Angelo J. Arcoleo, PMP

Title: Heuristic Schedule Modeling Using Full Monte How to Set Better Limits Based on Actual Performance.

All too often we set general limits to schedule tasks when preparing for a Monte Carlo Analysis. Even when complex teams are working on difficult projects a global edit may not be the best option. In this presentation we will discuss how to look at actual complex team performance and apply past performance to future tasks. We will use a 5 by 5 matrix approach. Our demonstration will use information from 5 engineering design teams working on an aerospace or petroleum industry project and applying Minimum and Maximum Limits based on 5 baseline duration groups from actual tasks performed. After determining the limits, you can run Full Monte analysis for all remaining tasks based on these discrete limits to yield better prediction results!

Angelo Arcoleo Bio

Angelo is a PMP with 30+ years of experience in engineering, project management, planning and training. He leads projects and teams to plan and execute critical projects utilizing his experience, quiet-leadership, passion and versatility to work with anyone. He is a professionally trained Civil Engineer and has a BS degree from the Rochester Institute of Technology. Angelo is a Master Scheduler for Exelis – Geospatial Systems Division (formerly KODAK and ITT); Orange Belt in Microsoft® Office Project; and President of MPUG (Microsoft® Project Users Group).

Mr. Arcoleo earned his B.S. degree in Civil Engineering at Rochester Institute of Technology.