Slice, mine and dice : complexity-aware automated discovery of business process models

Automated process discovery techniques aim at extracting models from information system logs in order to shed light into the business processes supported by these systems. Existing techniques in this space are effective when applied to relatively small or regular logs, but otherwise generate large and spaghetti-like models. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. The result is a collection of process models -- each one representing a variant of the business process -- as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically by means of subprocess extraction. The proposed technique allows users to set a desired bound for the complexity of the produced models. Experiments on real-life logs show that the technique produces collections of models that are up to 64% smaller than those extracted under the same complexity bounds by applying existing trace clustering techniques.

Normative requirements for business process compliance

Norms regulate the behaviour of their subjects and define what is legal and what is illegal. Norms typically describe the conditions under which they are applicable and the normative effects as a results of their applications. On the other hand, process models specify how a business operation or service is to be carried out to achieve a desired outcome. Norms can have significant impact on how business operations are conducted and they can apply to the whole or part of a business process. For example, they may impose conditions on the different aspects of a process (e.g., perform tasks in a specific sequence (control-flow), at a specific time or within a certain time frame (temporal aspect), by specific people (resources)). We propose a framework that provides the formal semantics of the normative requirements for determining whether a business process complies with a normative document (where a normative document can be understood in a very broad sense, ranging from internal policies to best practice policies, to statutory acts). We also present a classification of normal requirements based on the notion of different types of obligations and the effects of violating these obligations.

Specifying information systems for business process integration : a management perspective

Supply chain management and customer relationship management are concepts for optimizing the provision of goods to customers. Information sharing and information estimation are key tools used to implement these two concepts. The reduction of delivery times and stock levels can be seen as the main managerial objectives of an integrative supply chain and customer relationship management. To achieve this objective, business processes need to be integrated along the entire supply chain including the end consumer. Information systems form the backbone of any business process integration. The relevant information system architectures are generally well-understood, but the conceptual specification of information systems for business process integration from a management perspective, remains an open methodological problem. To address this problem, we will show how customer relationship management and supply chain management information can be integrated at the conceptual level in order to provide supply chain managers with relevant information. We will further outline how the conceptual management perspective of business process integration can be supported by deriving specifications for enabling information system from business objectives.

A methodological evaluation of business process compliance management frameworks

Existing compliance management frameworks (CMFs) offer a multitude of compliance management capabilities that makes difficult for enterprises to decide on the suitability of a framework. Making a decision on the suitability requires a deep understanding of the functionalities of a framework. Gaining such an understanding is a difficult task which, in turn, requires specialised tools and methodologies for evaluation. Current compliance research lacks such tools and methodologies for evaluating CMFs. This paper reports a methodological evaluation of existing CMFs based on a pre-defined evaluation criteria. Our evaluation highlights what existing CMFs offer, and what they cannot. Also, it underpins various open questions and discusses the challenges in this direction.

Improving business process models using observed behavior

Process-aware information systems (PAISs) can be configured using a reference process model, which is typically obtained via expert interviews. Over time, however, contextual factors and system requirements may cause the operational process to start deviating from this reference model. While a reference model should ideally be updated to remain aligned with such changes, this is a costly and often neglected activity. We present a new process mining technique that automatically improves the reference model on the basis of the observed behavior as recorded in the event logs of a PAIS. We discuss how to balance the four basic quality dimensions for process mining (fitness, precision, simplicity and generalization) and a new dimension, namely the structural similarity between the reference model and the discovered model. We demonstrate the applicability of this technique using a real-life scenario from a Dutch municipality.

Business process variability modeling : A survey

It is common for organizations to maintain multiple variants of a given business process, such as multiple sales processes for different products or multiple bookkeeping processes for different countries. Conventional business process modeling languages do not explicitly support the representation of such families of process variants. This gap triggered significant research efforts over the past decade leading to an array of approaches to business process variability modeling. This survey examines existing approaches in this field based on a common set of criteria and illustrates their key concepts using a running example. The analysis shows that existing approaches are characterized by the fact that they extend a conventional process mod- eling language with constructs that make it able to capture customizable process models. A customizable process model represents a family of process variants in a way that each variant can be derived by adding or deleting fragments according to configuration parameters or according to a domain model. The survey puts into evidence an abundance of customizable process modeling languages, embodying a diverse set of con- structs. In contrast, there is comparatively little tool support for analyzing and constructing customizable process models, as well as a scarcity of empirical evaluations of languages in the field.

Development and validation of an instrument to measure organizational cultures' support of business process management

The purpose of Business Process Management (BPM) is to increase the efficiency and effectiveness of organizational processes through improvement and innovation. Despite a common understanding that culture is an important element in these efforts, there is a dearth of theoretical and empirical research on culture as a facilitator of successful BPM. We develop the BPM culture construct and propose a validated instrument with which to measure organizational cultures’ support of BPM. The operationalization of the BPM culture concept provides a theoretical foundation for future research and a tool to assist organizations in developing a cultural environment that supports successful BPM.

Dynamic weaving in aspect oriented business process management

Reducing complexity in Information Systems is an important topic in both research and industry. One strategy to deal with complexity is separation of concerns, which results in less complex, easily maintainable and more reusable systems. Separation of concerns can be addressed through the Aspect Oriented paradigm. Although this paradigm has been well researched in programming, it is still at the preliminary stage in the area of Business Process Management. While some efforts have been made to extend business process modelling with aspect oriented capability, it has not yet been investigated how aspect oriented business process models should be executed at runtime. In this paper, we propose a generic solution to support execution of aspect oriented business process models based on the principle behind dynamic weaving of aspects. This solution is formally specified using Coloured Petri Nets. The resulting formal specification serves as the blueprint to the implementation of a service module in the framework of a state-of-the-art Business Process Management System. Using this developed artefact, a case study is performed in which two simplified processes from real business in the domain of banking are modelled and executed in an aspect oriented manner. Through this case study, we also demonstrate that adoption of aspect oriented modularization increases the reusability while reducing the complexity of business process models in practice.

