Enhancing the management of resource-aware business processes

The resource perspective has received much less attention than other business process (BP) perspectives, e.g., control flow. This thesis focuses on human resource management in BPs, and addresses challenges related to resource specification and resource analysis. In particular, it introduces novel techniques for resource specification, which rely on a new resource selection language called RAL; and it provides automated support for a set of analysis operations at design time and at run time based on the formal semantics of RAL defined in description logics (DLs), by leveraging existing DL reasoners. All the contributions have been validated

BPM Adoption at Bilfinger

Big size corporate companies that opt for Business ProcessManagement (BPM) adoption invest a lot in BPM initiatives with theprimary focus on the identification and standardization of best practicesin the different phases of the BPM lifecycle. The business processes de-signed are usually seen as the standard way of executing the processesand tend not be adapted to specific customers' need or changing condi-tions. Furthermore, the acceptance of a paradigm shift by the end usersis an added challenge. This case introduces a success story on BPMadoption in complex environments where different organizational unitswith different needs are involved. The projects executed in different unitsrespond to specific customers’ requirements, which affects the set of pro-cesses to be designed and executed within them. We developed a novelapproach inspired by the Cynefin framework and used it to define processarchitectures and the respective business process models for a subset ofthe units. To ensure the applicability and acceptance of the new paradigmwe followed a number of well-known methodologies and practices (e.g.SCRUM and gamification). As a result, we managed to move from thetraditional function orientation to BPM orientation taking into consid-eration the flexibility needs, and we received very positive feedback fromour end users

A template-based approach for responsibility management in executable business processes

Process-oriented organisations need to manage the different types of responsibilities their employees may have w.r.t. the activities involved in their business processes. Despite several approaches provide support for responsibility modelling, in current Business Process Management Systems (BPMS) the only responsibility considered at runtime is the one related to performing the work required for activity completion. Others like accountability or consultation must be implemented by manually adding activities in the executable process model, which is time-consuming and error-prone. In this paper, we address this limitation by enabling current BPMS to execute processes in which people with different responsibilities interact to complete the activities. We introduce a metamodel based on Responsibility Assignment Matrices (RAM) to model the responsibility assignment for each activity, and a flexible template-based mechanism that automatically transforms such information into BPMN elements, which can be interpreted and executed by a BPMS. Thus, our approach does not enforce any specific behaviour for the different responsibilities but new templates can be modelled to specify the interaction that best suits the activity requirements. Furthermore, libraries of templates can be created and reused in different processes. We provide a reference implementation and build a library of templates for a well-known set of responsibilities

A framework for efficiently mining the organisational perspective of business processes

Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions, which is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they do not aim at providing efficient solutions; or (iii) the discovered process models are difficult to read due to the number of assignment conditions included. In this paper we address these problems and develop an efficient and effective process mining framework that provides extensive support for the discovery of patterns related to resource assignment. The framework is validated in terms of performance and applicability

Mining Project- Oriented Business Processes

Large engineering processes need to be monitored in detail regarding when what was done in order to prove compliance with rules and regulations. A typical problem of these processes is the lack of con- trol that a central process engine provides, such that it is difficult to track the actual course of work even if data is stored in version control systems (VCS). In this paper, we address this problem by defining a mining technique that helps to generate models that visualize the work history as GANTT charts. To this end, we formally define the notion of a project-oriented business process and a corresponding mining algorithm. Our evaluation based on a prototypical implementation demonstrates the benefits in comparison to existing process mining approaches for this specific class of processes

Mining team compositions for collaborative work in business processes

Process mining aims at discovering processes by extracting knowledge about their different perspectives from event logs. The resource perspective (or organisational perspective) deals, among others, with the assignment of resources to process activities. Mining in relation to this perspective aims to extract rules on resource assignments for the process activities. Prior research in this area is limited by the assumption that only one resource is responsible for each process activity, and hence, collaborative activities are disregarded. In this paper, we leverage this assumption by developing a process mining approach that is able to discover team compositions for collaborative process activities from event logs. We evaluate our novel mining approach in terms of computational performance and practical applicability

Specification and Automated Design-Time Analysis of the Business Process Human Resource Perspective

The human resource perspective of a business process is concerned with the relation between the activities of a process and the actors who take part in them. Unlike other process perspectives, such as control flow, for which many different types of analyses have been proposed, such as finding deadlocks, there is an important gap regarding the human resource perspective. Resource analysis in business processes has not been defined, and only a few analysis operations can be glimpsed in previous approaches. In this paper, we identify and formally define seven design-time analysis operations related to how resources are involved in process activities. Furthermore, we demonstrate that for a wide variety of resource-aware BP models, those analysis operations can be automated by leveraging Description Logic (DL) off-the-shelf reasoners. To this end, we rely on Resource Assignment Language (RAL), a domain-specific language that enables the definition of conditions to select the candidates to participate in a process activity. We provide a complete formal semantics for RAL based on DLs and extend it to address the operations, for which the control flow of the process must also be taken into consideration. A proof-of-concept implementation has been developed and integrated in a system called CRISTAL. As a result, we can give an automatic answer to different questions related to the management of resources in business processes at design time

Mining Resource Assignments and Teamwork Compositions from Process Logs

Process mining aims at discovering processes by extracting knowledge from event logs. Such knowledge may refer to different business process perspectives. The organisational perspective deals, among other things, with the assignment of human resources to process activities. Information about the resources that are involved in process activities can be mined from event logs in order to discover resource assignment conditions. This is valuable for process analysis and redesign. Prior process mining approaches in this context present one of the following issues: (i) they are limited to discovering a restricted set of resource assignment conditions; (ii) they are not fully efficient; (iii) the discovered process models are difficult to read due to the high number of assignment conditions included; or (iv) they are limited by the assumption that only one resource is responsible for each process activity and hence, collaborative activities are disregarded. To overcome these issues, we present an integrated process mining framework that provides extensive support for the discovery of resource assignment and teamwork patterns

A Conceptual Architecture for an Event-based Information Aggregation Engine in Smart Logistics

The field of Smart Logistics is attracting interest in several areas of research, including Business Process Management. Awide range of research works are carried out to enhance the capability of monitoring the execution of ongoing logistics processes and predict their likely evolvement. In order to do this, it is crucial to have in place an IT infrastructure that provides the capability of automatically intercepting the digitalised transportation-related events stemming from widespread sources, along with their elaboration, interpretation and dispatching. In this context, we present here the service-oriented software architecture of such an event-based information engine. In particular, we describe the requisites that it must meet. Thereafter, we present the interfaces and subsequently the service-oriented components that are in charge of realising them. The outlined architecture is being utilised as the reference model for an ongoing European research project on Smart Logistics, namely GET Service