Canadian Centre for Justice and Community Safety Statistics
June 2025

Executive summary

In response to increasing demands for better disaggregated data to help shed light on individuals' diverse experiences, Statistics Canada and the Canadian Association of Chiefs of Police have committed to collaborating on an initiative to collect data on the Indigenous and racialized identity of all victims and accused persons through the Uniform Crime Reporting (UCR) Survey. The current article provides an update on the status and next steps of this initiative—the Police-reported Indigenous and Racialized Identity Data (PIRID) project.

On September 1, 2022, Statistics Canada published the interim Report and Draft Recommendations: Police-Reported Indigenous and Racialized Identity Statistics via the Uniform Crime Reporting Survey (hereafter referred to as "the September report"). This report was a culmination of feedback received through engagements with various partners as part of the initial step toward the collection of police-reported data on the Indigenous and racialized identity of all victims and accused persons through the UCR Survey. The September report included reassurances, guiding principles and recommendations to inform the next steps of the initiative. There were six recommendations developed as part of the first phase; expanded to 12 throughout Phase II, which are informing the work currently underway related to the PIRID project. These recommendations can be found in Appendix A below.

Following the release of the September report, Phase II of the project began with the goal of operationalizing the recommendations outlined in Phase I and developing a process roadmap for interpreting the draft recommendations from this report into concrete data collection and analysis methods and plans. Similar to Phase I, Statistics Canada conducted a second phase of engagements with various partners with diverse perspectives to obtain their feedback on the recommendations and assess any concerns or considerations related to the operationalization. The "What we have done" section below outlines the efforts undertaken related to operationalizing the initiative during Phase II, and the beginning of implementation during Phase III.

Background

On July 15, 2020, a joint announcement was made by Statistics Canada and the Canadian Association of Chiefs of Police (CACP) committing to working collaboratively on the collection of Indigenous and racialized identity data of all accused and victims of criminal incidents through the Uniform Crime Reporting (UCR) Survey. The announcement was in response to increasing demands for better disaggregated data that would speak to the disparate treatment and overrepresentation of Indigenous and racialized persons in the Canadian criminal justice system. A lack of national-level data has made it difficult to assess the extent of these issues accurately and to develop effective solutions (David & Mitchell, 2021; Millar & Owusu-Bempah, 2011; Samuels-Wortley, 2021; Truth and Reconciliation Commission of Canada, 2015; Wortley, 1999).

Although UCR Survey data are limited to criminal incidents, the collection of data on the Indigenous and racialized identity of all accused and victims of crime may prove critical in understanding and addressing disparities in the criminal justice system (David & Mitchell, 2021; Millar & Owusu-Bempah, 2011). As a first point of entry into the criminal justice system, UCR Survey data may also allow for further analyses of Indigenous and racialized groups' experiences with other aspects of the criminal justice system, through the linkage of policing, courts and corrections data.

Using a multi-phased approach, Statistics Canada has begun working toward the goal of enabling the collection of these data by police services. The remainder of this document will discuss the completed  phases of the initiative, the current status of the initiative and next steps. The chart below shows the major deliverables and timelines of the initiative.

Following the joint announcement in 2020, Statistics Canada consulted internally and with its key partners on how best to approach the initiative to collect Indigenous and racialized identity data of victims and accused persons through the UCR Survey. In Phase I of the initiative, Statistics Canada embarked on an engagement process to seek feedback from diverse perspectives, including Indigenous and racialized group organizations, police services, academics, and other parties of interest at the national, provincial or territorial, municipal, and local government levels. Next, Statistics Canada distributed to over 500 identified stakeholders a written engagement document with a discussion guide to seek feedback and input. The agency also held virtual roundtables between July 2021 and February 2022. These engagements led to Statistics Canada publishing a draft report and recommendations in September 2022 to guide the next phases of the initiative. The activities undertaken since the September report are briefly outlined below. For more details on Phase I of the initiative, please see the full September report.

In Phase II of the initiative (see "What we have done"), the focus was to develop a process roadmap for translating the draft recommendations from the September report into concrete data collection and analysis methods and plans. Similar to Phase I, Statistics Canada conducted a second phase of engagements with various partners with diverse perspectives, including community organizations, academics, police services, police associations and other parties of interest at the national, provincial or territorial, municipal, and local government levels to obtain their feedback on the recommendations and assess any concerns or considerations related to operationalization. The "What we have done" section below outlines the efforts undertaken related to operationalizing the initiative during this phase.

Following the completion of Phase II, the focus of the initiative will be shifted to Phase III (implementation). In the "Where we are headed" section, the goals of this phase are briefly outlined.

To stay up to date on this initiative, please visit Statistics Canada's Crime and Justice Statistics.

What we have done

Following the release of the draft report and recommendations in September 2022, the second phase of the project began with the goal of operationalizing the recommendations outlined in the first phase. The focus of Phase II (operationalization) was to conduct a second round of engagements to seek further input, address any additional concerns, and develop a process roadmap for translating the draft recommendations into concrete data collection and analysis methods and plans.

Stakeholder engagement

During Phase II, Statistics Canada held debriefs with partners, stakeholders and other interested parties on the results of Phase I, seeking their feedback and reactions.

Additionally, Statistics Canada conducted a second phase of engagements with various partners with diverse perspectives, including community organizations, academics, police services, police associations and other parties of interest at the national, provincial or territorial, municipal, and local government levels. While seeking feedback on all of the recommendations and planned next steps, these engagements primarily focused on how to operationalize recommendations 1 and 2:

Recommendation 1
The collection of information on the Indigenous and racialized identity of accused persons and victims of crimes through the Uniform Crime Reporting Survey should be conducted through both the "officer perception" method and the "self-identification" method.

Recommendation 2
The collection of information on the Indigenous and racialized identity of accused persons and victims of crimes through the Uniform Crime Reporting Survey should be conducted using Statistics Canada's standardized population group categories for both the "self-identification" method and "officer perception" method.

More specifically, these engagements sought input on

• operational needs, concerns and issues
• guidelines on how to best collect Indigenous and racialized information
• guidelines on when it is appropriate to collect Indigenous and racialized information
• ways to develop the standards and guidelines
• provincial legislation and privacy acts that may affect Indigenous and racialized identity data collection
• the use of data after collection.

Statistics Canada will continue to work with its partners toward the collective goal of providing jurisdictions with guidelines and standards for data collection and analysis, while also acknowledging that jurisdictional nuances and contexts must be considered when adopting a data collection approach. For example, Statistics Canada will work with the policing community and propose variables for the collection of officer perception data with an option to roll up detailed Indigenous and racialized identity categories that will align with existing jurisdictional standards to ensure consistency in reporting.

Launch of the Canadian Association of Chiefs of Police Special Purpose Committee

Recommendation 3
of the September report stipulates:
The Canadian Association of Chiefs of Police should work together with Statistics Canada and other parties of interest to establish national collection standards and guidelines that will integrate with police procedures, processes, and workflow.

To action this recommendation, Statistics Canada and the CACP collaborated to establish the CACP Special Purpose Committee to guide the next steps of the initiative, particularly as they relate to operationalizing the September recommendations and producing guidelines (Operational Guidelines) for police services to implement data collection. Endorsed by the CACP Board of Directors, the special purpose committee (SPC) consists of over 40 members from across different police services of different sizes, and from different regions, and other policing and non-policing CACP representatives. The work of the SPC was supported by five working groups established to bring together experts from across the participating police services and CACP committees. Working group participants had a range of experience and expertise, including front line policing, policing for Indigenous and racialized communities, outreach and engagement, records management systems or technical expertise, standards development, training, research and analysis and working on equity, diversity and inclusion initiatives.

