In these sample papers from the 2022 M3 Challenge, students were asked to create models that will help predict whether the shift to remote work will last, and to what extent. Each paper has a cover sheet that indicates what judges liked about the paper and what could have been improved.
“As the world continues to overcome the socioeconomic setbacks of the pandemic, there have been significant, new trends in employment and working circumstances. The necessity of remote work has evolved into a relevant alternative to the traditional office life. However, there continues to be immense strife regarding the necessity of maintaining an online workplace as companies worry over the lack of face-to-face interaction. Our team aims to discover past and present trends regarding remote-work employment in the United States and United Kingdom to interpret the long-term economic impact on several cities.”
“The question this year is very much relevant to our future career. Since the beginning of the COVID-19 pandemic, remote working seems to have become more and more common and more widely discussed as an alternative to conventional working styles, and while the widespread awareness of remote working is helping to bring such work style into discussion in urban and suburban areas, from Seattle, WA in USA to Barry, Wales in the UK, increase in percentage of workers working remotely can be observed in the past few years, albeit in different levels.”
“Our team aims to create models that predict the percentage of workers who can and will work remotely in 2024 and 2027, as well as evaluate the magnitude of the impact that remote work will have on any given city. We first created a model to predict the percentage of workers with “remote-ready” jobs in Seattle, Omaha, Scranton, Liverpool, and Barry in 2024 and 2027….Next, we were tasked with finding the percentage of the employed workforce of a specific occupation who, given the option, would elect to work remotely….For Part III, we applied our previous models to determine an individual’s likelihood of working from home to each member of a city’s entire working population to get an aggregate model for the whole city that is extremely accurate.”
