Organizations depend on different formats of reporting to gain some visibility into the large amount of data that is collected every day. A well-designed dashboard can provide relevant data, leading to effective decision-making. On the other hand, basing decisions on incorrectly presented data can lead to disaster. It is important to ensure that your dashboard presents data in a relevant, concise, and well-thought out manner, and is not just a collection of visual representations of a spreadsheet.
A common problem with dashboard design arises when trying to fit a lot of data into one view, to provide a comprehensive picture for the viewers. While there are some incidences when this works, dashboards that display too many metrics and provide too little information are a common result.
Why is too much data such a bad thing?
There are a number of reasons why showing too much on your dashboard can be detrimental:
- Sensory overload - Dashboards are visual. With many metrics displayed on the dashboard at once, viewers need to figure out what they're seeing.
- Obfuscated focus - Dashboards display key metrics front and center. Too many peripheral metrics on a dashboard can confuse the message.
- Slow performance - Dashboards extract data from data repositories. More data being loaded equates to longer wait times for your users.
- Cramped real-estate - Dashboards are single page displays. The more visualizations you add to the page, the less space each visualization has to display critical information.
So what do I do?
While reducing the number of visualizations on your dashboard reduces clutter and achieves greater focus, displaying context for your key metrics is invaluable to how the data is interpreted. The goal is to highlight key metrics using appropriate visualizations, and support those with additional context, in the form of drill-downs, pop-ups, and other techniques.
Some ways to avoid clutter while maintaining context are provided below. Not all of these techniques will be applicable in every situation, but they provide a good starting point.
- Use appropriate visualizations - Different visualizations convey different messages, even with the same data – make sure your selected visuals accurately (and effectively) relay the correct message. Specific examples include:
1. trend line charts and categorical bar charts – implicit continuity
2. scorecards versus data tables – provide additional context information using colors
3. traffic light indicators versus numeric displays – threshold values defined
4. bullet graphs versus radial gauges – increased real estate optimization
- Leverage interactions to provide context-specific data - Interactive dashboards help alleviate the need to cram a lot of visuals into a small area by allowing dashboard viewers to view additional information on the fly. Specific examples include:
- Organize metrics into multiple dashboard views - Creating a different view for each audience will help to keep metrics focused to what is relevant to each group.
Effective dashboard design takes practice.
While data is integral to any dashboard, the goal should not be to cram as much data as possible into a single page. Piecemeal dashboards showing too many – often unrelated – metrics cause confusion and can lead to wrong decisions. If you design your dashboard to solve a specific business problem, you will end up with more relevant metrics which will in turn lead to more informed decisions.
Data visualization expertise – knowing how to choose key metrics and the correct visualizations for this data – will result in dashboards that are both easy to understand and effective. So the next time you design a dashboard, keep this lesson in mind: Less is More. Minimalist dashboards are very effective because they deliver a clear message: These are your important metrics. The use of drill-downs, tooltips and pop-ups will provide the context. Efficient design will guide the user through the workflow of the dashboard to arrive at the information they need.