The Ethical Rainmaker

Decolonizing Data w Anna Rebecca Lopez and Vu Le

Episode Summary

“...the processes we’ve used in evaluation are perpetuating a lot of the harms we thought we were helping with…” “we’re all using data problematically!” In this season finale, host Michelle Shireen Muri talks with Anna Rebecca Lopez and Vu Le about how the traditional ways that data has been collected and used can be harmful - causing misrepresentation, oppression and erasure. Anna Rebecca shares her personal journey with deep academic cred as a data nerd and disruptor and the three talk about what questions we must ask to truly center our communities.

Episode Notes

Data can make a significant difference in addressing community needs and tracking progress towards a goal, but it can also be a tool of oppression, misrepresentation and erasure. From who is generating the data and why, to the assumptions and narratives created we must interrogate data practices and processes that can cause harm to our communities. 

Anna Rebecca dropped a lot of concepts and knowledge, and Vu shared great examples, so here are some highlights that were mentioned in the show (sign up for our mailing list to get ahold of episodes early and learn more about these topics):

Here are some concepts:

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Episode Transcription

Anna Rebecca Lopez (00:01):

As a non-black person of color, who has ascribed to white ways of thinking and white ways of doing, we're recognizing that the processes we have used in evaluation, are perpetuating a lot of the harms that we thought we were helping with. Problems like poverty tourism, problems like the white savior complex.

Michelle Shireen Muri (00:23):

This is Michelle Shireen Muri, your host and fellow traveler on the Ethical Rainmaker. A podcast exploring topics that deserve a deeper examination in nonprofits and philanthropy, including the places we can step into our power or step out of the way. Today we're exploring common ethical issues around how data is gathered and misused. Yes, data when collected and analyzed appropriately, can make a significant difference in addressing community needs and tracking our progress towards a goal. But it can also be a tool of oppression, misrepresentation and eraser. One of the worst experiences I had with data, was on the final day of an entire year of statistics at university. The course had been grueling and painful, and the lesson the professor gave after practicing extreme rigor all year, you can make data say anything you want it to. Data can be manipulated easily, accidentally or completely fail to capture reality.

Michelle Shireen Muri (01:19):

My fear was affirmed and I've remained wary about how numbers are used in our sector ever since, since that time, I, and no doubt you, have seen many ways in which data has been used badly or even erased whole communities. And in the nonprofit sector, data can persuade a funder to pour cash into your mission, or to suddenly pull out depleting your resources. Big institutions like the Gates Foundation or the government, require loads of hard or impossible to quantify data, often asking the wrong questions. I was recently on an organization's committee advocating for more speakers of color. I got the response that their membership was only 20% people of color. The speakers should reflect those numbers. I was livid and crestfallen. Data can be used to excuse continued inequity or reinforce white supremacy. Today's guests are talking to us not only about how data is weaponized against our communities, but also how we can bring justice to the Serena and to the process.Anna Rebecca Lopez who uses both they and she pronouns is a data nerd, disrupter, nonprofit evaluator, and social justice advocate.

Michelle Shireen Muri (02:27):

They're a founding member of Community Centric Fundraising, and enjoy working with communities who are often marginalized. They believe data and evaluation can be powerful tools for justice, and strive to hold white lead organizations accountable to the communities they serve. She organizes with the Duwamish Solidarity Group and as part of the Seattle Evaluation Association's leadership team. Anna Rebecca also has a master's from the University of Washington, and founded their own evaluation and community research consultancy. We are also joined by Vu Le, a different kind of data nerd and a well-known figure in nonprofit and philanthropic spaces through his blog Nonprofit AF. He's a co-author of Unicorns Unite, a book about how nonprofits and foundations can build epic partnerships. And he's a co-founder of Community Centric Fundraising. If you've listened to the very first episode of this show, you know that Vu has his master's in social work, from Washington University in St. Louis. Welcome you two.

Anna Rebecca Lopez (03:27):

Thank you for having us.

Vu Le (03:28):

Hi Michelle, It's nice to be back.

Michelle Shireen Muri (03:31):

Yes, it nice to have you back. It's nice to have you on E.R. I usually save this question to the end, but I'd rather talk about your identities upfront. Anna Rebecca, will you mind sharing with us before we get into this episode, What do you consider some of your identities to be?

Anna Rebecca Lopez (03:49):

Oh my goodness, that's a big question. When thinking about my identities, I feel like I have to often go back to my ancestry. It's not just my identity I'm holding or carrying, it's also my parents' identities, my grandparents identities, my communities identities. I am a proud Latina who comes from an indigenous background. I'm a proud descendant of the Maya peoples from Guatemala, and I'm a child of immigrants. My parents immigrated to the U.S. and married in the U.S. and that's where my brother and I were born in California.

