Business Process Management Workshops

Process fragmentation is the foundation of many state-of-the-art techniques for supporting management, reuse and change of process models. Such techniques vary greatly in terms of which types of processes they are applicable to, what they aim at accomplishing, how they define the resulting process fragments, etc. The comparison, analysis, reuse and selection of the available process fragmentation techniques are hindered by the lack of a common terminology and classification criteria, and by the large discrepancy in the characteristics that are covered when presenting novel fragmentation techniques. This work starts addressing this issue by investigating classification criteria for process fragmentation techniques based on the “seven Ws”, namely Why, What, When, Where, Who, Which, and hoW. The presented classification criteria are applied to some of the process fragmentation approaches available in the literature. In addition to enabling the classification of fragmentation techniques, the classification criteria here presented form a “check-list” for authors of future works in the field of process fragmentation.

Categories:

Process improvement techniques and tools

When multiple similar business processes must be designed, a trade-off is necessary between designing a single, standardized, process or designing multiple, specific, processes. Standardization, on the one hand, helps to benefit from re-use of resources and to reduce redundancy. Specificity, on the other hand, helps to tailor the processes to specific needs. The activity of deciding on this trade-off is called harmonization. This paper operationalizes the notion of process harmonization, identifies aspects that determine harmonization and defines metrics to determine the level of harmonization. Furthermore, it presents the factors that influence the level of harmonization that can be achieved in a company. The harmonization aspects and factors are extracted from case studies in practice. Together the metrics, aspects and factors can be used to determine the current and optimal level of harmonization for a company.

Semi-structured workflow approaches are being recognised as essential to support collaboration whenever ad-hoc work needs to be performed due to the occurrence of unanticipated events in dynamic environments. However, semi-structured workflows need to balance the support of unexpected situations with guidance for the situations where a standard behaviour is wanted. The blended workflow approach proposes an integration of two distinct workflow specifications, the activity-based specification, which precisely defines how to coordinate work for expected situations, and a goal-based specification, which empowers people to accomplish the business process goals using their tacit knowledge. In this paper we describe the blended workflow approach, illustrate it with an example, and identify the compliance properties that a blended workflow approach needs to have to integrate activity and goal specifications.

Business processes are subject to changes due to frequently fluctuating opportunities. The changes has as result a modification of business process models and also the organizational model since both models are jointly linked through the assignment of roles to process activities. A consistent adaptation of both model types (due to changes) still poses challenges. For instance, varying competences and skills are insufficiently considered for the (re-)assignment of roles to process activities. As a consequence, tasks are performed inefficiently. In this paper we will present an organizational model that considers resources’ competences, skills and knowledge. Based on this model the hidden Markov model is applied to efficiently assign roles to process activities. The improvement in task processing through automated role assignment is a significant contribution of this approach.

An important task of business process design is the definition of what and how members of an organization are involved in the activities of the business processes developed within it. In this paper we analyse the capabilities of BPMN 2.0, the de-facto standard for business process modelling, in this regard. The conclusion is that, although it provides some mechanisms to assign resources to business process activities, they present several drawbacks. On the one hand, it does not provide a clear way to relate the assignment of resources with a model of the structure of the organization. On the other hand, it relies on XPath as the default language to assign resources to activities. The consequence is that it has limitations regarding the expressiveness of resource assignment expressions. Furthermore, it makes resource assignment not easy to learn and use since XPath has not been designed for that purpose. To overcome these drawbacks we introduce RAL (Resource Assignment Language), a DSL based on a well-known organizational metamodel that can be used together with BPMN 2.0. RAL provides more expressiveness to the resource assignments and it uses a high-level sintaxis defined to be used by technically unskilled users.

To assure quality in a Business Service it is imperative to engineer quality into the process that produces it. We introduce

f

QDF: a Quality Design Framework for

fine

-

granular

quality control of business process outcomes. The framework defines a Quality Breakdown Structure (QBS) that provides a fine-granular quality definition for process outcomes. QBS is used to derive a Process Breakdown Structure (PrBS) ensuring that the process is engineered-in for quality outcomes. Deploying

f

QDF results in a quality-aware business process, where the quality is designed-in up-front rather than it being an afterthought. We introduce and explain the concepts of

f

QDF and their impact on quality-building in the context of a real-life case study viz., a Document Processing Service.

