A total of 862 questionnaires were mailed to a national sample of school foodservice directors from school districts with 10,000 or more students enrolled. The questionnaire included queries regarding the financial data and characteristics of foodservice operations. The mean and standard deviation were calculated for financial data, size of the district, and characteristics of the foodservice operation. In addition, one-way ANOVA was conducted to see if there were differences in financial and operational characteristics among five school district size groups.


A total of 191 directors returned questionnaires for a 22% response rate. Mean food cost percentage was 45% ± 7% and mean labor cost was 46% ± 9% of total revenue. Financial and operational characteristics were not different among the five size groups, except for food cost percentages (F=2.66, p=0.04).

Applications to Child Nutrition Professionals

The results of this study provide information for school foodservice directors to use when comparing their financial performance to various benchmarks, such as the national mean or mean of school districts of a similar size. Child nutrition professionals can plan future actions based on these comparisons. Regular collection and publication of national data could be valuable for school foodservice directors to use during a continuous benchmarking process.

Full Article

Please note that this study was published before the implementation of Healthy, Hunger-Free Kids Act of 2010, which went into effect during the 2012-13 school year, and its provision for Smart Snacks Nutrition Standards for Competitive Food in Schools, implemented during the 2014-15 school year. As such, certain research may not be relevant today.

Managing food costs to ensure quality and optimize financial performance is a challenge for many school foodservice directors. Changes in education budgets make it difficult for school districts to subsidize meal programs (Decker et al., 1992; Stainbrook, 1991) and school foodservice directors need to achieve program goals within a limited budget. A number of school foodservice programs are operated at a deficit (March & Gould, 2001) and many state directors of child nutrition programs have concerns about cost control and effective financial management (Cater, Cross, & Conklin, 2001). For the purpose of effective financial management, Boehrer (1993) suggests that directors manage expenses and income as if school foodservice operations were businesses.

Benchmarking can help school foodservice directors meet their financial objectives, which is one of the basic goals for school foodservice operations. Furthermore, in order for directors to establish financial objectives and goals, benchmarking provides the information needed to support continuous improvement (Leibfried & McNair, 1992). Establishing financial objectives and goals for child nutrition programs is one of the competencies identified by ASFSA’s School Foodservice and Nutrition Specialist (Rainville & Carr, 2001). Directors of noncommercial foodservice operations reported that there are many benefits to benchmarking. These benefits, which are based on an in-depth understanding of the strengths and weaknesses of operation (Johnson & Chambers, 2000b), include improved operational efficiency and decision-making processes.

Benchmarking was first employed by the Xerox Corporation to meet the Japanese competitive challenge of the 1970s (Leibfried & McNair, 1992). It is defined as “a continuous, systematic management process for measuring work processes, products, and services for the purpose of organizational comparison and improvement” (Johnson & Chambers, 2000b). Five steps in benchmarking have been identified (Leibfried & McNair, 1992; Spendolini, 1992 ;Yasin & Zimmerer, 1995):

  • Determining what to benchmark;
  • Forming a benchmarking team;
  • Identifying sources of benchmark information;
  • Collecting and analyzing data; and
  • Taking

There are four types of benchmarking – internal, competitive, industry, and functional (generic) benchmarking (Liebfried & McNair, 1992; Spendolini, 1992). Internal benchmarking is done by collecting and analyzing information to compare the performance between different departments or operating units. It is also used to compare an operation with itself over time. Internal benchmarking is the most widely used yardstick for measuring performance by noncommercial foodservice directors, followed by competitive and functional benchmarking (Johnson & Chambers, 2000b).

Competitive benchmarking compares an operation with direct competitors that are selling to the same customer base. Industry benchmarking evaluates an operation within industry trends.

Functional, or generic, benchmarking contrasts organizations with state-of-the-art products, services, or processes (Liebfried, & McNair, 1992; Spendolini, 1992).

For some industries, there are established sources of data for benchmarking. For example, computer software is available to track important information for benchmarking in healthcare foodservices (Fuller, 2000). The National Restaurant Association (2002) regularly collects and publishes operational data for limited-service and full-service restaurants, such as food and labor cost percentages, other cost percentages, and sales percentages from food and beverages.

