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-

An SMT-based discovery algorithm for C-nets

Recently, Causal nets have been proposed as a suitable model for process discovery, due to their declarative semantics and the great expressiveness they possess. In this paper we propose an algorithm to discover a causal net from a set of traces. It is based on encoding the problem as a Satisfiability Modulo Theories (SMT) formula, and uses a binary search strategy to optimize the derived model. The method has been implemented in a prototype tool that interacts with an SMT solver. The experimental results obtained witness the capability of the approach to discover complex behavior in limited time.Postprint (published version

The Relational Process Structure

Using data-centric process paradigms, small processes such as artifacts, object lifecycles, or Proclets have become an alternative to large, monolithic models. In these paradigms, a business process arises from the interactions between small processes. However, many-to-many relationships may exist between different process types, requiring careful consideration to ensure that the interactions between processes can be purposefully coordinated. Although several concepts exist for modeling interrelated processes, a concept that considers both many-to-many relationships and cardinality constraints is missing. Furthermore, existing concepts focus on design-time, neglecting the complexity introduced by many-to-many relationships when enacting extensive process structures at run-time. The knowledge which process instances are related to which other process instances is essential. This paper proposes the relational process structure, a concept providing full support for many-to-many-relationships and cardinality constraints at both design- and run-time. The relational process structure represents a cornerstone to the proper coordination of interrelated processes

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

Designing a Process Mining-Enabled Decision Support System for Business Process Standardization in ERP Implementation Projects

Process standardization allows to optimize ERP systems and is a nec-essary step prior to ERP implementation projects. Traditional approaches to standardizing business processes are based on manually created "de-jure" process models, which are distorted, error-prone, simplistic, and often deviating from process reality. Theoretically embedded in the organizational contingency theory as kernel theory, this paper employs a design science approach to design a process mining-enabled decision support system (DSS) which combines bottom-up process mining models with manually added top-down standardization infor-mation to recommend a suitable standard process specification from a repository. Extended process models of the as-is process are matched against a repository of best-practice standard process model using an attributebased process similarity matching algorithm. Thus, the DSS aims to reduce the overall costs of process standardization, to optimize the degree of fit between the organization and the implemented processes, and to minimize the degree of organizational change re-quired in standardization and ERP implementation projects. This paper imple-ments a working prototype instantiation in the open-source process analytics platform Apromore based on a real-life event log and standardization attributes for the Purchase-to-Pay and Order-to-Cash processes from three SAP R/3 ERP systems at the industry partner

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

Process and Data: Two Sides of the Same Coin

Companies increasingly adopt process management technology which offers promising perspectives for realizing flexible information systems. However, there still exist numerous process scenarios not adequately covered by contemporary information systems. One major reason for this deficiency is the insufficient understanding of the inherent relationships existing between business processes on one side and business data on the other. Consequently, these two perspectives are not well integrated in many existing process management systems. This paper emphasizes the need for both object- and process-awareness in future information systems, and illustrates it along several examples. Especially, the relation between these two fundamental perspectives will be discussed, and the role of business objects and data as drivers for both process modeling and process enactment be emphasized. In general, any business process support should consider object behavior as well as object interactions, and therefore be based on two levels of granularity. In addition, data-driven process execution and integrated user access to processes and data are needed. Besides giving insights into these fundamental characteristics, an advanced framework supporting them in an integrated manner will be presented and its application to real-world process scenarios be shown. Overall, a holistic and generic framework integrating processes, data, and users will contribute to overcome many of the limitations of existing process management technology

Generating business process recommendations with a population-based meta-heuristic

In order to provide both guidance and flexibility to users during process execution, recommendation systems have been proposed. Existing recommendation systems mainly focus on offering recommendation according to the process optimization goals (time, cost…). In this paper we offer a new approach that primarily focuses on maximizing the flexibility during execution. This means that by following the recommendations, the user retains maximal flexibility to divert from them later on. This makes it possible to handle (possibly unknown) emerging constraints during execution. The main contribution of this paper is an algorithm that uses a declarative process model to generate a set of imperative process models that can be used to generate recommendations

Die Politische Ökonomie Beruflicher Weiterbildung: Der Einfluss von Tarifverträgen auf Arbeitgeberinvestitionen und Teilnahmequoten

Warum sind aber Arbeitgeber in einigen Ländern bereit, sich an Weiterbildungsmaßnahmen ihrer Mitarbeiter zu beteiligen, während dies in anderen Ländern nicht der Fall ist? In diesem Artikel wird die tarifvertragliche Abdeckung als zentraler Mechanismus hierfür herausgearbeitet: Einerseits intendiert, durch vertraglich geregelte Weiterbildungsmaßnahmen, und anderseits unintendiert, durch die Angleichung von Löhnen zwischen Firmen. Mithilfe von Mehrebenenregressionsanalysen auf Basis von Daten des European Social Survey kann gezeigt werden, dass Tarifverträge einen postiven Effekt auf die Finanzierungsbeteiligung von Arbeitgebern haben, sowie auf individuelle Teilnahmen. Diese Ergebnisse legen nahe, dass institutionelle Faktoren gewichtige Einflussgrößen in Erklärungen von Firmeninvestitionen und Weiterbildungsbeteiligung sind. In einer abschließenden Diskussion werden diese Funde im Kontext der internationalen Debatte um die Dezentralisierung korporatistischer Arrangements besprochen.Why are employers in some countries willing to pay for further training of their employees, but not in other countries. In this article, it is argued that the central mechanism for this is collective bargaining coverage. On the one hand, intentionally through contractual regulations regarding further training. On the other hand, unintentionally through equalization of wages between companies. Using multilevel-regression based on data from the European Social Survey, results indicate a positive effect of collective bargaining coverage on employer’s willingness to pay for further training, as well as on participation in further training. These results suggest institutions are significant factors in explanations of firm investments into skills and further training. In a concluding discussion, findings are reviewed in the context of the international debate about decentralization of corporatist arrangements

The 4C spectrum of fundamental behavioral relations for concurrent systems

The design of concurrent software systems, in particular process-aware information systems, involves behavioral modeling at various stages. Recently, approaches to behavioral analysis of such systems have been based on declarative abstractions defined as sets of behavioral relations. However, these relations are typically defined in an ad-hoc manner. In this paper, we address the lack of a systematic exploration of the fundamental relations that can be used to capture the behavior of concurrent systems, i.e., co-occurrence, conflict, causality, and concurrency. Besides the definition of the spectrum of behavioral relations, which we refer to as the 4C spectrum, we also show that our relations give rise to implication lattices. We further provide operationalizations of the proposed relations, starting by proposing techniques for computing relations in unlabeled systems, which are then lifted to become applicable in the context of labeled systems, i.e., systems in which state transitions have semantic annotations. Finally, we report on experimental results on efficiency of the proposed computations