Predictive modeling for an effective resource allocation : foreseeing Rappi courrier shortage for the sake of improving service quality (2019)
Rappi is a Colombian startup whose activity revolves around home delivery services of a diverse product portfolio in multiple Latin American cities. To create value via delivery and commerce, this venture uses integrated technological and physical channels materialized by a mobile app and a courier network that interact with supply and demand to achieve service completion. To reach an efficient network synergy the venture must overcome several operational challenges such as an assertive human resource allocation: delivery couriers should be strategically placed over the city surface to diligently satisfy demand at any given time. However, due to their business model, Rappi isn't allowed to call couriers for specific placements, representing a boundary to any allocation policy implementation. The present consultancy aims to develop a methodology supporting demand-synchronized courier allocation objectives that contributes to the company's goal of developing business convenient circumstances via analytic tools. The developed methodology seeks to enhance operational performance and user satisfaction by proposing a robust prediction of courier deficit per cluster, suitable to meet the organizationþs specific context and needs, and a resource allocation model designed to relocate couriers between high-demand clusters.