Financial Evaluation and Decision Making in the Swine Breeding Herd

SWINE REPRODUCTION

0749-0720/92 $0.00

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FINANCIAL EVALUATION AND DECISION MAKING IN THE SWINE BREEDING HERD Dale D. Polson, DVM, MS, William E. Marsh, PhD, and Gary D. Dial, DVM, PhD

REQUIREMENTS FOR MEASURING FINANCIAL IMPACT

To measure the financial impact of interventions in the breeding herd there are five basic requirements: (1) historical biologic production data must be recorded; (2) all actual cash and accrued expenses through weaning must be recorded, preferably providing for a distinction between breeding/gestation and farrowing/lactation expenses; (3) there must be a record of all points of sale or value added through which changes in breeding herd biologic productivity can be converted to their income or value-equivalent effects; (4) appropriate techniques must be used to quantify both the biologic and financial implications of any and all interventions; and (5) there must be an effort made to obtain market information (like expected grain prices and pig prices) so that expected results can be estimated. Requirement One

The first of these requirements, recording biologic production data, is becoming increasingly met through the implementation of production information systems such as the PigCHAMP Program (Dept. of Clinical and Population Sciences, University of Minnesota College of Veterinary Medicine, St. Paul, MN). Such systems are essential for the accurate collection and evaluation of physical output as well as the evaluation of the changes in biologic variables resulting from interventions (e.g., liveborn litter size, nonproductive days). Using standard values that have been derived from information assembled

From the Department of Clinical and Population Sciences, University of Minnesota College of Veterinary Medicine, St. Paul, Minnesota

VETERINARY CLINICS OF NORTH AMERICA: FOOD ANIMAL PRACTICE VOLUME 8 • NUMBER 3 • NOVEMBER 1992

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from many different farms is, in most cases, an inappropriate source of input, output, and production values owing to the often considerable variability between farms and over time. 22 Ideally, such values should be derived as a result of the appropriate farm-specific use of epidemiologic techniques, which measure the relationship between production measures and various risk factors and account for confounding when attempting to isolate the effect of specific factor combinations on production. Without such information, the decision-maker must rely on experience and understanding of the farm, the expertise of his or her core group of advisors, and results generated from other on-farm trials carefully constructed and prudently managed.

Requirement Two

Accrual accounting* is a much less widely adopted means of compiling financial data than is cash accounting. Even where accrual accounting has been implemented, it is often only at the herd level. Implementation at a lower level, that is, by stage of production, is much more informative. The reasons for this are many. In true accrual accounting, as pigs move through each stage of production, they are assessed the costs that are incurred in that stage during that particular time period. These accrued costs, then, are not recognized as expense for calculation of profit margins until those particular pigs are sold or move out of the growing pig herd. Accrued expense can, however, be monitored along the way to evaluate how the resulting overall expense is accumulated.

Requirement Three

The third basic requirement, defining a point of sale or value added, is simple for the growing pig herd, as current markets for feeder pigs and market hogs have existed for many years. However, when it comes to the breeding herd, the uproduct" is the weaned pig. Currently, there is no established market for weaned piglets in North America, although such a market is feasible given the advent of multiple-site production technologies. As a result, evaluation of the financial impact of management interventions in the breeding herd necessitates that the resulting changes in weaned pig output be projected through to the related number of feeder pigs and/or market hogs, adjusted for postweaning mortality. It must be remembered that any change in weaned pig output will affect the selling pattern of each individual farm uniquely throughout all stages of production. For example, Farm A currently sells 5200 market hogs per year (IOO/week) and is running at 100% capacity in the nursery and grower/finisher. A suggested management intervention in the breeding herd is projected to result in an increase of 550 pigs weaned per year (roughly 10 /week marketed). Farm A must evaluate the financial impact of such an intervention not only in terms of its impact in the breeding herd up to weaning the additional pigs but also for the impact through to the point of sale. The farm may simply crowd the pigs more. If so, the effect on postweaning performance must be considered. Alternatively, Farm A may elect to

*" a method of recognizing revenues (income) as goods are sold or seroices are rendered, expenses are recognized in the period when related revenues are recognized, independent of the time when cash was paid out,"3

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sell 5 or 6 weeks of weanings as feeder pigs throughout the year, crowding only the nursery. In this case, marginal changes in profitability will have to be considered on feeder pigs instead of market hogs. In both scenarios, the cost to produce a weaned pig may decrease, but the profitability of each option may be quite different. Such differences in the pattern of potential profitability will have an effect on the selection and implementation of management interventions in the breeding herd, as well as on any related interventions in the postweaning herd resulting from changes in the breeding herd. This brings us to the concept of profit centers and cost centers. A profit center is "a unit of activity for which both revenue and expenses are accumulated,"3 that is, a unit of activity that results in a product sale. In contrast, a cost center is "a unit of activity for which expenditures and expenses are accumulated (but not revenues),"3 that is, a defined point of sale is absent. In pig production, the breeding herd is often not differentiated as a distinct cost center but is considered part of a larger profit center, either farrow-to-feeder pig or farrow-to-finish. For financial evaluation, however, it is appropriate to divide the business into a cost center (the breeding herd) and a profit center (the growing pig herd). With the advent of weaned pig markets, the breeding herd increasingly will be considered a profit center, along with the nursery stage (selling feeder pigs) and growing/finishing stage (selling market hogs). Often, an on-farm feed mill and trucking are simply expense items that are part of the production profit center. Occasionally, farms will set up the feed mill or trucking as cost centers. Less frequently, the feed mill or trucking are set up as profit centers. As seen in our previous example, only projecting the effect of the intervention through the breeding herd cost center is an incomplete job of evaluation. We cannot do an adequate job of analysis until the profit implications of our intervention are considered, requiring our projection to include the growing pig profit center. Requirement Four

The fourth basic requirement, use of appropriate techniques in financial evaluation, is of considerable importance. Incorrect input/output assumptions, incomplete information, or improper application of techniques can generate completely erroneous and misleading results and may lead to poor decision-making. Making decisions based upon poor information that is assumed to be good is much worse than making decisions based upon no information, because information assumed to be good generates some level of confidence by the decision-maker. Similarly, making decisions based upon good information, but in which financial techniques are misused or not used at all, is potentially misleading. Requirement Five

Obtaining quality production-related information is necessary to provide projections that are believable and relatively trustworthy. The key production-related variables are those that, when changed, have the greatest effect on the outcome of projections, namely (1) feed costs, (2) market price, and (3) the changes in biologic productivity attributable to each intervention or combination of interventions. There are numerous sources of this type of information, and none can provide certainty-only time will do that. Where uncertainty exists, it must be dealt with effectively through the application of techniques such as sensitivity analysis and stochastic modeling.

