Technical Program Abstracts

(RISK) Decision and Risk Management

(RISK-3037) Combining Parametric and CPM-Based Integrated Cost-Schedule Risk Analysis

Author(s)/Presenter(s): Colin H. Cropley; Matthew D. Dodds


Parametric modelling (“P”) of systemic risk plus Expected Value (EV) modelling of project specific risks to quantify project contingency is described in detail by John K Hollmann in his book “Project Risk Quantification” which highlights the value of empiricism to forecast project cost and schedule outcomes, consistent with AACE RP 40R-08. Hollmann recommends the combined P+EV methodology as reliable, easy to perform and not requiring the use of Critical Path Method (CPM).  However, the assessment of schedule risk is not straightforward without use of a CPM schedule and requires significant expertise.

CPM-based Integrated Cost-Schedule Risk Analysis, described in RP 57R-09, represents the most common approach used to quantify contingencies.  It lacks explicit empiricism and is criticised for failing to forecast adequate cost contingency.  But when practised carefully using good quality schedules, it is a good predictor of schedule contingency and enables schedule risk and thus time-dependent cost risk optimisation.

Combining parametric modelling of systemic risk with CPM-based ICSRA is considered invalid because the parametric forecasting covers all project risk except major project specific risk events.  This paper describes a valid method of combining P+(CPM-) ICSRA, to optimise schedule risk and forecast realistic cost contingency.  It describes experience implementing this methodology.

(RISK-3042) A Multi-Dimensional Approach to Optimize Risk Response Performance

Author(s)/Presenter(s): Mehdi S. Mohammadi, CCP PSP


In management of urban projects, a project manager needs to identify possible risks, and determine optimized risk responses to guarantee success of the project. Therefore, the main focus of this study was on optimization of risk response performance which is one of the last phases of project risk management. In this paper, within an illustrative example, at the first step, possible risks of an urban project were classified in eight main groups as follows; physical risk, personal risk, technical risk, safety risk, regulation risk, financial risk, contractual risk, and environmental risk. At the second step, a multi-dimensional approach based on a hybrid tool consisted of two most employed Multi-Attribute Decision-Making (MADM) techniques namely; AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was developed and applied to the example to determine most suitable response for each individual risk identified formerly in the project. In the proposed approach, the most suitable risk response could be one of these four alternatives: 1) controlling the risk, 2) avoiding the risk, 3) accepting the risk, and 4) transferring the risk. The proposed multi-dimensional approach also considers project conditions as the analysis criteria. 15 analysis criteria for the studied example were: cost, time, budget, quality, safety, project size, project complexity, site accessibility, technical knowledge, required information, design capacity, required equipment, required human resources, personnel skill, and project surroundings. In this study, the convincing results of the provided analytical process for risk response optimization demonstrated that the proposed approach can efficiently and simultaneously take all project conditions into consideration.

(RISK-3044) The Maintenance Projects Way: How Risk-Informed Portfolio Sponsors Protect Value

Author(s)/Presenter(s): Justyna Krzysiak, P.Eng, DRMP


We are all familiar with the fundamental differences between growth investing and value investing. These two styles of investing - made famous by world-renown investor Warren Buffett and his less infamous partner Charlie Munger - are fundamentally different strategies, requiring different decision-making principles and different tactics. Project portfolio management is no different.  Growth or opportunity projects create value, while maintenance capital or sustaining projects protect value. These two fundamentally different risk strategies necessitate different guiding principles, different tactics; and require different competencies of the portfolio sponsor during both the selection and the execution phases of projects. In particular, maintenance capital or sustaining value projects require the portfolio sponsor to not only understand alignment to business unit strategy and to possess project risk management skills required for effective execution; but to also possess a comprehensive understanding of current operational risk management challenges and multi-year asset management plans. These portfolio sponsor competencies allow for more agile decision-making, while maintaining alignment to business unit asset management strategies; and clear line of sight to the enterprise strategic objectives.

