6 important UX considerations in a dashboard design!
As data becomes the new fuel, almost every business becomes significantly dependent on a dashboard. Dashboards are used across industries to provide a real-time representation of data in a summarized format leading to an easier comprehension.
For example, a logistics and transportation solution company improves its processes by cumulating all the metrics related to delivery and inventory on a dashboard, while a loan provider wants to see all the relevant customer data at one place before approving and disbursing a loan.
Since dashboards are being used more commonly across every industry, it becomes imperative for businesses to create dashboard designs which lead to a seamless viewable experience for their audience.
In this article, we put across 6 important UX stages to consider while creating a dashboard design.
Categorize your personas into roles
Your target persona is based on market research and demographics which are usually created while identifying the target audience. A dashboard design allows you to summarize data in the most optimized format which allows you to cater to the audience effectively.
Unlike other applications, a dashboard does not cater to each persona, but to each role.
Filter your target audience into personas and create a comprehensive list of each persona. Then, categorize each persona into roles and create a dashboard for each role and NOT for each persona. This will enable you to create an accurate user experience for your target audience.
Check the viability of your user research data
The first phase of creating any dashboard design is to gather an abundance of user data. The data that you collect is required to meet 3 criteria.
- The type and authenticity of the source — Is the source primary or secondary? Primary sources are to be given a higher weight. For example, Primary sources like audience interviews and autobiographies are more reliable than secondary ones like magazine articles.
- The veracity of the data — What is the sample size? Does the collected information contain biased data? A simple example would be including the audience that has recently migrated into a new city while collecting data to check the ease of navigating in the city.
- Dashboard mission and audience — Is the mission of the dashboard to maintain a daily schedule for doctors? If yes, do you need the prescription history of a patient while conducting an analysis? This will help in filtering the relevant data and discarding the data that would lead to distraction in creating the UX module.
Acknowledge the limitations
Dashboard designs are to be created after understanding limitations, both, business and technological. Create the most feasible user experience after acknowledging the current atmosphere of challenges. Understand your product beforehand and note all the problems that it can’t currently cater to. It becomes imperative to create a design that effectively portrays the data that is available currently while acknowledging the additional features the dashboard would want to provide in the near future.
Create hierarchies
Once the data is filtered and each role for a dashboard has been identified, understand the importance of each metric for each role based on market research and then create visual hierarchies.
For example: While managing a warehouse staff of 1000 people the head supervisor would want to see the absenteeism rates across months, while a junior supervisor would want to see absentees on an individual level. Furthermore, for a head supervisor, the inventory turnover rate would be the most important metric while for a junior supervisor, the days in hand would be very important.
Group relevant metrics
Once you understand the importance of each metric, create a group of associated metrics. Grouping allows the audience to find the relevant metrics easily and thereby making the dashboard logically consistent.
For example, for a finance dashboard, it is important to group monthly revenue and monthly expenditure together. Furthermore, the addition of filters for these groups will allow the audience to explore the dashboard seamlessly.
Give context to each element
How would a sales manager know whether a sales of $10k for the day is a good performance or not? However, if the sales manager is shown that sales are $10k and have increased by 50% as compared to yesterday, it would be a clear indicator of a great performance.
Each metric has to be supported by contextual elements that provide the audience with a reference to change. Another example would be where the sales manager is shown a bar graph which displays the total sales across days/months.
These were the 6 UX design and research takeaways which empower every designer to create impactful and seamless dashboards.
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