Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective

TL;DR

This paper systematically reviews metrics and KPIs for data valuation and monetisation, focusing on the Internal Processes Perspective of the Balanced Scorecard, and develops a comprehensive taxonomy to support standardised valuation frameworks.

Contribution

It introduces a detailed taxonomy categorising metrics related to data quality, governance, and operational efficiency, linking technical, organisational, and regulatory indicators for data valuation.

Findings

Identified and categorised hundreds of relevant metrics.

Structured a taxonomy to clarify metric relationships and dependencies.

Provided a foundation for standardised data valuation frameworks.

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.