Delivering food items is challenging, particulary for fresh fruits and vegetables. Such products often have short shelf lives and further require specific storage conditions. In earlier posts, we looked at common challenges, investigated strategies to reduce food waste and considered specific consumer preferences. This post discusses benefits of integrating food quality data and how having such information available can improve decision making along food supply chain processes.
For this purpose, we investigated a regional organic strawberry supply chain in recent work. Strawberries are a highly interesting product as they are in high demand and have short shelf lives (~7 days at optimal storage temperatures). Additionally, customers can easily evaluate their quality through visual inspection.
The considered supply chain starts at the field where products are harvested. Strawberries are subsequently brought to a closeby cold store, where they are stored until shipment to the central distribution center. At this location, strawberries from multiple fields are consoldited for the final delivery to multiple retail stores. The considered supply chain ends at the customer once he/she purchases the product in-store.
Our main question of focus was how having quality data available during these process steps can assist operations. As an objective, we aim to minimize food waste while keeping sales as high as possible. Therefore, we consider implementing quality thresholds. These minimium quality requirements are set at various stages throughout the supply chain. If the measured remaining food quality falls below this level, products are sorted out and moved to alternative distribution channels (e.g., juice or jam production).
To investigate this question, a discrete-event simulation model was developed. It compares running a supply chain without having such quality data available with the above-mention setting and further tests varying quality thresholds at cold stores and the distribution center. Results show that integrating quality data not only allows one to reduce food waste, it further may increase sales as more high quality items are shipped to stores.
Naturally, whether the implementation of quality data make sense for a specific supply chain depends on the decision maker’s objectives and requires a careful cost analysis. Simulation models such as the one developed in our work assists one to estimate benefits of such an integration. Additionally, it provides the user a tool to investigate varying problem settings to derive findings and improve understanding of related food supply chain processes.
– Leither M, Fikar, C (2019) A simulation model to investigate impacts of facilitating quality data within organic fresh food supply chains. Annals of Operations Research, in press. DOI: https://doi.org/10.1007/s10479-019-03455-0