Unfortunately, there are limited data available for school foodservice directors to use for benchmarking. Previous studies on financial management in school foodservice have, for example, identified indicators of financial self-sufficiency (Wilson & Alkire, 1995), evaluated financial tools used by school foodservice directors (Johnson & Chambers, 2000a; Sanchez, Gould, & Sanchez, 1998), discovered operational commonalities among financially successful programs (Cater & Mann, 1997), and investigated components impacting financial status of an operation (Durham & Babb, 1997; Hiemstra, Foo, & Jaffe, 1996; Tart & Taylor, 1997).

However, these studies did not provide national data for benchmarking.

Benchmarking has long been a management tool for many other industries. Although most noncommercial foodservice managers recognize the need for a national database to measure and evaluate their operations (Schuster, 1997), limited data are available. In addition, there is no consistent way in which to organize and manage financial data (Cornyn, 2001); this challenges foodservice directors to compare their organizations against other similar operations.

The purpose of this study is to provide national benchmarking data on general financial performance and operational characteristics for foodservice operations in large school districts. The results of this study can provide valuable information for school foodservice directors to compare their program’s general financial performance against the benchmark standard and subsequently plan future actions.



To minimize variations caused by school district size, large school districts are the primary focus of this study. There were 865 school districts with more than 10,000 students in the national database maintained by Market Data Retrieval, a national school marketing company based in Shelton, CT. Out of this group, 30 were selected randomly to pilot test the questionnaire.

A total of 835 school districts received the final questionnaire. In addition, a list of 33 school districts with central kitchens, collected from previous research, was checked for overlapping districts. Twenty-seven school districts from the list met the size criteria and were added to the study sample to ensure adequate representation of districts with central kitchens. As a result, a total of 862 school districts were included in the final sample.

Research Questionnaire

A draft questionnaire was designed to collect general financial data. The survey included questions concerning annual figures for total food cost; total labor cost, including salary, wages, and benefits of production and non-production staff; other costs, such as direct and indirect costs; revenue from catering, a la carte, and snacks; total revenue; and excess or loss (total revenue minus total cost). Foodservice directors could either fill out the questionnaire or send a copy of their actual budget for the 2000-01 school year. Out of 191 responding school districts, 34 sent actual budgets and these numbers were coded by the researcher. A variety of terms were used for specific cost and revenue categories. However, specific categories could be aggregated to food, labor, other costs, total revenue, and excess or loss. These general categories were consistent across the school districts, even though sub-categories under general categories differed from district to district.

Other questions were included to obtain information about the school district size, the foodservice operation, and the foodservice director. The school district size was defined as the number of students enrolled in the district. Questions concerning foodservice operations included number of breakfasts, lunches, and snacks served (both annual and daily averages), method of defining meal equivalents (ME) to calculate meals per labor hour (MPLH), usage of prepared products, and type of production system. Definitions of each type of production system were given so that directors could choose the production type that most closely reflected their facilities. In this study, “on-site system” was defined as producing and serving food at the same site, “base kitchen system” produces food at a base kitchen for on-site service and at remote sites, and “central kitchen system” produces food at a central kitchen for service at remote sites. For foodservice directors, questions concerning education level and experience in school foodservice were posed.

The questionnaire was refined through a pilot test conducted with 30 randomly selected directors who were excluded from the final study sample. Based on comments from the pilot study, questions regarding food production type were revised to include all existing types. Other minor changes in wording were made to improve readability. The Iowa State University Human Subjects Committee approved the study protocol and questionnaire prior to use.

Data Collection

The questionnaire was mailed with a cover letter and self-addressed postage-paid return envelope. Each questionnaire was coded for follow-up purposes. Those who were interested in receiving a summary of the study results were invited to complete an enclosed postcard and return it with the questionnaire. It was explained to respondents that the card would be separated upon receipt of the questionnaire to ensure the confidentiality of the participant. Reminder and thank-you postcards were mailed one week after the first mailing. As recommended by Dillman (2000), the questionnaire was sent a second time to those who had not yet responded three weeks after the initial mailing.

