Cost Prediction 1

8/7/2019 Cost Prediction 1

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Cost estimation - Cost behavior

What we really want to understand is howspending will vary in a variety of decision

settings.

Cause-effect relations and costs drivers.


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Capacity and capacity costs:

Theoretical = 100,000

Practical = 90,000

Normal = 85,000

Budgeted = 80,000

Suppose fixed overhead is budgeted at$1,000,000; variable overhead is $1 per unit;

direct material costs = $3; and direct labor =

$3. Overhead is applied based on units of

roduct.


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Capacity and capacity costs:

What does a unit of product cost if overhead

is allocated based on theoretical capacity?

Practical capacity?

Normal capacity?

Budgeted capacity.

Which measure should the company use?

$17

$18.11

$18.76

$19.50


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Capacity and capacity costs:Suppose the company allocates overhead

based on practical capacity and actual

production is 70,000 units.

By how much is overhead underapplied?

What does that cost represent?About $222,300

The cost of idle

or excess capacity.


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Capacity and capacity costs

Who should pay for excess capacity?

Who should pay for idle capacity?

How is capacity measured?What is the scarcest resource?

Idle capacity and opportunity costs.


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Cost estimation: overhead When is it important to understand how overhead

behaves?

When pricing, production, process and product

design decisions are made.

When bids and make or buy decisions are made.

When we need to answer what if questions.


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Cost estimation: overhead costs

First weeks product costing exercises:

applied overhead.

Valuing inventories & costs of sales.

Not for costing individual products

Not for predicting costs


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What methods are available?

Engineering estimates

Account analysis

Scattergraph and high-low estimates

Statistical methods (typically regression)


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Cost behavior: linear function by

assumption.TC = FC + VC*(level of cost driver)

where

TC = total cost

FC = fixed cost

VC = variable cost per unit of the cost

driver,

and sometimes the cost driver is

represented by X.


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Volume

Overhead Costs

AB

C D


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Cost estimation: Account

analysis

Review each account

Identify it as fixed or variable (or mixed)

Attempt to determine the relationship

between the activity of interest and the cost

Cost of building occupancy

Cost of quality inspections

Cost of materials handling


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Example

Suppose management believes that the monthly

overhead cost ($5000) in the factory is mixed. It is

believed to be 50% fixed and 50% variable. Thevariable portion is believe to depend on machine

hours, which average 10,000 per month. How

would you show this as a linear equation?

TC = $2500 + $.25(machine hours)

Peterson Mfg. in Problem Set #1 will require account analysis.


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Scattergraph

Suppose you have data on overhead costs and

machine hours for the past 15 months. Can

you easily determine whether the posited

relationship exists?

Yes, plot the data and look for a relationship.


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Plot of overhead costs vs.

machine hours

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

4000.00

0.00 30.00 60.00 90.00 120.00 150.00

Machine Hours

Scattergram


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High-Low cost estimation

Find the variable cost per unit of the cost

driver (VC):

activityLowest-activityHighest

activitylowestatOverhead-activityhighestatOverheadVC!


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High-Low method: Example

continued

mhr50-mhr142

$1,896-$3,105VC !

mhr92

$1,209VC !

$13.14/mhrVC !


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High-Low cost estimation

$1,

mhr)142*($13.14-$3,105costFixed

!

!

$2,7T

r)*($13.14$1,239T

r115*FT

!

!

!

Estimate the total overhead cost during a

months when 115 machine hours will be used:


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Cost estimation using regression

Y = the dependent variable (total O/H cost)

X = the explanatory variables

Y = EFX +I

where X = machine hours and I = random error.

T

C =F

C + VC*X + I


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Regression fits a line through

these data points:

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

4000.00

0.00 30.00 60.00 90.00 120.00 150.00

Machine Hours

Scattergram


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S

imple linear regression

One explanatory variable

Cost estimation equation

Coefficient of correlation (R)

Coefficient of determination (R2)

Goodness of fitMeasure of importance

F-statistic (hypothesis testing)

p-value


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Coefficient of correlation

Measures the correlation between the independent

and the dependent variables.


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Coefficient of determination

Measures the percentage of variation in the

dependent variable explained by the independentvariable.

When the predicted values exactly equal the

actual costs, R2 = 1.

A goodness of fit test: R2 > .3


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T

he F statistic

Goodness of fit hypothesis testing

Compute a statistic for regression results

Compute the associated p-value, or

Look up a critical F-value and compare

1 numerator degree of freedom (n-2) denominator degrees of freedom

alpha = .05


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T

he F test:

The hypothesis is: The slope coefficient is

zero.

The F-statistic measures the loss of fit that

results when we impose the restriction that

the slope coefficient is zero.

IfF is large, the hypothesis is rejected.


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Regression result interpretation

15

0

.896

.802

.787

182.244

Count

Num. Missing

R

R Squared

Adjusted R Squared

RMS Residual

Regression Summary

Overhead Costs vs. Machine Hours

1 1753772.049 1753772.049 52.804


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Simple linear regression

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

4000.00

0.00 30.00 60.00 90.00 120.00 150.00

Machine HoursOverhead Costs = 1334.293 + 12.373 * Machine Hours; R^2 = .802

Scattergram


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R

esults using DM$15

0

.960

.921

.915

115.087

Count

Num. Miss ing

R

R Squared

Adjust ed R Squared

RMS Residual

Regression Su ary

Overhead osts vs. Direct Materials ost

1 2013351.144 2013351.144 152.007


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Multiple regression15

0

.976

.952

.944

93.658

Count

Num. Miss ing

R

RS ua e

juste RS ua e

RMS Resi ual

Regress n Summ ry

OverheadC s s vs. 2 Independen s

2 2080274.802 1040137.401 118.576


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Forecasting overhead Predict monthly overhead when machine

hours are expected to be 62 and direct

materials costs are expected to be $1,900.

Recall

E = $1,333.96

Coefficient for mhrs = $4.359

Coefficient for DM$ = $.258


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Predicted overhead

$2,094.42

00)$.258($1,9$4.359(62)$1,333.96Overhead

!

!


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Putting together a bid

Calculate a minimum bid for a contract that

would use 22 machine hours and $900 in

direct materials. This would be a one-time-

only job.

What if there is no idle capacity?

Would your bid change if there were

potential for repeated business?


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Problems with regression

Nonlinear relationships

Outliers Spurious relationships

Data problems

I

naccurate accounting cut-offsArbitrarily allocated costs

Missing data

Inflation


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Thursday

Cenex and Burd & Fletcher Cases.

U

seE

xcel for regression computations We will discuss the problems in class and

Work a handout problem in groups.

Documents

Cost Prediction 1