When using dashboards, numerical
measurements are usually the most common statistics gathered by a company. As obvious as this statement sounds, it is actually quite significant. Though
measures can comprise many seemingly useful figures such as sales, many of these have no significance other than to show what has already happened at a
specific point in time. While there are many situations where managers need to know specific statistics, measures are most useful when used to find trends
in data. Coincidentally, finding trends easily is one of the functions which Target Dashboard was designed for, and as such allows users to create charts
which clearly show trends and measurements.
However, while one type of chart may be useful for showing trends, it may not be as effective at showing measures, and vice versa. This article will shed
some light on the most appropriate charts for effectively showing measurements and trends individually.
Measures
As mentioned in a previous post on measures vs. targets, measures are defined as any value linked to the performance of a process, be that process
quantitative (i.e. sales performance) or directional (i.e. no. of employees ill each month). Usually, multiple measures will be recorded at regular
intervals, which then have to be communicated in the form of a chart for easy deliberation, often against a target value, which a company might set as a
goal for that metric. For example, a company might want a certain number of people to visit their website each month, as a means of gauging consumer
interest in their product. The actual measure of this figure will then be compared to the target. To do this, there are a few options to choose from which
are more effective depending on the kind of measurement you wish to show.
1. Gauge
If you wish to display only one month’s measure and target, this can be done via a gauge, which essentially displays if the company has hit their goal for
that month or not. While this can be useful for showing a company’s current strength and ability to hit targets, it is only indicative of that particular
period of time, and ineffective for finding trends in data (to be discussed later).

2. Column Chart
In this case, if the user was trying to show the website hits for each consecutive month, a column chart is in my opinion the most effective way to
communicate this. It may not be the flashiest chart around, but it has the best clarity.

Column charts also benefit a lot from having the numerical values of each column displayed, as this gives both a visual and textual component to the chart.
However, what you should watch out for is putting too many bars on the same chart, as this can clutter it up and make it harder to read.
Another point to note is that column charts are often difficult to interpret by themselves, but become incredibly useful when used in conjunction with a
target line. This not only allows you to see if each measure has hit its target, but can also point towards trends.
3. 3-D Column Chart

Some managers might be tempted to add an extra dimension to their presentations (literally!). But, because the entire chart is slanted to give a solid
look, it is often difficult to see the exact values of measurements in this way. While 3D charts can be effective for their visual impact, they are not the
best option for showing hard numbers. It’s best to stick with 2-D column charts, in my view.
Trends
While the gauge is only really effective for taking a ‘snapshot’ of a company’s performance at a single moment, the column chart clearly shows the
relationship between each month’s metrics and targets. A target line added to a column chart also gives an immediate picture of how the company is
progressing. This progress is far more useful to managers than the gauge’s single target status, as that target could not take into account, say, an
overall fall in visitors from the previous months. That would make that month’s measure warrant action, even while the gauge states that the target was
met. Conversely, a target not met from a gauge’s perspective may not take into account a steady rise in visitors, which would make that month a success
despite the target not being reached.
However, column charts also require viewers to spend more time scrutinising for trends in data. Therefore, a chart which shows a clear path through time is
required.
1. Line Charts and Area Charts
Line graphs are far more useful for analysing trends than column charts, because whereas the tops of the columns are spaced apart and broken (requiring
more time for viewers to process), a line graph draws a direct timeline for a measure. This line can be easily followed by the viewer.

Yet, while this line may be easy to follow if there are large fluctuations from month to month, a data set with a comparatively small variance might mean
that finer trends are missed by following the line alone. To remedy this, the minimum value on the Y-axis can be changed to stretch the graph out, or the
intervals made smaller to give a more exaggerated line.
2. Area Charts
To make trends even clearer to see, the space under the line can be filled in, giving an area chart. The contrast between the colour of the chart and the
white background makes the chart easier to read without detailed scrutiny.

Also, since this example doesn’t require individual numerical measures to be shown, converting the area chart to 3-D actually makes the chart more visually
striking without removing much of the detail.
3. Combining Charts and Chart types
While Area charts are very useful for showing the progress of one measurement, care must be taken when creating area charts for multiple measures. For
example, our company might want to chart website visits and online sales figures on the same chart to find trends in the two measures. For this, an area
chart might get messy if the two lines regularly cross each other. For this, multiple line graphs with different colours for each line are easier to read.

However, if your data doesn’t clash too much (you can create a line graph to check this first), an area graph or 3-D area graph with contrasting colours
for each section might be ideal.

Choose the Right Visualisation depending on your KPI
As discussed previously, Measures come in quantitative and directional varieties, from which different Trends can be found. However, these are not all best
represented by one universal chart type. For different measure and trend requirements, you can see that each variation benefits most from a different chart
type, as data can be made easier to read through a simple change in visual representation. To learn more, please take a look at our Guide to Dashboard Best Practice, which has more ideas and
examples to make your dashboards more effective.