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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.10622 |
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| _version_ | 1866914195859046400 |
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| author | Vyhmeister, Eduardo Pietropaoli, Bastien Molina, Alejando Martinez Gonzalez-Ferreiro, Montserrat Gonzalez-Castane, Gabriel Aroca, Jordi Arjona Visentin, Andrea |
| author_facet | Vyhmeister, Eduardo Pietropaoli, Bastien Molina, Alejando Martinez Gonzalez-Ferreiro, Montserrat Gonzalez-Castane, Gabriel Aroca, Jordi Arjona Visentin, Andrea |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_10622 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective Vyhmeister, Eduardo Pietropaoli, Bastien Molina, Alejando Martinez Gonzalez-Ferreiro, Montserrat Gonzalez-Castane, Gabriel Aroca, Jordi Arjona Visentin, Andrea Emerging Technologies 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. |
| title | Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- Internal Processes Perspective |
| topic | Emerging Technologies |
| url | https://arxiv.org/abs/2512.10622 |