Enterprise modeling and simulation

Citation

Barjis, J. and Verbraeck, A. (2010), "Enterprise modeling and simulation", Business Process Management Journal, Vol. 16 No. 5. https://doi.org/10.1108/bpmj.2010.15716eaa.001

Enterprise modeling and simulation

Article Type: Guest editorial From: Business Process Management Journal, Volume 16, Issue 5

About the Guest Editors

Joseph Barjis Associate Professor of Systems and Simulation at Delft University of Technology. His research interests are focused on business process modeling and simulation, enterprise modeling and simulation, information systems analysis and design, systems engineering, collaborative, participative, and interactive modeling. He is the founder of the Special Interest Group on Modeling and Simulation of the Association for Information Systems (www.AIS-SIGMAS.org/) and the International Workshop on Enterprise and Organizational Modeling and Simulation (www.EOMAS.org/).

Alexander Verbraeck Full Professor in Systems and Simulation and head of the Department of Systems Engineering at Delft University of Technology. He also serves as a part-time full professor in supply chain management at the R.H. Smith School of Business of the University of Maryland. He is a specialist in discrete event simulation for real-time control of complex transportation systems and for modeling business systems. His current research focus is on generic libraries of object oriented simulation building blocks, on tools for web-based simulation, and on the use of simulation models and virtual reality for serious gaming.

An enterprise is a complex sociotechnical system, purposefully designed for a certain service, which is realized through the business of the enterprise. The enterprise service is delivered to its customers in a certain business environment, which is often dynamic and changing. The already complex business operation (business processes) of modern enterprises are further challenged by the dynamicity posed by the enterprise business environment. For tackling this enterprise complexity (analysis and design), modeling and simulation have shown great potential.

Modeling in enterprise study, especially during the analysis and design phases, plays crucial role as it represents a design artifact in a more visualized manner such as intuitive diagrams. Enterprise modeling makes the business process knowledge explicit and captures the structure, behavior, and organization of the enterprise. Thus, the key role of enterprise modeling is capturing existing knowledge about the enterprise operation, actor roles, authorities and responsibilities. Furthermore, modeling facilitates shared understanding and communication of design ideas and concepts among the stakeholders (analysts, users, decision makers). In this regard, simulation deals with comparison of different scenarios and possible design ideas to investigate the solution space and capture the dynamic system behavior over time.

In a complementary manner, modeling and simulation covers a more complete cycle of analysis and design in enterprise study. While modeling provides the static view of the system or business processes by visualizing concepts and documenting reality, simulation brings the model to life by executing the model, exhibiting the dynamic behavior of the captured system or business processes. This also includes studying the effects of interactions of (human) actors and reaction to changes.

Increasingly, enterprise simulation is also used to augment analytical models. The two models are used for cross-validation as well as for overcoming restrictions in analytical models due to their assumptions that stem from linearity of processes, homogeneity of occurrences, normality, and stationary state of the underlying process.

In this special issue, we aimed at a broader application of modeling and simulation in the enterprise context. The selected papers show the diversity of application potential for enterprise modeling and simulation ranging from re-engineering to organizational aspects, technology alignment, and domain-specific type of enterprise.

Enterprise simulation has been used in many capacities, including for supporting decision making and implementation of changes.

In the paper, “Simulation for emergency care process reengineering in hospitals” by Sung J. Shim and Arun Kumar, the authors use simulation to study healthcare processes in an emergency care of a hospital. The study evaluates the impacts of proposed changes on the patient waiting time for service. This paper is based on a case study with the use of historical data retrieved from the hospital, where the simulation results demonstrate that the proposed changes potentially reduce the waiting time. This is a typical enterprise simulation example, in which the simulation model and the derived results exhibit that computer simulation can be an effective decision support tool in modeling the emergency care process and evaluating the impacts of changes in the process. The proposed changes, based on the simulation results, are suggested and supported for implementation as the hospital is seeking measures for reducing the patient waiting time.

Enterprise business process modeling, which is a prerequisite for successful enterprise simulation, is a daunting task and often error prone. A simulation model is as good as the underlying business process model.

