arXiv subjects

Bastien Pietropaoli

Publications and source records attributed to Bastien Pietropaoli.

3 recordsLinked to original sources

arXiv2025

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

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.

cs.ET↗

arXiv2025

A Framework for Data Valuation and Monetisation

As organisations increasingly recognise data as a strategic resource, they face the challenge of translating informational assets into measurable business value. Existing valuation approaches remain fragmented, often separating economic, governance, and strategic perspectives and lacking operational mechanisms suitable for real settings. This paper introduces a unified valuation framework that integrates these perspectives into a coherent decision-support model. Building on two artefacts from the Horizon Europe DATAMITE project, a taxonomy of data-quality and performance metrics, and an Analytic Network Process (ANP) tool for deriving relative importance, we develop a hybrid valuation model. The model combines qualitative scoring, cost- and utility-based estimation, relevance/quality indexing, and multi-criteria weighting to define data value transparently and systematically. Anchored in the Balanced Scorecard (BSC), the framework aligns indicators and valuation outcomes with organisational strategy, enabling firms to assess monetisation potential across Data-as-a-Service, Information-as-a-Service, and Answers-as-a-Service pathways. Methodologically, the study follows a Design Science approach complemented by embedded case studies with industrial partners, which informed continual refinement of the model. Because the evaluation is connected to a high-level taxonomy, the approach also reveals how valuation considerations map to BSC perspectives. Across the analysed use cases, the framework demonstrated flexibility, transparency, and reduced arbitrariness in valuation, offering organisations a structured basis for linking data assets to strategic and economic outcomes.

cs.CY↗

arXiv2025

Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation -- A Systematic Literature Review

Data valuation and data monetisation are complex subjects but essential to most organisations today. Unfortunately, they still lack standard procedures and frameworks for organisations to follow. In this survey, we introduce the reader to the concepts by providing the definitions and the background required to better understand data, monetisation strategies, and finally metrics and KPIs used in these strategies. We have conducted a systematic literature review on metrics and KPIs used in data valuation and monetisation, in every aspect of an organisation's business, and by a variety of stakeholders. We provide an expansive list of such metrics and KPIs with 162 references. We then categorise all the metrics and KPIs found into a large taxonomy, following the Balanced Scorecard (BSC) approach with further subclustering to cover every aspect of an organisation's business. This taxonomy will help every level of data management understand the complex landscape of the domain. We also discuss the difficulty in creating a standard framework for data valuation and data monetisation and the major challenges the domain is currently facing.

cs.DB↗