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The relationship between information and uncertainty is an inverse one. Specifically, as the quantity and/or quality of information increases, the uncertainty of an outcome decreases. 38 Conversely, as the quantity and/or quality of information decreases, the uncertainty of the outcome increases, and multiple potential outcome analysis becomes more important. 38 If, for example, a producer were certain of the cost of feed, of the production gains or losses for each decision alternative, and of the price to be received for the product produced, that producer would be assured that outcome projections would closely approximate actual results. However, in a real world filled with real uncertainty, the information used in projections generally cannot provide a certain outcome. Thus, the need exists for evaluation of alternatives at multiple combinations of relevant variables (i.e., sensitivity analysis) to evaluate the relative advantages and disadvantages of decision alternatives under comparison. QUANTIFYING CHANGES IN BIOLOGIC PRODUCTIVITY

Financial evaluation of breeding herd interventions must be viewed first in terms of any changes in productivity. This necessitates that (1) the key indicators of biologic productivity be identified and their relationships be described, (2) the actual productivity of the herd be measured and known, and (3) productivity targets resulting from interventions be estimated with reasonable accuracy and confidence (i.e., target - actual = potential), the difference being the potential gains projected for any interventions. In the breeding herd, the single most important unit of output is the weaned pig. As the basic economic unit of the breeding herd, production efforts should be aimed first at optimizing weaned pig output. Increasing total annual weaning weight output measured in pounds is of secondary value to the total annual output of weaned pigs. Such a conclusion is a rather intuitive one, particularly if it is thought of in terms of the entire spectrum of pig production - it is easier to put weight on growing pigs that you have than pigs that you do not have. Even though increasing weaned pig output is a higher goal than total weaning weight for the breeding herd, once pigs are weaned into the growing pig herd, the fundamental economic unit becomes the unit weight of pigs, and the number of pigs produced now becomes secondary. Such is the mission of the breeding herd: To produce weaned pigs that will be fed out and marketed in the growing pig herd. Total weaning weight output may be increased by (1) increasing the number of weaned pigs of the same weight, (2) increasing the average weaning weight of the same number of pigs, or (3) some combination of increased number of pigs and average weight at weaning. Increasing the average weaning weight of pigs is a function of some combination of genetics, nutrition (sow and/or piglet), environment, and exposure to disease. Improvements in weaned pig output from a given herd size are primarily a function of either increasing litter size and/or increasing female efficiency, specifically, reductions in either or both lactation length a~d nonproductive days. Example

The concept may be more easily understood through the use of an example (Tables 1 and 2). In our example, the breeding herd is considered a cost center and the growing pig herd is a profit center. If Farm B can maintain the average weaning weight of pigs as well as the total expense for the breeding herd while

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Table 1. COMPARISON OF WEANED PIG PRODUCTION COSTS AND FEEDER PIG PROFITS BETWEEN TWO FARMS WITH 6-WEEK NURSERIES Variable Breeding Herd Annual weaned pig production Average weaning weight (Ib) Average weaning age (weeks) Annual Ib weaned Annual weaned/pig production costs (US Currency) Costjlb weaned Cost/pig weaned Nursery Weeks in the nursery Average daily gain (Ib) Feed conversion ratio Percent mortality Average feeder pig weight (Ib) Average feeder pig price/lb Annual pigs sold Annual Ib sold Profit/farm Profit/inventoried female

Farm A

Farm B

Difference

4837 14.0 3.5 67,718 $125,000 $1.85 $25.84

5170 12.5 3.5 64,625 $125,000 $1.93 $24.18

(333) 1.50 0.00 3,093 $0.00 $(0.08) $1.66

6 weeks 0.82 1.90 2.0% 47.0 $0.98 4,741 222,792 $49,011 $196.04

6 weeks 0.79 1.95 2.5% 44.5 $0.98 5041 224,313 $48,886 $195.54

0.03 (0.05) (0.5%) 2.5 $0.00 (300) (1,521) $125 $0.50

increasing the annual weaned pig output over that of Farm A, it is obvious that Farm B will be more profitable. However, we have not yet really challenged our hypothesis. If Farm B produces more weaned pigs per year than Farm A, but fewer pounds of weaned pig per year, choosing the more profitable farm is less obvious. Farm A produces 67,7251b of weaned pigs (4,837 pigs X 14lb per 31/2-weekold pig) from 250 sows per year (Table 1). In contrast, Farm B produces 64,625 lb of weaned pigs (5,170 X 12.5 lb per 3V2-week-old weaned pig), also from 250 sows per year. Farm B weans, on average, 6.4 more pigs per week than does Farm A. Assume both herds have identical disease profiles, facilities, nutritional programs, and genetic programs. Both Herds A and B produce their annual weaned pig output at a cost of $125,000. The cost per pound is $1.85 and $1.93, respectively, whereas the cost to produce one weaned pig is $25.84 and $24.18, respectively. Although the cost per pound for Farm B is higher than Farm A, the cost per pig is lower. To understand the relative importance of the number of pigs compared to the number of pounds, the example must be projected to a point of sale-in this case, feeder pigs. First, let us consider the projections through the nursery stage if both sets of Table 2. COMPARISON OF FEEDER PIG PROFITS BETWEEN TWO FARMS WITH THE SAME SALE WEIGHT BUT A DIFFERING NUMBER OF WEEKS IN THE NURSERY Variables

Farm A

Farm B

Difference

Nursery Weeks in the nursery Annual weaned pigs Annual pigs sold Annual Ib sold Profit/farm Profit/inventoried female

6 weeks 4,837 4,741 222,792 $49,011 $196.04

7 weeks 5,170 5,041 236,927 $56,334 $225.34

(1) (333) (300) (14,135) $(7,323) $(29.29)

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pigs are raised in identical six room nurseries and fed identical diets. Nursery pigs on Farm A have an average daily gain (ADG) of 0.82, a feed conversion ratio (FCR) of 1.90, and a mortality of 2.0%. Corresponding figures for Farm B are a 0.79 ADG, a 1.95 FCR, and a 2.50% mortality. The lower performance for Farm B is an assumed consequence of the lower average weaning weight. The number of feeder pigs sold annually for each farm is 4,741 (Farm A) and 5,041 (Farm B). Each week's production is sold after 6 weeks in the nursery so that the farms may maintain their production schedule. Feeder pigs from Farm A weigh an average of 471b, Farm B's pigs average 44.5. The average annual feeder pig price is $0.98 per lb. Farm B sells 1,498 lb more per year than Farm A, but at somewhat higher costs. Both farms have similar annual profit margins: $49,011 per year for Farm A, and $48,886 per year for Farm B, or $196 per sow per year. Given that Farm B has 333 more pigs available to sell per year, the addition of a seventh nursery room would allow all pigs to be fed to the same 47-lb weight as on Farm A (Table 2). In this case, Farm B will have a projected profit advantage of $7,323, or an additional $29.29 per sow per year. Simply adding a seventh room on Farm A to match Farm B does not eliminate an advantage of $419 for Farm B, primarily owing to the presence of the additional pigs and the now increasing role of the weight of the pigs. Had Farm B been able to keep the pigs longer to add the additional weight without adding a seventh nursery room, the net margin would have been even greater, because additional fixed costs would have been avoided. The key to capturing a greater profit is to take advantage of the potential provided by the presence of the additional pigs when they reach the growing pig herd. One timely caution: increasing the weaned pig output is not always enough to capture the profit potential those additional pigs represent at their point of sale. H additional weaned pigs are produced at a sufficiently reduced average weaning weight, the additional growing costs to raise them up to their natural point of sale may more than offset the income they generate, even though increasing the weaned pig output may reduce the cost per weaned pig. There are practical biologic limitations to increasing weaned pig output at the expense of average weaning weight, particularly where such a shift requires the use of very high cost diets and nursery facilities, as well as where sufficient changes in mortality and nursery performance (e.g., gain, and feed conversion) are seen. At times, particularly when the potential for increasing weaned pig output is low, increasing the total weight output through heavier pigs at weaning will demonstrate the greatest potential. The Breeding Herd Productivity Tree

