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© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-1
7 Cost Estimation
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-2
7 The Strategic Roleof Cost Estimation
Predicting costsof alternative . . . .Predicting costs
of alternative . . . .
Activities, processes, or organizational
forms.
Activities, processes, or organizational
forms.
Implementationstrategies.
Implementationstrategies.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-3
7
strategic positioninganalysis.
value chain analysis.
target costing and life cycle costing.
strategic positioninganalysis.
value chain analysis.
target costing and life cycle costing.
Using Cost Estimation toPredict Future Costs
Strategic management requiresaccurate cost estimates to facilitate:
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-4
7 The Six Steps of Cost Estimation
Define the cost object to be estimated. Determine the cost drivers. Collect consistent and accurate data. Graph the data. Select and employ the estimation method. Assess the accuracy of the cost estimate.
Define the cost object to be estimated. Determine the cost drivers. Collect consistent and accurate data. Graph the data. Select and employ the estimation method. Assess the accuracy of the cost estimate.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-5
7 Cost Estimation Methods
High-lowmethod
High-lowmethod
WorkMeasurement
WorkMeasurement
RegressionAnalysis
RegressionAnalysis
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-6
7
Ben Garcia, the management accountant,is interested in estimating
maintenance cost. Bencollected this data for
seven recent years.
Ben Garcia, the management accountant,is interested in estimating
maintenance cost. Bencollected this data for
seven recent years.
Cost Estimation Methods
Year 1995 1996 1997 1998 1999 2000 2001Total Operating Hours 3,451 3,325 3,383 3,614 3,423 3,410 3,500 Maintenance Costs 22,843 22,510 22,706 23,030 22,413 22,935 23,175
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-7
7
Total Operating Hours
Maintenance Cost
22,000
22,200
22,400
22,600
22,800
23,000
23,200
3325 3383 3410 3423 3451 3501 3614
x
Ben graphed the Ben graphed the data and selected data and selected two points--the two points--the high and low high and low
activities.activities.
Ben graphed the Ben graphed the data and selected data and selected two points--the two points--the high and low high and low
activities.activities.
High-Low Method
The high-low method uses two points to estimate the general cost equation Y = a bH
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-8
7 High-Low Method
The high-low method uses two points to estimate the general cost equation Y = a bH
Y = the value of the estimated maintenance cost
a = a fixed quantity that represents the value of Y when H = zero
b = the slope of the line, the unit variable cost for maintenance.
H = the cost driver, the number of hours of operation for the plant
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-9
7
Ben used these two levels of activity to compute: the variable cost per unit; the fixed cost; and then express the costs in equation form Y = a + bH.
Hours Cost
High activity level 3,614 23,030$ Low activity level 3,325 22,510 Change 289 520$
High-Low Method
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-10
7
Unit variable cost = $520 ÷ 289 hours = $1.80 per hour
Hours Cost
High activity level 3,614 23,030$ Low activity level 3,325 22,510 Change 289 520$
High-Low Method
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-11
7
Hours Cost
High activity level 3,614 23,030$ Low activity level 3,325 22,510 Change 289 520$
Unit variable cost = $520 ÷ 289 hours = $1.80 per hour Fixed cost = Total cost – Total variable cost Fixed cost = $23,030 – ($1.80 per hour × 3,614 hours)
Fixed cost = $23,030 – $6,505 = $16,525
High-Low Method
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-12
7
Unit variable cost = $520 ÷ 289 hours = $1.80 per hour Fixed cost = Total cost – Total variable cost
Fixed cost = $23,030 – ($1.80 per hour × 3,614 hours)
Fixed cost = $23,030 – $6,505 = $16,525 Total cost = Fixed cost + Variable cost (Y = a + bH) Y = $16,525 + $1.80H
High-Low Method
Hours Cost
High activity level 3,614 23,030$ Low activity level 3,325 22,510 Change 289 520$
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-13
7
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the variable portion of sales
commission per unit sold?
a. $.08 per unit
b. $.10 per unit
c. $.12 per unit
d. $.125 per unit
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the variable portion of sales
commission per unit sold?
