Characteristics of Australian Business methodology

The Business Characteristics Survey (BCS) is a biennial survey used to produce estimates of a broad range of non‑financial business characteristics, including business use of information and communication technology (ICT) and business innovation. A flexible modular component is included to collect data on emerging areas of interest or to meet point‑in‑time information needs (e.g. the Principal Manager suite in 2024–25).

The BCS has undergone a recent redevelopment, which resulted in changes to survey content and collection frequency (see History of changes for further information).

Characteristics of Australian Business, 2024–25 is the first release under this revised approach.

The scope of the estimates in this publication consists of all employing business entities in the Australian economy, except for:

• SISCA 3000 General government
• SISCA 6000 Rest of the world
• ANZSIC06 Division O Public administration and safety
• ANZSIC06 Division P Education and training
• ANZSIC06 Groups 624 (Financial asset investing) and 633 (Superannuation funds)
• ANZSIC06 Groups 954 (Religious services) and 955 (Civic, professional and other interest group services)
• ANZSIC06 Subdivision 96 Private households employing staff and Undifferentiated Goods-and Service-Producing Activities of Households for Own Use

The BCS frame is updated to take account of:

• new businesses
• businesses that have ceased employing
• changes in employment levels
• changes in industry
• other general business changes 

Collection of data included in this release was undertaken based on a random sample of approximately 7,000 businesses via online forms. The sample was stratified by industry, employment size and a state-based indicator. All businesses on the ABSBR identified as having 1,000 or more employees were included in the sample.

The 2024-25 BCS had a response rate of 87.9%.

The reference period for all data items included in the 2024-25 BCS is either during the year ended 30 June 2025 or as at 30 June 2025.

The BCS draws on the conceptual definitions and guidelines included in the Guidelines for Collecting, Reporting and Using Data on Innovation, 4th Edition. Jointly published by the OECD and Eurostat, this manual provides a framework for the collection of innovation statistics and specifies the definitions of innovating businesses and innovation-active businesses that are used by the ABS.

Key indicators of innovation include measures of:

• business innovation (innovating, innovation-active)
• types of innovation (goods, services or processes)
• status of innovation (introduced, still in development, abandoned)

Definitions for each of these are provided in the Glossary.

For output purposes, businesses are classified to employment size ranges based on actual data reported in the survey.

For industry output, the classification is drawn from information held about the business on the ABS Business Register (ABSBR).

For state output, the classification is drawn from the main state of operation of the business.

The location classification is drawn from the location of business premises reported by the business in the survey.

Estimates of proportions have been calculated using unrounded figures but are shown in the tables rounded to one tenth of a percentage point. Where figures have been rounded, discrepancies may occur between the sum of the component items and the total. Figures presented in the commentary have been rounded to the whole percentage.

The Economics Unit Model is used by the ABS to determine the structure of Australian businesses and other organisations. The model consists of:

• The Enterprise Group (EG)
• Legal Entities (LEs)
• Type of Activity Units (TAUs)
• Location Units

Businesses contributing to the estimates in this publication are sourced from the ABS Business Register (ABSBR) and are selected at either the Australian Business Number (ABN) unit or the Type of Activity Unit (TAU) level, as described below.

In the BCS, the statistical unit used to represent most businesses, and for which statistics are reported, is the ABN unit. The ABN unit is the business unit which has registered for an ABN and thus appears on the Australian Tax Office (ATO) administered Australian Business Register (ABR). These units are suitable for ABS statistical needs when the business is simple in structure and are generally referred to as the non-profiled population. In these instances, one ABN equates to one statistical unit.

For more significant and diverse businesses where the ABN unit is not suitable for ABS statistical needs, the ABS maintains its own units structure through direct contact with the business, and the statistical unit used is the TAU. A TAU comprises one or more business entities, sub-entities, or branches of a business entity within an Enterprise Group that can report production and employment activities. When a minimum set of data items is available, a TAU is created which covers all the operations within an industry subdivision (and the TAU is classified to the relevant subdivision of the Australian and New Zealand Standard Industrial Classification (ANZSIC)). These units are generally referred to as the profiled population.

ANZSIC is used to classify the industry in which the TAU or ABN has productive activity. Further information on this classification can be found in Australian and New Zealand Standard Industrial Classification (ANZSIC), 2006 (Revision 2.0).

The Standard Institutional Sector Classification of Australia (SISCA) provides a framework for dividing the Australian economy into institutional sectors. Further information on this classification can be found in Standard Economic Sector Classifications of Australia (SESCA), 2021.

When interpreting the results of a survey, it is important to consider factors that may affect the reliability of the estimates. Estimates in this publication are subject to both non-sampling and sampling errors.

