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Lane DM. 1997;3:95-102 Using partial budgets to analyze selected

   

Production tool

May and June, 1997

Using partial budgets to analyze selected management practices associated with reduced preweaning mortality

David M. Lane, DVM; C. Matthew Rendleman, PhD; Stephen L. Ott, PhD

DML: 1314 East Grand Street, Carbondale, Illinois, 62901; CMR: Southern Illinois University, Department of Agribusiness Economics, Agriculture Building- Room 226, Carbondale, Illinois 62901-4410; SLO: Centers for Epidemiology and Animal Health, USDHA:APHIS:VS, Fort Collins, Colorado. Reprint requests to CMR.

Note: To make them readable, the figure GIFs in this article are very large [23k-43k each]. You may prefer to download the Acrobat PDF file instead (184k).

Summary

To illustrate the usefulness of the partial budget technique in analyzing four management variables associated with reduced preweaning mortality: all-in-all-out (AIAO) pig flow, power washing farrowing crates after every farrowing, observing a long idle time between farrowings, and washing sows prefarrowing.

The partial budget technique is a simple, yet powerful technique that can be easily set up as a spreadsheet. This analysis technique can help practitioners analyze the financial advisability of adopting a given management strategy in their clients’ herds.

Keywords: swine, partial budget, economic analysis, preweaning mortality

Received: Nov 2, 1995
Accepted: Jan 8, 1997

Preweaning mortality has historically been a problem for veterinarians and producers.1-5 While it is important to find management techniques that reduce preweaning mortality, it is also necessary to determine whether these strategies would be economically feasible to implement. The partial budget is a simple economic analysis technique that can nonetheless be a powerful tool in helping determine the financial feasibility of a given management strategy. In this paper, we describe the partial budget technique and, using data from the NAHMS National Swine Survey as example variables, illustrate its use.

Partial budgets

Partial budgets use the following formula to estimate the change in farm profit or loss that would occur when a management change is made in the operation of the farm:

  increased revenues
+ decreased costs
– increased costs
– decreased revenues
========================
= change in revenue

Because a given management change will affect only some expenses or income items, only the expenses and income that would be altered by the change are entered into a partial budget. A partial budget model does not take into account any changes in income or expenses that would be the same whether or not the management change was made.6 A simple partial budget can be calculated manually or can be easily constructed on a spreadsheet (Figure 1).

[Editors’ note: A partial budget spreadsheet template, compatible with Microsoft® Excel, is available for download from this page.]

Using the partial budget

The management variables serving as examples in this analysis represent the four management variables that were observed in the NAHMS National Swine Survey to significantly reduce preweaning mortality.1 (The data collection protocol of this survey has been described elsewhere.2) Bowman, et al.,1 investigated the impact on preweaning mortality of several facility attributes and management variables, including flooring type, supplemental piglet heat, cleaning method, length of idle time, cleaning frequency, sow washing, and all-in-all-out (AIAO) versus continuous swine flow in farrowing rooms. They analyzed these variables, along with farm size and region of the country, using a regression model. Bowman, et al., found that four of these management variables significantly reduced preweaning mortality. We have included these four for further economic analysis:

(We did not include the nonmanagement variables Bowman, et al., found significant in their study. Facility attribute variables are beyond the scope of this paper, which focuses on cost:benefit analysis of management parameters to help veterinary practitioners make economic judgements related to the daily management and operation of an average swine farm.)

Model assumptions

In our example analyses, our partial budget models all assume a hypothetical 85-sow, total confinement hog operation with 15 farrowing crates producing 160 litters per year.

The 85-sow hypothetical operation we used as our baseline in the model is small compared to many swine operations in the country today. However, we selected a farm of this size for our model because small hog operations still represent the average Midwestern hog operation. As of December 1995:

It is important for veterinarians to address issues of swine health affecting farms that, although declining in number, still represent the greatest number of swine enterprises. We believe that swine practice must address the economic health as well as the physical health of the operation. The partial budgeting technique applies to large operations as well as small ones, and can be used to input variables from a large unit as well as the 85-sow operation we used as our baseline.

We used the following assumptions to calculate an initial baseline revenue for our hypothetical herd:

In addition to these model settings, we assumed in our analysis that the baseline herd:

A partial budget analysis was then used to predict the effect of each management change on our hypothetical farm based on the change in piglets weaned per litter associated with each management variable. The change in revenue was divided by the number of litters to give cost or benefit in dollars per litter for each management variable for our hypothetical farm.

Capital recovery charges

Two of the management variables (longer idle times and washing sows before they farrow) require no initial capital expenditures to implement. Two of them, however (AIAO animal flow and pressure washing) do require significant initial capital expenditures to implement. For example, in our hypothetical model, we assumed that converting continuous-flow facilities to AIAO would have a fixed cost of $4000. We assumed that a unit would have a fixed cost of $3000 to purchase a high-pressure power washer for washing facilities between sow groups. It is necessary to properly account for fixed costs in the partial budget model to determine an accurate measure of the advisability of implementing various management strategies that require an initial outlay of capital.

