Dashboard Design Mistake #1 - Building a one-size-fits-all dashboard

Dashboard Design Mistake #1 - Building a one-size-fits-all dashboard

The one-size-fits-all dashboard is the most common dashboard design mistake. It arises when people begin their dashboard projects by asking “data-centric” questions like:

  • “What data is available?”
  • “What data is important enough to put in the dashboard?”
  • “What are the best ways to visualize each type of data?”

This line of thinking typically yields a dashboard that’s designed around the data, and not around how that data might be used, or who might be using it.

Dashboard Design Mistakes | All departments, one dashboard

At first, it may sound like a good idea: Any data that anyone might need, all in a single display.

In our experience, however, “one-size-fits-all” dashboards usually end up being underused or abandoned within a few weeks.

The problems start to become visible when you consider that the answer to the question “What data is important enough to put on the dashboard?” is usually, “Most of it.”

If your organization is collecting a particular type of data, chances are that someone in the organization is going to be interested in seeing it at some point.

When the actual dashboard-building process begins, the builders will usually find themselves trying to put a very large amount of information onto what now seems like a very small display.

Consequently, the only way to get all that information onto a single dashboard is to add a lot of filters, selectors, tabs, drill-down links and other user controls. This results in only small portions of the data being displayed on the screen at any one time.

Dashboard Design Mistakes | An example of poor design

The one-size-fits nobody Dashboard

It’s not the end of the world, until you start looking at things from the perspective of an individual user.

Because only small parts of the data are visible at a time, a single user will almost certainly need to click a large number of tabs, filters, selectors, drill-downs, etc., in order to see all of the data they need for their particular job.

This could mean five or 10 clicks at best - and maybe even dozens more.

Even five or 10 clicks can be enough to turn off many users, since they need to click through that same sequence over and over again, every time they want check the dashboard.

Even the most dedicated employee is going to get frustrated and end up checking the dashboard less and less often.

Another big problem with one-size-fits-all dashboards is that they show a lot of information to each individual user that’s completely irrelevant to their job.

Does the Vice-President of Sales need to know the page error rate of the website? No, but she’s seeing it every single day because the IT department says that it’s a key performance indicator (KPI).

This visual noise quickly adds up, forcing users to expend a large amount of energy ignoring irrelevant information.

One-size-fits-all dashboard also makes it impossible to apply many basic best practices for dashboard design, such as putting the most important information in the upper-left quadrant of the dashboard, where users tend to look first when using languages that read left-to-right and top-to-bottom.

This is impossible to do when creating a one-size-fits-all dashboard, because what’s most important for the CEO may be completely different from what’s most important for the CTO.

Even users in the same department interested in the same data will need that data displayed differently if they’re doing different jobs.

A marketing manager, for example, may need to see detailed views of specific campaigns and perhaps even individual prospects, whereas the Vice-President of Marketing would benefit from a more aggregated view - and possibly seeing a lot of high-level budget information that’s of little use to the marketing manager.

So what dashboard design steps should you take?

The solution to these issues is to create one dashboard for each role within the target audience. This may sound like a lot of work, but it’s actually easier than trying to cram all of the data that could be of interest to everyone onto a single display.

With a one-dashboard-per-role approach, the need for filters, tabs, selectors, extensive drill-downs is minimized, and it becomes much easier to get all of the relevant information onto a single at-a-glance display.

Here’s how to do it:

Step 1 - Figure out who your dashboards need to service

For example, for the marketing department this might include:

  • the CMO
  • the digital marketer
  • the social media marketer
  • the content marketer

Each role in an organization has very different KPIs and information needs, and each should get its own dashboard.

Step 2 - Start with the more junior roles

It is very tempting to start with the most senior roles (CEO, CMO, CIO, etc.), first but in our experience, it’s almost always faster and easier to start with the more junior roles.

This is because the dashboards for more senior people often contain aggregated versions of the data found on the dashboards for people in more junior roles. So getting the junior-level dashboards sorted out first makes the senior ones much easier to create.

Here are some examples of role based dashboards:

Here is an exception to the one-dashboard-per-role rule.

If you’re creating a dashboard for a common area such as a lobby or conference room, and its purpose is to provide anyone who happens to glance at it some interesting stats, then a different approach must be taken.

It must be understood that such a dashboard is basically eye candy. Employees at their desks will still need role-based dashboard software of their own to help them make rapid, high-quality, data-driven decisions.

In my next post on this topic I’ll drill into Mistake #2: Not adding comparison values or the “so what" problem.


Originally published November 17, 2015, updated Apr, 09 2021

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