In particular, each of the five working groups addressed a specific aspect of the Operational Guidelines:

• Community Engagement
• Legislative and Regulatory;
• Education and Awareness
• Data Standards; and
• Data Analysis and Dissemination.

Note: The Data Analysis and Dissemination working group was also tasked with developing recommendations and suggestions for the Analytical Framework.

The committee is intended to provide assessments and decisions to develop guidelines for technical and operational changes and implementation, Records Management System (RMS) changes, training, communications, and community engagement. The CACP Special Purpose Committee also has been a key support in the development of guidelines and best practices for the analysis, presentation, interpretation and dissemination of the data. They aided in developing methods for identifying appropriate benchmarks and approaches for properly contextualizing the results of analysis, in order to align with Recommendation 5 from the September report.

Recommendation 5
The analysis and use of information on the Indigenous and racialized identity of accused persons and victims of crimes should be done in a manner that reflects the realities experienced by Indigenous and racialized communities through the inclusion of context in all publications and related dissemination products.

Training Development

Police training is a critical aspect of implementing the enhancements to the UCR Survey. The Education and Awareness Working Group under the CACP Special Purpose Committee, has developed introductory training (hosted on Articulate360) for police services, with emphasis on the purposes of the data collection, as well as how and when the data should be collected.

Three Foundational Reports

Statistics Canada will be publishing three foundational reports throughout Spring/Summer 2025. These reports are: A What we Heard Report on the results of the Phase 2 engagements by StatCan: Planned release date: May 26th, 2025), an Analytical framework promoting the ethical and responsible use, analysis and dissemination of the data (Planned release date: July 16th, 2025); and the Operational guidelines for supporting police services in implementing data collection and reporting through the UCR (Planned release date: July 16th, 2025).

Other activities

In addition to the Phase II engagements and launch of the CACP Special Purpose Committee, other activities completed during this phase include the following:

• UCR system updates at Statistics Canada
  This included technical changes to develop a new version of the UCR Survey (UCR 2.5) that was released in February 2024.^{Footnote 1}
• Continued debriefs and collaboration
  Statistics Canada continues to provide updates to and engage partners. This includes presentations at various conferences and to working groups and various police services boards, as well as ad hoc presentation requests. Further, to align this national initiative with existing jurisdictional priorities, Statistics Canada is communicating and coordinating with various police services and other partners to ensure they can meet both national and jurisdictional or provincial priorities.

Where we are headed

As Phase II of the initiative draws to a close -- with the publication of the three foundational documents  (What We Heard Report, Analytical Framework, and Operational Guidelines) in Summer of 2025, Statistics Canada has now begun work on Phase III. In brief, Phase III (implementation) includes the following established goals:

• support of continued training for police, beginning with the introductory training through the Articulate 360 platform prepared by the Education and Awareness Working Group under the SPC; and
• planning and launch of PIRID (UCR 2.5) pilot projects with first adopters.

More information on pilot Implementation of PIRID Data Collection through the UCR

In the coming months, Statistics Canada aims to lead the implementation of a multi-site pilot project on collecting Police-Reported Indigenous and Racialized Identity Data (PIRID) for accused persons and victims involved in criminal incidents, through the Uniform Crime Reporting (UCR). This pilot project will serve as a springboard for the national rollout of PIRID data collection. By gathering valuable data, taking stock of lessons learned, and refining data collection procedures for both officer perception and self-identification methods, the pilot will help optimize the different components of the PIRID framework and pave the way for scaling the initiative up to the national level.

Additional details on plans and activities related to upcoming phases of the initiative will be shared at a later date.

For information and to remain up to date on the progress of this initiative, please visit Crime and Justice Statistics.

Conclusion

Statistics Canada recognizes that communities across Canada are diverse, and that the collection of police-reported identity information must consider the specific characteristics, existing relationships and contexts of the policing organizations and the communities they serve.

From a national standpoint, this initiative aims to develop evergreen national standards and guidelines for data collection and analysis that build on expertise, established frameworks, lessons learned and best practices. The agency looks forward to continuing to work with police, communities and other parties of interest to enable data collection and analysis of police-reported identity information and finding a balance that results in sound and meaningful data to help shed light on the experiences of Indigenous and racialized communities with police and the criminal justice system.

References

David, J.D., & Mitchell, M. (2021). Contacts with the Police and the Over-representation of Indigenous Peoples in the Canadian Criminal Justice System. Canadian Journal of Criminology and Criminal Justice, 63(2), 23-45.

Millar, P., & Owusu-Bempah, A. (2011). Whitewashing Criminal Justice in Canada: Preventing Research through Data Suppression. Canadian Journal of Law and Society, 26(3), 653-661.

Samuels-Wortley, K. (2021). To Serve and Protect Whom? Using Composite Counter-Storytelling to Explore Black and Indigenous Youth Experiences and Perceptions of the Police in Canada. Crime & Delinquency, 67(8), 1137-1164.

Truth and Reconciliation Commission of Canada. (2015). Calls to Action.

Wortley, S. (1999). A Northern Taboo: Research on Race, Crime, and Criminal Justice in Canada. Canadian Journal of Criminology, 41(2), 261-274.

Appendix A: Recommendations

Based on the feedback received throughout the engagement for the PIRID initiative, the following final recommendations were developed to support the implementation of a national data collection strategy.

Recommendation 1

The collection of information on the Indigenous and racialized identity of accused persons and victims of crimes through the Uniform Crime Reporting Survey should be conducted through both the "officer perception" method and the "self-identification" method.

Recommendation 2

The collection of information on the Indigenous and racialized identity of accused persons and victims of crimes through the Uniform Crime Reporting Survey should be conducted using Statistics Canada's standardized population group categories for both the "self-identification" method and the "officer perception" method.

Recommendation 3

The Canadian Association of Chiefs of Police should work together with Statistics Canada and other parties of interest to establish national collection standards and guidelines that will integrate with police procedures, processes and workflow.

Recommendation 4

Any training delivered by Statistics Canada, or the police community, should emphasize the importance of the data collection initiative and the benefits for the Canadian population, policy makers and the police.

Recommendation 5

In developing or delivering any additional training related to the collection of Indigenous and racialized identity data, police services should consider including components related to systemic racism, the purposes of collecting these data, power differentials, the importance of informed consent without reprisal when collecting self-identification data, cultural competency, sensitivity training, and ongoing training and evaluation to address evolving needs and best practices.

Recommendation 6

Police services should consider how the voices of local community members can be incorporated in the development and implementation of a data collection initiative and related training through meaningful engagement and collaboration throughout the entire process, from initial planning to implementation and evaluation. Community advisory boards or working groups can provide ongoing input and guidance.

Recommendation 7

The analysis and use of information on the Indigenous and racialized identity of accused persons and victims of crimes should be done in a manner that reflects the realities experienced by Indigenous and racialized communities through the inclusion of context (e.g., colonialism, ongoing systemic barriers, the social determinants of health and inequities for Indigenous and racialized peoples, etc.) in all publications and related dissemination products.

Recommendation 8

To ensure consistency, the standards developed in the context of this initiative should be considered for future data collection within the justice and community safety sectors.

