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AGEC 407 Whole-farm Planning 1.Which enterprises to include? 2.How many units for each? 3.For the upcoming year or for a representative year 4.Done as.

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Presentation on theme: "AGEC 407 Whole-farm Planning 1.Which enterprises to include? 2.How many units for each? 3.For the upcoming year or for a representative year 4.Done as."— Presentation transcript:

1 AGEC 407 Whole-farm Planning 1.Which enterprises to include? 2.How many units for each? 3.For the upcoming year or for a representative year 4.Done as a short-term or long-term plan

2 AGEC 407 Whole-farm Planning Six steps involved: –Review goals and objectives –Inventory resources –Identify possible enterprises and their requirements –Calculate the gross margins for each –Select a plan (combination of enterprises) –Develop a whole-farm budget

3 AGEC 407 Inventory Resources Need to know what is available Most important to know what the constraints are

4 AGEC 407 Inventory Resources Things to inventory –Land –Buildings and machinery –Labor –Capital; position and availability –Management ability

5 AGEC 407 Identify Enterprises Likely choices are often known Might pay to “think outside the box” Resource requirements –Land –Labor –Capital –From enterprise budgets Resource availability

6 AGEC 407 Estimate Gross Margins Income over variable costs –From enterprise budgets –For short-run planning –fixed costs are constant, does not affect profit-maximizing plan –contribution of enterprise to farm fixed costs and to profits

7 AGEC 407 Choose a Plan Combination of enterprises Must be feasible Want most profitable combination Can analyze selected scenarios Can use linear programming

8 AGEC 407 Develop a Budget Why? –Estimate profit and cash flow –Evaluate changes in the plan –Needed to acquire capital

9 AGEC 407 Develop a Budget Sum from each enterprise: # of units * gross margin gross margin = income - variable costs For whole farm: other income indirect costs Result: Net farm income

10 AGEC 407 Linear Programming Uses to find best combinations of enterprises Optimizes an objective subject to certain specified constraints


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