Marcello La Rosa

Process Mining Manifesto

Process mining techniques are able to extract knowledge from event logs commonly available in today’s information systems. These techniques provide new means to discover, monitor, and improve processes in a variety of application domains. There are two main drivers for the growing interest in process mining. On the one hand, more and more events are being recorded, thus, providing detailed information about the history of processes. On the other hand, there is a need to improve and support business processes in competitive and rapidly changing environments. This manifesto is created by the IEEE Task Force on Process Mining and aims to promote the topic of process mining. Moreover, by defining a set of guiding principles and listing important challenges, this manifesto hopes to serve as a guide for software developers, scientists, consultants, business managers, and end-users. The goal is to increase the maturity of process mining as a new tool to improve the (re)design, control, and support of operational business processes.

Business Process Model Merging: An Approach to Business Process Consolidation

This article addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The article considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models -- typically representing variants of the same underlying process -- with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The article presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modeling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modeling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modeling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

Editorial: Managing large collections of business process models-Current techniques and challenges

Nowadays, business process management is an important approach for managing organizations from an operational perspective. As a consequence, it is common to see organizations develop collections of hundreds or even thousands of business process models. Such large collections of process models bring new challenges and provide new opportunities, as the knowledge that they encapsulate requires to be properly managed. Therefore, a variety of techniques for managing large collections of business process models is being developed. The goal of this paper is to provide an overview of the management techniques that currently exist, as well as the open research challenges that they pose.

Questionnaire-based Variability Modeling for System Configuration

Variability management is a recurrent issue in systems engineering. It arises for example in enterprise systems, where modules are configured and composed to meet the requirements of individual customers based on modifications to a reference model. It also manifests itself in the context of software product families, where variants of a system are built from a common code base. This paper proposes an approach to capture system variability based on questionnaire models that include order dependencies and domain constraints. The paper presents analysis techniques to detect circular dependencies and contradictory constraints in questionnaire models, as well as techniques to incrementally prevent invalid configurations by restricting the space of allowed answers to a question based on previous answers. The approach has been implemented as a toolset and has been used in practice to capture configurable process models for film post-production.

Merging business process models

This paper addresses the following problem: given two business process models, create a process model that is the union of the process models given as input. In other words, the behavior of the produced process model should encompass that of the input models. The paper describes an algorithm that produces a single configurable process model from a pair of process models. The algorithm works by extracting the common parts of the input process models, creating a single copy of them, and appending the differences as branches of configurable connectors. This way, the merged process model is kept as small as possible, while still capturing all the behavior of the input models. Moreover, analysts are able to trace back which model(s) a given element in the merged model originates from. The algorithm has been prototyped and tested against process models taken from several application domains.

Preserving correctness during business process model configuration

A configurable process model captures a family of related process models in a single artifact. Such models are intended to be configured to fit the requirements of specific organizations or projects, leading to individualized process models that are subsequently used for domain analysis or solution design. This article proposes a formal foundation for individualizing configurable process models incrementally, while preserving correctness, both with respect to syntax and behavioral semantics. Specifically, assuming the configurable process model is behaviorally sound, the individualized process models are guaranteed to be sound. The theory is first developed in the context of Petri nets and then extended to a process modeling notation widely used in practice, namely Event-driven Process Chains.

Configurable Process Models: Experiences from a Municipality Case Study

Configurable process models integrate different variants of a business process into a single model. Through configuration users of such models can then combine the variants to derive a process model optimally fitting their individual needs. While techniques for such models were suggested in previous research, this paper presents a case study in which these techniques were extensively tested on a real-world scenario. We gathered information from four Dutch municipalities on registration processes executed on a daily basis. For each process we identified variations among municipalities and integrated them into a single, configurable process model, which can be executed in the YAWL workflow environment. We then evaluated the approach through interviews with organizations that support municipalities in organizing and executing their processes. The paper reports on both the feedback of the interviewed partners and our own observations during the model creation.

Questionnaire-driven configuration of reference process models

Reference models are a widely accepted means to facilitate reusable information system and organizational design. At present, besides domain knowledge, the configuration of a reference model requires a thorough understanding of the notation it is captured in. This hinders the involvement of domain experts without specialized modeling background, in the configuration of reference models. In this paper, we propose a questionnaire-driven approach to reference model configuration which abstracts away from the modeling language. For illustration, we show how this approach can be applied to reference process models captured in the Configurable EPC notation. To demonstrate its applicability, the proposal has been implemented as a toolset that guides users through the configuration process by means of a form-based interface.

Beyond Control-Flow: Extending Business Process Configuration to Roles and Objects

A configurable process model is an integrated representation of multiple variants of a business process. It is designed to be individualized to meet a particular set of requirements. As such, configurable process models promote systematic reuse of proven or common practices. Existing notations for configurable process modeling focus on capturing tasks and control-flow dependencies, neglecting equally important aspects of business processes such as data flow, material flow and resource management. This paper fills this gap by proposing an integrated meta-model for configurable processes with advanced features for capturing resources involved in the performance of tasks (through task-role associations) as well as flow of data and physical artifacts (through task-object associations). Although embodied as an extension of a popular process modeling notation, namely EPC, the meta-model is defined in an abstract and formal manner to make it applicable to other notations.