(RISK-3055) Performance Impacts in Risk Management

Author(s)/Presenter(s): Eric Ho


When evaluating risks, risk managers often focus on only two types of impacts, cost and schedule.  Cost and schedule are the primary focus of quantitative risk analysis, as those are the metrics used to determine contingency and project confidence.  However, other types of impacts, while acknowledged, are often dismissed when evaluating risks.  This results in risk registers that minimizes or ignores key risks to the project, including those related to impacts on project performance.  Performance impacts could include impacts to the project’s quality, scope, aesthetics, operations & maintenance, environment, and health & safety.  If these metrics are not considered, then the risk register would not represent the entire range of risks to the project.  As such, a risk that could result in a critical performance impact to the project could be minimized or excluded from the risk register.

This paper will present the importance of factoring considerations for performance impacts when evaluating and identifying project risks.  Examples of different types of performance impacts and recommendations on implementation to risk management will be presented.

(RISK-3069) Who Owns Earned Schedule Contingency?

Author(s)/Presenter(s): Michelle L. McMillan, P.Eng.; Roxane Joubert


This paper was initiated by a situation on a large industrial project.  The owner stipulated a finish on or before contractual completion date. To gain a competitive cost advantage, during the bidding process, the contractor claimed to have planned their work to be completed 3 months early but there was no mechanism in the bidding process to identify this condition.  The contractor’s schedules were compliant with the contract requirements and consistently showed a construction completion date, three months earlier than the contractual “finish no later than” completion date.  Late in the Project, the consultant provided changes which required the contractor to be on site after their anticipated construction completion date but not after the final contractual completion date.  The contractor put forward a request for additional costs for the additional time on site, after their planned completion but before contractual completion.

This paper reviews the issues raised by this situation including terminal float, ownership of project float, ownership of earned schedule contingency and contract risk allocation.  The paper also investigates the current recommended practices and legal precedents related to this situation as well as providing alternative contracting solutions to deal with similar issues on future projects.

(RISK-3078) Cost and Schedule Risks Interact in Megaprojects

Author(s)/Presenter(s): Dr. David T. Hulett, FAACE; Waylon T. Whitehead


Megaprojects can be described as both complex and fragile.  They are technically challenging and may stress the organization’s resources and systems to execute successfully.  They are often schedule-driven, magnifying the need for contractors to be closely coordinated and mutually successful. Oil and gas megaprojects are sometimes located in areas where there is a need to create an environment and infrastructure stable enough to support project execution.  Management may fail to appreciate the extent to which problems in one area affect other areas. Risks that affect the duration and costs of these projects interact with each other and produce effects that are magnified beyond the impacts of the risks considered individually.

The thesis of this paper is that, for these megaprojects, risks often occur in series rather than parallel and can have a compounding effect on each other.  For example, labor productivity may be worse than planned and workplace security risks (work actions or worker safety) may cause work to be suspended.   These two risks together reduce the number of days left to execute the plan within schedule, driving up labor costs and jeopardizing the finish date.  Using Monte Carlo simulation, we will demonstrate that risks occurring in series, causing the impacts to be worse than the original assessments, are often at the root of extreme overrun.

(RISK-3111) Identifying the Most Probable Cost – Schedule Values from a Joint Confidence Level (JCL) Risk Analysis

Author(s)/Presenter(s): Dr. David T. Hulett, FAACE; Samuel Steiman, PE


Integrating cost and schedule risk analysis using Monte Carlo simulation yields a scatterplot of internally consistent pairs of cost and finish dates for a project or phase.  When cost and schedule are not highly correlated the JCL values, say JCL-70, to achieve both objectives will imply later dates and more cost than the P-70 values for cost and finish date when examined individually.  The risk analyst is faced with multiple possible JCL-70 date and cost combinations that yield a JCL-70. The challenge is to pick the right combination of values to show to management. 

The question is: “Which combination of cost and finish date which with a JCL-70 value for both objectives is most likely to occur?”  Usually the analyst “eye-balls” a selected JCL-70 point, approximating the densest point in the scatter plot, but that is not convincing for budgetary purposes.  Some people draw the regression line through the time-cost scatter and pick the intersection of that and the JCL-70 “necklace,” but linear regression answers a different question and is not reliable as a measure of the most likely combination.