Process mining is an emerging topic in the BPM marketplace. Recently, several (commercial) software solutions have become available. Due to the lack of an evaluation framework, it is very difficult for potential users to assess the strengths and weaknesses of these process mining tools. As the first step towards such an evaluation framework, we developed a set of process mining use cases and validated these use cases by means of expert interviews and a survey. We present the list of use cases and discuss the insights from our empirical validation. These use cases will then form the basis for a detailed evaluation of current process mining tools on the market.

Processes are not always executed as expected. Deviations assure the necessary flexibility within a company, but also increase possible internal control weaknesses. Since the number of cases following such a deviation can grow very large, it becomes difficult to analyze them case-by-case. This paper proposes a semi-automatic process deviation analysis method which combines process mining with association rule mining to simplify the analysis of deviating cases. Association rule mining is used to group deviating cases into business rules according to similar attribute values. Consequently, only the resulting business rules need to be examined on their acceptability which makes the analysis less complicated. Therefore, this method can be used to support the search for internal control weaknesses.

Process mining techniques try to discover and analyse business processes from recorded process data. These data have to be structured in so called

computer log files

. If processes are supported by different computer systems, merging the recorded data into one log file can be challenging. In this paper we present a computational algorithm, based on the Artificial Immune System algorithm, that we developed to automatically merge separate log files into one log file. We also describe our implementation of this technique, a proof of concept application and a real life test case with promising results.

The paper investigates the relationship between analytical capabilities in the plan, source, make and deliver area of the supply chain and its performance. The effects of analytics on different maturity levels are analyzed with various statistical techniques. A sample of 788 companies from the USA, Europe, Canada, Brazil and China was used. The results indicate the changing impact of business analytics use on performance, meaning that companies on different maturity levels should focus on different areas. The theoretical and practical implications of these findings are thoroughly discussed.

The organizational perspective of process mining supports the discovery of social networks within organizations by analyzing event logs recorded during process execution. However, applying these social network mining techniques to real data generates very complex models that are hard to analyze and understand. In this work we present an approach to overcome these difficulties by focusing on the discovery of communities from such event logs. The clustering of users into communities allows the analysis and visualization of the social network at different levels of abstraction. The proposed approach also makes use of the concept of modularity, which provides an indication of the best division of the social network into community clusters. The approach was implemented in the ProM framework and it was successfully applied in the analysis of the emergency service of a medium-sized hospital.

In order to be able to flexibly adjust a company’s business processes (BPs) there is an increasing interest in flexible Process-Aware Information Systems (PAISs). This increasing flexibility, however, typically implies decreased user guidance by the PAIS and thus poses additional challenges to its users. This work proposes a recommendation system which assists users during process execution to optimize performance goals of the processes. The recommendation system is based on a constraint-based approach for planning and scheduling the BP activities and considers both the control-flow and the resource perspective.

We present a metric for the comparison of business process models. This new metric is based on a representation of a given model as two sets of local relations between pairs of activities in the model. In order to build this two sets, the same relations defined for the Alpha Algorithm [2] are considered. The proposed metric is then applied to hierarchical clustering of business process models and the whole procedure is implemented and made publicly available.

The integration of customers in service processes leads to interruptions in the processing of customer orders. To still enable an efficient delivery, we propose a new approach combining ideas of process mining and statistical methods. The aim of the paper is to identify patterns of customer integration within event logs of a service process and to make the impact of these patterns on the processing time more transparent and predictable. The approach will be applied to a quantitative case study using a financial service process as an example. The results provide the opportunity for identifying adequate steps for improving the control of service processes.

Most Process Mining techniques assume business processes remain steady through time, when in fact their underlying design could evolve over time. Discovery algorithms should be able to automatically find the different versions of a process, providing independent models to describe each of them. In this article, we present an approach that uses the starting time of each process instance as an additional feature to those considered in traditional clustering approaches. By combining control-flow and time features, the clusters formed share both a structural similarity and a temporal proximity. Hence, the process model generated for each cluster should represent a different version of the analyzed business process. A synthetic example set was used for testing, showing the new approach outperforms the basic approach. Although further testing with real data is required, these results motivate us to deepen on this research line.

