Risk Opportunity Uncertainty and Other Random Models

<p><em>Risk Opportunity Uncertainty and Other Random Models</em> (Volume V in the Working Guides to Estimating and Forecasting series) goes part way to debunking the myth that research and development cost are somewhat random as under certain conditions they can be observed to follow a pattern of behaviour referred to as a Norden-Rayleigh Curve which unfortunately has to be truncated to stop the myth from becoming a reality! However there is a practical alternative in relation to a particular form of PERT-Beta Curve.</p><p></p><p>However the major emphasis of this volume is the use of Monte Carlo Simulation as a general technique for narrowing down potential outcomes of multiple interacting variables or cost drivers. Perhaps the most common of these in the evaluation of Risk Opportunity and Uncertainty. The trouble is that many Monte Carlo Simulation tools are ‘black boxes’ and too few estimators and forecasters really appreciate what is happening inside the ‘black box’. This volume aims to resolve that and offers tips into things that might need to be considered to remove some of the uninformed random input that often creates a misinformed misconception of ‘it must be right!’</p><p></p><p>Monte Carlo Simulation can be used to model variable determine Critical Paths in a schedule and is key to modelling Waiting Times and cues with random arisings. Supported by a wealth of figures and tables this is a valuable resource for estimators engineers accountants project risk specialists as well as students of cost engineering.</p>