Download Managing Meal Costs: Variance Generation, Analysis, and

Managing Meal Costs:
Variance Generation,
Analysis, and
Interpretation
BY KEN MILANI, PH.D.,
THE AUTHORS
AND
AARON PERRI
PROVIDE AN EXAMPLE OF HOW A RESTAURANT HAS APPLIED A COST
VARIANCE FRAMEWORK TO ITS FOOD AND LABOR COSTS.
ALTHOUGH APPLYING
THESE TECHNIQUES IN A RESTAURANT SETTING POSES UNIQUE PROBLEMS THAT
A MANUFACTURING OR SERVICE SETTING DOES NOT HAVE TO FACE, THE FRAMEWORK
OFFERS HIGH-QUALITY INFORMATION THAT A RESTAURANT CAN INTEGRATE
INTO ITS PROFIT-AND-LOSS REPORTING.
This article is dedicated to the memory of Grace and Albert Milani, Ken’s parents, who owned
and operated a restaurant for almost 20 years.
imes are tough in the restaurant industry. Because of the weak economy, the number of
people eating out has fallen at the same time
that the costs of producing and serving meals
have increased. To coax more customers into
dining away from home, restaurants are exploring and
implementing marketing and promotion efforts. This
article, however, will focus on meal costs by examining
an integrated cost control analysis.
First, we will explain the traditional cost variance
framework, then apply it to the control of labor and
food costs in a restaurant operation. Next, we will dis-
cuss the considerations in setting cost standards, illustrate calculations of cost variances, and propose possible
interpretations of the calculated variances. Throughout
the effort, Legends of Notre Dame Restaurant and Alehouse Pub (LEGENDS) serves as the primary example, and there are five supporting examples.
Cost variance analysis begins with the accounting
processes of determining theoretical costs, setting cost
standards, collecting actual costs, and ending with evaluating performance. Properly determining theoretical
costs in the restaurant business involves setting standard recipes and preparation procedures for every menu
T
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SUMMER 2013, VOL. 14, NO. 4
item. Setting cost standards is the next step in this
process. The standard or expected cost is the total cost
that should occur for an actual level of activity within
the restaurant. An example dealing with Irish Nachos at
LEGENDS will reveal in greater detail that standard
costs vary from theoretical costs as the result of a certain
degree of unavoidable occurrences in the kitchen.
The analysis rounds out with collecting actual costs
and evaluating performance evaluation. Expected costs
result primarily through analyzing theoretical costs and
looking at historical operations. Ideally, this deliberate
process involves many people, including purchasing
personnel, budget administrators, managers, and possibly kitchen or wait staff. Although actual costs are simply the actual cost of goods or labor during a certain period, collecting actual cost data can be quite difficult.
We will discuss this topic thoroughly later. Finally, performance evaluation compares budgeted and actual
costs during the period. We can separate the difference
between actual costs and budgeted costs (i.e., variance)
into subcomponents so we can pinpoint, explore, and
address the causes of and responsibilities for the
variances.
Table 1. Traditional Cost Variance
Framework
Total Variance = (AR ✕ AQ) – (SR ✕ SQ), or
Actual Cost – Standard Cost
This variance measures the total difference between the actual cost and the standard cost for
a given output.
Rate Component = (SR ✕ AQ) – (AR ✕ AQ), or
AQ (SR – AR)
This variance subcomponent measures the effects that result from utilizing units of input (labor
or goods) at a price or cost different from the
standard.
Quantity Variance = (SR ✕ AQ) – (SR ✕ SQ), or
SR (SQ – AQ)
This variance subcomponent measures the effect
of using a quantity of input (goods or labor) that
is different from the amount predicted for the
level of output.
T R A D I T I O N A L C O S T VA R I A N C E F R A M E W O R K
Example 1
We developed a variance analysis model to evaluate
costs that occur in the meal preparation process. To begin, we can express the actual cost of meal preparation,
defined as the exact amount the restaurant expended,
as the actual quantity of resources (AQ) times the actual
per-unit cost rate (AR), or AQ ✕ AR. On the other hand,
the budgeted cost represents the desired cost of the
preparation process given the actual number of prepared meals. In other words, this is the amount that the
restaurant should have expended to produce the actual
output. We can express this as the standard quantity of
resources used (SQ) for the actual meal preparation
level times the standard per-unit rate (SR), or SQ ✕ SR.
