Grains Research and Development

Date: 01.07.2013

Profit strategies for climate variability

Author: Tim McClelland, Yield Prophet coordinator, BCG

A BCG project examining farm profitability and risk has gone some way to showing growers that it is possible to take control of their farm business and make better business decisions, even when faced with unfavourable climatic conditions.

The project had growers take part in workshops that investigated how farm profitability and risk were affected by a range of variables including climate, soil type, enterprise mix (crops/sheep), level of debt, machinery investment and land purchase.

A hypothetical farm was constructed and a range of best and worst-case scenarios/options were analysed and discussed. The approach challenged participants’ understanding of the financial parameters necessary for this analysis and allowed comparisons with their own farms.


Key points

  • When conducting whole-farm analysis, it is essential that
    your outputs are real and reflect the actual situation
  • Reducing variable costs in response to a consecutive run
    of poor seasons can significantly reduce losses; further
    savings can be made if the rotation is adjusted to remove
    risky or expensive crops
  • Mixed cropping/livestock systems are better able to withstand
    a run of poor seasons – although in better seasons (>decile 5)
    livestock can reduce the potential profit
  • If available, leasing allows businesses to expand while
    still maintaining low exposure to risk
Table 1: Case-study farm assumptions
Location
Nhill/Woorak
 Climate records
 Nhill
 Farm size
(arable land)
 1500ha
 Soils  33 per cent light /
66 per cent heavy
 Light land value
 $2000/ha
 Heavy land value
 $2750/ha
Cropping system
(land allocation)
 Wheat = 40 per cent
Barley = 25 per cent
Vetch fallow with
opportunistic hay = 15 per cent
Canola = 10 per cent
Lentils = 5 per cent
Beans = 5 per cent
No livestock
 

In setting up the hypothetical farm, the group selected a location (Nhill/Woorak in Victoria’s western Wimmera) and made assumptions about machinery and equipment, overhead costs, crop inputs and crop yield potential that reflected ‘typical’ practice in their district (Tables 1 and 2). Not all details are reported but are available on request.

An analysis of cumulative cash flow revealed that basing farm budgets on an ‘average’ season was potentially problematic, with some regions more prone to below-average seasons. To better reflect the performance of the farm business under good and bad conditions, and to assess any associated risk, the case-study farm was analysed over different rainfall deciles and different seasons.

Findings

The project delivered key outcomes relating to:

  • assumptions used to devise budgets and farm plans;
  • the value of altering rotations and practices according to the season;
  • the impact of a livestock enterprise on business risk and profit in good and poor seasons; and
  • the impact of farm expansion on business sustainability, profitability and risk.

As the workshops progressed, it became evident that seasonal conditions had a significant impact on farm profitability. However, a business’s ability to withstand climate variability was largely influenced by how managers responded on a practical level and how they chose to structure their businesses.  The case-study farm accumulated $2.5 million in five years of good growing conditions (best-case scenario) but reached a deficit of over $1 million after five years of poor seasons (worst-case scenario). The case-study group, however, deemed these results unrealistic: the ‘best-case scenario’ was too positive and the ‘worst-case scenario’ too negative.

Table 2:
 Crop  Light soil
Heavy soil
 Decile 3
Decile 5
Decile 7
 Decile 3
Decile 5
Decile 7
 Wheat (t/ha)
 1.50  2.75  4.00 1.00
 2.50 5.00
 Barley (t/ha)
 1.50  3.00  4.00  1.00  3.00  5.00
 Vetch hay (t/ha)
 2.00  2.50  3.00  2.00  2.50  3.00
 Canola (t/ha)
 0.75  1.50  2.50  0.50  1.50  2.25
 Lentils (t/ha)
 0.50  1.50  2.00  0.25  1.50  2.50
 Beans (t/ha)
1.00
 1.75  3.00  0.75 1.75
 3.00
 

The group felt that grain prices used for the case study (based on the average trend from 2000–10) did not accurately reflect reality. It was also suggested that while the impact of seasonal conditions on the farm business’s cash position could not be denied, farm managers in real-life would be more responsive to the preceding season and current climatic outlooks and alter practices to mitigate potential losses.

This highlighted the importance of basing output projections on fact, and ensuring that assumptions reflect actual situations when conducting whole-farm analysis.

After adjusting the best-case scenario to use average grain prices (deemed to better reflect reality) the cumulative cash flow was more realistic, with the business reaching less than $2 million after five years. However, it was noted that the best-case scenario is a rare event.

As a result, the project focused the group’s attention on the worst-case scenario, with the understanding that under the best-case scenario the business would do well under any circumstances.

Analysis of the case-study farm demonstrated that any business that did not react to a run of poor seasons put itself at significant risk.

Participants were able to see how small adjustments made to business agronomics and structure could have a significant impact on the business’s resilience, and its ability to survive a poor period. Such adjustments included reducing fertiliser, fungicide and chemical use, delaying repairs and maintenance, and removing risky and expensive crops from the rotation (Figure 1).

The project also showed the degree to which a livestock enterprise could positively influence the farm business, particularly in terms of reducing risk. Assuming a non-self-replacing sheep flock, and taking into account ‘fair’ assumptions (additional costs, labour and revenue), it was evident that a mixed-farming system in the environment under investigation had a better capacity to withstand a consecutive run of poor seasons.

Discussion within the group found that livestock provided a consistent income irrespective of the season. This buffered the business against interest costs when consecutive losses were experienced.

However, the benefits from livestock only went so far. In better seasons (greater than decile 5) livestock had the potential to reduce profits. This was a result of less land being devoted to cropping.

Figure 1: graph

Figure 1: Worst-case (2005-09) cumulative cash flow
under altered business scenarios.

The final scenario focused on farm expansion, in this instance an additional 400 hectares of ‘heavy’ land, representing a 26 per cent increase in the size of the property.

Taking into account assumed associated costs including labour, contractors’ fees, overheads, repairs and maintenance and fuel and oil usage, the analysis revealed that purchasing additional land at the start of a run of poor seasons could put the business in serious jeopardy. The business net cash-flow deficit would be $1.1 million, slightly better than the baseline situation (see Figure 1).

Expansion was also considered under a range of business scenarios and compared in a ‘break-even’ season. This enabled participants to see the effect of purchasing as opposed to leasing land, incorporating livestock into the system and the difference between the purchase of heavy and light land.

From this investigation it was apparent that leasing provides a safer option for expanding a business. It gives the grower an opportunity to generate increased income under favourable conditions, but minimised losses if less than optimal conditions prevailed.

It was concluded that unless the business was in a strong position, leasing was the preferred option as it provided an opportunity to expand while still maintaining low exposure to risk. In reality, however, finding land available for lease is difficult, often forcing businesses to purchase.

Profitability and risk

The project allowed growers to understand how business decisions could affect both profitability and risk under a range of scenarios. While the hypothetical farm did not represent any individual farm, participants were able to relate the analysis to their own situation. In doing so, they gained a solid understanding of how farm and business practice changes could influence business profitability, risk and sustainability.

There were significant lessons about what had the greatest effect on business resilience, about taking advantage of better seasons, and about deciding on the best strategies for expansion.

The project was funded through GRDC’s Low Rainfall Collaborative Project as part of their Profit/Risk Management Initiative.

More information:

Tim McClelland,
03 5492 2787,
yieldprophet@bcg.org.au

www.grdc.com.au/GCTV

Read the full report at www.grdc.com.au/CaseStudy-ProfitabilityAndRisk-2013

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