Mercredi, 17 novembre 2021, de 11 h 00 à 12 h 00
Validation Estimating LLC
In 2011 I was primary contributor to an AACE Recommended Practice (RP 68R-11) for using probabilistic methods to forecast project escalation cost. Escalation is a shorthand term for the impact of economic trends, volatile or otherwise, on project costs. Unfortunately, this is a very lonely RP. 2011 was near the end of the commodity super-cycle; project prices to owners increased by 50% from 2003 to 2008 at a time that inflation was negligible. The RP captured the super-cycle forecasting lessons learned but the RP was largely ignored as prices declined. So, this talk is to resurrect those lessons, and update them for recent times.
Few recognize escalation for the potentially devastating risk that it can be. Economic cycles like these are sporadic but their volatility can span a decade. Every mega-project stands a good chance of getting hit by cycle. Despite this experience, few quantify escalation as a risk. Many confuse escalation and inflation. Few realize that the published price indices do not track the price of services that are bid. Others fail to factor in that if revenue (sales price) increases, capex will too. The situation is getting worse because the duration of pre-sanction project definition is increasing as sustainability demands increase. A new mining project for example may take 10 years or more from the time of a FEL 2/Class 4 estimate to the start of construction. That is a lot of time for an economic wave to wash through. All this and more will be discussed. The session is based on Chapter 13 of the presenter's book: “Project Risk Quantiﬁcation: A Practitioner's Guide to Realistic Cost and Schedule Risk Management”.
The fourth industrial revolution has led to widespread digitalization across the delivery chain of construction and project industries. The digitalization of project processes and other technological enhancements such as digital project delivery, building information modeling, and digital twins have created vast amounts of promising data. At the same time, data science, artificial intelligence, and machine learning are becoming ever more streamlined and available for a variety of tasks, raising debates and discussions about what is project analytics and how analytics processes and functions can create a competitive advantage. Systematic approach to this issue requires a holistic view into three aspects of it: first, inherent complexities of projects as complex and interdependent systems; second, nature of project delivery processes, management, and controls; and third, knowledge of high-performance analytical algorithms, tools, and trends in technological innovation. This paper provides an overview of the authors' experiences and perspectives on project complexities, success factors in dealing with such complexities and the impact on data-driven forecasting and project cost and schedule delivery. A framework is also proposed for successful project analytics functions.
John Hollmann, lead author of AACE® International's TCM Framework (2006) and author of “Project Risk Quantification” (2016), owns Validation Estimating, LLC (VE). He works with capital program managers and project leaders in a variety of industries from process to infrastructure to improve their cost engineering practices; i.e., estimating, project control, risk quantification, etc. Mr. Hollmann is a frequent speaker at international conferences, has written many papers, and often leads training workshops. He is an Honorary Life Member of AACE® and also recipient of their Award of Merit and Lifetime Achievement Awards. He was Director of Recommended Practices at AACE® and also led development of the AACE® Decision and Risk Management Professional certification. Prior to founding VE, Mr. Hollmann led metrics and research efforts at Independent Project Analysis, Inc. Prior to that he worked in estimating and controls for owner and contractor companies. His latest venture is cloud-based risk quantification software called ValidRisk (www.validrisk.com) based on his 2016 book.
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En cliquant sur « Accepter », vous acceptez le stockage de témoins (cookies) sur votre appareil pour améliorer les performances de notre site Web et recueillir certaines statistiques de fréquentation via Google Analytics. Le respect de votre vie privée est important pour nous, nous ne collectons aucune donnée personnelle sans votre consentement.