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Powered by Design with Purpose.
Powered by Design with Purpose.
Picture this: it’s the middle of the year, you’re trying to figure out how much work you need to take on for the rest of the year in order to have a real vacation. You open your fancy sales tracking app to figure out how far from your goal you are. The dashboard screen is sleek and balanced.
You can see how much more you’ve sold this year than last year, how many people have visited your online store in the last 3 months, and sales broken down by each quarter, all outlined with beautiful gradients. What you don’t see is the one thing you really want to know - how much money do you still have to make to meet your yearly goal.
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What a beautiful and useless screen. Sure the extra click isn’t the end of the world, but wouldn’t it have been nice to open the app and immediately see something useful to you? This is where the art of the dashboard comes in.
The dashboard’s job is to quickly deliver insights and prompt quick action when needed, all on one single, easy to scan screen. Sounds useful… why doesn’t everything use a dashboard? Great question with a couple answers:
While it’s tempting to create one page to summarize them all, it’s usually unnecessary and therefore gets skipped right over.
If a dashboard is necessary, the next step is to understand what information is important to people and what makes it important. This is going to take a bit of observation and user research. I know it sounds like the answer to everything in design is user research - but that’s because it is! And while every part of good design should involve user research, dashboards are a place that you really shouldn’t skimp on it. Often the information that product designers, developers, and higher ups think is important is just noise to those who are actually using the app.
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A note about qualitative data vs quantitative for dashboards
While analytical data (what sections of the app are most visited within the first minute, how long people are engaged on a single page, etc) can be really informative, to really understand what people want to see, it should be paired with qualitative research like contextual inquiry and interviews. For example, if you see someone is spending a lot of time scrolling back and forth or rage clicking around the dashboard, it could be there’s lag time, they can’t find what they’re looking for, they don’t understand what they see, or everything is there, but it’s not organized in an efficient way. Chatting with people and watching them work will fill in the quantitative dots in order to make the research more actionable.
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Once the key information has been identified and you know how it's being used, the fun can begin! The team will need to decide how to categorize the information and what visualizations will best represent the data. For example, comparing data needs a different visual than tracking one piece of data overtime.
We worked on a redesign for a large coaching application that had a lot of moving parts. From the quantitative and anecdotal data, we could tell people weren’t really using the existing dashboard, but we weren’t sure why.
After completing a series of interviews with frequent users, we found that there were too many things on their dashboard that just weren’t relevant to them after they had been onboarded. Important messages and support tickets got lost at the bottom, and most people didn’t realize that each section could be moved.
In fact, the first thing that we hear to try to solve the “what goes on the dashboard” problem is “we’ll just customize it!”. But the truth is people just don’t want to take the time to mess with moving widgets around, and there often isn’t enough affordance to even indicate that it’s possible. Better to start with good, informed defaults.
In the end, we decided that because the app was task oriented, the dashboard should be more of an action oriented page with upcoming appointments and tasks to complete. Rather than have a persistent place for alerts and system notifications, we decided to use contextual banners to deliver important information. The final screen became less of a traditional dashboard and more of an activity page.
One of our recent projects involved an app that tracked the status of several different formulas at once. The goal was to quickly provide a high level summary of all the different formulations to answer the question: are we good or is something amiss? If everything was good, they could close the app and carry on, if there was something wrong, they should know it the minute they look at the screen. The current dashboard had all the key metrics to make that assessment but it wasn’t getting a lot of traction.
Our team spent a lot of time pouring over quantitative data to try to see how many people were getting to individual formulas from the dashboard, how much time they were spending on the dashboard, and where were they going instead of the dashboard?
We found that although the metrics they wanted were there, they weren’t presented in a useful way. Instead of using the dashboard, users preferred to look at their formulas one by one so they could really dive into three key metrics (we're calling them metric 1, metric 2, and metric 3). To us, this felt too cumbersome. Turns out the customers felt that way too.
After talking to people, we had a workshop with stakeholders and used Figjam to determine priority and nail down visualizations.
Turns out people preferred a good old fashioned graph that allowed them to compare their actual formula against the ideal formula. They weren't using the dashboard because the numbers were meaningless without the extra context.
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This dashboard may look less sexy than a lot of other dashboards, but it was highly effective for the people who needed to scan a lot of data quickly. Getting the right amount of information on the dashboard is just as important as the presentation of it. If there isn't enough context, the dashboard becomes a glorified stepping stone to a detail page. If there’s too much, it becomes noise and people can’t find what they’re looking for.
Before spending the resources on creating a dashboard, ask yourself what problem you’re trying to solve or what task you want to help people complete. If the answer is “to quickly inform customers about or act upon important, relevant data”, start talking to your customers, observe how they work, check out the analytics, and then follow these hot tips:
And most importantly, don’t skip on customer input!! Happy dashing!