This presentation shows an innovative way to evaluate scatterplot data to allow the analyst to recommend the most likely cost and schedule targets at a desired JCL. Just as probability density function histograms for cost or schedule examined individually show the number of iterations of the Monte Carlo analysis falling into cost or schedule bins, a 3D histogram of the scatterplot data can be created showing the number of iterations in bins of a combined cost and schedule grid.  The intersection of this 3D histogram with the JCL-70 “necklace” clearly shows the cost and schedule values most likely to occur at that JCL.  Data representing both highly correlated cost and schedule projects as well as non-correlated and bimodal results are presented to illustrate how this methodology produces more defensible results than the regression analysis or simply “eye-balling” the scatterplot data.

(RISK-3118) Schedule Risk Analysis for Transit Projects: Case Study in Differing Approaches

Author(s)/Presenter(s): Andrew Christofas


Effective project risk management leads to many inherent benefits. From recognizing potential pitfalls early on and putting plans in place to control outcomes, to having increased confidence in management decisions. However, even with a robust risk management program, the potential for schedule delay will always exist. Performing a schedule risk analysis allows a management team to determine how much delay can reasonably be expected.

In civil infrastructure mega projects, the effective application of a schedule risk analysis is a critical tool necessary to inform an Owner of what impact unmitigated risk may have on its project and allows for a more focused risk mitigation approach.

This case study will examine two schedule risk analysis approaches used on an actual rail transit project: the approach used by the Owner versus the approach used by the primary funding partner. Both methods were performed using the project’s Critical Path Method (CPM) schedule. While the two organizations used differing approaches, the results were surprisingly similar, and ultimately demonstrated the importance of performing a schedule risk analysis to arrive at realistic contingency needs.

(RISK-3126) Dynamic Quantitative Deployment and Prediction for Multi-Project Resources Based on Monte-Carlo Simulation

Author(s)/Presenter(s): Hong Dong; Chunfu Xu; Jin Feng; Xiaguang Liu


As the parallel implementation of projects with multi-technologies at multi-sites, the conflict and balance of different resources including but not limited to manpower and machines, materials among projects is becoming more serious. It is critical for EPC contractors to allocate and predict project resources in a scientific and reasonable way. According to the life cycle planning with standard curve of resources for projects, the probability model of resource configuration and prediction based on Monte Carlo Simulation(MCS) is proposed, which is combined with project schedule, risk and resource, to achieved the optimization control and prediction objectives plus the transformation of from static to dynamic  and qualitative to quantitative. This method takes into account the dynamic progress and risks, the short-term and long-term resource needs, which achieves the coordination and flexible deployment of resources, and reduces costs effectively. Finally, a case is studied in this paper, the more scientific multi project manpower reserve plan is developed based on the result to achieve the maximization of resources benefit for decision makers.

(RISK-3129) Lessons from Financial Risk Management

Author(s)/Presenter(s): Eric Ho


In 2007, the biggest financial crisis of our lifetime occurred, causing the collapse of banks, bailouts by the governments, and trillions of dollars in lost wealth.  While the causes of the financial crisis are many, financial institutions and governments have attempted to prevent future collapses with stronger risk controls and regulations.  This paper will present the lessons learned from the financial crisis and look at how they can be applied to capital project risk management.  Topics that will be covered include risk modeling, risk governance, data collection, bias, transparency, capital reserves, and conflicts of interest.  Similar to the banking sector, capital projects should also require stronger procedures and policies to prevent project failures.

(RISK-3140) Mitigating Energy Project Risks to Maximize Project Benefits

Author(s)/Presenter(s): Craig Steigerwalt, PE


You are developing and/or building fast-paced projects within the renewable energy industry; specifically, high-voltage electric transmission interconnections.  Maybe you are new to the industry and/or working for the first time with a electric utility.  Or simply, your portfolio has increased in size and with that the size and type of challenges. Regardless, you need to develop a delivery strategy to effectively execute your projects.  You need to identify and understand your stakeholders, as well as, the ‘rules of the game’ to successfully interconnect your projects to the grid.  It’s equally important to understand and gauge the project risks that might eventually hinder the project outcome.  This paper will educate you on how to manage your project and its risks to mitigate the impact to your overall schedule, cost, scope and quality and so, increasing the probability of having a positive project outcome.

