Sistem Biaya Taksiran PERTEMUAN XIII Dr Rilla Gantino, SE., AK., MM MM-FEB

  

Sistem Biaya Taksiran

PERTEMUAN XIII

Dr Rilla Gantino, SE., AK., MM

MM-FEB

KEMAMPUAN AKHIR YANG DIHARAPKAN

  Mahasiswa dapat menghitung dan menginterpretasikan sistem biaya taksiran, Penentuan biaya taksiran, Perlakuan akuntansi terhadap biaya taksiran.

  15-1 Lecture slides to accompany

  Engineering Economy

  7 ^th edition Leland Blank

  

Chapter 15

Chapter 15 Cost

Cost

Estimation

Estimation

and Indirect

and Indirect

  

Costs

Costs

  © 2012 by McGraw-Hill All Rights Reserved

  Cost Estimation

  

Direct and Indirect Cost Estimates

Direct cost Indirect cost examples examples

• Physical assets
• Utilities
• Maintenance and

  operating costs • IT systems and (M&O) networks

• Materials
• Purchasing
• Direct human labor
• Management

  (costs and benefts)

• Taxes
• Scrapped and
• Legal functions

  reworked product

• Warranty and
• Direct supervision

  of personnel guarantees _{© 2012 by McGraw-Hill All Rights Reserved} 15-3

  What Direct Cost Estimation

Includes

  

Direct costs are more commonly estimated than revenue in an

engineering environment. Preliminary decisions required are:

   What cost components should be estimated?

   What approach to estimation is best to apply? How accurate should the estimates be?

    What technique(s) will be applied to estimate costs? frst costs

Sample direct cost components:

  and its elements (P); annual costs (AOC or M&O); salvage/market value (S) bottom-up; design-to-cost (top

Approaches:

  down) feasibility stage through detailed design

Accuracy:

  estimates require more exacting estimates _{© 2012 by McGraw-Hill All Rights Reserved}

15-4

  Diferent Approaches to Cost

Estimation

  © 2012 by McGraw-Hill All Rights Reserved 15-5

Accuracy of Cost Estimates

  General guidelines for

accuracy

  Conceptual/Feasibility stage order- –

of-magnitude estimates are in range of

±20% of actual costs Detailed design stage Detailed - estimates are in range of ±5% of actual costs

  Characteristic curve of accuracy vs. time to make estimates © 2012 by McGraw-Hill All Rights Reserved

  15-6

Unit Method

  preliminary design stage estimates

• Commonly used technique for

• • Total cost estimate C is per unit cost (u) times number of units

  _T

  (N)

C = u × N

_T

• Example uses:
T<
• Cost to operate a car at 60¢/mile for 500 miles: C = 0.60 × 500 = $300
^{2 2} Cost to build a 250 m house at $2250/m : C T = 2250 × 250 = $562,50
• Cost factors must be updated periodically to remain

  timely When several components are involved, estimate cost of each component and add to

determine total cost estimate C

_T

  © 2012 by McGraw-Hill All Rights Reserved 15-7

Cost Indexes

  

 Defnition: Cost Index is ratio of cost today

to cost in the past over time ; therefore,

• Indicates change in cost they account for the impact of infation
• Index is dimensionless
• CPI (Consumer Price Index) is a good example

  © 2012 by McGraw-Hill All Rights Reserved

15-8

Example: Cost Index Method Problem: Estimate the total cost of labor today in US dollars for a maritime construction project using data from a similar project in Europe completed in 1998

  

Labor index, 1998: 789.6 Cost in 1998: €3.9 million

Labor index, current: 1165.8 Currently, 1 € = 1.5

US$ Solution: Let t = today and 0 = 1998 base

C = 3.9 million × (1165.8/789.6) = €5.76

t million = €5.76 × 1.5 = $8.64 million _{© 2012 by McGraw-Hill All Rights Reserved}

  

15-9

Why Estimate Costs?

  Managers make decisions and need to compare costs and benefits among alternative actions.

  Cost estimates can be an important element In helping managers make decisions. Basic Cost Behavior Patterns LO 5-1 Understand the reasons for estimating fixed and variable costs.

  Costs Fixed costs

  Variable costs

  Total fixed costs do not change proportionately as activity changes.

  Per unit fixed costs change inversely as activity changes.

  Total variable costs change proportionately as activity changes.

  Per unit variable cost remain constant as activity changes. ^{LO 5-1}

  _5-1 LO

Methods Used to Estimate Cost Behavior

  

Charlene, owner of Charlene’s Computer Care

(3C), wants to estimate the cost of a

new computer repair center.

  

1. Engineering estimates

  2. Account analysis

  3. Statistical methods

  _5-2 LO

  Engineering Estimates Estimate costs using engineering estimates.

  Cost estimates are based on measuring and then pricing the work involved in a task.

  Identify the activities involved:

• – Labor – Rent – Insurance Estimate the time and cost for each activity.

  _5-2 LO

Engineering Estimates

  Details each step required to perform an operation Permits comparison of other centers with similar operations Costs for totally new activities can be estimated without prior activity data.

