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CHAPTER 3

CHAPTER 3. MEASUREMENT OF COST BEHAVIOUR. CHAPTER 3 LEARNING OBJECTIVES. Explain step- and mixed-cost behaviour. Explain management influences on cost behaviour. CHAPTER 3 LEARNING OBJECTIVES. Measure and mathematically express cost functions and use them to predict costs.

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CHAPTER 3

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  1. CHAPTER 3 MEASUREMENT OF COST BEHAVIOUR

  2. CHAPTER 3LEARNING OBJECTIVES • Explain step- and mixed-cost behaviour. • Explain management influences on cost behaviour.

  3. CHAPTER 3LEARNING OBJECTIVES • Measure and mathematically express cost functions and use them to predict costs. • Describe the importance of activity analysis for measuring cost functions.

  4. CHAPTER 3LEARNING OBJECTIVES • Measure cost behaviour using the account analysis, high-low, visual-fit, and least-squares regression methods.

  5. Introduction This chapter focuses on measurement of cost behaviour. WHAT DOES THAT MEAN?

  6. Linear-Cost Behaviour • Linear-cost behaviour can be graphed with a straight line when a cost changes proportionately with changes in a single cost driver.

  7. Progressive or digressive behaviour Cost Volume

  8. Marginal cost (MC) The extra cost for producing 1 unit more or TC’(x)

  9. Relevant Range • Recall that therelevant range specifies the limits of cost-driver activity within which a specific relationship between a cost and its cost driver will be valid.

  10. Step- and Mixed-Cost Behaviour Patterns Chapter 2 describes two patterns of cost behaviour: variable and fixed costs. Recall that a purely variable cost varies in proportion to the selected cost driver, while a purely fixed cost is not affected by the cost-driver level.

  11. Step- and Mixed-Cost Behaviour Patterns In addition to these pure versions of cost, two additional types of costs combine characteristics of both fixed- and variable-cost behaviour.These are step costs and mixed costs. See exhibit 3-2 page 88

  12. Step Costs • Step costs change abruptly at intervals of activity because the resources and their costs come in indivisible chunks.

  13. Capacity Costs • Capacity costs are the fixed costs of being able to achieve a desired level of production or to provide a desired level of service while maintaining product or service attributes, such as quality.

  14. Mixed Costs • Mixed costs contain elements of both fixed- and variable-cost behaviour.

  15. Committed Fixed Costs • Committed fixed costs usually arise from the possession of facilities, equipment, and a basic organization. These are large, indivisible chunks of cost that the organization is obliged to incur or usually would not consider avoiding.

  16. Discretionary Fixed Costs • Discretionary fixed costs are costs fixed at certain levels only because management decided that these levels of cost should be incurred to meet the organization’s goals.

  17. Discretionary Fixed Costs Each planning period, management will determine how much to spend on discretionary items. These costs then become fixed until the next planning period.

  18. Advertising & promotion Public relations Research & development Charitable donations Employee training programs Management consulting services Examples ofDiscretionary Fixed Costs

  19. Cost Functions • The first step in estimating or predicting costs iscost measurement or measuring cost behaviour as a function of appropriate cost drivers.

  20. Cost Functions • The second step is to use these cost measures to estimate future costs at expected, future levels of cost-driver activity.

  21. Form of Cost Functions • An algebraic equation used by managers to describe the relationship between a cost and its cost driver(s) is called a cost function.

  22. Cost Function Equation Let: Y = Total cost F = Fixed cost V = Variable cost per unit X = Cost-driver activity in number of units

  23. Cost Function Equation We can rewrite the mixed-cost function as: Y = F + VX The mixed-cost function has the familiar form of a straight line -- it is called a linear-cost function.

  24. Other examples Y = VX + F Y = AX2 + BX + F Y = AX3 + BX2 + CX + F V1X + F1 for X<100 Y = 1200000 V2X + F2 for X>100

  25. Plausibility • The cost function must be plausible or believable.

  26. Activity Analysis Activity analysis is especially important for measuring and predicting costs for which cost drivers are not obvious.

  27. Cost Prediction • Cost prediction applies cost measures to expected future activity levels to forecast future costs.

  28. Methods of Measuring Cost Functions Once managers for a firm have determined the most plausible drivers behind different costs, they can choose from a broad selection of methods of approximating cost functions, including:

  29. Methods of Measuring Cost Functions • Engineering analysis • Account analysis • High-low analysis • Visual-fit analysis • Simple least-squares regression, & • Multiple least-squares regression.

  30. Engineering Analysis • Engineering analysis entails a systematic review of materials, supplies, labour, support services, and facilities needed for products and services.

  31. Engineering Analysis It measures cost behaviour according to what costs should be, not by what costs have been.

  32. Account Analysis • The simplest method ofaccount analysis selects a volume-related cost driver and classifies each account as a variable or fixed cost.

  33. Account Analysis The cost analyst then looks at each cost account balance and estimates either the variable cost per unit of cost-driver activity or the periodic fixed cost.

  34. High-Low Analysis • A simple method for measuring a linear-cost function from past cost data is thehigh-low method. It focuses on the highest-activity and lowest-activity points and fitting a line through these two points.

  35. Visual-Fit Analysis • In thevisual-fit methodthe cost analyst visually fits a straight line through a plot of all of the available data, not just between the high point and the low point, making it more reliable than the high-low method.

  36. Simple Least-Squares Regression • Least-squares regression (regression analysis) measures a cost function more objectively by using statistics to fit a cost function to all the data.

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