cost estimation
DESCRIPTION
11. Cost Estimation. Cost prediction. Cost estimation. Introduction. Cost behavior. Existing relationship between cost and activity. Process of estimating relationship between costs and cost driver activities that cause those costs. - PowerPoint PPT PresentationTRANSCRIPT
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Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved.McGraw-Hill/Irwin
11Cost Estimation
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Costprediction
Using results ofcost estimation
to forecast alevel of cost at
a particularactivity. Focusis on the future.
Existingrelationship
betweencost andactivity.
Process ofestimating relationship
between costsand cost driveractivities that
cause those costs.
Costestimation
Costbehavior
Introduction
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Learning Objective 1
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Management needsto know the costs that
are likely to beincurred for each
alternative.
How muchwill costs increaseif sales increase
10 percent?
What will mycosts be if I introducethe new model in a
foreign market?
Reasons for Estimating Costs
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Increasedcompany
value
More accurate cost estimates
Better informed decisions about:• efficient business processes• alternative courses of action• performance standards• financial forecasts
Reasons for Estimating Costs
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Relationship between activities and costs
Relationship between activities and costs
ActivitiesActivities
CostsCosts
3. To reduce these
1. First identify this
We estimate costs to:
manage costsmake decisions
plan and set standards.
We estimate costs to:
manage costsmake decisions
plan and set standards.
2. Then manage these
Exh.11-1
Reasons for Estimating Costs
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Summary of variable and fixed cost behavior
Cost In total Per unit
Variable Total variable cost changes Variable cost per unit remainsas activity level changes. the same over wide ranges
of activity.
Fixed Total fixed cost remains the Fixed cost per unit goessame even when the activity down as activity level goes up.
level changes.
Total Costs = Fixed costs + Variable costsTC = F + VXV is the variable cost per cost driver unit (cost driver rate).X is the number of cost driver units.
Basic Cost Behavior Patterns
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Learning Objective 2
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Intercept = Fixed Cost
Intercept = Fixed Cost
Slope = Cost Driver Rate
Slope = Cost Driver Rate
$.16
One Cost Driver and Fixed/Variable Cost Behavior
Exh.11-2
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Multiple Cost Drivers and Complex Cost Behavior
In cases of complex cost behavior and
multiple cost drivers, the cost-benefit test
should be considered when developing a
cost estimation model.
In cases of complex cost behavior and
multiple cost drivers, the cost-benefit test
should be considered when developing a
cost estimation model.
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Step Cost•A cost that increases in steps as the amount of the cost driver volume increases.
•Also called a “semifixed cost”
Step Cost•A cost that increases in steps as the amount of the cost driver volume increases.
•Also called a “semifixed cost”
Total cost remains unchanged over a narrow
range of activity. As activity increases to the
next range, total cost steps up to the next level.
Total cost remains unchanged over a narrow
range of activity. As activity increases to the
next range, total cost steps up to the next level.
Co
st
Activity
Step Costs
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Example: Office space is available at a rental rate of $30,000 per year in increments of 1,000 square feet. As the business grows more space is rented, increasing the total cost.
Example: Office space is available at a rental rate of $30,000 per year in increments of 1,000 square feet. As the business grows more space is rented, increasing the total cost.
Continue
Step Costs
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Rent Cost
0 1,000 2,000 3,000 Rented Area (Square Feet)
$30,000
$60,000
$90,000
Total cost remains unchanged for a range of activity, then jumps to a
higher cost for the next range of activity.
Step Costs
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The activity limits within which acost projection may be valid is the relevant range of activity.
Unit variable costsremain unchanged.
Total fixed costsremain unchanged.
Relevant Range of Activity
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Mixed Costs
A mixed cost is one that has both a
fixed and a variable component.
For example, a cellular phone plan that charges $40 for
the first 600 minutes and $0.10
per minute thereafter.
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CurvilinearCost Function
Relevant Range
Activity
To
tal
Co
st
A nonlinear cost pattern (e.g. changes in unit variable cost)
may often approximate a straight line (when
the unit variable cost is constant) within the
relevant range.
Nonlinear Costs
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Engineering method
Account analysis
Scattergraph and high-low estimates
Statistical methods (regression analysis)
Methods of Estimating Costs
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Simply plotting past cost behavior on a graph may be a helpful first step in analyzing costs
regardless of the estimation method ultimately chosen.
