On the Common Support of Workflow Type and Instance Changes under Correctness Constraints

The capability to rapidly adapt in-progress workflows (WF) is an essential requirement for any workflow system. Adaptations may concern single WF instances or a WF type as a whole. Especially for long-running business processes it is indispensable to propagate WF type changes to in-progress WF instances as well. Very challenging in this context is to correctly adapt a (potentially large) collection of WF instances, which may be in different states and to which various ad-hoc changes may have been previously applied. This paper presents a generic framework for the common support of both WF type and WF instance changes. We establish fundamental correctness principles, position formal theorems, and show how WF instances can be automatically and efficiently migrated to a modified WF schema. The adequate treatment of conflicting WF type and WF instance changes adds to the overall completeness of our approach. By offering more flexibility and adaptability the so promising WF technology will finally deliver

Discovering duplicate tasks in transition systems for the simplification of process models

This work presents a set of methods to improve the understandability of process models. Traditionally, simplification methods trade off quality metrics, such as fitness or precision. Conversely, the methods proposed in this paper produce simplified models while preserving or even increasing fidelity metrics. The first problem addressed in the paper is the discovery of duplicate tasks. A new method is proposed that avoids overfitting by working on the transition system generated by the log. The method is able to discover duplicate tasks even in the presence of concurrency and choice. The second problem is the structural simplification of the model by identifying optional and repetitive tasks. The tasks are substituted by annotated events that allow the removal of silent tasks and reduce the complexity of the model. An important feature of the methods proposed in this paper is that they are independent from the actual miner used for process discovery.Peer ReviewedPostprint (author's final draft

A Method to Improve the Early Stages of the Robotic Process Automation Lifecycle

The robotic automation of processes is of much interest to organizations. A common use case is to automate the repetitive manual tasks (or processes) that are currently done by back-office staff through some information system (IS). The lifecycle of any Robotic Process Automation (RPA) project starts with the analysis of the process to automate. This is a very time-consuming phase, which in practical settings often relies on the study of process documentation. Such documentation is typically incomplete or inaccurate, e.g., some documented cases never occur, occurring cases are not documented, or documented cases differ from reality. To deploy robots in a production environment that are designed on such a shaky basis entails a high risk. This paper describes and evaluates a new proposal for the early stages of an RPA project: the analysis of a process and its subsequent design. The idea is to leverage the knowledge of back-office staff, which starts by monitoring them in a non-invasive manner. This is done through a screen-mousekey- logger, i.e., a sequence of images, mouse actions, and key actions are stored along with their timestamps. The log which is obtained in this way is transformed into a UI log through image-analysis techniques (e.g., fingerprinting or OCR) and then transformed into a process model by the use of process discovery algorithms. We evaluated this method for two real-life, industrial cases. The evaluation shows clear and substantial benefits in terms of accuracy and speed. This paper presents the method, along with a number of limitations that need to be addressed such that it can be applied in wider contexts.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-

Supporting Flexible Processes with Adaptive Workflow and Case Handling

Workflow management technology has profoundly transformed the way complex tasks are being handled in modern, large-scale organizations. However, it is mostly those systems’ inherent lack of flexibility that hinders their broad acceptance, and that is perceived as annoyance by users. In this context, Adaptive Process Management and Case Handling provide two very different paradigms, which both attempt to make process management more flexible and user-friendly. In this paper, we compare strengths and weaknesses of these two paradigms, and point out situations in which each is particularly appropriate. We further outline ways, in which either technology can be enhanced by crucial concepts from the other. This integration of flexibility approaches has the potential to remedy fundamental problems still present in each technology on its own

RALph: A Graphical Notation for Resource Assignments in Business Processes

The business process (BP) resource perspective deals with the management of human as well as non-human resources throughout the process lifecycle. Although it has received increasing attention recently, there exists no graphical notation for it up until now that is both expressive enough to cover well-known resource selection conditions and independent of the BP modelling language. In this paper, we introduce RALph, a graphical notation for the assignment of human resources to BP activities. We define its semantics by mapping this notation to a language that has been formally defined in description logics, which enables its automated analysis. Although we show how RALph can be seamlessly integrated with BPMN, it is noteworthy that the notation is independent of the BP modelling language. Altogether, RALph will foster the visual modelling of the resource perspective in BP

Modeling and enacting complex data dependencies in business processes

Enacting business processes in process engines requires the coverage of control flow, resource assignments, and process data. While the first two aspects are well supported in current process engines, data dependencies need to be added and maintained manually by a process engineer. Thus, this task is error-prone and time-consuming. In this report, we address the problem of modeling processes with complex data dependencies, e.g., m:n relationships, and their automatic enactment from process models. First, we extend BPMN data objects with few annotations to allow data dependency handling as well as data instance differentiation. Second, we introduce a pattern-based approach to derive SQL queries from process models utilizing the above mentioned extensions. Therewith, we allow automatic enactment of data-aware BPMN process models. We implemented our approach for the Activiti process engine to show applicability. Keywords: Process Modeling, Data Modeling, Process Enactment, BPMN, SQ

Enhancing workflow-nets with data for trace completion

The growing adoption of IT-systems for modeling and executing (business) processes or services has thrust the scientific investigation towards techniques and tools which support more complex forms of process analysis. Many of them, such as conformance checking, process alignment, mining and enhancement, rely on complete observation of past (tracked and logged) executions. In many real cases, however, the lack of human or IT-support on all the steps of process execution, as well as information hiding and abstraction of model and data, result in incomplete log information of both data and activities. This paper tackles the issue of automatically repairing traces with missing information by notably considering not only activities but also data manipulated by them. Our technique recasts such a problem in a reachability problem and provides an encoding in an action language which allows to virtually use any state-of-the-art planning to return solutions

Managing Process Variants as an Information Resource

Many business solutions provide best practice process templates, both generic as well as for specific industry sectors. However, it is often the variance from template solutions that provide organizations with intellectual capital and competitive differentiation. In this paper, we present a modeling framework that is conducive to constrained variance, by supporting user driven process adaptations. The focus of the paper is on providing a means of utilizing the adaptations effectively for process improvement through effective management of the process variants repository (PVR). In particular, we will provide deliberations towards a facility to provide query functionality for PVR that is specifically targeted for effective search and retrieval of process variants

Investigations on Soundness Regarding Lazy Activities

Abstract. Current approaches for proving the correctness of business processes focus on either soundness, weak soundness, or relaxed sound-ness. Soundness states that each activity should be on a path from the initial to the final activity, that after the final activity has been reached no other activities should become active, and that there are no unreach-able activities. Relaxed soundness softens soundness by stating that each activity should be able to participate in the business process, whereas weak soundness allows unreachable activities. However, all these kinds of soundness are not satisfactory for processes containing discriminator, n-out-of-m-join or multiple instances without synchronization patterns that can leave running (lazy) activities behind. As these patterns occur in interacting business processes, we propose a solution based on lazy soundness. We utilize the pi-calculus to discuss and implement reasoning on lazy soundness.