Despite billions spent on modern data stacks, dashboards, lakes, and warehouses, a frustrating reality remains: most organizations still struggle to make their data useful. According to new research from Info-Tech Research Group, the problem isn’t a lack of tech—it’s a lack of purpose.
The global IT advisory firm has just published a new strategic blueprint titled “Launch a Customer-Centric Data-as-a-Product Journey,” laying out a practical framework to help organizations transform their approach to data from passive reporting to proactive, customer-aligned delivery.
And their message is clear: until data is treated like a real product—with customers, ownership, accountability, and quality control—trust, usability, and adoption will remain elusive.
The Core Problem: Not Just the Stack, But the Mindset
At the heart of Info-Tech’s findings is a subtle but important shift: stop treating data as a byproduct and start treating it as a product.
For years, IT teams have collected data without clear objectives, only to ask business units later, “So… what should we do with all this?” That backward model, argues Pooja Khandelwal, a senior analyst at Info-Tech, is part of what leads to low data trust, slow delivery, and a culture of reactivity.
“The data-as-a-product approach flips that by starting with the organization’s needs and aligning data efforts from the beginning,” says Khandelwal. “This enables better collaboration, stronger governance, and more consistent value delivery.”
What Is “Data as a Product,” Really?
At its core, the data-as-a-product (DaaP) model applies product development principles to data—meaning it has:
- Defined consumers (internal or external)
- Clear use cases
- Dedicated owners
- Continuous improvement cycles
- Measurable outcomes
The approach aligns data work with business goals from day one. Instead of dumping massive datasets into dashboards and calling it analytics, teams design purpose-built data products that are reliable, understandable, and immediately valuable to users.
Why Now? Because Data Alone Isn’t Enough
Even as generative AI, predictive analytics, and advanced ML capabilities go mainstream, most companies still suffer from low data maturity. Info-Tech notes that:
- Data ownership is typically concentrated in a single team
- Silos persist between IT and business units
- Many users don’t trust or even understand the data they’re given
The result? A flood of tools and dashboards with little real-world impact.
But the DaaP approach reframes data not as a technical project, but as a strategic business product, making it easier to scale, govern, and align across teams.
The Four-Step Framework: A Product Journey, Not a Tech Project
Info-Tech’s blueprint lays out a four-step methodology to help organizations begin their DaaP journey:
- Evaluate Organizational Readiness
Assess current data capabilities and alignment with business priorities. This ensures foundational gaps are addressed before launch. - Create Customer Personas & Journey Maps
Understand what data consumers need, how they work, and what frustrates them. This human-centric step informs product design. - Identify Opportunities & Prioritize a Use Case
Map pain points and key touchpoints to uncover high-impact use cases that deliver early wins and strong ROI. - Pick a Pilot Data Product
Launch with a high-value, tightly scoped product to demonstrate value quickly and build momentum for broader transformation.
These steps guide data leaders through not just delivery, but adoption—ensuring data isn’t just pushed out, but actually used.
From Numbers to Narrative: Building Data People Want
What sets DaaP apart is its emphasis on usability and trust—two elements often left behind in enterprise data projects. With an intentional design process, shared ownership, and ongoing optimization, data becomes a reusable, scalable asset—not just a report that no one reads.
And with the rise of self-service analytics, AI-driven tools, and data mesh architectures, the timing couldn’t be better. Organizations that succeed in this shift are likely to:
- Accelerate time to insight
- Reduce operational risks
- Foster a data culture across departments
- Boost user trust and adoption
- See real ROI from their data investments
A Strategic Wake-Up Call for Data Leaders
Info-Tech’s research reads like a subtle critique of the past decade’s “data-first” hype: we built pipelines, platforms, and clouds—but skipped the people part. The DaaP model is a correction, grounded in service design and product thinking.
It’s not just another framework. It’s a call to data leaders to focus less on collection and more on connection—between data, business needs, and the people making decisions every day.
In other words, treat your data like something people pay for, even if they don’t.
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