The total variance is the difference between the actual
cost and the standard cost, expressed mathematically as
(AR ✕ AQ) – (SR ✕ SQ). If the actual amount exceeds
the budgeted amount, we label the variance as unfavorable, and we label the opposite result as favorable. See
Table 1 and Example 1 for a summary and application
of the traditional cost variance framework.
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Use the following values and the information from Table 1 for
Brian’s Better Burgers, which sold 1,000 half-pound burgers in
the time period being examined:
Actual rate/cost
$5.95/pound for 580 pounds
Actual quantity
0.58 pound per burger
(i.e., 580 divided by 1,000)
Standard rate/cost
$6.00/pound for 500 pounds
Standard quantity
0.50 pound per burger
Total Variance
Actual (AR ✕ AQ) or $5.95 ✕ 580 = $3,451
Standard (SR ✕ SQ) or $6.00 ✕ 500 = $3,000
Unfavorable variance
($451)
Rate Component
AQ (SR – AR) or 580 ($6.00 – $5.95) $29 Favorable
Quantity Component
2
SR (SQ – AQ) or $6.00 (500 – 580)
($480) Unfavorable
Total variance
($451)
SUMMER 2013, VOL. 14, NO. 4
In a restaurant setting, the expected or budgeted
amount in the variance analysis model is a flexible
value that depends on the actual activity level rather
than a static projection of costs based on expected
activity. This flexible amount is part of the post-mealpreparation analysis and is a function of the actual activity level. At higher activity levels, the total flexible budget figure is larger, and it is smaller at lower levels.
Example 2 illustrates the flexible budget procedure
used in an analysis of labor costs.
ance is unfavorable, revealing that the company spent
more than it should have for this amount of input. If
the opposite holds true, the variance is favorable.
The second element of the total variance, the quantity component, results from comparing a new, recalculated value of standard rate times actual quantity with
the flexible budget amount. As Table 1 shows, we express this in a shortened formula of SR (SQ – AQ). This
variance results from incurring an actual rate per unit
for a quantity of input that differs from the expected
standard quantity. As before, if the actual amount exceeds the standard, the variance is unfavorable, and the
opposite is favorable.
Example 2
Kelly’s Kitchen developed the following standard information
for its upcoming year:
USING
Standard labor cost: $25 per hour
ONE-DISH EXAMPLE
To provide a more usable end result and to illustrate
the ultimate goal of cost variance analysis within a
restaurant setting, let’s look at one menu item from start
to finish and use that as a framework to discuss the
overall restaurant operation. Once the LEGENDS chef
establishes exactly how many ounces of chips, cheese,
and other toppings go into an order of Irish Nachos,
he/she will be able to properly calculate the theoretical
cost of that particular dish. Note that the food cost does
not, and should not, take into consideration indirect materials such as the oil to fry the chips. Table 2 illustrates
that the food cost associated with making a plate of
Irish Nachos is $2.87 under normal conditions in a perfectly run kitchen at LEGENDS.
The phrase “perfectly run kitchen” is obviously a
major assumption. A restaurant kitchen will never operate with such efficiency that will permit actual food
costs to align with theoretical costs. While a good
kitchen manager will work to reduce the cause of these
variances, there will inevitably be miscues in the
kitchen (e.g., food will spoil, measurements will not be
as precise). This is where setting expected costs comes
into play. Developed primarily from historical data
analysis, the expected cost will take into account inevitable operating situations that cause costs to fluctuate. For example, it is nearly impossible to measure out
exactly four ounces of shredded cheese, and some tortilla chips in every bag are unusable because they are
broken into crumbs. Careful observation of the Irish
Nachos preparation and costing through the years has
Standard hours/meal: 12 minutes or 0.2 hours
The static budget amount to prepare 3,000 meals, the
expected number for a particular time period, is $15,000:
3,000 ✕ 0.2 hours/meal ✕ $25
The restaurant served 2,750 meals during the time period.
