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Description
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 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.
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 '
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.
About the Author
Alan R. Jones is Principal Consultant at Estimata Limited, aconsultancy service specialising in Estimating Skills Training. He is a Certified Cost Estimator/Analyst (US) and Certified Cost Engineer (CCE) (UK). Prior to setting up his own business, he enjoyed a 40-year career in the UK aerospace and defence industry as an estimatorAlan is a Fellow of the Association of Cost Engineers and a member of the International Cost Estimating and Analysis Association. Historically (some four decades ago), Alan was a graduate in Mathematics from Imperial College of Science and Technology in London, and was an MBA Prize-winner at the Henley Management College.