Characteristics of Australian Business methodology

Latest release
Reference period
2021-22 financial year

Explanatory notes


The Business Characteristics Survey (BCS) is an annual survey and is the vehicle for estimates of business use of information technology, business innovation, and a broad range of other non-financial business characteristics.

The BCS has recently gone through a redevelopment process; changes have been made to both the survey content and sample design.

The BCS now comprises of two question modules to be collected in alternate years:

  • an omnibus style collection with a strong focus on Digital Activities; and
  • a subject specific Innovation module.

The 2021-22 BCS Digital activities module is the first iteration of the survey since the redevelopment.  

Reference period

The reference period for most of the characteristics items included in the 2021-22 BCS is during the year ended 30 June 2022 or as at 30 June 2022.

Output classifications

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 ABSBR.

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

In 2021-22, outputs were made available for some data items by location for the first time. The location classification is drawn from the location of business premises reported by the business in the survey.

Rounding and other adjustments

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.


ABS publications draw extensively on information provided freely by individuals, businesses, governments, and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.

Statistical unit

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 unit's 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.

Classification of units

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.

Scope and coverage

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.

The frame for the BCS is a subset of the ABSBR and includes employing businesses only. These are defined as those businesses which register for the ATO's Pay As You Go Withholding (PAYGW) scheme. It is not unusual for some of these 'employing businesses' to have zero employment at various times during the reporting period. The BCS frame is updated to take account of new businesses, businesses that have ceased employing, changes in employment levels, changes in industry and other general business changes. Businesses which have ceased employing are identified when the ATO cancels their ABN and/or PAYGW registration. In addition, businesses with less than 50 employees, which did not remit under the PAYGW scheme in each of the previous five quarters, are removed from the frame. The estimates in this publication include an allowance for the time it takes a newly registered business to be included in the survey frame.

Survey methodology

Collection of data included in this release was undertaken based on a random sample of approximately 7,000 businesses via online forms or mail-out questionnaires. 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 2021-22 BCS had a response rate of 77.1%.

Content changes

As a result of separating the BCS into separate modules for innovation and digital activity, a significant part of the 2021-22 Digital activity module content was redeveloped.

There were 11 new questions added to the Business characteristics sections of the questionnaire and 6 new questions added to the Digital activity sections.



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

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 business use of ICT.

Sampling error

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 two chances in three that a sample estimate differs from the true value by less than one standard error, and about nineteen chances in twenty 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 businesses with a DSL internet connection. If the estimated proportion of businesses with a DSL internet connection was 24.9% and the standard error of this estimate was 1.6. There would be approximately two chances in three that a full enumeration would have given a figure in the range of 23.3% and 26.5%, and nineteen chances in twenty that it would be in the range of 21.7% to 28.1%.

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. RSEs for all data included in this release (including data cube content) are available upon request.

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 businesses with internet access was 0.25%. Multiplied by 100 and then divided by 50 gives an RSE calculated on this basis of 0.5%. 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.

Relative Standard Errors, selected indicators, by employment size(a), 2021-22
 0-45-1920-199200 or more personsTotal
ICT Indicators     
Businesses with:     
internet access0.
Businesses that:     
placed orders via the internet2.
received orders via the internet2.
  1. RSEs for 2021-22 are on proportions basis. 


3D Printing

3D printing is the action or process of making a physical object from a three-dimensional digital model, typically by laying down many thin layers of a material in succession.


The terms 3G and 4G refer to generations of mobile network technology. 3G is an older technology associated with the first wave of touch-screen smartphones. 4G is a newer technology that delivers much faster speeds and supports more intensive mobile activity such as streaming.


Fifth-generation wireless (5G) is the latest iteration of cellular technology, engineered to greatly increase the speed and responsiveness of wireless networks.

Artificial intelligence (AI)

Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.

Blockchain technology

Decentralised, distributed, digital ledger that is used to record transactions across many computers so that any involved record cannot be altered retroactively, without the alteration of subsequent blocks.


Defined by the ABS as an 'always on' internet connection with an access speed equal to or greater than 256kbps.


Describes those technologies including coaxial cable, fibre optic cable and hybrid coaxial cable which are capable of transmitting data at speeds of up to 10Gbps.

Cloud computing

Cloud computing refers to IT services that are used over the internet to access software, computing power and/or storage capacity.


Active joint participation with other organisations which involves some sharing of technical or commercial risk. Straight fee-for-service arrangements are not deemed to be collaborative and are therefore excluded.

Customer Relationship Management software (CRM)

CRM is a technology for managing all a company’s relationships and interactions with customers and potential customers. A CRM system helps companies stay connected to customers, streamline processes, and improve profitability.

There are 3 types of CRM systems: Operational, Analytical and Collaborative.

Digital Subscriber Line (DSL)

More properly referred to as xDSL as this covers several digital technologies (e.g., Asymmetric DSL or ADSL and Symmetric DSL or SDSL) for fast two-way data connections over the public switched telecommunications network.

Debt finance

Includes any finance the business must repay.


eInvoicing is the new standardised way of exchanging invoices directly between suppliers' and buyers' software.

Electronic Data Interchange (EDI)

EDI is the computer to computer exchange of business documents in a standard electronic format between business partners. For example:  Buyers internal system sending a purchase order online and receiving an invoice online from the supplier’s internal system.

Enterprise resource planning software (ERP)

ERP or Enterprise Resource Planning, is a modular software system designed to integrate the main functional areas of an organisation’s business processes in a unified system.

Some examples of the types of processes that ERPs can be applied to are: Financial operations, Human resources, Production & distribution, Orders & inventory.

Equity finance

Includes finance provided in exchange for a share in the ownership of the business.

Financial reference period

Financial year ended 30 June 2022. Businesses with a different financial year were asked to report for a 12-month period between 1 October 2021 and 30 September 2022.

Fixed Wireless Internet access

A terrestrial point-to-point microwave or radio link, generally building to building or tower to building, which allows subscribers within the receiving building to access the internet.

Internet of things (IoT)

System of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.

Examples of IoT devices include Universal remote control, smart power plug, smart light switch, home voice controller e.g., Google home voice controller.


A commitment to purchase goods or services.

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