Risky Business Farm Optimization Comparison - Analysis And Recommendations

Risky Business Farm Optimization Comparison.

Agribusiness in the modern world is faced with tough trade-off decisions as a farm management is forced to choose between sustainability and profit maximization. The choice between the two affects the techniques that the management will follow in subsequent important processes such as allocation of land, application of chemicals such as fertilizers and herbicides, farming techniques such as crop rotation and density of crop per land use among others. This report presents the analysis of the two scenarios developed from the virtual management of a farm through the Risky Business Farm Game that represents a similar farm decision dilemma. Two excel files from the two scenarios are analyzed. The first excel file is analyzed on the basis of Key Performance Indicators as it focuses on the maximizing of the profit of the farm while the second excel file is analyzed on the basis of observation and track of the salinity and the depth of water table with a focus on the sustainability of the farm. The goal of the analysis is to determine the different effect that decisions made by the management have on the sustainability of the firm in comparison to the maximization of the farm’s profit. The report seeks to recommend the optimal level of operation on the farm that can both provide high profits while keeping in mind the sustainability of the farm.

Unsustainability in agriculture was as a result of the introduction of commercialized farming that was introduced in the late 20^th century and is characterized by the heavy use of modernized farming methods and a focus on an industrialized production of food under the protection of the government (Bowler, 2012). This type of farming focuses on the maximization of profits. Profit maximization and sustainable farming seem to be a fierce tradeoff that a farmer must face during resource allocation. Key indicators of unsustainable farming include pollution of underground water otherwise known as table water through the use of inorganic fertilizers to increase production, facilitation of soil erosion and rising levels of salinity of the soils (Bowler, 2012). However, Johnson (2008) notes that with proper farm management and the utilization of agricultural economics and production economics, it is possible to develop an optimal use of land that both provides reasonable profits while at the same time maintaining sustainable land use practice.  A careful analysis of farm data over a significant period of time is necessary to obtain an optimal level of production that will guarantee both profit maximization and sustainable land use. A farm model is simulated using a computer-based game to demonstrate this possibility.

Risky Business Farm Game

Two scenarios are developed using the computer-based game; Risky Business Farm Game. The game involves the management of a farm with all the necessary operations and crop rotation in 9 paddocks. The processes undertaken during the management include sowing of crops, application of fertilizers, and facilitating the sale of the produce. The market and the climate are left to vary to model, in precise, the environment of a real farm. Two different scenarios that focus on sustainability and another one that focuses on profit maximization are processed and the results exported to an excel file for each of the scenarios. The results are explained on the basis of the Key Performance Indicators (KPIs) for profit maximization and the levels of the water table and salinity for sustainability. The KPIs chosen were after-tax profit, farm equity, the proportion and proportion variation between crop and pasture, gross margins of the different crops and the changes in prices of the commodity.

Scenario 2 recorded an average of $138,223.98 in profit after tax compared to $75,711 for scenario 1. The highest value was recorded in the year 2020 with a value of $359,601 for scenario 2 while the lowest least profitable year was 2017 at $0. For Scenario 1, the most profitable year was 2018 recording a profit after tax of $209,883 while the least profitable year was 2023 with a negative record of profit after tax of -$15,536.

The average farm equity for scenario 1 stood at $6,552,305.05 with a pick of $6,780,669 and a minimum of $6,117,028 in 2022 and 2017 respectively. On the hand scenario, 2 recorded an average of $6,681,709.71 over the years with a minimum of $6,117,028 in 2017 and a maximum of $7,215,617 in the year 2023.

Scenario 2 maintained a constant pasture crop proportion for all the years holding it 67% of the crop against a 33% of pasture with the exception of the year 2017 where it was at 22% of pasture and 78% of the crop. On the other hand scenario 1 was more dynamic having a 78%-22% crop-pasture proportion for the year 2017, then having a 78%-21% proportion of the same in years 2018 to 2020. In the year 2021 and 2022, the proportion is kept at 56% crop and 44% pasture while in the last year, it 67% of crops against a 33% of pasture.

The highest net profit margin recorded for scenario 1 is $1,223,327.33 recorded in the year 2024 while the lowest was recorded 2023 at $235,042.23. For scenario 2, 2024 recorded the highest net margin at $1,053,242.46 while the least net margin was recorded in the year 2023 at $258,386.14. Margins for 2017 are not included in this analysis.

Data Analysis

Prices are available for the five commodities; wheat, barley, canola, lupins, and peas. However, the prices may not be as useful as the other KPIs because they depend largely on the stage at which the commodity was bought, indicating some sort of future/forward contracts. For instance, there was a pre-seeding price, growing price and harvest price.

The state of Salinity and the water table level are used to measure the sustainability of the soil. Soils with lower salinity and lower water table levels are generally considered to be less useful than the soils that have improved salinity and water tables. These two indicators of sustainability are regulated by the planting of shrubs. Alternating of shrubs with lupins and legumes also plays an important role in

Among the many factors that are likely to influence the financial performance of a farm, one of them is a land allocation between livestock rearing and cropping. Research shows that livestock is likely to take up more space for production with lower returns as it is more easier to manage crops within a limited space than livestock (Sumner, 2014). This seems to be the case presented in Scenario 1. An analysis of the excel file for this scenario shows that years that had higher proportions in pasture farming recorded also recorded the lowest of profit after tax with the exception of 2021 which recorded  $131,466 with a 56%-44% crop-pasture proportions. However, this is after preceding a year that favored crops after which the profit after tax plums to negative.