Fixed costs for capital items consist mostly of capital recovery charges (CRC).6 The CRC value can substitute for depreciation, interest, repairs, taxes, and insurance. Capital recovery charges provide an accurate measure of fixed costs over time because the calculation takes into account the time value of money. The CRCs reflect changes in the market value of the asset over time. Ultimately, CRCs represent the annual opportunity cost of owning capital items.

The formula for calculating the CRC is:

where:

i = annual interest rate
n = number of years of useful life
BV = beginning market value
EV = ending market value

Once calculated, these capital recovery charges can be used as inputs into the standard partial budget (Figure 1).

All of the management strategies we analyzed in our partial budget model represent efforts to reduce preweaning mortality by reducing the pathogen load in the farrowing phase.8 Because the NAHMS study did not collect data that would allow us to ascertain whether concentrations of pathogens were indeed reduced in the farrowing units included in the survey,5 we lack the means to assess the correlation between the observed decreases in preweaning mortality and reduced disease. For this reason, we have not included in our partial budget some of the decreased costs (e.g., reduced veterinary costs, reduced medication, etc.) that would probably accompany reduced disease in farrowing units.

Examples using the model

Increased idle time

In the NAHMS survey, producers were asked to indicate whether they normally observed an idle time between farrowing groups of 1-2 days, 3-5 days, 1 week, 2 weeks, or 1 month or more. In the Bowman study,1 increasing idle time beyond 2 days was associated with decreased piglet mortality of 1.17 piglet deaths per 1000 piglet days and increase piglets weaned per litter of 0.2063 (Table 1).

It is unlikely that respondents who indicated that they observed no idle time between farrowings actually achieved 100% crate occupancy. Our example assumes 160 litters over 13 farrowing cycles per crate per year. This number of cycles has an inherent idle time of 2 days per cycle (365 days ÷ 13 = 28 days, but each farrow period averages 26 days). For our baseline herd, we assume that there will be an inherent 1- to 2-day idle time between farrowings (93.33% real occupancy at 160 litters). Thus, we input an additional 2 days of idle time into our partial budget model. This reduces litters per female year in our partial budget from the original 160 litters to 149.3 litters per female per year (160 x 0.9333 = 149.33). We did not anticipate that leaving facilities idle for a longer period between farrowings would result in any additional out-of-pocket expenses to a unit, so we added no additional expense to our partial budget model (Figure 2).

In our example, the partial budget analysis demonstrates a severe economic penalty for our hypothetical farm when farrowing crates are left idle for more than 2 days between farrowings. In operations that leave crates idle for 1-2 extra days over 13 farrowing cycles, there will be a penalty of 13-26 idle crate days in a given year. Idle time in the farrowing house reduces litters per female year. For the hypothetical herd in our partial budget analysis, the cost to the producer for loss of crate use exceeds the benefit gained from disease reduction (Figure 2). This example illustrates the fact that just because a given variable reduces disease and increases piglet survival, it may not be advisable to implement the practice.

Sow washing

The Bowman, et al.,1 study found that washing sows before they farrow was associated with a statistically significant reduction in preweaning mortality, yielding an extra 0.00169 piglets per litter–a reduced death incidence of 0.0099 piglet deaths per 1000 piglet days. We therefore added 0.00169 piglets to the partial budget to analyze the sow washing management strategy. We did not anticipate that initiating a sow-washing management strategy would result in any additional expenses to a unit (we are assuming that existing labor could be used), so we added no additional expense to our partial budget model (Figure 3). Sow washing in our model resulted in a $0.55 loss per litter.

It is likely that sow washing, which had a negligible impact on revenues in our hypothetical simulation, is highly confounded with another variable, such as facility washing.

AIAO pig flow

After accounting for farm size and region of the country, Bowman, et al.,1 found that there were 1.29 fewer piglet deaths per 1000 piglet days in AIAO facilities compared with facilities managed using continuous animal flow.1 Thus, we increased the number of pigs weaned per litter in the hypothetical model by 1.29. Because it is likely that adopting an AIAO animal flow strategy would reduce breeding efficiency somewhat, we assumed a 2% reduction in scheduling efficiency with AIAO. This leads to a small reduction in litters per female per year (156.8) from the original 160 litters. Converting this reduced mortality rate to additional piglets weaned, an additional 0.2273 pigs per litter were added to the 8.14 baseline litter size for AIAO over continuous flow (Table 1) in our model.

Also, we anticipated that there would be a one-time expense of $4000 to convert existing facilities to accommodate AIAO animal flow.9 We assumed that the life of the converted facilities would be 10 years, with a 6% interest rate, and an ending value of $800.00. The capital recovery charges for these inputs were calculated using the standard CRC formula:

using i = 6%, n = 10 years, BV = $4000, and EV = $800; and inserted into our partial budget (Figure 4).

