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© Mcgraw-Hill Companies, 2008 Farm Management Chapter 12 Whole-Farm Planning.

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Presentation on theme: "© Mcgraw-Hill Companies, 2008 Farm Management Chapter 12 Whole-Farm Planning."— Presentation transcript:

1 © Mcgraw-Hill Companies, 2008 Farm Management Chapter 12 Whole-Farm Planning

2 © Mcgraw-Hill Companies, 2008 Chapter Outline What Is a Whole-Farm Plan? The Planning Procedure Example of Whole-Farm Planning Linear Programming Other Issues

3 © Mcgraw-Hill Companies, 2008 Chapter Objectives 1.Show how whole-farm planning differs from the planning of individual enterprises 2.Learn the steps and procedures to follow in developing a whole-farm plan 3.Understand the uses for a whole-farm plan and budget 4.Compare the assumptions used for short- run and long-run budgeting 5.Introduce linear programming as a tool for whole-farm planning

4 © Mcgraw-Hill Companies, 2008 What Is a Whole-Farm Plan? A whole-farm plan is an outline or summary of the type and volume of production to be carried out on the entire farm and the resources needed to do it. When the expected costs and returns for each part of the plan are organized into a detailed projection, the result is a whole-farm budget.

5 © Mcgraw-Hill Companies, 2008 The Planning Procedure Review goals and specify objectives Inventory resources Identify enterprises and technical coefficients Estimate the gross margin per unit Choose the enterprise combination Prepare a whole-farm budget

6 © Mcgraw-Hill Companies, 2008 Resources Land: total number of acres, types of land, fertility levels, climate, potential pests, tenure arrangements and leases, etc. Buildings: number, type, condition Labor: quantity and quality Machinery: number, size, and capacity Capital: short-run and long-run availability Management: age, experience, and past performance Other resources: markets, quotas, specialized inputs

7 © Mcgraw-Hill Companies, 2008 Technical Coefficients The technical coefficients for an enterprise indicate how much of a resource is required to produce one unit of the enterprise. Technical coefficients are important in determining the maximum possible size of enterprises and the final enterprise combination.

8 © Mcgraw-Hill Companies, 2008 Estimating Gross Margin Enterprise budgets, discussed in detail in Chapter 10, are important tools for farm planning. Enterprise budgets provide estimates of gross margin, or returns above variable costs.

9 © Mcgraw-Hill Companies, 2008 Choosing the Enterprise Combination Managers want to find the combination of enterprises that will provide the highest amount of profit through the best use of the farm’s limited resources. Linear Programming is a mathematical technique that can be used to find the optimal combination of enterprises.

10 © Mcgraw-Hill Companies, 2008 Example of Whole-Farm Planning The following example will illustrate the process of whole-farm planning. The objective of the manager is to choose the combination of crop and livestock enterprises that will maximize total gross margin.

11 © Mcgraw-Hill Companies, 2008 Table 12-1 Resource Inventory for Example Farm

12 © Mcgraw-Hill Companies, 2008 Table 12-2 Potential Enterprises and Resource Requirements

13 © Mcgraw-Hill Companies, 2008 Table 12-3 Estimating Gross Margin

14 © Mcgraw-Hill Companies, 2008 Enterprise Combination for the Example The procedure for choosing the enterprise combination will be discussed shortly. The results of the process are that the manager will choose to produce 200 acres of cotton and 200 acres of wheat on Class A land, 150 acres of milo on Class B land, and 100 head of beef cows. The beef cows require 50 acres of Class B land.

15 © Mcgraw-Hill Companies, 2008 Figure 12-2 Constructing the whole-farm budget

16 © Mcgraw-Hill Companies, 2008 Table 12-4 Example of a Whole-Farm Budget

17 © Mcgraw-Hill Companies, 2008 Linear Programming Linear Programming (LP) is a mathematical procedure that uses a systematic technique to find the most profitable combination of enterprises. Linear programming models have linear objective functions that are maximized (or minimized) subject to the resource restrictions.

18 © Mcgraw-Hill Companies, 2008 Table 12-5 Linear Programming Tableau for the Farm Planning Example

19 © Mcgraw-Hill Companies, 2008 Table 12-6 Linear Programming Solution to the Farm Planning Example

20 © Mcgraw-Hill Companies, 2008 Shadow Prices and Reduced Costs Linear programming routines provide other useful information in addition to the optimal enterprise combination. Shadow prices tell the manager how much the objective function would increase if one more unit of a limited resource were available. A shadow price is the marginal value product of the resource. Reduced costs tell the manager how much the objective function would decrease if the manager chose to produce one unit of an enterprise that was not selected.

21 © Mcgraw-Hill Companies, 2008 Other Issues Sensitivity analysis: analyzing how changes in key assumptions affects income and cost projections Liquidity analysis: analyzing the ability of the business to meet cash flow obligations Long-run versus short-run budgeting

22 © Mcgraw-Hill Companies, 2008 Long-Run Budgeting 1.Use average or long-run prices 2.Use average or long-run yields 3.Ignore carryover inventories 4.Ignore borrowing and repayment of operating loans, but incorporate interest costs if significant 5.Assume enough capital investment each year to maintain depreciable assets 6.Assume constant size of the operation

23 © Mcgraw-Hill Companies, 2008 Table 12-7 Example of Liquidity Analysis for a Whole-Farm Budget

24 © Mcgraw-Hill Companies, 2008 Summary Whole-farm planning and budgeting analyze the combined profitability of all enterprises in the farming operation. Linear programming can be used to select the optimal enterprise combination.

25 © Mcgraw-Hill Companies, 2008 Appendix Graphical Example of Linear Programming

26 © Mcgraw-Hill Companies, 2008 Table 12-8 Information for Linear Programming Example

27 © Mcgraw-Hill Companies, 2008 Figure 12-3 Graphical illustration of resource restrictions in a linear programming problem

28 © Mcgraw-Hill Companies, 2008 Figure 12-4 Graphical solution for finding the profit- maximizing plan using linear programming


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