Business Process Management Forum

Although research exists on Business Process Management (BPM) maturity models, few studies report on their practical use. This paper explores the situational needs and practitioner’s views on assessing BPM maturity. Data triangulation uncovered different applications in Swedish industry and public sector organizations through three phases: (1) data collection in a practitioner-driven BPM maturity model design, (2) validation of the design in a workshop and follow-up interviews, and (3) testing the BPM maturity model by practitioners. The basic assumption is that a generic BPM maturity model will most likely not fit all organizations. Therefore, a framework is presented with elements (e.g. scope and measures) for a BPM maturity model to be customized to an organization’s needs, supplemented by a practical ‘tailoring template’. The framework and template contribute to the BPM discipline with a Swedish example, and allows twelve design propositions with recommendations to simplify the application of BPM maturity models and enhance their fit.

In a changing and competitive business world, business processes are at the heart of modern organizations. In some cases, service level agreements (SLAs) are used to regulate how these business processes are provided. This is usually the case when the business process is outsourced, and some guarantees about how the outsourcing service is provided are required. Although some work has been done concerning the structure of SLAs for business processes, the definition of service level objectives (SLOs) remains a manual task performed by experts based on their previous knowledge and intuition. Therefore, an evidence-based approach that curtails humans involvement is required for the definition of realistic while challenging SLOs. This is the purpose of this paper, where performance-focused process mining, goal programming optimization techniques, and simulation techniques have been availed to implement an evidence-based framework for the definition of SLAs. Furthermore, the applicability of the proposed framework has been evaluated in a case study carried out in a hospital scenario.

Empirical Research is becoming increasingly important for understanding the practical uses and problems with business processes technology in the field. However, no standardization on how to report observations and findings exists. This sometimes leads to research outcomes which report partial or incomplete data and make published results of replicated studies on different data sets hard to compare. In order to help the research community improve reporting on business process models and collections and their characteristics, this paper defines a modular template with the aim of reports’ standardization, which could also facilitate the creation of shared business process repositories to foster further empirical research in the future. The template has been positively evaluated by representatives from both BPM research and industry. The survey feedback has been incorporated in the template. We have applied the template to describe a real-world executable WS-BPEL process collection, measured from a static and dynamic perspective.

Real-life processes are typically less structured and more complex than expected by stakeholders. For this reason, process discovery techniques often deliver models less understandable and useful than expected. In order to address this issue, we propose a method based on statistical inference for pre-processing event logs. We measure the distance between different segments of the event log, computing the probability distribution of observing activities in specific positions. Because segments are generated based on time-domain, business rules or business management system properties, we get a characterisation of these segments in terms of both business and process aspects. We demonstrate the applicability of this approach by developing a case study with real-life event logs and showing that our method is offering interesting properties in term of computational complexity.

Dynamic markets and new technology developments lead to an increasing number of compliance requirements. Thus, affected business processes must be flexible and adaptable. Ensuring business processes compliance (BPC) is traditionally operationalized by means of controls, which can be described as simple target-performance comparisons. Since such controls are not always suitable for achieving BPC, the view is extended by so-called compliance processes. However, the definition and design of appropriate compliance processes for effective BPC depend on a multitude of process characteristics. To address this issue on a general level, we developed a taxonomy for compliance processes consisting of 9 dimensions and 37 characteristics. As a result, the taxonomy allows researchers and practitioners to classify compliance processes according to the state of the art in a formal way. Furthermore, it provides a systematic fundament for greater flexibility, i.e. an ad hoc integration of compliance processes into ongoing business processes to ensure BPC during runtime.

Clinical pathways are highly variable and although many patients may follow similar pathway each individual will experience a unique set of events, for example with multiple repeated activities or varied sequences of activities. Process mining techniques are able to discover generalizable pathways based on data mining of event logs but using process mining techniques on a raw clinical pathway data to discover underlying healthcare processes is challenging due to this high variability. This paper involves two main contributions to healthcare process mining. The first contribution is developing a novel approach for event selection and outlier removing in order to improve pattern detection and thus representational quality. The second contribution is to demonstrate a new open access medical dataset, the MIMIC-III (Medical Information Mart for Intensive Care) database, which has not been used in process mining publications.

