The article introduces a new way to assess employee performance using a modified decision tree algorithm. The researchers improved upon the original algorithm by using Taneja entropy instead of Shannon entropy, resulting in a simpler and more efficient tree structure. By selecting the most important attribute for each step, they were able to create a smaller tree with fewer nodes and branches. This approach was tested on a dataset of university employees and showed that the modified algorithm can accurately predict performance with less complexity.