Process mining can be used to measure the compliance between the actual behavior and the designed process. Traditionally, a single figure expressing the overall process compliance has only limited value to managers trying to improve their processes. This article proposes a new compliance methodology which first clusters the event log into homogeneous groups of event traces and then computes the compliance degree for each cluster separately. Additionally, each cluster is profiled by means of case information, which allows the discrimination between less and more compliant parts of the process. The benefits of this new compliance methodology in a business context are illustrated by means of a case study.

A real-life event log, taken from a Dutch Academic Hospital, provided for the BPI challenge is analyzed using process mining techniques. The log contains events related to treatment and diagnosis steps for patients diagnosed with cancer. Given the heterogeneous nature of these cases, we first demonstrate that it is possible to create more homogeneous subsets of cases (e.g., patients having a particular type of cancer that need to be treated urgently). Such preprocessing is crucial given the variation and variability found in the event log. The discovered homogeneous subsets are analyzed using state-of-the-art process mining approaches. More specifically, we report on the findings discovered using

enhanced fuzzy mining

and

trace alignment

. A dedicated preprocessing ProM plug-in was developed for this challenge. The analysis was done using recent, but pre-existing, ProM plug-ins. The high-level view of our approach is depicted in Fig. 1. Using this approach we are able to uncover many interesting findings that could be used to improve the underlying care processes.

Health-care processes are typically human-centric processes characterized by heterogeneity and a multi-disciplinary nature. This contribution gives an executive summary of our submission for the 2011 Business Process Intelligence Challenge. We proposed both the department-based sub processes and specific treatement/drug focus as new process mining techniques that result in useful information.

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.

This paper identifies a set of workflow patterns necessary to support community-oriented localisation. Workflow pattern discovery is based on use case analysis of five community translation tools, and modelled using the Yet Another Workflow Language (YAWL) notation. An analysis is presented of the support for these baseline patterns in two mainstream enterprise-oriented Translation Management Systems (TMS) - GlobalSight and WorldServer. A gap is identified with respect to the emerging need for community-oriented workflows and their potential support in mainstream enterprise localisation architectures.

The participation of end users on the collaborative design of business process models is particularly challenging because they do not master the existing formal business process modeling languages, and they regard business processes on a case-by-case perspective. On the other hand, end users wish to focus their efforts on their daily work and do not want to be interrupted with peculiar modeling tasks. However, regarding the importance of tacit knowledge about business processes, how can this end users’ knowledge be captured non-intrusively?

This paper presents an ad-hoc workflow system that focus on supporting and capturing human-interactions while using a non-intrusive strategy in the context of end users’ daily operations, and with the support of social software features. Additionally, the information collected through this approach can readily be provided to other stakeholders, including other end users, fostering an implicit collaboration among them.

The integration of social software and BPM can help organizations harness the value of informal relationships and weak ties, without compromising the consolidated business practices embedded in conventional BPM solutions. This paper presents a process design methodology, supported by a tool suite, for addressing the extension of business processes with social features. The social process design exploits an extension of BPMN for capturing social requirements, a gallery of social BPM design patterns that represent reusable solutions to recurrent process socialization requirements, and a model-to-model and mode-to-code transformation technology that automatically produces a process enactment Web application connected with mainstream social platforms.

In recent years social technologies such as wikis, blogs or microblogging have seen an exponential growth in the uptake of their user base making this type of technology one of the most significant networking and knowledge sharing platforms for potentially hundreds of millions of users. However, the adoption of these technologies has been so far mostly for private purposes. First attempts have been made to embed features of social technologies in the corporate IT landscape, and Business Process Management is no exception. This paper aims to consolidate the opportunities for integrating social technologies into the different stages of the business process lifecycle. Thus, it contributes to a conceptualization of this fast growing domain, and can help to categorize academic and corporate development activities.

