Mind Blowing, Powerful, Deficient: Scoping Philanthropic Grantmaking Data in Canada

This blog provides a short overview of the 2024 MPNL Capstone Project for Philanthropic Foundations Canada. For the full report or to connect with the researchers please contact Dr. Michele Fugiel Gartner.

Anna Hamilton, Jing Jia, Michelle Murphy, and Tara Russell

Overview

A critical gap exists in the collection, interpretation, and use of philanthropic grantmaking data in Canada. Undoubtedly, philanthropic actors are interested in altering the strategy behind their investments, spurring the desire to enhance knowledge of what types of charitable activities are being funded (what), the demographic of organizations being supported (who), and the locale (where). Improving data access, interpretation, and available tools could dramatically improve functionality, equity, and wellbeing within the sector.ⁱⁱⁱⁱⁱⁱ

Over the last three months, our research team – consisting of four graduate students at Carleton University – has been diving into the landscape of philanthropic data production in Canada. This research stemmed from the proposal by Philanthropic Foundations Canada for a project which would consider the scope of grantmaking data in Canada. Our work picks up following the “2024 Landscape Report,” (PFC) which outlined the current landscape of nonprofit practices. Our report seeks to answer one question: What are the challenges with accessing and interpreting philanthropic data in Canada as it pertains to grantmaking data?

Our research group conducted 12 interviews with intermediaries, foundations, academic institutions, and consultancies, and reviewed both grey and academic literature to try and answer this question. The literature revealed themes around data accessibility, quality, interpretation challenges, workarounds, limited primary data sources, collaboration, and international practices. Interview findings confirmed similar themes, highlighting Canada’s Revenue Agency’s T3010 as the sector’s primary data source, the challenges in data quality management, and the gaps in the nonprofit data sector. With these themes in mind, our report tries to scope the challenges, rather than answer them.

Two Key Findings

Amongst both the literature and through our interviews, two main data challenges arose: first, data quality, and second, data gaps.

The CRA’s T3010 Form

The Canada Revenue Agency (CRA), through the T3010 form, is the primary producer of grantmaking data, collecting and disseminating most of the charitable sector’s data in Canada. The T3010 data is used to understand the sector, inform strategic decision making, and attempt to inform and understand the impact of policy changes. The T3010’s primary purpose is not for informing decisions-making nor for improving strategic decisions, but for regulatory purposes.

Challenges resulting from the T3010 data include:

poor data quality

the exclusion of nonprofits from data collection

inconsistencies from filing errors

inability to categorize funding destinations

delayed release within the T3010 data

These data challenges, listed above, make it challenging to use and inform strategic decision making.

Statistics Canada

The second main area of grantmaking data production happens at Statistics Canada (StatsCan). StatsCan collects and disseminates significant amounts of data on most Canadian economic sectors; StatsCan has had a notable lack of focus on the charitable sector.^iv The disjointed areas span different surveys, including but not limited to:

Satellite Account of Nonprofit Institutions and Volunteering

Summary of Charitable Donors

Survey on Giving, Volunteering and Participating (SGVP)

National Insights into Non-profit Organizations, Canadian Survey on Business Conditions.

Notably, the Satellite Account of Nonprofit Institutions and Volunteering, was discontinued in 2010, and recently restarted in 2019. This hiatus has led to furthering data gaps, leading sector researchers to piece together information from other publications of Statistics Canada.^v

The main challenges pertaining to data quality are created through the ways in which data is collected, generally caused by transcription errors, the structure of the T3010 form, and filing errors. These combined challenges lead to the overall poor quality of data collected. Additionally, there are significant data gaps within the data landscape. The CRA plays a significant role in contributing to these gaps, because they do not collect data from nonprofits, and the T3010 form fails to provide detailed information about long term investments, leadership demographics, programmatic details, or categorization of funds given to other charities.

  “[Filers] just report the wrong information. They put the wrong number in, they interpret the question incorrectly” (P2

“CRA is the most comprehensive source of data and they do not have a mandate to disseminate that data.“ (P11).

The data sources themselves are challenging to access, and their inconsistencies and quality issues make them even more difficult to interpret. Third party processors such as Charity Data, or Imagine Canada’s Grant Connect were mentioned as better access points for the everyday person who wanted to catch a glimpse at financial or other information on charities in Canada. Third-party processors undertake significant work to add information from other sources, to compensate for the quality and lack of data, in order to enrich sector understanding.

One participant noted “it would be exceptionally challenging” if their organization did not have a staff person with the skill set to interpret and analyze data, because it would force them to “use just like the web-based tables which are really just clunky and not user friendly”

Overall, using the T3010 data to identify trends in philanthropic funding, evaluate policy impacts, or address sector-wide issues like equity and diversity is complex and resource-intensive. Interviewees highlighted the significant effort required to clean, organize, and manipulate the data to make it usable for research or strategic purposes. This heavy reliance on resources helps us to raise important questions about who should ultimately bear responsibility for ensuring accessible and actionable sector data.

