Copyright © 2000, Decisioneering, Inc.
All rights reserved.
Risk Analysis and Monte Carlo Simulation
by Lawrence Goldman,
Decisioneering, Inc.
So you're new to the idea of risk analysis, and you've got a lot of questions.
What is risk?
What
do we mean by a "model?"
What exactly is Monte Carlo simulation?
Is anyone in your industry
using this technique?
This article is a simple overview to help you to understand what risk
analysis is and why Monte Carlo simulation has become an increasingly popular and necessary
technique for business analysis and forecasting.
What is Risk?
Uncertainty about a situation can often indicate risk, which is the possibility of loss, damage, or
any other undesirable event.
Most people desire low risk, which would translate to a high
probability of success, profit, or some form of gain.
For example, if sales for next month are above a certain amount (a desirable event), then orders
will reduce the inventory, and there will be a delay in shipping orders (an undesirable event).
If a
shipping delay means losing orders, then that possibility presents a risk.
Thus, there are two points to keep in mind when analyzing risk:
1. Where is the risk?
2. How significant is the risk?
Almost any change, good or bad, poses some risk.
Your own analysis will usually reveal
numerous potential risk areas: overtime costs, inventory shortages, future sales, geological survey
results, personnel fluctuations, unpredictable demand, changing labor costs, government
approvals, potential mergers, pending legislation.
What is a model?
Once you have identified the risks, a model can help you to quantify them.
Quantifying risk
means putting a price on risk, to help you decide whether a risk is worth taking.
For example, if
there is a 25% chance of running over schedule, costing you a $100 out of your own pocket, that
might be a risk you are willing to take.
But if you have a 5% of running over schedule, knowing
that there is a $10,000 penalty, you might be less willing to take that risk.
One very popular modeling tool is a spreadsheet such as Microsoft’s Excel.
If you only use
spreadsheets to hold data--sales data, inventory data, account data, etc., then you don't have a
model.
Even if you have formulas that total or subtotal the data, you might not have a model.
A model is a spreadsheet that has taken the leap from being a data organizer to an analysis tool.
A model represents a process with combinations of data, formulas, and functions.
As you add
cells that help you better understand and analyze your data, your data spreadsheet becomes a
spreadsheet model.