Data collection automation using Python and leave application development at Perusahaan Otomobil Nasional Sdn Bhd

This technical report presents an analytical and development study conducted at the Human Capital Strategy & Effectiveness Department of Perusahaan Otomobil Nasional Sdn Bhd (PROTON). The study focuses on two main operational improvements: automating data collection processes using Python and developing a digital Leave Application using Microsoft Power Apps. Initially, the department managed over one thousand employee data entries manually in Microsoft Excel, which was highly time-consuming. A Python script was developed to automatically transpose, clean, and convert this raw data into a newly structured Excel file. Furthermore, the existing offline leave application process was digitized to improve operational efficiency. A customized application was built using Microsoft Power Apps, integrated with Microsoft Power Automate to enable a dynamic, multi-level approval flow. The results indicate that the Python automation significantly accelerated data processing, while the Leave Application provided a seamless, multi-screen platform for employees to submit requests, check balances, and receive automated PDF approvals. Overall, these implementations successfully modernized the human capital workflows, demonstrating the practical value of programming and business analytics in corporate operations.