Based on the actual information, the flexible budget is
$13,750:
2,750 ✕ 0.2 hours/meal ✕ $25
Clearly, the flexible amount differs from the static
amount because the expected level of activity did not
occur. Although we may use the difference between the
static and flexible budget amounts to evaluate the budget forecasting process, we must compare the evaluation of actual operations through cost variance analysis
to the flexible or recalculated budget amount.
The total variance (budgeted or standard costs minus
actual costs) includes two elements: the rate or price
component and the quantity component. The rate component finds the product of the standard rate and the
actual quantity being calculated and compared to the
actual cost of production. The formula for rate variance
of (SR ✕ AQ) – (AR ✕ AQ) is shortened to AQ (SR – AR),
as Table 1 shows. A rate or price variance results when
the actual quantity of input is incurred at a rate or price
that is different from the standard rate or price. Once
again, if the actual cost exceeds the standard, the vari-
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Table 2. LEGENDS’ Irish Nachos Recipe and Theoretical Cost
Amount/Item
6 oz. Tortilla Chips
Cost
Total
$0.08/oz.
$0.48
4 oz. Shredded Cheese
$0.24/oz.
$0.96
6 oz. Salsa
$0.15/oz.
$0.90
1 oz. Guacamole
$0.13/oz.
$0.13
1 oz. Black Beans and Corn
$0.08/oz.
$0.08
1 oz. Sour Cream
$0.22/oz.
$0.22
½ oz. Jalapeños
$0.20/oz.
$0.10
$2.87
revealed that the expected cost of making Irish Nachos
is $2.92, not $2.87.
Now that we have theoretical and expected costs for
the Irish Nachos, it is time to determine the actual cost
of the dish during a certain period of time—one month,
for example. This step can be very difficult, especially
if the recipes are complex or if a menu cross-utilizes
many different items. We will discuss overcoming these
complexities later. For simplicity’s sake at this juncture,
we will assume that LEGENDS uses the ingredients
for Irish Nachos only and depletes inventory levels at
the end of each month.
To calculate the actual cost of the Irish Nachos,
LEGENDS takes the cost of all the ingredients (i.e.,
salsa, cheese, guacamole, etc.) the restaurant purchased
during the given month and divides it by the number of
Irish Nachos sold in that month. For example, if the
cost of ingredients was $5,008 and there were 1,600 orders of the Nachos, the actual cost of Irish Nachos
would be $3.13 ($5,008/1,600). This actual cost of $3.13
is higher than the theoretical cost of $2.87 and also the
expected cost of $2.92, meaning there is an unfavorable
variance.
An operator should be concerned with the variance
between actual and expected. In this case, the Irish Nachos have produced an unfavorable variance of $0.21
($3.13– $2.92) per order on average. Because customers
ordered 1,600 servings of this appetizer, this equals a total unfavorable variance of $336 ($0.21 ✕ 1,600) for the
month. If the manager ignores the variance, this could
create a negative variance of more than $4,000 for the
year.
Naturally, the next step is to question why the vari-
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ance occurred. Did the cost of cheese increase? Did a
case of tortilla chips get smashed? Are the cooks not
portioning the ingredients properly? The numbers simply become a tool that allows the kitchen manager to
detect and address the problem. This is just one item
on a menu containing more than 100 different food and
beverage offerings, so it becomes evident why using
cost variance analysis in a dining operation is important.
DETERMINING LABOR
AND
FOOD
C O S T S TA N DA R D S
The first step in cost variance analysis is to set standards by which to judge performance. This is an essential element of the restaurant’s budgeting process.
There are three major aspects of operational budgets:
planning, motivation, and evaluation. For planning purposes, the operational budget, or standard, should represent the expected, most likely outcome for an operation, but such a budget may not serve as an adequate
motivator to those responsible for the budgeted activity.
