Annual Survey of Software Development and Computer Services

Detailed information for 1998





Record number:


This survey collects the data necessary for the statistical analysis of the Software Development and Computer Services industry.

Data release - February 2, 2001


The survey objective is to collect and publish data from businesses engaged in providing computer services data processing services, Internet service providers, or software publishers in Canada.

The information can be used by businesses for market analysis, by trade associations to study performance and other characteristics of their industries, by government to develop national and regional economic policies, and by other involved in research or policy making.

Statistical activity

This survey is part of the Service Industries Program. The survey data gathered are used to compile aggregate statistics for over thirty service industry groupings. Financial data, including revenue, expense and profit statistics are available for all of the surveys in the program. In addition, many compile and disseminate industry-specific information.

Reference period: Calendar year


  • Business, consumer and property services
  • Business performance and ownership
  • Financial statements and performance
  • Information and culture
  • Professional, scientific and technical services

Data sources and methodology

Target population

The target population consists of all statistical establishments (sometimes referred to as firms or units) classified as Computer Systems Design and Related Services (NAICS 541510), Software Publishers (NAICS 511210) and Data Processing, Hosting and Related Services (NAICS 514210) according to the North American Industry Classification System (NAICS) 1997 during the reference year.


This is a sample survey.

The survey is a Sample Survey with a take-all portion.

Even though the basic objective of the survey is to produce estimates for the whole industry --- incorporated and unincorporated--- the portion of the population eligible for sampling was defined as all incorporated statistical establishments with revenue above $50,000. Some exceptional unincorporated units were also added to direct data collection if their contribution was deemed significant. The same principle applies to unincorporated units belonging to complex enterprises. The main motivation for the exclusion of unincorporated firms and incorporated firms below $50,000 from direct data collection was to achieve major reductions in the response burden.

The survey design covered only the portion of the frame subject to direct data collection. Prior to the selection of a random sample, units are grouped in homogeneous groups defined using industrial (NAICS) and geographic (province/territory) attributes. Similar quality requirements are targeted for each group which is then divided into four sub-group called strata: must-take, take-all, large take-some and small take-some.

The take-all stratum includes the largest firms in terms of industrial performance which are selected in the sample with certainty making such units self-representing. The must-take stratum is also comprised of self-representing units that have a complex structure (multi-establishments, multi-legal, multi-NAICS or multi-province enterprises).

Units in the two take-some strata are subjected to a random sample where each sampled firm represents a number of other, similar firms in the industry/province combination according to the inverse of their probability of selection.

Finally, the size of the sample was increased to compensate for such situations as non-response and firms which cannot be contacted because they have moved or gone out of business.

Data sources

Responding to this survey is mandatory.

Data are collected directly from survey respondents and extracted from administrative files.

Data are collected through a mail-out/mail-back process, while attempting to provide respondents with the option of telephone or other electronic filing methods as required. Even though the sampling unit was the statistical establishment, the statistical company was chosen as the collection entity in order to reduce respondent burden and simplify collection procedures. Therefore, companies with production at more than one locale were mailed only one questionnaire, and were instructed to report for all their operations in the surveyed industry. Summary data were collected for each province or territory in which the company operated.

View the Questionnaire(s) and reporting guide(s) .

Error detection

Annually, during preparation of preliminary and final estimates, previous years' data are revised to reflect new information (eg. more recent taxation data, more reliable indicators of industry code).


For non-response, imputation is performed using a "nearest neighbour" procedure (donor imputation) using available auxiliary information to substitute the data from a company with similar characteristics. In addition to the donor imputation approach, imputation can also be done using historical responses.


Prior to estimation, data for companies with production in more than one province or territory were allocated to the provincial level. The survey data collected from the sample were then weighted using the inverse of the probability of selection of each sampled unit to produce estimates representative of the target population. Tax information was used to estimate the portion that was excluded from survey activity (i.e. unincorporated firms and incorporated firms with revenue less than $50,000).

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects which could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

Data accuracy

For surveyed firms, data quality is largely dependent upon the accuracy of the figures reported by respondents. Reported data for the current year are compared with data reported for previous years. Large variations are confirmed by telephone or letter. Industry estimates are influenced by the attribution of a firm's data to a single industry even though it may be engaged in more than one industrial activity.

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