QANTM Valuations - FAST30 Webinar Series
- Apr 13
- 2 min read
Updated: May 12
Data: can the new 'oil' be reliably valued?
Presented 'Live' on: Thursday, 12 February 2026
Data assets are increasingly central to competitive advantage across sectors including financial services, TMT, energy and FMCG. Yet data remains one of the least understood and most inconsistently valued asset classes.
Reliable valuations of data assets is now critical to informed decision-making in areas such as corporate strategy, risk management, M&A, tax compliance and financial reporting.
Speakers:
Tim Heberden, QANTM Valuations
Nicolas Konialidis, Director (Asia) of the International Valuation Standards Council (IVSC)
You will learn, in this 30-minute presentation:
How to identify and define data assets, and map how they generate value
The role of International Valuation Standards in valuing data
Key technical, legal and commercial factors to consider when valuing data assets
How valuation insights can inform data governance and strategic decision-making
How sudden shifts in technology, market sentiment, or stakeholder expectations can rapidly erode enterprise value.
Key themes from the session
A few of the points that resonated most strongly were:
Start with the intended use and define the asset clearly. Data valuation is highly context-dependent, and reliable outcomes rely on clear asset definition, purpose and professional judgement, consistent with the International Valuation Standards.
Data often creates value indirectly. In many cases it improves decision-making, operational efficiency and risk outcomes, rather than being monetised directly. Understanding how data contributes across the value chain is central to estimating its economic contribution. One framework we use is illustrated below:
Avoid double counting where data sits alongside technology and people. Data is often tightly connected with software, IP and human capital, which can make separability difficult. The right approach depends on purpose, and in some cases a bundled assessment is more appropriate than trying to isolate components.
Useful reference
Nicolas Konialidis' perspective paper referenced during the webinar is available here:
Practical reflection questions
If it is helpful, here are three questions you may wish to consider internally:
Do you have clear visibility of your most important data assets and how they contribute to business value?
Are the rights and permissions clear (who owns the data, how it can be used, and where value and risk ultimately sit)?
Can you estimate the contribution of data to performance, whether through pricing, efficiency, customer outcomes or risk management?
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