Innovation Performance of Indigenous Fintech Firms A Data-Driven Decision-Making Perspective in Developing Economies

Abstract

The relationship between data-driven decision-making (DDDM) and innovation performance among indigenous Fintech firms in Nigeria was examined by the study. Specifically, it determined how data usage frequency and employee data literacy levels influence firms’ innovation rates. A quantitative cross-sectional survey design was adopted, with data collected from 48 respondents drawn from 24 indigenous Fintech firms headquartered in Lagos State. Using a structured questionnaire and analyzed through Ordinary Least Squares (OLS) regression, the study evaluated the extent to which selected dimensions of DDDM explain variations in innovation performance. The findings revealed that DDDM significantly explained 61.5% of the variance in innovation rate, confirming its strategic importance in Fintech operations. However, contrary to expectations, data usage frequency exhibited a significant but negative relationship with innovation, suggesting the possibility of “paralysis by analysis,” where excessive data engagement may hinder creative processes. In contrast, employee data literacy demonstrated a significant positive effect on innovation performance, highlighting the critical role of human capital in transforming data into actionable insights. The study concluded that while data-driven practices are essential for competitive advantage, their effectiveness depends on how they are implemented and balanced within organizational processes. Consequent upon this, it was recommended that Fintech firms prioritize the development of employee data literacy through continuous training while optimizing data usage practices to avoid excessive reliance on routine data interactions. These findings contributed to the growing discourse on digital transformation and innovation in developing economies, particularly within the rapidly evolving Fintech sector.