Data Analysis

Descriptive statistics (mean and standard deviation) were calculated for the school districts’ financial performance and other operational characteristics, including size of the school, lunch participation rate, and usage of prepared ingredients. One-way ANOVA was conducted to see if there were differences in financial and operational characteristics among the five different size groups. Group 1 is composed of schools with less than 12,000 students enrolled, Group 2 from 12,000 to 16,000 students, Group 3 from 16,000 to 22,000 students, Group 4 from 22,000 to 37,000 students, and Group 5 with more than 37,000 students. For all statistical tests, an alpha level of 0.05 was used for significance.

Results And Discussion

 Sample Characteristics<br> Of the 862 questionnaires mailed, 191 were returned for a 22% response rate. More than one-half of responding foodservice directors (53%) in school districts with more than 10,000 students had a graduate degree, followed by 36% had with a bachelor’s degree. The majority of the directors (63%) had more than 15 years of school foodservice experience.

Table 1 summarizes the school districts’ financial performance and other operational characteristics, including size of the school district, lunch participation rate, and usage of prepared ingredients. The number of students in the school districts varied from 9,800 to more than 230,000. Sales from a la carte service were about 20% of the total revenue with considerable variation from district to district. Catering accounted for 1% ± 3% of the total revenue. The foodservice operations in these school districts had a mean food cost of 45% ± 7% and labor cost of 46% ± 9%. Food and labor cost percentages were calculated as the cost percent of total revenue. The mean lunch participation rate (number of lunches served per day/number of students enrolled) was 57% ± 17%. More than half of the ingredients used in school foodservice operations were pre-prepared items.

Table 1: Financial Performance and Operational Characteristics of School District Foodservice Operations (N=191)
Mean ± SD
Total revenue $8,466,121 ± $9,771,496
Excess (loss) $214,954 ± $1,136,741
Catering revenue % 1% ± 3%
A la carte revenue % 20% ± 15%
Food cost % 45% ± 7%
Labor cost % 46% ± 9%
Other cost % 13% ± 12%
Number of students 28,930 ± 31,960
Average lunch participation ratea  






Percentage of prepared ingredients used  






Note: All the percentages are percent of total revenue


a average number of lunch served daily / number of students enrolled


Productivity was measured using meals per labor hour (MPLH). To calculate MPLH, the total number of meals produced was determined by using a meal equivalent (ME) calculation. ME was calculated using lunch as the standard means of comparison. The mean of what each school district indicated as breakfasts, snacks, a la carte sales, and catering sales was equivalent to one lunch. As a result, one lunch corresponded to two breakfasts, four snacks, $2.15 of a la carte sales, or $2.32 of catering sales. To calculate MPLH, the sum of those four numbers and the annual number of lunches served was used as the total ME.

The formulas used to calculate ME and MPLH were:

The mean MPLH was 14.9 ± 5, indicating that school foodservice operations produced approximately 15 lunches or ME per labor hour.


Although data were gathered from large school districts with an average of ten thousand students or more, size of school districts varied greatly from 9,800 students to 230,000. Comparing financial and operational characteristics to general mean figures may not be meaningful due to the way in which district size influences many aspects of foodservice operations. Table 2 organizes financial and operational figures by the five school district size groups.

Table 2: Financial Performance and Operational Characteristics By Size of School District (N=191)
Groupa Mean ± SD
Total revenue
1 $3,220,235 ± $860,992
2 $4,151,216 ± $1,285,847
3 $5,318,698 ± $1,793,645
4 $8,617,876 ± $2,207,422
5 $22,115,326 ± $16,328,039
Excess (loss) %
1 0% ± 6%
2 5% ± 17%
3 2% ± 7%
4 5% ± 15%
5 1% ± 9%
Catering revenue %
1 3% ± 6%
2 2% ± 2%
3 1% ± 3%
4 2% ± 3%
5 1% ± 2%
A la carte revenue %
1 19% ± 11%
2 23% ± 21%
3 23% ± 16%
4 21% ± 17%
5 14% ± 10%
Food cost %
1 48% ± 6%
2 45% ± 9%
3 44% ± 6%
4 43% ± 5%
5 43% ± 9%
Labor cost %
1 46% ± 8%
2 47% ± 13%
3 46% ± 8%
4 43% ± 7%
5 47% ± 9%
Other cost %
1 9% ± 4%
2 13% ± 13%
3 15% ± 14%
4 16% ± 18%
5 13% ± 8%
Average lunch participation rateb
1 61% ± 13%
2 55% ± 19%
3 56% ± 17%
4 58% ± 17%
5 55% ± 17%
Percentage of prepared ingredients used
1 65% ± 21%
2 71% ± 22%
3 67% ± 23%
4 66% ± 25%
5 67% ± 22%
Meals per labor hour
1 16 ± 6
2 15 ± 5
3 13 ± 4
4 15 ± 4
5 14 ± 4
Note. All the percentages are percent of total revenue


