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DSS-ESTIMATING COSTS

DSS-ESTIMATING COSTS. 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.

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DSS-ESTIMATING COSTS

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  1. DSS-ESTIMATING COSTS

  2. Costprediction Costestimation Introduction Costbehavior Existingrelationshipbetweencost andactivity. Process ofestimating relationship between costsand cost driveractivities that cause those costs. Using results ofcost estimationto forecast alevel of cost ata particularactivity. Focusis on the future.

  3. How muchwill costs increaseif sales increase10 percent? What will mycosts be if I introducethe new model in aforeign market? Reasons for Estimating Costs Management needsto know the costs thatare likely to beincurred for eachalternative.

  4. Reasons for Estimating Costs AccurateCostEstimates BetterDecisionsAdd Value ImprovedDecisionMaking

  5. Exh. 11-1 Reasons for Estimating Costs Relationship between activities and costs 3. To reduce these 1. First, identify this Costs • We estimate costs to: • manage costs • make decisions • plan & set standards 2. Then manage these Activities

  6. Exh. 11-2 One Cost Driver and Fixed/Variable Cost Behavior Slope = Cost Driver Rate $.16 Intercept = Fixed Cost

  7. CurvilinearCost Function A straight-Line(constant unit variable cost) often closely approximates a nonlinear line withinthe relevant range. Total Cost Relevant Range Nonlinear Costs CurvilinearCost Function Activity

  8. The High-Low Method 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.

  9. The High-Low Method The high-low method uses two points to estimate the general cost equation TC = F + VX 20 * * * * * * Total Cost in1,000s of Dollars * * * * 10 The two points should be representative ofthe cost and activity relationship over the rangeof activity for which the estimation is made. 0 0 1 2 3 4 Activity, 1,000s of Units Produced

  10. The High-Low Method 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.

  11. The High-Low Method • 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

  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. Before doing the analysis, take time to determine if a logical relationship between the variables exists. Independent variables are the cost drivers that drive the variation in dependent variables.

  13. Regression Analysis 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

  14. Regression Analysis 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. 400 350 300 250 200 Dependent Variable 50 100 150 200 Independent Variable

  15. Regression Analysis V = the slope of the regression line or the coefficient of the independent variable, the increase in TC for each unit increase in X. 400 350 300 250 200 Dependent Variable F = a fixed quantity, the intercept 50 100 150 200 Independent Variable

  16. Regression Analysis Thecorrelation coefficient, r,is a measure of the linear relationship between variables such as cost and activity. 20 * * * * * * * * * * Total Cost 10 The correlation coefficient is highly positive (close to 1.0) if the data points are close to the regression line. 0 0 1 2 3 4 Activity

  17. Regression Analysis Thecorrelation coefficient, r,is a measure of the linear relationship between variables such as cost and activity. * * * * 20 * * * * * * Total Cost 10 The correlation coefficient is near zero if little or no relationshipexists between the variables. 0 0 1 2 3 4 Activity

  18. Regression Analysis Thecorrelation coefficient, r,is a measure of the linear relationship between variables such as cost and activity. * * 20 * * * * * * * * Total Cost 10 This relationship has a negative correlation coefficient, approachinga maximum value of –1.0 0 0 1 2 3 4 Activity

  19. Regression Analysis R2, the coefficient of determination, is a measureof the goodness of fit. R2 tellsus the amountof the variation of the dependent variable thatis explained by the independent variable. 400 350 300 250 200 Dependent Variable Regression withhigh R2 (close to 1.0) 50 100 150 200 Independent Variable

  20. Regression Analysis The coefficient ofdetermination, R2,is the correlationcoefficient squared. 400 350 300 250 200 Dependent Variable Regression withlowR2 (close to 0) 50 100 150 200 Independent Variable

  21. Regression Analysis • 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.

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