(RISK-3158) Innovative and Real Time Risk Analysis with Senior Management in Megaprojects Using a 4D Visualization Model in Australia

Author(s)/Presenter(s): Abhijnan Datta, CCP


Megaprojects suffer from optimism bias as its project team consistently underestimate costs and overestimates benefits. They fail to learn from their mistakes despite the increased number of projects and researchers claiming the presence of optimism bias leading to a ‘performance paradox.’ Thus, megaprojects are an example of the knowing-doing gap similar to other industries. We explore how megaprojects use innovative ways to address risks that would arise during construction and its role in achieving realistic schedules which help to reduce the optimism bias relating to schedule in these projects. For this, we used a case study approach for studying a vent facility in a megaproject in Australia. The 4D model helped the project to visualize, discuss construction methodology, identify risks in the construction process to convince decision-makers and the wider project community towards taking appropriate action. The risks identified were safety risks, program risks, and interface risks.

(RISK-3159) Risk Identification and Assessment of Facility Engineering for International Oil and Gas Projects

Author(s)/Presenter(s): Li Huaiyin; Dang Xuebo; Zhang Lei


International oil & gas exploration and development projects face many risks, mainly from 3 aspects: political/economic/taxation risks, E&P technology risks, engineering design and execution risks.Facility engineering is a major aspect which is a key link to achieve oil & gas production targets, control CAPEX, and achieve on-time commissioning target. The related risk factors, risk identification and risk assessment are difficult.

The methods used in the identification of facility engineering risks include: expert survey method, fault tree analysis method, HAZOP, scenario analysis method, flow chart method, work-risk breakdown method, warranty comparison method, SWOT analysis, etc.Basing on project classification with combination of stages and levels decomposition, the identified risks are divided into qualitative and quantitative categories, and the probability and impact scores are determined according to the specific conditions of each factor in the project, so as to grading the risk level and properly responding to them. For complex facility engineering systems, Analytic Hierarchy Process(AHP) could be used for risk factor assessment.

This paper describes the risk factors identification and assessment methodology for facility engineering in international oil and gas projects. Based on the author's study and experience, the practical methods and application for 5 types of projects both offshore and onshore are described in detail, hoping to provide reference for international counterparts.

(RISK-3170) Uncertainty Management

Author(s)/Presenter(s): Aud Hilje Langeland; Ole Jonny Klakegg; Olav Torp; Anna Swärd; Ingemund Jordanger


The paper is separated into:

Empiric data and Recommended method of Uncertainty Management.

The Empiric data method compares two specific parallel and similar projects from concept-phase to contract. One project used the Recommended method of Uncertainty Management and the other project used a traditional Risk Management method. The Empiric data method illustrates that final project investment cost differs significantly.

The Recommended method of Uncertainty Management part of the paper are made by a work group for Project Norway as a recommendation to the building and property industry and the Norwegian state departments, by August 2018. The paper answers five central question related to the Recommended method of Uncertainty Management and includes an Uncertainty register.

(RISK-3172) How to Quantify the Pricing Risk of Engineering Company’s Mergers and Acquisitions Based on Risk Drivers

Author(s)/Presenter(s): Jin Feng; Xiang Wenwu; Zhang Daping


Currently, Mergers and Acquisition (M&A) is an effective way for Chinese engineering companies as the buyers to enlarge their scales and business rapidly, of which the pricing of target enterprise is very hard to forecast precisely due to the impact of many risks such as politic, economic, regulation, etc..Considering that the past pricing model of target enterprise valuation in M&A could not describe the uncertainties of some parameters influenced by the afore said risks to meet the demand of the buyers , one new model by integrating DCF model and two dimensional Monte Carlo simulation based on risk drivers is proposed to solve this dilemma. In this proposed model, the sensitivity analysis, correlation matrix, probability density function (PDFs) and stress analysis of corporate value are deeply studied to show the uncertainty and variability of the pricing risk of target enterprise valuation in M&A, which helps the buyers to determine the reasonable acquisition value and counter with the high risks. Finally, one case is successfully studied to show the validity and applicability of the proposed model.

