How is a data licensing royalty rate determined? At a basic level, a defensible data licensing royalty rate starts from the ground up. Given that data is a unique asset, usable comparable license and transaction data often is not readily available. Therefore, one must begin with an enterprise-specific analysis of what each party contributes to the planned development. Then, if possible, a benchmarking exercise comparing those contributions against comparable license agreements and partnerships where they exist, and any realistic alternatives, should be conducted. The result is the starting point for a supportable royalty rate range. Ocean Tomo, a part of J.S. Held, used this framework as financial advisor to a national health and wellness organization negotiating a data licensing and pricing agreement with the life sciences arm of a multinational technology company. The recommended range supported a double-digit royalty rate range, 50% to 100% above the counterparty’s initial offer.
Health Data Is a Licensable Asset
Organizations that provide health insurance and/or deliver care collect large volumes of data as part of daily operations. For years, that data was treated as a mere record rather than an asset with its own value.
While we recognize that much healthcare data is highly regulated, there are growing use cases for anonymized or non-restricted patient data. Technology companies, life sciences researchers, and AI developers now want longitudinal, real-world health data to build platforms, train models, and speed up research. When one of these organizations approaches a data holder about a partnership, the data holder’s key question is no longer whether to take part. It is what the data is worth inside the partnership, and how to support that number at the negotiating table.
Why Data Is Harder to Value Than Other Intellectual Property
In patent and trademark licensing, a valuation often starts with comparable license agreements. Data licensing rarely offers that starting point, for three reasons:
- Confidentiality: Many data licensing deals are private, and their terms are seldom disclosed.
- Context-Dependent Value: The same dataset can be worth very different amounts depending on how it is combined with the partner’s platform, technology and distribution.
- Limited Comparability: Differences in data types, depth, exclusivity, and permitted use make direct comparisons difficult even when agreements are available.
- Novelty: The relative novelty of data licensing, especially in the context of AI, means that there is a limited number of precedent licenses and transactions available compared to patent and trademark licenses.
Because of these gaps, a data royalty rate often requires a ground-up analysis of contributions, risks, and business models, with market benchmarks used when available.
A Five-Step Framework for a Defensible Data Royalty Rate
Define the Use Case
The value of data, even more so than other IP assets, is driven by its use case, the capabilities of the licensee, and the restrictions on its use.
Analyze the Contributions & Profitability
Royalty rates depend on profitability and IP contribution. The analysis starts with the identification of what each party brings to the planned venture: data, platform, distribution, technology, etc. It then assesses how much each contribution matters to the value and profitability the partnership is expected to generate.
Benchmark the Market
Where comparable license agreements and partnerships are available, analyze them to test the assumptions behind the profitability and contribution analysis.
Study Alternatives
Evaluate the subject companies and the competitive landscape to understand each party’s realistic alternatives. A licensor’s negotiating leverage depends on whether or not there are available alternatives and what the counterparty would do if the deal doesn’t happen.
Deliver a Range
The result is a supportable royalty rate range the party can defend throughout the negotiation. A single number is easy to attack. A well-supported range gives the client room to negotiate while staying anchored to independent analysis.
Engagement Spotlight: Pricing Health Data in a Digital Health Partnership
A national health and wellness organization that offers health insurance and care delivery was approached by the life sciences research arm of a multinational technology company. The goal was to build an integrated digital health platform together. The licensor organization engaged Ocean Tomo, a part of J.S. Held, as financial advisor on the data licensing and pricing negotiation. The task was to provide an independent, supportable view of data value before terms were set.
The Ocean Tomo team applied the five-step framework. It analyzed each party’s contributions to the planned platform, reviewed available comparable agreements and partnerships, and assessed the economics and feasibility of each side’s alternatives.
The Outcome: Ocean Tomo’s report supported a double-digit royalty rate 50% to 100% higher than the counterparty’s initial offer. The client entered negotiations with an independent, defensible assessment of value, setting the rate instead of accepting it.
Connect With Our Experts
To learn how Ocean Tomo, a part of J.S. Held, supports data licensing valuation and negotiation, contact Greg at [email protected] or Noor at [email protected].
Transparency Statement: Artificial intelligence tools were used to support the development of this thought leadership content, which could include research support, information synthesis, and editorial refinement. The analysis, insights, perspectives, and conclusions presented are those of the author(s) and reflect their professional expertise and judgment. The content was reviewed by the author(s) for accuracy, relevance, and consistency with the source materials. Artificial intelligence tools did not independently determine the content’s conclusions or recommendations.
