to this problem and on evaluating them in the same setting. Therefore, this paper presents three similarity metrics that can be used to answer queries on process repositories: (i) node matching similarity that compares the labels and attributes attached to process model elements; (ii) structural similarity that compares element labels as well as the topology of process models; and (iii) behavioral similarity that compares element labels as well as causal relations captured in the process model. These metrics are experimentally evaluated in terms of precision and recall. The results show that all three metrics yield comparable results, with structural similarity slightly outperforming the other two metrics. Also, all three metrics outperform text-based search engines when it comes to searching through a repository for similar business process models.     

Lightweight extraction of object models from bytecode

A program's object model captures the essence of its design. For some programs, no object model was developed during design; for others, an object model exists but may be out-of-sync with the code. This paper describes a tool that automatically extracts an object model from the class-files of a Java program. Unlike existing tools, it handles container classes by inferring the types of elements stored in a container and eliding the container itself. This feature is crucial for obtaining models that show the structure of the abstract state and bear some relation to conceptual models. Although the tool performs only a simple, heuristic analysis that is almost entirely local, the resulting object model is surprisingly accurate. The paper explains what object models are and why they are useful; describes the analysis, its assumptions, and limitations; evaluates the tool for accuracy, and illustrates its use on a suite of sample programs     

Discovering hierarchical object models from captioned images

We address the problem of automatically learning the recurring associations between the visual structures in images and the words in their associated captions, yielding a set of named object models that can be used for subsequent image annotation. In previous work, we used language to drive the perceptual grouping of local features into configurations that capture small parts (patches) of an object. However, model scope was poor, leading to poor object localization during detection (annotation), and ambiguity was high when part detections were weak. We extend and significantly revise our previous framework by using language to drive the perceptual grouping of parts, each a configuration in the previous framework, into hierarchical configurations that offer greater spatial extent and flexibility. The resulting hierarchical multipart models remain scale, translation and rotation invariant, but are more reliable detectors and provide better localization. Moreover, unlike typical frameworks for learning object models, our approach requires no bounding boxes around the objects to be learned, can handle heavily cluttered training scenes, and is robust in the face of noisy captions, i.e., where objects in an image may not be named in the caption, and objects named in the caption may not appear in the image. We demonstrate improved precision and recall in annotation over the non-hierarchical technique and also show extended spatial coverage of detected objects.     

Regional business cycles in Italy

There is clear evidence for differences in the structure of the Italian regional business cycle in the period 1951-2004: the relationship with the national business cycle is closer in the North than in the South. The interaction between regional cycles shows considerable variation over time. There is a change in the timing of the turning points and the strength of the relationship. In the 1950s and the early 1960s, the cycle in the North leads the cycle in the South. Comovement is strongest in the period 1965-1975. After 1975, the cycles start to drift out of phase, again with the North leading the South.     

On the refactoring of activity labels in business process models

Large corporations increasingly utilize business process models for documenting and redesigning their operations. The extent of such modeling initiatives with several hundred models and dozens of often hardly trained modelers calls for automated quality assurance. While formal properties of control flow can easily be checked by existing tools, there is a notable gap for checking the quality of the textual content of models, in particular, its activity labels. In this paper, we address the problem of activity label quality in business process models. We designed a technique for the recognition of labeling styles, and the automatic refactoring of labels with quality issues. More specifically, we developed a parsing algorithm that is able to deal with the shortness of activity labels, which integrates natural language tools like WordNet and the Stanford Parser. Using three business process model collections from practice with differing labeling style distributions, we demonstrate the applicability of our technique. In comparison to a straightforward application of standard natural language tools, our technique provides much more stable results. As an outcome, the technique shifts the boundary of process model quality issues that can be checked automatically from syntactic to semantic aspects.     

Detection and quantification of flow consistency in business process models

Business process models abstract complex business processes by representing them as graphical models. Their layout, as determined by the modeler, may have an effect when these models are used. However, this effect is currently not fully understood. In order to systematically study this effect, a basic set of measurable key visual features is proposed, depicting the layout properties that are meaningful to the human user. The aim of this research is thus twofold: first, to empirically identify key visual features of business process models which are perceived as meaningful to the user and second, to show how such features can be quantified into computational metrics, which are applicable to business process models. We focus on one particular feature, consistency of flow direction, and show the challenges that arise when transforming it into a precise metric. We propose three different metrics addressing these challenges, each following a different view of flow consistency. We then report the results of an empirical evaluation, which indicates which metric is more effective in predicting the human perception of this feature. Moreover, two other automatic evaluations describing the performance and the computational capabilities of our metrics are reported as well.     

aCHAT-WF: Generating conversational agents for teaching business process models

Software and Systems Modeling - This paper proposes a general approach for using conversational interfaces such as chatbots to offer adaptive learning of business processes in an environment...