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

TL;DR

This paper systematically reviews metrics and KPIs for data valuation and monetisation, providing a comprehensive taxonomy and highlighting challenges in establishing standard frameworks for organizations.

Contribution

It offers an extensive taxonomy of metrics and KPIs for data valuation and monetisation, based on a systematic literature review of 162 references.

Findings

Provided an expansive list of metrics and KPIs used in data valuation and monetisation.

Categorised metrics into a detailed taxonomy following the Balanced Scorecard approach.

Discussed major challenges and the complexity of creating standard frameworks in the domain.

Abstract

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.