The results of cycle time prediction, analysis, and modeling can support various management activities, such as internal due date assignment, output projection, job sequencing and scheduling, competitiveness enhancement, customer relationship management, human resource management, and supply chain management. This chapter describes how to apply the results of cycle time prediction, analysis, and modeling to these management activities. Two management activities are especially focused on: internal due date assignment and output projection. Internal due date assignment refers to determining the date on which the manufacturing system can complete and deliver a potential order. The internal due date of a potential order can be determined by adding a certain allowance to the estimated completion time of the potential order. Advanced information technologies, such as cloud and edge computing, can also be applied to internal due date assignment. Therefore, a hybrid cloud and edge computing approach to enhance the effectiveness of internal due date assignment in advanced manufacturing systems is reviewed. In addition, imprecise output projection forecasts can lead to delivery delays, loss of potential orders, or unnecessary inventory accumulation, which is a critical challenge for manufacturing systems to overcome. Therefore, various machine learning or deep learning methods have been applied to output projection. Advanced information technologies, such as Industry 4.0 and explainable artificial intelligence, can also be applied to enhance the effectiveness and interpretability of output projection.