Decision Support Tools: Machine Learning Application in Smart Planner

Immaculate Project Planning and Execution (PPE) is capital to edge over competitors, decrease costs and honour delivery dates.Project Management Information System (PMIS) is necessary towards an improved and efficient quality of any project.Machine Learning (ML) Algorithms enabled learned the date of experience to develop insights into various associations between data and outcomes.A defined set of rules prescribed by the analysts makes the probability of the fault possible.In this paper, Regression Model compute across all viable sectors expending the tool for Downstream Business and other Facilities Upstream, including Resource Estimation Schedule Generation.Extending structured information into a reliable database allows super users to define the data structures and completely configurable the setting�s dynamics.The model used to decrease the approximation error and measure the closest possible outcome.This subset of artificial intelligence has tremendous potential in improving schedule generation configuration to develop Project Planning timely and financially smartly.This paper aims to share standard protocols and methods applied in ML-aided as a tool in PPE decision making.Additionally, the abundant used data resources devoted to implementing ML are outlined.Finally, ML success as a Decision Support tool in project management by having a Smart Planner in supporting project recommendation accelerates the decision process, increases stakeholder confidence, and minimizes uncertainty; results are reviewed and analyzed where gaps and potential improvement for future projects are being noted and highlighted. © 2023, Institute of Technology PETRONAS Sdn Bhd.