Dashboard Gallery:
Sales and Returns Analysis

 

In this Retail Example we analyze the Sales and Return data in a fictional Bicycle retailer. As returned goods are expensive to process and stock that can not be turned into a sell immediately, not controlling this process can impact profitability very fast. Understanding and analyzing  the underlying factors is a key driver for bottom line profits.

Sales Detail overview, KPIs and Details.

The first page shows an overview of sales data, the four main KPI shown on the top line. Explained with exact numbers in the table below. We can see that a lot of these numbers are in the deep red.

The Graphs below show Sales ($) and % Contribution as well as Units Sold and % Contribution. So where are we loosing money.

Returns Analysis

The second page allows us to dive deeper into the Return Process. A map shows us the countries with the highest return rates (UK and Germany), this is detailed in the Table below.

The Sankey Chart now allows us to connect Returned Goods and Return Reasons. Filtering Down we can find the key manufacturers and reasons for returns. This then can be used to work on these topics and improve bottom line profitability. This is also an example of using Model Mapping to sync data from the Sales data model to the Returns data model.

If you have questions about this Dashboard, please let us know in a comment below.