  Can be quite expensive to use Based on optimal conditions

  Account Analysis LO 5-3 Estimate costs using account analysis.

  Review each account comprising the total cost being analyzed.

  Identify each cost as either fixed or variable.

  Fixed Variable ^{LO 5-3}

Account Analysis

  Costs for 360 repair-hours Office rent Utilities Administration Supplies Training Other Total Per repair hour

  $ 3,375 310 3,386 2,276 666 613 $10,626

  $1,375 100 186 2,176 316 257 $4,410 $12.25

  $2,000 210 3,200 100 350 356 $6,216

  Account Total Variable cost Fixed cost ^{LO 5-3}

Account Analysis

  Fixed costs + (Variable cost/unit × No. of units) = Total cost Cost at 360 repair-hours:

  $6,216 + ($12.25 × 360) = $10,626 Cost at 480 repair-hours:

  $6,216 + ($12.25 × 480) = $12,096 ^{LO 5-3}

Account Analysis

  Managers and accountants are familiar with company operations and the way costs react to changes in activity levels.

  Managers and accountants may be biased.

  Decisions often have major economic consequences for managers and accountants. ^{LO 5-3} Statistical Cost Estimation LO 5-4 Estimate costs using statistical analysis.

  Analyze costs within a relevant range, which is the limits within which a cost estimate may be valid.

  Relevant range for a projection is usually between the upper and lower limits (bounds) of past activity levels for which data is available. ^{LO 5-4}

Overhead Cost Estimation for 3C

  11

  These data will be used to estimate costs using a statistical analysis. ^{LO 5-4}

  Month Overhead costs Repair- hours

  248 248 480 284 200 380 568 344 448 544 340 412 384 404 212

  15 $ 9,891 $ 9,244 $13,200 $10,555 $ 9,054 $10,662 $12,883 $10,345 $11,217 $13,269 $10,830 $12,607 $10,871 $12,816 $ 8,464

  14

  13

  12

  1

  2

  9

  8

  7

  6

  5

  4

  3

  10

Scattergraph

  Does it look like a relationship exists between repair-hours and overhead costs? ^{LO 5-4} Scattergraph

  We use “eyeball judgment” to determine the intercept and slope of the line. ^{LO 5-4}

  _5-4 LO

  Hi-Low Cost Estimation

  This is a method to estimate cost based on two cost observations, the highest and lowest activity level.

  Overhead Repair-

Month costs hours

  High $12,883 568 Low $ 9,054 200 Change $ 3,829 368 Total cost at lowest activity

  

Variable cost per unit (V) =

^{LO 5-4}

  Hi-Low Cost Estimation

Fixed cost (F) =

• – (Variable cost × Lowest activity level)

  _5-4 LO

  Hi-Low Cost Estimation

  Variable cost ($12,883 – $9,054) $3,829 $10.40 =

  = = per RH (V) 568 RH – 200 RH 368 RH per RH Fixed costs (F) = ($12,883 – ($10.40 × 568 RH) = $6,976 Fixed costs (F) = ($9,054 – ($10.40 × 200 RH) = $6,974

  Rounding difference Hi-Low Cost Estimation

  How do we estimate manufacturing overhead with 480 repair-hours?

  TC = F + VX TC = $6,976 + ($10.40 × 480) = $11,968 ^{LO 5-4}

  _5-4 LO

Regression Analysis

  Regression is a statistical procedure to determine the relation between variables.

  It helps managers determine how well the estimated regression equation describes the relations between costs and activities.

Regression Analysis

  Hi-low method: Uses two data points

  Regression: Uses all of the data points ^{LO 5-4}

Regression Analysis

  Y = a + bX Y = Intercept + (Slope × X)

  For 3C: OH = Fixed costs + (V × Repair-hours) ^{LO 5-4}

  _5-5 LO

  Interpreting Regression Interpret the results of regression output.

  Independent variable:

• – The X term, or predictor
• – The activity that predicts (causes) the change in costs Activities:
• – Repair-hours Dependent variable:
• – The Y term
• – The dependent variable
• – The cost to be estimated Costs:
• – Overhead costs

Interpreting Regression

  The computer output of 3C’s scattergraph gives the following formula: Total overhead = $6,472 + ($12.52 per RH × No. of RH) Estimate 3C’s overhead with 480 repair hours.

  

TC = F + VX

TC = $6,472 + ($12.52 × 480) = $12,482

^{LO 5-5}

Interpreting Regression

  Correlation coefficient (R): This measures the linear relationship between variables. The closer R is to 1.0 the closer the points are to the regression line. The closer R is to zero, the poorer the fit of the regression line.

  Coefficient of determination (R ² ): This is the square of the correlation coefficient.

  It is the proportion of the variation in the dependent variable (Y) explained by the independent variable(s) (X). ^{LO 5-5}

  _5-5 LO

Interpreting Regression

  T-statistic: This is the value of the estimated coefficient, b, divided by its estimated standard error (Se ). Generally, if it is _b over 2, then it is considered significant. If significant, the cost is NOT totally fixed.

