In a traditional face-to-face logistics course, students have been learning for some time, how to forecast the demand of products by utilizing different formulas that they select depending on multiple variables in scenarios. However, taking this knowledge to the next level, required the application of these concepts in a real-world context is crucial.
To make this happen, we decided to try to create a simple simulation which would incorporate as many real-world factors as possible. We included: group collaboration and decision making, use of online conferencing tools, application of forecasting methods, utilization of previous data, and the uncertainty of the real world.
This simulation has been run now for two consecutive years. For this last iteration, we had 45 groups of 5 students, which joined a Bb Collaborate virtual classroom environment instead of coming to the regular classroom. Each team assigned a team-leader who oversaw sending the final answers through Socrative.com. Before the session professor had already distributed the rules of the game and establishing that he would manage the pace of the game so that all participant would be inputting responses for the same questions at the same time. and provided data about the past year’s demand for a certain product.
Once the session started the professor gave an overview of the scenario, in which students assumed the role of a consultant group who had started to work for a certain company. Their purpose was to be able to predict the demand of a certain product month by month thorough an entire year so that the company could prepare in advance to meet these demands. Students then had to decide which knowledge to apply depending on the situation and the data they had from the previous year, to calculate the forecast for each month which was submitted one by one at the professor’s request.
After each month’s submission, the team behind the simulation, checked for the best and worst responses and fed this info to the instructor so that then he would call on someone from those teams to explain how they got to these responses, and then received immediate feedback. The team behind also helped the professor moderate the session by managing turn taking and microphone privileges.
With each month’s submission, the student experience grew and grew, receiving feedback from peers and the instructor. Each turn the time allowed to perform the calculation was also decreasing, making it more pressing to get the responses right and fast. Suddenly at some point unexpected events started happening. A stock out, a hurricane, an event that triggers demands! These events started disrupting calculations, but teaching a valuable lesson that can’t be taught with theory.
The objective is to share what we did, what tools we used, the roles of the people involved, and our lessons learned. The audience members and decide if you want to adapt something similar to one of your classes. Finally, we want to have a conversation with the audience and receive feedback on how they think we could improve what we are doing.