1. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin DSS-ESTIMATING COSTS

2. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-2 Cost prediction Using results of cost estimation to forecast a level of cost at a particular activity. Focus is on the future. Existing relationship between cost and activity. Process of estimating relationship between costs and cost driver activities that cause those costs. Cost estimation Cost behavior Introduction

3. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-3 Management needs to know the costs that are likely to be incurred for each alternative. How much will costs increase if sales increase 10 percent? What will my costs be if I introduce the new model in a foreign market? Reasons for Estimating Costs

4. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-4 Better Decisions Add Value Accurate Cost Estimates Improved Decision Making Reasons for Estimating Costs

5. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-5 Relationship between activities and costs Activities Costs 3. To reduce these 1. First, identify this We estimate costs to:  manage costs  make decisions  plan & set standards We estimate costs to:  manage costs  make decisions  plan & set standards 2. Then manage these Exh. 11-1 Reasons for Estimating Costs

6. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-6 Intercept = Fixed Cost Slope = Cost Driver Rate $.16 One Cost Driver and Fixed/Variable Cost Behavior Exh. 11-2

7. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-7 Curvilinear Cost Function Relevant Range Activity Total Cost Curvilinear Cost Function A straight-Line (constant unit variable cost) often closely approximates a nonlinear line within the relevant range. Nonlinear Costs

8. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-8 The high-low method uses two points to estimate the general cost equation TC = F  VX TC = the value of the estimated total cost F = a fixed quantity that represents the value of Y when X = zero V = the slope of the line, the unit variable cost. X = units of the cost driver activity. The High-Low Method

9. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-9 0 1 2 3 4 10 20 0 * * * * * * * * * * The high-low method uses two points to estimate the general cost equation TC = F + VX The two points should be representative of the cost and activity relationship over the range of activity for which the estimation is made. Activity, 1,000s of Units Produced Total Cost in 1,000s of Dollars The High-Low Method

10. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-10 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. The High-Low Method

11. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-11  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 The High-Low Method

12. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-12 Regression Analysis A statistical method used to create an equation relating dependent (or Y ) variables to independent (or X ) variables. Past data is 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. Past data is used to estimate relationships between costs and activities. 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.

13. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-13 The objective of the regression method is still a linear equation to estimate costs TC = F + VX TC = value of the dependent variable, estimated 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 Analysis

14. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-14 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 Dependent Variable Independent Variable Regression Analysis

15. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-15 50 100 150 200 400 350 300 250 200 Dependent Variable Independent Variable V = the slope of the regression line or the coefficient of the independent variable, the increase in TC for each unit increase in X. F = a fixed quantity, the intercept Regression Analysis

16. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-16 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 20 0 * * * * * * * * * Activity * The correlation coefficient is highly positive (close to 1.0) if the data points are close to the regression line. Regression Analysis

17. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-17 0 1 2 3 4 Total Cost 10 20 0 Activity * * * * * * * * * * The correlation coefficient is near zero if little or no relationship exists between the variables. The correlation coefficient, r, is a measure of the linear relationship between variables such as cost and activity. Regression Analysis

18. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-18 0 1 2 3 4 Total Cost 10 20 0 Activity * * * * ** * * * * This relationship has a negative correlation coefficient, approaching a 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

19. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-19 50 100 150 200 400 350 300 250 200 Regression with high R 2 (close to 1.0) Dependent Variable Independent Variable R 2, the coefficient of determination, is a measure of the goodness of fit. R 2 tells us the amount of the variation of the dependent variable that is explained by the independent variable. Regression Analysis

20. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-20 Regression with low R 2 (close to 0) 50 100 150 200 400 350 300 250 200 Dependent Variable Independent Variable The coefficient of determination, R 2, is the correlation coefficient squared. Regression Analysis

21. The McGraw-Hill Companies, Inc. 2006McGraw-Hill/Irwin 11-21  Uses all data points resulting in a better 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.  Uses all data points resulting in a better 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