A similar trend in profit after tax in relation to crop-pasture proportion is seen in scenario 2. However, there seems to be an optimal level for the proportion. For instance, in scenario 2, the proportion starts at 78%-22% then reduced to 67%-33% over the rest of the years. This seems to keep the profit after tax at fairly high levels for two years before it starts declining. This an indication that there are other factors other than the proportion of crop-pasture that have an effect of the KPIs of a farm.

Schurle & Tholstrup (2009) indicates that other factors such as a farms obligation are also likely to determine its net income. Farm management practices that give the farm a higher financial ability through lower debt and higher returns will lead to better after-tax profits (Schurle & Tholstrup, 2009). Analysis of Scenario 2 excel file indicate that profits after tax were increasing as the amount paid for the long-term loan was decreasing, an indication that there is a relationship between the financial obligation of a farm and its performance on profit after tax. This is, however, not the case with scenario 1.

Results and Discussion

However, performance will also depend on the specific Indicators one focuses on. For instance, total equity for the farm assumes an increasing trend for both scenarios except with a slight decrease in the last year of scenario 1. An explanation for this could be based on the varying proportions of crop-pasture proportions. We assume that a bigger proportion of pasture indicates more livestock which is recorded as an asset compared to crop sales which are recorded as revenue.

In addition, an uncertain factor such as climate also has an impact on the financial performance of the farm.  The variation of rainfall across the years could be the explanation of the variation in profits after tax even with a constant crop-pasture proportion. The uncertainty of market conditions as indicated through the price of commodities has also a significant impact on the profit after tax of the farm. Given the prices of the commodities range from depending on the stage of the commodity, forward and futures contracts can be used to reduce the uncertainty of the market. However, this means the farm will have to forgo possible higher future prices and hence lowering its revenue in the long run.

The salinity of the soil and the water table are good indicators of sustainability (Bowler, 2012). However, these sustainability indicators do not seem to have any immediate effects on the profitability of the farm. From the analysis of both files, the performance of all the paddocks seems to follow a similar trend irrespective of their depth of water table or saline levels in all the three financial indicators of cost, revenue, and gross margins. This could be attributed to the fact that the financial indicators of these paddocks are not tied to just one factor but a web of factors that are interlinked. A change in one factor is likely to affect another. For instance, if more money is put into improving the salinity levels of one paddock, lower resources will be allocated in the maintenance of another. The ultimate end result is lower revenue for the paddocks.

Shrubs and trees have a positive effect on the health of soils. Trees and shrubs use their deeper roots to reach deep soils and facilitate the transfer of water from soil to the atmosphere hence improving the aeration which in turn may regulate the salinity levels of the soil (Schilfgaarde, 1987). The simulation of the two scenario show that there is a constant improvement of the salinity level recorded in the soils of the lower two paddocks; Spring and Soak. At the same time, the water levels show an improvement in both scenarios. This is attributed to the tree aided upward movement of water from lower levels to upper levels of the soils which leads to better salinity levels in the upper soils (Schilfgaarde, 1987).  A similar cause effect is seen on the effects of legumes on the soils. It is observed that during the rotation of crops, the crops that succeed legumes perform better. This is attributed to the effect of legumes on soils. Mthembu, Everson, & Everson  (2017) note that legumes add nitrogen to the soil which is used by other plants especially cereals such as wheat as fertilizer. The crop rotation therefore, allows the soil health to improve for the next crops.

Conclusion

With modern farm management techniques, farms can make decisions that would optimize the operations of the farm without having to choose between profits and sustainability.  A farm management can ensure that it finds this optimum level of operation by adjusting the different factors that affect the Key Performance Indicators of profit maximization of the farm while at the same time keeping track of the state and the nature of the soil to ensure that the water table level and salinity levels of the soils are within manageable and recommended levels. The good thing is that by use of computer simulated games, farmers and farm managers can utilize computer games to determine this optimal level of operation before the implement it on the farms by studying indicators such as after-tax profit, farm equity, the proportion and proportion variation between crop and pasture, gross margins of the different crops and the changes in prices of the commodity.

For effective management of a farm, a balance is necessary to ensure that it is both profitable and sustainable. Although sustainability does not bring immediate results, in the long run, it will allow the farm to operate for longer periods which translates to prolonged revenue. From the analysis of the two scenarios, the following can be recommended:

• Farmers should utilize computer games to develop the necessary balance between sustainability and profit maximization
• Paddocks can help in the development of crop rotation which will help farmers to allocate the right crops to the right sections of the land.

References

Bowler, I. (2012). Sustainable Farming Systems. The GeoJournal Library, 169-187. doi:10.1007/978-94-017-3471-4_9

Johnson, G. L. (2008). Agricultural Economics, Production Economics and the Field of Farm Management. Journal of Farm Economics, 39(2), 441. doi:10.2307/1234162

Mthembu, B. E., Everson, C. S., & Everson, T. M. (2017). Tree legumes-temperate grass agroforestry system effects on inorganic soil nitrogen as ecosystem services provision for smallholder farming systems in South Africa. Journal of Crop Improvement, 32(2), 141-155. doi:10.1080/15427528.2017.1376239

Schilfgaarde, J. V. (1987). Forage and fuel production from salt affected wasteland. Agricultural Water Management, 12(4), 341-342. doi:10.1016/0378-3774(87)90008-4

Schurle, B., & Tholstrup, M. (2009). Farm Characteristics and Business Risk in Production Agriculture. North Central Journal of Agricultural Economics, 11(2), 183. doi:10.2307/1349106

Sumner, D. A. (2014). American Farms Keep Growing: Size, Productivity, and Policy. Journal of Economic Perspectives, 28(1), 147-166. doi:10.1257/jep.28.1.147