How (not) to provide valuable steering information to your organization: 8 common dashboarding mistakes

Are your dashboards effective or counterproductive? Here are 8 common dashboarding mistakes that render your dashboarding efforts useless.

Who doesn’t like a well organized data dashboard? It’s easy on the eyes, and it seems very efficient. After all, a dashboard provides decision-makers in your organization with at-a-glance steering information. But does it, really?

The truth is, many dashboards aren’t as effective as they should be. Common pitfalls include an inappropriate foundation for decision-making (some data is simply not suitable) and a giant waste of development time and effort. When stretched to extremes, such aspects can even render dashboards counterproductive.

In this blog post, we’ll discuss eight common mistakes people make when creating dashboards — so you can avoid them.

1. A focus on (the wrong) details

Often, the metrics on a dashboard’s front page aren’t very relevant. By including such off-topic details, you’ll encourage decision-makers to focus on the wrong things. If you want to prevent this from happening, involve decision-makers in your dashboard creation process. Together, you can decide which metrics reflect performance and are therefore important to display.

2. An overload of metrics

Less is more. We’ve seen organizations include tens of pages full of not-so-relevant management information. The result: finding key insights is like looking for a needle in a haystack. It also takes a lot of effort to maintain the dashboard. So, pick your metrics wisely!

3. The ‘dashboard creation reflex’

Whenever you encounter a performance-related question, your inner voice might scream, “Dashboard!” But do you really need one? Sometimes you should ignore your reflex response. One-time insights often require a one-time data analysis. Only if a question returns at certain intervals, a dashboard can be a viable, sustainable solution.

4. The static dashboard

We live in a dynamic world. With changes happening around us all the time, you should constantly reconsider which metrics are important. Use your findings to update your dashboards: delete insights that are no longer relevant, and only create new dashboards if your organization really needs them.

5. No data cleaning efforts

Sure, your dashboard looks impressive. But have you checked (and double-checked) that all your data is correct? Without the necessary data cleaning, you’ll have a deceivingly great-looking dashboard that spurs decision-makers to draw conclusions based on faulty or incomplete data. So make sure to clean things up first.

6. A lack of ownership

A dashboard can’t ‘float around’ freely. It needs an owner (perhaps the person who created it) who is responsible for keeping it up to date and answers decision-makers’ dashboard-related questions. The dashboard owner should regularly check databases and systems — if these change, so should your dashboard connections (provided the information you include is still relevant!). This way, you’ll avoid errors and misinformation.

7. Assumptions about users’ interpretation skills

Those who create dashboards often assume users will correctly interpret the information shared. But even though your well-thought-out charts might seem extremely logical to you, not everyone will immediately get the gist of them. It’s paramount that you properly explain every single element you include. If you show numbers, make sure to elaborate them.

8. No single source of truth

If your organization uses multiple dashboards, make sure you display consistent information. Often, dashboard creators don’t use a single source of truth, which results in misinformation. This, in turn, leads people to abandon dashboards altogether because they don’t know what to believe. One tiny miscalculation is sometimes enough for your entire dashboard strategy to fail. So, consistency is key!

Successful dashboarding requires context

 A final note: however visually pleasing your dashboard, it rarely tells people everything they need to know. When interpreting metrics, make sure you always consider all relevant contextual information. Only then, you’ll have accurate insight into your organization’s performance.