Práctica empresarial mejoras para el área de T&M (Training and Mentoring) en GPVCM (Global Pharmacovigilance Case Management)

Abstract

This report details the activities carried out during the business internship at Merck Sharp Dohme (MSD), focusing on process improvement through the application of agile methodologies and data science to administrative processes in the T&M area. Challenges related to data and process management were addressed, such as conducting a comprehensive statistical study with training and quality data, reviewing the tasks performed and identifying those with improvement opportunities, using machine learning models for decision-making, utilizing tools like Visual Studio Code, Python, Jupyter Notebooks, Excel, and necessary libraries for data analysis such as: Numpy, Pandas, Matplotlib, and Scikit-learn. The result was a notable improvement in the optimization of time in administrative tasks, standardization in the number of training days for new employees and those who want to extend their skills, identification of the training type issues according to the environment, finding the trends of the most common findings according to the training environment type, and thus focusing the training to improve quality