The knowledge of data enables exploring how value is created from data. Organizations’ strategic planning becomes easier if the value of data is understood and adopted. Unless managers know how to use data, its exploitable value remains limited. Previous studies assessed either data dimensions such as volume, variety, velocity, veracity and granularity, or data management processes. However, many of these topics have been treated with a technical approach and only a few focused on the data value in management, strategy, and planning. The ubiquitous of data has allowed insurance incumbents and startups to exploit technologies, from which InsurTech, leveraging a unique data-driven proposition and often gaining a competitive advantage. The paper aims to explore the economics of data, enabling to strategically plan data management practices. It contributes to the management and strategy literature with an evidence-based systematic literature review that embraces the value generated by knowing data sources, data types, extended data dimensions, analyzes enabling technologies, and extends data management practices for reaching organizations’ objectives in the InsurTech empirical context. In addition to further avenues of research, it provides managers with a theoretical data-valorization framework for data strategic planning, and institutions an overview for guiding the digital transformation. The novelty of this paper is the comprehensive focus on the economics of data at the intersection between traditional and emerging business models.