PROJECT RISK ANALYSIS AND MODELLING SKILLS

OVERVIEW

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.

WORKSHOP CONTENT

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

Data/Distribution Fitting

• 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.

Time-Series Forecasting

• 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

Simulation Optimization

• Introduction to Simulation - Optimization with OptQuest
• Everyday Optimization applications and examples

Portfolio Optimization Techniques : 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)

Decision Tables to compare complex 2 dimensional problems

• Workshop: Inventory Options
• Workshop: Oil Field Development Strategies
• Creating 3D solution plots

BENEFITS

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