How to Design Effective Analytics Dashboards That Look Incredible in 5 Steps
Dashboards help effectively communicate tons of information and data which otherwise would have been boring. But creating good dashboards is an art. And let this be your how-to guide in making the art possible. We will take you in a step-by-step process of creating effective analytics dashboards.
5 Steps to Design Effective Analytics Dashboards
Step 1: Understanding who is the Dashboard for?
We can’t stress the importance of knowing the end user enough. The “end-user”- not the department, not the business unit — but the end-user.
If you’re thinking why? Then think about this scenario. The end-user of the dashboard is a C-Suite executive and instead of combined sales and the overall picture of the organization, the dashboard shows data specific to one region. Would that be useful for him? But instead, if the user was the Regional head then the data would be on point.
Therefore to make effective dashboards, an understanding of the users’ roles and knowing what they need can help you tailor the dashboard to their needs effectively, and streamline the process of effective decision making.
Step 2: Building the right type of dashboard
Wait! Are there are many types of dashboards? Yup, there are majorly three types of dashboards. They are Operational, Strategic, and Analytical Dashboards. Understanding these is important as the same people might need dashboards for a different purpose. Therefore, in addition to who the user is, understanding why is also important.
Operational Dashboards
Normally operations intend for the day-to-day activities of the business. This is what the dashboards represent. These dashboards are for managers who need to make decisions for short-term operations and performance optimization. These dashboards also involve data that needs to be real-time or at least recent enough to help make effective decisions and take prompt actions.
Strategic Dashboards
These dashboards are intended for executives who want a high-level performance overview at a larger scale. They use data accumulated over a period of time to decide on the KPIs which would help them make decisions. But for this drilling in and out features need to be enabled such that certain issues can be pinpointed on the dashboards.
Analytical Dashboards
The word Analytics in the name itself should be a giveaway for its properties. These dashboards are useful for benchmarking, comparing theories, and linking all the data to explore it in detail. This is for the people who want to understand the why, when, how, and what of the data by using filters, slicers, and drills. You might be thinking that the goal might be operations or strategic decision making, then why do we have a new category for it- it’s to emphasize that the goal is to dig deep into the data to get an overview of what is happening instead of the operations or strategy.
Step 3: Choosing the right chart type
Dashboards are the representation of a collection of data in a single place. It means you need to choose the kind of chart you want to represent your data with. Look at the infographic below, for more information on what types of charts can be used based on data usage.
Again, bringing in the first step back — knowing the user back because knowing how comfortable executives are with charts is important. You can’t use waterfall and box charts wherever even though they look nice. Make sure your audience is comfortable with the kind of charts you are using.
Source: Power BI Dashboards Best practices
Step 4: Think about the layout
No one likes cluttered data, nor too much white space. Find the perfect balance between the two to represent data well. Effectively using whitespace helps users to pause and study the report in detail than just skim through the facts.
As for the layout and the placement of charts, it is said that people read in a “Z” fashion. So keep your data accordingly i.e. focus more on the top left corner, so keep your important elements there and your least important items to the right bottom corner. But again, we are not generalizing it. If your audience reads from right to left this pattern might be different from them. So, use the convention of your audience.
Other parameters to think about are proximity and similarity. These mean to group elements of similar use together and group similar fonts and colors for visual appeal. This means keeping the reports legible by not putting in random things to fill the space but by grouping your related data. Most BI platforms allow you to create multiple tabs, therefore create sub-tabs if you think data doesn’t go with one other.
Also, expand yourself with a secondary palette in addition to your primary colors. This lets the audience experience the dashboards, instead of having highly contrasting colors.
Step 5: Add context
What are the two things that help users understand what is on the dashboard? Labeling and Context. Why is context important? Let’s take sales data for example. If you don’t mention the geography, time period, product, etc., would the data be really useful?
Otherwise, even beautifully designed dashboards, which have lots of data, colors, and various chart types wouldn’t make sense at a glance. This means you went overboard with — creating dashboards is an art — we were talking about and created something beautiful but redundant. Therefore labeling reports, including titles, legends, short-synopsis wherever necessary, etc. can be done.
That’s it. We’ve reached the end of the steps. But if you think these are enough then you might be wrong. The most important step comes after all this. It is practice. Only with practice can you achieve better results.
In conclusion
Know your audience. Practice regularly i.e. keep making dashboards regularly.
You can create an effective analytic dashboard design by:
- Understanding who is the Dashboard for
- Building the right type of dashboard
- Choosing the right chart type
- Thinking about the layout
- Adding context
Read about the 7 Best Practices To Make Effective Power BI Dashboards
