Research On JC Company’s New Business Product Line Schedule Optimization Based On Refined Earned Value Analysis

JC Company is an information technology company managed by the Sports Lottery Management Center.In recent years,with the core business of sports lottery becoming stable,JC Company has expanded its sports lottery-related business beyond lottery games,such as compliance audits and business analysis.However,due to fast-changing demands and a lack of effective progress control and management,the development and promotion of the business process management and compliance audit system in the new business product line have caused project delays,affecting the operation of new products.Therefore,this article aims to optimize the progress of JC Company’s new business product line based on the refined earned value analysis method and Bayesian principle.This article determines the project stages where progress risks occur through earned value analysis of historical projects in JC Company’s new product line.Refined earned value analysis is conducted on high-risk stages with progress deviation greater than 0,and the historical earned value progress indicators of the problem stages are combined with the Bayesian formula to calculate the "activity resource probability matrix." Interviews are conducted on high-performance task resources to evaluate whether efficient work methods are present,and the performance indicators in the efficient work methods are compared with the standard performance to determine the threshold and establish the "progress assurance model" to improve subsequent evaluation efficiency.The efficient work methods are recorded in the organizational process asset library.Finally,the methods derived from this study are applied to the development of progress plans,and the basic earned value method indicators before and after optimization are compared.Earned value analysis is conducted on the progress plan after plan execution to ensure that the optimized progress plan has better performance,reduces project progress risks,ensures project quality,and ultimately achieves project goals.The application of the research results in version V23.03.01 shows that by combining the "resource task probability matrix," the resources of three activities have been adjusted,and the probability of high performance has been increased by 4.34% while ensuring that the probability of normal performance is above 90%.Combining the "progress assurance model" has shortened the critical path by three activity nodes.Combining two quantitative models has advanced the progress plan by five days overall,releasing 25person-days of buffer for the development team’s related activities and 10person-days of buffer for the testing team’s related activities,effectively reducing the risk of the progress plan.Compared with the previous version,the number of defects has also decreased by 25%,and the quality has been improved.At the same time,the earned value deviation and performance indicators of the project as a whole have returned to normal.The research method of this article also provides effective reference for other projects in the new business product line when doing progress management.In future research,it is possible to further explore how to combine the refined earned value analysis method with artificial intelligence technology to improve the efficiency and accuracy of project progress management.