Not everything that counts can be counted, and not everything that can be counted counts.
-reads the sign in Albert Einstein’s office at Princeton.
Early in my career, I worked in the art department of a newspaper and was lucky enough to be mentored in the art of creating effective charts. The main goal was to ensure the chart type chosen was effective in communicating the data, not obscuring it, and to ensure the reader could see the “story” of the data quickly. The same rules apply in creating dashboards.
I had the good fortune to work with GoodData very recently. This company helps convert big data into profitable insights and strategies for business executives by offering a disruptive cloud-based enterprise business intelligence platform. We collaborated to show how effective investigation and counsel when envisioning a dashboard will give the executive more actionable information. In newspaper vernacular, it tells a story.
For example, in a request for a dashboard to show the volume of Support Calls within a group, a basic chart would look like this below.
Chart by GoodData
At first glance, it looks like Janice is not working up to par with her colleagues. However, let’s look at the same information in a different way.
Chart by GoodData
Notice that instead of a single color bar chart, it is now a stacked, colored bar chart. A time element was also introduced. The stacked bar chart quickly shows that a major product issue cropped up this week. And in fact Janice is not avoiding work. She doesn’t work on product calls, but her colleagues do. There is an issue that must be dealt with by management.
This illustration shows how by not choosing the proper report attributes and chart type, you can obscure the information that would be most meaningful and actionable to you, your staff and the business. Below are 5 best practices we at Bluewolf and GoodData counsel when we approach dashboard creation.
Albert Einstein had good reason to like the quote above. Data can be misleading, and you don’t want to be led to the wrong conclusions.
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