Top 3 Best Practices For Dashboard Design

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An increasing number of organisations are adopting self-service BI, which is leading to the production of more and more reports/dashboards. Unfortunately, within these organisations, there’s often a lack of governance and data literacy. People who are creating these reports and dashboards have very little formal training in the analytics space, leading to an abundance of visualisation artefacts that don’t adhere to some of the fundamental dashboard design best practices.

A world of data analysts?

According to Forbes, data literacy is the most important job skill that companies will be looking for in 2020. The ability to leverage data and use analytics tools to produce valuable insights is no longer a skillset that only people with analytics and marketing backgrounds have. With intuitive analytics tools such as Power BI, Tableau, MicroStrategy and Qlik, coupled with high demand for data and not enough supply of in-house analytics capabilities, the rapid shift to self-service BI is happening.

In this blog, I’m not going into the whys/why nots of whether this trend is either positive or negative – although that sounds like a great topic for another time! Instead, I’ll provide my top 3 dashboard design best practices to consider before designing and creating your dashboard. 


#1- Know Your Target Audience

The first question before even starting on the design of a dashboard is-

Who is this dashboard being built for?  

Here are some examples:

C-Level Executives – “What Is Happening?”

Executives use dashboards to monitor what is happening quickly e.g. projected sales forecasting for the month. If there are any questions on the sales numbers, they would be able to contact somebody on the sales & marketing team to do some more in-depth analysis. A high-level executive dashboard that contains pertinent KPIs with little to no interaction capabilities embedded in it would be a good approach to take.

Sales and Marketing – “Why Are Things Happening?”

Compare the above to the marketing or sales team who want to be able to explain why things are happening in regards to the sales forecasting numbers being on target or not. Somebody on the team would need to have the ability to conduct some exploratory analysis on the data at a lower grain, which is what the KPIs are based off.

As you can see, these are two completely different audiences who want to look at the insights from a different granularity perspective. In the visual examples below, you can see how these dashboards might look. 

Take a look at the dashboard images below:

A: C-Level Executives

The dashboard helps a user understand “what things are happening”. The dashboard contains:

  • High-level KPIs and trend visuals which can be easily read and interpreted quickly.
  • Comparisons can be done by reviewing the current results, last month results, and target from a high level.
  • No interactivity via filters as it is primarily for an analysis perspective.

Source: Datapine

B: Sales/Marketing

The dashboard helps a user understand “why things are happening” from a customer segmentation standpoint. This dashboard contains:

  • Visuals that show results by different categories right below the KPIs at the top.
  • Filter at the top that allows the user to interact with the dashboard to compare results by different years.
  • Interaction with different visuals to answer their own “why” story.

Source: Power BI Data Stories Gallery

#2 - Formulate a specific question that dashboard visualisations will answer

The keyword in the title of this best practice is “specific”. Let’s use an HR dashboard as an example.

An HR dashboard that contains a visual for attrition, one on demographics, and one on performance displays a range of data, but does it answer a specific question? Not really. It’s common to see these types of dashboards, and they’re almost always created without developing the specific question in mind first.

Creating dashboards based on specific questions

Continuing to use HR as an example, here’s a list of specific questions you may want to answer along with a corresponding dashboard title. Rather than creating one cluttered dashboard, you’d create three separate dashboards.

Specific question Dashboard Name
Why are we experiencing high employee turnover? Employee Attrition
Who are my current employees? Employee Demographics
How are employees performing based on our annual performance reviews? Employee Performance

Take a look at the dashboard images below:

Image A - Bad example - You'll see an example of a dashboard that has lots of interesting insights to look at, but they’re answering different questions. It ends up being cluttered and non-specific.

Image B - Good example - In this dashboard, all the visuals contribute towards answering a specific question “why are we experiencing high employee turnover?”

#3 - Define a consistent layout for all your enterprise dashboards

When creating a dashboard, I’d highly recommended that you create a template so that future dashboards have a consistent look and feel. By creating the template to be used by others in your organisation, you ensure that users will have the same experience when working with your enterprise dashboards. These templates should have the following components:

  • Title

At the top of the screen is recommended. Think of a newspaper article - you start with the title, then the summary, and then dive into detail. Your dashboard should be structured similarly.

  • Company Logo

This can be in the header and footer section. I’ve seen each approach taken at various organisations. I’d recommend working with your marketing/UX team to ensure this is consistent with other logos used in other applications in the organisation.

  • Filter Pane

Can be in the top right-hand corner in the header section or the right or left-hand side below the header section and above the footer. It should be easy for the user to distinguish where it is as it’ll be used to interact with the visuals on the dashboard.

  • Colour Scheme

In many of the analytics tools, you’re able to create and customise your own templates. Again, I’d recommend working with your marketing/UX teams to define these colour schemes in your template.

Take a look at the dashboard images below:

Image A - Bad example - This dashboard does not have a consistent and simple layout. The dashboard has the following issues:

  • Summary (KPI's) and detailed (table) visuals are chaotic. It's not easy to read as the user is continuously shifting their focus between looking at summary and detailed visuals. 
  • No consistent colour and font scheme in place. 

Image B - Good example - This dashboard does have a consistent and simple layout. 

  • Filter pane in the top right
  • Company logo and title on the top left. 
  • Brand colour scheme and font are used. 


Here are three other best practices that did not quite make the cut of my top 3 list but are extremely important as well when designing and building your dashboard:

  1. Reduce the clutter - limit the number of visualisations.
  2. Provide context.
  3. Choose the right visual.

If you need a bit more guidance about creating a well-designed dashboard that meets best practice and delivers the right expectations, get in touch. Our in-house training is also a great way of making sure your team are on the same page with this too.  

Find out more about our Power BI Training 



About the author: Ryan Fonnett has been in the BI and analytics space for over 12 years. His passion is to deliver end to end data-driven solutions that enable our customers to have an edge over their competitors.