Designing a digital management implementation framework for formula student teams

Abstract

Formula Student is a global university-level engineering competition in which student teams design, build, and race a single-seater formula-style car. Beyond the technical challenge, teams must secure significant sponsorship funding each season, yet the business-side processes that support this: acquisition, contracting, payment tracking, deliverable fulfilment, and relationship continuity are rarely formalised. At the University of Malta Racing team (UM Racing), these processes were found to be heavily person-dependent, untracked, and experience driven rather than data driven, creating structural fragility that recurs with each annual intake of new members. This dissertation applies a Design Science Research (DSR) (Doyle et al., 2016) methodology to design, implement, and evaluate a digital sponsorship management framework tailored to the constraints of a volunteer, student-led Formula Student team. The study begins with an empirical as-is analysis of UM Racing’s five sponsorship related sub-processes, identifying seventeen pain points consolidated across three analytical criteria: person-dependency (C1), absence of automated tracking and reminders (C2), and experience-based rather than data-driven decision-making (C3). These findings are benchmarked against nine anonymised peer Formula Student teams from the EV and combustion classes worldwide, confirming that the identified inefficiencies are sector wide rather than organisation specific. From this analysis, twenty five system requirements are derived and used to select and configure Notion as the implementation platform. The resulting framework comprises eight relational databases covering the full sponsorship lifecycle, with automated reminders, role-filtered views, and a standardised request approval workflow. The framework is demonstrated through a walkthrough of each sub-process and evaluated against the three analytical criteria and the full requirement set. The study finds that the framework fully or partially addresses all twenty-five requirements and eliminates all three criteria-level failure modes within the constraints of a no-cost, no-code platform. Limitations include Notion’s automation ceiling and the volunteer nature of Formula Student teams.