When Does Data Become an Asset? Xu Ke on Identifying and Defining Data Assets

Editor’s Note — DCC.

Xu Ke’s two other pieces DCC published today are deep doctrine — the anonymization reconstruction and the rights-block structure. This one, written for Entrepreneur Magazine, is the practitioner- facing complement: when does data actually become an asset a Chinese enterprise can put on its books, and how do the three rights map onto operational boundaries? It’s the most directly useful of the three for overseas counsel doing transactional or accounting-adjacent work with Chinese counterparties — particularly as China’s “data on balance sheet” (数据入表) movement gathers pace.

Resource vs asset — the two viewpoints

Xu Ke’s first distinction is between two vantage points:

Data resource (数据资源) — the national viewpoint. Introduced in the State Council’s 2015 Action Outline for Promoting Big Data Development, “data resource” is a macro-economic positioning emphasizing data’s public attributes and strategic value.
Data asset (数据资产) — the market-actor viewpoint. An enterprise’s commercial framing: whether data can produce actual value in business activity.

Two essential differences follow:

Data resource carries plural interests — public, individual, and enterprise. Data with strong public attributes or involving personal privacy can’t be monopolized by an enterprise; from the national view it’s an important resource, but it can’t all be classed as enterprise assets. Data asset, by contrast, must point clearly to the enterprise’s commercial scenario.
Data asset has a narrow and a broad sense:
- Narrow (accounting) sense — meets the Ministry of Finance’s Enterprise Accounting Standards test: the data can be owned or effectively controlled by the enterprise, can bring economic benefit, and its cost or value can be reliably measured — thus eligible for “data on balance sheet” (数据入表) as an accounting-recognized data asset.
- Broad sense — any data that creates value for the enterprise.

The three-part asset test

Xu Ke gives enterprises a practical three-question test for whether their data has asset character:

Does the data serve the enterprise’s core business activity?
Can the enterprise own or effectively control the data?
Is there a clear value-realization (monetization) path?

His example: user-behavior data accumulated by an internet enterprise has asset character if it can be analyzed to optimize products or run precision marketing — i.e., if there’s a realization path.

Mapping the three rights onto operational boundaries

The practitioner payoff: Xu Ke works the three-rights framework into concrete operating boundaries by right and by data type.

By right:

Hold right (持有权) — attribution of the original data resource; the defensive perimeter against others stealing, tampering, leaking, or destroying the held data.
Use right (使用权) — the right to process, analyze, apply; needs a defined scope, method, and compliance boundary. His example: a hospital using patient data for research must comply with PIPL and ensure anonymization to protect patient privacy — directly linking the use-right boundary to the anonymization standard.
Operate right (经营权) — commercialization of data products: authorization, trading, services. His example: when selling a processed data product to a third party, the parties must define rights and obligations clearly to ensure compliant circulation.

By data type:

Personal data — use right must strictly follow PIPL and related rules.
Enterprise operational data — operate right is more market-regulated (left to the market).
Government data — public attribute must be clear; commercial use is limited to prevent private capture of public resources.

What this tells overseas compliance teams

Distinguish “data asset” (accounting) from “data we find valuable” (everything). When a Chinese counterparty talks about its “data assets,” clarify which sense — narrow (on-balance-sheet, MOF-standard-qualified) or broad (anything valuable). The narrow sense carries specific ownership/control, economic-benefit, and measurability requirements that bear on valuation, due diligence, and deal structuring.
The three-question asset test is a useful diligence screen. When valuing or acquiring a Chinese entity’s data assets, run Xu Ke’s test: core-business nexus, ownership/control, realization path. Data that fails any prong is unlikely to survive as a recognized asset — relevant to purchase-price allocation and rep-and-warranty scoping.
Anonymization is the use-right boundary for personal data. Xu Ke ties the use right for personal data directly to PIPL compliance and anonymization. If a deal contemplates using personal-data-derived assets, the anonymization posture (and its risk-based, continuously-monitored standard) is the gating compliance question — not an afterthought.
Data-on-balance-sheet is a live and growing practice. China’s 数据入表 movement (data assets recognized on corporate balance sheets under MOF rules effective 2024) means Chinese counterparties increasingly carry data assets on their books. Overseas counsel doing M&A, financing, or audit-adjacent work should expect to encounter recognized data assets and should understand the recognition basis (which traces back to the three-rights hold/control determination).
Government-data commercial use is fenced. Where a deal touches government / public data, the operate right is constrained — public attribute must be preserved, commercial use limited. Don’t assume government-data-derived products can be freely commercialized; the public-data authorized-operation regime governs.

The connective point across Xu Ke’s three pieces: the rights-block structure defines what kind of thing data rights are; the anonymization reconstruction defines how personal data exits the PI regime to become freely usable; and this piece defines when the resulting data becomes a recognized, monetizable, balance-sheet asset. Together they trace the full arc from raw data to recognized asset — which is exactly the arc a multinational structuring a Chinese data transaction has to walk.

— 许可, 数据资产的识别与界定 (Identifying and Defining Data Assets), 《企业家》杂志 (Entrepreneur Magazine); reposted via 企业家杂志 WeChat Official Account. Original article (Chinese).

Not legal advice. The above is DCC’s structured summary of Xu Ke’s analysis, with framing for overseas counsel; the resource/asset and narrow/broad distinctions, the three-question test, and the rights-by-data-type mapping are Xu Ke’s.