Design and development of a Variance Analysis model on an EPM solution to support the periodic analysis of industrial performance in a manufacturing context

Management control is a key function to ensure that business activities are aligned with strategic goals and that performance is continuously monitored and improved. Within this framework, variance analysis stands out as a fundamental analytical tool used to compare actual results against planned targets. Far from being a mere accounting exercise, it serves as a diagnostic mechanism to uncover the root causes of deviations, support accountability, and guide corrective actions based on data-driven insights. This thesis investigates how the design and implementation of a variance analysis model within an Enterprise Performance Management (EPM) system can strengthen the periodic evaluation of industrial performance. By standardizing data flows and automating reporting and calculation processes, this software solution enhances the accuracy, efficiency, and timeliness of performance reviews. The value of this approach is demonstrated through a case study from a manufacturing company, highlighting the improvements achieved in monitoring and decision-making processes.