Assessing advantages of drone logistics through simulation modelling: an application in public healthcare

By Pietro Negri, in collaboration with Vincenzo Damico

Assessing advantages of drone logistics through simulation modelling: an application in public healthcare

Written by: Pietro Negri, in collaboration with Vincenzo Damico

The advancements in technology have led to the introduction of commercial drones in different business activities and we are witnessing the rising of a market for the application of drone logistic in different sectors: from the early experimentations on parcel delivery in the USA to a more mature market of emergency and healthcare logistic in Europe. The benefits offered by drones are many: fastest delivery times, reduced traffic and pollution, possibility to reach remote areas, flexible and scalable distribution networks.

Although the potential advantages of this application are quite clear, recent studies have pointed out the lack of business cases able to clarify, quantitatively speaking, the real advantages of drone logistic. This, together with the strict regulation on domestic autonomous flight, represents a great cultural barrier for the companies that could adopt this type of logistic.

Simulation modelling represents the ideal methodology for assessing in an analytical way the advantages carried out by drone logistic, not only focusing on traditional indicators such as service and cost but also considering other relevant KPIs, such as the environmental footprint, the robustness of the system to stress factors, its scalability and so on. In the following case study Skkip has analyzed, together with an Italian drone service provider, how drone logistic could be implemented in the public healthcare sector for the delivery of Covid-19 vaccines in two provinces of Italy, located in Sardinia. The case study points out the differences in main financial and non-financial indicators resulting from a benchmark between traditional logistic (performed with vans) and a possible innovative fleet composed by both vans and drones.