The 7 Most Important BI Dashboard Best Practices

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A picture is worth a thousand words — or so the saying goes, right?

Consider the dashboard the “picture” of the business intelligence world. They are powerful tools and considered essential features for many BI tools. As data visualization aids, dashboards help decision-makers save time by converting complex data into actionable insights. However, as effective as a well-designed dashboard can be at communicating these insights, a poorly-designed one can be just as confusing and misunderstood.

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Best Practices for BI Dashboards


How can you make sure to design a successful, visually appealing dashboard? We’ll list some best practices to keep in mind, but first, let’s explore what a BI dashboard can do for you.

What is a BI Dashboard and Why Use One?

A dashboard is a data visualization that seeks to answer a business question by displaying key performance indicators (KPIs) and analyzing information. They are built to fulfill specific needs and generally include charts and graphs, interactivity, real-time connectivity and customization options.

Power BI Dashboard

Example of a dashboard, from Microsoft Power BI

A well-designed BI dashboard:

  • Makes sense of and demonstrates the true, underlying meaning of data
  • Tells a clear story about your data
  • Reveals the next step in the decision-making process
  • Is easily decipherable and scannable in about five seconds
  • Saves time and money
  • Makes data easily accessible to all

According to a 2019 study by Dresner, dashboards ranked second overall in technologies and initiatives strategic to business intelligence. More than 80% of respondents said that dashboards are “critical” or “very important” to business intelligence, with only 2% of respondents saying dashboards are “not important.”

With all of the benefits a dashboard can provide, it’s clearly worth the time and effort to learn how to make one. To help you along, here are seven best practices for designing BI dashboards.

Let’s dig deeper and find out how you can implement these practices in your business.

BI Dashboard Best Practices

1. Identify Requirements

The purpose of business intelligence dashboards is to find data-driven answers to critical business questions. From start to finish, the number one priority of a dashboard is to provide information that answers a question. So, your first step should be to identify what information you need to include on the dashboard to accomplish this.

Ask yourself these questions when designing BI dashboards:

  • Why do you need this dashboard?
  • What is the problem you are trying to solve?
  • What data do you need to make a decision?
  • What kind of device will viewers use to access this dashboard?
  • Which metrics should be highlighted in particular?
  • What reports do you already have?
  • What action can you take based on these insights?

A dashboard is a snapshot of specific data, not a detailed report from every source. Each KPI on your dashboard should provide valuable information and address the question for which the dashboard was created. It should offer an at-a-glance view of a particular set of metrics relevant to the decision at hand — so identifying what is necessary is step one.

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2. Target Your Audience

The best dashboards start with their intended audience in mind.

Consider your audience and answer this question: what do they need from this dashboard to be successful? While designing your dashboard, you should consider your audience’s specific needs. If you don’t know much about your audience, you can start by considering their priorities.

Executives and investors want to see dashboards that summarize KPIs over time so they can make data-driven business decisions for the future. The marketing department will want to see dashboards that consolidate metrics that they can use to determine the ROI of their marketing campaigns. A busy salesperson will want to spare just a few seconds to see the KPIs most relevant to their work.

As such, you should design separate dashboards that are tailored to different audiences. What information is important to each audience and what are the kind of decisions that they need to make regularly? Customization is a key feature in many BI solutions nowadays, so after evaluating these needs, you should be able to personalize your dashboard to be as relevant to the user as you can.

3. Accentuate the Most Important Information

Dashboards are all about telling a story — and just like a journalist puts the most important information in the first paragraph of their article, your dashboard should begin by highlighting your most relevant insights first. A useful practice to adhere to is the inverted pyramid — a concept that came from journalism, coincidentally. Put the most significant and substantial data at the top, followed by important details that provide further understanding and finally finish with granular, background information which helps the reader dig even deeper.

Inverted Pyramid for Dashboard Design


A dashboard should cut through the junk and give the user their main takeaways at the start. By doing so, it accomplishes its goal: saving the user time.

Eye-tracking studies show that web users spend more time viewing the left half of a page versus the right half. Considering that most people read from left to right and top to bottom, you can leverage the top-left, which is the most-viewed spot, for your most significant insights.

BI reports are often packed with tons of numbers and information, making them hard to digest. This doesn’t have to be the case with dashboards! With the right BI tools, you can guide users to the right metrics and trends with visual cues like positioning and a color palette to highlight critical points and subdue insignificant ones.

4. Use the Right Visualizations for Your Data

The visualization that best communicates your data often may not necessarily be the best-looking one. I know – those pie charts are tempting, but they’re actually not effective at conveying data. Let’s look at an example of where a row chart is more effective than a pie chart.

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Here, the row chart is less confusing because it uses one color instead of 10 different colors. It’s also more effective because it presents the 10 data points in comparison to each other instead of as parts of a whole – when they’re not really parts of a whole.

Ask yourself this one question when choosing the right visualization:

What do I want to communicate with these insights?

