Four checkpoints that separate a dashboard people actually use from one that quietly becomes wallpaper.

Walk into almost any company and you'll find dashboards everywhere: on office screens, pinned browser tabs, weekly export routines nobody remembers setting up. And yet ask people how often those dashboards actually change what they do on a Tuesday morning, and the answer is usually “not really.” The dashboard gets built, gets a warm reception in the kickoff meeting, and then quietly turns into wallpaper.

This isn't because dashboards are a bad idea. It's because building one that actually works is a much harder problem than it looks.
In this blog we will go through a list of topics you need to consider, if you want a dashboard that actually moves the needle in your business

01: Solving the Right Issue

Before a single metric gets chosen, there has to be a real question the dashboard is trying to answer.
Way too often a dashboard starts with a topic, like “Sales” or “Service”, and not a business issue that needs to be solved.

The starting point shouldn’t be “let's visualize our sales data,” but something closer to “why are deals stalling in the negotiation stage?” or “where are we losing service capacity?”
Skip this step and you end up with a dashboard that's technically impressive and practically pointless, a wall of numbers in search of a question.

This is also the step that gets rushed most often, because it's the least fun part. Picking chart types feels like progress; sitting with stakeholders to pin down the actual operational pain point feels like a delay. But every dashboard that never gets used traces back to this same root cause: nobody was quite sure what problem it was solving in the first place.

02: Choosing Metrics That Relate to the Issue

Once the issue is clear, the next job is finding metrics that genuinely explain it, not metrics that are simply available, or that look good in a slide, or that everyone else in the industry happens to track. A metric earns its place on the dashboard by having a real, traceable connection to the issue at hand.

This is where a lot of dashboards quietly go wrong. Vanity metrics sneak in because they're easy to pull and always trend upward. Total page views, total tickets logged, total anything: numbers that grow simply because the business grows, and that say nothing about whether things are actually going well.
A metric that doesn’t add to the answers to the question being asked isn't wrong exactly, it's just occupying space that a more relevant metric should have.

03: Making It Understandable, for the Metric and the Chart

Here's a distinction that's easy to overlook: understandability isn't only about picking a metric with a clear, unambiguous definition. It's just as much about how that metric is presented. You can have exactly the right metric, precisely defined, and still lose your audience entirely if it's buried in a dense table, plotted on a misleading axis, or crammed next to twelve other numbers competing for attention.

Good data with a bad chart produces the same outcome as bad data: nobody trusts it, nobody reads it correctly, and nobody uses it. Time spent choosing the right metric is wasted the moment it's rendered in a way people have to squint at or reverse engineer. A dashboard's visual design isn't decoration on top of the analysis, it's part of the analysis. It's the difference between a number sitting on a page and a number actually landing in someone's head.

BI Developers often gets this wrong. A data-savvy person often has a higher ‘data literacy’ than dashboard user. Therefore, getting the charts/visualizations right is key!

Data visualizations are like jokes... if you must explain them, they are bad!

04: Getting It to the People Who Can Act on It

The last link is the one that's easiest to forget entirely: does the insight actually reach the people who can do something with it, and do they actually absorb it? A flawless dashboard that only the person who built it ever opens hasn't created any value. Neither has one that reaches the right team but gets glanced at once a quarter during a review meeting.

This link is about distribution and habit as much as design: making sure the dashboard lives where people already work, that it's part of a recurring rhythm (a morning huddle, a weekly check in), and that the people looking at it are the ones with the authority and context to act on what they see. A dashboard's value isn't created when it's built. It's created every time someone looks at it and changes course.

A think worth considering, when working with Analytics inside Salesforce is, that CRM Analytics or Tableau Next component can be implement directly into the Salesforce Interface like Record Page or Home Pages.

Bringing It Together: The Metrics Hierarchy

To see how these four links actually play out, picture a Sales department with one overarching goal: Increase revenue

The natural top level metric could be “Budget to reach this Month” and “Current revenue this month”. It's relevant, it maps directly to the goal, and it's easy enough to understand. But it fails on actionability in an interesting way: the Sales Reps themselves can't use this number to become more efficient in closing deals, but it sets the context for what the rep is trying to achieve.

So the team needs a metric one level down, closer to what they actually influence: Average Deal Velocity.
This is more actionable (Sales Reps can genuinely affect how fast their deals move), but it's still a lagging, aggregate number. Knowing the average sits at 15.2 days doesn't tell any individual Sales Reps what to do this afternoon.

That's where the third layer comes in: a live view of every deal that is about to stall within the next 24 hours. This isn't a KPI in the traditional sense, it's an operational worklist derived from analytics. And if you add the option for the Sales Rep to call the customer directly from the dashboard... then we’ve beautifully tied analytics and actionability together.

This is the exact layer that actually drives behavior, because it delivers the answers to the only question that matters at 9am on a Monday: what do I work on right now? Getting back to the deals that are about to go cold, before they are lost entirely is precisely the behavior that pulls the needle in the right direction.

This is the metrics hierarchy: a chain running from a strategic, top level indicator that tells you whether you're winning the broader war, down through team level metrics that show whether you're winning the relevant battles, to operational views that tell individual people what to do today.
Not every layer needs to be directly actionable; the top level metric's job is to keep everyone honest about the bigger picture, not to hand out daily to do lists. But without the layers underneath it translating that goal into something concrete, the top metric just sits there looking important.

A strong dashboard doesn't happen by accident. It happens when someone has been deliberate about all four links (the right issue, metrics that explain it, a presentation people can actually read, and a path to the people who can act) and has built the layers connecting the big picture to the daily work. Get all four right, and the dashboard stops being wallpaper and starts being the reason things actually change.