It can reveal outlier data points and suggest possible relationships between the variables.
The Scattergraph
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****
**
**
*
*
0 1 2 3 4
$10,000
$20,000
0
Plot the data points on a graph (total cost vs. activity).
Activity: Units produced (‘000)
Total cost
The ScattergraphThe Scattergraph
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Draw a line through the plotted data points so that about an equal amount of points falls above and below the line.
0 1 2 3 40
****
**
**
*
*
Activity: Units produced (‘000)
Total Cost
The Scattergraph
Estimated fixed cost = $10,000
The Scattergraph
$20,000
$10,000
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0 1 2 3 40
****
**
**
*
*
The slope of this line is the unit variable cost. (Slope is the change in total cost for a one-unit change in activity).
Activity: Units produced (‘000)
Total Cost
The Scattergraph
Vertical distance
is the change in cost.
Horizontal distance is the change in activity.
The Scattergraph
$20,000
$10,000
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The high-low method uses two data points to estimate the general cost equation TC = F VX
TC = the estimated total cost
F = a fixed quantity that represents the value of Y when X = zero
V = the slope of the line(equivalent to the unit variable cost)
X = units of the cost driver activity
The High-Low Method
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0 1 2 3 4
$10,000
$20,000
0
****
**
**
*
*
The high-low method uses two data points to estimate the general
cost equation TC = F + VX
The two points should be representative ofthe cost and activity relationship over the range
of activity for which the estimation is made.
Activity: Units produced (‘000)
Total Cost
The High-Low Method
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WiseCo recorded the following production activity and maintenance costs for two months:
Using these two levels of activity, compute: the variable cost per unit; the fixed cost; and then express the costs in equation form TC = F + VX.
Units Cost
High activity level 9,000 9,700$Low activity level 5,000 6,100 Change 4,000 3,600$
The High-Low Method
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Unit variable cost = $3,600 ÷ 4,000 units = $.90 per unit Fixed cost = Total cost – Total variable cost
Fixed cost = $9,700 – ($.90 per unit × 9,000 units)
Fixed cost = $9,700 – $8,100 = $1,600 Total cost = Fixed cost + Variable cost (TC = F + VX) TC = $1,600 + $0.90X
Units Cost
High activity level 9,000 9,700$Low activity level 5,000 6,100 Change 4,000 3,600$
The High-Low MethodThe High-Low Method
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Learning Objective 3
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Regression Analysis
A statistical method used to create an equation relating dependent (or Y) variables
to independent (or X) variables.
Data from the past are used to estimate relationships between costs and activities.
A statistical method used to create an equation relating dependent (or Y) variables
to independent (or X) variables.
Data from the past are used to estimate relationships between costs and activities.
Independent variables are the cost drivers that
drive the variation in dependent variables.
Independent variables are the cost drivers that
drive the variation in dependent variables.
Before doing the analysis, take time to determine if a logical
relationship between the variables exists.
Before doing the analysis, take time to determine if a logical
relationship between the variables exists.
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The objective of the regression method is still a linear equation to estimate costs TC = F + VX
TC = value of the dependent variable(estimated total cost)
F = a fixed quantity, the intercept, that represents the value of TC when X = 0
V = the unit variable cost, the coefficient of the independent variable measuring the increase in TC for each unit increase in X
X = value of the independent variable, the cost driver
Regression AnalysisRegression Analysis
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A statistical procedure that finds the unique line through data points that minimizes the sum of
squared distances from the data points to the line.
50 100 150 200
400
350
300
250
200
De
pen
de
nt
Va
ria
ble
Independent Variable
Regression AnalysisRegression Analysis
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50 100 150 200
400
350
300
250
200
De
pen
de
nt
Va
ria
ble
Independent Variable
V = the slope of the regression line or the coefficient of the independent variable. Here it represents the increase in TC for each unit increase in X.
F = a fixed quantity, the intercept
Regression AnalysisRegression Analysis
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Outlier
proper line, excluding the outlierimproper line, influenced by outlier
Outliers may be discarded toobtain a regression that is more
representative of the data. 50 100 150 200
400
350
300
250
200
De
pen
de
nt
Va
ria
ble
Independent Variable
Regression AnalysisRegression Analysis
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The correlation coefficient (r) is a measure of the linear relationship between variables such as cost and activity.
