The 5 Questions You Must Ask Before Building a Dashboard

In the world of data, the greatest temptation is to jump straight into the technology. To open Power BI, connect to a data source, and start "drawing" charts. This approach is almost always a recipe for failure, leading to slow, confusing, and, above all, useless dashboards that end up being ignored by everyone.

A successful dashboard is not born from a tool, but from a strategy. And a strategy is always born from the right questions. Before writing a single line of code, an expert consultant guides the client through a discovery phase to build a solid foundation. Here are the 5 fundamental questions I ask with my clients at the start of every project.

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1. What is the Business Objective? (The "Why")

This is the most important question, the North Star of your entire project. We don’t ask, "what data do you want to see?" but rather, "what business problem are you trying to solve?". The answer cannot be a generic "I want to see sales." It must be deeper, more specific, and tied to a clear business outcome.

• Vague goal: "I want to see our sales."
• Actionable objective: "I want to understand which of our products have the highest profit margins so I can optimize the production budget," or "I want to identify the marketing channels with the lowest customer acquisition cost to scale our investments effectively."

A dashboard without a clear business objective is merely a stylistic exercise, not a professional tool. Getting the "Why" right ensures that every single element we build is purposeful and contributes to a tangible business result.

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2. Who Will Use This Dashboard? (The "Who")

A dashboard is a product, and every good product is designed for a specific user. A dashboard for a CEO must be different from one for a marketing specialist or an operations manager. The CEO needs a high-level, immediate, and strategic overview (the classic "traffic light" indicators). The specialist, on the other hand, needs to be able to dig deeper, apply filters, and analyze the details to find the root cause of a problem.

Designing without a specific end-user in mind is like speaking a language no one understands.

• Concrete Example: For an e-commerce company, the CEO’s dashboard might show only three key numbers: Total Revenue vs. Target, Overall Profit Margin, and Customer Satisfaction Score. In contrast, the Marketing Specialist's dashboard would show a detailed breakdown of campaign performance, conversion rates by channel, and return on ad spend (ROAS) for each specific ad. The Operations Manager's dashboard would focus on inventory levels, shipping times, and return rates.

This is why defining a "User Persona" (e.g., "Giulia, the Marketing Manager") is a crucial step in my UX-first design process. It allows us to build with empathy and ensure the final product is genuinely useful.

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3. What Decisions Will Be Made? (The "Action")

A dashboard is not meant to be passively "looked at"; it is meant to "trigger an action." Its value is not in the data it shows, but in the quality of the decisions it enables. For every chart and every KPI we consider including, we must ask ourselves: "What specific decision will be made by looking at this number?". If the answer is vague or "none," then that element is likely just noise and should be ruthlessly eliminated.

• Concrete Examples of Decisions:
  • Marketing: Increase the budget for Campaign A and pause Campaign B.
  • Sales: Contact the top 5 clients whose purchasing frequency has dropped this month.
  • Operations: Reorder Product X because inventory levels are below the safety threshold.

Thinking in terms of decisions forces us to design a tool that is active, not passive.

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4. How Do We Measure Success? (The "What")

Only now, after defining the Why, Who, and Action, do we talk about metrics. Based on the decisions to be made, we identify the few, fundamental Key Performance Indicators (KPIs) that will tell us if we are moving in the right direction. The most common mistake is to drown a dashboard in dozens of secondary metrics, creating a "data dump" that is impossible to interpret. My job is to help the client distinguish the signal from the noise.

• Concrete Example: For an online business, a simple metric is the "number of social media followers." It's satisfying to watch it grow, but it doesn't necessarily correlate with business success (a "vanity metric"). A true KPI, tied to the business objective of profitability, is the "Customer Lifetime Value (LTV) to Customer Acquisition Cost (CAC) Ratio." This single, powerful KPI tells us if our business model is sustainable in the long run.

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5. What is the Context? (The "Story")

A number on its own means nothing. Is "€10,000 in revenue" good or bad? It depends. Compared to last month? Compared to the same month last year? Compared to our target?

Every KPI must be presented with the right context (a trend, a comparison, a goal) to transform it from a simple data point into an insight that tells a story. Without context, data is just information; with context, it becomes intelligence.

• Concrete Example: Seeing a card that just says "Revenue: €10,000" is unhelpful. A well-designed card would say: "Revenue: €10,000" and right below it, in a smaller font and with clear visual cues, show "+5% vs. Last Month" and "-10% vs. Target," perhaps with a red indicator arrow. Instantly, the user understands the full story: we are growing month-over-month, but we are behind schedule on our strategic goals.

Starting with these five questions shifts the focus from technology to value. It is the first and most critical step in transforming a data visualization project from a simple cost into a powerful strategic investment. If you too want to start on the right foot, let's talk about your project.