Recommendation 9

Police services should develop plans for implementing the standards and guidelines co-developed by Statistics Canada and the Canadian Association of Chiefs of Police in their data collection initiatives or processes, considering their local contexts and the need for flexibility and adaptability. Leveraging technology and data analytics can improve data collection and analysis.

Recommendation 10

The Canadian Association of Chiefs of Police should develop mechanisms that discourage police services from using any part of the self-identification data collection process as a performance metric and recommend systems of reassurance for police service members and the communities they serve. Performance metrics should focus on outcomes and impact, rather than on the quantity of data collected. Consideration should be given to developing a code of ethics for the collection and use of Indigenous and racialized identity data.

Recommendation 11

Statistics Canada should develop guardrails to ensure the responsible use of Indigenous and racialized identity data collected through the Uniform Crime Reporting Survey. Transparency, accountability and a data governance framework should be prioritized to oversee the collection, storage and use of these data.

Recommendation 12

Police services should consider expanding the collection of Indigenous and racialized identity information for specific types of police incidents beyond criminal incidents, such as traffic stops, use of force incidents and calls for service, and for other involved persons, such as persons of interest and subjects of various interactions, to provide a more comprehensive picture of policing interactions.

Release date: September 27, 2017 More Information

The objective of this toolkit is to raise awareness about
data quality assurance practices.

1. Context
2. Quality attributes
3. Data quality assurance practices
4. Checklists

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1. Context

Question: what do you get when you combine "data" and "quality"?

Answer: the Data quality toolkit!

Well, technically, you just get "data quality", but in the context of this webpage you can consider the toolkit something of an extremely useful bonus.

But, talk of bonuses aside, a question remains: what, exactly, is data quality?

To answer this question, we must first answer two more:

• What are data?
• What is quality?

Data are made up of numbers, letters and symbols. When organized into sets, phrases, or patterns, data become information. We use information to identify needs, measure impacts and inform decisions. If the data underlying that information are incorrect in some respect, then our conclusions and decisions could also be wrong or misleading.

Quality is gauged in terms of various attributes discussed in the following section, which will vary depending on from which point of view we are assessing things.

With respect to the data producer, measures of quality include reproducibility of the process, timeliness and punctuality in delivery of data and metadata, willingness and availability to support users of the data and perception of authority and trustworthiness; with respect to the actual data and metadata, quality measures include relevance and usefulness, coverage, granularity, accuracy and reliability, and standardization or conformance.

All of this leads us to data quality, a concept which is shaped by the two just outlined above and which in turn provides two ways to determine whether data are likely to be correct or not:

• describe what was done during the gathering and processing of the data to ensure that the data are correct
• observe measurable characteristics of the data

Following good data quality assurance practices does not guarantee that the data are correct, but it does reduce the likelihood of errors. Completing a data quality assessment is a way of measuring the extent to which the data are protected against errors, and sharing that assessment with data users gives them confidence in the quality of the data.

2. Quality attributes

Quality attributes related to the data producer^{Definition of data producer}

Quality assurance practices^{Examples of quality assurance practices}: The extent to which targeted and documented quality assurance practices were followed in the gathering and processing of the data, both through commitment of the data producer at an organizational level and implementation of monitoring and reporting practices at the working level.

Reproducibility of the process: The extent to which the data production process is reproducible or repeatable. Examples of non-reproducible processes would be ad-hoc processes or instances where intermediate steps or data files were not archived and cannot be recreated.

Timeliness and punctuality: Timeliness refers to the delay between the end of the reference period to which the data pertain, and when they are available to users. Ideally this delay is brief, and the data and metadata should be available at the same time. Punctuality refers to how reliably the data and metadata are available at the expected time, as scheduled or promised by the data producer.

Contactability: The willingness and accessibility of the data producer to discuss the data with potential users, and even to facilitate usage of the data.

Viability: The extent to which one can expect the data producer to continue producing these data for a reasonable length of time into the future.

Perception of authority, impartiality and trustworthiness: The extent to which the data producer is perceived as authoritative on the subject matter of the data, is immune to undue influence of its stakeholders or other external bodies and is worthy of trust.

Security: The extent to which data security is protected in all holdings and transmissions, and access to data during production is restricted to only those with appropriate training and authority. In particular, access is granted on a "need to know" basis.

Quality attributes related to the data and metadata^{Definition of metadata}

Relevance and usefulness: The extent to which the data pertain to the desired phenomenon. Data would be considered less relevant if they are too old, or do not include information about topics of interest. Usefulness of metadata refers to the extent to which it describes the data in terms of methods, concepts, limitations, assumptions made, and quality assurance practices followed.

Coverage: The extent to which the data represent the entire desired phenomenon. This could be assessed in terms of temporal or geographic coverage, or coverage of population units (i.e., people, households, businesses). Coverage is sometimes referred to as completeness (particularly when referring to metadata).

Granularity: Granularity refers to the unit or level of a single record in the dataset. For example a highly granular dataset could contain records of people, medical procedures or lakes, while a less granular dataset could contain records aggregated to the level of a province, or a year. The more granular or local a dataset, the greater the perceived value, balanced by greater need to protect data from unauthorized disclosure. It is usually straight-forward to aggregate or roll-up from granular data to a less granular level, but rolling down from an aggregate level is not usually possible.

Accuracy and reliability: Accuracy refers to the extent to which the data correctly describes the phenomenon they are supposed to measure. Reliability is the extent to which the data are accurate consistently over time. Accuracy is often decomposed into precision, which measures how similar are repeated measurements of the same thing, and bias, which measures any systematic departures from reality in the data. Other factors contributing to accuracy and reliability are validity, the extent to which variables in the dataset have values that correspond to expected outcomes, and consistency, the extent to which the data are free of contradiction.

Standardization or conformance: The extent to which the data and metadata follow recognized standards in terms of formats and naming conventions, and conform to recognized dissemination standards such as SDMX for statistical products. Other aspects of standardization and conformance are the use of industry-standard software and file formats, and controlled vocabulary for data values where appropriate.

Protection of sensitive information: Unless consent has been explicitly given, it is not acceptable to disclose sensitive information in datasets made available to users beyond those granted specific access. Sensitive information includes, but is not limited to, identifiers that would associate granular data to a person, household or business, or sufficient detail in aggregate data such that one could deduce attributes of a person, household or business. There are various methods for protecting data against disclosure of sensitive information, depending on the nature and granularity of the data. Examples include suppression of sensitive information and introduction of random disturbance to data values. Many disclosure control algorithms provide diagnostics of the level of protection achieved.

Combinability or linkability: The extent to which it is possible to integrate two or more sources of data. For example unique identifiers such as social insurance number (SIN), business number, health insurance number can be matched directly, while somewhat unique identifiers such as combinations of name, sex, date of birth, address can be linked using statistical matching algorithms based on probabilities. The success of integrating datasets is improved when the concept of what is represented by a single record from each dataset is well aligned.

Accessibility: The ease with which users can obtain and use the data and metadata. Highly accessible data and metadata have relevant and appropriate labels, keywords and tags so that they are discoverable electronically; are in commonly used formats and software; are downloadable or available through transparent or navigable processes. Accessibility also involves reducing barriers to access, including cost.

Processability and understandability: The ease with which users can manipulate, interpret, explore, analyze, or otherwise use the data and metadata. An important component of this is the extent to which metadata and other support from the data producer lead to correct use of the data, for example through the inclusion of appropriate quality indicators.

Perception of reliability and credibility: The extent to which the data are perceived to be reliable and the metadata are perceived to be credible.