In this paper, we developed a new method for variations reduction in clinical pathways data. Variation can result from outlier events that prevent capturing clear patterns. Our approach targets the behavior of repeated activities. It uses interval-based patterns to determine outlier threshold based on the time of events occurring and the distinctive attribute of observed events.

The approach is tested on clinical pathways data for diabetes patients with congestive heart failure extracted from the MIMIC-III medical database and analyzed using the ProM process mining tool. The method has improved model precision conformance without reducing model fitness. We were able to reduce the number of events while making sure the mainstream patterns were unaffected. We found that some activity types had a large number of outlier events whereas other activities had a relatively few. The interval-based event selection method has the potential of improve process visualization. This approach is undergoing implementation as an event log enhancement technique in the ProM tool.

With the recent release of the Decision Model and Notation (DMN) specification, standardized decision models can be designed to represent the decisions required for executing business processes. Outsourcing decision logic from process to decision models leads to a separation of concerns and therefore to decision-aware business processes. However, no exhaustive considerations regarding the soundness of the integration of the two types of models have been made so far. Classical soundness checking only looks at the control-flow of a process model. In this paper, we formally define soundness criteria for decision-aware processes that ensure that the process can continue after a decision has been taken, and that all activities following the decision can be executed. A scalable implementation and an analysis of models from participants of an online course on process and decision modeling as well as a from a BPM project of a large insurance company demonstrate the benefits of our contribution.

Recent years have seen an increase in the concern for the environment, with attempts being made to raise public awareness about the need to have sustainable development that enables the use of any resource in the present, without compromising its future. This concept of sustainability should be applied in the lifestyle of individuals, but also in companies or organizations that deal with business process management, known as BPM. This would allow the creation of business processes that are more sustainable and which use resources more efficiently; this is the concept of Green BPM. It is thus of prime importance to find an incentive for the workers in the companies to get involved in these sustainable initiatives. This has led to a consideration of the need to incorporate gamification, i.e., the use of game elements in non-game contexts in an effort to induce certain behaviors in people. The aim of these games would be to enhance participation and foster commitment to sustainable development. With all these issues in mind, in this article the BPMS-Game tool is described; the tool combines the concepts of gamification, sustainability, and business processes to support the definition of games that promote sustainability in BPM environments. A set of base and derived measures have been defined to evaluate the user behavior with respect to sustainability in their daily work when using a BPMS system. The contributions that BPMS-Game can offer are illustrated with a representative example.

Event handling is a fundamental concept for the implementation of business processes. It enables the specification of how a process communicates with its environment and how this environment influences the execution of a process. However, even feature-rich languages for process specification such as BPMN are severely limited in their event handling semantics. They largely neglect the design choices to be made when deciding on when to subscribe to event sources and how to retrieve events for a particular process instance. In this paper, we therefore propose a model for event handling in business processes that is grounded in explicit subscriptions and event buffering. This model is integrated in BPMN using its extension mechanism and comes with formal execution semantics. Based on the latter, we further show how existing techniques for verification and adapter synthesis can be leveraged to analyse the interactions of a business process. Finally, we demonstrate the feasibility of our event handling model by means of an implementation in Camunda, an open-source process engine.

The current digital era is characterized by increasing globalization and a fast evolution in new technologies (e.g. social media, mobile, cloud, big data analytics, Internet of Things and smart devices). Since organizations are exponentially challenged to achieve business results more effectively and efficiently, topics such as process performance and the constant search for optimizations and transformations are key. Business Process Management (BPM) and digital innovation are both ways for organizations to constantly improve, change and excel. Nonetheless, more research is needed on the intersection between these two approaches. While current literature acknowledges a link between BPM and digital innovation, this study digs deeper into the digital innovation strategies that organizations apply to incorporate technological transformations into their business processes. Based on our survey findings, we open the discussion about the strength of the assumed relationship between BPM and digital innovation, and which implications can be drawn.