ACCA F5: Chapter 9 - Quantitative Analysis

1 High/low analysis A method of analysing a semi-variable cost into its fixed and variable elements based on an analysis of historical information about costs at different activity levels.

1 High/low analysis - The high-low method has the enormous advantage of simplicity. - It is easy to understand and easy to use.

1 High/low analysis - It assumes that activity is the only factor affecting costs. - It assumes that historical costs reliably predict future costs. - It uses only two values, the highest and the lowest, so the results may be distorted due to random variations in these values.

2 Regression analysis Regression is another method of forecasting. It involves using historical data to find the line of best fit between two variables (one dependent on the other), and uses this straight line to predict future values.

2 Regression analysis y = a + bx y = dependant variablex = independant variablea = fixed costb = var cost per unit

2 Regression analysis The strength of the linear relationship between the two variables (and hence the usefulness of the regression line equation) can be assessed by calculating the correlation coefficient (“r”)

2 Regression analysis 1) there is a strong positive correlation between the two variables 2) there is a strong negative correlation between the two variables 3) there is little relationship between the two variables

2 Regression analysis It shows the percentage change in the dependent variable, e.g. sales, that can be explained by a change in the independent variable, e.g. advertising spend r²

3 Time series analysis A time series is a series of figures relating to the changing value of a variable over time. The data often conforms to a certain pattern over time. This pattern can be extrapolated into the future and hence forecasts are possible. Time periods may be any measure of time including days, weeks, months and quarters.

3 Time series analysis - The trend – this describes the long-term general movement of the data - Seasonal variations – a regular variation around the trend over a fixed time period. - Cyclical variations – economic cycle of booms and slumps. - Residual variations – irregular, random fluctuations in the data usually caused by factors specific to the time series. They are unpredictable.

3 Time series analysis Actual = Trend + Seasonal Variation (SV) The SV will be expressed in absolute terms.

3 Time series analysis Actual = Trend × SV factor The SV will be expressed as a percentage, a decimal or an index

4 Average growth models Strategic plans may incorporate an objective of a target average growth of profit or sales over a number of years. There may also be requirements for a target average growth rate of productivity over a number of years. g = average growth rate, as a decimal n = number of periods of growth

5 The use of judgement and experience in forecasting The quantitative models available are mainly based on past information and extrapolate these results into the future. Managers will have access to many sources of information to help them judge whether past results are likely to be good predictors of future results. ie a competitor has recently launched a new product in the market or a new advertising medium is to be used

6 Learning curves As cumulative output doubles, the cumulative average time per unit falls to a fixed percentage (referred to as the learning rate) of the previous average time.