a. $.08 per unit
b. $.10 per unit
c. $.12 per unit
d. $.125 per unit
High-Low Method Question 1
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-14
7
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the variable portion of sales
commission per unit sold?
a. $.08 per unit
b. $.10 per unit
c. $.12 per unit
d. $.125 per unit
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the variable portion of sales
commission per unit sold?
a. $.08 per unit
b. $.10 per unit
c. $.12 per unit
d. $.125 per unit $4,000 ÷ 40,000 units = $.10 per unit
Units Cost
High level 120,000 14,000$Low level 80,000 10,000 Change 40,000 4,000$
High-Low Method Question 1
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-15
7
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the fixed portion of the sales
commission?
a. $ 2,000
b. $ 4,000
c. $10,000
d. $12,000
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the fixed portion of the sales
commission?
a. $ 2,000
b. $ 4,000
c. $10,000
d. $12,000
High-Low Method Question 2
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-16
7
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the fixed portion of the sales
commission?
a. $ 2,000
b. $ 4,000
c. $10,000
d. $12,000
If sales commissions are $10,000 when 80,000 units are sold and $14,000 when 120,000 units are sold, what is the fixed portion of the sales
commission?
a. $ 2,000
b. $ 4,000
c. $10,000
d. $12,000
Total cost = Total fixed cost + Total variable cost
$14,000 = Total fixed cost +($.10 × 120,000 units)
Total fixed cost = $14,000 - $12,000
Total fixed cost = $2,000
High-Low Method Question 2
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-17
7
A cost estimation A cost estimation method that makes a method that makes a detailed study of an detailed study of an
activity to measure the activity to measure the time required per unit time required per unit
of output. of output.
A cost estimation A cost estimation method that makes a method that makes a detailed study of an detailed study of an
activity to measure the activity to measure the time required per unit time required per unit
of output. of output.
Work Measurement
ExampleExample
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-18
7
Kupper Insurance Company analyzes the time it takes to process a claim. The mean processing time
is 18 minutes, while 95% of the claims require between 10 and 25 minutes.
Work Measurement
This information enables Kupper toestimate cost more effectively.evaluate the processing clerks
more effectively and fairly.
This information enables Kupper toestimate cost more effectively.evaluate the processing clerks
more effectively and fairly.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-19
7
Regression analysis is a statistical method for
obtaining the cost estimation unique
equation that best fits a set of data points.
Regression analysis is a statistical method for
obtaining the cost estimation unique
equation that best fits a set of data points.
Regression Analysis
Lease squares regression is Lease squares regression is widely viewed as one of the widely viewed as one of the most effective methods for most effective methods for
estimating costs.estimating costs.
Lease squares regression is Lease squares regression is widely viewed as one of the widely viewed as one of the most effective methods for most effective methods for
estimating costs.estimating costs.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-20
7
Statistics courses and computer courses deal
with detailed regression
computations using computer spreadsheet
software.
Statistics courses and computer courses deal
with detailed regression
computations using computer spreadsheet
software.Accountants and managers
must be able to interpret and use regression
estimates.
Accountants and managers must be able to interpret
and use regression estimates.
Regression Analysis
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-21
7
The objective of the regression method is still a linear equation to estimate costs Y = a + bX + e
Y = value of the dependent variable, estimated cost
a = a fixed quantity, the intercept, that represents the value of Y when X = 0
b = the unit variable cost, the coefficient of the independent variable measuring the increase in Y for each unit increase in X
X = value of the independent variable, the cost driver
Regression Analysis
e = the regression error, the distance from the regression line to the data point
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-22
7
Month Supplies Expense (Y) Production Level (X)
1 $250 50 units
2 310 100 units
3 325 150 units
4 ? 125 units
Month Supplies Expense (Y) Production Level (X)
1 $250 50 units
2 310 100 units
3 325 150 units
4 ? 125 units
Regression Analysis
Regression analysis willenable us to predict the amount of supplies
expense for month four.