a Group: 1 (less than 12,000); 2 (12,000~16,000); 3 (16,000~22,000);

4 (22,000~37,000); 5 (more than 37,000)

b Average number of lunch served daily/number of students enrolled

One-way ANOVA was conducted to see if there were differences in financial and operational characteristics among differently sized groups. Table 3 summarizes the results. Even though total revenue increased in relation to the size of school districts, other percentage figures were not different among the groups, except for food cost percentage (F=2.66, p=.04). Food cost percentages decreased as the school district size increased.

Table 3: Analysis of Variance for Financial

and Operational Characteristics By Size of Districts.

dfa F p
Total revenue 4 39.92 0.0**
Excess (loss) 4 1.08 0.37
Catering revenue % 4 0.66 0.62
A la carte revenue % 4 1.43 0.23
Food cost % 4 2.66 0.04*
Labor cost % 4 1.13 0.34
Other cost % 4 1.79 0.13
Average lunch participation rateb  






Percentage of prepared ingredients used  






Meals per labor hourc 4 0.81 0.52
Note. All the percentages are percent of total revenue


* p < .05

** p < .01

a The district size was collapsed into five groups as explained in Table 2 thus degrees of freedom is four. Each group included approximately equal number of districts.

b average number of lunch served daily / number of students enrolled

c total ME / total labor hours

Conclusions And Applications

Results of this study provide national means for financial performance indicators and operational characteristics. By comparing these numbers, school foodservice directors can evaluate their financial performance, using the national mean or the mean of school districts of a similar size as a benchmark. In order to achieve organizational improvement, benchmarking should be a continuous process (Spendolini, 1992). Therefore, financial performance data in school foodservice operations need to be collected regularly. Frequent collection and publication of this data could be valuable for school foodservice directors in their benchmarking processes.

Data collected for this study indicated that school districts were not consistent in their systems of accounts. Although the result of this study provided aggregated information, such as total food, labor, and other costs, sub-categories of cost and revenue varied. The use of different systems of accounts in noncommercial foodservice operations can be challenging to foodservice directors who desire to accurately compare and analyze data for benchmarking (Cornyn, 2001). The National Food Service Management Institute (NFSMI) proposed a uniform financial management information system (Cater, Cross, & Conklin, 2001). Utilizing this system is recommended to school foodservice directors, as it is useful in collecting information that is necessary to monitoring financial performance. Such a uniform system can aid in the collection of comparable information among school districts and facilitate continuous benchmarking of financial performance.

Due to the inconsistent data management among school districts, one limitation of this study was that only general financial figures could be provided. In addition, the relatively low response rate (22%) could imply that the national mean figures provided in this study may be different from the true value. Further research is necessary to guide school foodservice operators toward continuous improvement and provide basic benchmarking information in other aspects of school foodservice operations, including quality of food, student satisfaction, and employee job satisfaction. In addition, studies to identify accurate and easy-to-collect measurements for other aspects of school foodservice operations can benefit from these benchmarking efforts.


 The authors wish to thank the American School Food Service Association’s Child Nutrition Foundation for funding this study through the Hubert Humphrey Research Grant and the participating school foodservice directors for their valuable responses.



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Hyunjoo Hwang and Sneed are, respectively, a PhD candidate and professor of Hotel, Restaurant, and Institution Management at Iowa State University.

Purpose / Objectives

The purpose of this study is to present compiled national benchmarking data on the financial performance and operational characteristics for foodservice operations in large school districts.