This document summarizes a presentation on using Monte Carlo simulation to improve forecasting processes. It discusses how single point forecasts do not adequately account for risk and uncertainty. Monte Carlo simulation involves running hundreds or thousands of simulations with random variables drawn from probability distributions. This allows forecasting outcomes over a range of possible scenarios. The presentation demonstrates applying Monte Carlo simulation to a company's financial model. It shows how key drivers like sales volume, material costs, and wages can be set as probability distributions rather than single values. Running the simulation provides a range of potential outcomes for metrics like net income and cash flow. It identifies the areas most impacting profits and cash, allowing management to better understand and mitigate risks.

1. the imitative representation of the functioning of one
system or process by means of the functioning of
another <a computer simulation of an industrial process>
SIMULATION

2. Injecting Certainty Into An Uncertain
Process
Webinar Presentation To The Members Of
“You can’t control risk, unless you measure it or model it!”
Using Monte Carlo Simulation to Improve Your Forecast Processes

3. The Landscape In Which We Plan
“There are known knowns. These are things we know that we know. There are
known unknowns. That is to say, there are things that we know we don't know. But
there are also unknown unknowns. These are things we don't know we don't
know.” Donald Rumsfeld
“If there's one thing that's certain in business, it's uncertainty.” Stephen Covey
“Information is the resolution of uncertainty.” Claude Shannon
“You can’t control risk, unless you measure it or model it!”

4. Why Do We Plan?
• You can’t get to where you want to go without a road map!
• You may have objectives for Net Sales, Net Earnings and Returns on Equity and/or Capital
Employed. How are they going to be achieved within the national or global economic
climate? In the next 6-12 months it is likely that we will see higher market interest rates;
investors seeking greater liquidity; and “lumpy” demand by customers.
• You may also have objectives for conserving Cash for future investments. How will this be
done?
• You have an obligation to your stakeholders to protect and enhance their interests.
“You can’t control risk, unless you measure it or model it!”

5. The Osborne Company
• Manufacturer of widgets
• Purchases partially assembled product
• Adds manufactured components
• Sells nationally
• 5 year old profitable company with Retained Earnings of $110,760
• C Corporation for Income Tax purposes
“You can’t control risk, unless you measure it or model it!”

6. Monday, August 15th
• Management staff meeting
• Attendees
• CEO
• CMO
• GM
• CFO
“You can’t control risk, unless you measure it or model it!”

7. Planning for next year begins
• CEO says
• Market dictates that we can’t change price
• Give me your forecasts of Unit Volume?
• CMO says
• Production line functioning well and positive reaction to new design
• 989,300 Units
• GM says
• Too high for shop to handle
• 950,000 Units
“You can’t control risk, unless you measure it or model it!”

8. CEO makes final call
• Let’s shoot for the moon. I say 995,000
“You can’t control risk, unless you measure it or model it!”
http://cliparts.co/clipart/183111

9. CFO is deep in thought
• How will he create a single financial projection with three disparate
projections of unit volume?
• No mention has been made of purchased assemblies required to
achieve those projections while maintaining inventory
• Minimum 685,000; maximum 700,000; most likely 690,000
• Sourced from several suppliers whose prices range from $.375 to $.48 cents
each depending on supplier availability
“You can’t control risk, unless you measure it or model it!”

10. General Manager interrupts CFO’s thoughts
• Possibility of an increase in the minimum wage
• 9 people in the shop
• 6 of them earn at the minimum wage of $8.25 per hour
• 1,896 production hours for each, without overtime, that I need to put an
hourly rate on
• What are the odds of an increase and to what amount?
• Group consensus is that there is a 30% likelihood of the minimum
wage going to $10.50 an hour
“You can’t control risk, unless you measure it or model it!”

11. CFO is rolling his eyes when CEO turns to him
• Take these figures that we have discussed and put together our most
likely case scenario
• We’ll meet again next Monday and go over what you come up with
• By the way, don’t forget about that mandatory $20,000 bank loan
repayment
• There should be no problem meeting that requirement based on the
numbers discussed, RIGHT?
• CFO says it appears that way but let me see what the numbers look
like
“You can’t control risk, unless you measure it or model it!”

12. CFO hurries back to his office
• He can’t wait to put pencil to paper
• He also has a glimmer of an idea that he would like to try, but
first he has to create the “most likely case scenario”
• He comes up with the following
“You can’t control risk, unless you measure it or model it!”

