PROJECT RISK ANALYSIS AND MODELLING SKILLS
If you need to calculate the odds of delivering on-time or on budget, the only way is through probabilistic project risk analysis.
Using Oracle Crystal Ball or Palisade’s @RISK, participants will learn simple and effective quantitative modelling techniques/skills and tools to calculate the odds of success using Monte-Carlo Simulation. Focused on project risk analysis, participants will discover how to use Monte-Carlo simulation and optimization tools to make decisions and assess risk in day-to-day situations as well as planning for building complex models & forecasts.
This workshop is designed for both the beginner and advanced business analyst and we will fully cover the A to Z of applying risk analysis techniques and modelling best practices to CAPEX Cost Estimates, Project Schedules and Discounted Casflows.
MODULE 1 – Enhancing the modeling process with simulation
Why is Risk Analysis critically important in today’s world?
- Making decisions under uncertainty
- Where risk analysis and simulation integrate with the planning process
- The flaw of averages: Why 70%+ projects fail to deliver on expectations
- Understanding risk analysis key concepts and definitions
- Workshop: What does 90% confidence really mean?
Modeling vs. Simulation
- Overview and history of Monte-Carlo Simulation
- Advantages and Disadvantages of simulation
- How and Where predictive modelling and risk analysis can have a positive impact on the organization
The Modeling Process
- Modelling best practices for formating and organizing spreasheet models to be clear and easily auditable.
- Sourcing and using historical or published data
- Discussion on using the Monte-Carlo Method for properly scoping the need, building assumptions and establishing model constraints with Subject Matter Experts
- Workshop: Using risk analysis to develop a New Compensation Model
Using and Configuring Crystal Ball for Risk Analysis: Toolbar, Basic Terminology, Sampling, Reporting and Data Extraction
Module 2 – Building and Running Models
Essential Statistics For Risk Modeling
- Workshop: Understanding how probabilities work with the DICE model
- Basic probability statistics (Mean, Standard Deviation, Kurtosis, Skewness)
- Overview of principal distributions and when to use them
- How Multi-Modal distributions are generated
Tornado Charts and One Way Sensitivity Analysis
- Analyze existing models to identify inputs with the greatest impact.
- Spider-Charts vs Tornado Charts
- Workshop: Analyzing variables to model in a Loan Process
Fundamentals in Project Estimation
- What is Project Risk Analysis
- Working defenition of a good project estimate
- Overestimating vs. Underestimating
- The difference between: Targets, Commitements, Estimates and Plans.
Working with Distributions and Model Inputs
- Best practices for defining model inputs in Excel and selecting the right distribution
- Continuous vs. Discrete Distributions
- Comparing risk profiles:
- How to correctly ask for ranges
- Using Custom Distributions
- Workshop: How different distributions compare using the same input parameters.
Defining, Analyzing and Communicating results to the business
- Setting up model outputs and visualizing results and charts (Sensitivity, Forecasts, Assumptions and Overlays)
- Establishing Confidence Intervals and configuring precision control to optimize the number of trials
- Generating simulation result reports & documentation
- Techniques to effectively and simply communicate your analysis to your peers, clients and superiors
- Question handling
Project Risk identification and Assessment using Simulation
- Interpreting Forecasts and Sensitivity Analysis
- Using Monte-Carlo simulation to calculate project contigencies.
- Discussion on how to correctly organize risks into schedule, cost and market models.
- Workshop: Schedule Risk Analysis
- Workshop: Analyzing Cost Estimates with conditional costs and discrete risk registries.
Module 3 – Incorporating Historical Data and Trends into your SIMULATION Models
Correlation and Regression
- What are correlations and their impact on results
- Making sure your model behaves correctly using correlation
- 3 techniques to calculate correlation and their differences.
- Overview of regression and its basic applications
- Discussion on the how Monte-Carlo simulation works.
- Workshop: How to calculate rank correlation and use it to correlate model assumptions
- Aggregate Assumptions
- How to research which distributions you should fit.
- Best practices on how to source and fit historical data using statisitical methods.
- Analyzing fit results and selecting the RIGHT distribution for both univariate and multivariate data.
- Forecasting vs. stress-testing your model over time.
- Overview of the components and applications of time-series forecasting
- Univariate Forecasting using Geometric Brownian Motion by calculating historical trend and volatility. (Escalation/Inflation Models)
- Time-series projections using to easily incorporate Seasonality, Smoothing algorithms, Growth Projections using historical data
- Workshop: Projecting Next Year’s Sales using CB Predictor.
- Workshop: Building Correlated Forecasts using Multiple Linear Regression using CB Predictor.
Module 4 – Optimization and Scenario Modeling
Portfolio Optimization Techniques :
- Introduction to Simulation - Optimization with OptQuest
- Everyday Optimization applications and examples
With the help of several integrated financial models, this workshop will provide financial analysts with a complete understanding of why, where and how to apply spreadsheet forecasting, simulation, real options and optimization within their analyses.
- Project Portfolio Selection: Use OptQuest to pick the best projects based on Organizational Budget Constraints
- Portfolio & Resource Allocation Optimization: Allocate resources or budgets among various investments to maximize NPV or ROI or minimize risk or expense.
- Modeling Efficient Frontier Analysis to optimize risk against benefit for projects and investments. (Portfolio Allocation)
to compare complex 2 dimensional problems
- Workshop: Inventory Options
- Workshop: Oil Field Development Strategies
- Creating 3D solution plots
At the end of this 16hr workshop, participants will be able to:
- Understand and apply Monte-Carlo simulation and optimization in their day-to-day activities.
- Quickly build effective models or customize existing ones with Crystal Ball or Palisade @RISK.
- Pick and manage project more effectively
- Use Monte-Carlo-Simulation to calculate risk based contigencies for projects and schedules.
- Clearly explain how Monte-Carlo simulation works and how its results should be interpreted.
PRE-PAID REMOTE TRAINING
Our workshops last 16hrs / 24hrs and are delivered, one-on-one, in 2 hour sessions at your convenience. Just call to book the times that work best in your schedule. Each 16 hour remote training program is billed at 2,199.00$ and 24hrs at 3,175.00$ USD Our remote and onsite training topics for Crystal Ball, Primavera Risk Analysis, RiskSolver, Julia, @RISK and ModelRisk include: Visit https://store.technologypartnerz.com/risk-and-business-analysis-trainingfor a complete list