Is Data Really the New Product, or Just Another Asset?

Created on 2025-08-09 07:01

Published on 2025-08-22 11:15

When I hear companies call data “the new oil,” I can’t help but wonder: is data truly the product, or just another corporate asset waiting to expire or clutter storage? With global data volumes forecasted to keep exploding, it’s time to ask whether treating data as your product strategy is a masterstroke—or a misstep.

The Buzz: Why Some See Data as the Product

Data monetization is more than marketing jargon—it’s happening. McKinsey charts how organizations are climbing the DIKW pyramid, transforming raw data into AI-powered intelligence that becomes the foundation for entirely new offerings and businesses  . Similarly, companies across industries—PepsiCo, JetBlue, Fox Networks, Checkout.com—are building internal “data products” for analytics or customer insights that directly drive decisions and bottom-line value  .

Beyond internal cost savings, some firms are licensing insights—or even anonymized data—to monetize externally. Banks and fintechs are experimenting with selling anonymized customer data for advertising or upselling, though not without privacy backlash 

Even further, Deloitte’s Aug 2025 survey reveals that while a whopping 88% of respondents call data “critical,” only 11% involve IP teams in its management—suggesting that data is still treated like an afterthought, not a strategic intangible asset  . One of their recommendations? Adopt a “lean data” mindset: collect only what’s essential to reduce storage and privacy risk while boosting value  .

All this momentum forms a strong argument for treating data as a product worthy of strategic focus.

The Skeptic’s Lens: Why Data May Not Always Be the Product

On the flip side, turning everything into a “data play” comes with hazards. Overcollection can lead to bloated infrastructure, steep storage costs, and complexity—for situation where there’s no real insight, just noise. Datamation calls out the high price tag of big data initiatives: hardware, tools, specialist hires—and often slow returns  . Worst of all, without governance, data becomes debt—muddy, untrustworthy, and non-actionable.

Privacy risk isn’t hypothetical. Revolut’s eyebrow‑raising attempt to monetize transaction data triggered backlash and fueled skepticism about how comfortable customers are with firms treating their data as a commodity  .

Platform-based models like Data-as-a-Service (DaaS) promise flexibility, but rent rather than ownership—and raise concerns around leaks, piracy, or misuse, particularly when consent or anonymization fall short  .

Bridging the Divide: Product vs. Asset, Not Either/Or

Maybe we don’t need a binary answer. The modern concept of a data product—as defined in recent literature—is a reusable, governed, discoverable asset enriched with metadata, quality controls, and domain ownership  . It’s not just raw data; it’s packaged for real value.

Enter data mesh, which codifies “data as a product” as one of four pillars: treat data from each domain as a product with discoverability, trustworthiness, and interoperability baked in  . The concept of autonomous data products takes this further—self-contained, self-governing services that manage their lifecycle, quality, dependencies, security and observability automatically  .

In short, smart organizations are reframing data as product—with product thinking applied when, where, and how it delivers value—while treating it as an asset when sitting dormant.

Provocative Questions for Your Team to Debate

I hope this exploration stirs deeper thinking. Here are some questions to spark meaningful discussion at your next all-hands—or strategy offsite:

Practical Approaches to Anchoring This in Your Organization

If you’re considering taking data strategy in a more product-led direction, here are three practical, action‑oriented approaches you might consider:

Start small with a high-impact pilot. Identify one domain—like customer churn, logistics, or product usage—where data, properly packaged and governed, becomes a tangible product for internal or external users. Build with metadata, SLAs, quality metrics, and user feedback loops baked in. If PepsiCo, JetBlue or Fox can do this for decisions at scale, so can you  .

Lean Data + Governance Framework. Follow Deloitte’s advice to trigger “lean data” strategies: only collect what’s directly valuable. Couple that with data product governance—clear ownership, quality thresholds, metadata, access policies. Lean data means less risk and cost; governance provides trust  .

Treat data monetization like product development. Adopt R&D and product management disciplines: research stakeholder needs, scope iterations, define customer/user personas, measure ROI, and staff accordingly. Monetization should feel as rigorous as building any other product  .

In the End, What’s the Punchline?

Treating data as a product strategy is neither magic nor brandspeak—it works when applied thoughtfully and targeted. Done right, it unlocks new insights, monetization paths, and innovation. Done wrong, it becomes noise, cost, and risk. So, is data the new product—or just another asset? The real answer: it depends how smartly you make it a product.

References