ch03 guan cm aise ppt

8/11/2019 Ch03 Guan Cm Aise Ppt

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COST MANAGEMENT

Guan Hansen Mowen

COPYRIGHT 2009 South-Western Publishing, a division of Cengage Learning.Cengage Learning and South-Western are trademarks used herein under license. 1

Chapter 3Cost Behavior


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Study Objectives

1. Define and describe fixed, variable, and mixed costs.

2. Explain the use of resources and activities and their relationship to

cost behavior.

3. Separate mixed costs into their fixed and variable components

using the high-low method, the scatterplot method, and the methodof least squares.

4. Evaluate the reliability of the cost formula.

5. Explain how multiple regression can be used to assess cost

behavior.6. Define the learning curve, and discuss its impact on cost behavior.

7. Discuss the use of managerial judgment in determining cost

behavior.


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Two production lines can process 10,000computers per year each. The workers on eachline are supervised by a production-line manager

who is paid $24,000 per year. For production upto 10,000 units, only one supervisor is needed.

When production is between 10,001 and 20,000units, two supervisors are required.

Cost Behavior: Fixed Costs

Fixed costsarecosts that in to tal areconstant within the relevant range asthe level of the activity driver varies.


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Supervision

Computers

Processed

$54,000 4,00054,000 8,000

54,000 10,000

108,000 12,000

108,000 16,000108,000 20,000

Days Computers, Inc.



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Supervision

Computers

Processed

$54,000 4,00054,000 8,000

54,000 10,000

108,000 12,000

108,000 16,000108,000 20,000




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Supervision

Computers

Processed Unit Cost

$54,000 4,000 $13.5054,000 8,000 6.75

54,000 10,000 5.40

108,000 12,000 9.00

108,000 16,000 6.75108,000 20,000 5.40




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Variable costs are costs that in to talvary in direct proportion to changes inan activity driver.

A CD-ROM disk drive is added to eachcomputer at a cost of $30 per computer.

The total cost of disk drives for each level of

production varies.

Cost Behavior: Variable Costs


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Total Cost of

CD-ROMs

Number of

Computers

Processed

$120,000 4,000

240,000 8,000

360,000 12,000

480,000 16,000

600,000 20,000



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Total Cost of

CD-ROMs

Number of

Computers

Processed

Unit Cost of

CD-ROMs

$120,000 4,000 $30.00

240,000 8,000 30.00

360,000 12,000 30.00

480,000 16,000 30.00

600,000 20,000 30.00



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Mixed costs are costs that have both afixed and a variable component.

Ten sales representatives each earn anannual salary of $30,000plusa commissionof $50 per computer sold. 10,000 computers

are sold.

Cost Behavior: Mixed Costs


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Y= Fixed cost + Total variable cost

Y= F+ VX

where

Y= Total cost

For Days Computer, the selling cost is:

Y = $300,000 + $50X



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Fixed Cost of

Selling

Variable

Cost of

Selling Total Cost

Computers

Sold

Selling Cost

per Unit

$300,000 $200,000 $500,000 4,000 $125.00

300,000 400,000 700,000 8,000 87.50

300,000 600,000 900,000 12,000 75.00

300,000 800,000 1,100,000 16,000 68.75

300,000 1,000,000 1,300,000 20,000 65.00



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Flexible resources

Acquired as used and needed

Usually considered variable costs

Examples: materials, energy

Committed resources

Acquired in advance of usage

Usually considered fixed costs

Examples: buying or leasing buildings, contractswith employees

Resources, Activities,and Cost Behavior


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Step cost behaviordisplays a constantlevel of cost for a range of output and then

jumps to a higher level of cost at some

point Step-Variable costs

Narrow increments Approximate as a strictly variable assumption

Step-Fixed costs Wide increments Assigned to the fixed cost category


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Methods for Separating Mixed Costsinto Fixed and Variable Components

The High-Low Method

The Scatterplot Method The Method of Least Squares

Variable

Component

FixedComponent


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Y = F + VX

Methods for Separating Mixed Costsinto Fixed and Variable Components

whereY = Total activity cost

F = Fixed cost componentV = Variable cost per unit

X = Measure of activity output

Straight-line equation:


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Step 1: Solve for variable cost (V)V= Change in cost Change in activity

High-Low Method

Month

Materials

Handling Cost

Number of

Moves

January $2,000 100

February 3,090 125

March 2,780 175

April 1,990 200May 7,500 500

June 5,300 300

July 4,300 250

August 6,300 400

September 5,600 475October 6,240 425


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High-Low Method

$7,500 - $2,000Step1: $13.75

500 - 100V

Low Activity

High Activity

Month

Materials

Handling Cost

Number of

Moves

January $2,000 100

February 3,090 125

March 2,780 175

April 1,990 200May 7,500 500

June 5,300 300

July 4,300 250

August 6,300 400

Septembe 5,600 475

October 6,240 425


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High-Low Method

$7,500 - $2,000$13.75

500 - 100V

Step 2: Using either the high cost or low cost, solve forthe total fixed costs F

Step 1: Solve for variable cost (V)V= Change in cost Change in activity

( )