When developing an understanding of the factors that influence weaned pig output, it is helpful to think of the breeding herd production system as an organizational chart or productivity tree (Fig. 1 and 2). Everything that happens in the breeding herd will eventually affect the number and total lb of weaned pigs produced per year, and, in tum, the profit of the operation. The top of the breeding herd's biologic productivity tree is total annual pounds weaned (Fig. 1). However, total annual weaned pig output is the parameter that warrants more attention. Why? As suggested earlier, if you've got them, you can feed them. H you don't, you can't. The key production variables that influence weaned pig output are illustrated in Figures 1 and 2. For a facility of a given size, the two factors that directly determine weaned pig output are total average female inventory and pigs weaned per female per year (see Fig. 1: Breeding female conSiderations). Herd inventory is constrained by the available facility capacity. For weaned pig output to be affected by a change in herd inventory, the facility would have to be operating at some

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Total Pounds Weanedl Year

I

I Total Pigs Weanedl Year

Average Poundsl Pig Weaned

I

I

I

I

Facility Considerations (PWIC/y x ACrl)

Breeding Female Considerations (PW/F/Y x AFI)

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Pigs Weaned Cratel Year

I

Average Crate Inventory

Pigs Weaned Femalel Year

I Lactation Weight Gainl Pig Weaned

Average Birth Weight

I Average Female Inventory

Weaning Age (Days)

Figure 1. Breeding herd productivity tree: pounds weaned/year. WND

Average Daily Gain

= weaned;

ACrl

=

average crate inventory; AFI = average female inventory.

level outside of its optimal capacity range; either underutilized or overcrowded (see Fig 1: Facility considerations). At a herd inventory within the optimal range, a more important factor than average female inventory affecting weaned pig output is the number of pigs each inventoried female can wean per year. In the breeding herd production system, many relationships between production variables at a given level in the productivity tree are simply capacity X efficiency relationships. That is to say, two key factors drive output: (1) the capacity of the system, and (2) the efficiency of the system (capacity X efficiency = output). In effect, the capacity of the herd involves the female inventory. The efficiency of the herd involves each unit of inventory, the breeding female. Relatedly, the capacity of a facility may be measured in farrowing crates (among other things), and the efficiency of the facility involves the individual crate. Two variables directly affect pigs weaned per female per year: (1) average weaned litter size (the capacity of the female to generate pigs), and (2) litters weaned per female per year (LFY) (the level of efficiency with which a female generates litters of weaned pigs) (Fig. 2A). Weaned litter size is affected by (1) total born litter size, (2) stillbirths, (3) mummified piglets, and (4) preweaning mortality (Fig. 2). All other factors affecting weaned litter size do so indirectly, exerting their influence directly on one of the four listed parameters. Similarly, LFY is affected by (1) nonproductive days, (2) lactation length, and (3) gestation length (Fig. 2). Any influence on LFY m¥st exert its influence indirectly, through one of these three parameters. In terms of the facility, litters/crate/year is affected by: (1) LFY, and (2) female: crate ratio (a measure of the relationship between female inventory and facility capacity). It is interesting to note that, whether we begin evaluating weaned pig output from the perspective of the facility or the breeding female, in both cases, we eventually

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POLSON, et al Pigs Weaned! Female! Year

Litters! Female! Year

Pigs Weaned! Litter

Gestation Days

Lactation Days

Born Dead! Litter

Totalborn! Litter

Mummies! Litter

Stillborn! Litter

A Pigs Weaned! Crate! Year

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I

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Litters! Crate! Year

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Totalborn! Litter

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r

Born Dead! Litter

Nonproductive Days

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I

Stillborn! Litter

Mummies! Litter

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Litters! Female! Year

Preweaning Mortality

Liveborn! Litter

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I

Pigs Weaned! Crate Turn (Le., Litter)

I

Female:Crate Ratio

1 Productive Days

1 r Lactation Days

I Gestation Days

B

Figure 2. Breeding herd productivity tree. A, Breeding female considerations. B, Facility considerations.

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come down to the three key intermediate factors that drive the system: (I) female inventory, (2) weaned pig litter size, and (3) LFY. For effective financial evaluation of the breeding herd to be done, the direct influences of recommended interventions on each of the key production parameters must be quantified first. In this way, the inevitable impact on weaned pig output and weaned pig weight may be quantified and the biologic ingredients from the breeding herd used in financial evaluation determined. As suggested earlier, these changes must then be projected to the point{s) of sale appropriate for the farm, obviously requiring that the relationships between biologic variables in the growing pig herd be known and the farm's performance measured. A final note regarding biologic parameters: the breeding herd does not operate in isolation from the growing pig herd; rather, they operate in harmony. Factors affecting weaned pig output and average weight inevitably affect the performance of the growing pig herd. For example, factors that increase preweaning mortality, such as an outbreak of transmissible gastroenteritis (TGE), often have a long-term effect on the performance of the survivors. QUANTIFYING CHANGES IN FINANCIAL PRODUCTIVITY