For a long time, business process management has been based on the understanding that the single point of interaction between the producer and the consumer is at the end of the business process. Products and services are exchanged against the payment. However, there is a growing conviction that both the producer and the consumer can profit from intensifying the interaction during the business process. Value can be co-created between producer and an active consumer, called prosumer. This active involvement of the prosumer is done by ad-hoc asynchronous interactions between producer and a now prosumer called consumer. Social software is an ideal means for supporting these value-providing asynchronous interactions.

Peer production uses the collaborative intelligence of its environment by relying on self-managed, decentralized coordination. Social software offers a broad variety of methods and applications for simplifying communication and harnessing collective intelligence. Status feeds, which are regularly used within social networks, may be considered as an important feature of these approaches. This article examines the use of status feeds for supporting the execution of non-predictable business processes. Given the context of Enterprise 2.0, existing business process management approaches will be discussed before developing resulting requirements for a feed-based system which will then be implemented as a prototype and showcased via an exemplary peer production process. The implementation is followed by an evaluation of the findings and results.

This talk discusses the challenges of enabling and supporting cross enterprise collaboration (CEC) from a technology perspective. We use the collaboration requirements of multiple service providers in the context of multi-sourcing service engagements as an exemplary scenario to study this problem. We provide a conceptual model for examining CEC from various stakeholders’ perspectives, collaboration at the business process level and technology enablement requirements at different level of the stack. Finally, we present a vision and technical architecture for offering the technology support to facilitate cross enterprise collaboration, offered as a service (called CEC as a Service).

This position paper provides an informal framework for thinking about Cross-Enterprise Collaboration (CEC), which is an increasingly crucial factor in driving business results. We argue that sustaining effective CEC generally requires careful consideration of technology to support

both

person-to-person

and

system-to-system interaction. We outline the main ingredients of CEC, identify common CEC patterns, and discuss some key technologies that enable collaboration across enterprise boundaries.

Standardized business documents are a prerequisite for successful electronic information exchange in inter-organizational systems. These documents are typically defined through Standard Developing Organizations (SDOs) such as the United Nations Centre for Trade Facilitation and eBusiness (UN/CEFACT). In today’s highly dynamic environment with ever-changing market demands, SDOs are confronted with the need to constantly evolve their standardized business documents based on the needs of business partners utilizing these documents. However, the business document development process between SDOs and business partners is currently lacking efficient collaborative support. In this position paper, we present (i) a reference model supporting hierarchical, collaborative and cross-organizational business document modeling, (ii) a conflict resolution model to find a consolidated version of a new business document model as well as (iii) our vision of a Configurable Collaboration-Aware Online Model Repository.

The verification of collaborative processes is a key issue to consider in cross-organizational modeling methodologies. Some of the existing verification approaches provide only partial support, whereas others impose some restrictions to verify models with advanced control flow, compromise (completely or partially) the enterprise autonomy, or are focused on technology-dependent specifications. In order to deal with these issues we introduce Global Interaction Nets, which are based on Hierarchical and Colored Petri Nets, and the Global Interaction Soundness property, which was adapted from the classical definition of soundness, as the main correctness criterion. The method can be used to formalize and verify models defined with different modeling languages. In addition, we apply the method through a case study modeled with UP-ColBPIP, which is a modeling language for collaborative processes, and formalize its constructs by means of Global Interaction Nets.

The planning of complex logistics service systems is increasingly characterized as a collaborative process with various participants involved. The planning process of a logistics service system can be rendered by a Fourth Party Logistics Service Provider (4PL) together with an existing network of logistics partners. Simulation can be used to improve the decision-making process in the planning phase and to detect errors that can become cost intensive in the future. This paper outlines how simulation is integrated into a planning approach for a 4PL. The focus is on the derivation of goals and requirements from the specific characteristics of a 4PL. Based on these goals and requirements an initial integrated planning and simulation procedure is presented.

Semantic technology enables a bridge between the currently isolated worlds of information retrieval and process management. Relevant and required information is selected and assigned to any process instance by automatically and dynamically linked enterprise data to support each process participant. This approach consequently implements the idea of automized information logistics.

