This lesson delves into the vital relationship between costs and business activity levels. It examines the characteristics of variable, fixed, and semi-variable costs and introduces methods for separating fixed and variable elements from mixed costs.

• Variable Costs: Costs that change, in total, in direct proportion to changes in the level of activity . The variable cost per unit remains constant, but total variable cost varies with volume. Examples include direct materials and sales commissions. This behaviour is linear within a defined ‘relevant range’ .

• Fixed Costs: Costs that remain constant in total, within a specific period and relevant range, irrespective of changes in activity levels . The fixed cost per unit decreases as activity increases and increases as activity falls. Examples include rent, property taxes, and salaries for permanent staff.

• Semi-Variable (Mixed) Costs: Costs that contain both a fixed and a variable element . For instance, a telephone bill includes a fixed line rental plus a variable element for the number of calls made. A utility bill might have a fixed base charge plus a variable element based on consumption.

• Stepped Costs: These are fixed over a particular range of activity but ‘step up’ to a higher level of total cost when that range is exceeded. For example, when production volume passes a certain threshold, a factory may need to hire a second supervisor, causing the total supervisory cost to ‘step up’ .

• Analysing Semi-Variable Costs: For planning and control, it is necessary to separate semi-variable costs into their fixed and variable components. Common methods, as detailed in CIMA curricula, include:

  • High-Low Method: This method uses the costs at the highest and lowest activity levels to calculate the variable cost per unit . The variable cost per unit is the difference in cost divided by the difference in activity. The fixed cost is then derived by subtracting the total variable cost at either level from the total cost .

  • Least Squares Regression (Scattergraph Method): A statistical technique that determines the line of best fit for a set of data points, providing a more accurate estimate of the fixed and variable cost components compared to the high-low method .