BAN403 Simulation of Business Processes

• Topics

  Simulation, i.e., experimentation with a computer model of a real system in order to determine the effect of changes in the system, is the most widely used management science method in practice. The use of simulation in business is increasing as the cost of modeling and running experiments with computers has been drastically reduced.

  It is particularly useful when the actual business process is complex and characterized by uncertainty in demand, processing capacity and delivery times, future interest and currency rates, etc.

  Simulation allows us to capture dynamics and uncertainty in these systems as they evolve over time. It is also possible to model more details of a real system when compared to an analytical or optimization-based model. Experiments are then conducted at a fraction of time and expenses of similar experiments in real systems. A sensitivity analysis of different "what-if" scenarios allows us to evaluate risk of proposed changes to the modeled system as well as forecast outcomes of business decisions before they are implemented in real-world.

  Simulation is alternative to some project management methods and traditional analytical tools of operations research to analyze problems related to queuing theory, inventory theory, etc. It also represents a predictive modeling tool for robust planning and risk reduction in many systems. It is widely applied for resource capacity planning, finding and removal of bottlenecks in complex systems, evaluation of effectiveness of current and improved systems, alternative capital investment decisions and analysis of cash flows of businesses.

  The course focuses mainly on two methodologies of computer-based simulation: Monte Carlo method and discrete-event simulation. The course participants will learn to model various business processes from the input data collection to interpretation and analysis of the results. The simulation modeling software JaamSim and excel, and Python will be used to model and analyze different systems.

  Throughout the course, students will learn different examples of simulation applications from a wide range of systems: banking (e.g., consumer credits), healthcare, logistics, inventory and manufacturing (e.g. capacity planning), telecommunications (e.g. call and support centers), retail and service (e.g. airport processes), etc.

• Learning outcome

  Upon completion of the course, the students shall

  Knowledge

  • understand the key principles and applications of simulation modeling
  • understand the impact of uncertainty factors on performance of systems models
  • be able to identify real-world problems and situations where simulation modeling can be used for improved decision making

  Skills

  • be able to model and analyze various business cases using different simulation methods
  • be able to perform input data collection and analysis for a simulation project
  • be able to design, implement, validate, and calibrate simulation models of real business processes
  • have developed good analytical skills to interpret simulation results and draw the necessary conclusions to support business decisions

  General competence

  • be able to use computational tools for implementing and analyzing real problems
  • understand the scope and limitations of the power of analytical and computational models to provide insights for decision making

• Teaching

  Lectures, modeling tutorials.

• Recommended prerequisites

  Basics of Python

  Basics of Microsoft Excel

• Required prerequisites

  Basics of Statistics and Probability Theory.

• Credit reduction due to overlap

  Course identical to BUS423.

• Compulsory Activity

  None

• Assessment

  Two projects will be done in groups of 1-3 students. The same groups will be used for both projects.

  The project reports must be written in English and submitted electronically. The final grade will be based on both project reports. The first project will be handed out in the middle of the semester and accounts for 40% of the final grade and the second project will be handed out at the end of the semester and accounts for 60% of the final grade.

• Grading Scale

  A - F

• Computer tools

  Standard laptop, JaamSim simulation modeling software, Microsoft Excel, Python.

  Details regarding the required software will be provided during the course.

• Literature

  https://www.routledge.com/search?author=Manuel%20Laguna Manuel Laguna and https://www.routledge.com/search?author=Johan%20MarklundJohan Marklund, 3rd Edition, Business Process Modeling, Simulation and Design, 2019.