There are three key questions when evaluating the financial implications of any intervention: (I) is it likely to be profitable, (2) how risky is it (i.e., what are the chances that it will not be profitable after all), and (3) do I have the financial resources to implement it (i.e., will it produce sufficient cash flow)? The first consideration, profitability, may be evaluated through the application of classical decision analysis techniques designed to measure changes in profitability: the budget, partial budget, and related variants such as pay-off matrices. 2 The second consideration, risk, may be evaluated using those same techniques at multiple combinations of inputs and outputs (i.e., sensitivity and threshold analysis). Additionally, risk may be evaluated through the application of a special type of technique called stochastic modeling. An example of a stochastic model is a budget that, using probabilities (e.g., what are the chances that the price of com will be $2.50 vs. $3.00 vs. $3.50) and multiple runs of the stochastic model, generate from one set of input values a distribution of output values. The variability in this output distribution allows one to assess risk. The third consideration, evaluating the availability and use of financial resources, is best evaluated through techniques such as cash-flow analysis, net present value analysis, and financial feasibility. At the farm level, the financial impact of interventions can be measured by quantifying the relationships between key physical performance and financial values. For the breeding herd, the four key values are (I) weaned pigs, (2) average weaned pig weight, (3) sow days,* and (4) input costs. In the postweaning stage there are also four key values: (I) pounds sold, (2) pig days,t (3) input costs, and (4) income. Combinations of these values exhibit their influence on a herd's profitability and cash flow characteristics in one of two major ways: (I) as a negative (additional expense and/or reduced income), and (2) as a positive (reduced expense and/or additional income). The sum of the positive and negative influences indicate the effect on profits and cash flow. ·One sow day is any day that one live sow is physically present in the herd. For example, 1000 sow days may indicate 20 sows present the herd for 50 days, or 200 sows present for 5 days. tOne pig day is any day that one live weaned pig is physically present in the herd. It follows that 100 pig days indicate 100 pigs present for 1 day or 1 pig present for 100 days.

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The financial impact of management interventions may be broken into direct and indirect components. The direct financial component is the impact associated with changes in the quantity of production outputs, measured in terms of the actual change in pigs and/or lb produced, and changes in potential pigs/lb represented by a change in sow efficiency (measured by: LSY, nonproductive days, and farrowing rate). The indirect financial component is defined as the impact associated with changes in input quantity and/or unit costs, including diversion of existing resources away from other operations toward management of the intervention and incurring expense associated with using new resources not normally required for operations.

DECISION ANALYSIS TECHNIQUES

Practicing swine veterinarians are increasingly faced with the necessity of financial justification for interventions in a wide range of factors causing suboptimal productivity. Classic decision analysis techniques, such as budgeting, partial budgeting, decision tree analysis, and payoff matrices, are useful in the analysis of benefits and costs associated with such interventions.2.17.25.30 Several techniques currently used extensively in the business world have useful applications to agriculture, and specifically to pork production. Recently, an increasing number of papers presented at veterinary meetings and in the literature deal with the application of decision analysis to food animal agriculture.4.5.8.12-15.21.25.29-32.37.47,49.52 Epidemiologic textbooks are including chapters describing the application and use of decision analysis techniques in veterinary medicine. 27.43 The attention in the literature given to the application of decision analysis within food animal agriculture indicates an increasing recognition of the importance of the financial dimension of food animal production.22 A basic understanding of each of the various decision analysis techniques is important to their effective use in supporting decision-making on pig farms. Decision analysis has been defined as "any framework or strategies for handling complex decisions so that they can be more readily handled by the human mind . . . one can consider all economic and statistical/epidemiological models and frameworks used in problem-solving to be part of decision analysis."32 Decision analysis is a step-by-step process of outlining all the benefits and costs that result from any management decision, and includes measures of both the production and financial impacts of the problem and the possible solutions. The value of decision analysis lies in the proactive evaluation and objectivity it can provide for the decision maker in making the short-, medium-, and long-term management decisions that will dictate the "health" of the business. The result of this objectivity should be an increase in the level of confidence of the decision maker. Application of decision analysis techniques to pork production could range from measuring the change in preweaning mortality resulting from the use of an E. coli bacterin in sows to comparing the impact of the addition of a crated breeding/gestation building and hand-mating versus a current practice of pen-mating and outside pen gestation on various production and economic measures over a period of time. Decision analysis techniques are very useful in analyzing interventions with benefits that follow in a relatively short period of time (e.g., in less than 1 year). Typically, expenses associated with treatment of infectious disease, initiation of immunization, or the use of antiparasitics are followed closely by their consequent benefits. Often, these techniques are used as the sole criterion for justifying whether to proceed with the implementation of recommendations and interven-

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tions. Although these techniques may, when conducted properly, be a good measure of potential profitability, they have two key limitations: (1) they are of little value in evaluating the logistic financial demands placed on the enterprise that occur with medium-term interventions deemed profitable, and (2) they are inadequate indicators of true costs and benefits for interventions that require an initial outlay of capital, but whose benefits are realized over a long period of time. Examples of such projects in hog production are construction of a new breeding/ gestation building, buying a new feed mill to prepare diets on-farm in place of all diets being delivered complete, or changing breeding herd genetics to develop an improved quality carcass and enhance performance. The single most important key to effective decision analysis is obtaining the best available information. 41 ,46 There is a certain degree of subjectivity to decision analysis, that is, assigning probabilities to input or output events or assigning a measure of change in some production parameter that is the direct result of the decision. 2 However, to provide a reliable analysis, the information should be the most accurate and objective available. Attempts to correlate input, production, and output variables can be found in the literature. 6,9,28,3o,52 The assumptions that are a product of the information used are critical to determining the optimum decision option. Useful in evaluating costs and benefits, two major limitations of several decision analysis techniques (e.g., the partial budget, decision trees, and payoff matrices) are that they (1) do not adequately reflect the temporal relationship (relationship over time) of cash costs and cash income, and (2) they do not always account for the time value of money. The evaluation of the flow of cash associated with interventions or recommendations is essential for logistic anticipation of the cash demands placed on an enterprise while implementation of interventions progresses to the point of realizing expected benefits. Techniques that consider this logistic time relationship are cash flow analysis, financial feasibility, and repayment capacity. Accounting for the time value of money is also really a temporal consideration and involves reducing the value of expected revenues generated in future time periods, using a "discount rate." The logic for discounting is simple: a dollar received 2 years from now is worth less than a dollar received in 1 year, and even less than a dollar received today. Thus, the same value cannot be placed on a dollar paid for some investment (e.g., a building or piece of equipment) and any future expense or income it may generate. Techniques that consider the time value of money are net present value analysis, internal rate of return, and benefit/cost

analysis. Discussions of the details and usage of the various decision analysis techniques may be found in various textbooks and are not included in this article. 2,3 However, two techniques are briefly outlined, one as an example of a technique that is useful and the other as an example of a technique to be avoided. Payback Period2.3

Payback period is a decision analysis technique that deserves special attention as a technique to be used sparingly, even avoided. Payback period is commonly used but is of very limited value. The purpose of payback period is to determine the number of years it takes to recover the original investment (i.e., initial capital outlay [ICO)) of a capital asset. To calculate the payback period for a building or a piece of equipment, the ICO is divided by the cumulative expected annual net after-tax earnings, excluding depreciation (i.e., cash income - cash expense) generated by that investment. The decision to invest is then based on an acceptably short payback period. Payback

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period is simple to understand. However, this technique suffers from distinct disadvantages: 1. Payback period ignores the economic life of an investment; that is, how long the building is useful. Therefore, payback period is not really a measure of profitability at all. Instead, it is more a measure of liquidity, because it measures how soon an investment can be recouped. 2. There is no good logical criterion for accepting or rejecting an investment. Typically, if the investment has a sufficiently short payback period, it is accepted. However, there is no indication by the payback period of the overall profit potential generated by that investment. 3. As with several decision analysis techniques, payback period ignores the time values of money. Future net revenues generated by the investment are valued at the same level as the initial investment.

