Advancement of Decision-Making in Agile Projects by Applying Logistic Regression on Estimates

With the advent of iterative software development methodologies such as Agile the emphasis is on light weight software development methodologies. Emphasis is on accommodating frequent changes and also relies on individuals and interaction over processes and tools. Estimation methods used rely on expert-judgment and methods such as planning-poker. During project execution, when changes arise due to dynamic nature of the project, individuals' interaction, mode of communication and expert judgment decide the actions and decision-making in distributed teams. In this paper logistic regression equation method is suggested to capture the schedule changes that are possible due to the dynamic changes to the project. Logistic regression provides the change in probability of completing the feature for an expected change in any of the explanatory variables. Due to the quantified output from logistic regression it augments shared decision-making in distributed environment resulting in better actions.