Dashboards can contain data visualizations that are either qualitative in nature such as behavioral patterns across populations, or quantitative such as crime statistics.
Dashboards can contain data visualizations that are either qualitative in nature such as behavioral patterns across populations, or quantitative such as crime statistics (see https://www.police.uk/metropolitan/E05000631/crime/)
Now when it comes to meassuring the effectiveness of dashboards the yard stick that should be used should be the speed and accuracy with which users can
- draw conclusions, and
- identify specific patterns
Questions that can guide the answers to these three points are:
- How easy is it to compare two or more bits of information with each other at once?
- How fast can information be compared?
- How fast can insights be generated?
- How relevant is each piece of information provided?
- How relevant are the new insights, or knowledge?
- How fast can insights be understood?
- How easy and how fast is it to see and perceive the information?
- What insights are taken away from the comparison?
- What does the reader of this information know, what he or she did not know before?
- How does it help the reader to have this information at hand?
- What are patterns that are of importance?
What role does the designer take in this?
Designers make it so that the raw data is visualized in such a way that it can be understood within the limitations of human cognition. Designers make it so that the readers that consume the condensed information are capable of immediately determining the most important information.