0 1 2 3 4
Total Cost
$10,000
$20,000
0
***
**
****
Activity: Units produced (‘000)
*
The correlation coefficient is highly positive (close to 1.0) if the data points
are close to the regression line.
Regression Analysis
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0 1 2 3 4
Total Cost
$10,000
$20,000
0
Activity: Units produced (‘000)
*
*
*
*
*
*
**
* *
The correlation coefficient is near zero if little or no relationshipexists between the variables.
The correlation coefficient (r) is a measure of the linear relationship between variables such as cost and activity.
Regression Analysis
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0 1 2 3 4
Total Cost
$10,000
$20,000
0
Activity: Units produced (‘000)
*
*
*
** *
***
*This relationship has a negative
correlation coefficient, approachinga maximum value of –1.0
The correlation coefficient (r) is a measure of the linear relationship between variables such as cost and activity.
Regression Analysis
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50 100 150 200
400
350
300
250
200
Regression withhigh R2 (close to 1.0)
De
pen
de
nt
Va
ria
ble
Independent Variable
R2, the coefficient of determination, is a measureof the goodness of fit. R2 tells us the amount
of the variation of the dependent variable thatis explained by the independent variable.
Regression AnalysisRegression Analysis
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Regression withlow R2 (close to 0)
50 100 150 200
400
350
300
250
200
De
pen
de
nt
Va
ria
ble
Independent Variable
The coefficient ofdetermination, R2,is the correlation
coefficient squared.
Regression AnalysisRegression Analysis
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Includes all data points, resulting in more thorough study of the relationship between the variables.
Generates statistical information that describes the relationship between variables.
Permits the use of more than one cost driver activity to explain cost behavior.
Includes all data points, resulting in more thorough study of the relationship between the variables.
Generates statistical information that describes the relationship between variables.
Permits the use of more than one cost driver activity to explain cost behavior.
Regression Analysis
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Statistics courses deal with detailed regression computations using computer spreadsheet software.
Accountants and managers must be able to interpret and use regression estimates.
Let’s look at an example using Excel.
Statistics courses deal with detailed regression computations using computer spreadsheet software.
Accountants and managers must be able to interpret and use regression estimates.
Let’s look at an example using Excel.
Regression Analysis
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Simple Regression Example
Eagle Enterprises wants to analyze the relationship between units
produced and total costs.
Using the data to the right, let’s see
how to do a regression using
Excel.
Eagle Enterprises wants to analyze the relationship between units
produced and total costs.
Using the data to the right, let’s see
how to do a regression using
Excel.
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Simple Regression Using Excel
We will obtain three piecesof information from ourregression analysis:
1. Estimated Variable Cost per Unit (line slope)
2. Estimated Fixed Costs (line intercept)
3. Goodness of fit, or R2
We will obtain three piecesof information from ourregression analysis:
1. Estimated Variable Cost per Unit (line slope)
2. Estimated Fixed Costs (line intercept)
3. Goodness of fit, or R2
To get these three pieces of
information we will need to
find the following Excel
functions: LINEST,
INTERCEPT and RSQ.
To get these three pieces of
information we will need to
find the following Excel
functions: LINEST,
INTERCEPT and RSQ.
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After opening Excel and
entering your data, click on “Insert” and “Function”
After opening Excel and
entering your data, click on “Insert” and “Function”
Simple Regression Using Excel
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When the function box opens, click
on “Statistical”,
then on “LINEST”
When the function box opens, click
on “Statistical”,
then on “LINEST”
Simple Regression Using Excel
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1. Enter the cell range for the cost amounts in the “Known_y’s” box.
2. Enter the cell range for the quantity amounts in the “Known_x’s” box.
1. Enter the cell range for the cost amounts in the “Known_y’s” box.
2. Enter the cell range for the quantity amounts in the “Known_x’s” box.
By clicking on the buttons to the left, you can highlight the desired cells
directly from the spreadsheet.
By clicking on the buttons to the left, you can highlight the desired cells
directly from the spreadsheet.
