The Dartmouth Master of Engineering Management program is a rigorous academic program that prepares students for leadership roles in engineering and technology management. One of the core requirements of the program is ENGM183 Operations Management, which provides students with a comprehensive understanding of operations management principles and practices. This course involves a project that includes a field simulation game, where students get to apply their learnings in a real-world scenario. The simulation provides a unique opportunity for students to learn how to manage operations in a dynamic and ever-changing environment, and to develop their problem-solving skills. By completing this course, students are well-equipped to tackle the complex challenges that come with managing operations in today's fast-paced business world.
Littlefield is an online simulation tool that is used for teaching operations management and supply chain management concepts. It is designed to help students understand the trade-offs between various production strategies and the impact of demand variability on production performance. In the Littlefield simulation, participants are tasked with managing a virtual factory that produces and sells a specific product. The simulation tracks various performance metrics such as production lead time, inventory levels, and machine utilization, among others. Participants are given a starting budget and must make decisions about how to allocate resources such as machine capacity and inventory levels to maximize their profits. They can also invest in upgrades and new equipment to improve their production capacity. The Littlefield simulation provides a realistic and engaging learning experience that helps students develop a better understanding of operations management concepts and the challenges faced by real-world businesses. (OpenAI, ChatGPT generated content)
The game updates every hour with new data, which includes many parameters that change over time. In order to perform effective analysis, it is necessary to download CSV files from various URLs each time. However, this can be a time-consuming process. To streamline the data extraction process, the author of this document has opted to use Apps Script. By publishing all data in a Google Spreadsheet, the data extraction process can be automated and triggered every hour. This will save time and allow for deep analytics to be implemented without needing to constantly download and compile the data.
For those interested in reviewing the source code, please refer to the JavaScript file provided by the author.