  From the data used in the 3C regression, the t-statistic is:

  t = b ÷ Se _b

= 12.5230 ÷ 1.5843

  = 7.9044

Interpreting Regression

  An 0.91 correlation coefficient means that a linear relationship does exists between repair hours and overhead costs.

  An 0.828 coefficient of determination means that 82.8% of the changes in overhead costs can be explained by changes in repair-hours.

  Both have t-statistics that are greater than 2, so the cost is not totally fixed. ^{LO 5-5}

  _5-5 LO

Multiple Regression

  Multiple regression: When more than one predictor (x) is in the model

  Is repair-hours the only activity that drives overhead costs at 3C? Predictors:

  X : Repair-hours ₁ X : Parts cost ₂ Equation: TC = VC(X ) + VC(X ) + FC _{1 2}

  _5-5 LO

Multiple Regression Output

  The adjusted R-squared is the correlation coefficient squared and adjusted for the number of independent variables used to make the estimate.

  The statistics supplied with the output (rounded off) are:

• – Correlation coefficient (R) = 0.953
2<
• – R = 0.908
2<
• – Adjusted R = 0.892

Multiple Regression Output

  TC = F + V ₁ X ₁ + V ₂ X ₂ TC = $6,416 + ($8.61 × 480) + (77% × $3,500)

TC = $13,244

^{LO 5-5}

  _5-6 LO

  Practical Implementation Problems Identify potential problems with regression data.

  Effect of:

• – Nonlinear relations
• – Outliers – Spurious relations
• – Using data that do not fit the assumptions of regression analysis

  _5-6 LO

  Practical Implementation Problems The Effect of Nonlinear Relations $800 Assumed actual cost function $700 $600 t $500 s o

  Regression C $400 estimate $300

  Relevant $200 Capacity range $100 $0 0 5 10 15 20 25 30 35 40 Volume

  _5-6 LO

  Practical Implementation Problems

  Problem:

• Attempting to fit a linear model to nonlinear data
• Likely to occur near full-capacity Solution: • Define a more limited relevant range.

  (Example: from 25-75% capacity) • Design a nonlinear model.

  _5-6 LO

  Practical Implementation Problems

The Effect of Outliers on the Computed Regression

  Computed regression line “Outlier” True regression line

  _5-6 LO

Practical Implementation Problems

  Problem: Outliers move the regression line.

  Solution: Prepare a scattergraph, analyze the graph, and eliminate highly unusual observations before running the regression.

  

The Effect of Spurious Relations

  Problem: Using too many variables in the regression (i.e., using direct labor to explain materials costs).

  Although the association is very high, actually both are driven by output.

  Solution: Carefully analyze each variable and determine the relationship among all elements before using in the regression. ^{LO 5-6}

  Practical Implementation Problems

  _5-6 LO

  Practical Implementation Problems

The Effect of Using Data That Do Not

Fit the Assumptions of Regression

  Problem: If the assumptions in the regression are not satisfied, then the regression is not reliable.

  Solution: There is no clear solution. Limit time to help assure costs behavior remains constant, yet this causes the model to be weaker due to less data.

Learning Phenomenon

  Learning phenomenon is the systematic relationship between the amount of experience in performing a task and the time required to perform it. ^{LO 5-6}

  _5-7 LO

  How an Estimation Method is Chosen Evaluate the advantages and disadvantages

  LO 5-7 of alternative cost estimation methods.

• Reliance on historical data is relatively inexpensive.
• Computational tools allow for more data to be used than for non-statistical methods.
• Reliance on historical data may be the only readily available, cost-effective basis for estimating costs.
• Analysts must be alert to cost-activity changes.

  _5-7 LO

Data Problems

• Missing data
• Outliers • Allocated and discretionary costs
• Inflation • Mismatched time periods

  _5-7 LO

  Efect of Diferent Methods on Cost Estimates Estimated manufacturing overhead with 480 repair-hours. Total Estimated Estimated estimated fixed variable

  

Method costs costs costs

  Account analysis $12,096 $6,216 $12.25/repair-hour High-low $11,968 $6,976 $10.40/repair-hour Simple regression $12,482 $6,472 $12.52/repair-hour Multiple regression $13,244 $6,416 $8.61/repair-hour

• 77% of parts cost

Appendix A: Regression Analysis Using Microsoft Excel

  (Appendix A) Use Microsoft Excel to perform a regression analysis.

  Many software programs exist to aid in performing regression analysis.

  Data is entered and the user then selects the data and type of regression analysis to be generated.

  The analyst must be well schooled in regression in order to determine the meaning of the output.

  In order to use Microsoft Excel, the Analysis Tool Pak must be installed. ^{LO 5-8} Appendix B: Learning Curves

  This is the systematic relationship between the amount of experience in performing a task and the time required to perform it.

  First unit Second unit Fourth unit Eighth unit

  100.0 hours 80.0 hours 64.0 hours 51.2 hours

  (assumed) 80% × 100 hours 80% × 80 hours 80% × 64 hours

  Unit Time to produce Calculation of time

  (Appendix B) Understand the mathematical relationship describing the learning phenomenon. ^{LO 5-9}

• Impact: It causes the unit price to decrease as production increases.
• This implies a nonlinear model.