We’ve all been there. A business stakeholder makes a request, and before the meeting is even over, ideas are already buzzing: What dashboard we could create, what model we could train, which tools we could use. But just because you can build something doesn’t mean you should. As data professionals, our first responsibility isn’t to code. It’s to think.
In fast-paced environments, it's tempting to prove value by delivering quickly. But real value comes from solving the right problem, not just building a solution. That means taking a beat. Asking better questions. Getting clear on the “why” before diving into the “how.”
Step back to step forward
When a stakeholder says they need a data pipeline, dashboard or report, try to understand what’s really driving the request:
What decision are they trying to make?
What pain are they trying to reduce?
What does “useful” actually mean to them?
Sometimes they want a short-term answer to unblock a project. Other times, they need a long-term lens into business health. The form may look similar, but the underlying need can be wildly different. Without that clarity, you risk building something that’s technically sound and brilliant but functionally ignored.
Think beyond the request: Be a thought partner
The most impactful data teams aren’t the ones that respond the fastest. They’re the ones that think deeper. They don’t just fulfill requests. They challenge assumptions, refine problem statements, and surface alternative approaches.
This shift builds trust. It leads to better products. It makes the work more fulfilling. And it starts with a mindset rooted in curiosity, not compliance.
Instead of:
“Okay, let’s build that dashboard.” Try: “What decisions will this help you make? What does success look like here?”
That one question can change the trajectory of a project.
Delivering the right thing, not just the first thing
One of the biggest risks in data work is optimizing for speed over fit. But if a solution doesn’t actually help someone make a better decision, or, worse, leads to a misleading one, it can cause more harm than good.
Taking time upfront to clarify needs doesn’t slow you down. It saves you time by reducing rework, realigning expectations and increasing adoption.
Some practices that help:
Start with use cases, not data sources Don’t begin by exploring what data is available. Start with what the user is trying to accomplish, then work backward.
Distinguish between exploratory and repeatable needs Is this a one-time investigation or something that should live in a dashboard?
Clarify time sensitivity Does this need to go out tomorrow, or are we building a long-term asset?
Ask who else will use this Designing for one stakeholder is different from designing for a broad audience.
Why this matters more than ever
Data teams are increasingly seen as enablers of strategic advantage. But with that visibility comes the pressure to deliver faster, build cooler things, adopt newer tech.
Plus with the rise of gen AI, it has become even easier to spin up analyses, dashboards and even code with minimal effort. The barrier to building is lower, but that conversely means that the cost of building the wrong thing is even higher.
That’s why it’s more important than ever to stay grounded in business value. You don’t have to incorporate the flashiest model or build the most beautiful dashboard to have impact. Sometimes the best product is a simple metric that is clear to understand and leads to action.
Final thought
So before you spin up that query, start that notebook or mock up that dashboard, pause. Don’t jump to the first thing you can build. Get curious. Ask the right questions. Then go build the right solution.
Rajat Verma is a developer with ServiceNow.
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