The interviews conducted by our team made it clear – people and organizations crave the ability to make more effective and strategic grantmaking decisions.

Organizations desire to have better quality and consistent data; some even use publicly available data (T3010) and individually create improved and usable grantmaking data to inform their own granting strategies.

Examples include a report published by Environment Funders Canada, the Definity Foundation Report, and the Unfunded report, all which highlight the efforts and investment made into understanding trends and challenges within the narrow scope of an individual organization.

In these cases, the data is used and interpreted for specific causes rather than improving data quality for the sector as a whole. These reports also come with many caveats due to the challenges associated with the T3010 and StatsCan data on the sector.

Despite the investment needed, interviewees recognize the importance of data for strategic decision making. For example, sector data should inform decisions around philanthropic funding choices, or sector level policy decisions to improve the strategic nature and efficacy of grantmaking. Understanding grantmaking funding flows specifically to improve equity factors would provide insights into equity in funding distribution and identify areas requiring additional support.

Additionally, many of the data management workarounds utilized by individual organizations require financial capacity, meaning data usage is becoming an equity issue. Interviewees noted the inability of the available data inhibits the ability to interrogate and interpret the impact of funding choices on justice, equity, and diversity, thus creating a ‘blind spot’ in sector data.

Participants also referenced the disbursement quota as a key example of the failings of the current data in its ability to inform policy decisions and enable tracking of the impact of policy decisions. The data limitations prevent a full understanding of the impact of these changes to foundations.^vi

Moving Forward

Our project has been a scoping exercise – seeking to capture a snapshot of how accessing and interpreting philanthropic grantmaking data is affecting the sector today and identify areas for further exploration – and in this instance, we were successful. Over the course of the project, the team noted some areas of particular interest for future investigation.

Provincial Roles in Data Production

The role of provincial and territorial governments in data production has often been overlooked in discussions about sector data. Three participants noted that because nonprofits are excluded in the criteria for data collected by the CRA there is an opportunity for data collection at the provincial level in order to include these left-out organizations. While the exclusion of nonprofits in sector wide data collection discussions is raised repeatedly in the literature, alongside other data deficiencies, the attention and focus appear to target the federal level of government, rather than provincial.^vii These observations suggest that provincial roles in sector level data production and management may deserve further attention.

Explore International Jurisdictions as Models

Interview participants’ responses had limited input or interest in the data practices of other jurisdictions. One participant said it best when dealing with data in this field – “what you have to do is go out there and construct it.” This reflects the transformative potential of a unified, strategic approach to grantmaking data, where equity, collaboration and impact fuel its core. Collaboration emerged as a key theme in both interviews and literature, alongside a strong desire for better data to guide decision-making.

International examples, such as the USA’s Environmental Grantmakers Association’s Tracking the Field Project and the UK’s 360Giving initiative, demonstrate how justice, equity, and inclusion concerns have driven improvements in data collection and accessibility.^viii^ix Notably, 360Giving’s voluntary data standard arose from sector-wide demand for actionable data to inform strategic funding and policy decisions—mirroring similar desires within Canada. These examples of collaboration and innovation highlight opportunities for Canada to explore data production, standards, and sharing to strengthen its philanthropic sector.

Machine Learning

Notably, only one interviewee spoke about artificial intelligence (AI) or machine learning tools as an avenue to reduce the burden on the sector when it comes to managing and working with data. Given the attention that machine learning, AI, and language models are receiving globally, it was surprising that AI support was not raised by interviewees or in the literature as an option to reduce the workload in managing, cleaning, or interpreting sector data.

Conclusion

Participants expressed optimism about the sector’s capacity to innovate, emphasizing that progress lies not only in collecting more data, but in utilizing existing resources and fostering collaboration. Future research avenues in this area are abundant. The challenges of data collection, access, and interpretation are present at various scales, from macro- to meso- and micro-levels. However, utilizing data at each of these levels will provide a deeper understanding of targeted interventions.

The CRA’s T3010 data limitations pose challenges for stakeholders. These challenges are notable and emphasize the need for systemic improvements in how data is collected, managed, and utilized in the philanthropic sector.

Participants offered recommendations for improving access and interpretation of data. These include mandatory electronic filing of the T3010, the establishment of a nonprofit data unit at Statistics Canada, timelier release of data, and improved tracking of funding flows. These recommendations align with the broader demand for collaboration and innovation within the sector, which is prevalent in both international and provincial practices.

Accessible and quality grantmaking data is essential to the philanthropic grantmaking capacity to make informed decisions and drive equity-focused initiatives. As one participant noted “if you want to make big differences in this area, what you have to do is go out there and construct it.” This reflects the transformative potential of a unified, strategic approach to grantmaking data, where equity, collaboration and impact fuel its core.