(RISK-3175) Actions for Improving Risk Management Culture

Author(s)/Presenter(s): Aaron P. Ingebritson, PE; Jesse Lund, CCP PSP


Risk assessments can be contentious.  Results can challenge strongly held organizational assumptions, impact personal interests, such as sales targets, or point out poor decisions and control.  Even with excellent historic data and a rigorous quantitative assessment, risk assessments can be questioned since the events have not yet occurred.  Moreover, organizations have varying cultures and differing levels of risk management acumen.  Therefore, establishing an enterprise risk management program often proves difficult. Nevertheless, risk management is a critical component to effective organizational management. Research clearly indicates that organizations that proactively manage risk achieve better results.      

The aim of our research is to identify governance and practices that organizations can take to improve their risk management culture.  We will start by evaluating existing literature that reviews approaches shown to support organizational risk cultural change.  Next, we will conduct case study interviews of engineering and construction executives to review specific instances of risk management success and failure.  We will apply our research to the case studies to identify alignment and gaps in the case study organizational practices.

(RISK-3183) Addressing Cost Underestimation in Transport Infrastructure Projects

Author(s)/Presenter(s): John K. Hollmann, PE CCP CEP DRMP FAACE Hon. Life


In 2018, a paper titled: “De-bunking ‘Fake News’ in a Post-Truth Era: The Plausible Untruths of Cost Underestimation in Transport Infrastructure Projects” was published by Drs. Peter E.D. Love and Dominic D. Ahiaga-Dagbui. It exposed a convenient but false narrative that transport project cost overruns result almost entirely from delusion (optimism bias) and/or deception (strategic misrepresentation). The authors called for policy-makers to instead use evidence-based research to support decision making considering practices and risks beyond bias. This paper responds to their call by summarizing industry evidence-based research on key causes of cost growth and discusses the risk profession’s failure to realistically quantify these causes (i.e., our facilitation of the false narrative). It also addresses the essential role of stage-gate project systems and associated estimate classification (the pending AACE International® Recommended Practice for rail and road estimate classification will be highlighted). Finally, it reviews the critical practice of estimate validation which quantifies estimate bias which should be planned as part of a “cost strategy” and not left to counter-productive speculation.

(RISK-3184) Estimate Validation and Bias Assessment: Ratio-to-Driver Method

Author(s)/Presenter(s): John K. Hollmann, PE CCP CEP DRMP FAACE Hon. Life


This paper describes a cost estimate validation method called “ratio-to-driver”. Validation starts with establishing an explicit “cost strategy” in the Basis of Estimate document. The strategy sets requirements for bias (every estimate is biased; it must be planned and never assumed) that is to be assured by validation. Then, reliable metrics (comparison ratios) must be developed from an historical or other benchmarking database. The ratio-to-driver method applies the metrics in a stepped sequence that exposes variations from expectations, but also points to their cause. Database systems often do double-duty as validation tools. Because bias is a key systemic risk, and validation measures bias, validation is also defined as a first step in quantitative risk analysis. This paper is intended as a basis for a potential new AACE® RP that builds on RP 31R-03 (Estimate Review), enhances RP 34R-05 (Basis of Estimate) and supports RP 42R-08 (Parametric Risk Analysis) in respect to bias assessment.

(RISK-3191) Cost Risk Analysis (CRA) and its Importance to the Project Estimate from Owners Point of View

Author(s)/Presenter(s): Mashitah Bte Mat Jais; Zariah Ismail


In reality, cost estimate is not a single number; it is a range. The range is due to the uncertainties around the risk of the projects at its implementation stage. From the owner perspective, the project begins as early as the initial stage (Front End Development) to project execution, the uncertainties and risks are notably bigger in the early stage due to uncertainties.