When a standard is set, the operation gets a specific
target. If this target is too easy to attain, the budget is
inadequate for the purpose of motivation, so the planning and motivation roles conflict. A budget based on
the most likely outcome will be exceeded half of the
time merely by chance if the standards were determined in an unbiased manner. Such a budget is too
easy to achieve. Potential conflict may also exist between the budget’s motivational purposes and the budget’s purpose of evaluation, which obviously happens
after the operator has collected the actual results. It is
not, however, as simple as looking at actual-vs.expected results because there must be some differenti-
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Table 3. 16-Week Data for LEGENDS of Notre Dame
Week
Labor Hours
Direct Labor Cost
Food Cost
1
2
# Customers Served Food Sales
958
$8,124
$7,340
1,795
$25,882
999
$8,298
$7,608
1,873
$26,886
3
1,026
$8,938
$7,947
1,944
$27,828
4
963
$8,257
$7,451
1,820
$26,139
5
1,006
$8,189
$7,342
1,864
$26,210
6
1,009
$8,485
$7,842
1,946
$26,957
7
960
$8,237
$7,395
1,815
$26,114
8
948
$8,255
$7,353
1,801
$25,928
9
968
$8,347
$7,791
1,896
$26,773
10
909
$7,972
$7,010
1,728
$25,183
11
914
$7,992
$7,062
1,716
$25,126
12
1,001
$8,147
$7,821
1,885
$26,345
13
926
$8,054
$7,143
1,746
$25,423
14
947
$8,079
$7,187
1,771
$25,731
15
932
$8,065
$7,180
1,757
$25,454
16
946
$8,083
$7,350
1,781
$25,759
15,412
$131,522
$118,822
29,138
$417,738
ation between controllable and uncontrollable (i.e., the
causes of a variance between actual and budgeted cost
at the end of a period may be classified into two
components—those causes that are and should have
been controlled by the manager and those that are not).
Unexpected inflation is an example of an event in the
latter category that should have caused the standard to
change during the period. The manager then should be
evaluated on a sort of prorated standard to extract the
uncontrollable components from the budget variance.
At the same time, managers may not be totally committed to achieving budget objectives if there is some possibility that the standards by which they are judged may
change. On the other hand, managers may become frustrated if they believe that uncontrollable factors may
trump the effect of their actions on budget variances.
Example 3 illustrates this type of situation.
For these reasons and to standardize the budgeting
process to some degree, we recommend that restaurants
use a statistical approach to setting the cost standards
that will be used later in the cost variance analysis.
In developing labor and food cost standards, the
restaurant manager should note that labor and food
costs are by nature variable within a relevant range of
activity. Labor costs vary with the number of labor
hours consumed, and food costs generally vary with dollars of sales. Thus, calculating an average is a convenient and simple way to approximate the costs incurred
per unit of activity. Averaging the 16 observations in the
first two columns of Table 3 yields a standard labor rate
of $8.534 per labor hour. Similarly, dividing total food
cost by total food sales for the 16-week period yields a
standard food cost of 28.44% of sales:
Standard labor rate
$8.534 = $131,522/15,412
Example 3
Standard food cost
A LEGENDS manager knows that an upward spike in petro-
28.44% = $118,822/$417,738
leum costs drives up dairy and fresh fruit prices, which gen-
Many costs, however, are not purely variable since
they include both fixed and variable elements. In this
case, a second statistical technique, linear regression,
erates higher costs than anticipated. The impact of the increased dairy and fruit prices more than offsets efficiencies
the manager recently introduced in the kitchen operation.
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can approximate both the rate of variable costs and the
component that remains fixed with the activity level. In
developing quantity standards, the standard number of
labor hours per customers served apparently exhibits
such a relationship.
Figure 1 plots the relationship between the number
of customers the restaurant served and the labor hours
to serve them. The plotting reveals that labor hours do
not relate to the number of customers served in a
purely variable fashion. As a result, the line drawn to
approximate the relationship between the number of
customers and the number of labor hours does not begin at 0,0. In fact, calculation of the least-squares regression line, which is intended to make the best fit of the
plotted points shown in Figure 1, yields the following
estimate of the relationship: Y = 119.86 + 0.4631x.
Spelled out, this means that the total number of labor
hours for any given number of customers will be a minimum of 119.86 plus an additional 0.4631 labor hours for
each customer served. In other words, it takes approximately 120 hours of direct labor simply to open the
doors at LEGENDS, regardless of the number of
guests.
P O I N T- O F - S A L E S Y S T E M S
Point-of-sale (POS) systems can be extremely valuable tools
in a restaurant. The most advanced software on the market
can automatically calculate some of the information we discussed. These machines are not financially or logistically
feasible for all organizations, and they vary greatly in functionality. Additionally, it is important for all restaurant operators to effectively understand the intuition involved in cost
variance analysis because the numbers tell only a part of the
story. Furthermore, the numbers from POS systems are frequently skewed because they rely entirely on employees
accurately inputting thousands of pieces of data throughout
any given period.
made up of more than 100 menu items that cross-utilize
ingredients at every turn. Furthermore, the example
does not evaluate labor cost variances, which is where
the pragmatics of cost variance analysis come into play.
