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9609 · 1.3.1

Measurements of business size — common mistakes

Common exam mistakes on 9609 Measurements of business size. Learn what loses marks, then practise the topic with Examiner’s Ink.

Exam tip 1

In an exam, when asked to compare the size of two businesses, always state which measure you are using and justify why it is (or is not) appropriate for the given industry. For example, 'Using revenue, Firm A is larger, which is a suitable measure for the retail industry. However, this ignores profitability...'

Exam tip 2

Market share is a powerful tool for analysis. Use it to discuss a firm's competitive position. A business with a high market share is a 'market leader' and may have significant influence over prices and distribution channels.

Is a business with high revenue always 'bigger' than a business with high profit?

Not necessarily. 'Size' is a multi-faceted concept. A supermarket might have massive revenue but tiny profit margins, making it large by the revenue measure. A specialist software firm could have lower revenue but huge profits and be considered large due to its profitability and market value. Different measures tell different stories about a business's scale and success.

Can a business be considered 'large' by one measure but 'small' by another?

Absolutely. This is a key point of analysis. For example, a modern technology firm might have a huge market share and high capital employed (servers, infrastructure) but a relatively small number of employees due to automation. Conversely, a large legal firm might have thousands of employees but relatively low capital employed as its main assets are its people.

How do you decide which measure of size is the 'best' one to use?

There is no single 'best' measure; the most appropriate one depends entirely on the context. You must consider the industry and the purpose of the comparison. For comparing manufacturing firms, capital employed is often most suitable. For retailers, revenue is a common benchmark. For assessing market power, market share is key. A good analysis will often use multiple measures to build a more complete picture.