It is very critical to have comprehensive knowledge on the risks around cost in order to make conscious decisions on the project viability. The Cost Risk Analysis (CRA) methodologies and techniques must be institutionalized in the Company to ensure it embedded in each and every process of the cost estimate development at all phases:  no stones is left un turn.

This paper will illustrate and focus on how owners make decision around the risks at the various project stages and gate reviews, and further translate these risks into cost estimate. At these various stage, a difference methodology shall be applied in order to determine the magnitude of the cost risks.

(RISK-3198) The Elegant EASE of Utilizing Cost Engineering Inputs in Strategic Decision Making

Author(s)/Presenter(s): Gagandeep S. Issar


Rationally, Great organizations should differentiate themselves from the rest by relentlessly working on two basic strategic decisions – where would they play and how would they win, on a sustained basis. A quest to answer these key questions should lead these organizations to formulate a set of guiding principles that, when communicated and adopted, should generate a desired pattern of decision making. Further, these organizations should provide a clear roadmap or rules, that define the actions people in the business take (and not take) and the things they should prioritize (and not prioritize) to achieve desired goals. Yet, a staggering 70% of the fortune 500 companies in 1961 haven’t been able to retain their place in this list in 2018. What ails these companies to maintain a sustainable competitive advantage?

This paper aims to delve into the key reasons for lack of anticipation of the consequences that follow with each strategic choice that companies make. It also details how cost engineers incorporate uncertainty (risk) into the decision making models and proposes a framework – EASE – Eyeing Implementation, Accuracy of Data, Solutions from ground-up, and Evidence based decision making to alleviate the bottlenecks of strategic decision making through cost engineering principles.

(RISK-3207) Visualising Schedule Risk for Linear Infrastructure Construction Projects

Author(s)/Presenter(s): Santosh Bhat, PSP


Linear Infrastructure projects, such as tunnels, railways, roadways and pipelines, are becoming increasingly complex, and face greater constraints on achieving the desired project outcomes. Under such pressures the requirements for robust scheduling and time-related risk management are gaining increased focus.

A visual method of representing construction schedules known as “Time Location” charts offers benefits beyond traditional CPM outputs by incorporating the physical location of schedule activities along the physical, linear alignment of a project.

Time Location charts allow communication of a project schedule, in a manner that would not be possible with traditional CPM schedule outputs. Typically, such charts on a single page allow identification and analysis of production rates, sequencing and conflicts of work, resourcing and physical access constraints, ensuring that the schedule represents the desired project methodology and outcomes.

Schedule risk assessments for infrastructure projects typically focus on results for overall project duration or key project milestones. The application of Time Location charting offers benefits for managing time-related risks that go beyond those typical outputs, including the assessment of schedule risk outcomes on key construction elements, the validation of schedule risk inputs and the ability to visualise scenarios to assess the sensitivities of the schedule risks.

This paper will demonstrate the practical application of Time Location charting based upon traditional CPM schedules, and extends this to visualising schedule risk analysis outputs.

(RISK-3208) Risk Allocation to Asses Public Contract: Particular Case - Brazil

Author(s)/Presenter(s): Helber da Cunha Macedo, CCP; Carlos Eduardo Moreira Fernandes Braga; Cesar Teodoro Ferreira; Fabrizio Cesar Reis Fonseca


Reasonable contracts have a scope clearly defined, accountabilities established and allow involved parties to reach their objectives. However, there´s always uncertainties involved. Therefore, to avoid disputes and ensure contract´s results predictability, you have to allocate contract´s risks to the most capable parties to handle them. This means that could be more “things” to be considered in the budget.

In Brazil, a new Law (13,303) regulates the acquisition process in public companies. For engineering services, the owner must define contract’s risks allocation. The overall objective of this law is to increase transparency, to minimize future disputes and additives.

In this context, the paper propose a methodology to calculate risk’s cost impacts and how they affect the contract’s estimates, considering transferred and assumed risks. Finally, through a case study, the proposed methodology is exemplified.

The case study explore owner and contractor perspectives to set their cost estimates, considering contract´s risks allocation. According to the proposed method, each party calculate its own probabilistic cost estimates and they could have different distributions. The benefit of establishing a common method is to facilitate establish a potential negotiation zone, characterized by the overlap of these ranges.