A critical analysis of business process management education and alignment with industry demand : an Australian perspective

Business Process Management (BPM) is accepted globally as an organizational approach to enhance productivity and drive cost efficiencies. Studies confirm a shortage of BPM skilled professionals with limited opportunities to develop the required BPM expertise. This study investigates this gap starting from a critical analysis of BPM courses offered by Australian universities and training institutions. These courses were analyzed and mapped against a leading BPM capability framework to determine how well current BPM education and training offerings in Australia address the core capabilities required by BPM professionals globally. To determine the BPM skill-sets sought by industry, online recruitment advertisements were collated, analyzed, and mapped against this BPM capability framework. The outcomes provide a detailed overview on the alignment of available BPM education/training and industry demand. These insights are useful for BPM professionals and their employers to build awareness of the BPM capabilities required for a BPM mature organization. Universities and other training institutions will benefit from these results by understanding where demand is, where the gaps are, and what other BPM education providers are supplying. This structured comparison method could continue to provide a common ground for future discussion across university-industry boundaries and continuous alignment of their respective practices.

Professionalizing Business Process Management : towards a Body of Knowledge for BPM

Business Process Management (BPM) is rapidly evolving as an established discipline. There are a number of efforts underway to formalize the various aspects of BPM practice; creating a formal Body of Knowledge (BoK) is one such effort. Bodies of knowledge are artifacts that have a proven track record for accelerating the professionalization of various disciplines. In order for this to succeed in BPM, it is vital to involve the broader business process community and derive a BoK that has essential characteristics that addresses the discipline’s needs. We argue for the necessity of a comprehensive BoK for the BPM domain, and present a core list of essential features to consider when developing a BoK based on preliminary empirical evidence. The paper identifies and critiques existing Bodies of Knowledge related to BPM, and firmly calls for an effort to develop a more accurate and sustainable BoK for BPM. An approach for this effort is presented with preliminary outcomes.

Expertise in Business Process Management

As organizations attempt to become more business process-oriented, existing role descriptions are revised and entire new business process-related roles emerge. A lot of attention is often being paid to the technological aspect of Business Process Management (BPM), but relatively little work has been done concerning the people factor of BPM and the specification of BPM expertise in particular. This study tries to close this gap by proposing a comprehensive BPM expertise model, which consolidates existing theories and related work. This model describes the key attributes characterizing “BPM expertise” and outlines their structure, dynamics, and interrelationships. Understanding BPM expertise is a predecessor to being able to develop and apply it effectively. This is the cornerstone of human capital and talent management in BPM.

Business process mining success

Process mining has developed into a popular research discipline and nowadays its associated techniques are widely applied in practice. What is currently ill-understood is how the success of a process mining project can be measured and what the antecedent factors of process mining success are. We consider an improved, grounded understanding of these aspects of value to better manage the effectiveness and efficiency of process mining projects in practice. As such, we advance a model, tailored to the characteristics of process mining projects, which identifies and relates success factors and measures. We draw inspiration from the literature from related fields for the construction of a theoretical, a priori model. That model has been validated and re-specified on the basis of a multiple case study, which involved four industrial process mining projects. The unique contribution of this paper is that it presents the first set of success factors and measures on the basis of an analysis of real process mining projects. The presented model can also serve as a basis for further extension and refinement using insights from additional analyses.

Consolidation of business process model collections

This thesis presents novel techniques for addressing the problems of continuous change and inconsistencies in large process model collections. The developed techniques treat process models as a collection of fragments and facilitate version control, standardization and automated process model discovery using fragment-based concepts. Experimental results show that the presented techniques are beneficial in consolidating large process model collections, specifically when there is a high degree of redundancy.

The Six Core Elements of Business Process Management

The previous chapters gave an insightful introduction into the various facets of Business Process Management. We now share a rich understanding of the essential ideas behind designing and managing processes for organizational purposes. We have also learned about the various streams of research and development that have influenced contemporary BPM. As a matter of fact, BPM has become a holistic management discipline. As such, it requires that a plethora of facets needs to be addressed for its successful und sustainable application. This chapter provides a framework that consolidates and structures the essential factors that constitute BPM as a whole. Drawing from research in the field of maturity models, we suggest six core elements of BPM: strategic alignment, governance, methods, information technology, people, and culture. These six elements serve as the structure for this BPM Handbook.

Controlled automated discovery of collections of business process models

Automated process discovery techniques aim at extracting process models from information system logs. Existing techniques in this space are effective when applied to relatively small or regular logs, but generate spaghetti-like and sometimes inaccurate models when confronted to logs with high variability. In previous work, trace clustering has been applied in an attempt to reduce the size and complexity of automatically discovered process models. The idea is to split the log into clusters and to discover one model per cluster. This leads to a collection of process models – each one representing a variant of the business process – as opposed to an all-encompassing model. Still, models produced in this way may exhibit unacceptably high complexity and low fitness. In this setting, this paper presents a two-way divide-and-conquer process discovery technique, wherein the discovered process models are split on the one hand by variants and on the other hand hierarchically using subprocess extraction. Splitting is performed in a controlled manner in order to achieve user-defined complexity or fitness thresholds. Experiments on real-life logs show that the technique produces collections of models substantially smaller than those extracted by applying existing trace clustering techniques, while allowing the user to control the fitness of the resulting models.