Managing context in business process management systems

Businesses need to continuously focus on change and innovation in order to survive in dynamic environments. The ability of an organization to deploy appropriate business processes requires that the fit between business processes and systems that support the management of these processes is continuously maintained and evolved. Acquisition and use of the knowledge about the context in which business processes are defined, modified, and implemented can help maintain this fit. We identify requirements for a business process management system (BPMS) capable of managing contextual knowledge. Based on these requirements, we have enhanced KOPeR, a knowledge-based system for business process improvement, with an explanation facility that can acquire and maintain knowledge about the context behind process definitions and design choices. A case study that illustrates the functionalities of this system which is designed to improve the fit between business processes and BPMS is presented.

Workflow simulation for operational decision support using event graph through process mining

It is increasingly common to see computer-based simulation being used as a vehicle to model and analyze business processes in relation to process management and improvement. While there are a number of business process management (BPM) and business process simulation (BPS) methodologies, approaches and tools available, it is more desirable to have a systemic BPS approach for operational decision support, from constructing process models based on historical data to simulating processes for typical and common problems. In this paper, we have proposed a generic approach of BPS for operational decision support which includes business processes modeling and workflow simulation with the models generated. Processes are modeled with event graphs through process mining from workflow logs that have integrated comprehensive information about the control-flow, data and resource aspects of a business process. A case study of a credit card application is presented to illustrate the steps involved in constructing an event graph. The evaluation detail is also given in terms of precision, generalization and robustness. Based on the event graph model constructed, we simulate the process under different scenarios and analyze the simulation logs for three generic problems in the case study: 1) suitable resource allocation plan for different case arrival rates; 2) teamwork performance under different case arrival rates; and 3) evaluation and prediction for personal performances. Our experimental results show that the proposed approach is able to model business processes using event graphs and simulate the processes for common operational decision support which collectively play an important role in process management and improvement.     

Version management for business process schema evolution

The current business environment changes rapidly, dictated by user requirements and market opportunities. Organisations are therefore driven to continuously adapt their business processes to new conditions. Thus, management of business process schema evolution, particularly process version control, is in great demand to capture the dynamics of business process schema changes. This paper aims to facilitate version control for business process schema evolution, with an emphasis on version compatibility, co-existence of multiple versions and dynamic version shifts. A multi-level versioning approach is established to specify dependency between business process schema evolutions, and a novel version preserving graph model is proposed to record business process schema evolutions. A set of business process schema updating operations is devised to support the entire set of process change patterns. By maintaining sufficient and necessary schema and version information, our approach provides comprehensive support for navigating process instance executions of different and changing versions, and deriving the process schema of a certain version. A prototype is also implemented for the proof-of-concept purpose.     

基于业务规则的信息系统建模方法研究

信息系统的开发需要对业务过程进行建模。论文提出一种从业务规则的角度对业务过程进行建模的方法。通过对业务规则的分析，讨论了将业务规则转化为建模构件的方法，研究了构件之间的关系——元模型，并给出了利用这些构件建立业务过程的规则模型的方法。最后给出了一个业务规则模型的实例。     

From business to software: a B2B survey

In recent years business-to-business (B2B) e-commerce has been subject to major rethinking. A paradigm shift can be observed from document centric file-based interchange of business information to process-centric and, finally to service-based information exchange. On a business level, a lot of work has been done to capture business models and collaborative business processes of an enterprise; further initiatives address the identification of customer services and the formalization of business service level agreements (SLA). On a lower, i.e., technical level, the focus is on moving towards service-oriented architectures (SOA). These developments promise more flexibility, a market entry at lower costs and an easier IT-alignment to changing market conditions. This explains the overwhelming quantity of specifications and approaches targeting the area of B2B—these approaches are partly competing and overlapping. In this paper we provide a survey of the most promising approaches at both levels and classify them using the Open-edi reference model standardized by ISO. Whereas on the technical level, service-oriented architecture is becoming the predominant approach, on the business level the landscape is more heterogeneous. In this context, we propose—in line with the services science approach—to integrate business modeling with process modeling in order to make the transformation from business services to Web services more transparent.     