(RISK-3220) Risk Based Inspection of Capital Projects

Author(s)/Presenter(s): Ahmed K. Al-Mulhim, CCP CEP EVP PSP


A practical case study to Implement Recommended Enhancements to Institutionalize Risk Based Methodology to Manage Quality of Capital Program Projects. There were four business drivers. Firstly is managing risks through transforming inspection coverage from one size fits all to risk based inspection approach. Secondly is to prevent past repeated quality issues in order to meet projects quality objectives with resources optimization and high agility to ensure continuous improvement. Thirdly is to optimize resources utilization and level of involvement. Finally is to standardize best practices and set baseline for continued improvement. This exercise covered the main stages of the project life cycle where quality is involved from project proposal up to the construction phase including the preservation as a major stage between procurement and construction.

(RISK-3233) Project System's and Complexity's Parameters as Inputs to Non-Linear Monte Carlo Risk Models

Author(s)/Presenter(s): Dr. Yuri Raydugin


It was demonstrated by the author at the 2018 AACE conference (RISK-2808) that newly-developed non-linear Monte Carlo risk quantification methodology could predict project cost outcomes even in case of most complex and difficult projects. This is based on consistent evaluation of systemic and project-specific risks and requires, among other things, an in-depth characterization of

a) implemented project development & delivery systems (project team’s strengths and weaknesses, various realizations of bias, quality and consistency of implementation of adopted project procedures, etc.), and

b) project complexities (number and interactions of project components and stakeholders, applications of new technologies, etc.).

This paper zeroes in on practical methods and tools to characterize project systems and complexities that could serve as required inputs to non-linear Monte Carlo risk models.

Alignment with corresponding empirical methodologies previously developed by AACE, CII, and the IPA Institute is discussed, which would be used for calibration of the non-linear Monte Carlo risk models of upcoming projects.

(RISK-3242) Strategies for Managing Low-Probability, High-Impact Events in Capital Projects

Author(s)/Presenter(s): Dr. Manjula Dissanayake, CCP; Thomas Vogt


Capital project execution is plagued with cost and schedule overruns across the globe. Substantial efforts are invested in planning and preparing projects, including the identification and mitigation of risks and uncertainties through qualitative and quantitative risk models. Despite these efforts, residual uncertainties remain and are often a major contributor to overruns.   These include both ‘known unknowns” and ‘unknown unknowns” that are difficult to incorporate into typical risk models and project controls approaches. These uncertainties tend to be low-probability and high-impact events. They are typically overlooked, impact is underestimated and not adequately prepared for.

This paper presents a five step strategy to plan and prepare for such events. It will propose a common taxonomy for uncertainty categories, a review of statistical methods and modeling approaches commonly used,  assessment of structure of project organizations, a communication strategy to enable effective decision making and incentive scheme to ensure project organizations remain focused and driven.

(RISK-3262) Stochastic Forecasting of Contingency or Management Reserve Requirements and Drawdown

Author(s)/Presenter(s): Steven W. Wageman, CCP CEP EVP PSP


Establishing an appropriate amount of cost contingency or management reserve for a project can be a challenging and oftentimes perilous task for many organizations. There are many methods currently in use to help determine this elusive value. Arguably, the most robust and therefore defendable method is quantitative Monte Carlo cost uncertainty and risk analysis, which can and should also include an assessment of potential schedule delays. However developed, cost reserves are ideally time-phased to better understand when in the lifecycle of the project they will most likely be needed. This paper will describe a comprehensive method and model for evaluating the actual use of reserves relative to their forecast, and more importantly for most organizations, to stochastically forecast remaining reserve requirements and drawdown without conducting an updated uncertainty and risk analysis. This approach will provide managers with higher confidence when requesting additional cost reserves, or alternatively, when releasing budgeted cost reserves for more productive use in other activities of the organization.

