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Implementing best practices in your dashboards

Implementing best practices in your dashboards

The goal of a dashboard is to provide business users with an easy way to gain valuable insight into their business or operation. Instead of pouring over tons of data, reports or pages, the dashboard provides you with a summary that quickly answers your business questions and tracks key metrics.

 

I found this cool dashboard above made with Excel which shows a summary of a company’s sales over a period of time.  This dashboard ties together all the relevant Sales information of the company in one space with interactivity to filter this information by the year filter at the top of the dashboard.

My goal with this post is to review this dashboard to find out if it meets visual best practices and if not, ways it can be improved.

 

WHAT THIS DASHBOARD GETS RIGHT

Layout and style:

It is good practice to divide your dashboard into sections to prevent cramming too much information together. By separating the dashboard into 3 sections, this dashboard makes it easy to navigate. The use of white space also gives a clean feel to the dashboard. The dashboard makes varied use of charts and color that makes it interesting and visually appealing.

To engage an audience, you need the dashboard to have that appeal that would make them stop to take a look at what this dashboard is all about. All charts on the dashboard also have titles that help you to identify the information you are looking at. A consistent font style has been used across the dashboard.

If you want to check this dashboard out because it looks cool, then it has achieved its first purpose but does it communicate the necessary insight or provide you with useful information?

 

WHAT THIS DASHBOARD GETS WRONG

Titles and Logos:

For starters, the Dashboard title is set on the same level as the chart title. It is best practice to make the Dashboard title clear and on its own where possible. The logo doesn’t fit in well and it overlaps the space provided.

Spacing:

The second section is too squished and dying for space. It’s best practice to be consistent with the sizes of the boxes on the dashboard unless in cases where you have large elements that you need to stand out such as maps or large charts.  It’s possible to have an area take up less space if it’s less important.

In other words, by giving more visual weight via sizing, spacing, font, etc. our brain assigns more weight or importance to that thing.  It would be ok if this was more of a drill down or some additional detail but putting the size of the space in the middle of the dashboard doesn’t seem to be a logical flow of what’s important and why a manager should care about it.

Inconsistencies in font sizes:

Some of the charts have a larger font size compared to the others. For example, the Order Quantity comparison and Sales by Product charts have smaller fonts. The dashboard title and other charts use the same font.

It is best practice to make the dashboard title a lot bigger than the rest of the elements on the dashboard to make it stand out.

Inconsistencies in color usage:

The use of color in some charts is inconsistent particularly with the Order Qty Comparison and Sales by Product Category chart. Both use a green color which might make a user think they have some relationship.

This color makes sense when it is used with just the donut chart to set it apart from the other navigational elements of the dashboard.

KPI’s:

It is obvious this dashboard is tracking the Sales of the company year-to-date, but at the same time, the Month has been prefiltered to May. This makes us assume everything on the dashboard is prefiltered to 2015-16 May Sales. For example, we cannot tell what month or years the charts for the Order Qty COGs 000s and Order Quantity Comparison 000s represent but it is clearly not the 2015-16-year period.

Placing the year filter at the top can make a user assume it is a global filter. In situations where filters could be confusing, it is best practice to provide some information on ways to use them and the charts they apply to.

The whole chart becomes confusing just by the Year and Month filter alone. You will expect the year to date monthly total to be just one value. What about the overall Sales? How can we tell what that is at first glance of the dashboard?

The bottom donut charts are KPI’s that should be at the top of the chart so a user can see right away how the Product categories are doing.

 

Flow of information:

There is no logical flow to the information contained on the dashboard which makes it look like a whole bunch of unrelated metrics were thrown together.  What does customer satisfaction have to do with order quantities, customer segments, sales, COGS, regions, etc.

If we could show that sales are down and that’s correlated with negative customer satisfaction and people are unhappy about the following three things, that’s amazing insight.  We know we’ve got to fix some stuff right away to get sales back up.  But if we’re just throwing metrics around, no one takes any action on anything.

Some of the information can be presented on a separate dashboard, so business users can go through them quickly.  For example, a customer satisfaction dashboard might show the overall percentage vs. a target, the change year over year, the biggest drivers of customer satisfaction and dissatisfaction, and the estimated financial impacts or improvements to net promoter score when the things people aren’t happy about is fixed.  But, this wouldn’t include the number of new customers unless customer satisfaction is impacting that somehow.

 

CHOOSING THE RIGHT CHART TYPE

Section 1

In dashboard design, it is important to select charts that are appropriate for your data rather than charts that look pretty and defeats the purpose of your dashboard, i.e. to provide an easy way to read all the data you have on hand.

Sparkline charts:

The left-hand sparkline charts show the trend of the states but without an axis, we don’t know exactly what we’re looking at. Perhaps starting all of them on a common axis and using an action to highlight a state will give a clear way to compare one state to another.

A small multiple chart might also be a great way to show all the trends in one chart for easy comparison. Another approach would be to label the start and end of the line or label just the min/max across the entire table.

Perhaps the simplest approach would be to use an average for the entire table and then show the percentage above or below the average each month. The same changes apply to the bottom left Total Customer chart.

Bar and Pie Chart:

The bar and pie chart represent the same information of Sales by Region. It is best practice to avoid displaying the same information in different chart types to make them look cool. These two can be combined into one chart.

The bar chart would be appropriate and the labels can show the actual numbers and the percentage of the total. The bar charts only show the sales data in the chart without the category labels, which is bad practice.

Section 2

Shape chart:

The shape chart on the left-hand side doesn’t make a lot of sense to use here unless we have a legend that tells us what each shape represents.  There are 30 shapes, 24 black, and 6 greys. The total number of black shapes is supposed to represent 77% of the data but what is the actual number that 100% represents?

Further information provided says customer satisfaction increased by 5%. This can be misleading because without the actual numbers we can’t tell how significant 5% is. If 65% customer satisfaction is good enough, then 77% is great. If 95% satisfaction is the goal, we’re well below target, even though it’s improved by 5%.  Charts without context are often meaningless.

It’ll be appropriate to use a comparison chart that shows us the current vs the previous and then shows us the % change.

Comparison chart:

Right away you’ll notice that the legend doesn’t tell us what the colors represent in the comparison. Is the green the previous period? These colors also compete with the chart below.

Section 3

As mentioned before, the sparklines for the States on the left-hand side could have a common axis with labels to allow easy comparison.

Donut charts:

The donut charts here are wrong to show the part-to-whole relationship. It would be appropriate to use a bar chart to display this. However, since they are KPI’s we could use BAN’s to display them at the top of the chart

Conclusion

At face value, this dashboard looks pretty, but does it serve the purpose for which it was created? A Sales dashboard should tell a user right away what the Overall Sales or current Sales figures are. This dashboard fails to present this basic information.

It overcomplicated the analysis by trying to make the charts fancy and cool. The best dashboard is the simplest one to understand. Check out my next blog post for the makeover for this chart.