Non-sampling errors may arise because of errors in the reporting, recording, or processing of the data and can occur even if there is a complete enumeration of the population. These errors can be introduced through inadequacies in the questionnaire, treatment of non-response, inaccurate reporting by respondents, errors in the application of survey procedures, incorrect recording of answers, and errors in data capture and processing.

The extent to which non-sampling error affects the results of the survey is difficult to measure. Every effort is made to reduce non-sampling error by careful design and testing of the questionnaire, efficient operating procedures and systems, and the use of appropriate methodology.

Some of the items collected in the BCS are dynamic in nature and the concepts measured are subject to evolution and refinement over time; it is not possible to measure the impact of these changes on data quality.

The approach to quality assurance for the BCS aims to make the best use of ABS resources to meet user prioritised requirements - both in terms of data quality and timing of release. The approach specifies the level and degree to which each data item is quality assured, noting that only some of the total output from the BCS can be quality assured to the highest standards. Different priorities are assigned to groups of data items, with highest priority being assigned to key point in time data on innovation.

The difference between estimates obtained from a sample of businesses, and the estimates that would have been produced if the information had been obtained from all businesses, is called sampling error. The expected magnitude of the sampling error associated with any estimate can be estimated from the sample results. One measure of sampling error is given by the standard error (SE), which indicates the degree to which an estimate may vary from the value that would have been obtained from a full enumeration (the 'true' figure). There are about 2 chances in 3 that a sample estimate differs from the true value by less than one standard error, and about 19 chances in 20 that the difference will be less than two standard errors.

The following is an example of the use of standard error on the estimated proportion of innovation-active businesses. If the estimated proportion of innovation-active businesses was 45.6% and the standard error of this estimate was 2.0, there would be approximately 2 chances in 3 that a full enumeration would have given a figure in the range of 43.6% and 47.6%, and 19 chances in 20 that it would be in the range of 41.6% to 49.6%.

In this publication, indications of sampling variability are measured by relative standard errors (RSEs). The relative standard error is a useful measure in that it provides an immediate indication of the percentage errors likely to have occurred due to sampling and thus avoids the need to refer to the size of the estimate. Relative standard errors are shown in the Relative Standard Error table in this section.

To annotate proportion estimates, a value of 50% has been used in the calculation of RSE rather than the estimated proportion from the survey data. This avoids inconsistencies between the way very low and very high proportions are annotated. Relative standard errors for estimates in this publication have been calculated using the actual standard error and the survey estimate (referred to as x) in the following manner: RSE%(x) = (SE(x)*100)/50.

Using the previous example, the standard error for the estimated proportion of innovation-active businesses was 2.0%. Multiplied by 100 and then divided by 50 gives an RSE calculated on this basis of 4.0%. It is these figures that appear in the table appended to this chapter.

Estimates may have corresponding RSE range values annotated. Depending on the level of RSE, data should be used with caution. Estimates with RSEs between 10% and 25% are subject to sampling variability too high for some purposes. Estimates with RSEs between 25% and 50% are subject to sampling variability too high for most practical purposes and estimates with an RSE greater than 50% indicate that the sampling variability causes the estimates to be considered too unreliable for general use.

Estimates with an annotated RSE of between 10% and 25% should be used with caution as the estimate from full enumeration could lie more than a decile away. For example, a proportion estimate of 30% with this RSE annotation, means the full enumeration value could lie beyond the range 20% to 40%. Estimates with an annotated RSE of between 25% and 50% could lie more than a quartile away and is subject to sampling variability too high for most practical purposes. A proportion estimate of 30% annotated with this RSE annotation, means the full enumeration value could lie beyond the range 5% to 55%. Proportion estimates annotated with RSE greater than 50% have a sampling error that causes the estimates to be considered too unreliable for general use.

The BCS was conducted annually from 2005–06 and was previously published across multiple releases, including:

• Innovation in Australian Business (8158.0)
• Characteristics of Australian Business (8167.0)
• Summary of IT Use and Innovation in Australian Business (8166.0)
• Business Use of Information Technology (8129.0) 

After stakeholder consultation in 2019–20, survey content was reviewed and separated (‘decoupled’) into two collections released in alternating years:

• Innovation in Australian Business, based on the Innovation Module (IM), provides detailed information on innovation activities, including collaboration and expenditure, and was released for the 2020–21 and 2022–23 reference years. 
• Characteristics of Australian Business, based on the Digital Activity Module (DA), provides information on digital technology use, Information and Communication Technology (ICT) use, general business characteristics and cybersecurity practices, and was released for the 2021–22 reference year. The scheduled 2023–24 cycle did not proceed.

The survey has subsequently been redesigned into a single biennial collection. Content from the innovation and digital activity modules has been combined (‘recoupled’), with the addition of a flexible component, into a single survey instrument. Characteristics of Australian Business, 2024–25 is the first release under this revised approach, with the next release scheduled for 2026–27.