Resource-based modeling and simulation of business processes

International audienceThe simulation-based analysis of business processes (BPs) is a key activity at various phases of the BP lifecycle, from the design phase, to predict the process behavior, down to the execution and improvement phases, to recover from possible performance downgrades and/or improve the process performance. The BP analysis is usually carried out taking as input the BP description in a given BP modeling language. This paper specifically addresses BPs described in BPMN (Business Process Model & Notation) and introduces an approach that exploits both model-driven principles and the DEVS (Discrete Event System Specification) formalism to first annotate the BPMN model with the allocation of task resources described in terms of performance and reliability properties and then transform the annotated BPMN model into a DEVS-based model, which can be eventually executed to get the analysis results of interest. The BPMN annotation is carried out by use of PyBPMN, a lightweight BPMN extension that allows business analysts to specify the allocation of task resources and their properties in terms of both time-related attributes and reliability attributes. The paper overviews the proposed approach and gives the details of the DEVS components that are used to model the behavior of the corresponding BPMN primitives

Design Product-Service Systems by Using a Hybrid Approach: The Fashion Renting Business Model

As is known, sustainability issues represent one of the main challenges companies have to face. Among all, the fashion industry is considered one of the most impactful, both in terms of resource utilization and pollution. Fashion renting is a recent business model for companies to reduce their environmental footprint, following a circular economy approach. The study aims to develop and discuss the proposed hybrid approach to effectively support fashion companies in designing new business models, taking into account both the customer and the company perspective. On the one hand, agent-based modeling (ABM) allow us to represent customers’ behaviour and interaction. On the other hand, discrete event simulation (DES) paradigm is used to model fashion renting processes. Because customers’ attitude to that service reflects its successful implementation, motivators and barriers have been investigated to be included in the model. The practical implication is defining a model to support fashion companies in designing rental business models before implementing them. From a theoretical point of view, it overcomes the literature gap about the definition of a unique model for fashion renting, including processes, customers and interactions between agents. Follow-up research will include the presentation of simulation results

An Examination of Business Process Reengineering Techniques and Their Contribution to Process Improvement

The Department of Defense\u27s Corporate Information Management Initiative is part of an effort to achieve savings through specified programs focused on business process improvement A major process improvement methodology being used by the DoD is Business Process Reengineering (BPR). BPR offers the possibility for a fundamental rethinking and radical redesigning of DoD business processes, but there has been little systematic study of the effectiveness of the various techniques used in BPR projects. This study evaluates whether organizations conducting BPR efforts using five specific techniques (strategic planning, activity modeling, activity based costing, benchmarking, and simulation) achieve improvement in critical process performance measures. The survey was sent to two Air Force sample groups. The first group consisted of respondents to the Defense Information Systems Agency 1994 Business Process Reengineering Survey, and the second group consisted of members of the Air Force Institute of Technology Information Resource Management e-mail list. The survey resulted in a small sample of cases that were analyzed using descriptive statistics. The results of the survey indicate a surprisingly high success rate for BPR projects. Reliability analysis of the survey data was conducted and conclusions and recommendations for further research are presented

Agent modelling of cluster formation processes in regional economic systems

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

Data-Driven Simulation Modeling of Construction and Infrastructure Operations Using Process Knowledge Discovery

Within the architecture, engineering, and construction (AEC) domain, simulation modeling is mainly used to facilitate decision-making by enabling the assessment of different operational plans and resource arrangements, that are otherwise difficult (if not impossible), expensive, or time consuming to be evaluated in real world settings. The accuracy of such models directly affects their reliability to serve as a basis for important decisions such as project completion time estimation and resource allocation. Compared to other industries, this is particularly important in construction and infrastructure projects due to the high resource costs and the societal impacts of these projects. Discrete event simulation (DES) is a decision making tool that can benefit the process of design, control, and management of construction operations. Despite recent advancements, most DES models used in construction are created during the early planning and design stage when the lack of factual information from the project prohibits the use of realistic data in simulation modeling. The resulting models, therefore, are often built using rigid (subjective) assumptions and design parameters (e.g. precedence logic, activity durations). In all such cases and in the absence of an inclusive methodology to incorporate real field data as the project evolves, modelers rely on information from previous projects (a.k.a. secondary data), expert judgments, and subjective assumptions to generate simulations to predict future performance. These and similar shortcomings have to a large extent limited the use of traditional DES tools to preliminary studies and long-term planning of construction projects. In the realm of the business process management, process mining as a relatively new research domain seeks to automatically discover a process model by observing activity records and extracting information about processes. The research presented in this Ph.D. Dissertation was in part inspired by the prospect of construction process mining using sensory data collected from field agents. This enabled the extraction of operational knowledge necessary to generate and maintain the fidelity of simulation models. A preliminary study was conducted to demonstrate the feasibility and applicability of data-driven knowledge-based simulation modeling with focus on data collection using wireless sensor network (WSN) and rule-based taxonomy of activities. The resulting knowledge-based simulation models performed very well in properly predicting key performance measures of real construction systems. Next, a pervasive mobile data collection and mining technique was adopted and an activity recognition framework for construction equipment and worker tasks was developed. Data was collected using smartphone accelerometers and gyroscopes from construction entities to generate significant statistical time- and frequency-domain features. The extracted features served as the input of different types of machine learning algorithms that were applied to various construction activities. The trained predictive algorithms were then used to extract activity durations and calculate probability distributions to be fused into corresponding DES models. Results indicated that the generated data-driven knowledge-based simulation models outperform static models created based upon engineering assumptions and estimations with regard to compatibility of performance measure outputs to reality

Business Process Management Education in Academia: Status, challenges, and Recommendations

In response to the growing proliferation of Business Process Management (BPM) in industry and the demand this creates for BPM expertise, universities across the globe are at various stages of incorporating knowledge and skills in their teaching offerings. However, there are still only a handful of institutions that offer specialized education in BPM in a systematic and in-depth manner. This article is based on a global educators’ panel discussion held at the 2009 European Conference on Information Systems in Verona, Italy. The article presents the BPM programs of five universities from Australia, Europe, Africa, and North America, describing the BPM content covered, program and course structures, and challenges and lessons learned. The article also provides a comparative content analysis of BPM education programs illustrating a heterogeneous view of BPM. The examples presented demonstrate how different courses and programs can be developed to meet the educational goals of a university department, program, or school. This article contributes insights on how best to continuously sustain and reshape BPM education to ensure it remains dynamic, responsive, and sustainable in light of the evolving and ever-changing marketplace demands for BPM expertise

Simulation modelling and strategic change : creating the sustainable enterprise

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