Business Process Management (BPM) has gained considerable importance in research and practice in recent years and has become one of the currently mostly discussed fields of research in the Information Systems (IS) discipline. BPM research aims to develop innovative methods and techniques for the management of business processes in the first place and, moreover, to build and further develop theory, which is an important objective of every scientific discipline. The state of theory is commonly considered a significant indicator for the maturity and grounding of a field of research. This article investigates theoretical foundations of empirical BPM research based on conceptual considerations and a review of empirical BPM literature. Our analysis shows that empirical BPM research is only to a certain extent guided by existing theory. Furthermore, the investigated contributions often refer to theories originating from different other fields of research, like economics or sociology. Implications and the potential of dedicated BPM theory development by means of empirical research are discussed.

An increasing data overload makes it difficult to provide the needed information to knowledge-workers and decision-makers in today’s process-oriented enterprises. The main problem is to identify the information being relevant in a given process context. Moreover, there are new ways of collaboration in the context of distributed processes (e.g., automotive engineering, patient treatment). The goal is to provide the right process information, in the right format and quality, at the right place, at the right point in time to the right people. Picking up this goal, enterprises crave for an intelligent and process-oriented information logistics. In this paper we investigate fundamental issues enabling such information logistics based on two exploratory case studies in the automotive and the clinical domain. Additionally, we present results of an online survey with 219 participants supporting our case study findings. Our research does not only reveal different types of process information, but also allows for the derivation of factors determining its relevance. Understanding these factors, in turn, is a fundamental prerequisite to realize effective process-oriented information logistics.

We develop a workshop technique for process co-creation with domain experts called tangible business process modeling. After assessing the idea in a laboratory experiment, we started workshops with professionals in the field. This paper illustrates how we used action research in two subsequent studies in which groups modeled BPMN and EPCs using tangible tiles on a table.

The practical result is best practice guidance for moderators applying tangible process modeling. Our research interest is to investigate the differences between tangible modeling and other techniques. In the lab experiment we found that tangible modeling supports user engagement and validated results. In the field, we compare the workshop performance and outcome to software-supported workshops. We found tangible modeling to be competitive in speed and result.

Empirical studies of business process modeling typically aim at understanding factors that can improve model quality. We identify two limitations of such studies. First, the quality dimensions usually addressed are mainly syntactic and pragmatic, not addressing semantic quality sufficiently. Second, while findings related to model understanding have been anchored in cognitive theories, findings related to model construction have remained mostly unexplained. This paper proposes to study the process of process modeling, based on problem solving theories. Specifically, the work takes the approach that problems are first conceptualized as mental models, to which solution methods are applied. The paper suggests that investigating these two phases can help understand and hence improve semantic and syntactic quality of process models. The paper reports on an empirical study addressing the mental model created during process model development, demonstrating the feasibility of such studies. It then suggests designs for other studies that follow this direction.

The quality of a business process model is presumably highly dependent upon the modeling process that was followed to create it. Still, there is a lack of concepts to investigate this connection empirically. This paper introduces the formal concept of a phase diagram through which the modeling process can be analyzed, and a corresponding implementation to study a modeler’s sequence of actions. In an experiment building on these assets, we observed a group of modelers engaging in the act of modeling. The collected data is used to demonstrate our approach for analyzing the process of process modeling. Additionally, we are presenting first insights and sketch requirements for future experiments.

Streams of research are emerging that emphasize the advantages of using declarative process modeling languages over more traditional, imperative approaches. In particular, the declarative modeling approach is known for its ability to cope with the limited flexibility of the imperative approach. However, there is still not much empirical insight into the actual strengths and the applicability of each modeling paradigm. In this paper, we investigate in an experimental setting if either the imperative or the declarative process modeling approach is superior with respect to process model understanding. Even when task types are considered that should better match one or the other, our study finds that imperative process modeling languages appear to be connected with better understanding.

In the domain of Process-Aware Information Systems, business processes, events, rules and information models appear intertwined and this calls for a representation that integrates different viewpoints. A motivating example is the mapping of several customer orders to one bulk supplier order: a distributor may wait until the number of items needed by customers entitles them to take advantage of a quantity discount. The individual events representing the incoming customer orders need to be mapped to complex events that trigger the submissions of supplier orders. Complex events are defined through rules that must be able to access the properties of the events involved; rules then need an information model providing the relevant information at an adequate abstraction level. This paper presents a notation, called Chant, which consists of three interrelated models, i.e. the process model, the information model and the rule model. Processes imply choices, which can be classified into a number of selection patterns. Two major categories are addressed in this paper: they are referred to as data selection patterns and path selection patterns.