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events

Monitoring the performances of a business process is a key issue in many organizations, especially when the process must comply with predefined performance constraints. In such a case, empowering the monitoring system with prediction capabilities would allow us to know in advance a constraint violation, and possibly trigger corrective measures to eventually prevent the violation. Despite the problem of making run-time predictions for a process, based on pre-mortem log data, is an active research topic in Process Mining, current predictive monitoring approaches in this field only support predictions at the level of a single process instance, whereas process performance constraints are often defined in an aggregated form, according to predefined time windows. Moreover, most of these approaches cannot work well on the traces of a lowly-structured business process when these traces do not refer to well-defined process tasks/activities. For such a challenging setting, we define an approach to the problem of predicting whether the process instances of a given (unfinished) time window will violate an aggregate performance requirement. The approach mainly rely on inducing and integrating two complementary predictive models: (1) a clustering-based predictor for estimating the outcome of each ongoing process instance, (2) a time-series predictor for estimating the performance outcome of “future” process instances that will fall in the window after the moment when the prediction is being made (i.e. instances, not started yet, that will start by the end of the window). Both models are expected to benefit from the availability of aggregate context data regarding the environment that surrounds the process. This discovery approach is conceived as the core of an advanced performance monitoring system, for which an event-based conceptual architecture is here proposed. Tests on real-life event data confirmed the validity of our approach, in terms of accuracy, robustness, scalability, and usability.     

Business process mining: An industrial application

Contemporary information systems (e.g., WfM, ERP, CRM, SCM, and B2B systems) record business events in so-called event logs. Business process mining takes these logs to discover process, control, data, organizational, and social structures. Although many researchers are developing new and more powerful process mining techniques and software vendors are incorporating these in their software, few of the more advanced process mining techniques have been tested on real-life processes. This paper describes the application of process mining in one of the provincial offices of the Dutch National Public Works Department, responsible for the construction and maintenance of the road and water infrastructure. Using a variety of process mining techniques, we analyzed the processing of invoices sent by the various subcontractors and suppliers from three different perspectives: (1) the process perspective, (2) the organizational perspective, and (3) the case perspective. For this purpose, we used some of the tools developed in the context of the ProM framework. The goal of this paper is to demonstrate the applicability of process mining in general and our algorithms and tools in particular.     

Simplifying process model abstraction: Techniques for generating model names

The increased adoption of business process management approaches, tools, and practices has led organizations to accumulate large collections of business process models. These collections can easily include from a hundred to a thousand models, especially in the context of multinational corporations or as a result of organizational mergers and acquisitions. A concrete problem is thus how to maintain these large repositories in such a way that their complexity does not hamper their practical usefulness as a means to describe and communicate business operations. This paper proposes a technique to automatically infer suitable names for business process models and fragments thereof. This technique is useful for model abstraction scenarios, as for instance when user-specific views of a repository are required, or as part of a refactoring initiative aimed to simplify the repository's complexity. The technique is grounded in an adaptation of the theory of meaning to the realm of business process models. We implemented the technique in a prototype tool and conducted an extensive evaluation using three process model collections from practice and a case study involving process modelers with different experience.     

Discovery and analysis of e-mail-driven business processes

E-mail is used as the primary tool for business communication and collaboration. This paper presents a novel e-mail interaction mining method to discover and analyze e-mail-driven business processes. An e-mail-driven business process is perceived as a human collaboration process that consists of interactions between people who may each play different roles. The notion of message threads (i.e. sets of e-mail messages that are replies to each other) is used as the fundamental building block to construct the interactions in the e-mail-driven business process. The proposed method adopts an interaction-centric business process modeling language to visualize the discovered e-mail-driven business process. The method identifies message threads from an e-mail archive, and constructs an interaction-centric process model based on the temporal order and similarity of the threads. Process-related information is extracted from e-mail header fields. A software tool, named E-mail Interaction Miner, implements the proposed method. A case study is used to apply and evaluate the method on a set of e-mails collected from a Dutch gas transport company. The evaluation results are discussed. These results comprise business process improvement opportunities for the case organization, and contributions to theory and language development.     