13. Assumptions for Most Likely Case
“You can’t control risk, unless you measure it or model it!”
Most Likely
Case
Estimates
Not
Considered
In Most
Likely Case

14. Income Statement
“You can’t control risk, unless you measure it or model it!”

15. Cost of Goods Sold and Direct Labor
“You can’t control risk, unless you measure it or model it!”

16. Balance Sheet
“You can’t control risk, unless you measure it or model it!”

17. Cash Flow Statement
“You can’t control risk, unless you measure it or model it!”

18. CFO Reaction to Current Forecasting Process
• Satisfied
• Mandatory Debt Repayment is barely covered
• Dissatisfied
• Did not address wide discrepancy in unit volume forecasts
• Did not address wide discrepancy in raw material unit purchases
• Did not address wide range of prices for the raw materials
• Did not even consider the 30% likelihood of an increase in the minimum wage
• Conclusion: We need a forecasting process that will give us sensitivity
of key drivers and probability of outcomes!
“You can’t control risk, unless you measure it or model it!”

19. Risk Modeling: The Old Way
• Single Point Estimates
 Do you make multi-million dollar decisions based on 1 number?
• 3-Point Estimates or Scenario Analyses
 Do you make multi-million dollar decisions based on 3 numbers?
• Manual What-if Analyses
 Will you mandate that your analysts run hundreds or thousands of scenarios for your million dollar
decision? How much will that cost and will you get those analyses in time?
******************************************
What if something changes? What if many things change, and change at different times?
Managing risk then becomes cumbersome, time consuming, and error laden.
“You can’t control risk, unless you measure it or model it!”

20. Risk Modeling: The New Way
• Use Probability Distributions
The direct result of Monte Carlo simulations, which are necessary for making
competitive business decisions and for balancing risk and return.
• Probability distributions furnish you with the full range of possible
outcomes, how likely those outcomes are to occur, and identify those
items that impact your bottom line most significantly and by how
much.
“You can’t control risk, unless you measure it or model it!”

21. A Bright Idea ● Use Monte Carlo Simulation
“You can’t control risk, unless you measure it or model it!”
What is Monte Carlo simulation?!?!
It’s really not rocket science.
At its core, Monte Carlo simulation is a virtual experiment – repeated
hundreds, thousands, even millions of times – all the while generating
random samples, bound by a set of parameters that you define, from
each repetition of that experiment.
Those random samples are collected and then organized and analyzed to
help you understand the behavior of a simple or complex system or
process.

22. CFO starts with the model he just created
• He uses Monte Carlo simulation software which is commercially available.
• He gives effect to the discrepancies missing from that scenario by assigning probability
distributions to the key model drivers.
• You may already be familiar with the normal or “bell shaped” curve distribution. There
are many others.
• Which distribution to use is a question that always comes up.
• Historical data, expert opinion or management “gut feel” are all acceptable answers to that
question
• With available historical data, it is possible to use software to analyze the data and determine the
most appropriate distribution to use
• In this case, the CFO is using his own judgement
“You can’t control risk, unless you measure it or model it!”

23. Let’s move over to the Excel Model and run a
simulation
“You can’t control risk, unless you measure it or model it!”

24. Net Income Observations
• 90% of the results fall between a Net Loss of $16,303 and a Net
Income of $53,351
• 10% of the results are outside of these values
• The single most damaging impact to Net Income was the Unit Price of
Raw Material Purchases
“You can’t control risk, unless you measure it or model it!”

25. Net Change In Cash Observations
• Model suggested that the company could really lose its shirt cash-
wise, with 90% of the results falling between a cash shortfall of
$62,840 and a cash gain of only $6,814. With all of the results
considered, the cash flow ranges from a negative $94,146 to a
positive $18,391. The mean cash flow is a negative $26,522.
• The $20,000 mandatory debt repayment could be in serious jeopardy
• In fact, the bank and mortgage holder might be uncomfortable
enough to foreclose against the company
“You can’t control risk, unless you measure it or model it!”

26. Conclusions
• Single point presentations do not provide an in depth picture of risk. Using Monte Carlo
simulation gives you much greater insight into an uncertain future and points the way to areas
where your risk can be mitigated.
• If you have not begun to collect history, it is a good thing to do. The past can be a useful resource
for selecting the right probability distribution.
• The use of statistical techniques like Monte Carlo simulation can actually support gut feel and
lead to more confidence and better, more insightful forecasts in the future. In the example shown
here today, it led to the structuring of fixed price contracts with the company’s raw material
providers.
• Thank you for your time and attention
“You can’t control risk, unless you measure it or model it!”

27. Who Are We?
With more than 30 years of experience in utilizing
technology to assist in management decision making, Jerry
Scherer, a member of FENG, focuses on changing corporate
culture to embrace stochastic rather than deterministic
modeling. As a financial officer at a Fortune 200 company,
Jerry utilized Monte Carlo simulation and optimization in the
management of a $1.1 Billion dollar Revolving Credit
portfolio. He now builds risk models for clients.
JB Scherer Consulting Group LLC
(847) 835-1175
januerry@Comcast.net
www.jbschererconsultinggroup.com
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“You can’t control risk, unless you measure it or model it!”