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In Part 1 of the  Data Visualization series, we talked about various charts supported in SAP SuccessFactors People Analytics Report Stories. In this blog post, we would try to cover the Comparison Charts, its application, and best practices in details

Before we proceed let’s define an example organization “BestRun Pvt Ltd” and various individuals in the organizations. We would be using this organization in reference for later blog posts in the series as well


Best Run Pvt Ltd is a large global multinational headquartered in the United States. Let’s look at part of its HR Organization Structure which we would be using to demonstrate use cases for the charts

Best Run Pvt Ltd Org Chart

Comparison Charts

It is used for comparing multiple variables in a data set or multiple categories in a single variable. Following charts are categorized as comparison charts in Report Stories

Category Chart
Comparison Column Chart
Bar Chart
Stacked Bar Chart / Column Chart
Combination Column & Line
Combination Stacked Column & Line

Comparison Chart SAC

Let’s look at some of the best practices while using various comparison charts

Column Chart

  • One of the most frequently used charts is a column chart. Values of measures are represented as vertical bars

  • They are ideal for comparing values when we have fewer categories

  • When using time as a dimension, better to go for column charts rather than a bar chart

  • In the case of dimensions like Time, Age, Generation, etc better to arrange the categories in their natural order

  • Eg:- Steve, Global CHRO wishes to compare the distribution of employees across employee group for a given year

Bar Chart

  • They are ideal for comparing values when we have a large number of categories

  • In case the dimension labels are longer bar charts are much suited for readability

  • Eg:- Eugene, VP, Recruitment & Onboarding wishes to compare the performance of all the recruiters in his team on the parameter of positions filled

Stacked Bar/Column Chart

  • They are meant for comparison of the total across categories and look at the distribution of each category

  • It is important to ensure the color-coding range for each category is distinguishable to not confuse among distribution

  • Eg:- Shelly, HR Head, APAC wishes to compare APAC headcount across the last four quarters with the breakdown in terms of gender

Waterfall Chart

  • Waterfall charts are very similar to a stacked column chart but used for understanding how the starting point and ending point have changed over a time frame with the stacked components showing increase or decrease.

  • Waterfall chart to be used when you want to show the positive and negative changes that a measure goes through according to a dimension.

  • Eg:- Kirk, HR Head, Europe wants to see how Headcount has changed over the last 5 years. Another example could be Headcount seen as the breakdown of Start of Period Headcount + Hires+ Movements In – Movements Out – Terminations.

Combination of Column & Line chart

  • This should be used cautiously as we are bringing more than one measure with primary measure across column chart and secondary over line chart.

  • Ideally, this is used when we wish to demonstrate how 2 measures have changed across the time periods.

  • Eg:- Kirk, HR Head, Europe wishes to look at the change in average headcount for European regions across months with changes in Hires and Terminations for the year 2016.

Combination of Stacked Column & Line

  • A combination stacked column and line chart should be used in a scenario when the goal is to show trends as well as a breakdown of a measure in relation to a dimension.

  • It should be used very selectively and cautiously as we are introducing 3 aspects for viewers that can act as too much of a visual load – a comparison across primary measure, distribution of primary measure, and comparison across the secondary measure.

  • Eg:-  Shelly, HR Head, APAC wants to have APAC Headcount across column chart breakdown in terms of Gender and also have quick diversity ratio numbers as well.

You can also refer to the official SAP Analytics Cloud Reference chart type guide.

Will adding a chart be good enough to communicate effectively?

The answer depends on what the report creator is wishing to communicate. Let’s take more nuanced comparison use cases and demonstrate how we can use a comparison chart much effectively using additional aspects like conditional formatting and reference lines to communicate our message more succinctly.

Let’s now look at Eugene’s use case of comparing the Performance of its Recruitment team with additional asks from Eugene.

Case 1: Eugene wishes to compare the performance of its recruitment team in terms of positions closed.

Case 2: Eugene wishes to compare the performance of its team on positions filled but also wishes to know automatically who are the best and worst performers of the team (Automatic Color Coding).

Case 3: Eugene wishes to compare the performance of the team with respect to the common individual target it had set for everyone (Adding Reference Lines).

Case 4: Eugene wishes to compare the team performance w.r.t to the minimum and maximum targets that he had been set for the team members (Adding Reference Lines).

Case 5: Eugene had hired a promising candidate Sandra last year and wishes to see how she had performed with respect to her peers this year (Color Coding Individual Bars).

For each of the different use cases mentioned above, we used additional aspects over base charts to communicate more effectively.

For details refer to the following SAP Analytics Cloud Visual Thresholds Reference Lines.

Hope this helps you in getting closer to get near to the perfect comparison chart in People Analytics Report Stories.

In the next blog post, we would cover Trend Charts in more detail.