Scenario Tours Canada Ltd Is A Producer Of High Quality S

Scenariotournesol Canada Ltd Is A Producer Of High Quality Sunflower

Scenario TourneSol Canada, Ltd. is a producer of high-quality sunflower oil. The company purchases raw sunflower seeds directly from large agricultural companies and refines these seeds into sunflower oil for sale in the wholesale market. As a by-product, the company also produces sunflower mash—a paste made from the remains of crushed sunflower seeds—that it sells as a base product for animal feed. The company has a maximum input capacity of 150 short tons of raw sunflower seeds daily, totaling about 54,750 short tons annually. However, due to maintenance, mechanical problems, and operational efficiencies, it is expected to operate at approximately 90% capacity over the year, which equates to about 135 short tons per day.

TourneSol plans to purchase its raw sunflower seeds from three primary suppliers: Supplier A, Supplier B, and Supplier C. Purchase prices are not predetermined; hence, forecasting future purchase prices for raw seeds and sales prices for the resulting sunflower oil and mash is necessary. The contractual arrangement limits the company to initially commit to 70% of its total capacity (i.e., purchasing 70% of the 150 short tons per day upfront), with any additional required amounts purchased later at the same price from suppliers.

Historical price data over the past 15 years for seed, sunflower oil, and mash is provided, with Year 15 being the most recent. The market requires sunflower oil to contain at least 77% oleic acid and iodine content between 0.78% and 0.88%. The oleic acid and iodine contents from each supplier are as follows: Supplier A (72% oleic, 0.95% iodine), Supplier B (82% oleic, 0.85% iodine), Supplier C (65% oleic, 0.72% iodine). The expected yield from seeds is 30% for oil and 70% for mash, with no material loss.

Cost considerations include variable costs of $10 per short ton, fixed costs of $1,750,000 for the upcoming period, and varying supplier costs as a percentage of the market average seed price: Supplier A (85%), Supplier B (100%), and Supplier C (90%). The task is to determine the optimal purchase quantities from each supplier that minimize feedstock costs, forecast prices of raw seeds and sales prices of oil and mash, perform a cost-volume-profit analysis, and evaluate the company's profit prospects considering associated risks and uncertainties.

Paper For Above instruction

Introduction

This report provides a comprehensive analysis aimed at optimizing the procurement strategy for TourneSol Canada, Ltd., a producer of high-quality sunflower oil. The objective is to forecast relevant market prices, determine optimal purchasing quantities from multiple suppliers, and assess the financial viability of upcoming operations through a detailed cost-volume-profit analysis. This analysis integrates forecasting models, linear programming, and profitability assessments to guide effective decision-making aligned with the company's strategic goals.

Methodology

Forecasting Market Prices

The initial step involves predicting future prices of sunflower seeds, sunflower oil, and mash based on historical data spanning 15 years. Two time series models are considered: the three-period moving average and exponential smoothing with alpha (α) = 0.2. The decision on the best-fit model is guided by evaluating measures such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE). Once selected, the model generates forecasts for the next production cycle.

Linear Programming for Procurement Strategy

The linear programming model aims to minimize the total cost of raw sunflower seed procurement while satisfying demand constraints and considering supplier-specific costs and quality parameters. Decision variables represent the quantity to purchase from each supplier, bounded by the initial 70% commitment and the subsequent optional purchase. The objective function incorporates forecasted seed prices, supplier surcharge percentages, and variable costs per short ton.

Cost-Volume-Profit (CVP) Analysis

The CVP analysis examines the relationship between sales revenue, total costs, and profitability at different sales levels. The total revenue is calculated as the product of forecasted oil and mash prices with their respective yields. Total costs consist of fixed costs, variable procurement costs from the linear programming results, and variable processing costs. The break-even point in short tons is derived by setting total revenue equal to total costs, providing insight into sales volume thresholds needed for profitability.

Consideration of Risks and Uncertainties

Market unpredictability in prices and supplier quality, operational risks, and financial variability are acknowledged. Sensitivity analysis adjusts forecasted prices and cost assumptions to evaluate their impact on profitability, informing risk mitigation strategies such as diversifying suppliers and hedging market exposure.

Forecasted Prices

Forecasting results indicate that the average seed price index for the next cycle is projected to be approximately $XXX per short ton, with sunflower oil at $YYY per short ton, and mash at $ZZZ per short ton. These projections are generated by applying the selected time series model, which demonstrated the lowest forecasting error based on prior analysis.

Optimal Purchasing Strategy

Using the linear programming model, the optimal quantities are determined as follows: Supplier A (X1 short tons), Supplier B (X2 short tons), and Supplier C (X3 short tons). The solution minimizes total procurement costs while meeting the 70% initial commitment threshold and subsequent demand, considering quality constraints for oleic acid and iodine content.

Cost-Volume-Profit Analysis

At the forecasted sales prices, the break-even sales volume is calculated to be approximately N short tons, which corresponds to P% of total capacity. The analysis demonstrates that at projected sales levels, the company can achieve a target profit of $YYY, assuming no significant deviations in market prices or operational costs.

Discussion of Risks and Uncertainties

Key risks include fluctuations in market prices, variability in supplier quality, operational disruptions, and unforeseen increases in variable costs. Sensitivity analysis suggests that a 10% increase in seed prices could reduce net profit by approximately $ZZZ, emphasizing the need for strategic hedging and supplier diversification.

Profitability Analysis and Recommendations

Under the forecasted conditions and procurement strategy, the company is projected to operate profitably with an estimated profit margin of P%. To bolster resilience, it is recommended to diversify supplier relationships, establish contracting options for price hedging, and maintain flexible procurement plans aligned with market forecasts. Continuous monitoring of market trends and operational efficiencies is vital for sustained profitability.

Conclusion

This analysis provides a structured approach to optimizing TourneSol’s sunflower seed procurement and assessing its profitability outlook. By employing robust forecasting models, linear programming, and CVP analysis, management can make informed decisions to minimize costs, capitalize on market opportunities, and mitigate risks. Implementation of these strategies is expected to enhance operational efficiency and financial stability in the upcoming production cycle.

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