We present in this paper logical tools for verification of Complex Event Processing (CEP) system at design time, and maintenance at runtime. Although the framework is general enough for most applications, we focus on its use in Business Process Management (BPM).

In software development projects, process execution typically lacks automated guidance and support, and process models remain rather abstract. The environment is sufficiently dynamic that unforeseen situations can occur due to various events that lead to potential aberrations and process governance issues. To alleviate this problem, a dynamic exception handling approach for software engineering processes is presented that incorporates event detection and processing facilities and semantic classification capabilities with a dynamic process-aware information system. A scenario is used to illustrate how this approach supports exception handling with different levels of available contextual knowledge in concordance with software engineering environment relations to the development process and the inherent dynamicity of such relations.

Ubiquitous technologies such as radio frequency identification (RFID) and wireless sensor network (WSN) have enabled companies to realize more rapid and agile manufacturing and service systems. In this paper, we design an event-driven ubiquitous process management system by using complex event processing technology for RFID and WSN. Such ubiquitous process management can be applied to manufacturing, logistics, and supply chain process. In particular, we focus on complex event processing of sensor and RFID events in order to integrate them to business rules of business process. The ubiquitous event processing helps to filter and aggregate ubiquitous events, to detect event patterns from sensors and RFID by means of event pattern languages (EPL), and trigger event-condition-action (ECA) rules in logistics processes.

Event-driven Business Process Management (edBPM) is based upon exchanging and processing business events. As yet, no commonly adopted event format for communicating business events between distributed event producers and consumers has emerged. This paper is an effort to review the status quo of event formats against the requirements of edBPM. We particularly discuss BPAF, CBE, and XES as promising candidates and identify prospects for development.

Business rules define and constrain various aspects of the business, such as vocabulary, control-flow and organizational issues. Although the presence of many languages for expressing business rules that differ in expressivenes, knowledge representation mechanism and execution model, none of these cover all the necessary business aspects. In this paper, we show how business rules, not only vocabulary rules, but also control-flow rules and organizational rules can be expressed in SBVR and translated using patterns into a more uniform event mechanism, such that the event handling could provide an integrated enforcement of business rules of many kinds. As a proof of concept a prototype tool integrates this pattern mechanism and provides an execution environment in which these rules are enforced.

As a result of globalization and the falling profit margin, companies started to outsource their processes ensured by contracts. This is also happening within the logistics service sector. The resulting networks, which must be managed and monitored, have a very collaborative and dynamic character. Based on the Fourth Party Logistics Provider business model that aims at establishing as a coordinator of such networks the usability of complex event processing is discussed. A typical workflow exemplifies the challenges in terms of monitoring. Besides the theoretical model a possible solution approach with the use of complex event processing is discussed.

The European PLAY project aims at providing an event management platform. That platform should be tested and stimulated through use-cases. Obviously, these use-cases should be relevant on the business point of view, but to make them relevant, it could be interesting to be able to redesign them as often as required (to improve their business context). This article presents a specific use-case for the PLAY platform evaluation and also a technical framework dedicated to make this use-case as agile as possible. The general principle is to bridge the gap between business level (process models) and technical level (workflows definition and web-services implementation). The way the use-case will be simulated (to stimulate the PLAY platform) and the way the use-case will be designed and potentially re-designed (to be simulated) are described in this article.

Today’s fast, competitive and extremely volatile markets exert a great deal of pressure on businesses to react quicker against the changes, and sometimes even before the changes actually happen. A late action can potentially result in a legal compliance failure or violation of service level agreements (SLA’s). A business analyst needs to be notified before these failures and violations occur. This paper proposes an approach that enables real-time and process-centric decision support in the form of performance prediction as an application of Event-Driven Business Process Management (EDBPM). The ability of simulations to produce future-events, which are of the same type like the live-events generated by the really executed business process, is utilised. Live-events and simulated future-events can therefore be treated by a Complex-Event Processing (CEP) engine in the same way and parameters representing the historic, current, and future performance of the business process can be easily computed.