3. Data quality assurance practices

This is a set of good practices that can be followed by any organization producing data. Data producers can adapt these practices to their own environment, and are encouraged to document the data quality assurance practices that they follow and to share that documentation with their data users. Knowing what data quality assurance practices were followed in the production of data builds confidence that the data themselves are of good quality. These quality assurance practices are a subset of those found in Statistics Canada's Quality Assurance Framework and Quality Guidelines.

Data quality assurance practices for producing registers and databases

• Use known unique identifiers (SIN, Business Number, health card number, …), with appropriate protection of sensitive information
• Use check-digits on known unique identifiers to ensure valid values
• Use drop-down menus, look-up tables or reference lists for variables that should have a fixed codeset^{Definition of codeset}
• Use recognized standard formats wherever possible, i.e., ISO 8601 for dates (YYYYMMDD) and time (HH:MM), standard province abbreviations (ON, MB, etc.)
• Include built-in edits to alert when outliers or unexpected entries are made
• Validate aggregated or tabulated data against other sources
• Use a logical, documented naming convention for variables and files
• Document inclusion and exclusion rules, procedures to be followed and quality checks
• Produce output datasets at regular, predictable intervals (the last day of every month, the last day of the year)
• Define and implement a strategy for back-up, storage and retention

Data quality assurance practices for survey data (sample or census)

• Use statistically sound methods for sampling, weighting and estimation
• Ensure all methods are documented and reproducible
• Ensure survey frame is as up to date, complete and as accurate as possible
• Document frame and sample coverage with respect to time period, geographic coverage and population units
• Test questionnaire flow and interpretability
• Choose a collection method appropriate for the target population and the subject matter, given cost considerations and other factors
• Use a quality control technique such as Statistical Process Control^{Definition of Statistical Process Control} to ensure that collected data are accurate
• Make at least one attempt to contact every sampled unit, and track contact attempts
• Use editing resources efficiently and effectively; in other words, make data fit for purpose^{Definition of fit for purpose}, not perfect
• Validate aggregated or tabulated data against other sources

Data quality assurance practices for producing scanned data, satellite data or meter data

• Use a quality control technique such as Acceptance Sampling^{Definition of acceptance sampling} or "ground truthing"^{Definition of ground truthing} to ensure that data are accurate
• Ensure that changes are conveyed to all users e.g., when a new UPC code is introduced for a product

Data quality assurance practices for combining data from different sources

• Ensure that definitions align for: concepts; populations of interest; units of observation; reference periods
• Report all data sources and what contribution they make to the final product
• Analyze non-matching or leftover data to see why they did not match
• Ensure all methods are documented and reproducible

Data quality assurance practices for metadata (documentation)

• Include documentation needs in project planning and resource allocation
• Document as you go; don't leave it all to the end
• Use templates and standard naming conventions
• Describe all concepts: the population covered by the data; any limitations or exceptions in the data; the reference period
• Describe all methods used in sampling, data collection, data entry, editing, combining data from various sources, tabulation
• Describe data security measures
• Describe quality assurance practices followed
• Describe measures to protect against the disclosure of sensitive information
• Provide summary statistics on key variables (mean, median, mode, range, set of valid values)
• Provide a data dictionary or controlled vocabulary set for variables, where appropriate
• Use recognized standard formats wherever possible, i.e., ISO 8601 for dates (YYYYMMDD) and time (HH:MM), standard province abbreviations (ON, MB, etc.)
• Make documentation available to data users
• Use relevant and appropriate labels, keywords and tags so that the data and associated metadata are discoverable electronically
• Track and document updates and revisions

Data quality assurance practices for data security, accessibility and protecting against the disclosure of sensitive information

• In the data production process, restrict access to only those who have appropriate training and authority and a defined need to access the information ("need to know")
• In the data production process, protect security of data in all holdings and all transmissions through encryption and other techniques
• Adopt the "single source of truth" strategy for minimizing duplication of information and effort, in part through efficient database structures
• Use standard formats for names, dates, addresses, and other commonly used variables (international, regional or national standards where appropriate, for example ISO 8601 for dates and time (YYYYMMDD HH:MM using the 24 hour clock)
• Use standard software and file formats for files made available to other users
• Plan and prepare to share datasets at the lowest possible level of granularity (detail)
• Do regular backups
• Define and implement a retention and storage strategy
• Protect against the disclosure of sensitive information (the identity or attributes of any person or business), by masking values^{Definition of masking values} and other techniques

4. Checklists

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Thank-you for reading the toolkit! We want to make it better for you. Please take a moment to let us know which parts of it you find useful, what's missing, how we can make it better. We're also happy to answer your questions. Please send an email to the Statistics Canada Quality Secretariat.

Definition of data producer

The entity responsible for generating, collecting, gathering, processing or manipulating the data, and making it available to others.

Examples of quality assurance practices

Use recognized standards for date and time, such as YYMMDD HH:MM; validate tabulated data against other sources.

Definition of metadata

Metadata are data that describes other data. Metadata summarize basic information about data, making it easier to find and to work with.

Definition of codeset

The set of values that the variable can take on; for example the codeset for a traffic light is red, amber, green.

Definition of Statistical Process Control

A particular type of Quality Control, Statistical Process Control is a way of monitoring the variation in a process and detecting deviations from normal, to be expected variation using control charts.

Definition of fit for purpose

The expression "fit for purpose" or "fit for use" is used to represent the concept of meeting the needs of a client or user of a product, but not exceeding them. An example of a "fit for purpose" commuter vehicle would be a Honda or Mazda, not a Lamborghini.

Definition of Acceptance Sampling

A particular type of Quality Control, acceptance sampling uses statistical sampling to determine whether to accept or reject a production lot of material.

Definition of ground truthing

The process of gathering the proper objective (provable) data as opposed to information provided by inference.

Definition of masking values

Simple methods for protecting against disclosure of sensitive information are rounding, grouping values together or adding random "noise".

More information

Note of appreciation

Canada owes the success of its statistical system to a long-standing partnership between Statistics Canada, the citizens of Canada, its businesses, governments and other institutions. Accurate and timely statistical information could not be produced without their continued co-operation and goodwill.

Standards of service to the public

Statistics Canada is committed to serving its clients in a prompt, reliable and courteous manner. To this end, the Agency has developed standards of service which its employees observe in serving its clients.

Copyright

Published by authority of the Minister responsible for Statistics Canada.

© Her Majesty the Queen in Right of Canada as represented by the Minister of Industry, 2017

All rights reserved. Use of this publication is governed by the Statistics Canada Open Licence Agreement.

