US Cold Storage (USCS), a refrigerated warehousing and food logistics company, wants to create a predictive tool that can anticipate its customers’ future product disposal events. Doing so will help facilitate an ongoing initiative to minimize the amount of customers’ food products sent to landfill as a result of damage or expiration.

USCS wants the team to create and train a predictive analytics model using historical inventory and disposal order data sets. The data will need to be consolidated, cleaned, and assessed to decide what modeling methodology should be applied. The construction of the model will require the team to research data engineering and forecasting concepts both independently and in partnership with USCS. Outputs of the model will be used to inform waste servicing partnerships and sustainability metric reporting. The team will also present to USCS on the accuracy and usability of the developed model in their company operations. Additionally, the students will design a hypothetical waste processing facility that is capable of composting, anaerobically digesting, or recycling the volumes of food waste disposed of at a subset of USCS facility in the Indiana/Illinois area.