This week, our team has faced the challenge of analyzing superannuation data. Although I initially found learning about space to be intense, I soon realized that working with this complex data was an even greater challenge! Given the tight deadline of only 6 hours, I chose to narrow my focus and examine one particular superannuation fund – an outlier in the dataset.

To provide context for the data about this fund, I decided to compare it to other funds. I also selected a specific time period to further narrow down the focus of my dashboard. Using an Alteryx workflow, I was able to prepare the dataset for analysis.

One of the tables in the dataset contained information similar to a balance sheet. Although I am not an expert in financial performance indicators of superannuation funds, I decided to focus on the debt ratio and debt to equity ratio. Upon calculating the debt ratio, I found that one outlier stood out – the superannuation fund that I ultimately chose to focus my dashboard on.

To create the dashboard, I decided to make a portfolio for CommInsurance. Using the following dashboard, I was able to present my findings in a clear and visually appealing way:

Link: https://public.tableau.com/views/DashboardweekDay2-AppaSuperannuationFunds/Dashboard2?:language=en-US&publish=yes&:display_count=n&:origin=viz_share_link

There are several important areas on this dashboard that are worth highlighting, including:

  1. Key performance indicators (KPIs) that showcase the average debt ratio of the fund versus that of the outlier. These ratios can be quite telling when it comes to evaluating the fund’s overall financial health and stability.
  2. Additional text has been added to the dashboard to help explain the various topics and how the ratios were achieved. This is particularly helpful for those who may not be as familiar with the world of finance and investing.
  3. The dashboard also provides information on the number of new members who have joined the fund, as well as the gender distribution of the current members. Users can select which measure they would like to be shown on the dashboard depending on their specific needs and interests.
  4. Another important area of the dashboard is the distribution of age among the members of the fund. This can provide valuable insights into the demographics of the fund’s members and help fund managers make informed decisions about investment strategies and other important issues.
  5. Users can also set actions on the dashboard, such as selecting a specific fund to see the age distribution highlighted. This can be a helpful tool for those who are looking to make more informed investment decisions based on specific criteria.

In addition to these key areas, there are several other important factors that could be added to the dashboard with more time and resources, such as:

  • Comparing equity to debt of superannuation funds, which can provide important insights into the fund’s overall financial health and stability.
  • Looking at cashflows and liquidity of funds, which can help fund managers make more informed decisions about investment strategies and other important issues.
  • Examining investments return and asset allocation, which are commonly used by superannuation fund managers and analysts to evaluate the fund’s financial health, investment performance, and efficiency. By monitoring these indicators over time, fund managers can identify areas where the fund is performing well and areas where improvements can be made.

Overall, there are many important areas to consider when evaluating the financial health and stability of a superannuation fund, and this dashboard provides valuable insights and tools to help fund managers and analysts make more informed decisions about investment strategies and other important issues.

The process of analyzing superannuation data was challenging, but through careful focus and analysis, I was able to produce a meaningful and useful dashboard for CommInsurance.

Veronika Varaksina
Author: Veronika Varaksina

Meet Veronika, a dynamic and adaptable individual with a diverse background in economics, accounting, finance, and data analytics. Veronika pursued a Bachelor’s degree in Economics and gained valuable experience in financial analysis, budgeting, and forecasting while working for five years in accounting and finance. However, she soon realized her passion for data analytics and decided to pursue a postgraduate degree in Analytics at Victoria University. Throughout her academic journey, Veronika honed her skills in data visualization, statistical modeling, and machine learning. Her expertise earned her a spot in the highly competitive Data School program, where she further continues to expand her skills in data analysis.