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Covers the entire process of risk management by providing methodologies for determining the sources of engineering project risk, and once threats have been identified, managing them through: identification and assessment (probability, relative importance, variables, risk breakdown structure, etc.); implementation of measures for their prevention, reduction or mitigation; evaluation of impacts and quantification of risks and establishment of control measures. It also considers sensitivity analysis to determine the influence of uncertain parameters values on different project results, such as completion time, total costs, etc. Case studies and examples across a wide spectrum of engineering projects discuss such diverse factors as: safety; environmental impacts; societal reactions; time and cost overruns; quality control; legal issues; financial considerations; and political risk, making this suitable for undergraduates and graduates in grasping the fundamentals of risk management.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Principles and Elements of Risk Management – Data and Initial Conditions

This chapter is devoted to furnishing background information on Risk Management, explaining the string of steps that comprise it, and the use of techniques within it, as well as their relationships. The chapter follows the widely accepted sequence for risk identification, assessment, execution, remediation and control; it starts with some basic definitions and, in its first topic, analyzes the sources for risks, considering internal and external risks and opportunities. It follows with a guide for identifying and managing risks in different areas of a project and suggests appropriate tools and techniques for each one. Completion of sequence sensitivity analysis, a subject developed in full in Chap. 6, is commented upon briefly just to give the reader an idea of its use and potential, the sequence finishes with steps for closing and reporting. Establishing a procedure that is a norm in this book, a real life example is proposed using SWOT analysis (This is a planning technique for assessing a firm capability for executing a project considering Strength, Weakness, Opportunities and Threats) to illustrate a firm self-evaluation regarding risks for a particular project. The chapter concludes with the definition of a project strategy, a fundamental step, since it will determine the road to follow for a successful project to be finished on time, under budget and with the required quality.
Nolberto Munier

Chapter 2. Planning

This chapter deals with project planning. It comments upon different approaches for planning normally used nowadays, such as Gantt, Critical Path Method (CPM), Program Evaluation and Review Technique (PERT), and the Monte Carlo Model (MC), and lists many other techniques, for instance, Earned Value Analysis (EV), Probabilistic Trees, Risk Matrix, etc., as well as illustrating other tools, namely Work Breakdown Structure (WBS), Risk Breakdown Structure (RBS), and Z-Matrix. Using the same problem, a comparison between CPM, PERT and MC is proposed; it starts with CPM deterministic and consequently average durations and costs (and thus, with the same chance for success and failure). It moves on to probabilistic, but static PERT (because of its unique scenario), to Monte Carlo, with its hundreds of probabilistic scenarios (subsequently yielding a more reliable outcome). This analysis involves risks related to Time (Delays), Costs (Overruns), Quality, Social impacts, Project safety, Quality, Communications, External factors, Legal, and Environment, in other words, all components of a project. Needless to say, no technique will guarantee that a project will finish on time and under budget, since that technique has not been invented yet, and probably never will be, owing to the many predictable and unpredictable uncertainties in modern projects. However, the chapter offers the most advanced technology for the time being.
Nolberto Munier

Chapter 3. Probabilities in Risk Management

A project is generally a complex undertaking in which most things are uncertain (durations, costs, project and suppliers performance, weather, soil geology, public reaction, etc.), and thus, risk permeates everything. Risk is closely related to uncertainty, and the latter with probabilities and distributions the conceptual aspects of which are explained in Chap. 9. It is inconceivable to address risk without considering probabilities of occurrence, and the measures that must be taken to prevent or mitigate risk; in that sense, the ‘buffer’ concept is introduced. In Chap. 2, a comparison was mentioned between CPM, PERT and MC; now, Chap. 3 proposes a case for numerically demonstrating the advantage of working with probabilities using a network and its critical path for durations and costs; it is here in which the working of MC is explained in detail, using an Excel spreadsheet with commercial software. The chapter moves on to discrete distributions, and explains the mathematical expression of risk as the product of a probability of the occurrence of a threat and the impact that it can produce on human lives, assets, land, etc.; in other words, it puts a value to risk. The chapter finishes with the use of dedicated software and provides information about the companies that provide it.
Nolberto Munier

Chapter 4. Risk Identification

This chapter introduces the first step of the Risk Management process, the detection or identification of risks in a project. It starts building a risk-linking matrix in which every sector is compared with the others in order to determine if there is a risk-wise relationship. This is a good starting point that obliges us to engage in a mental exercise to look for potential risks. It follows an analysis of different types of risks and their limits measured by their impacts. The proposed Risk Breakdown Structure analyses risks and determines their relative importance through a real-life case based on tree analysis. Relative significance is important, and to that effect, two types of diagrams are proposed. A new tool, the Z-Matrix, is used to detect and evaluate a series of impacts where one influences others. Situations are analyzed for identifying risks in construction, environmental, society, project safety, geological risk, quality, legal issues, communications and external factors in projects, and some of them are illustrated with case examples. It moves on for identification and mitigation measures for more complex cases involving transportation, with an example using a tool called ‘The Bowtie Diagram’. The chapter finishes with the explanation and exemplification of the ‘Risk Register’, a fundamental tool for Risk Management.
Nolberto Munier

