Sources of Data

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1 Introduction

The management accountant needs data in order to be able to process it into information.

This chapter lists various sources of data and also various sampling techniques.

2 Primary and secondary sources of data

Primary data are data that have been collected for the specific purpose.

Secondary data are data that have been collected for some other purpose but which we then use for our purposes.

3 Internal and external sources data

• Internal data are data collected from our own records. These are the main source of primary data.

There will be costs associated with collecting this data, for example the labour cost of entering the data or the implementation of bar codes. These are direct data capture costs.

• External data are data collected from elsewhere – e.g. the internet, government statistics, financial newspapers. These will be secondary data.

There will be costs associated with collecting this data. For example the cost (if relevant) of paying the other party for the data and the cost of checking how reliable to data is. There are indirect data capture costs.

4 Sampling

It is common to collect data from a sample rather than from the whole population. Data from the sample are used as representative of the whole population.

5 Sampling methods

You should be aware of the following methods of sampling:

• random sampling

Every item in the population has an equal chance of being selected

• systematic sampling (quasi-random)

Select (for example) every 10th item in the population

• stratified sampling (quasi-random)

Split the population into groups, and then select at random. For example, if 60% of the population are women and 40% are men, then 60% of the sample should be women and 40% men.

• multistage sampling (quasi-random)

For example, suppose a company has several thousand purchase invoices filed, filling 20 files. Take a random sample of (say) 5 files, and then a random sample of (say) 20 invoices from each of these files.

• cluster sampling (not random)

For example, suppose a company has 100 offices through the country, each issuing sales invoices.

Take a random sample of (say) 5 offices and check every invoice at each of these offices.

• quota sampling (not random)

Suppose the population is 60% women and 40% men, and that we want to question a sample of 200 total. Decide on a quota of 120 women (60%) and 80 men (40%) and then stop people as they appear until we have the required number of each.

6 Big data

‘Big data’ are extremely large collections of data that can be analysed to reveal patterns, trends, and associations, especially relating to customers of a business.

For example, airlines know where you’ve flown, your preferred seats, cabin class, when you fly, how often you search for a flight before booking, probably which airline you might book with instead, whether you are returning with them but didn’t fly out with them, whether car hire was purchased last time, what class of hotel you might book through their site, which routes are growing in popularity, seasonality of routes. They also know the profitability of each customer so that, for example, if a flight is cancelled they can help the most valuable customers first.

This information allows airlines to design new routes and timings, match routes to planes and also to make individualised offers to each potential passenger.