In the paper, “A heuristic method for detecting problems in business process models” by Volker Gruhn and Ralf Laue, the authors present a new heuristic approach for finding errors and possible improvements in business process models. They propose to translate the information that is included in a model into a set of Prolog facts, which is then analyzed to search patterns that are related to a violation of the soundness property or bad modeling style. For the validation of their approach, the authors analyzed a repository of 1,000 business process models. Three different model-checkers have been used as tools to explore the state space of all possible executions of a model. The results of these tools have been compared with the results given by the proposed heuristic approach, which establish that the heuristic approach identifies violations of the soundness property almost as accurate as model-checkers. Furthermore, the proposed heuristic approach can also detect patterns for bad modeling style which can help to improve the quality of models.

Modern enterprises are heavily supported by complex information and communication technologies. Performance of an enterprise can significantly benefit from proper alignment of enterprise processes with these supporting technologies and integration of information system in the work of the enterprise.

In the paper, “Performance effects of information systems integration: a system dynamics study in a media firm” by Nicholas C. Georgantzas and Evangelos Katsamakas, the authors study the relationship between information systems integration and business performance in the context of the advertisement traffic system of a media company. The study uses system dynamics for developing a model of advertisement traffic system structure for examining different simulation scenarios. These simulation scenarios identify the dysfunctional effects of the lack of information systems integration. The model shows how information systems integration problems increase the dynamic complexity of business processes, resulting in poor business performance. By implication, the results show how and why integration improvements contribute to better performance. Through the study, it has been shown that system dynamics modeling can help enterprises analyze and streamline their business processes through supporting information technology, thus improving their business performance.

Not only in purposefully designed enterprises with available current or historical data, but simulation is also used to deal with the lack of data and difficulty in designing controlled experiments in the field of crisis response.

In the paper, “Developing a multi-agent system of a crisis response organization” by Rafael A. Gonzalez, the author studies the development of a multi-agent system used to simulate a crisis response organization. Following an agent-based approach, a model is developed to evaluate different coordination mechanisms for a crisis response organization. The characteristics of the response organization and the study of structured versus emergent coordination fit with the capabilities and nature of multi-agent systems, therefore the multi-agent system model is built using the GAIA methodology and the JADE agent framework. The model can be configured differently to deal with an emergency scenario developed separately as a discrete-event simulation, which provides a test-bed for simulating coordination in crisis response. The study finds that the GAIA methodology can be combined with an additional GAIA2JADE process to bridge the gap between design and implementation. Keeping the multi-agent system organization separate from the crisis scenario model enables testing different configurations of the crisis response organization in different scenarios.

For a thorough enterprise analysis, a comprehensive representation of an enterprise is needed to understand its dynamic behavior, processes, resources, internal and external stakeholders, and the constraints it must work within, and its relationship with the environment in which it operates. Therefore, modeling in isolation is not sufficient.

In the paper, “Sustainable enterprise modeling and simulation in a warehousing context” by Kah-Shien Tan, M. Daud Ahmed, and David Sundaram, the authors argue that sustainability of enterprises can only be achieved by integrating, balancing, and managing the economic, environmental, and social inputs and outputs in a holistic manner. This paper explores the application of sustainability principles in the context of storage and distribution management and introduces simulation models for a sustainable warehouse that primarily provides storage services. A sustainability model is an integrated model of the environmental, social, and economic dimensions of businesses that helps to understand the complexities and impacts of sustainability issues. The validity and usefulness of the sustainability models for the day-to-day decision making has been authenticated by the management of the warehousing organization. While the domain in which sustainable enterprise modeling was carried out was warehousing, the concepts and principles that were explored, developed, and validated is applicable across most enterprises.

Acknowledgements

For the success and appearance of this special issue, the Guest Editors would like to thank the management of the journal and the executive and production team working behind the scene. They would like to thank the reviewers who dedicated their time and efforts to help in the selection of relevant papers and their needed improvements for publication. Their deepest appreciations go to the authors for their excellent contribution and diligent work as their papers made rounds of reviews and revisions.

Joseph Barjis, Alexander VerbraeckGuest Editors