Take a look at the flowchart below:

Data visualizations generally show four different types of information:

  1. Relationship
    Shows a connection between two or more variables
    Examples: Scatter plots, spider charts, bubble charts
  2. Comparison
    Compares two or more variables side by side
    Examples: bar chart, column chart, spider chart, table, line chart
  3. Composition
    Visualizes variables in relation to the whole
    Examples: stacked bar chart, stacked area chart, pie chart, donut chart, waterfall chart
  4. Distribution
    Lays out how variables are distributed
    Examples: Line charts, histogram chart, scatter charts

Assess which category of visualization works best with your data. It’s best to play around with your BI tool and figure out which visualization makes the most sense in context. Some BI solutions even include a wizard or AI-powered helper that can assist you in choosing the right data visualization for the job!

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5. Provide Context

Showing a metric isn’t enough – you have to also add context to how good or bad it is. Without context, users can’t understand the true meaning of data, what kind of action they need to take, or whether action is needed at all.

For example: Yes, it’s great to know how many leads you generated this year, but what about last year? How does that number compare to the target you set for this year? Is that number good, bad, or unusual in any way?

Including historical data is an easy way to answer these questions. Note essential milestone dates or compare the numbers with those of previous time frames (i.e., month, quarter, year) so that the trends become self-evident.

Leads Generated in 2019


Pro Tip: make sure to label the axes, columns, rows, legend, etc., and add appropriate titles and descriptions if needed so that users understand the scale and significance of the numbers presented.

Clear, contextual data differentiates an effective dashboard from an ineffective one. This best practice ensures that your BI dashboards help users understand the impact of the information and empower them to take action.

6. Add Interactivity

Boring presentations and unintelligible analyst reports are a thing of the past – nowadays, interactive dashboards are the tool of choice to present information. Interactivity is especially crucial to delivering insights in today’s digital world.

Tableau BI Dashboard

Example of an interactive dashboard from Tableau which explains details when users hover their mouse over a metric and changes the charts when users click on them

Some of the best interactive dashboard features on the market right now include:

  • Click-to-filter to dissect data
  • Drill-down to show additional details
  • Time interval widgets
  • Chart zoom
  • Show or hide charts
  • Real-time metrics
  • Responsiveness for mobile and web

Interactive dashboard capabilities such as these engage end-users as active participants in your data’s story, instead of a captive audience. Users can focus on the big picture and then drill down at will for specific details. By giving the user control over which data they want to focus on, an interactive dashboard encourages users to explore for themselves.

Klipfolio BI Dashboard

Interactive dashboards like this one from Klipfolio can give real-time insight at a glance

It’s easy to understand why many BI tools have interactive dashboards as a key feature; the interactivity adds value and boosts engagement. If you’re still selecting software, be sure to compare dashboard functionalities between products; if you already have your solution, become familiar with all its interactive capabilities so that you can use them to your advantage.

7. Prioritize Readability: The Big Dashboard Don’ts!

So far, we’ve talked about the do’s, but what about the don’ts?

The biggest one is definitely, “Don’t make your dashboard hard to read!”

Here are some common mistakes to avoid to make sure your dashboard is optimized for readability:

3 Big Don'ts of BI Dashboard Design


Don’t clutter

Less really is more when it comes to dashboards. Don’t put too much information on one; confronting a flood of numbers can be just as confusing as picking through a scarcity of them. As mentioned previously, don’t pack too many visual elements into one dashboard at the risk of overwhelming the viewer.

Every element on your dashboard should have a purpose and a place. Anything that is not essential to the dashboard’s purpose and the overarching question should be axed.

Don’t be afraid of white space

Though it can seem daunting to leave emptiness on a between objects or widgets, white space helps viewers by drawing invisible lines that make a dashboard easier to read.

Don’t use too many colors

As data scientist Connor Rothschild notes, “Too often, we ask how we can use color in our visualizations when we should be asking why we are using it.”

While it may seem enticing to go all out with the colors of the rainbow, this actually can make your dashboard an eyesore. Sure, go ahead and accent certain data points with color if they need to stand out, but make sure to keep your overall aesthetic simple — or else it will overload your viewers. Using a uniform, limited color palette of, ideally, three or fewer colors across your dashboard will ensure consistent design and simple navigation.

Readability is quintessential: Your dashboard should be visually appealing and easy to understand. By prioritizing readability, you improve a dashboard’s ability to communicate information effectively.

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Final Thoughts

Ease is the name of the game with dashboards. They are easy to create, easy to use, easy to understand and easy to share. Hopefully, these best practices make it even easier for you to design your BI dashboards.

Dashboards are designed to simplify complex insights and, above all else, to save the user time and increase efficiency in making informed decisions. An effective dashboard helps the user analyze data meaningfully and leads them to the next steps.

Utilizing these best practices has become a must as more and more analysts implement dashboards moving into the digital age. If you’re looking for a BI solution with powerful data visualization capabilities that can make these kinds of dashboards, check out our customizable comparison tool scorecard, which ranks products according to your company’s requirements.

Did we leave anything out? What else are you interested in learning about BI dashboards? Be sure to let us know in the comments.

Hsing TsengThe 7 Most Important BI Dashboard Best Practices

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