Chapter 5. Risk Assessment and Analysis

Once threats are identified, they must be assessed or evaluated, which is the objective of this chapter. There is usually a large number of threats, making it impossible or unprofitable to analyze them all, meaning selection of the threats that will be addressed is important. It is a decision-making process; an example is proposed and solved by one of the many techniques available. The chapter proposes a very standard requested study, which is the assessment of the economic and financial risks of a project. This is done through a real-life-example, followed by another appraisal, this time devoted to economic issues, as well as another for transportation, introducing the important concept of conditional probability. The chapter moves on to the assessment of risk associated with costs related to Labor, Materials and Equipment. A still more realistic approach contemplates the simultaneous analysis of all risk costs in a project, introducing the reliability of estimates concept through the use of entropy. It also explores the notion of Probabilistic Risk Assessment together with Tree Analysis and Fault Tree Analysis, which are tools designed for situations that are more complex. Finally, Failure Mode and Effects Analysis are also examined, together with more advanced concepts, such as Correlation Risks and Qualitative and Quantitative assessments. The chapter finishes with the development of the best strategy regarding remediation costs.
Nolberto Munier

Chapter 6. Sensitivity Analysis

The chapter begins by defining sensitivity in projects, whatever their nature. The main word here is uncertainty, because no matter the kind of project, there is always uncertain data and predictions, vague information, unexpected people or stakeholder reactions, deviations in prices, labor performance different from estimated, etc. Sensitivity analysis is designed to examine the response or reaction of an output variable, such as the IRR, the NPV or the Payback Period, to variations of input variables, such as sales volume, price, etc. To this extent, this chapter starts by examining variations on task durations in a schedule, and introducing concepts such as the Tornado Diagram and the Criticality Index. It also refers to variations associated with the outcomes of the project’s profitability linked with economic and financial issues, as well as those related to equipment and material costs. The chapter examines the sensitivity in even more realistic cases where variations from different variables acting simultaneously and in different scenarios. The chapter concludes by examining the Sensitivity Ratio or Elasticity, a very well-known and widely used tool in Economics.
Nolberto Munier

Chapter 7. Project During Execution – Strategy – Updating

This chapter fundamentally examines project performance during its execution period, however, risk must always be considered, especially at the very beginning of the project when the risk is normally maximum, and at each update. In the Project Monitoring stage, this chapter explores what happens with foreseen risks, that is, if they really happened or not and their consequences. In the Project Control stage, the chapter uses Earned Value Analysis and examines Performance Factors, which are used to predict completion regarding time and cost. However, because these calculations are based on past performance, there is always the risk that this performance will not be replicated in the future, and consequently, there is uncertainty about the completion time and cost. Risk Management can help in forecasting distribution of values by limiting this uncertainty, considering that it will probably follow a normal distribution probability curve and determine durations and cost values with a 95 % confidence, that is, assuming only a 5 % risk or whatever other value that stakeholders are willing to accept.
Nolberto Munier

Chapter 8. Closing and Reporting

It often happens that closing and reporting do not deserve particular attention from the contractor or consultant Project Manager, however, they are important. This chapter analyzes diverse situations that imply risk specifically related to an owner being dissatisfied owing to a deficiency of documentation in quantity and quality handed over, or perhaps due to a lack of quality in finishing concrete work, or through failure to clean the site. The chapter analyzes these aspects, pointing out that closing-out a project is a process as important as the rest of the processes in the project’s life cycle, and examines the need to produce a good Technical Memory that must incorporate a string of information not only related to the work done, but also to be used as a future reference. This chapter continues with the production of ‘As built’ drawings, a fundamental document that depicts the real condition of the project, which may differ from the original planning, as well as the need to produce a complete and trusty report.
Nolberto Munier

Chapter 9. Brief Introduction to Probability Distributions

There is a great deal of uncertainty in any project. That is, data is seldom absolutely reliable and exact, since there is never certainty about duration of tasks, price variations, effect on the environment, etc., to say nothing about those aspects which are external to the project and for which the project developer has no control, such as weather conditions, demand, stock fluctuations, inflation, supplier’s delays, etc. It is believed that many projects are not completed in time and finish with cost overrun, because in their preparation, data is taken as unquestionable, and then actual conditions show that it is not precisely the case. For this reason the uncertainty aspect has to be considered in projects preparation, and this is the objective of this chapter, by introducing statistic techniques.
Nolberto Munier

Backmatter

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