Data Valuation Diagnostic [D-Val]
If you hold a data estate and you have no rigorous basis for knowing what it may be worth, whether you have the legal right to commercialise it, or what stands between your current position and a formally authenticated data portfolio, this is the conversation worth having.
HOW IT WORKS
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We establish what you hold. Where it came from, the consent conditions under which it was collected, what legal rights appear to attach to it, and what encumbrances travel with it. Most organisations have never done this systematically. The inventory is where the picture becomes visible for the first time.
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Each dataset is scored across two dimensions simultaneously: technical quality and legal standing. Completeness, accuracy, and AI readiness on one side. Provenance, consent conditions, and rights of use on the other. The D-Val score reflects where each dataset sits at the intersection of both. Potential value lives there.
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You receive a D-Val score for each dataset, an approximate value indication for the data portfolio, and a prioritised roadmap covering technical remediation and rights clarification. The datasets that appear ready for formal assetisation are identified. The pathway to Phase Two authentication is set out clearly.
THE PRACTICE
Most organisations accumulate data as a by-product of operations and have never assessed what it may be worth, whether they have the legal right to commercialise it, or what stands between their current position and a formally authenticated data asset. Technical quality without legal clarity cannot be safely deployed. Legal rights over fragmented data cannot command market value. Potential value sits at the intersection of both. That is where D-Val works.
The organisations that understand their data estate is actually a data portfolio earliest will hold a structural advantage that compounds as AI governance requirements tighten and authenticated data markets grow. The value was always there. D-Val is what makes it visible.
THE CLIENT
“We had no idea how much value our clients were sitting on, or how exposed they were. The Legally Authenticated Data process makes both of those things visible for the first time.”
CASE STUDY
ILLUSTRATIVE · ENTERPRISE · 2026
A large logistics operator holds billions of shipment records spanning multiple jurisdictions, along with fleet telematics, warehouse inventory, and customer interaction logs.
The data is technically strong. The legal standing across the portfolio is almost entirely undocumented.
A D-Val engagement would assess the full estate, fractionalising it into discrete datasets scored for technical quality and legal standing. The result would be a D-Val score per dataset, an approximate portfolio value indication, and a prioritised roadmap covering rights clarification and technical remediation. The fleet telematics dataset would be identified as the highest-priority candidate for Phase Two authentication. For the first time the organisation could see what it held, what it may be worth, and where to move first.
INDICATIVE OUTCOME
Approximate value indication and prioritised authentication pathway
INDICATIVE TIMELINE
3 months to final report
SCOPE
D-Val scoring, rights map, technical and legal remediation roadmap
