Universiti Sains Malaysia (USM) Talent Management Dashboard

In this competitive knowledge-based world, it is vital for management to handle the attrition issue. When employees leave an organization, they bring invaluable tacit knowledge, which is often the source of competitive advantage for the business. For an organization to continually have a higher competitive advantage over its competition, minimizing employee attrition is crucial. Promotion is another issue that the organization must address to keep its employees for the long term. This study aims to develop a talent management dashboard that focuses on the attrition and promotion structures at the USM main campus involving permanent staff only and identify the attrition trend for the upcoming 3 years. A descriptive analysis of these two issues has been performed using the PowerBI platform. The prediction of the attrition trend for the upcoming three years’ model has been developed using time series algorithms. As the dataset is static, the autoregression (AR), Moving Average (MA), and ARIMA models have been developed and evaluated using the Root Mean Square Error (RMSE) score. Based on the result, the ARIMA model has the best performance with an RMSE score of 4.901 compared to other models chosen to represent the attrition trend.