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Prepared by Diane Tanner University of North Florida

Chapter 10. Cost Estimation. Prepared by Diane Tanner University of North Florida. Cost Estimation . Purpose is to measure a relationship based on data from past costs and the related level of an activity i . e., determine the cost equation

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Prepared by Diane Tanner University of North Florida

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  1. Chapter 10 Cost Estimation Prepared by Diane Tanner University of North Florida

  2. Cost Estimation • Purpose is to measure a relationship based on data from past costs and the related level of an activity • i. e., determine the cost equation • A cause-and-effect relationship may arise as a result of • A physical relationship between the level of activity and costs • A contractual arrangement • Knowledge of operations

  3. Cost Functions • Format of cost function • TC = VCx+ TFC • Y = mX + b • Y = a + bX • Dependent variable = y • Independent variable = x • Assumptions • Variations in the level of a single activity (cost driver) explain the variation in the related total cost • Costs behave in a linear manner within the relevant range of activity • A linear cost function is represented by a straight line M = VC per unit = slope b = TFC = y-intercept

  4. Sample Cost Functions • Fixed cost function • Y = 250 • Variable cost function • Y = 4.56X • Mixed cost function (semi-variable) • Y = 4.56X + 250

  5. Cost Estimation Methods • Industrial engineering method • Estimates cost functions by analyzing the relationship between inputs and outputs in physical terms • Conference method • Estimates cost functions based on analysis and opinions about costs and their drivers gathered from various departments of a company • Account analysis method • Estimates cost functions by classifying various cost accounts with respect to the identified level of activity • Reasonably accurate, cost-effective, and easy to use • Quantitative analysis methods • Mathematical models – high-low, regression

  6. Quantitative Analysis of Cost Functions Step 1: Identify the dependent variable • The cost being estimated or predicted, Y Step 2: Identify the independent variable • The independent variable, i.e., the cost driver, X Step 3: Collect data Step 4: Plot the data - scattergraph Step 5: Estimate the function Regression method or high-low method Step 6: Evaluate the cost driver

  7. High-Low Method • Advantages • Simple • Gives quick insight in cost-activity relationships • Disadvantages • Uses extreme data points • Ignores much of the data • Steps: • Choose high and low activitylevels • Determine the slope (VC per unit) • Plug the slope and one data point into the cost equation to solve for TFC • Write the cost equation in standard form (replacing VC and FC with the correct amounts) • Y = VCx + FC

  8. Regression Analysis • A statistical technique that measures the average amount of change in the dependent variable associated with a unit change in the independent variable • Excel generates output providing cost function components • Uses all the data points • Provides a more accurate cost estimation formula than the high-low method

  9. Excel Regression Output Cost equation: Y = 177.40x + 3,121 Y-intercept X-variable

  10. Evaluating Cost Drivers • Three criteria • Economic plausibility • Does it make sense? • Goodness of fit • Indicates how good a predictors of cost the equation is • R2 • Significance of independent variable • Indicates the percentage of the total variation in the y-values (total cost) that is explained by the regression equation. • Steep slope • Indicates the strength of the relationship between the cost driver and the costs incurred

  11. The End

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