Towards collaborative modeling of business processes on large interactive touch display walls

Analyzing and redesigning business processes is a complex task, which requires the collaboration of multiple actors. Current approaches focus on workshops where process stakeholders together with modeling experts create a graphical visualization of a process in a model. Within these workshops, stakeholders are mostly limited to verbal contributions, which are integrated into a process model by a modeling expert using traditional input devices. This limitation negatively affects the collaboration outcome and also the perception of the collaboration itself. In order to overcome this problem we created CubeBPM – a system that allows groups of actors to interact with process models through a touch based interface on a large interactive touch display wall. Using this system for collaborative modeling, we expect to provide a more effective collaboration environment thus improving modeling performance and collaboration.

Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

Complete and interpretable conformance checking of business processes

This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.

ITS Training: 'VLE - no distance too far - enhancing the learner journey and business processes'

ITS Training has undergone a revolutionary transformation in the past two years. The company has saved money, generated more business, improved recruitment, retention and achievement and expanded throughout the world because of its virtual learning environment (VLE): the ‘Student Campus'. Under its previous paper-based distance learning programme it was a hard enough task to deliver lectures to students in Liverpool. Now, the company has a classroom of learners in Tokyo, Japan.

pessimistic predicate/transform model for long running business processes

Many business processes in enterprise applications are both long running and transactional in nature. However, no current transaction model can provide full transaction support for such long running business processes. This paper proposes a new transaction model, the pessimistic predicate/transform (PP/T) model, which can provide full transaction support for long running business processes. A framework was proposed on the enterprise JavaBeans platform to implement the PP/T model. The framework enables application developers to focus on the business logic, with the underlying platform providing the required transactional semantics. The development and maintenance effort are therefore greatly reduced. Simulations show that the model has a sound concurrency management ability for long running business processes.

Acknowledging risks when deciding to outsource business processes : the case of data theft

Outsourcing is generally framed in terms of benefits and cost savings, rather than risks. One important risk is “data theft”. This paper draws upon a longitudinal study into IT and business process outsourcing to present a theoretical model incorporating risk. Sources include qualitative interviews with purchasers, non purchasers, and vendors of outsourced business process services. It concludes that data theft is an under-acknowledged risk in all business process outsourcing (BPO), but is higher for offshore outsourcing. This risk may be mitigated, but when factored into the business case can invalidate typically small cost savings. In acknowledging and adequately costing this risk, decision-makers may find BPO, particularly where offshore vendors are involved, less attractive.

Analysing business processes to manage and resolve strategic issues in a manufacturing business

This paper demonstrates the value of applying heuristics to knowledge systems of business processes in a manufacturing company to resolve strategic issues and enable the attainment of strategic business goals. The manufacturing company was losing market share through not being able to get its new products to market quickly enough. The research illustrates the ‘location’ and use of information systems in a manufacturing context. The researchers collected the specific business process knowledge in the company and developed a knowledge management system and then applied heuristics to the ‘AS IS’ manufacturing process to determine better models of manufacturing that would enable faster to market product development and thus enable better strategic alignment between company expectations and realisation of market share. The paper highlights the strategic use of information systems as a means of directly solving business problems.

Implementing green business processes : the importance of functional affordances of information systems

An environmentally sustainable and thus green business process is one that delivers organizational value whilst also exerting a minimal impact on the natural environment. Recent works from the field of Information Systems (IS) have argued that information systems can contribute to the design and implementation of sustainable business processes. While prior research has investigated how information systems can be used in order to support sustainable business practices, there is still a void as to the actual changes that business processes have to undergo in order to become environmentally sustainable, and the specific role that information systems play in enabling this change. In this paper, we provide a conceptualization of environmentally sustainable business processes, and discuss the role of functional affordances of information systems in enabling both incremental and radical changes in order to make processes environmentally sustainable. Our conceptualization is based on (a) a fundamental definition of the concept of environmental sustainability, grounded in two basic components: the environmental source and sink functions of any project or activity, and (b) the concept of functional affordances, which describe the potential uses originating in the material properties of information systems in relation to their use context. In order to illustrate the application of our framework and provide a first evaluation, we analyse two examples from prior research where information systems impacted on the sustainability of business processes.

Flexibility and modeling in business processes: a multi-dimensional relationship

Over the last few years, Business Process Management (BPM) has achieved increasing popularity and dissemination. An analysis of the underlying assumptions of BPM shows that it pursues two apparently contradicting goals: on the one hand it aims at formalising work practices into business process models; on the other hand, it intends to confer flexibility to the organization - i.e. to maintain its ability to respond to new and unforeseen situations. This paper analyses the relationship between formalisation and flexibility in business process modelling by means of an empirical case study of a BPM project in an aircraft maintenance company. A qualitative approach is adopted based on the Actor-Network Theory. The paper offers two major contributions: (a) it illustrates the sociotechnical complexity involved in BPM initiatives; (b) it points towards a multidimensional understanding of the relation between formalization and flexibility in BPM projects.

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.