Table 3 shows a weekly cost data sample for
LEGENDS. With the information in the table, we can
use statistical techniques such as averages or linear regression to create price and quantity standards. Once
we develop historical standards, we can analyze labor
and food costs by using basic statistical methods to develop standards for both. The rate standard for labor
T O TA L R E S TAU R A N T A N A LY S I S
The very basic Irish Nachos example poses many difficulties when trying to evaluate an entire menu portfolio
Labor Hours
Figure 1. Relationship of Labor Hours to Customers Served
1,040
1,020
1,000
980
960
940
920
900
y = 119.86 + 0.4631x
1,700
1,750
1,800
1,850
1,900
Customers Served
1,950
Note: y = Labor Hours
x = Customers Served
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SUMMER 2013, VOL. 14, NO. 4
2,000
Table 4. Data for Week X
Week
Labor Hours
Direct Labor Cost
Food Cost
X
975
$8,229
$7,350
# Customers Served Food Sales
1,730
$26,098
recommended way to calculate food costs. If inventory
levels are stable, however, we can approximate food
costs satisfactorily using the value of the period’s purchases. Direct labor costs in Table 3 encompass the
wages that direct labor employees earn and do not include indirect labor costs (e.g., salaries of the manager
or chef). Presumably, the restaurant can control other
labor costs (e.g., wages of cooks, dishwashers, and bartenders) by scheduling staff as a function of forecasted
activity levels. In the case of a restaurant, the appropriate activity level to forecast is commonly the number
of customers.
costs is the cost of using one labor hour, while the quantity standard is the number of labor hours to provide
food and service for one restaurant guest. For food cost,
the price standard is the food cost per dollar of sales,
otherwise known as the food cost percentage, and the
quantity standard is the dollars of sales that the restaurant should earn per guest. A restaurant operator should
have or should develop the ability to capture this data
from either a point-of-sale system or some other recordkeeping system (see Point-of-Sale Systems, p. 6).
Data that might be somewhat difficult to obtain
would be the weekly food cost because restaurants
usually maintain some food in inventory. To determine
food costs, the most accurate method is to adjust the
purchases for a period for the costs of beginning and
ending inventory (i.e., Cost of Meals Served = Beginning Inventory + Purchases – Ending Inventory). The
calculation requires taking a physical inventory or applying an approximation technique each time the
analysis occurs, which is the most accurate and highly
Now that we have established standards, we can effectively analyze cost variances for a set period. For example, we want to analyze week X, which Table 4 features.
Using the standards we already calculated and the
data from week X, we can determine the labor and food
cost variances in Tables 5 and 6.
Table 5. Labor Cost Variance
Table 6. Food Cost Variance
Actual Rate ✕ Actual Quantity
Actual Food Cost
$8.44* ✕ 975 = $8,229
$7,350*
Standard Rate ✕ Standard Quantity
Standard Food Cost
$8.534** ✕ 921.02*** = $7,860
$7,422**
Standard – Actual = Total Variance
Standard – Actual = Total Variance
$7,860 – $8,229 = ($369)
$7,422 – $7,350 = $72
Because actual labor costs were higher than the
Because actual food costs were lower than standard
standard costs, we have determined an unfavorable
(expected) food costs, we have determined a
variance of $369 in labor costs.
favorable variance of $72 in food costs.
*This
C O S T V A R I A N C E A N A LY S I S
*From
is Direct Labor Cost/Labor Hours
**Average
***Regression
**28.44%
from Table 3
relationship formula:
inventory
Standard Food Cost ✕ $26,098
Actual Food Sales
0.4631(1,730) + 119.86 = 921.02
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Table 5 indicates an unfavorable direct labor variance
of $369 that we can further break down:
Rate Variance = AQ (SR – AR), or
975 ($8.534 – $8.44)
$92 Favorable
Quantity Variance = SP (SQ – AQ), or
$8.534 (921.02 – 975)
($461) Unfavorable
($369)
◆ Did the purchaser overlook discounts?