Catalogue no. 12-606-X

Frequency: Occasional

Ottawa

Day 1: February 24, 2025 from 8:30am to 4:00pm

Attendance

CSAC Members

Dr. Howard Ramos (Chairperson), Catherine Beaudry, David Chaundy, Benoit Dostie, Annette Hester, Anke Kessler, André Loranger, Vinamra Mathur, Stephen Tapp, Rosemary Bender

Statistics Canada

Josée Bégin, Geoff Bowlby, Kathleen Mitchell, Katy Champagne, Jennifer Withington, Eric Rancourt, Étienne Saint-Pierre

Time	Agenda	Presenter(s)
8:30 – 8:50	Members meet-and-greet	All members
8:50 – 9:00	Chairperson introductory remarks	Howard Ramos Chairperson, CSAC
9:00 – 9:55	Process for defining official statistics at Statistics Sweden	Heather Bergdahl Statistics Sweden
9:55 – 10:15	Break
10:15 – 11:00	Chief Statistician updates and hot files	André Loranger Chief Statistician of Canada
11:00 – 12:00	Data linkages and data transfers at Statcan	Presenters (in order) Julio Rosa, Section Manager, Centre for Special Business Projects Winnie Chan, Chief, Social Analysis and Modelling Division Guests Chris Li, Director, Centre for Special Business Projects Li Xue, Director, Social Analysis and Modelling Division Shelly Jeglic, Assistant Director, Data Access Division
12:00 – 13:00	Working lunch – Discussion on the Terms of Reference
13:00 – 14:00	Advancing the Government of Canada’s Data Landscape	Stephen D. Burt Chief Data Officer of Canada, Data & Digital Policy Sector, Office of the Chief Information Officer, Treasury Board Secretariat
14:00 – 14:45	Update on Censuses	Census of Population Patrice Mathieu Director, Census Operations, Census Program Division Census of Agriculture Erin Kumar Assistant Director, Agriculture Division Guests: Augustine Akuoko-Asibey, Director General, Agriculture, Energy and Environment Statistics Cindy St-Germain, Director, Agriculture
14:45 – 15:05	Break
15:05 – 15:55	Roundtable discussion In camera	All members
15:55 – 16:00	Chairperson closing remarks	Howard Ramos Chairperson, CSAC

Day 1 Summary

1. Chairperson introductory remarks - Howard Ramos

Mr. Ramos opened the meeting by welcoming members and Assistant Chief Statisticians (ACS) and provided an overview of the agenda for the day.

2. Process for defining official statistics at Statistics Sweden – Heather Bergdahl

Ms. Bergdahl presented Statistics Sweden’s framework for defining official statistics, grounded in the Official Statistics Act and Ordinance, which require standardized methods, quality documentation, public access, annual evaluations, and gender-based breakdowns.

She outlined relevant government directives, key quality concepts, and criteria for determining official statistics, and addressed implementation challenges. An open Q&A followed. CSAC members asked about the roles of Statistics Sweden and other authorized organizations, focusing on guidance, oversight, and compliance. Ms. Bergdahl clarified that while exceptions may be granted, data quality remains essential.

3. Chief Statistician updates and hot files – André Loranger

Chief Statistician André Loranger briefed CSAC members on key priorities and challenges, including the agency’s financial position, 2026 Census planning, Canada–U.S. data relations, the role of artificial intelligence, and upcoming initiatives. He concluded by providing a summary of his recent international engagements.

Members asked about Statistics Canada’s authority during government prorogation. Mr. Loranger addressed these questions, reaffirming the agency’s international leadership and the importance of sustaining it through responsible budgeting.

4. Data linkages and data transfers at Statcan – Julio Rosa, Winnie Chan

Mr. Rosa and Ms. Chan presented on Data Linkage and Integration, outlining key drivers and two primary environments: the Business Linkable File Environment (B-LFE) and the Social Data Linkage Environment (SDLE), along with supporting analytical platforms.

CSAC members inquired about interconnections between the environments and recommended considering provincial models. The presenters confirmed ongoing collaboration with provinces and reaffirmed Statistics Canada’s responsibility under the Statistics Act to ensure strong data governance.

5. Working Lunch – CSAC Member Discussion on the Terms of Reference

The Canadian Statistics Advisory Council (CSAC) met to discuss its future composition and structure, including the anticipated departure of three members and potential vacancy in the Chair position in 2025. Members reviewed the current Terms of Reference, considering possible amendments to better reflect the Council’s evolving needs.

6. Advancing the Government of Canada’s Data Landscape – Stephen Burt

Mr. Burt presented Canada’s policy, legislative, and digital landscape, with a focus on the 2023–2026 Data Strategy, including year one achievements and year two priorities.

CSAC members raised questions about short-term challenges and long-term cultural change. Mr. Burt emphasized the need for a more unified approach across departments. The discussion also addressed the role of a national statistical system, the value of data reference standards, and potential legislative adjustments linked to budget and government-wide support.

7. Update on Censuses – Patrice Mathieu and Erin Kumar

Mr. Mathieu and Ms. Kumar provided an update on the Censuses. Topics included the start of operations, communication strategy, reducing respondent burden, and promoting job opportunities. They also outlined the content determination process, with tentative approval expected in May 2025, pending Cabinet approval.

The discussion explored potential automation options, such as notification systems and chatbots. The presenters also shared future strategies, including analysis to support recruitment and data collection.

8. Chairperson closing remarks – Howard Ramos

Mr. Ramos provided closing remarks for the day.

Day 2: February 25, 2025 from 8:50am to 12:30pm

Attendance

CSAC Members

Dr. Howard Ramos (Chairperson), Catherine Beaudry, David Chaundy, Benoit Dostie, Annette Hester, Anke Kessler, André Loranger, Vinamra Mathur, Stephen Tapp, Rosemary Bender

Statistics Canada

Geoff Bowlby, Katy Champagne, Jennifer Withington, Eric Rancourt, Étienne Saint-Pierre

Day 2 Summary

1. Chairperson Opening Remarks – Howard Ramos

Mr. Ramos welcomed members back and provided an overview of the agenda for the day.

2. Introduction to the regulation of UK Official Statistics – Helen Miller-Bakewell and Penny Babb

Ms. Miller-Bakewell, joined by Ms. Babb presented on the regulation of UK official statistics. They outlined the structure of the UK Statistical System, highlighting the role of the Office for Statistics Regulation, and described the 2007 introduction of official statistics and the accreditation process based on the principles of Trustworthiness, Quality, and Value (TQV).

CSAC members asked about the impact of the official statistics framework on public trust and sought clarification on the relationship between the National Statistician and the UK Statistics Authority (UKSA).

3. Using citizen data to report on the Sustainable Development Goals - Cara Williams and Catherine Michaud

Ms. Williams and Ms. Michaud presented the 17 Sustainable Development Goals (SDGs) and potential role of citizen-generated data in addressing current data gaps. They discussed the origins of such data, the role of national statistical offices (NSOs), reporting capabilities, and considerations around data quality.

CSAC members raised questions about data quality evaluation and fit-for-use thresholds and sought further clarity on how Statistics Canada might use this data.

4. Chairperson closing remarks – Howard Ramos

Mr. Ramos thanked CSAC members, including the Chief Statistician, the Assistant Chief Statisticians and their teams and the CSAC Secretariat for their support.

Business or organization information

1. Which of the following categories best describes this business or organization?

• Government agency
• Private sector business
• Non-profit organization
  • Who does this organization primarily serve?
    • Households or individuals
      e.g., child and youth services, community food services, food bank, women's shelter, community housing services, emergency relief services, religious organization, grant and giving services, social advocacy group, arts and recreation group
    • Businesses
      e.g., business association, chamber of commerce, condominium association, environmental support or protection services, group benefit carriers (pensions, health, medical)
• Don't know

Business or organization information

2. In what year was this business or organization first established?

Please provide the year this business or organization first began operations.
Year business or organization was first established:
OR
Don’t know

• Approximately how long ago was this business or organization first established?
  • 2 years ago or less
    Established in 2025, 2024, or 2023.
  • 3 to 10 years ago
    Established in 2015 to 2022.
  • 11 to 20 years ago
    Established in 2005 to 2014.
  • More than 20 years ago
    Established in 2004 or earlier.
  • Don't know

3. Over the last 12 months, which of the following international activities did this business or organization conduct?

Select all that apply.

