Can Benefits Comparison Across Your Organization Be Useful?

Supposing that you came across Levels.fyi webpage on benefits comparison and was struck by how such comparison can be useful internally at your oganization as opposed to comparison between external companies. It can give a broader prospective of compensation in terms of benefits of rewards when an organization operates in more than 50 countries with varying benefits in terms of total value.

The total compensation that one receives typically includes salary, equity and bonus that comes with benefits that has a monetary value attached to it. 

By having such an internal comparison table or data visualization, it helps to evaluate the situation and estimate the value of each country’s total employee compensation. 

How to get started?

To set up something similar to Levels.fyi , you would require data and a suitable tool that can display table and visualize data easily. For data, you can retrieve key information on employee compensation with annual salary and benefits/allowance eligibility per employee with your existing Human Capital Management(HCM) system. In the software industry, typically big organizations would have SAP Successfactors, Workday or Peoplesoft.

Data

Data template woud look like the following below

Tool

Streamlit would be the proposed tool as it is a tool often used by data scientist and works on Python. There are many data visualization libraries that can be used for this purpose and Plotly is recommended. Plotly is a graphing library that works well with maps such as Mapbox. It is easy to display scatter plots in Python with Plotly.

Let’s Get Started

You would need to install python, Streamlit and Plotly. When it is set up , you can then create a page like below that can show some initial introduction followed by a file upload option that would be used to upload the employee benefits data. If you intend to enhance it with maps, then you would need to install Geopy. With Geopy, you can do it to automatically do geocoding and append latitude/longitude coordinates for visualization on Mapbox. Geocoding is supported by the python library , Geopy and it can connect to various geocoding services by e.g Google, OpenStreet and Bing.

The file would look something like this after geocoding.

Benefits visualization across countries

You could try to generate 3 columns that contains the filtered data with a total at the end of it like below. Tbe downside of this method is that you are unable to compare it by benefit or by type.

Alternatively, you can explore the parallel categories diagram in Plotly Express which is a visualizaiton of multidimensional categorical data sets. In this instance, we have the benefit types costs per country. By hovering over a category rectangle(type,benefits,etc), the tooltip display will show the number of benefits that falls under the single trait e.g type. Color can be used to display the costs(Amount).

Besides parallel categories, you can also explore with a strip plot where each row of dataframe is represented as a jittered mark within categories. The x axis ,y axis and facet column can be positioned to display different categories with color coding to categorize the types. In the examples below, you can see the hover data contains all information for each point. Strip plot is useful for one dimensional data in this instance and would not be suitable if that are too many data points and not as useful in a boxplot.

Food for thought after reviewing the dashboard and charts;

1. The insights from total value of benefits across different entities operating in different countries may lead to further streamlining of benefits and allowances granted globally.
2. The insights from the chart of benefits with e.g average median of benefits for Gen Z can help other functions such as recruitment identify which countries would have more talent pool due to the attractive benefits where there are less competing organization with similar benefits.
3. Though it may not be obvious, with Gen Z as the next talent pipeline, organization’s would need to consider updating the benefits plan to include bitcoin for monthly bonuses. It has been reported on Coindesk that SwanBitcoin offers such crypto benefits plan. It is positioned as a saving plan and helps in building a nest egg of Bitcoin.
4. The dashboard and charts can be further enhanced with a map supported by Mapbox. 
5. The usefulness of these data visualization may be challenged internally by your IT or HR team as there would be existing tools in place that can provide such information and requires full integration with your HCM system.