The evolution of performance measurement systems in SaaS startups: a contingency-based approach across the investment cycle

Purpose This study aims to investigate how SaaS startups structure and evolve their performance measurement systems (PMS). Design/methodology/approach Nine semi-structured interviews were conducted with founders and CEOs of SaaS startups operating at various stages of venture funding. The data were analysed through open, axial and selective coding, which enabled the development of an emergent theoretical model. Findings Startups do not follow a linear or standardised trajectory in developing their PMS. They dynamically and reactively adjust these systems in response to three strategic imperatives: market expansion, product development and fundraising. Research limitations/implications The number of interviews analysed is limited, but the empirical depth of the study captures PMS’s dynamic and contingent nature in SaaS startups. The research contributes to theory by challenging the linearity assumed by traditional models and advancing a contingency perspective on performance measurement in innovation contexts. Practical implications A more strategic, flexible PMS tailored to a startup’s stage and business model contributes to more efficient operational management and a more consistent evaluation of startups, promoting sustainable growth and alignment between market expectations and business realities. Social implications Structured, adaptive PMS adoption by SaaS startups enhances financial sustainability, reduces information asymmetry and attracts investments. Simultaneously, it boosts qualified job creation, technological democratisation and responsible innovation. Originality/value The originality lies in its empirical analysis of SaaS startups in an emerging economy. It provides novel insights into how ventures dynamically configure their PMS under conditions of uncertainty and limited resources, and challenges dominant assumptions of KPI standardisation.