A picture is worth a thousand words — or so the saying goes, right? Dashboards in BI tools accelerate decision-making by converting complex data into actionable insights.

While a well-designed dashboard can be a handy resource, a poorly-designed one can be just as confusing and misunderstood. This article discusses some business intelligence best practices to keep your presentations looking good!

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Article Roadmap

• What Is a BI Dashboard, and Why Use One?
• Business Intelligence Best Practices
• Next Steps

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 unified data view that seeks to answer business questions by displaying key performance indicators (KPIs) for analyzing information. A dashboard is need-specific — you might want to view the sales figures by city for the last six months.

Or you might pull data from sales and marketing reports to show conversion metrics by channel, the cost incurred and the revenue earned from each channel. A dashboard is your at-a-glance view of this consolidated information.

What’s great about them is — they include easy-to-understand charts and graphs and provide interactivity, real-time connectivity and customization options.

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

With all the benefits a dashboard can provide, learning to make one is worth the time and effort. To help you along, here are seven BI best practices for designing BI dashboards.

Let’s dig deeper and find out how to implement them at your place of work.

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Business Intelligence Best Practices

1. Identify Requirements

From start to finish, the number one priority of a dashboard is to provide information that answers a question. Your first step should be identifying what information you need to include.

Ask yourself these questions as a BI dashboard best practice:

• Why do you need this dashboard?
• What problem are you 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 will need highlighting?
• 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 to address your questions.
It should offer critical decision support with an at-a-glance view of the desired metrics — so identifying which metrics matter is an essential BI best practice.

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? If you don’t know much about your audience, you can start by considering their priorities.

As a BI best practice, you should design separate dashboards tailored to your specific audiences. What information is important for each audience, and what decisions must they regularly make?

• Executives and investors want to see dashboards summarizing KPIs over time using time-series analysis.
• The marketing department wants to determine the ROI of their marketing campaigns.
• A busy salesperson might have just a few seconds to see the KPIs most relevant to their work.

Customization is a key feature in many BI solutions nowadays, and it’s easy when you know what your audience wants to see.

3. Accentuate the Most Important Information

Dashboards are all about telling a story — and just as a journalist puts the most important information in the first paragraph, your dashboard should begin by highlighting your most relevant insights first.

A BI dashboard best practice is the inverted pyramid — a concept that came from journalism, coincidentally.

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

  Put the most significant data at the top, followed by important details that provide further understanding. Finally, finish with granular background information, which helps the reader dig deeper.

• 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, the most-viewed spot, for your most significant insights.

• BI reports are packed with tons of numbers and information, making them hard to digest. It doesn’t have to be the case with dashboards! With the right BI tools, you can highlight critical points with visual cues like positioning and a color palette.

4. Use the Right Visualizations for Your Data

The visualization that best communicates your data may not be the best-looking one. Those pie charts are tempting but might not always be the right choice.

Let’s look at an example of where a row chart is more effective than a pie chart.

Convey your message better with the right visualization. Source

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 compared to each other instead of as parts of a whole – when they’re not parts of a whole.

As a BI dashboard best practice, ask yourself when choosing a 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 and spider and bubble charts
2. Comparison
   Compares two or more variables side by side
   Examples: Bar, column, spider, table and line charts
3. Composition
   Visualizes variables in relation to the whole
   Examples: Stacked bar, area, pie, donut and waterfall charts
4. Distribution
   Lays out the distribution of variables
   Examples: Line, histogram and scatter charts

As a BI best practice, assess which visualization type works best with your data. It’s best to play around with your BI tool and determine which visualization makes the most sense in your context.

Some BI solutions include a wizard or AI assistant for choosing the right data visualization for the job!

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5. Provide Context

Showing a metric isn’t enough – you must add context about whether it shows a positive or negative trend. Without context, users can’t understand the true meaning of data, what action they need to take or whether it’s required.

Knowing how many leads you generated this year is excellent, but what about last year? How does that number compare to the target you set for this year? Is it an upward trend or an improvement area?

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

Pro Tip: Labeling the axes, columns, rows and legends with appropriate titles and descriptions conveys the scale and significance of the presented numbers.

Precise, contextual data determines if a dashboard can support your business workflows and decisions. This business intelligence best practice drives daily tasks and contributes to higher-level decision support.

6. Add Interactivity

Boring presentations and unintelligible analyst reports are a thing of the past. Nowadays, interactivity is crucial to delivering insights in today’s digital world and interactive dashboard software are the tools of choice for enterprises.

SSome of the best interactive dashboard features on the market include:

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

These capabilities engage end-users as active participants in your data story instead of consuming the information passively. Starting with a high-level overview, users can drill down at will for specific details.

With interactive dashboards, users can explore information independently and focus on the data relevant to their role.

It’s easy to understand why many BI tools have interactive dashboards as a critical feature; the interactivity adds value and boosts engagement.

If selecting software, comparing dashboard functionalities can help you decide on a best-fit solution. If you already have one, getting acquainted with its
interactive capabilities will help maximize your investment.

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, “Don’t make your dashboard hard to read!”

Here are some common mistakes to avoid and optimize your dashboard for readability:

Don’t clutter

Less really is more when it comes to dashboards. Don’t put too much information on there — picking through too many numbers can be just as confusing as making sense of too few.
As a BI dashboard best practice, 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. It would help to remove anything that isn’t essential to the dashboard’s purpose and the overarching question.

Don’t Be Afraid of Whitespace

Though it can seem daunting to leave empty spaces 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, it can make your dashboard an eyesore.

Sure, accentuate specific data points with color if they need to stand out, but try to keep your overall aesthetic simple. Otherwise, it’ll overload your viewers. Using three or fewer colors in a dashboard will keep it easy on the eyes and clutter-free.

Readability is quintessential — your dashboard should be visually appealing and easy to understand. You can convey information better by focusing on readability.

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Next Steps

Dashboards save time by simplifying complex insights and providing crucial decision support. An effective dashboard allows for analyzing business-critical information to decide the next steps.

These business intelligence best practices should be part of every organization’s data culture as they scramble to keep pace with changing trends, and time to market is at a premium.

Need help buying a dashboard software solution? Get our free, customizable comparison scorecard which ranks products on the features that matter the most to you.

Which BI dashboard best practices do you follow at your organization? What worked and what didn’t? Would you like to add to the list? Let us know in the comments!