Risk taking's positive side
GroundCover™ Supplement Issue: 113 | 03 Nov 2014 | Author: Cam Nicholson
When we talk about farming risk most of us immediately think about the negative consequences stemming from a management decision gone wrong. But taking risks is also the path to rewards
To manage farming risk effectively we need to understand both the negative and positive consequences of taking risks.
Traditionally, we have calculated the anticipated profit from a particular farming decision by multiplying the expected average yield by the average price less the average costs. While this type of analysis is fine if we get the average values, in reality we rarely do!
To make this traditional analysis more meaningful we can include a ‘scenario analysis’ by testing our anticipated profit with some yield/price/cost values on either side of the average.
But the problem with most scenario analyses is that we still have no idea how often a particular value (average or otherwise) might occur; for example, will yield be higher than average two years in 10 or five years in 10?
In reality, the key profit drivers in agriculture – yield, prices and input costs – present as a range of values over time in response to seasonal and market conditions. By using the traditional ‘average’ method to calculate the anticipated impact of a decision we usually overestimate the profit and hide the volatility in those profits.
Managing risk is not about the middle or the expected. It is the opposite. It is what happens at the extremes that is important to farm profit. It is about managing for the inevitable poor seasons and, perhaps even more importantly, what we will do when we get a good result.
In Grain & Graze 2 we set out to get a better handle on farm business risk by using the @RISK software program to analyse how farm profits responded to a range and probability of likely prices, yields and costs.
We wanted to show:
- how extremes in yields, prices and costs influenced the range of farm profit over time (how high it could be and how low);
- how often these extremes occurred over time; and
- which of these variables contributed most to profit volatility and extremes.
With this information we were able to show workshop participants what their individual farm risk profile looked like and start the conversation about how management decisions changed this profile.
The @RISK analysis is more realistic than an ‘averages’ approach because it combines a value (how big or small)
with a likelihood (how often). This approach builds context and helps us understand exposure and risk (see Beware average prices).
Cam Nicholson, Nicon Rural Services,
0417 311 098
Region National, South
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