Partial Budget2,3,36

The partial budget is intended to measure the impact of a single change or small number of changes on net profitability. The partial budget essentially isolates the impact of any management intervention into each of four basic areas: reduced expense (RE), additional income (AI), increased expense (IE), and reduced income (RI). The differences in these four areas are all relative to the actual overall budget, affording a measure of the net effect of that intervention in the equation: Net difference = [(RE

+ AI) -

(IE

+ RI)].

The intent of the partial budget is to evaluate the net benefit/cost relationship of a single change or small number of changes relative to the current standard; that is, "what will the net dollar difference be between how it is being done now and how it will be done after the change is made." The technique considers all four possible economic effects that change(s) could have on the profitability of the operation. A partial budget may supplement a total enterprise budget, isolating specific components of the enterprise budget that are affected by the particular intervention(s). Additionally, partial budgets may be developed independent of an enterprise budget. If a particular intervention affects only specific components of input costs, production variables, and sale of outputs, a partial budget could be developed to reflect the net effect of this intervention on profitability, assuming that all other nonrelated components of the total budget remain constant. This flexibility allows the use of partial budgeting in situations in which a complete set of information is unavailable. A limitation of the partial budget is that it evaluates the net difference at a single benefit/cost level; that is, at one feed cost/ton and one market price/cwt of pork. If the cost of feed and market price do not change from the projected levels, then the partial budget can reliably predict the benefit/cost and allow the decision maker the means to make an informed decision-one that will result in a net improvement in profit/loss. Of course, this is essentially never the case, because feed costs and market prices are constantly changing. To take this variability into account, a decision maker must use sensitivity analysis. Sensitivity analysis simply involves running several partial budget projections, each at a different level of one or more key variables. For example, three levels of feed cost and market price would result in nine combinations of feed cost and market price. Generating the nine corresponding partial budgets would constitute sensitivity analysis. Other

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decision analysis techniques, such as decision trees and payoff matrices, are essentially made up of multiple partial budgets. An additional limitation of the partial budget is that, like payback period, it does not take into consideration the time value of money. Any lag time that exists between costs incurred and benefits received will result in some degree of discount in the value of the delayed benefits relative to the value of the immediate costs. This would obviously lead to a less than realistic evaluation of the intervention under consideration; that is, an overestimation of the current value of any net benefit. Given the limitations of the method, the partial budget and related techniques are still very useful in the determination of profitable interventions in pig production.

The Importance of Risk Assessment in Financial Evaluation

The management of risk or uncertainty is a fundamental requirement for all areas of pig production. Pig farm managers and veterinary advisors to those farms must deal effectively with the various manifestations of risk. Financial evaluation of any area of a pig farm is simply one method for managing risk. Financial evaluation becomes a step in the overall process for managing risk and making decisions. 38 With the acceptance of some risk comes the potential for financial reward. Typically, the greater the risk taken, the greater is the potential for financial reward. In the total absence of risk, there would be no reason for a return above costs. In other words, without risk, all businesses would be expected to exactly break-even, because all physical and financial values would be known and be completely predictable. Of course, this is not the case. All businesses face risk and generate either a profit or loss. Profit, then, could be considered the premium received for accepting some level of risk (Lawrence J, personal communication). Every intervention carries with it a range of possible outcomes, some more likely than others. 38 This outcome variability or variance is, in effect, the risk associated with that decision. Uncertainty in the outcome of potential interventions and the influence such uncertainty has on the chosen course of action have a profound impact on the operations of a pig farm. Complete knowledge of the biologic and economic (price) input-output relationships making up pig production systems are seldom, if ever, known. 2 Effective management of a pork-producing business necessitates, however, that steps be taken to deal with the presence of risk in the operations of the business. Methods for quantitating risk and subsequently dealing effectively with the presence of risk are tantamount to effective management. The consequences of realized risks for pig farms are suboptimal biologic and financial productivity. The factors that are responsible for suboptimal performance could be termed risk factors. For each facet of farm productivity, the risk-related consequences of suboptimal productivity are expressed through (1) infectious disease, (2) the quality of genetics, facilities, equipment, and nutrition, and (3) the management of each of these facets. For pig farms, therefore, appropriate risk management must be directed at minimizing the effects of risk-related consequences on productivity.38 Because it is the deviation from potential biologic and financial productivity that identifies and quantitates the consequences of risk, it becomes necessary to be able to reasonably determine the real potential of any given pig farm's production system. The benchmark parameters that are the target production levels may then be used to gauge the presence, degree, and duration of suboptimal productivity.38

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POLSON, et al

Risk exists in different forms for pig farms. A broad classification of enterprise risk contains two categories: business risk and financial risk (Fig. 3).2 Business risk may be defined as, ". . . the inherent uncertainty in the firm

independent of the way it is financed . . . business risk includes those sources which would be present with 100 percent equity financing. ''2 Exposure to business risk comes in two basic areas: price risk and production risk (Fig. 3). Effective management of business risk is designed to control variability in key input and output variables. Minimizing variance, or risk, in these variables is the fundamental goal. Price risk refers to uncertainty and variability of input costs and output prices in a dynamic market. For example, the costs of com and soybean meal, equipment, breeding stock, and labor all inherently exhibit a degree of uncertainty, reflected in their variability over time. Production is a significant source of risk exposure that may originate from variability in several key areas: (1) disease, (2) environment, (3) management, (4) nutrition, and (5) genetics. The potential for transmissible gastroenteritis (TGE), extremely cold or hot weather, problems with worker performance, a moldy corn supply, or inferior genetic lines will all add to the load of risk exposure in pork production. The second broad classification of risk is that of financial risk (Fig. 3). Financial risk may be defined as, ". . . the added variability of net returns to owner's equity that results from the financial obligation associated with debt financing. ''2 This added risk would apply to all agribusinesses that receive any proportion of funds through outside sources of credit.

Enterprise Risk

I

1

I

Business Risk

Financial Risk

I

I Price Risk

I

J Fixed (Capital) Risk

t

I

Input Price Risk

Output Price Risk

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I

Variable (Operating) Risk

Opportunity (Potential) Risk

1 Disease

I

I

I

Production Risk

Price Risk

Non-Price Risk

1

I

1 I

I

I

Environment

Management

Nutrition

Genetics

Figure 3. Conceptual relationship between types of enterprise risk.

