In the modern economy, data is often described as “the new oil,” but how do you measure the value of a digital asset that doesn’t appear on the balance sheet?
From healthcare algorithms to customer behavior datasets, proprietary data is driving deal premiums and intellectual property strategies across sectors. However, many businesses struggle to articulate, let alone defend, their value in a transaction, litigation, or financial reporting context.
Why Now?
Recent M&A activity underscores this trend. In several high-profile tech and healthcare transactions, buyers have paid premiums largely attributed to the target’s data assets, even when revenue was minimal. At the same time, regulatory attention around privacy (e.g., GDPR, HIPAA, AI regulations) has elevated the risk-adjusted value of compliant, structured data repositories.
Notably, Twitter’s acquisition serves as a cautionary tale in this regard. When the company was sold, the transaction largely overlooked the immense value contained within its user-generated data. The deal focused primarily on platform ownership and brand, missing a critical opportunity to recognize and monetize the proprietary behavioral and engagement data that could have significantly impacted the valuation. This omission highlights the importance for buyers and sellers alike to fully understand and articulate the worth of data assets during negotiations, especially in industries where data drives strategic advantage.
As more companies move toward data-driven models, understanding how to quantify, categorize, and support the value of proprietary data has become essential.
AI Relevance
As artificial intelligence (AI) continues to gain prominence across industries, the need to accurately value data assets is becoming even more critical. AI models depend on vast amounts of high-quality, proprietary data to deliver meaningful insights and gain a competitive advantage. This growing reliance on data for AI development and deployment is expected to further amplify the emphasis on data valuation in business transactions and strategic decision-making.
How Do You Value Data?
Data does not lend itself to a one-size-fits-all approach when it comes to understanding its value. A valuation specialist should examine the facts and circumstances before selecting the right approach. A few commonly accepted approaches include:
- Cost Approach: Estimating the cost to recreate the dataset (including time, infrastructure, collection, and compliance).
- Income Approach: Modeling the incremental cash flows attributable to the data (e.g., predictive analytics improving churn or underwriting accuracy).
- Market Approach: Benchmarking against recent transactions involving similar datasets, though comparables are rare and often confidential.
Choosing the Right Valuation Method
The appropriate valuation method for proprietary data assets is largely determined by the valuation’s specific context and objectives. Whether the purpose is financial reporting, mergers and acquisitions (M&A), or intellectual property (IP) litigation, each scenario may require a distinct approach to accurately reflect the data’s worth.
In financial reporting, the emphasis is often on compliance with accounting standards, such as ASC 805, which governs the recognition and measurement of intangible assets in business combinations. In this setting, auditors and valuation specialists typically seek robust, supportable models that can withstand regulatory scrutiny.
In M&A transactions, the valuation method must address the strategic motivations of buyers and sellers. Here, the focus may shift toward demonstrating how proprietary data drives deal premiums or supports future revenue streams, often necessitating a blend of income and market approaches. The stage of monetization is also critical; datasets that are already generating cash flows or underpinning commercialized products may be valued differently than those still in development or with uncertain future use.
During IP litigation, the method must be defensible in court and supported by clear documentation linking the data asset to alleged damages or lost profits. Experts may rely on cost, income, or market approaches depending on the facts of the case and the availability of reliable comparables.
Ultimately, selecting the correct valuation method requires a careful analysis of the data’s characteristics, the intended use of the valuation, and the maturity of the asset’s monetization. Engaging a valuation specialist who understands these nuances is essential for producing credible, defensible results that meet the needs of all stakeholders.
Valuation in Practice
At Withum, we help clients:
- Identify whether the company's data meets the criteria for separate recognition under ASC 805 in a business combination, and assess how the data contributes to or enhances other identifiable intangible assets (such as developed technology);
- Value data assets during purchase price allocations, spin-offs, and internal reorgs;
- Support legal claims in disputes over data misappropriation or breach of contract;
- Develop internal models for licensing, monetization, and planning.
- Provide transaction advisory services to help clients uncover, articulate, and defend the true value of their data assets during M&A negotiations, ensuring critical data-related value is not overlooked.
Our team also regularly works with auditors and legal counsel to ensure our conclusions are robust, compliant, and defensible.
What sets Withum apart is our deep understanding of both the technical and strategic aspects of data valuation. We leverage multidisciplinary expertise to guide clients through complex regulatory frameworks, maximize the financial impact of proprietary data, and mitigate risks associated with emerging data-centric business models. By offering tailored solutions and proactive advice, Withum empowers organizations to unlock hidden value, gain a competitive edge, and make confident, data-driven decisions at every stage of their growth journey.
Contact Us
For more information on this topic, reach out to Withum’s Forensic and Valuation Services Team.