Since the use of AIAO is thought to reduce disease, veterinary and drug costs should decrease and will further benefit the producer, although these decreased expenses were not entered into the partial budget model.

Adopting an AIAO animal flow strategy may bring other economic benefits that are not accounted for by this model. Because in an AIAO system farrowing occurs within a tighter schedule and less time is needed to supervise farrowings, a labor advantage for AIAO is assumed to exist.

For the hypothetical farm used in our analysis, converting the farrowing facilities to an AIAO animal flow stratetgy resulted in an increased profit. Such returns, however, depend upon many variables and may not be realized in your clients’ herds, or may exceed these estimates. Careful economic analysis with a simulation model can help your clients assess the advisability of adopting a technology like AIAO.

Pressure washing

Bowman, et al.,1 found that cleaning by pressure washing and disinfecting after each farrowing was associated with decreased piglet deaths per 1000 piglet days by 1.96, and increased piglets weaned per litter by 0.3449 compared to not cleaning after every farrowing (Table 1).

We specifically focused our analysis of power washing with disinfectant because it is the most common type of cleaning method used for cleaning the farrowing house. Because power washing after every farrowing does not reduce farrowing crate use, our budget assumes no loss of efficiency in the farrowing house. Thus, we input 160 litters per year into our model. We assumed $6.00 per hour labor and 15 minutes to clean each crate as an additional expense for this strategy, resulting in a total additional annual labor charge of $392. There would also be an additional $30 per year for electricity to run the washer (Figure 5).

The cost of a high-pressure washer for cleaning farrowing crates is $1200-$3000. Again, we must calculate the CRC formula to determine the fixed costs of a pressure washing system over time, and input the resulting value into our partial budget. For this calculation, we assume that the pressure washer costs $3000 and will last 5 years. Thus, with an interest rate of 6%, we have the following equation:

using i = 6%, n = 5 years, BV = $3000, and EV = $0.0.

This gives us an annual CRC of $712.19 — about 25% of the original cost. This is higher than the 12.5%-17% that is the rule of thumb return expected for machinery; however, in this case there is no salvage value and a short useful life.

Although not accounted for in our model, veterinary and drug cost should also be reduced if a producer began to clean facilities between groups, and that reduction could be substantial.

Sensitivity analysis

To make partial budgets more useful, one can perform further economic analysis to determine what effect various changes to the inputs into the partial budget would have on the profitability of the strategy. This technique is called sensitivity analysis. In our hypothetical model, we determined the effect on profitability of the following possible changes to inputs:

Generally, as the hog:feed ratio decreases–the price of hogs falls or the cost of feed rises—management changes that are profitable in the baseline case remain profitable, but less so. With hogs at $0.50 per lb and feed at $0.07 (a hog:feed ratio of 7.3), pressure washing is worth $25.48 more per litter. But with hogs at $0.42 and feed at $0.12, pressure washing is worth only $3.09 more per litter.

Partial budget analysis, particularly when coupled with sensitivity analysis, can provide practitioners with a reasonably simple yet powerful method to assess the potential financial impact of various management strategies on a given farm.

Implications

A template partial budget template, compatible with Microsoft® Excel, is available for download at the AASP website. Follow links to this article at: http://www.aasp.org/shap/issues/v5n3/.

References

1. Bowman GL, Ott SL, Bush EJ. Management effects on preweaning mortality: A report of the NAHMS National Swine Survey. SHAP. 1996;4(1):25-32.

2. Tubbs RC, Hurd HS, Dargatz D, Hill G. Preweaning morbidity and mortality in the United States swine herd. SHAP. 1993;1(1):21-28.

3. Crooks AC, Hurd HS, Dargataz D, Hill G. Economic cost of preweaning mortality: A report of the NAHMS national swine survey. SHAP. 1993;1(3)15-21.

4. Yeske P, Ott SL, Hurd HS. Facility effects on preweaning mortality: A report of the NAHMS national swine survey. SHAP. 1994;2(2)11-18.

5. National Swine Survey: Morbidity/Mortality and Health Management of Swine in the United States. USDA:APHIS:VS. Center for Epidemiology and Animal Health, Fort Collins, 1992.

6. Boehlje MD, Eidman VR. Farm Management. New York, New York: Wiley and Sons. 1984.

7. Hogs and Pigs Report. USDA:NASS. December 28, 1995.

8. Quinn PJ. Disinfection and disease prevention in veterinary medicine. In: Block SS. Disinfection, Sterilization, and Preservation. 4th Ed. Philadelphia, Pennsylvania: Lea and Febiger. 1991:846-868.

9. Kephart K. All-in, all-out management of swine. Pen Pages. Pennsylvania State University. 1992. (posted on the Internet) Document Number 28901232.