FINANCIAL EVALUATION AND DECISION MAKING IN THE SWINE BREEDING HERD

739

Assessing the Cash-Flow Characteristics of Interventions40 The inherent value in cash-flow analysis is the ability to evaluate the influence of time on various decision alternatives. Many months often elapse between the time when inputs are purchased and the finished products are sold. The time involved in processing inputs through a biologic production system to generate outputs may substantially affect the cash position of the business. For example, a business plan involving the building of a new breedingjgestation building may demonstrate a positive net return in a partial budget but fail to account for the financial implications associated with the time lag between incurring the costs associated with such a large capital investment and realization of any subsequent benefits. Initiating such a project would create an immediate large demand for capital and the demand for repayment of principal and interest for any debt assumed to raise sufficient capital. All of these cash outflows would occur before any expense savings or cash income from additional sales could be realized. In projects such as this, or any of a multitude like it, cash-flow analysis should be carried out to show whether the business can generate sufficient cash flow in a timely manner to allow implementation of such a plan, or if additional funds will be required to meet obligations during the transition period. The need for additional borrowings to meet cash obligations in the interim will incur additional interest charges and a demand for repayment at a later date. The concept of cash flow analysis could be summed in a statement made at a business management school, "A good cash flow keeps you in business long enough to make your profits."· One limitation of cash-flow analysis is that it does not show the accrued profit for a given period due to what is called lag time. Lag time is the period after which the expense or income item is accrued but before cash is actually paid out or received. For example, if a I-month lag time occurs between the replacement of input materials used to generate products and the actual payment of the accounts due as a cash expense, the net result is that the cash income from product sales lags behind the payment for input materials to produce those products by some period of time, predisposing a struggle to maintain a cash surplus (positive net cash balance). This lag time also is reflected at the beginning and end of a cash-flow period. The beginning of the year contains cash income from the accounts receivable and expenses from accounts payable from the prior year; similarly, the end of the year will carry over into the following year. Depreciation of capital expenditures such as buildings or equipment is not a cash expense and therefore not reflected in a cash flow. Therefore, it is not possible to determine pre-tax profit, the tax due, or the post-tax profit of an enterprise. Instead, the initial cost of the capital expenditure and subsequent repayment of principal and interest toward any loan are recorded in the cash flow. If the capital expenditure is purchased with equity funds (i.e., "out-of-pocket" funds), the cash flow does not, and should not, reflect the opportunity cost of tying up equity in the business unless a formal interest charge is made and paid for the use of the equity funds in the same fashion as borrowed or debt funds. Equity is "tied up in the business" by definition: it's what the business "owes" the owner(s) or shareholders. The addition of an opportunity interest rate for equity is not

*Effective Business Management School, Wayne Feeds Division, Continental Grain Company, Chicago, IL, September 1988

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POLSON, et al

necessary, because it is not a cash expense. Including an opportunity cost has its place, but not in cash-flow analysis. A final limitation of the use of a projected cash flow is that it does not typically consider the time value of money in the long-term planning (greater than 3 - 5 years) for a business. Economic techniques suitable for long-term planning are: (1) net present value analysis or the discounted cash flow, (2) internal rate of return, and (3) benefit/cost analysis. 2,3 Application

To demonstrate the concept of decision analysis, specifically the partial budget, an example farm problem will be used. Farm C inventories 500 sows and farrows 20 litters per week. The farm has an identified problem of low parity-2 litter size (Fig. 4A). This type of problem suits the use of a partial budget reasonably well, because costs are relatively closely associated with resulting benefits. During 1986, parity-2 females on the farm recorded average total born litter sizes 0.9 to 1.0 pigs/litter less than parity-l females. The difference was found to be a significant one. An intervention to resolve the problem was suggested - skipping one estrus cycle on parity-l females and mating them on the second observed estrus postweaning. For the sake of simplicity, other possible interventions will not be considered for this example. However, when conducting an analysis, all appropriate potential interventions should be considered. When constructing a partial budget, it is helpful to list all the key the cost and income factors that will change as a result of the intervention, then fit these factors into their appropriate slot in the partial budget equation. To review, that equation is: [(AI

+ RE) -

(RI

+ AE)] = Net difference

Where net positive effects are AI = additional income and RE = reduced expense; net negative effects are RI = reduced income and AE = additional expense. One of the biggest challenges of partial budgeting is accounting for all the key factors that will affect the outcome of a projection. It is important to think carefully through all the possible biologic and financial effects to avoid missing variables that, if excluded, could change the decision. Table 3 summarizes the four components of the partial budget and the example-specific items associated with each of these components. Net Positive Effects

Additional Income. The additional income from this intervention will come from essentially one key area-more pigs marketed per year as a result of larger litters from parity-2 females (Fig. 4B). The benefit from these additional pigs, however, will take 11 to 12 months to be realized, considering the time it takes to acclimate the gilts used in the 3-week startup period, begin breeding the skipped sows, gestating and farrowing them, and growing the additional pigs to market weight. A small amount of income will also come in the first year from the few gilts used to start up the intervention that would be expected to be culled. The reason additional gilts are required in the startup period is because, while the parity-l females normally mated on first observed estrus are held for the 3-week skip period, there needs to be enough gilts available for service to fill in the gap in breedings. After 3 weeks, no additional gilts will be required, because the first animals skipped will then be available for service.

741

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742

POLSON, et al

Table 3. PARTIAL BUDGET CATEGORIES FOR A CASE INVOLVING DEPRESSED PARITY-2 LITTER SIZE Net Positive Effects Additional income (AI)

Reduced income (RI)

Reduced pigs marketed/year as a result of fewer litters generated/ year owing to additional nonproductive days from increase in weaning-to-service interval for all sows skipped Reduced growing pig variable costs (e.g., feed) for pigs that are "lost" as a result of fewer litters generated/year because of additional nonproductive days (i.e., additional weaning-toservice interval days)

Reduced expense (RE)

Additional expense (AE)

Net difference (AI

+ RE)

(RI

+ AE)

Net Negative Effects

Additional pigs marketed/year as a result of larger litters from parity-2 females (beginning in second year) Cull income from additional gilts required to start the "skipping" program (year 1 ONL Y)

Purchase cost of additional gilts required to start the skipping program (year 1 ONLY) Additional variable costs from the entry to service or removal days for these additional gilts (year 1 ONLY) Additional breeding facility costs, required to house the sows being skipped (year 1 ONLY) Additional variable costs (e.g., feed) incurred as a result of larger parity-2 litter size Additional income =

+

reduced expense

Reduced income

+

additional expense

The magnitude of the increase expected in parity-2litter size is very important to the eventual outcome. It is advisable to generate multiple scenarios at various levels of litter size increase to help in the evaluation. This method of changing one or more variables and rerunning the projection is called sensitivity analysis. For example, if the farm manager and veterinarian expected an increase of 1.5 pigs/ litter, it would be helpful to also look at values both above and below that level, say 0.9, 1.2, 1.8, and 2.1. Also important in the additional income area is the expected market price at which the additional pigs would be sold. The expected market price as a baseline in this example is $45.00/100 lb. The sensitivity analysis levels of market price, then, could be, say, $42.00 and $48.00/100 lbs. For all projections, the market weight used will be that normally recorded for the farm - 245 lb. One caveat: because there will be more pigs farrowed, there is a good chance that the weaning