VIVACE: A framework for the systematic evaluation of variability support in process-aware information systems

ContextThe increasing adoption of process-aware information systems (PAISs) such as workflow management systems, enterprise resource planning systems, or case management systems, together with the high variability in business processes (e.g., sales processes may vary depending on the respective products and countries), has resulted in large industrial process model repositories. To cope with this business process variability, the proper management of process variants along the entire process lifecycle becomes crucial.ObjectiveThe goal of this paper is to develop a fundamental understanding of business process variability. In particular, the paper will provide a framework for assessing and comparing process variability approaches and the support they provide for the different phases of the business process lifecycle (i.e., process analysis and design, configuration, enactment, diagnosis, and evolution).MethodWe conducted a systematic literature review (SLR) in order to discover how process variability is supported by existing approaches.ResultsThe SLR resulted in 63 primary studies which were deeply analyzed. Based on this analysis, we derived the VIVACE framework. VIVACE allows assessing the expressiveness of a process modeling language regarding the explicit specification of process variability. Furthermore, the support provided by a process-aware information system to properly deal with process model variants can be assessed with VIVACE as well.ConclusionsVIVACE provides an empirically-grounded framework for process engineers that enables them to evaluate existing process variability approaches as well as to select that variability approach meeting their requirements best. Finally, it helps process engineers in implementing PAISs supporting process variability along the entire process lifecycle.     

Business alignment: using process mining as a tool for Delta analysis and conformance testing

Increasingly, business processes are being controlled and/or monitored by information systems. As a result, many business processes leave their “footprints” in transactional information systems, i.e., business events are recorded in so-called event logs. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. In this paper we focus on the potential use of process mining for measuring business alignment, i.e., comparing the real behavior of an information system or its users with the intended or expected behavior. We identify two ways to create and/or maintain the fit between business processes and supporting information systems: Delta analysis and conformance testing. Delta analysis compares the discovered model (i.e., an abstraction derived from the actual process) with some predefined processes model (e.g., the workflow model or reference model used to configure the system). Conformance testing attempts to quantify the “fit” between the event log and some predefined processes model. In this paper, we show that Delta analysis and conformance testing can be used to analyze business alignment as long as the actual events are logged and users have some control over the process.

Business process archeology using MARBLE

Context

Legacy information systems age over time. These systems cannot be thrown away because they store a significant amount of valuable business knowledge over time, and they cannot be entirely replaced at an acceptable cost. This circumstance is similar to that of the monuments of ancient civilizations, which have aged but still hold meaningful information about their civilizations. Evolutionary maintenance is the most suitable mechanism to deal with the software ageing problem since it preserves business knowledge. But first, recovering the underlying business knowledge in legacy systems is necessary in order to preserve this vital heritage.

Objective

This paper proposes and validates a method for recovering and rebuilding business processes from legacy information systems. This method, which can be considered a business process archeology, makes it possible to preserve the business knowledge in legacy information systems.

Method

The business process archeology method is framed in MARBLE, a generic framework based on Architecture-Driven Modernization (ADM), which uses the Knowledge Discovery Metamodel (KDM) standard. The proposed method is validated using a case study that involves a real-life legacy system. The case study is conducted following the case study protocol proposed by Brereton et al.

Results

The study reports that the proposed method makes it possible to obtain business process models from legacy systems with adequate levels of accuracy. In addition, the effectiveness of the proposed method is also validated positively.

Conclusion

The proposed method semi-automatically rebuilds the hidden business processes embedded in a legacy system. Therefore, the business process archeology method quickly allows business experts to have a meaningful understanding of the organization’s business processes. This proposal is less time-consuming and more exhaustive (since it considers the embedded business knowledge) than a manual process redesign by experts from scratch. In addition, it helps maintainers to extract the business knowledge needed for the system to evolve.     

Assessing flexibility in event-driven process adaptation

Business process management (BPM) has emerged as a prominent information management approach focusing on the design, execution and governance of organizational business processes. The ability to deal with both foreseen and unforeseen changes in business processes is considered critical for contemporary business process management systems. This paper proposes an approach that couples an event-driven framework for detecting and reasoning in situations that pose the need for process adaptations with MCDM methods for selecting adaptations. The proposed approach has been implemented in an aspect-oriented extension of a BPMN2.0 engine in order to enact adaptations of business processes in real-time.     

