Using the “profitability tree” to diagnose the causes of low

When the consultant is considering a client’s business, he goes to the top of his diagnostic tree first in terms of profitability. He knows that what the client does is influenced by his or her goals, but he puts this to one side initially. He considers the farm business as if it was a straight business owned by a company and he stated that there are two things that are important to a company: 1) profitability and 2) shareholder wealth. Working back from this he considers the factors that affect profitability and what are the “key” measures of profitability. As such, he starts off looking at the key measures of profitability and then he will work down his “profitability tree” or diagnostic tree reviewing the other drivers and measures that are of lesser importance. The consultant stated “That helps [his diagnostic tree and knowledge of the key drivers of profitability], I mean like I say, I always keep in the back of my head what is the real important relationships, so that I don’t get lost”. He suggested that if one was training a young consultant, it would be important that he was taught these relationships and to think in terms of a “diagnostic

tree” for assessing the profitability of a client’s farm. This is particularly

important these days because of the range of farm system types and because “there is always many different ways to get a good profit”. Using this approach, the consultant draws logical conclusions about what is influencing the profitability of his client’s business.

The consultant’s process also highlights the importance of the context and its influence on profitability. At the top of the diagnostic tree is “return on assets” which is a function of “operating profit per hectare” and the “value of the

assets per hectare” (Figure 13). The consultant then looks at the next level

down in his “diagnostic tree” and the drivers of operating profit per hectare are

“gross farm income per hectare”11_{and “operating expenses per hectare”.}

From this, he then looks at the drivers of these and breaks them down into their components and so-on down the diagnostic tree. For example, gross farm income per hectare is a function of net milk income per hectare, net stock sales per hectare and other dairy income per hectare. Net milk sales per hectare is a function of milksolids production per hectare times the average milk price. Milksolids production per hectare is a function of milksolids per cow times

stocking rate. As the dotted lines in the diagnostic tree indicate, the consultant can continue down the diagnostic tree to further identify other lower level drivers of profitability on the farm.

Figure 13. The consultant’s diagnostic tree for profitability.

The diagnostic tree for profitability can be separated into different

components in different ways to allow the consultant to consider profitability.

For example, the consultant may break the income and expenditure down into units of per kilogram of milksolids (Figure 14). He used the example of a farmer who had average operating expenses of $4.50/kg MS, but produced 1500 kg MS/ha, 700 kg MS/ha above the average for the district. For a year where gross farm income is $5.50/kg MS, this farm would generate an operating profit per hectare of $1500/ha. The consultant contrasted this farm with another lower producing farm that also had average operating expenses per kilogram of milksolids of $4.50/kg MS. If operating expense per hectare was used as the sole indicator of profitability, farms 1 and 2 would be expected to have a similar level of profitability. However, the latter farm only produced 800 kg MS/ha, the average for the district, at a gross farm income of $5.50/kg MS. This generates an operating profit per hectare of $800/ha. As such, although the two farms have the same operating expenses per kilogram of milksolids, the first farm is

Return on assets Operating Expenses/ha Gross Farm Income/ha Asset Value/ha Operating Profit/ha Net milk income/ha Net stock sales/ha Other dairy income/ha Milksolids per ha Average milk price Milksolids per cow Stocking rate

much more profitable ($700/ha) because it has above average milksolids production. The consultant also contrasted the first farm with another farm that had a below average cost of milk production of $4.00/kg MS, but only produced 800 kg MS/ha, the average for the district. If an advisor had used the cost of milk production as the sole indicator of profitability, he would have identified the third farm as the most profitable. However, the first farm generates an operating profit per hectare that is $300/ha higher than the third farm because of the higher level of milksolids production. As such, the consultant is concerned that farmers and some advisors focus on partial measures of profitability such as cost of milk production or milksolids production per cow. Such measures are partway down the consultant’s diagnostic tree and are often not good indicators of overall profitability.

Figure 14. Diagnostic tree for profitability – using per kilogram milksolids indicators.

The consultant identified that the following financial factors were often the causes of low profitability: 1) low gross farm revenue per hectare, and/or 2) high farm working expenditure per hectare, or a high cost of milk production. These in turn lead to a low operating profit margin. He stated that a key factor that influences profitability is gross farm revenue per hectare. This can vary between years because of milk price and as such the key driver of gross farm revenue is milksolids production. The consultant points out that there are two sides to profitability, “firstly how much am I earning and secondly, how much am I spending”? As such, if gross farm revenue per hectare is low on a client’s farm there may be an opportunity to increase milksolids production. However, the consultant stressed that he has to be careful because it is a relative benchmark (Gross farm revenue does not take

Operating Profit/ha Gross Farm Income/ha Operating Expenses/ha Operating Expenses/kg MS Milksolids per ha Gross Farm Income/kg MS Milksolids per ha

into account the cost of producing the milk) and it is generated from farm data that covers a wide range of “landscapes” and different “farm types”. As such, a client might only be achieving a gross farm revenue per hectare that is about average, but this might be quite good because he has a difficult farm (e.g. poor soil types and/or climate).

On the other side of the equation, another cause of low profitability is the farm working expenditure per hectare. The consultant looks at this benchmark and he also looks at the cost of milk production ($/kg MS). However, he notes that the latter indicator is a double edged sword because it may be driven by the level of milksolids production and/or the client’s cost structure because of the enumerator/denominator effect. So a farmer could have average costs (per hectare), but a low level of milk production so that he has a high cost of milk production per kilogramme milksolids or he could have high farm working expenditure per hectare and an average level of milk production to end up with the same level of profitability. As such, he needs to determine if the problem is due to an average cost structure and a low level of milk production or a high cost structure and an average level of milk production or good levels of milk production and very high costs. This information starts to tell the consultant about the relativities in terms of costs and milk production.

Gross farm revenue in effect primarily reflects milksolids production on a farm because 90% of the income normally comes from milk sales unless the client has an abnormally high level of livestock sales. As such, the consultant’s concern with this indicator is around the client’s level of milk production relative to his bundle of physical resources. The consultant would not expect the same level of milk production from a farm in Eketahuna as compared to a farm in the Kairanga. He also pointed out that the cost of land per hectare would be lower in Eketahuna as compared to the Kairanga, reflecting the productivity of the relative resource bundles. When considering profitability, and in particular,

return on assets, the consultant is often thinking, “is this a good investment” over the medium to long-term? The consultant may also look at operating profit margin. It will indicate the proportion of profit that the client

is extracting from gross farm revenue, and as such it will indicate a low profitability problem. However, although this indicator tells the consultant that there is a profitability problem, it does not tell him what the cause of the problem is. It is then a matter of establishing whether it is because of low milk production per hectare, a high operating cost structure per hectare or a combination of the two. The consultant then just works down his diagnostic tree to determine the causes of the client’s low level of profitability.

This provides the consultant with a range of causes of low profitability:

1. Low levels of milk production for the farm’s bundle of physical resources 2. A high cost structure for the level of milk production

3. A combination of milk production and cost structure

a. An average cost structure and low levels of milk production

b. An above average cost structure for average levels of milk production

c. A high cost structure for good levels of milk production

d. A very high cost structure for very high levels of milk production.