FINANCIAL EVALUATION AND DECISION MAKING IN THE SWINE BREEDING HERD

743

weights could be less and that this reduction could be reflected in the market weight of these same pigs. If that is a reasonable assumption, an adjustment could be made in the market weight used for these pigs. Although it could be possible that a longer-term result of the skipping program may be increased litter size in parity-3 and higher, we will not assume any benefit for this example. The number of additional pigs would be determined by multiplying the number of expected parity-2 litters to be farrowed each year by the anticipated increase in litter size, then deducting the mortality through to market weight. Reduced Expense. One possible area of reduced expense may in a lower culling rate if skipped females have increased longevity in the herd, thus resulting in a lower annual expense for replacement gilts (and, obviously, reduced culling income). It would be extremely difficult to estimate a value here, particularly because, even though there may be a logical reason to expect this as a benefit, there is no good evidence to support it. For this reason, no value is assigned here in our example. A key reduction in expense would be the savings in variable costs from feeding fewer pigs. This reduction in the number of pigs available to feed is due to fewer litters being farrowed per year. The reduction in the number of litters farrowed per year is due to an increase in the farrowing interval of roughly 3 weeks for each female that is "skipped." The two areas of variable costs are feed and nonfeed. The logic here is that, "if we don't have the pigs, we don't have to feed or care for them." Net Negative Effects

Reduced Income. As mentioned in the section on reduced expense, the potential for increased longevity of skipped females exists but is not well substantiated. It could be argued that this income reduction could be offset by heavier culls as a result of skipped females being in overall better condition. Both points are speculative. Therefore, no assessment of any potential change in culling income is included. Because of the increase in total born litter size and the number of piglets nursing available sows, it is reasonable to expect that the herd will record a reduced piglet weaning weight at the same weaning age, which may be reflected in a lower market weight. We will assume that this lower weight will be O.5Ib/piglet weaned and that the difference will carry to market. A legitimate argument could be made for both compensatory gain or for an increase in the magnitude of the difference. In this example, we completely sidestep this issue. The most substantial issue regarding reduced potential income stems from the increase in the weaning-to-first service interval for those parity-1 females that are skipped and the resultant reduction in the number of litters of pigs that could be generated per year from a given number of females (i.e., LFY). Because we are basically adding, on average, 21 days onto the farrowing interval of each skipped female while maintaining the same number of females in the herd overall, we are essentially delaying the litters born to these females. The net effect is that we cannot farrow as many litters in a year as we could by not skipping females. To be conservative, we will assume that these increased weaning-to-first service days are not offset by fewer nonproductive days from a lower retum-to-estrus rate and/or culling rate. To calculate the number of pigs that would be "lost," the additional weaningto-first service days are calculated and divided by the current parity-specific farrowing interval on the farm, multiplied by the current parity-specific total born litter size, then adjusted for mortality through market. The counterpart to this reduction in potential income is the smaller amount of feed that we used and non-feed variable cost that we incurred because we did not have to feed and care for these pigs (see the section on reduced expense).

744

POLSON, et al

Additional Expense. Four areas of additional expense are considered in this example. The first three will be incurred as "start-up" costs in the first year only. As mentioned in the section on additional income, the reason additional gilts are required in the startup period is because, while the parity-1 females normally mated on first observed estrus are held for the 3-week skip period, there needs to be enough gilts available for service to fill in the gap in breedings. After 3 weeks, no additional gilts will be required, because the first animals skipped will then be available for service. The additional cost to purchase these gilts will be incurred during the first year of the intervention. Also, the additional cost associated with the entry-to-first service or removal days which these gilts would accumulate will be incurred only in the first year. A subtle start-up cost that must be accounted for is the possibility that, because parity-1 females will be held in breeding/gestation facilities roughly 3 weeks longer than at present, additional facility space will be required to house these animals throughout the year while maintaining breeding/gestation at its normal flow. The number of additional spaces required will depend upon what percent of weaned females are skipped at any given time. It is not intuitively obvious why additional space would be needed if the physical female inventory is essentially the same before and after beginning the "skipping" program. Think about it this way-if a sow is in the herd for 365 days/year, it will occupy an actual space for the entire year. Every time we add 365 sow days to the total breeding/gestation sow days, we are, in effect, requiring one more sow space to house the animals represented by these days for 1 year. For this example, we are assuming that we do not have sufficient spare breeding space to house the sows being skipped. It is often the case that additional space will already be available. If so, this particular cost could be avoided. However, if this space is available, it is an indicator of a different problem - a facility operating below its capacity. Because these start-up expenses are incurred in the first year when no real benefit is realized, it is appropriate that these expenses be distributed over the number of years that the benefits are expected to be maintained. This would mean simply that these expenses be totaled, an appropriate interest rate be identified, a "depreciation" period be used that equals the duration of the benefit period, and that the expense be amortized over that number of years. This amortized payment will allow us to account for a measure of depreciation and interest on the start-up costs in the partial budget for the years when benefits are expected. The last additional expense would be the variable costs (feed and non-feed) that are incurred by the additional pigs produced from the "skipped" females. The non-feed variable costs should be determined from existing farm records, if available. The feed costs should be estimated using the following information: (1) weight gain (market weight - weaning weight), (2) feed conversion, and (3) cost of feed. This added expense is the counterpart to the income realized from feeding them (see the section on additional income). We will not discuss the specific calculations for the example. The main thing is to understand the approach. Once you are comfortable with the concepts involved in partial budgeting, you will be able to apply them to many different situations in the course of practice.

SUMMARY

As the swine industry continues to evolve and develop a greater business orientation-one that demands justification of costs, benefits, and risk-exposure - the veterinarian will be confronted with the need to develop an economic basis