$2,000 $13.75(100)$625

Y F V X

FF

Low cost

( )$7,500 $13.75(500)

$625

Y F V X

F

F

High cost


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Scatterplot Method

Step 1: Plot the data points on a scattergraph


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Method of Least Squares

ActualCost

PredictedCost Deviation

DeviationSquared

2,000 1,742 258 66,564

3,090 2,088 1,002 1,004,004

2,780 2,780 - -1,990 3,126 (1,136) 1,290,496

7,500 7,278 222 49,284

5,300 4,510 790 624,100

4,300 3,818 482 232,3246,300 5,894 406 164,836

5,600 6,932 (1,332) 1,774,224

6,240 6,240 - -

5,205,832Total measure of closeness


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Regression Programs

The best-fitting lineis the line with thesmallest sum of squared deviations

Regression analysis determines the linearfunction with the minimum sum of squareddeviations

Utilize spreadsheet packages such as

Microsoft Excel to perform thecomputation


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Spreadsheet Data forAnderson Company

Regression Analysisfor the Method of Least Squares


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SUMMARY OUTPUT

Regression Statistics

Multiple R 0.92894908

R. Square 0.862946394

Adjusted R 0.845814693

SquareStandard Error 770.4987038

Observations 10

ANOVA

df SS MS F

Regression 1 29903853.98 29903853.98 50.37132077Residual 8 4749346.021 593668.2526

Total 9 34653200

Coefficient Standard Error t-Stat P-value

Intercept 854.4993582 569.7810263 1.49967811 0.172079925

X Variable 1 12.3915276 1.745955536 7.097275588 0.000102268

Regression Output forAnderson Company



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The regression analysis gives rise to the following

equation for Andersons material handling cost:


$854.50 + ($12.39 number of moves)


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Reliability of Cost Formulas

Hypothesis test of parameters

The lower the P-value, the more likely that thetrue parameter is significantly different from 0

Traditional benchmarks of significance are

0.10, 0.05 or 0.01


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Goodness of fit

R2 is the coefficient of determination

Measures the percentage of change in thedependent variable explained by changes in

the independent variable

The closer to 1.0, the better; no benchmark


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Confidence intervals

The standard error is used to determine the range of possible values around the

predicted value:

Standard Confidencet-statisticError Interval


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X1= first explanatory variable

X2= second explanatory variable

Multiple Regression

Least-squares method is used to fit anequation involving two or moreexplanatory variables

Y = F + V1X

1+ V

2X

2etc.

where


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Multiple Regression

Spreadsheet Data forAnderson Company

Month

Materials

Handling

Cost

Number

of Moves

Pounds

MovedJanuary $2,000 100 6,000

February 3,090 125 15,000

March 2,780 175 7,800

April 1,990 200 600

May 7,500 500 29,000

June 5,300 300 23,000July 4,300 250 17,000

August 6,300 400 25,000

Septembe 5,600 475 12,000

October 6,240 425 22,400

X2

X1


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Multiple Regression Analysisfor the Method of Least Squares

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.999420

R Square 0.998841

Adjusted R Square 0.998509

Standard Error 75.762721

Observations 10

ANOVA

df SS MS F

Regression 2 34613020.07 17306510.04 3015.076722

Residual 7 40179.92954 5739.989934

Total 9 34653200

Coefficients Standard Error t Stat P-value

Intercept 507.309711 57.322496 8.850098 0.000048

X Variable 1 7.835162 0.234048 33.476720 0.000000

X Variable 2 0.107181 0.003742 28.642864 0.000000


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Y= $507 + $7.84X1 + $0.11X

2

Y= $507 + $7.84(350) + $0.11(17,000)= $507 + $2,744 + $1,870

= $5,121

Multiple Regression

Based on the multiple regression analysis, thecost formula is written as:

In November the company expects to make 350moves with a weight of 17,000 pounds. Thepredicted cost of material handling is:


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1 100 100 100

2 80 (80% 100) 160 60

3 70.21 210.63 50.63

4 64 (80% 80) 256 45.37

5 59.57 297.85 41.85

6 56.17 337.02 39.17

7 53.45 374.15 37.13

8 51.20 (80% 64) 409.60 35.45

16 40.96 655.36 28.06

32 32.77 1,048.64

Cumulative Cumulative Cumulative Individual Units

Number Average Time Total Time: Time for nth

of Units per Unit in Hours Labor Hours Unit-Labor Hours

(1) (2) (3) = (1) (2) (4)

Cumulative Average Time LearningCurve with 80% Learning Rate


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Graph of Cumulative Total Hours Requiredand the Cumulative Average Time per Unit


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Managerial Judgment

Managerial judgment is critically important

in determining cost behavior and is by far

the most widely used method in practice Advantage simplicity

Disadvantage poor judgment leads to errors


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COST MANAGEMENT

Guan Hansen Mowen

End Chapter 3

ch03 guan cm aise ppt

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