Data Commercialisation
Data governed well enough to sell.
Governance, lineage and quality as the foundation — then the product, pricing and distribution work that turns a data asset into revenue rather than another line of cost.
The problem
Most institutions own more than they can sell.
The asset exists. What is missing is provenance you can stand behind, licensing clean enough to redistribute, a product definition, a price and a route to market. Commercialisation fails at governance far more often than it fails at demand.
The commercialisation path
- 01AssetWhat you hold, and what rights attach to it
- 02GovernanceLineage, quality, ownership and control
- 03ProductDefinition, packaging and service levels
- 04DistributionChannel, licensing model and contracting
- 05RevenuePricing, margin and commercial operating model
What we do
- Enterprise data design and target operating model
- Governance and compliance frameworks, including AI readiness
- Lineage and quality assessment against intended commercial use
- Upstream rights review — what you are permitted to redistribute
- Product definition, pricing approach and route to market
What you receive
- Data asset register with rights position per asset
- Governance framework and accountability model
- Commercial proposition with pricing logic
- Roadmap with sequencing, investment and dependencies
- Who it is forCDO, Head of Data, product leadership, strategy
- How longDiagnostic 2 weeks. Advisory 12–20 weeks.
Assessing a data asset?
The rights position is usually the deciding factor. We start there.