# Risk by Palisade - PowerPoint PPT Presentation

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### _at_Risk by Palisade. Janggam Adhityawarma. Matt Rhinehart. Brandon Richardson. Craig Soper ... Any method - qualitative and/or quantitative for assessing the ... – PowerPoint PPT presentation

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1
• Matt Rhinehart
• Brandon Richardson
• Craig Soper
• Don Yap

2
Introduction
• Risk Analysis
• Any method - qualitative and/or quantitative for
assessing the impacts of risk on decisions.
• Many Risk Analysis methods blend both qualitative
and quantitative techniques.
• The goal of these methods is to help the
decision-maker choose a course of action.

3
Features
• Uses Monte Carlo simulation to take all possible
outcomes into account.
• The result is a distribution of possible outcomes
and the probabilities of getting those results.
• One of the strengths of Monte Carlo simulation is
that it produces enough data to create accurate
graphs. Histograms, cumulative curves, area and
line graphs, etc.

4
Features
• Create a summary report of results using the
Quick Report command.
• Report in Excel containing a histogram,
cumulative curve, Tornado graph, and summary
statistics.
• Sensitivity Analysis
• Determines which input distributions have the
biggest impact on the outputs.
• Scenario Analysis
• Identifies combinations of inputs - or scenarios
- which lead to output target values.

5
_at_Risk Features
6
Risk Analysis with _at_RISK
• Risk Analysis in _at_RISK is a quantitative method
that seeks to determine the outcomes of a
decision as a probability distribution.
• In general, Risk Analysis with _at_RISK encompasses
four steps
• 1. Develop a Model - Define the problem or
situation in an Excel worksheet format.
• 2. Identifying Uncertainty - Determine which
model inputs are uncertain, and represent those
using ranges of values with _at_RISK probability
distribution functions. Identify which result or
output of the model to analyze.
• 3. Analyzing the Model with Simulation - Run
the simulation to determine the range and
probabilities of all possible outcomes for the
outputs identified.
• 4. Make a Decision - With complete information
from analysis and preferences, make a decision.

7
Developing a Model
• Model construction is based on spreadsheet data
• Examples
• Launching a new product - impact of potential
profits
• Potential pollution effects of a new factory on a
river
• Effectiveness of a new drug therapy on an illness
• Exploratory site for oil wells

8
Identifying Uncertainty
• Determine which inputs in your model are
uncertain
• Probability distribution functions to represent a
range of possible values
• _at_RISK takes uncertainty into account

9
Risk Distribution
10
RISKview
11
Best Fit
12
Analyzing the Model with Simulation
• Capabilities
• Specify the number of iterations
• Update the spreadsheet in real-time numerically
or graphically
• Control the convergence
• Use the default settings - _at_RISK will automate
• Provides a range of possible outcomes and
probabilities of occurrence

13
Simulation-Optimization
14
Sensitivity Analysis
15
Make a Decision
• Allows multiple simulations to be run
back-to-back.
• Correlate Inputs for More Accurate Models.
• Statistics and Graphing
• Custom Applications

16
Correlation
17
Graphing and Reporting
18
Model - Results
19
Risk Applications
20
Enhanced Editions
• _at_Risk Professional
• Integrated BestFit
• Goal Seek
• Stress Analysis