Is Your Nonprofit's Data Biased?
Updated: Jun 2
Your data may not be as objective as you think.
Program impact, wealth scores, digital profiles, funding interests & demographics. Data is everywhere and, all too often, nonprofits are leaving this invaluable resource on the table. While I trust our sector understands the inherent value of using data to inform our strategies, nonprofits rarely have the capacity or capital to prioritize data, let alone the time to deconstruct or investigate it. As public data brokerage firms continue to increase in popularity, nonprofits must not only continue to incorporate data overlays into their fundraising strategies but also must remain vigilant in our inquiry of its sources.
To expand, nonprofits must be critical of the data they purchase and generate. Before an organization begins to leverage donor data in order to raise more money, demonstrate impact in a grant report, or build out the organization's strategic plans, we need to investigate where it comes from and the bias that may be written into its collection methodology. Here's an example.
I remember it like it was yesterday. I was working at the Ms. Foundation as their Senior Manager of Donor Data. The Ms. Foundation is an incredible organization committed to the issues of equity and justice. We had been funded by the Ford Foundation to diversify our donor base and I couldn't have been more thrilled. My predecessor had worked with a vendor to purchase demographic data about our constituents including race, gender, age etc. He had appended this data to our donor records and we were tracking our metrics year-over-year. I joined staff in the third, and final, year of this grant. I inherited the vendor and began to go through the motions to conduct our third, and final, overlay. Simple right?
Knowing many of our donors personally, I was concerned by the number of incorrect values that were being returned. (By the way, don't even get me started on the limitations of categorizing human characteristics but I will leave that to a future post). I reached out to our vendor and shared my concerns. I inquired about how they determined their race and ethnicity values. Their answer shocked me. They told me that their values are rarely self-reported and, more often than not, relied on an algorithm that referenced the racial majority of the donors' zip code and the ethnic origin of their last name. Of course, this methodology is grossly problematic and was seething with bias; ultimately resulting in inaccurate data.
"At first glance, it seemed as though we were doing the right thing but how could we make progress if the very data that we were using had bias built right into its collection methodology?
At first glance, it seemed as though we were doing the right thing. We identified that our constituency was mostly White, understood the value of adjusting our fundraising strategy to acquire more donors of color, secured funding to operationalize our efforts, and sought to track our progress over time. But how could we make progress if the very data that we were using had bias built right into it? It was then that I realized that data, something that on the surface may seem objective, can be laden with bias and human influence. I was determined to do better.
For those who are hungry to learn more about this issue, I'd like to share a resource that I have found incredibly valuable. I recently had the opportunity to attend the Foundations of Data Equity course hosted by Heather Krause, CEO of We All Count, a project for equity within data science.
The Foundations of Data Equity workshop was exactly what I had been searching for. An all-day workshop, Heather spends the time carefully explaining how bias can be hidden in all stages of the data collection process from the initial funding to the distribution of the final results. I left with practical tools, checklists, and resources built into a comprehensive system for changing the way I work with data from beginning to end.
By the end of the day I was able to:
Use a seven-step data equity framework to surface bias, racism, homophobia, sexism, and more in my data products.
Take practical steps to embed equity, accessibility, and fairness into my data products.
Determine the difference between results and interpretation.
Facilitate a conversation between my data team and my non-technical stakeholders about what it means to embed equity in our data products.
Curious to learn more, I spoke to Heather after attending this workshop and asked her how she got into doing this work. She told me that, "Bias in data science permeates our systems. It’s hidden in every step of the process; data collection, analysis, communication, and visualization are rife with inequality-causing assumptions, misunderstandings, blind spots, shortcuts, and outright errors."
Heather goes onto say, "This workshop emerged out of a growing sense of awareness of the racism, sexism and other bias problems hidden deeply within data without an accompanying set of tools to move from being aware of bias to actually successfully working to reduce and repair it. It can be very overwhelming at first and many people want to get moving. to improve the way their organization works with data but don't know where or how to start. The We All Count Data Equity Framework and accompanying workshops aims to provide a grounded, robust set of steps to applying the concepts. We're excited to see them getting used from boardrooms to front porches."
We all Count is a total gamechanger. Few people intentionally use data to make racist, or sexist, or unethical decisions. However, it’s very easy to do so accidentally. This has serious consequences for communities, policies, individuals, and organizations. From regular citizens to decision-makers, to CEOs, to fundraisers, we all need a toolkit for embedding equity and ethics on our data products. If you agree, click here to attend their next session! PS- stay tuned for an upcoming guest blog post from Heather. She has generously offered to create special content just for julianacfre.com Thanks, Heather!
Juliana M. Weissbein, CFRE is a respected leader and decision influencer in regard to fundraising operations best practices. With over a decade of experience, Juliana thrives on professional growth, team success, measurable results, and inspiring fundraisers to utilize data-based strategies. Juliana currently serves as the Associate Director of Development Operations at Planned Parenthood Federation of America. She is AFP Global's 2019 Outstanding Young Professional Fundraiser and is a member of the AFP Global Women's Impact Initiative. Juliana is immediate past chair of the AFP New York City chapter’s Emerging Leaders Committee and currently serves on the chapter’s board chairing their mentorship program. She resides in Brooklyn, NY and never turns down a good kombucha.