Regression analysis willenable us to predict the amount of supplies
expense for month four.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-23
7S
up
plie
s E
xpen
se
400
350
300
250
200
50 100 150
Regression Analysis
Regression for the data isdetermined by a statistical procedure
that finds the unique line throughthe data points that minimizes
the sum of squared error distances.
Units of Output
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-24
7 Regression Analysis
Month Supplies Expense (Y) Production Level (X)
1 $250 50 units
2 310 100 units
3 325 150 units
4 ? 125 units
Month Supplies Expense (Y) Production Level (X)
1 $250 50 units
2 310 100 units
3 325 150 units
4 ? 125 units
Y = a + bX + e
Y = $220 + $.75 per unit 125 units
Y = $313.75 Expense estimate for month 4
Y = a + bX + e
Y = $220 + $.75 per unit 125 units
Y = $313.75 Expense estimate for month 4
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-25
7S
up
plie
s E
xpen
se
Units of Output
50 100 150
400
350
300
250
200
e = 7.5
e = 15 e = 7.5
220Fixed Cost = $220Fixed Cost = $220
Regression Analysis
b = the slope of the regression line or the coefficient of the independent variableb = $.75 per unit
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-26
7
50 100 150 200
400
350
300
250
200
Outlier
proper line, excluding the outlierimproper line, influenced by outlier
Regression AnalysisS
up
plie
s E
xpen
se
Units of Output
Outliers may be discarded toobtain a regression that is more
representative of the data.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-27
7 Regression Analysis
Evaluating a Regression Analysis
R2, the coefficient of determination, is a measure of the explanatory power
of the regression, the degree thatchanges in the dependent
variable can be predicted by changesin the independent variable.
R2, the coefficient of determination, is a measure of the explanatory power
of the regression, the degree thatchanges in the dependent
variable can be predicted by changesin the independent variable.
The t-value is a measureof the reliability of each ofthe independent variables.
The t-value is a measureof the reliability of each ofthe independent variables.
The standard error of the estimate (SE) is a measureof the accuracy of the regression’s estimates.
The standard error of the estimate (SE) is a measureof the accuracy of the regression’s estimates.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-28
7
50 100 150 200
400
350
300
250
200
Regression withhigh R2 (close to 1.0)
Regression AnalysisD
epen
den
t V
aria
ble
Independent Variable
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-29
7 Regression Analysis
50 100 150 200
400
350
300
250
200
Regression withlow R2 (close to 0)
Dep
end
ent
Var
iab
le
Independent Variable
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-30
7
standard error
Regression Analysis
50 100 150 200
400
350
300
250
200
Dep
end
ent
Var
iab
le
Independent Variable
Standard error is a range around the regression estimate in which we can be reasonably sure that the
unknown value will fall.
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-31
7
standard error
Regression with Wide(Poor) Standard Error
Slide 7-34
Regression Analysis
50 100 150 200
400
350
300
250
200
Dep
end
ent
Var
iab
le
Independent Variable
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-32
7
standard error
Regression Analysis
50 100 150 200
400
350
300
250
200
Dep
end
ent
Var
iab
le
Independent Variable
Regression with Narrow(Good) Standard Error
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-33
7
Data and Implementation ProblemsData and Implementation Problems Data AccuracyData Accuracy Selecting the time periodSelecting the time period
Mismatched time periodMismatched time periodLength of the time periodLength of the time period
Nonlinearity problemsNonlinearity problemsTrend and/or seasonalityTrend and/or seasonalityOutliersOutliersData shiftData shift
Data and Implementation ProblemsData and Implementation Problems Data AccuracyData Accuracy Selecting the time periodSelecting the time period
Mismatched time periodMismatched time periodLength of the time periodLength of the time period
Nonlinearity problemsNonlinearity problemsTrend and/or seasonalityTrend and/or seasonalityOutliersOutliersData shiftData shift
Regression Analysis
© The McGraw-Hill Companies, Inc., 2002McGraw-Hill/Irwin
Slide 7-34
7 The End
This is a toughcost to estimate!
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