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Risk Models for Project Managers

Monte Carlo and Beyond

Gregory Baecher

Projects move businesses and society forward as by delivering the services, products, and outcomes needed to achieve objectives. As investments they require detailed consideration to ensure we’re investing our time, money, and attention wisely. Project risk management offers logical and numerical methods to analyze important project decisions.

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Projects move businesses and society forward as by delivering the services, products, and outcomes needed to achieve objectives. As investments they require detailed consideration to ensure we’re investing our time, money, and attention wisely. Project risk management offers logical and numerical methods to analyze important project decisions.

The heart of modern project risk management focuses on the development of quantitative probabilistic models of cost, schedule, and other project risks. These quantitative models build on the qualitative risk register to create management forecasts which can be manipulated and optimized to develop risk management plans:

Modern quantitative risk models leverage probabilistic thinking about uncertainties and consequences to support formal analysis. These detailed models of the highest priority risks support optimizing strategies. Thus, they provide a quantitative approach to decision-making in the face of uncertainties, while leading to realistic targets for achievable cost, schedule, and scope.

  • Numerical models including Monte Carlo simulation, linear and non-linear approximations, and other practical computer methods allow these quantitative risk models to be translated into practicable solutions. Reliability and other systems risk modeling tools may also be used for quantitative risk analysis.

These tools provide powerful insights into evaluating a project at each stage of its lifecycle to see which courses of action work best for stakeholders. Simulating budget and schedule risk across scenarios provides a decision space for project managers and sponsors. Projects can then be appreciated as an investment of time, money, and resources to achieve the organizations goals.

What's inside

Learning objectives

  • ● how to quantify and assess projects for budget, schedule, and return on investment
  • ● project budget and scheduling fundamentals
  • ● how to develop a project budget estimate
  • ● how to model impacts on the project budget
  • ● how to develop and model project schedules
  • ● how to simulate using monte carlo methods the potential impacts of project risk on budgets and schedule
  • ● estimating the impacts of uncertainty
  • ● leverage insights to select strategies and invest in projects

Syllabus

Week 1: Budget Risk
Week 2: Schedule Risk
Week 3: Monte Carlo Calculations
Week 4: Monte Carlo Modeling
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Week 5: Projects as Investments

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a quantitative approach to decision-making amid uncertainty
Emphasizes modern project risk management through probabilistic models
Suitable for project managers, sponsors, and stakeholders seeking to evaluate and optimize projects
Leverages numerical models, including Monte Carlo simulations, for practical solutions
Focuses on estimating and modeling impacts on project schedules and budgets
May require prior understanding of project management fundamentals
Advisable to have familiarity with probability and statistics

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Career center

Learners who complete Risk Models for Project Managers: Monte Carlo and Beyond will develop knowledge and skills that may be useful to these careers:
Project Manager
A Project Manager is a professional who works with teams to plan and execute projects, ensuring they are completed on time, within budget, and to the required quality standards. This course provides project managers with the skills and knowledge needed to develop and implement project risk management plans, which can help them to identify and mitigate potential risks that could affect the project's success.
Risk Analyst
A Risk Analyst is responsible for identifying, assessing, and managing risks. This course provides Risk Analysts with the skills and knowledge needed to develop and implement risk management plans, and to make informed decisions about how to mitigate risks. The course also covers the use of Monte Carlo simulation to analyze risks, which is a valuable tool for Risk Analysts.
Program Manager
A Program Manager is responsible for overseeing multiple projects and ensuring that they are aligned with the organization's strategic goals. This course can help Program Managers to develop the skills and knowledge needed to manage complex projects and programs, and to make informed decisions about how to allocate resources and mitigate risks.
Risk Consultant
A Risk Consultant provides advice and guidance to organizations on how to manage risks. This course can help Risk Consultants to develop the skills and knowledge needed to provide expert advice on risk management, and to help organizations to develop and implement effective risk management strategies.
Investment Analyst
An Investment Analyst is responsible for analyzing and recommending investments for clients. This course can help Investment Analysts to develop the skills and knowledge needed to assess the risks and returns of different investments, and to make informed decisions about where to allocate funds. The course also covers the use of Monte Carlo simulation to analyze risks, which is a valuable tool for Investment Analysts.
Financial Analyst
A Financial Analyst is responsible for analyzing financial data and making recommendations on investments. This course can help Financial Analysts to develop the skills and knowledge needed to assess the risks and returns of different investments, and to make informed decisions about where to allocate funds.
Data Analyst
A Data Analyst is responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course can help Data Analysts to develop the skills and knowledge needed to use data to identify and mitigate risks, and to make informed decisions about how to allocate resources.
Business Analyst
A Business Analyst is responsible for analyzing business processes and making recommendations on how to improve them. This course can help Business Analysts to develop the skills and knowledge needed to identify and mitigate risks that could affect a business's operations, and to make informed decisions about how to improve business processes.
Systems Engineer
A Systems Engineer is responsible for designing, developing, and testing complex systems. This course can help Systems Engineers to develop the skills and knowledge needed to identify and mitigate risks that could affect the development and deployment of systems, and to make informed decisions about how to design and build systems.
Operations Research Analyst
An Operations Research Analyst is responsible for using mathematical and statistical methods to solve business problems. This course can help Operations Research Analysts to develop the skills and knowledge needed to use Monte Carlo simulation to model and analyze risks, and to make informed decisions about how to allocate resources.
Software Engineer
A Software Engineer is responsible for designing, developing, and testing software. This course can help Software Engineers to develop the skills and knowledge needed to identify and mitigate risks that could affect the development and deployment of software, and to make informed decisions about how to design and build software systems.
Actuary
An Actuary is responsible for assessing and managing financial risks. This course can help Actuaries to develop the skills and knowledge needed to use Monte Carlo simulation to model and analyze risks, and to make informed decisions about how to allocate resources.
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. This course can help Statisticians to develop the skills and knowledge needed to use Monte Carlo simulation to model and analyze risks, and to make informed decisions about how to allocate resources.
Quantitative Analyst
A Quantitative Analyst is responsible for using mathematical and statistical methods to analyze financial data. This course can help Quantitative Analysts to develop the skills and knowledge needed to use Monte Carlo simulation to model and analyze risks, and to make informed decisions about how to allocate resources.
Data Scientist
A Data Scientist is responsible for using data to solve business problems. This course may be useful for Data Scientists who want to develop the skills and knowledge needed to use Monte Carlo simulation to model and analyze risks, and to make informed decisions about how to allocate resources.

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Risk Models for Project Managers: Monte Carlo and Beyond.
Offers another perspective to reliability and risk assessment. It is an additional read that supplements the learning of the course.

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