These Are the 5 Characteristics of a Bad Dashboard

A lot has been written about the characteristics of good dashboards, but how do you know if you're dealing with a bad one? Discover the 5 characteristics of a bad dashboard in this blog, and what you can do about it.

1 Doubts about data quality

One of the first characteristics of a bad dashboard is questionable data quality. When there are doubts about the data quality of a dashboard, you can't be sure of the decisions you make based on that data. This is something you see a lot at organizations that work with Excel reports. Copies of original files are often used, resulting in an overgrowth of reports. This problem also occurs when organizations start working with multiple data visualization tools without a proper data warehouse or data management platform. Different departments may use different definitions, resulting in multiple versions of the truth.

The Solution:

A modern data warehouse or data management platform can ensure that all data comes together in one central place where definitions are created and stored. This way, you can easily give multiple tools such as Qlik or Power BI access to the same data while keeping your defined metrics and dimensions intact. At E-mergo we like to work with TimeXtender to build a solid data foundation. With this platform you quickly unlock your data with CData Connectors, automated ETL scripts are written, and you record your definitions in one central layer. From the Hub you push data easily and automatically to multiple analytics tools. See more information about TimeXtender here.

2 There's no steering

The second characteristic of a bad dashboard is when the dashboard isn't used to steer (or adjust course). This problem can have many causes, such as wrong KPIs or too many KPIs. KPIs can be 'wrong' when they aren't SMART (Specific, Measurable, Actionable, Relevant, Timely) or when they aren't well aligned with the goals you want to achieve.

However, showing a lot of SMART KPIs in a dashboard doesn't lead to a good dashboard either. If there's too much to look at, it becomes difficult for users to know what to focus on. A good dashboard should tell a clear story based on the data. By putting the right information in the right place, it should help users achieve the KPIs needed to reach their goals.

The Solution:

In the blog Do your KPIs really measure what you want to know? we discuss how important it is to look closely at your KPIs. For example, we discuss the KPI Tree technique, which lets you easily cascade your KPIs so you can see which factors affect each other. This way you know exactly which KPIs you need to steer on to achieve an overarching goal.

3 Context is missing

The third characteristic of a bad dashboard is a lack of context. Data without context doesn't say all that much yet. If you only look at revenue without a target or a comparison to a previous period, you still don't know how you're doing. Without this kind of context you don't know the whole story, or the data can even be misinterpreted. This makes it difficult to make well-founded decisions about the course you're going to take.

The Solution:

Useful context such as targets, legends, alternate states, and Natural Language Processing (NLP) technologies such as the Insight Bot or Narrative Science ensure you get a more complete picture of the data so you can make better decisions.

4 Wrong data visualizations

The fourth characteristic of a bad dashboard is the use of the wrong data visualizations. This may sound obvious, but we still see this happening far too often in practice. When you use the wrong visualization in your dashboard, it can undo the interpretation of the data. The design of your dashboard, and therefore the choice of data visualizations, should above all be functional.

The Solution:

In this decision chart from Qlik you can easily find which data visualization best fits your data. By choosing the right visualization, you ensure there's no confusion and that data is interpreted correctly. Besides choosing the right data visualization, it's also important not to use too many, to keep things clear. Read the blog '10 Pitfalls of Dashboard Design' for more important points to pay attention to when designing your dashboard.

5 Poor Use of Color

The fifth and final characteristic of a bad dashboard is incorrect or excessive use of color. Color can be used in data visualizations to show differences, emphasize certain information, or show the relationship between information. If used incorrectly, this can create confusion. Think, for example, of a dashboard where colors are used to indicate different categories. If one of the colors of such a category is also used in another data visualization to indicate something else, users might think it refers to that category, potentially leading to incorrect insights.

The Solution:

The use of color can have a big influence on a dashboard. Colors should therefore be used carefully and, above all, consistently. They should also only be used if the colors have a meaning and thereby add something to the dashboard. Finally, it's also important to take color blindness into account; about 10% of men and 1% of women deal with this.

Getting started with a good dashboard

Take a look at the tips and resources below for more information about good dashboards, or get in touch with us to see what we can do for you.

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