• Export or sell goods outside of Canada
  Include both intermediate and final goods.
• Export or sell services outside of Canada
  Include services delivered virtually and in person.
  e.g., software, cloud services, legal services, environmental services, architectural services, digital advertising
• Make investments outside of Canada
• Sell goods to businesses or organizations in Canada who then resold them outside of Canada
• Import or buy goods from outside of Canada
  Include both intermediate and final goods.
• Import or buy services from outside of Canada
  Include services received virtually and in person.
  e.g., software, cloud services, legal services, environmental services, architectural services, digital advertising
• Relocate any business or organizational activities or employees from another country into Canada
  Exclude temporary foreign workers.
• Relocate any business or organizational activities or employees from Canada to another country
• Engage in other international business or organizational activities
• OR
• None of the above

4. Over the next three months, how are each of the following expected to change for this business or organization?

Exclude seasonal factors or conditions.

• Number of employees
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Vacant positions
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Sales of goods or services offered by this business or organization
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Selling price of goods or services offered by this business or organization
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Demand for goods or services offered by this business or organization
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Imports of goods or services
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Exports of goods or services
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Operating income
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Operating expenses
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Profitability
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Cash reserves
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Capital expenditures
  e.g., machinery, equipment
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Training expenditures
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Marketing and advertising budget
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know
• Expenditures in research and development
  • Increase
  • Stay about the same
  • Decrease
  • Not applicable
  • Don't know

Business or organization obstacles

5. Over the next three months, which of the following are expected to be obstacles for this business or organization?

Select all that apply.

• Shortage of labour force
• Recruiting skilled employees
• Retaining skilled employees
• Shortage of space or equipment
• Cost of inputs
  An input is an economic resource used in a firm's production process.
  e.g., labour, capital, energy and raw materials
• Costs in real estate, leasing or property taxes
• Inflation
• Interest rates and debt costs
  e.g., borrowing fees, interest payments
• Difficulty acquiring inputs, products or supplies from within Canada
• Difficulty acquiring inputs, products or supplies from abroad
• Maintaining inventory levels
• Insufficient demand for goods or services offered
• Fluctuations in consumer demand
• Attracting new or returning customers
• Lack of financial resources
• Technological limitations
• Regulatory constraints
• Cost of insurance
• Transportation costs
• Obtaining financing
• Increasing competition
• Challenges related to exporting or selling goods and services to customers in other provinces or territories
• Challenges related to exporting or selling goods and services outside of Canada
• Maintaining sufficient cash flow or managing debt
• Attract local investment
• Attract foreign direct investment
• Other obstacle
  • Specify other obstacle:
• OR
• None of the above

Flow condition: If at least two obstacles are selected in Q5, go to Q6. Otherwise, go to Q7.

Display condition: Display in Q6 the obstacles selected in Q5.

6. Of the obstacles selected in the previous question, which obstacle is expected to be the most challenging over the next three months?

• Shortage of labour force
• Recruiting skilled employees
• Retaining skilled employees
• Shortage of space or equipment
• Cost of inputs  
  An input is an economic resource used in a firm's production process.
  e.g., labour, capital, energy and raw materials
• Costs in real estate, leasing or property taxes
• Inflation
• Interest rates and debt costs
  e.g., borrowing fees, interest payments
• Difficulty acquiring inputs, products or supplies from within Canada
• Difficulty acquiring inputs, products or supplies from abroad
• Maintaining inventory levels
• Insufficient demand for goods or services offered
• Fluctuations in consumer demand
• Attracting new or returning customers
• Lack of financial resources
• Technological limitations
• Regulatory constraints
• Cost of insurance
• Transportation costs
• Obtaining financing
• Increasing competition
• Challenges related to exporting or selling goods and services to customers in other provinces or territories
• Challenges related to exporting or selling goods and services outside of Canada
• Maintaining sufficient cash flow or managing debt
• Attract local investment
• Attract foreign direct investment
• Other obstacle

Flow condition: If “Cost of inputs” is selected in Q5, go to Q7. Otherwise, go to Q8.

7. Over the next three months, which of the following costs of inputs are expected to be obstacles for this business or organization?

Select all that apply.

• Cost of labour
• Cost of capital
• Cost of energy
• Cost of raw materials
• OR
• Don't know

Flow condition: If “Difficulty acquiring inputs, products or supplies from within Canada”, “Difficulty acquiring inputs, products or supplies from abroad”, or “Maintaining inventory levels” is selected in Q5, go to Q8. Otherwise, go to Q11. 
Display condition: If “Difficulty acquiring inputs, products or supplies from within Canada”, “Difficulty acquiring inputs, products or supplies from abroad”, or “Maintaining inventory levels” is selected in Q5, display in Q8. 

Supply chain challenges

8. How long does this business or organization expect the following to continue to be an obstacle?

• Difficulty acquiring inputs, products or supplies from within Canada
  • Less than 3 months
  • 3 months to less than 6 months
  • 6 months to less than 12 months
  • 12 months or more
  • Don't know
• Difficulty acquiring inputs, products or supplies from abroad
  • Less than 3 months
  • 3 months to less than 6 months
  • 6 months to less than 12 months
  • 12 months or more
  • Don't know
• Maintaining inventory levels
  • Less than 3 months
  • 3 months to less than 6 months
  • 6 months to less than 12 months
  • 12 months or more
  • Don't know

 9. Over the last three months, how have supply chain challenges experienced by this business or organization changed?

Supply chain challenges include difficulty acquiring inputs, products or supplies from within Canada or abroad and difficulty maintaining inventory levels.

Exclude seasonal factors or conditions

• Supply chain challenges have worsened
  • Which of the following factors have contributed to these challenges?
    Select all that apply.
    • Increased prices of inputs, products or supplies
    • Increased delays in deliveries of inputs, products or supplies
    • Supply shortages resulted in fewer inputs, products or supplies being available
    • Supply shortages resulted in no inputs, products or supplies available
    • Other factor
      • Specify other factor:
    • OR
    • Don't know
• Supply chain challenges have remained about the same
• Supply chain challenges have improved

10. Over the next three months, how does this business or organization expect supply chain challenges to change?

Supply chain challenges include difficulty acquiring inputs, products or supplies from within Canada or abroad and difficulty maintaining inventory levels.
Exclude seasonal factors or conditions.

• Supply chain challenges are expected to worsen
• Supply chain challenges are expected to remain about the same
• Supply chain challenges are expected to improve

Flow condition: If “Government agency” was selected in Q1, go to Q12. Otherwise, go to Q11.
Display condition: If “Non-profit organization” is selected in Q1, do not display “Transfer the business” or “Sell the business” in Q11.

Expectations for the next year

11. Over the next 12 months, does this business or organization plan to do any of the following? 

Select all that apply.

• Expand current location of this business or organization
• Expand operations of this business or organization internationally
• Expand operations of this business or organization into a new province or territory within Canada
• Move operations of this business or organization to another location within the province or territory
• Move operations of this business or organization to another province or territory within Canada entirely
• Expand this business or organization to other locations within the same province or territory
• Expand this business or organization without increasing physical space
  i.e., hiring more staff who will work remotely, or expanding online sales capacity
• Restructure this business or organization
  Restructuring involves changing the financial, operational, legal or other structures of the business or organization to make it more efficient or more profitable.
• Acquire other businesses, organizations or franchises
• Invest in other businesses or organizations
• Merge with other businesses or organizations
• Reduce the physical space of this business or organization
• Scale down operations of this business or organization to within a single province or territory within Canada
• Transfer the business
• Sell the business
• OR
• Close the business or organization
• OR
• Don't know
• OR
• None of the above

Flow condition: If “Export or sell goods outside of Canada” or “Export or sell services outside of Canada” was selected in Q3, go to Q12. Otherwise, go to Q13.

