Clevity Blog - Assessing Your Profit Risk Due to Volatility

Assessing Your Profit Risk Due to Volatility

Assessing Your Profit Risk Due to Volatility

Oftentimes in business, we are forced to live with uncertainty.  Really, nothing is certain, but even moreso certain volatile costs like gasoline, produce and currency exchange rates.  For example, a quick look at the following price of regular gas (credit: GasBuddy.com) shows some pretty heavy fluctuations between $1.70 and $2.80 per gallon for 2015 and 2016 YTD.

 

While this causes mixed feelings at the pump, imagine the headache that major businesses face when an upward or downward trend can make the difference between a more or less profitable year.  Clearly, volatility is not something that can be reasonably dealt with on intuition alone.  As an executive, it is easy to say that gas will float below $2.00 per gallon once again and profits will soar.  But what are the odds that $2.00 will actually happen?

Most of us don’t enjoy math, but we all do love food, so I will attempt to explain volatility risk with pizza.

Imagine you are an executive at a large pizza chain.  Your best selling pizza (for simplicity purposes) is a medium cheese pizza.  Also for simplicity, your material costs to make the pizza consist of dough, cheese, and sauce.

Let’s assume that dough and cheese costs rarely fluctuate up or down.  In fact, dough and cheese costs remained at $4.00 and $2.00 respectively for all of 2015 and are expected to remain the same for all of 2016.

Pizza sauce, however, is as volatile as gasoline, and fluctuated between $4.00 and $5.00 per pizza in 2015, with a definite upward trend heading into 2016.  At a sales price of $25 per pizza, this amounts to a total material profit of $15 (60%) at the beginning of 2015 dropping to $14 (56%) by the end of 2016 for a decrease of 4%.  At about 160,000 pizzas sold, this amounted to profits of almost $100,000 less than expected.

Sauce_Volatility

Your colleagues are very optimistic that pizza sauce prices will level out to begin 2016, following the unprecedented increase of 2016.  Therefore, they are forecasting your material margin to remain at 56% for January 2016.  However, given the upward trend, this does not settle well with you and you want to assess the risk associated with this assumption.  What can you do?

One approach would be to perform a Monte Carlo simulation to determine the likelihood that your margins exceed a given percent based on the likely fluctuations in pizza sauce.  Simply put, we can run a simulation of hundreds or thousands of possible outcomes of margin percentage given the likely fluctuations in pizza sauce.

In 2015, we saw our pizza sauce costs increase monthly by an average of 2.6%, with a standard deviation of 0.05.  Assuming a normal distribution, we generated 1,000 random possible outcomes for pizza sauce increases (or decreases) in January 2016.  As you can see from the below distribution, there were in fact numerous outcomes where margin did, in fact, reach your colleagues’ estimate of 56.0%.  To be exact, 476 of the 1000 outcomes reached 56.0% or higher margin.

MonteCarlo_Distribution

 

However, let’s look at this another way. In the below chart, we have rearranged the data to show the percent likelihood of each threshold.  In this view, we see that we only have a 48% chance of reaching our forecasted 56.0% margin.  However, we can say with 84% certainty that we will reach a 55.0% margin, and with 94% certainty that we will reach 54.5% margin.

MonteCarloResults

Using this method, you are now armed with the ammunition you need to contest the 56.0% margin forecast.  As an executive, do you feel comfortable betting your company on 48% odds?  Or would you rather work with 90% or better odds while focusing on other pieces of your business that are more under your control?

The answer is different for all types and sizes businesses, but the key takeaway is that you should not move forward with decisions without understanding the risk.

What risks does volatility pose for your business?  We would love to see your answers in the comments.

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