◆ Did avoidable rush orders cause higher costs?
◆ Did out-of-stock items necessitate substitution of
better quality items to meet demand?
On the other hand, the purchaser may justify the
variance as being a result of inflationary price increases
or rush orders that could not have been foreseen.
Favorable cost variances result from paying less for
food items than the restaurant anticipated. The manager should investigate significant favorable cost variances, however, to ensure that inferior goods are not being substituted because this practice may improve
short-run profitability but have an adverse impact in the
long run. If the cost variance is justifiable and continues, the restaurateur should alter the standard and take
action to extend the favorable purchasing outcome to
other items. As a final consideration, it might be worth
passing some savings on to restaurant patrons in the
hope of increasing volume.
Table 6 reports a favorable $72 food cost variance.
The variance cannot be segmented into cost and quantity components because of a lack of information.
I N T E R P R E TAT I O N
OF
VA R I A N C E S
The traditional analysis of food and labor costs in a
restaurant operation typically begins with determining
the food cost percentage (food cost divided by food
sales) and the labor cost percentage (labor cost divided
by food sales). The more astute restaurateur realizes
that, for the operation to be profitable, these ratios
should remain and report at some optimal level, given
the restaurant’s specific characteristics and goals. Percentages above the optimum suggest a higher level of
service or food quality, but also a degeneration of profits
unless increased sales volume offsets the higher costs.
Higher-than-expected percentages may also signal the
existence of theft, excess spoilage, or generally poor internal controls.
On the contrary, lower percentages suggest less service, lower quality, and smaller portions, but higher
profits unless sinking sales outstrip reduced costs.
Restaurateurs are right to examine food and labor cost
percentages, but examination at this level only fails to
suggest or uncover possible factors that affect deviations
from normal percentages.
Food Quantity Variances
The food quantity variance is the responsibility of the
production personnel. Unfavorable quantity variances
result from using more food than the standard allowance for the number of meals served. Possible
causes include waste, spoilage, insufficient portion control, pilferage, and poor preparation techniques. The
unfavorable result, however, might not be within the
control of the production personnel. Perhaps an incorrect end-of-period physical inventory or an unfavorable
food sales mix led to the quantity variance. As not all
menu items are expected to result in the same food cost
percentage, a greater ratio of high food cost at times results in a higher cost percentage.
Favorable quantity variances result from using less
food than anticipated, given the number of meals
served. This may be an unpopular outcome if the guest
has received less than expected. Alternatively, if the
variance resulted from production efficiencies, the manager should encourage such practices to not only continue but expand as well. If the cause is a favorable
sales mix, the manager should take note of it. Example 4
illustrates the calculation and analysis of a food cost
variance.
Food Cost Variances
The food cost variance is the responsibility of the individual or individuals performing the purchasing function for the restaurant. Unfavorable cost variances result
from paying more for food items than expected. An
analysis must determine:
◆ Did the purchaser obtain the best prices?
◆ Did the purchaser buy better quality items than
would be commensurate with the prices in the
restaurant?
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Example 4
Labor-Efficiency Variances
The labor-efficiency variance applies to the average
quantity of labor to serve one customer. Theoretically,
an unfavorable variance in this area is the responsibility
of the scheduler or production supervisor. For example,
for the number of customers served, fewer labor hours
should have been required, or, given the number of
hours worked, more customers should have been
served. In a typical manufacturing setting, such an allegation could be made legitimately. The restaurant environment, however, poses a particular problem in this
area because the purpose of production (food preparation) is to fill sales orders, not to produce inventory.
Scheduling is based on expected demand; production
is the result of actual demand. Unfavorable laborefficiency variances are perhaps as likely to be the result of significant forecasting errors and, therefore, bad
scheduling as they are of inefficient operations. Better
forecasting will lead to better scheduling, which should
result in a lower labor-efficiency variance. On the other
hand, a favorable variance is probably the result of an
underestimate of demand, causing the scheduled employees to do more than they should reasonably be
asked to do. Example 5 illustrates the calculation and
analysis of a labor cost variance.
