Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective
Abstract
Data valuation and monetisation are emerging as central challenges in data-driven economies, yet no unified framework exists to measure or manage data value across organisational contexts. This paper presents a systematic literature review of metrics and key performance indicators (KPIs) relevant to data valuation and monetisation, focusing on the Internal Processes Perspective of the Balanced Scorecard (BSC). As part of a broader effort to explore all four BSC perspectives, we identify, categorise, and interrelate hundreds of metrics within a comprehensive taxonomy structured around three core clusters: Data Quality, Governance & Compliance, and Operational Efficiency. The taxonomy consolidates overlapping definitions, clarifies conceptual dependencies, and links technical, organisational, and regulatory indicators that underpin data value creation. By integrating these dimensions, it provides a foundation for the development of standardised and evidence-based valuation frameworks. Beyond its theoretical contribution, the taxonomy supports ongoing practical applications in decision-support systems and data valuation models, advancing the broader goal of establishing a coherent, dynamic approach to assessing and monetising data across industries.
Keywords
Cite
@article{arxiv.2512.10622,
title = {Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective},
author = {Eduardo Vyhmeister and Bastien Pietropaoli and Alejando Martinez Molina and Montserrat Gonzalez-Ferreiro and Gabriel Gonzalez-Castane and Jordi Arjona Aroca and Andrea Visentin},
journal= {arXiv preprint arXiv:2512.10622},
year = {2025}
}