Simple Regression Using Excel
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The Slope, or estimated variable cost per unit, is identified here. Click OK to put this value on your
spreadsheet.
The Slope, or estimated variable cost per unit, is identified here. Click OK to put this value on your
spreadsheet.
Simple Regression Using Excel
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Repeat the procedure
using “Intercept”, to estimate fixed cost.
Repeat the procedure
using “Intercept”, to estimate fixed cost.
Simple Regression Using Excel
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As previously, enter the
appropriate cell ranges in their
appropriate places.
As previously, enter the
appropriate cell ranges in their
appropriate places.
The estimated fixed cost per unit is identified here.
The estimated fixed cost per unit is identified here.
Simple Regression Using Excel
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Finally, determine the “goodness of fit”, or R2, by
using the RSQ function.
Finally, determine the “goodness of fit”, or R2, by
using the RSQ function.
Simple Regression Using Excel
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As previously, enter the
appropriate cell ranges in their
appropriate places.
As previously, enter the
appropriate cell ranges in their
appropriate places.
The estimated R2 for your estimated cost function is identified here.
The estimated R2 for your estimated cost function is identified here.
Simple Regression Using Excel
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Simple RegressionExample Summary
The objective of the regression method is a linear equation to estimate costs TC = F + VX
We found the following linear equation for Eagle:TC = $2,618.72 + $2.768 per unit
The high value for R2 tells us that approximately93.26 percent of the variation in total cost
is explained by the variation in the number ofunits produced.
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For example, demand for a product may be affected by factors such as inflation, interest rates and
competitors’ prices.
For example, demand for a product may be affected by factors such as inflation, interest rates and
competitors’ prices.
Multiple Regression is a regression that has more than one independent (X) variable.
Can be very useful in situations where the dependent variable is impacted by several
different independent variables.
Can be very useful in situations where the dependent variable is impacted by several
different independent variables.
Multiple Regression Analysis
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Terms in the equation have the samemeaning as in a simple regression.
Here there are two or more independentvariables instead of only one.
TC = F + V1X1 + V2X2
Multiple Regression Analysis
Each additional independent variable increases the proportion of explained variation (R2)
which is then adjusted for the number of
independent variables.
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A logical relationship must
be established between
the variables. Entering data into the
analysis that have no
logical relationship will
result in meaningless
estimates.
Regression Analysis
Let me give you somepointers on
regression analysis.
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Data points that vary significantly from the regression line (outliers) draw the regression line away from the majority of data points. The least squares
procedure minimizes the sum of squares of the distances from the data points to the line.
Regression Analysis
Let me give you somepointers on
regression analysis.
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The intercept term should be used with caution to estimate fixed cost. The intercept is likely
to be outside the relevant range of observations as it occurs at an activity level of zero.
Regression Analysis
Let me give you somepointers on
regression analysis.
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A regression equation may be a poor predictor of future costs if . . . . Cost-activity
relationships have changed.
Costs themselves have changed independently of changes in activity.
Regression Analysis
Let me give you somepointers on
regression analysis.
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Attempting to fit a linear equation to nonlinear data
Failing to exclude outliers
Including variables that have apparent but spurious relationships
Regression Analysis – Utilization Problems
Regression results are questionable when:
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Missing Data
Mismatched Time Periods
Allocated Costs
Inflation
Regression Analysis Data Problems
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Learning Objective 4
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Objective: Relate costs and activity inthe form of the general cost equation:
TC = F + VX
Account Analysis
Cost estimates are based on areview of each activity account making up
the total cost being analyzed.
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Identify cost drivers and the costs associated with each driver.
Sum the fixed costs (facility costs).
Sum the variable costs for each cost driver activity.
Divide the total variable costs for each cost driver activity by the total number of cost driver units to obtain variable cost per unit.
Divide the fixed costs by the numberof time periods in the data.
Objective: TC = F + VX
Identify cost drivers and the costs associated with each driver.
Sum the fixed costs (facility costs).
Sum the variable costs for each cost driver activity.
Divide the total variable costs for each cost driver activity by the total number of cost driver units to obtain variable cost per unit.
Divide the fixed costs by the numberof time periods in the data.
