Optimum Pricing Strategy For Turnsol Company | Sunflower Oil Production

Forecasted Prices of Sunflower Seed, Oil, and Mash

The report gives an idea about the average market price of the sunflower oil seeds that are required to produce the oil. The price forecast figures, the price of raw materials and the optimum strategy that would be required to buy the raw materials are given in the report. The company buys the raw sunflower seeds from the growers. There are 3 suppliers from whom the Company Turnsol buys the sunflower seeds. The purchase prices of the seeds will be forecasted on the basis of purchase prices of raw materials. The Company produces oleic oil from the sunflower seeds. The oleic acid content varies according to the sunflower seeds. The optimum strategy for the production of oleic acid has to be chosen from the oleic acid content of the sunflower seeds of each supplier. The variable production cost and fixed cost of the company are also given. The problem is to determine the cost volume price analysis for the realization of profit of the company.

The objective of the study is to determine the profit of the company in the next production cycle. The Turnsol Company is a sunflower oil producing company. They prepare different products that are derived from the sunflower oil. The 15 years prices are obtained for the average prices of the seeds, oil and mash are given.

 The average prices are to be determined from these datasets. The data is a time series data. A time series analysis has to be performed in order to determine the average. The moving average method or the exponential smoothing method can be used for determining the parameters of the distributions (Box et al., 2015).The particular method for the study is to be decided by the method of standard method of error. The equation has to be fitted for the study should have a smaller value of error sum of squares. The error sum of squares for the variable average price index of seeds by the method of moving average is 2268.7 while that for the moving exponential smoothing method is 3921.964. Therefore, moving average method would be appropriate for the study. The forecasted values for the average price of seeds are given in the following table.

Table: Observed and forecasted values of time series

(Source: Created by author)

The regression equation obtained by the method of moving average is given below:

• Y = 98.2918 + 28.8465*x.

The average value of the seed price for the 16^th year obtained from the regression equation is 559.8359.

Linear Programming Problem to Minimize the Cost of Raw Sunflower Seeds

The 3 year moving average method has been employed for the average prices of oil and mash as well. The forecasted value of oils by the method of 3 year moving average is given below:

Table: Forecasted values of Oil prices

(Source: Created by author)

The regression equation from the above fitted values is given in the following table:

Table: Regression equation for prices of oil

(Source: Created by author)

The forecasted average prices of mash by three year moving average are given below:

Table: Forecasted Mash prices by the method of moving average

(Source: Created by author)

The moving average method is more appropriate in all three cases. In the last case, the exponential smoothing method could have been more appropriate as the error sum of squares is less in this case. The exponential method is more useful when the values in the final years are more important (Durbin & Koopman 2012).

The equation fitted by using the moving average method is given below:

Table: Regression equation for prices of mash

(Source: Created by author)

The following linear programming problem has been formulated to minimize the cost of raw sunflower seeds. The average price of the raw sunflower seeds has been forecasted for the 16^th year is 559.839. The sunflower seeds has been purchased from three suppliers A , B and C. Let X1 number of seeds be purchased from the first purchaser, X2 number of seeds be purchased from the second purchaser and X3 number of seeds be purchased from the third purchaser. The maximum price of the seed would be 559.839. The sunflower seeds are used to make oleic acid. The oleic acid content in the seeds varies according to the suppliers. The minimum amount of oleic acid content in the sunflower seeds should be 77%. Therefore, one has to decide the number of sunflower seeds to be purchased in such a way that the minimum amount of oleic acid content should be 77%. The iodine content should also vary between 0.78% and 0.88%. Therefore, the linera programming problem to find the optimum cost for buying the sunflower seeds has been formulated as follows:

• Z = 475.86X1 + 559.839X2 + 503.8551X3.

Subject to

• .72X1 + .82 X2 + .65 X3 <= 0.77
• .0095X1 + .0085X2+.0072X3 <=.0078
• .0095X1 + .0085 X2 +.0072 X3=> .0088
• X1 + X2+ X3 = 1.

The supplier prices are to be determined by solving the above linear programming problem. The optimum value that has been obtained by solving the above linear programming problem is 427.45. The optimum value of X1 is 0.39, the optimum value of X2 is 0.55 and the optimum value of X3 is 0.07.

The variable production cost is $10/short run. The fixed cost of production is $1750000. A cost volume analysis has been done by calculating the yields of the forecasted sunflower oil production. The effective cost per short run has been obtained by dividing the total cost of production that has been obtained in the previous problem. The total volume assumed in the previous assignment is 1. Therefore, the average cost of production is $427.45.

The average price of the mash as obtained by fitting the moving average method is $1633.434 and the average price of mash is $9002.468. The probability of yield of oil from the sunflower seeds is 0.3 while that of the mash is 0.7. Therefore, the effective selling price for the product would be 1633.434*0.3 + 9002.468*0.7 = 6791.7578.

Conclusion:

The report gives an idea about the optimum pricing of oil and seeds for the company Turnsol. The prices of seeds have been determined by the moving average method. The prices of oil and mash are also obtained by this method. The optimum pricing strategy and the number of seeds to be purchased from each of the supplier is obtained by solving a linear programming problem. A cost volume price analysis has also been done in order to determine the optimum pricing strategy. The expected selling price has been determined from the average prices of oil and mash that has been obtained by time series analysis.

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Chatfield, C., 2016. The analysis of time series: an introduction. CRC press.

Durbin, J. & Koopman, S.J., 2012. Time series analysis by state space methods (No. 38). Oxford University Press.

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