(RISK-3264) Establishing an Appropriate Level of Schedule Detail for a Quantitative Schedule Uncertainty and Risk Analysis

Author(s)/Presenter(s): Steven W. Wageman, CCP CEP EVP PSP


Various professional opinions exist as to whether a summary or detailed-level schedule is more appropriate for a quantitative Monte Carlo schedule uncertainty and risk analysis (SURA). Which is best? This paper will first outline the basic schedule quality requirements necessary to conduct a meaningful SURA and why those requirements are important. The pros and cons of using summary as well as detailed-level schedules will then be identified to help guide the practitioner in making an informed choice. Finally, the results of parallel SURAs conducted on both summary as well as detailed-level schedules for the same test project will be presented to ascertain if there are meaningful differences in modeling results.

(RISK-3286) Mega-Program Risk Based Estimating and Management

Author(s)/Presenter(s): Dr. Ovidiu Cretu, PE; David Dye


The authors present their findings on how the mega-program’s cost and schedule objectives are best managed by using risk based estimating and management process. The paper advocates for a risk based estimating and management process that goes beyond simple assessing mega-program’s risks. The mega-program risk based estimating and management shall evaluate the effects of: (1) estimated percentiles of global program cost Vs. sum of the percentiles projects’ estimated cost, (2) probabilistic estimate of the programmatic cost in addition to the probabilistic estimate of the direct projects cost, (3) contribution of the estimated cost risk Vs. contribution of the estimated cost of the schedule delay risk to the program’s contingency, (4) estimated the contribution of the base inflation to the program cost, and (5) the market conditions impact on estimated cost. The authors present real mega-program risk based estimating and management experience that demonstrates the benefits of better understanding and management of the uncertainties surrounding the delivery of the mega-programs. The paper concludes that the comprehensive risk based estimating and management process is a critical driver to delivery of a successful mega-program.

(RISK-3292) Monte Carlo Simulation Fails the Construction Industry

Author(s)/Presenter(s): Harvey J. Welker


Monte Carlo Simulation (MCS) risk analysis is widely misused in the construction industry.  The simulation process consistently fails to define actual project risk.  MCS risk analysis creates false assessment of economic risks.  The use of Monte Carlo simulation actually does harm; it is not merely useless.

Why is MCS a failure in the construction industry?  This presentation will first define the five levels of project cost development and their respective confidence levels.  The driving factors of MCS failure will be discussed. 

MCS risk assessments will be compared to traditional risk assessment and actual completed construction projects.

Solutions to correct the failed application of MCS will be proposed.

(RISK-3294) Some Key Points of Contingency Drawdown Curves

Author(s)/Presenter(s): Kim Kozak, PE; David A. Norfleet, CCP CFCC DRMP


The fundamentals of risk quantification used for estimating the amount of contingency for a project are well defined. An important step after quantification is the need for developing a forecast, i.e. drawdown curve, that represents when the contingency is expected to be used by the project. This paper will present positions on certain key points with respect to the drawdown curve including: 1. the value of creating separate curves for cost and schedule contingency; 2. whether the profile should represent expenditure, i.e. cash flow, or obligation, i.e. when a realized risk becomes an executed change order; 3. the most representative slope of the curve; and 4. how to treat management’s desire to use the project’s risk contingency funds for other purposes. 5. explore the traditional myths and misunderstandings of contingency drawdown curves

(RISK-3303) Application of Expert Knowledge for Inference in Industrial Megaprojects Risks

Author(s)/Presenter(s): Pouya Zangeneh; Brenda Y. McCabe; Murray Pearson; Nicholas St. John Mason


Last year we presented an article in which we outlined a framework to balance out biases in decision-making procedures by incorporating expert knowledge and project data (RISK.2947). Expanding on the previous article, we aim to describe updates and new findings that went into designing a comprehensive survey of project factors for capturing structured tacit knowledge from industry experts. As well, we sent out the survey to a large pool of industry experts who were asked to rate the prevalence or influence of a series of categorical factors and the categories themselves. The internal and external validity of the elicited knowledge is then examined. The results reveal valuable insights into the perception of project success and the importance of risk factors among different groups of experts. We incorporated the elicited knowledge as well as available data from the literature to train a probabilistic model that can predict the financial behaviour of the projects, using Bayesian belief networks.

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