Trade

12. Over the last 12 months, what percentage of this business’ or organization’s sales were made directly to clients or customers in the United States?

Provide your best estimate rounded to the nearest percentage.

Percentage of sales made directly to clients or customers in the United States:
OR
Don’t know

Flow condition: If “Import or buy goods from outside of Canada” or “Import or buy services from outside of Canada” was selected in Q3, go to Q13. Otherwise, go to Q14. 

13. Over the last 12 months, what percentage of this business’ or organization’s purchases were made directly from suppliers in the United States?

Provide your best estimate rounded to the nearest percentage.

Percentage of purchases made directly from suppliers in the United States:
OR
Don’t know

14. What is the impact of the following on this business or organization?

• U.S. tariffs on goods sold by businesses in Canada
  • High negative impact
  • Minor negative impact
  • No impact
  • Minor positive impact
  • Major positive impact
  • Don’t know
• Canadian tariffs on goods sold by businesses in Canada
  • High negative impact
  • Minor negative impact
  • No impact
  • Minor positive impact
  • Major positive impact
  • Don’t know
• The elimination of trade barriers between provinces or territories
  • High negative impact
  • Minor negative impact
  • No impact
  • Minor positive impact
  • Major positive impact
  • Don’t know

15. Over the next 12 months, does this business or organization plan to take any of the following actions as a result of any tariffs applied by the United States on goods sold from Canada?

Select all that apply.

• Seek alternative customers outside the United States 
• Seek alternative suppliers outside the United States
• Increase domestic sourcing
• Delay major investments or expenditures
• Delay Canadian investment or expansion plans
• Acquire or partner with United States-based businesses as a beachhead strategy
• Explore trade-related financial tools
  e.g., currency hedging, insurance
• Establish operations in the United States
• Increase inventory or stockpiled goods
• Invest in technology improvements 
  e.g., technology adoption, automation
• Lay off employees
• Hire employees
• Raise prices of goods or services
• Lower prices of goods or services
• Other action
  • Specify other action:
• OR
• None of the above
• OR
• Don’t know

United States administration

16. Over the next 12 months, how is this business or organization expected to be impacted for each of the following as a result of the new United States administration? 

• Business uncertainty
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Sales in Canada
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Sales to the United States
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Sales to other countries excluding the United States
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Cost of domestic material inputs    
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Cost of imported material inputs     
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Cost of domestic service inputs
  e.g., lawyer fees, accountant fees, IT support, transportation costs 
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Cost of imported service inputs
  e.g., lawyer fees, accountant fees, IT support, transportation costs
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know
• Selling price of goods or services offered by this business or organization
  • Higher
  • Unchanged
  • Lower
  • Not applicable
  • Don’t know

Flow condition: If the percentage of sales made directly to clients or customers in the United States reported in Q12 was greater than 0, go to Q17. Otherwise, go to Q18.

17. Over the last three months, has the United States imposed any tariffs specifically on any goods that this business or organization sells to the United States?

• Yes
• No 
• Don’t know

Flow condition: If the percentage of purchases made directly from suppliers in the United States reported in Q13 was greater than 0, go to Q18. Otherwise, go to Q19.

18. Over the last three months, has Canada imposed any tariffs on any goods that this business or organization specifically purchases from the United States?

• Yes
• No 
• Don’t know

19. If tariffs imposed by the United States and Canada remained at their current level, for how long would this business or organization be able to continue to operate?

• Less than 3 months
• 3 months to less than 6 months
• 6 months to less than 12 months
• 12 months or more
• Don’t know

20. If tariffs imposed by the United States and Canada remained at their current level, for how long would this business or organization be able to maintain their current level of staffing?

• Less than 3 months
• 3 months to less than 6 months
• 6 months to less than 12 months
• 12 months or more
• Don’t know

21. Over the last six months, has this business or organization experienced negative consequences because of the direct impact of tariffs on other businesses in the community? 

• Yes
  • What negative consequences did this business or organization experience?
    Select all that apply.
    • Other businesses had to raise their prices
    • Lower sales to business customers
    • Lower sales to individual customers
    • Had to lay off staff
    • Had to temporarily close business
    • Unable to acquire inputs from the other business
    • Other consequence
      • Specify other consequences:
    • OR
    • Don't know
• No
• Don’t know

22. Over the last six months, has this business or organization passed on any increases in its costs due to tariffs to its customers?

• Yes
• No
• This business or organization has not experienced any cost increases due to tariffs
• Don’t know

23. Over the next 12 months, how likely is this business or organization to pass on cost increases due to tariffs to its customers?

Include increases in costs related to inputs, products, or supplies.

• Very likely
• Somewhat likely
• Somewhat unlikely
• Very unlikely
• This business or organization does not expect any cost increases due to tariffs
• Don't know

Canada-United States-Mexico Agreement (CUSMA)

Flow condition: If the percentage of sales made directly to clients or customers in the United States reported in Q12 was greater than 0, go to Q24. Otherwise, go to Q25.

24. Over the last 12 months, were any of the goods sold by this business or organization to the United States compliant with the Canada-United States-Mexico Agreement (CUSMA)?

• Yes
  • What percentage of the goods sold by this business or organization to the United States were compliant with CUSMA?
    Provide your best estimate rounded to the nearest percentage.
    Percentage of goods this business or organization sold to the United States that were compliant with CUSMA:
    OR
    Don't know
• No
• This business or organization does not sell goods to the United States
• Don’t know

Flow condition: If the percentage of purchases made directly from suppliers in the United States reported in Q13 was greater than 0, go to Q25. Otherwise, go to Q26.

25. Over the last 12 months, were any of the goods purchased by this business or organization from the United States compliant with the Canada-United States-Mexico Agreement (CUSMA)?

• Yes
  • What percentage of goods purchased by this business or organization from the United States were compliant with CUSMA?
    Provide your best estimate rounded to the nearest percentage.
    Percentage of goods purchased by this business or organization from the United States that were compliant with CUSMA:
    OR
    Don't know
• No
• This business or organization does not purchase goods from the United States 
• Don’t know

Flow condition: If “No” was selected in both Q24 and Q25, go to Q26. Otherwise, go to Q27.

26. Has this business or organization arranged for the certification under CUSMA of any goods it purchases from or sells to the United States?

• Yes
• No
  • Why not?
    Select all that apply.
    • Too costly or complex to meet the requirements
    • Lack of information or support
    • Products contain too much foreign content
    • Other reason
      • Specify other reason:
    • OR
    • Don't know
• Don’t know

Canadian products

27. Over the last six months, has this business or organization changed its marketing practices to promote Canadian products?

e.g., labeling products that are either “Canadian”, “Made in Canada” or are a “Product of Canada”

• Yes
• No 
• Don’t know

28. Over the last six months, has this business or organization experienced an increase in sales of Canadian products?

e.g., products that are either “Canadian”, “Made in Canada” or are a “Product of Canada”

• Yes
• No 
• Don’t know

Change in suppliers

29. Over the last three months, did this business or organization change suppliers as a result of tariffs imposed by either Canada or the United States?

• Yes
• No 
• Don’t know

30. How challenging would it be for this business or organization to switch the main suppliers of its inputs, products or supplies, while minimizing impacts on customers or operations? 