Objective: TC = F + VX
Account Analysis
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Overhead Costs for 1,000 UnitsTotal Variable Fixed
Account Cost Cost CostIndirect Labor 450$ 450$ Indirect Material 700 700 Depreciation 1,000 1,000 Property Taxes 200 200 Insurance 300 300 Utilities 400 350 50 Maintenance 600 500 100 Totals 3,650$ 2,000$ 1,650$
V = $2,000 ÷ 1,000 units = $2 per unitTC = $1,650 + $2 per unit
Account Analysis - Example
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Estimate the total overhead cost for 1,400 units using the cost relationship from the the preceding
example.
a. $3,300
b. $4,450
c. $3,650
d. $5,650
Estimate the total overhead cost for 1,400 units using the cost relationship from the the preceding
example.
a. $3,300
b. $4,450
c. $3,650
d. $5,650
Account Analysis - Example
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Estimate the total overhead cost for 1,400 units using the cost relationship from the the preceding
example.
a. $3,300
b. $4,450
c. $3,650
d. $5,650
Estimate the total overhead cost for 1,400 units using the cost relationship from the the preceding
example.
a. $3,300
b. $4,450
c. $3,650
d. $5,650
TC = F + VXTC = $1,650 + ($2 × 1,400 units)TC = $1,650 + $2,800 = $4,450
Account Analysis - Example
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Learning Objective 5
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Engineering Method
Past costs are not
taken into account.
Past costs are not
taken into account.
Engineering estimates of cost are made, based on:
• Measurement of work involved in the
activities that go into a product.
• Assigning a cost to each of the activities.
Engineering estimates of cost are made, based on:
• Measurement of work involved in the
activities that go into a product.
• Assigning a cost to each of the activities.
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Direct Labor
•Material requiredfor each unit isobtained from
engineering drawings and specification sheets.
•Material prices are determined from
vendor bids.
•Analyze the kindof work performed.
•Estimate the time required for each labor
skill for each unit.
•Use local wage rates to obtain labor cost
per unit.
Direct Material
Engineering Method
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Overhead costs are obtained in a similar manner – a detailed step-by-step analysis of the work involved.
Advantages of the engineering approach:Detailed analysis results in better knowledge of the
entire process.
The method is used to estimate costs of new activities. Data from prior activities are not required.
A disadvantage of the engineering approach is the high cost of detailed analysis.
Engineering Method
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Choice of an Estimation Method
Regression and account
analysis rely on past data. The
engineering method relies
on present data.
Regression and account
analysis rely on past data. The
engineering method relies
on present data.
Each method will likely
yield a different estimate.
Each method will likely
yield a different estimate.
Cost/Benefit must be
considered in choosing a
method.
Cost/Benefit must be
considered in choosing a
method.
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No single method is best for all situations.
Better results are often obtained by use of several of the methods. For example: Engineering estimates and account analysis may
lead to the establishment of logical, causal relationships between variables.
A scattergraph plot will lead to a better understanding of the relationship and may reveal outlier data points.
Regression provides a cost equation for the data points with statistical measures of fit.
No single method is best for all situations.
Better results are often obtained by use of several of the methods. For example: Engineering estimates and account analysis may
lead to the establishment of logical, causal relationships between variables.
A scattergraph plot will lead to a better understanding of the relationship and may reveal outlier data points.
Regression provides a cost equation for the data points with statistical measures of fit.
Choice of an Estimation Method
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Use of the Results
Levels of demand under different prices Success of new products/services Adequacy of present production and office
facilities; feasibility of outsourcing Overall profitability under many cost and
price scenarios
Cost estimation provides important information for forecasting:
Just keep in mind the limitations of
these estimation techniques!
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Learning Objective 6
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Issues in Using Regressions
This technique does not provide exact measurements. It yields good approxima-tions of the actual relationships between cost drivers and costs.
There is seldom 100% confidence about a relationship between dependent and independent variables.
It cannot be always assumed that the cost estimation errors are normally distributed, independent and with constant variation.
So-called independent variables may be in fact closely correlated.
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Learning Objective 7
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Learning Curve
The learning phenomenon: as we gain in experience,
we take less time to perform a task.
For cost estimation:as cost driver activity increases,the learning phenomenon leads
to lower costs per unit andgreater profitability.
Time
Repeated tasks$
Output
Minimum profit
Incremental profit
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End of Chapter 11