Urlacher Fish Organization (UFO) operates a seafood restaurant where tilapia is a very popular item. UFO has established
the following standards for each tilapia dinner served:
Standard cost
$5.80 per pound
Standard quantity
0.4 lb. per meal
During the past quarter, the restaurant served 7,500 tilapia
dinners. Actual tilapia cost of $18,125 is based on:
2,900 pounds ✕ $6.25 per pound
Thus, a total food cost variance for tilapia served was $725
unfavorable:
Standard 7,500 dinners ✕ 0.4 ✕ $5.80 = $17,400
Actual (above)
$18,125
($725) Unfavorable
Analyzing the above variance into its component elements
shows the following:
Cost/rate variance
AQ (SR – AR) or 2,900 ($5.80 – $6.25) = ($1,305) Unfavorable
Quantity variance
SR (SQ – AQ) or $5.80 (3,000 – 2,900) = $580 Favorable
Total variance
($725)
Labor-Rate Variances
To the degree it can and should be controlled, the
labor-rate variance is the responsibility of the person doing the scheduling. The standards in this area combine
a number of different wage rates taken together to determine the average cost of labor to serve a customer
(e.g., servers, cooks, bussers, bartenders, dishwashers).
An unfavorable variance will result either from assigning higher-paid workers to perform tasks that lower-paid
staff should do or from employing standard wage rates
that do not reflect the current wage scale accurately.
The manager can rectify the former cause by proper
scheduling, whereas the latter should result in revising
standards. The favorable rate variance may result when
the manager schedules lower-paid employees to perform jobs that should command a higher wage rate or
when rate standards are higher than the current employee mix suggests they should be.
M A N A G E M E N T A C C O U N T I N G Q U A R T E R LY
Example 5
Muffet and Mike’s Magnificent Meals (4M) has developed the
following labor standards for its restaurant operations:
Standard labor cost = $30/hour
Standard hours per meal = 15 minutes or 0.25 hours
During a specific time period, 4M served 90,000 meals, and
the actual labor costs were $666,400 for 23,800 hours (i.e.,
$28/hour).
Using a flexible budget figure of $675,000 (i.e., 22,500 hours ✕
$30) results in a favorable labor variance of $8,600:
Flexible budget
$675,000
Actual
$666,400
$ 8,600 Favorable
Analyzing this variance further, 4M finds the following components of the favorable variance:
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Rate variance
AQ (SR – AR)
levels.
For labor cost, the case is somewhat weaker. Labor
cost is described more accurately as a step variable cost.
Up to a point, each additional customer does not require an increase in the labor force, but when volume
increases past a particular point, labor costs also must
increase. Labor hours, too, are related positively to customers served, but this relationship is not strictly linear.
As volume increases, labor hours, like labor costs, increase in a step-like fashion, and only when volume
reaches the next step does one expect the labor force to
increase. A particular size of staff may accommodate a
range of output levels, but at some point the workforce
must increase or decrease to reflect larger or smaller
volumes.
This description suggests that, even with accurate
forecasting, the relative efficiency of labor still depends
on sales volume. With all other variables constant, labor
will be most efficient at volumes just before the step
and least efficient just beyond the step. Because of the
step nature of labor costs, the distortion is less critical
than the forecasting problems noted earlier. Nevertheless, the combination of forecasting difficulties and step
variable labor costs causes the interpretation of labor
variances to be a bit muddled. Therefore, the manager
may need to conduct an in-depth investigation of the
causes of a significant variance before taking corrective
action.
The fourth limitation deals with the aggregation of
food items and labor grades in generating the variance
statistics. Menu items are neither priced identically nor
do they have the same production costs, and, similarly,
all laborers do not earn the same wages per hour nor do
they work with the same degree of efficiency. As a result, out-of-control cost components may be hidden by
offsetting errors. Having a service staff that is too small
and a dish crew that is too large may never become apparent if the manager aggregates labor costs for the two
staffs. By the same token, charging too much for one
menu item and too little for another may result in statistics that appear appropriate but hide menu price flaws.
