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

2.  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 2

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 3 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 4

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 5

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 6

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 activity levels  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 7

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 8

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

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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 10

11. 11 The End