FINANCIAL EVALUATION AND DECISION MAKING IN THE SWINE BREEDING HERD

745

to supplement the biologic. The profession should view such a challenge as an opportunity to broaden its role in serving the businesses that make up the industry. However, to be effective in such an expanded role requires that the veterinarian develop a good working knowledge of risk and risk management as well as the role played by economic evaluation techniques used in financial evaluation in the risk management process. Several potential advantages exist for the veterinarian who determines to expand his or her risk management role by using financial evaluation in the course of day-to-day practice routine: • Additional service or consulting income may be generated through evaluating alternatives through decision analysis. • Client confidence may be strengthened in the veterinarian and in the recommendations made. • The costs of consulting services and health products for the client may be viewed as income-generators instead of being viewed solely as expenses. • Referrals of additional progressive clients may be generated by satisfied current clients. • The veterinarian may achieve personal satisfaction through substantiating his or her recommendation beyond clinical or experimental judgment. With the capability of using financial evaluation techniques in the evaluation and justification of recommendations comes significant responsibility. Reliance upon financial evaluation techniques as a more objective approach in the management of risk for clients carries with it an inherently greater degree of trust. Such trust must be deserved. The universal adage "garbage in, garbage out" applies directly to financial evaluation. Financial evaluation techniques have the potential to provide the decision-maker with objective and accurate analysis, improving the probability of choosing an optimal course of action for the business. However, the objectivity and accuracy achievable is highly dependent upon the quality and quantity of information used in the analysis. Veterinarians must be cognizant of the increased responsibility demand placed on those using financial evaluation techniques to direct the course of action for their clients. Financial evaluation tools are available to decision-makers that may improve the objectivity of the decision-making process, providing for a greater degree of confidence in the expected outcome. Stated another way, these tools can reduce the number of surprises a decision-maker encounters as a result of the decisions made. Ultimately, then, financial evaluation is a means by which the decisionmaker may integrate the science and art of decision-making. References 1. Anderson JR, Dillon JL, Hardaker JB: Agricultural Decision Analysis. Ames, Iowa State University Press, 1977 2. Boehlje MD, Eidman VR: Farm Management. New York, John Wiley and Sons, 1984, pp 229-250, 315-336, 438-488 3. Brealey RA, Meyers SC: Principles of Corporate Finance. New York, McGraw-Hill Book Company, 1988, pp G1-G12, 11-45, 71-86,93-116 4. Carpenter TE, Dilgard P: An application of computerized decision analysis. In Proceedings of the 3rd International Symposium on Veterinary Epidemiology and Economics, Arlington, VA, 1982, pp 408-414 5. Charette R, Martineau G-P: A decision tool for veterinary recommendations involving production parameters in swine finishing operations, In Proceedings of the International Pig Veterinary Society, Ninth Congress, Barcelona, Spain, 1986, p 412 6. Charette R, Martineau G-P: The veterinarian's role in growing-finishing units-Parts I-IV. Compend Contin Educ Pract 8:F104-F111; 9:F35-38, F81-84, F123-F126, 1987

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7. Deen J: Standard deviation as a measure of production. Comp Contin Educ Pract Vet 10:525-527, 1988 8. Dijkhuizen AA, Morris RS, Morrow M: Economic optimization of culling strategies in swine breeding herds using the PorkCHOP computer program. Prev Vet Med 4:341353, 1986 9. Duffy SJ, Stein TE: Correlations between production, productivity, and population factors in swine breeding herds. In Proceedings of the 10th Congress of the International Pig Veterinary Society, Rio De Janerio, 1988, p 345 10. Duffy SJ, Stein TE: Parity-specific production values for 68 North American swine breeding herds. In Proceedings of the 10th Congress of the International Pig Veterinary Society, Rio De Janerio, 1988, p 346 11. Ellis PR, James AD: The economics of animal health: 2. Economics in farm practice. Vet Rec 105:523-526, 1979 12. Fetrow J, Madison JB, Galligan DT: Economic decisions in veterinary practice: A method for field use. J Am Vet Med Assoc 186:792-979, 1985 13. Galligan DT, Marsh WE: Application of portfolio theory for the optimal choice of dairy veterinary management programs. Prev Vet Med 5:251-261, 1988 14. Galligan DT, Marsh WE, Madison J: Economic decision making in veterinary practice: expected value and risk as dual utility scales. Prev Vet Med 5:79-86, 1987 15. Goodger WJ, Weaver L, Fetrow J, et al: Development and use of an economic worksheet to assess dairy reproductive health programs. J Am Vet Med Assoc 193:436-439, 1988 16. Herbst AF: Capital Budgeting: Theory, Quantitative Methods, and Applications. New York, Harper and Row, 1982, pp 82-86 17. Hoblet KH, Miller GY, Bartter NG: Economic assessment of a pseudorabies epizootic, breeding herd removal/repopulation, and downtime in a commercial swine herd. J Am Vet Med Assoc 190:405-409, 1987 18. Hubbert WT: Perspective on veterinary preventive medicine in the US. J Am Vet Med Assoc 174:378-379, 1979 19. Huffman DC: Economic decision making by livestock producers. J Am Vet Med Assoc 174:381-384, 1979 20. Kislingbury CK: Repopulation payoff time. In Proceedings of the 1986 Minnesota Swine Herd Health Programming Conference, st. Paul, MN September 21, 23, 1986, pp 303-309 21. Kislingbury CK: Assisting clients with cash flow analysis. Compend Contin Educ Pract Vet 9:F285-F290, 1987 22. Lloyd JW, Kaneene JB, Harsh S8: Toward responsible farm-level economic analysis. J Am Vet Med Assoc 191:195-199, 1987 23. Madison J8, Fetrow J, Galligan D: Economic decisions in food animal practice: To treat or not to treat?; J Am Vet Med Assoc 185:520-521, 1984 24. Marsh WE: Economic Decision Making on Health and Management in livestock Herds: Examining Complex Problems Through Computer Simulation [PhD Thesis]. St. Paul, MN, University of Minnesota, 1986 25. Marsh WE: Consequences for swine farm income of depopulation as a disease control measure. In Proceedings of the 5th International Symposium on Veterinary Epidemiology and Economics, Copenhagen, Denmark, 1988 26. Marsh WE, Dijkhuizen AA, Morris RS: An economic comparison of four culling decision rules for reproductive failure in United States dairy herds using DairyORACLE. J Dairy Sci 70:1274-1280, 1987 27. Martin SW, Meek AH, Willeberg P: Animal health economics. In Veterinary Epidemiology: Principles and Methods. Ames, lA, Iowa State University Press, 1987, pp 219-242 28. Mather EC, Kaneene J8: Economic of animal disease. In Proceedings of a Conference held at the Michigan State University, 1987 29. Morrison R, Hanyanun W, Anderson P, et al: The decision to vaccinate the breeding herd for pseudorabies virus. In Proceedings of the Minnesota Swine Herd Health Programming Conference, St. Paul, MN, 1988, pp 162-168. 30. Mousing J, Vagsholm I, Carpenter TE, et al: Financial impact of transmissible gastroenteritis in pigs. J Am Vet Med Assoc 192:756-759, 1988 31. Ngategize PK, Kaneene J8: Evaluation of the economic impact of animal diseases on production: A review. Vet Bull 55:153-162; 1985 32. Ngategize PK, Kaneene J8, Harsh S8, et al: Decision analysis in animal health programs: Merits and limitations. Prev Vet Med 4:187 -197, 1986 33. Penson J8, Pope RD, Cook ML: Introduction to agricultural economics. In Decision Making in an Uncertain World. Engelwood Cliffs, NJ, Prentice Hall, 1986

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Address reprint requests to Dale D. Polson, DVM, MS Department of Clinical and Population Sciences University of Minnesota College of Veterinary Medicine St. Paul, MN 55108