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Swiss Milk Memo

Essay by   •  March 29, 2016  •  Case Study  •  1,090 Words (5 Pages)  •  1,793 Views

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Cougar consulting

to:

Yann Zweifelhofer, swiss milk s.a.

from:

matt ehrhardt, cougar consultant

subject:

Swiss milk s.a. distribution model

date:

September 20, 2015

Introduction:

Cougar Consulting would be pleased to conducted an analysis of Swiss Milk’s financial operations. The objective of this analysis is to formulate the optimal business model to maximize profit. Multiple strategies were evaluated to determine the optimal solution for Swiss Milk. We investigated individual farms ideal operating capacity, introducing coupons to increase demand, and a new shipping service from Farm A to Geneva. Quantitative analysis of the information provided to Cougar Consulting has allowed us to determine the most effective and efficient recommendation for maximizing the company’s profit.

Discussion:

The goal of this analysis is to maximize Swiss Milk’s profit by finding the correct distribution of milk. The optimal distribution of milk can fluctuate by the amount of milk distributed to the towns and the amount of milk produced at each farm. Linear programming is helpful when there needs to be interpretation of a complex, multi-variable business decision such as this one.  

The linear programming model used to analyze the inquiries by Swiss Milk was Solver in Microsoft Excel. Linear programming is used when trying to maximize profit or minimize cost with limited resources to help make business decisions. Solver is an example of this type of model that also provides a sensitivity report. A sensitivity analysis is a review of how delicate solutions are to changes in the data. In simple terms, it answers how the solution deviates resulting from changes in the objective function, resources available or added constraints to the problem. Overall, this model solves for an objective function that is subject to constraints, or limits. In this situation, Solver is appropriate because we are trying to determine the maximum profit with production constraints for Swiss Milk’s milk supply. Using linear programming is very useful, but must follow certain guidelines in order to properly analyze and interpret future profits.

There are four fundamental assumptions that must be true in order for a problem to be able to be represented by linear programming.  The four assumptions include certainty, linearity, divisibility and a single objective. The values of the variables must be correctly represented and do not change. Swiss Milk’s figures in both the objective function and constraints are known and certain. The constraints and objective function must be proportional and additive. Swiss Milk’s values of the constraints on the objective function are linear and they do not have any interactions between the effects of different activities. All variables must be continuous. Swiss Milk’s variables are real numbers, integers and divisible. Finally, there must be only one single objective to determine. Swiss Milk’s single objective function is to maximize profit.  

Excel Solver has provided the calculations needed to give a good recommendation to Swiss Milk. The report shows that the maximum profit Swiss Milk can generate is CHF 1080 per day given the amount of resources presently available. The sensitivity report shows that all the farms are producing milk at full capacity. Sheet 1 shows Lausanne and Nyon demands are not being met. Lausanne’s demands are not being met by 100kg while Nyon’s is 50kg. This can be seen by looking at the demand compared to the total production. Under the optimal solution, Geneva milk demands are fully satisfied and is also the most profitable town at CHF 560. This can be seen in Table 1: Current Total Profit.

An option to increase profits would be introducing coupons at a cost of CHF 15 per day in order to generate an increased demand by 100 kg/day in Geneva. Geneva currently has profits of 0.7CHF/kg, but is only receiving milk from Farm A. In order to make this feasible, Farm A would need to decrease its supply to another town, such as Lausanne, and increase its supply to Geneva. The total cost would then be the cost of the coupon as well as the decrease in profit from Lausanne. This would result in an increased daily profit of CHF 5. This can be seen in Table 2: Farm A Milk Transfer from Lausanne to Geneva.

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