The thinking behind BioPharma Dive’s CEO compensation charts

Data gathering and analysis

BioPharma Dive compiled a list of 231 publicly traded biotech and pharmaceutical companies based on companies included in the SPDR S&P Biotech exchange traded fund, the iShares Nasdaq Biotechnology Index, and several large multinational pharmaceutical companies.

  1. The non-linear relationship between CEO and median employee compensation, and call attention to companies with particularly small or large CEO to median employee compensation ratios
  2. The small number of female CEOs and any differences in compensation by gender

Data visualization

I created an interactive data visualization for each of the three insights. The overall design goal was to communicate the insight while also allowing for exploration of individual data points. I allowed for this level of granularity because I anticipated readers wanting information on specific companies (e.g. their competitors, outliers in the data). Therefore, I included several interactive elements: a search bar to search for company names, filters for company size, and mouse-over tooltips on individual data points.

Visualization 1: Histogram

Design goal

Show the wide range of CEO and median employee compensation and emphasize several outliers

Design solution

A histogram is a great way to show a variable’s distribution. Right away, you can see that CEO compensation has a right tail (or a positive skew), while median employee compensation is more normally distributed. Both have several large outliers, which are also easily identifiable.

Visualization 2: Scatter plot

Design goal

Show the ratios between CEO and median employee compensation and highlight companies with particularly small or large ratios

Design solution

A scatter plot is one of the best ways to visualize the relationship between two variables. A linear relationship is easily recognizable by dots positioned along a slope, while a non-linear relationship is noticeable in its lack of a defined slope — which is what we have in this chart.

Visualization 3: Bar chart

Design goal

Show the small number of female CEOs in our dataset and shed light on differences in male vs. female CEO compensation

Design solution

A simple way to visualize gender differences would have been through summary statistics: the share and average compensation of male vs. female CEOs. However, calculating the average compensation was a bit dubious because there were so few female CEOs (N=20) compared to male CEOs (N=211).

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