{"id":5313,"date":"2019-09-04T10:52:52","date_gmt":"2019-09-04T14:52:52","guid":{"rendered":"https:\/\/www.ceros.com\/inspire\/?p=5313"},"modified":"2021-03-10T11:47:48","modified_gmt":"2021-03-10T16:47:48","slug":"5-tips-for-building-the-perfect-dashboard","status":"publish","type":"post","link":"https:\/\/www.ceros.com\/inspire\/originals\/5-tips-for-building-the-perfect-dashboard\/","title":{"rendered":"5 Tips for Building the Perfect Dashboard"},"content":{"rendered":"Reading Time: <\/span> 7<\/span> minutes<\/span><\/span>\n

While it\u2019s true that every set of data is unique, the dashboard\u2014which lets you present all the important, actionable data in a single view\u2014ought to be so easily understood that it\u2019s almost invisible. And, as it turns out, there aren\u2019t as many ways to do that as you might think. Take it from the blogger SeattleDataGuy<\/a>, who worked for a successful business which sold dashboards and insights to other companies. \u201cWe only had four dashboard products,” he says. “That was it, and yet, this company has existed for over a decade.\u201d <\/p>\n\n\n\n

Of course, there is a right way and a wrong way to build a data dashboard. And because of that, the design work that goes into creating one needs to follow the limitations of data visualization. Carly Fiorina, former CEO of Hewlett-Packard, once said: \u201cThe goal is to turn data into information, and information into insight.\u201d Here are some best practices to make sure that you\u2019re getting your dashboard design down to a science. <\/p>\n\n\n\n

1# Know Why The Dashboard Exists <\/h2>\n\n\n\n

The most important step of designing an effective dashboard is knowing why you\u2019re doing it in the first place. Dashboards are created with a wide range of purposes in mind\u2014some are meant to aid in immediate decision-making, others are intended to track long terms goals. Here are a few examples of how data can be arranged and visualized depending on the specific purpose and user.<\/p>\n\n\n\n

Operational Dashboard<\/strong><\/p>\n\n\n\n

Operational dashboards are designed to help users as they complete time-sensitive tasks and often highlight deviations in data while visualizing potential resources. <\/p>\n\n\n\n

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In this web analytics dashboard, designed by Jan Losert<\/a>, the operational data that\u2019s emphasized includes a bar graph of daily visitors, real-time users, total site visits, bounce rate, visit duration, top 5 pages, and a social-media breakdown. In just a single view, a user gets an overview of the status quo while being able to glean where changes could be made to improve site traffic. <\/p>\n\n\n\n

Strategic Dashboard<\/strong><\/p>\n\n\n\n

A strategic dashboard takes a long view of the data, and is organized around top-line KPIs and benchmarks that can be monitored by everyone from top executives to executive assistants. <\/p>\n\n\n\n

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Analytical Dashboard<\/strong><\/p>\n\n\n\n

An analytical dashboard is often the domain of a business analyst or an in-house expert. Like a strategic dashboard, this requires a much larger data set, and is intended for long-term thinking. Using insights gleaned from historical data, users are often able to take a look at various future scenarios, testing theories through various models. <\/p>\n\n\n\n

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This example of Zoho\u2019s Google AdWords dashboard<\/a> gives you a sense of time (monthly performance) as well as scale: You can click on any point to drill down to further insights about the data.<\/p>\n\n\n\n

2# Own the First 200 Milliseconds<\/h2>\n\n\n\n

There are certain properties of visual perception that all good design is based around, and dashboards are no exception. Preattentive processing, the human experience of taking in the visual environment, can happen even when the mind is barely conscious of what it is doing\u2014in the first 200 to 500 milliseconds of seeing something. The best dashboards play to these particular strengths of human cognition.<\/p>\n\n\n\n

The Nielsen Norman Group<\/a> published a test to see how preattentive processing works. Without much work, you should quickly be able to deduce which line in the following diagram is longest: <\/p>\n\n\n\n

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Our natural proficiency at determining length is one reason that bar graphs are so effective on a dashboard. We can instinctively grasp the length of each bar in comparison with its neighbors. Other preattentive markers include the area of an item, its angle and 2D position, which is why any kind of 2D graph\u2014including a scatter plot on a linear graph\u2014is a staple of the dashboard, too.<\/p>\n\n\n\n

But when it comes to size, 3D representation, and color, things can be a bit trickier for the mind to immediately grasp. For example, we might be able to tell that a large rectangle is bigger than a small one, but how much bigger is difficult to determine. This is why pie charts, radars, and gauges take longer for the mind to process. They all rely on the eye to be able to compare area, as in this example from uplabs<\/a>, which uses a donut chart in order to distinguish between mobile, laptop, and desktop users. <\/p>\n\n\n\n

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The relationship between the blue, purple, and green stripes on the donut take a little more time for the human eye to figure out than if they were in a bar graph. <\/p>\n\n\n\n

Final note on color: While color is a great way to create distinctions, it\u2019s important to remember that 4.5% of the general population is colorblind. What\u2019s more, it\u2019s not always visually apparent which color might have a higher value than another, so avoid using it in any quantitative capacity. For example, try to stay away from using green to display an increasing number and red to show a decreasing number. It can be a little confusing on first glance. <\/p>\n\n\n\n

3# Work within spatial limitations<\/h2>\n\n\n\n

Getting all operational data into a single view can be a challenge, but working within that constraint can result in brilliant visualizations,and surprisingly intuitive combinations of metrics. Just make sure that while you simplify information and summarize, you\u2019re still providing the necessary insight needed for difficult decision-making. Here are some principles to keep in mind:<\/p>\n\n\n\n