Data Isn't Oil: The Cognitive Shift from Metaphor to Business Value

"Data is the new oil" has become a ubiquitous slogan in the digital age. The analogy seems plausible: oil powered industrial society, data powers intelligent society; oil lies underground awaiting exploration, data lies scattered across systems awaiting governance. Yet many data teams feel frustrated: if data is a strategic resource, why is their work often questioned as having no value?

The Oil Value Logic

The oil industry's value chain, refined over a century, operates with mature clarity:

Exploration : Proving an oil field exists immediately attracts capital market attention.

Extraction : Bringing crude oil to the surface generates direct cash flow.

Trading : Crude oil is a standardized commodity that can be bought and sold on markets.

Refining : Processed into gasoline, diesel, and other products that end consumers purchase.

In this chain, "discovery" nearly equals "monetization." Oil's value is inherently visible; it is a tangible commodity.

Data's Different Reality

Data does not follow this pattern.

No standardization : Complex sources, diverse formats, and uneven quality make direct pricing difficult, unlike oil.

Cannot be directly traded : Enterprise core data is neither suitable for sale nor the true source of its value.

Value depends on scenario : The same data may be critical for a marketing team but meaningless for another business line.

This means data's value does not automatically emerge; it must be activated through business scenarios.

Why Teams Fall into the Value Trap

Data teams often showcase achievements by counting integrated data sources or built data catalogs. They view these as resource exploration and foundational value. However, management sees these results as still far from business value: data existence does not equal realized value .

Applying oil-industry thinking here is dangerous—data itself is not a commodity; it only creates results when it interacts with business.

Business Is the Value Amplifier

To make data work, it must combine forces with business roles:

They define scenarios : Identifying which problems are worth solving with data.

They convert value : Turning data insights into marketing strategies, product features, or management decisions.

They explore patterns : Using data capabilities to try new services and revenue models.

Without business, data remains cold inventory. Only in application does it become a driver.

The Cognitive Shift Data Teams Need

The "data is oil" metaphor highlights data's strategic attribute, but mechanically applying oil's value logic leads to a dead end. Data teams need clearer positioning:

Data is not an independent industry chain, but an accelerator of the business value chain.

When presenting results, don't just emphasize "exploration"; answer which business scenario it changes.

Maintain a sober view of data value—neither underestimate nor mythologize it.

Data work's value does not cash out overnight like oil, nor does it appear through slogans. It requires long-term refinement, co-creating scenarios with business, and continuous accumulation in practice. This is not an overnight task, but with clear direction and cognition, data will eventually precipitate into the true productivity that drives sustainable enterprise development.