Effective resource allocation is a critical component of successful project management. This paper explores the application of Analysis of Variance (ANOVA) techniques to optimize resource distribution across various project tasks. Traditional resource allocation methods often fail to account for the variability and specific needs of different project activities, leading to inefficiencies and potential project delays. The objective of this study is to demonstrate how ANOVA can be utilized to identify significant differences in resource requirements among project tasks, thus informing more precise allocation decisions. The methodology involves collecting detailed resource usage data from a series of past projects, including time, labor, and material costs associated with various activities. This data is subjected to ANOVA to analyze the variance in resource consumption across different tasks. By identifying which activities significantly deviate in their resource needs, project managers can allocate resources more effectively. Results indicate that ANOVA can pinpoint discrepancies in resource usage that traditional methods overlook, leading to more balanced and efficient resource distribution. This approach not only enhances resource utilization but also reduces overall project costs and improves timelines. The conclusion underscores the importance of incorporating ANOVA into project management practices. By leveraging statistical techniques, managers can make data-driven decisions that enhance resource efficiency, optimize costs, and ultimately improve project performance. This paper advocates for broader adoption of ANOVA in project management to achieve these benefits.

ANOVA, Resource Allocation, Project Management, Optimization Techniques, Variance Analysis, Data-Driven Decision Making, Resource Efficiency, Project Performance