Survey on Innovation in the Food Processing Industry

Detailed information for 2023

The objective of this survey is to collect new statistical information on the nature and extent of product, process, marketing and organizational innovations in the Canadian food processing industry and on other emerging issues in the food processing industry.

Data release - December 9, 2024

• Questionnaire(s) and reporting guide(s)
• Description
• Data sources and methodology
• Data accuracy

Description

Statistics Canada conducts the Survey on Innovation in the Food Processing Industry in collaboration with Agriculture and Agri-food Canada to collect new statistical information in the food processing industry. The data collection focuses on:
- the nature, extent, challenges, and benefits of innovation in the Canadian food processing industry;
- use of government support programs and efforts to raise capital for innovation;
- research and developments activities in the industry;
- unusable food parts and unmarketable food products; and
- private certification systems.

An innovation is the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organizational method in business practices, workplace organization or external relations.

For the purpose of this survey, innovations can be new to the business, but do not need to be new to one of its markets. This includes products, processes and methods that the business is the first to develop and those that have been adopted from within its enterprise, other businesses or organizations.

The Food Processing Industry is primarily involved in manufacturing and producing food for human and animal consumption, excluding beverage and tobacco manufacturing.

Results from this survey may be used by businesses and trade associations to study industry performance, government departments and agencies, including Agriculture and Agri-Food Canada, to assist in policy formation and by the academic community for research purposes.

Subjects

• Food, beverage and tobacco
• Innovation
• Manufacturing
• Science and technology

Data sources and methodology

Target population

The target population for the Innovation in the Food Processing Industry Survey is all establishments that are active, classified under the North American Industrial Classification System (NAICS) code 311 'Food Manufacturing' with revenues $1 million or more in the calendar year 2023. NAICS 311 includes:
- NAICS 3111 Animal food manufacturing;
- NAICS 3112 Grain and oilseed milling;
- NAICS 3113 Sugar and confectionary product manufacturing;
- NAICS 3114 Fruit and vegetable preserving and specialty food manufacturing;
- NAICS 3115 Dairy product manufacturing;
- NAICS 311614 Rendering and meat processing from carcasses;
- NAICS 311615 Poultry processing;
- NAICS 311616 Beef cattle slaughtering;
- NAICS 311617 Hog slaughtering;
- NAICS 311619 Other animal slaughtering;
- NAICS 3117 Seafood product preparation and packaging;
- NAICS 3118 Bakeries and tortilla manufacturing;
- NACIS 3119 Other food manufacturing.

There are approximately 3,600 in-scope establishments in the target population.

Instrument design

The Survey on Innovation in the Food Processing Industry 2023 uses an electronic questionnaire. The questionnaire was developed based on the 2018 iteration of the survey. Modified or newly added questions were mainly to incorporate emerging concepts and issues both in the innovation and food processing areas.

Statistics Canada's Questionnaire Design Resource Centre (QDRC) field-tested the questionnaire with potential respondents. The Centre for Special Business Projects reviewed and revised the 2023 questionnaire together with Agriculture and Agri-Food Canada to incorporate feedback from QDRC.

Sampling

This is a census of all establishments that are active, classified under the North American Industrial Classification System (NAICS) code 311 'Food Manufacturing' with revenues $1 million or more in the calendar year 2023.
The survey frame was built from units meeting these criteria on the January 31st 2024 snapshot of Statistics Canada's Business Register.

The target population was stratified by the NAICS 4-digit and 6 regions (Alberta, Atlantic, British Columbia and Territories, Ontario, Prairies and Québec).

A secure access code was mailed or emailed to all respondents inviting them to respond to the electronic questionnaire.

The final sample size was 3,660 units.

Data sources

Data collection for this reference period: 2024-03-11 to 2024-06-26

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

The data are collected through an electronic questionnaire (EQ), with non-response follow-up and failed edit follow-up for priority questions.

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

Error detection

To identify, minimize and correct errors, the following quality measures are applied to the data:

- A manual review is performed to ensure that the questionnaire coverage was as anticipated and that a complete response has been provided.

- Data are subjected to computerized edits. These edits are designed to ensure that the accounting relationships are respected and that related variables have been reported on a consistent basis.

- Unusual occurrences are queried to confirm and clarify with the respondents in question.

- If it was not possible to confirm with the respondents, ratios were calculated or Internet sources were used to validate the answer. If the values were considered non-valid, imputation was done.

Imputation

Imputation is used to determine plausible values for all variables that are missing or are inconsistent with the collected data and which could not be resolved through editing.

For most variables, random donor imputation was used within imputation classes.
A minimum number of units was required within each imputation class. When imputation classes were too small, larger classes were created by combining several classes together.

To ensure internal consistency (coherence between variables of the same record), missing or incoherent variable values were imputed in sequence in which they appeared on the questionnaire. This allowed for an imputed question at one point in the questionnaire may have been used as a matching variable for a question located further along in the questionnaire.

The imputation of survey variables was performed in an automated way using BANFF, a generalized system designed by Statistics Canada.

Estimation

The response values for sampled units are multiplied by a final calibrated weight in order to provide an estimate for the target population. Sampling error is measured using the standard error (SE) for proportions and the coefficient of variation (CV) for quantitative variables, which represents the proportion of the estimate that comes from the variability associated with it. The Generalized Estimation System G-EST is used to calculate the estimates and their associated variance (calculated using Taylor linearization). The SEs and CVs are presented in the data tables by letter-grade Quality Indicators from A to F, representing very high to very low quality.

Quality evaluation

To ensure data quality, Statistics Canada took into account and applied throughout the survey process all six dimensions of data quality control, namely, the relevance, accuracy, timeliness, accessibility, interpretability and coherence of the data collected, as per its mandate.

Statistics Canada carried out data validation for qualitative questions by ensuring the flows in the questionnaire were respected to confirm the correct population answered each question, to ensure coherence within a question and across questions in a thematic module and to ensure coherence across questions within the questionnaire.

For quantitative questions, Statistics Canada carried out two main validation processes: data coherence and data confrontation. Data coherence involved reviewing different parts of the questionnaire that covered questions which are either directly or indirectly related to ensure that responses were consistent with what was observed in practice. Data confrontation involves comparing the response from the respondent with other sources of information about either that particular respondent or other establishments within that industry.

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that 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.

Revisions and seasonal adjustment

This methodology type does not apply to this survey.

Data accuracy

Since all estimates from the Innovation in the Food Processing Industry Survey are based on sample results, they are subject to sampling error. This error is expressed using the coefficient of variation (CV) and the standard error (SE). The CV is used for estimates expressed as a number and the SE is used for estimates expressed as a percentage. The CV and SE are included adjacent to the estimates in the published tables.

Quality code A - Excellent (Coefficient of variation - up to 5%; Standard error for percentages - Up to 2.5%)
Quality code B - Very good (Coefficient of variation - greater than 5% up to 10%; Standard error for percentages - greater than 2.5% up to 5%)
Quality code C - Good (Coefficient of variation - greater than 10% up to 15%; Standard error for percentages - greater than 5% up to 7.5%)
Quality code D - Acceptable (Coefficient of variation - greater than 15% up to 25%; Standard error for percentages - greater than 7.5% up to 10%)
Quality code E - Use with caution (Coefficient of variation - greater than 25% up to 35%; Standard error for percentages - greater than 10% up to 15%
Quality code F - Unreliable (Coefficient of variation - greater than 35% ; Standard error for percentages - greater than 15%)

The Innovation in Food Processing Industry survey response rate was 66%