The final limitation concerns the lack of independence among the variances. Food price variances may
not be independent of food efficiency variables because, for instance, buying a cheaper cut of meat may
23,800 ($30 – $28) = $47,600 Favorable
Efficiency variance SR (SQ – AQ)
$30 (22,500 – 23,800) ($39,000) Unfavorable
$ 8,600
L I M I TAT I O N S
OF
V A R I A N C E A N A LY S I S
The traditional variance analysis model has a number of
limitations for restaurant operations. The first limitation
is the one just discussed. To a large degree, production
depends on actual demand, not capacity. Production capacity sets limits on how much can be produced and, in
a manufacturing setting, provides a standard to evaluate
actual productivity. Restaurants, however, do not produce inventory; they produce meals for immediate sale.
If there is no demand, there is no production, so productivity or efficiency in the restaurant is limited not
only by productive capacity, but also by actual demand.
Therefore, we must view labor efficiency in the traditional sense of efficiency and in relationship to the accuracy of forecasting.
Second, using statistical techniques to develop cost
standards has both advantages and problems. On the
positive side, one can combine large amounts of data in
an efficient, objective manner and revise standards periodically, based on experience and further accumulation
of data, without much additional cost. The main disadvantage of a statistical approach is that a standard setter
must assume no biases arise from using past data to approximate future relationships. It is not always valid to
assume that the environment generating these observations has remained stable from period to period, and we
can extrapolate this environment to determine what the
future relationships between costs and levels of activities should be.
The third limitation involves the actual nature of cost
behavior over changes in volume of activity (i.e., increases and decreases in the number of customers). The
variance model assumes a constant linear relationship
between the cost items and the activity level. For food
cost, this is a reasonable assumption since each additional sale requires a proportional increase in the
amount of food the restaurant uses. Perhaps some inefficiencies result at very low volumes, but the linearity
assumption appears reasonable within steady activity
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generate a favorable price variance only to yield an unfavorable quantity variance resulting from shrinkage or
spoilage. This is also true of labor. Employees earning
lower wages will produce favorable rate variances but
may also cause unfavorable efficiency variances. This
situation is particularly likely when significant turnover
of staff occurs or when the manager asks employees
skilled in one job to perform another. In general, dishwashers may not perform well when they work as lowpaid waiters, and they also do not always make good
low-paid cooks. This potential lack of independence
among variances simply requires an investigation of
variances that goes beyond number crunching and immediate finger-pointing. Variance analysis is only the
first step in the evaluation process.
GROWING UP
R E S TAU R A N T B U S I N E S S
Author Ken Milani knows firsthand about the restaurant business. For nearly 20 years, his parents owned and operated a
pizzeria and sandwich shop attached to a tavern, which his folks
also operated. Ken’s summers, Christmas breaks, and spring
breaks were spent working as a cook in the pizzeria and sandwich shop. While working at the restaurant, he took an interest
in ensuring food did not go to waste. Located in Chicago, Ill., for
more than 14 years before moving the business to a suburb, the
restaurant combined fun and work with the emphasis definitely
on the latter.
possibly even manufacturing management personnel
will go a long way to pose the proper questions as management generates and analyzes standards and variances. After one has become a champion of the cost
variance analysis system and starts to see the usefulness
of the information unfold, the natural next steps will involve plans to make data collection, standard computations, and variance calculations more intuitive and instinctive to the individual operation. ■
A S U C C E S S F U L SYS T E M
Cost variance analyses are useful to restaurateurs to signal which activities are functioning as planned. Although the implementation of a standard cost system in
restaurants poses unique problems that do not exist in a
typical manufacturing or service setting, the system has
strong potential to provide high-quality information that
restaurant managers have historically overlooked.
LEGENDS, however, has successfully adopted these
techniques and will continue to integrate this system of
cost variance analysis into its regular profit-and-loss examinations. If another restaurant plans to do the same,
it should ensure all standards are in place for a reasonable period of time prior to beginning analysis. It is also
important to have the entire management team on
board and educated about the new analysis system. Finally, conversations with other restaurant operators and
M A N A G E M E N T A C C O U N T I N G Q U A R T E R LY
IN THE
Ken Milani, Ph.D., is an accountancy professor at the University of Notre Dame in Notre Dame, Ind., and is a member of the Michiana Chapter of IMA®. You can reach him
at (574) 631-5296 or [email protected].
Aaron Perri is the executive director of Downtown South
Bend (DTSB). At the time the article was submitted, Perri
was general manager of Legends of Notre Dame Restaurant
and Alehouse Pub.
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