Risk, Opportunity, Uncertainty and Other Random Models (Volume V in the Working Guides to Estimating and Forecasting series) goes part way to debunking the myth that research and development costs are somewhat random. 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.

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 is 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 on 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!’

Monte Carlo Simulation can be used to model variables, determine Critical Paths in a schedule, and is key to modelling Waiting Times and queues 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.