Forecasting Performance: Leveraging Machine Learning on Earned Value Data for Proactive Control
Year: 2025
Type: article
Abstract: This study investigates the utilisation of machine learning methodologies in the context of earned value management (EVM) data, aiming for the anticipatory prediction and regulation of project outcomes. This research seeks to utilise machine learning frameworks, including regression analysis, decision trees, and neural networks, to forecast upcoming project outcomes, pinpoint possible risks, and improve the decision-making process. The study illustrates how the incorporation of sophisticated algorithms alongside conventional EVM data can yield enhanced, immediate insights into cost and schedule effectiveness. The document further explores the ramifications of this methodology for project leaders, providing a comprehensive structure for enhancing project oversight and regulation via insights derived from data.
Author: Rohit Shinde
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W6968464101
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