Determining ERP customization choices using nominal group technique and analytical hierarchy process

An enterprise resource planning (ERP) system is an information system that supports and integrates many facets of a business. A critical issue in ERP implementation is how to bridge the gap between the ERP system and an organization's business processes by customizing either the system, or the business processes of the organization, or both. Literature review shows that customization is a major hindrance in most of the ERP implementation projects. This research applies nominal group technique (NGT) and analytical hierarchy process (AHP) techniques to Luo and Strong's framework to help organizations determine feasible customization choices for their ERP implementation initiatives. A case study is presented to illustrate its applicability in practice. The study has theoretical and practical implications for our understanding of ERP implementation process.     

Information leak detection in business process models: Theory,application, and tool support

Despite the correct deployment of access control mechanisms, information leaks can persist and threaten the reliability of business process execution. This paper presents an automated and effective approach for the verification of information flow control for business process models. Building on the concept of place-based non-interference and declassification, the core contribution of this paper is the application of Petri net reachability to detect places in which information leaks occur. Such a feature allows for the use of state-of-the-art tool support to model-check business process models and detect leaks. We show that the approach is sound and complete, and present the Anica tool to identify leaks. An extensive evaluation comprising over 550 industrial process models is carried out and shows that information flow analysis of process models can be done in milliseconds. This motivates a tight integration of business process modeling and non-interference checking.     

From fine-grained to abstract process models: A semantic approach

Organizations actively managing their business processes face a rapid growth of the number of process models that they maintain. Business process model abstraction has proven to be an effective means to generate readable, high-level views on business process models by showing coarse-grained activities and leaving out irrelevant details. In this way, abstraction facilitates a more efficient management of process models, as a single model can provide for many relevant views. Yet, it is an open question how to perform abstraction in the same skillful way as experienced modelers combine activities into more abstract tasks. This paper presents an approach that uses semantic information of a process model to decide on which activities belong together, which extends beyond existing approaches that merely exploit model structural characteristics. The contribution of this paper is twofold: we propose a novel activity aggregation method and suggest how to discover the activity aggregation habits of human modelers. In an experimental validation, we use an industrial process model repository to compare the developed activity aggregation method with actual modeling decisions, and observe a strong correlation between the two. The presented work is expected to contribute to the development of modeling support for the effective process model abstraction.     

Modeling and execution of event stream processing in business processes

The Internet of Things and Cyber-physical Systems provide enormous amounts of real-time data in the form of streams of events. Businesses can benefit from the integration of these real-world data; new services can be provided to customers, or existing business processes can be improved. Events are a well-known concept in business processes. However, there is no appropriate abstraction mechanism to encapsulate event stream processing in units that represent business functions in a coherent manner across the process modeling, process execution, and IT infrastructure layer. In this paper we present Event Stream Processing Units (SPUs) as such an abstraction mechanism. SPUs encapsulate application logic for event stream processing and enable a seamless transition between process models, executable process representations, and components at the IT layer. We derive requirements for SPUs and introduce EPC and BPMN extensions to model SPUs at the abstract and at the technical process layer. We introduce a transformation from SPUs in EPCs to SPUs in BPMN and implement our modeling notation extensions in Software AG ARIS. We present a runtime infrastructure that executes SPUs and supports implicit invocation and completion semantics. We illustrate our approach using a logistics process as running example.     

Business processes—attempts to find a definition

Definitions of business process given in much of the literature on Business Process Management are limited in depth and their related models of business processes are correspondingly constrained. After giving a brief history of the progress of business process modeling techniques from production systems to the office environment, this paper proposes that most definitions are based on machine metaphor type explorations of a process. While these techniques are often rich and illuminating it is suggested that they are too limited to express the true nature of business processes that need to develop and adapt to today's challenging environment.     

Modelling non-functional requirements of business processes

This paper presents an approach to the identification and inclusion of ‘non-functional’ aspects of a business process in modelling for business improvement. The notion of non-functional requirements (NFRs) is borrowed from software engineering, and a method developed in that field for linking NFRs to conceptual models is adapted and applied to business process modelling. Translated into this domain, NFRs are equated with the general or overall quality attributes of a business process, which, though essential aspects of any effective process, are not well captured in a functionally oriented process model. Using an example of a healthcare process (cancer registration in Jordan). We show how an analysis and evaluation of NFRs can be applied to a process model developed with role activity diagramming (RAD) to operationalise desirable quality features more explicitly in the model. This gives a useful extension to RAD and similar modelling methods, as well as providing a basis for business improvement.