• Very easy
• Somewhat easy
• Somewhat difficult
• Very difficult
• Don’t know

Question 31 was skipped for all respondents.

Artificial intelligence (AI)

32. Over the next 12 months, does this business or organization plan to use artificial intelligence (AI) in producing goods or delivering services?

e.g., machine learning, virtual agents, voice recognition

• Yes
  • What types of AI applications is this business or organization planning to use in producing goods or delivering services?
    Select all that apply.
    • Machine learning
    • Natural language processing
    • Virtual agents or chat bots
    • Speech or voice recognition using AI 
    • Recommendation systems based on AI 
    • Large language models
    • Text analytics using AI 
    • Data analytics using AI 
    • Neural networks
    • Augmented reality
    • Decision making systems based on AI 
    • Deep learning
    • Image or pattern recognition
    • Machine or computer vision
    • Robotics process automation
    • Biometrics
    • Marketing automation using AI 
    • Other type
      • Specify other type:     
    • OR
    • Don't know

• No
  • Why does this business or organization not plan to use AI in producing goods or delivering services over the next 12 months?
    Select all that apply.
    • Too expensive
    • AI is not a mature enough technology yet
    • Lack of knowledge on the capabilities of AI
    • Concerns about privacy or security
    • Concerns about bias 
    • Lack of skilled workforce 
    • Lack of required data 
    • Laws and regulations prevent or restrict use of AI 
    • Previous or current use of AI did not meet expectations 
    • Other reason
      • Specify other reason:
    • OR
    • AI is not relevant to the goods produced or services delivered by this business or organization
    • OR
    • Don't know
• Don't know

Flow condition: If “Yes” was selected in Q32, go to Q33. Otherwise, go to Q35.

33. How does this business or organization expect AI to affect total employment?

• Increase
• Decrease
• No change
• Don’t know

34. Which of the following changes will this business or organization make when using AI to produce goods or deliver services?

Select all that apply.

• Train current staff to use AI
• Hire staff trained in AI
• Purchase computing power or specialized equipment
• Purchase cloud services or cloud storage
• Change data collection or data management practices
• Develop new workflows
• Use vendors or consulting services to install or integrate AI
• Other change
  • Specify other change:
• OR
• Don't know
• OR
• None of the above

Liquidity

35. Does this business or organization have the cash or liquid assets required to operate for the next three months? 

• Yes
• No
  • Will this business or organization be able to acquire the cash or liquid assets required?
    • Yes
    • No
    • Don't know
• Don’t know

Debt

36. Over the next three months, does this business or organization plan to apply to a financial institution for a new line of credit, a new term loan, a new non-residential mortgage, or refinancing of an existing non-residential mortgage?

Include commercial mortgages.
Exclude residential mortgages.

• Yes
  • What are the intended uses of this funding?
    Select all that apply.
    • Refinancing of existing debt
    • Non-residential investments
      i.e., machinery, equipment, R&D
    • Current expenditure
    • Business expansion
    • Financing the acquisition of another business
    • Other use
      • Specify other use:
    • OR
    • Don't know

• No
  • Does this business or organization have the ability to take on more debt?
    Answer based on this business' or organization's ability, even if there are no plans to take on more debt.
    • Yes
    • No
      • For which of the following reasons is this business or organization unable to take on more debt?
        Select all that apply.
        • Cash flow
        • Lack of confidence or uncertainty in future sales
        • Request would be turned down
        • Too difficult or time consuming to apply
        • Interest rates are unfavourable
        • Payment terms are unfavourable
        • Credit rating
        • Other reason
          • Specify other reason:
        • OR
        • Not applicable
        • OR
        • Don't know
    • Don't know
• Don't know

Flow condition: If “Yes” was selected when asked if the business of organization plans to apply to a financial institution for a new line of credit, a new term loan, a new non-residential mortgage, or refinancing of an existing non-residential mortgage in Q36, go to Q37. Otherwise, go to Q38.

37. Who will provide the debt financing this business or organization plans to request?

Select all that apply.

• Private financial institution 
  e.g., chartered banks
• Government agency
• Private markets
• Other source
  • Specify other source:    
• OR
• Don't know

Payments

38. Over the next three months, how confident is this business or organization in its ability to make its payments to suppliers and service providers in full and on time?

Exclude payments made to financial institutions.

• Very confident 
• Somewhat confident 
• Not at all confident
• Don't know

Working arrangements

39. Over the next three months, what percentage of the employees of this business or organization is anticipated to work on-site or work remotely?

Exclude employees that are primarily engaged in providing driving or delivery services or employees that primarily work at client premises, and contractors.

Working on-site refers to working from an office or job site, while working remotely refers to an employee working from home or another location of the employee’s choosing, other than their regular on-site location.

Provide your best estimate rounded to the nearest percentage.
If the percentages are unknown, leave the question blank.

a. Work on-site exclusively 
Percentage of employees:
b. Work on-site most hours 
Percentage of employees:
c.  Work approximately the same number of hours on-site and remotely 
i.e., 2 to 3 days per week on site        
Percentage of employees:
d. Work remotely most hours
Percentage of employees:
e. Work remotely exclusively 
Percentage of employees:

Future outlook

40. Over the next 12 months, what is the future outlook for this business or organization? 

• Very optimistic
• Somewhat optimistic
• Somewhat pessimistic
• Very pessimistic
• Don’t know

Flow condition: If “Private sector business” was selected in Q1, go to Q41. Otherwise, go to “Contact Person”.

Ownership

(i) The groups identified within the following questions are included in order to gain a better understanding of businesses owned by members of various communities across Canada. 

41. What percentage of this business or organization is owned by each of the following groups?

Provide your best estimate rounded to the nearest percentage.

If the business or organization is not owned by anyone that falls under that group, please enter “0”.

What percentage of this business or organization is owned by women?
Percentage of business or organization owned by women:
OR
Don’t know

What percentage of this business or organization is owned by First Nations, Métis or Inuit peoples?
Percentage of business or organization owned by First Nations, Métis or Inuit peoples:
OR
Don’t know

What percentage of this business or organization is owned by immigrants to Canada?
Percentage of business or organization owned by immigrants to Canada:
OR
Don’t know

What percentage of this business or organization is owned by persons with a disability?
Percentage of business or organization owned by persons with a disability:
OR
Don’t know

What percentage of this business or organization is owned by lesbian, gay, bisexual, transgender, queer, or two-spirited (LGBTQ2) people?
Percentage of business or organization owned by LGBTQ2 people:
OR
Don’t know

What percentage of this business or organization is owned by members of visible minorities?
A member of a visible minority in Canada may be defined as someone (other than an Indigenous person) who is non-white in colour or race, regardless of place of birth.
Percentage of business or organization owned by visible minorities:
OR
Don’t know

Flow condition: If more than 50% of this business or organization is owned by members of visible minorities, go to Q42. Otherwise, go to “Contact person”.

42. It was indicated that at least 51% of this business or organization is owned by members of visible minorities. Please select the categories that describe the owner or owners.

Select all that apply.

• South Asian 
  e.g., East Indian, Pakistani, Sri Lankan
• Chinese
• Black
• Filipino
• Latin American
• Arab
• Southeast Asian 
  e.g., Vietnamese, Cambodian, Laotian, Thai
• West Asian 
• e.g., Afghan, Iranian
• Korean
• Japanese
• Other group
  • Specify other group:
• OR
• Prefer not to say

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