Anna Rebecca Lopez (04:34):

We lived quite a transient lifestyle, moving up and down the West coast, but predominantly living in immigrant communities, Hispanic and Latinx communities, where there was a lot of agriculture and migrant labor. And that's where I come from. I come from small towns, communities that are often marginalized and often don't have resources for a variety of different reasons. It's because we're Brown people, because we're immigrants, because we come from a small town, many reasons. And I knew growing up if I wanted more opportunities, if I wanted to make the impact that I thought I could make, I would need to get an education. And that meant leaving the towns and leaving the communities that I come from. I'm a graduate of the University of Washington, as you've mentioned, I've held three degrees total. And yeah, all of this makes up me. I like to think that we all carry multitudes. We all multiple carry stories in ourselves. And yeah, that I'm a Latina, I'm an indigenous person. I'm educated, but I'm also a daughter and I'm a sibling and a cousin and a friend.

Michelle Shireen Muri (06:14):

Thank you for sharing. I think it's important as we get into this conversation. And Vu, we've talked a little bit about your background in the first podcast, but would you like to talk about some of your identities?

Vu Le (06:25):

Yeah, like I know Rebecca, I am also an immigrant kid. I was born in Vietnam and my dad fought against the communists. And then we escaped, and settled in Seattle after a stint in refugee camp and a few months in Philadelphia. And now we are here. I was supposed to be a doctor and make my family proud. And instead I went into social work and started getting to nonprofit management and community engagement. That's what I do, I'm a vegan and I watch TV a lot and I write NonprofitAF, which I think has become a huge part of my identity these last few years as well.

Michelle Shireen Muri (07:10):

Yeah, I would imagine so. Thank you for sharing. And to make it clear for our listeners, the three of us are homies. We have been through a lot together these last couple of years in releasing the work that we have done in this area of the world around CCF, through our platform And I think it's also important to identify who we are and where we come from, when we have conversations like this one, also because I don't usually mention or ask for education credentials. But as academia causes and perpetuates a lot of problematic practices, I did want to mention that you've both come from that world and have multiple degrees. Let's start with basic question, Anna Rebecca why is data so problematic ?

Anna Rebecca Lopez (08:02):

That it is also a big question. Oh goodness. Data is problematic in so many ways. It can be anywhere from how the data is gathered, who's using the data and even the types of question we're asking before we even start in the data collection mode. I'm trying to think how to answer this question because data in itself is used for so many reasons. It's used to make decisions for a community. Data is used to validate certain experiences or perspectives. Data is used to tell stories and oftentimes when those stories are inaccurate because of the data, it can cause serious harm to the communities.

Michelle Shireen Muri (09:00):

Who does problematic data harm usually?

Anna Rebecca Lopez (09:04):

The way I think about data is who's generating it? Who's it being used for? Who is it you being used by? And oftentimes it's people who have power who are using data. It's people who have resources who are using data as people who have education, it's people who know how to use data and be able to read data and talk about data. And unfortunately there's a big gap between those who have access to data and know how to talk about it, how to use it, and the people who are in and of themselves contributing to a data set, or contributing information that then gets filtered into data. And so automatically right there, there's a big separation. There's a separation of the people who are providing this information and the people who are using this information.

Anna Rebecca Lopez (10:03):

And so with that gap then, there's the potential to use data in a way that's benefiting those who know how to work with it. And it leaves the people who were contributing in the dust, it leaves them behind. And so the process of using data is a power move. And so I often think of who is using data problematically? Well, everyone. We're all using data problematically.

Anna Rebecca Lopez (10:33):

And it's really about, I would argue looking at data more holistically, looking at data as narratives of people, of communities, seeing data as people and including people in that opportunity to share their own stories. It's not just a data point, let alone a data set. These are people in communities. And when we remove data from that understanding of humanity, it's easier to use data against people.

Michelle Shireen Muri (11:06):

Your role in a lot of spaces. You've done this big research project for Community Centric Fundraising, you've done other huge research projects. You teach evaluation also. And I'm wondering what we're seeing currently in the field of evaluation and research.

Anna Rebecca Lopez (11:24):

Well, within evaluation and research there's Oh, dare I say a reckoning happening right now. These are conversations that I would say have not been happening in isolation. Evaluation as a tool that upholds white dominant culture, as a tool that even upholds white supremacy has been discussed since like the 1970s, especially when talking about culturally responsive evaluation, which is centering evaluation within the communities who are most impacted by the process. Now, just because that research has been around for 40-50 years now, doesn't mean that it's always being referenced or implemented.

Anna Rebecca Lopez (12:10):

I also want to say that most of this work culture responsive evaluation, indigenous led evaluation is led by people of color. And as we've seen people of color often not credited with the work that they've been doing. And so the evaluation that we are taught, the evaluation that I myself in the past have taught, comes from this very white centered perspective, this white dominant perspective. What we're seeing now, with the murder of George Floyd, with the current iteration of Black Lives Matter, with the current COVID pandemic that we're living in. We're recognizing, and I would say we as like the field, and I say we, I mean I'm not a white person. But as a non-black person of color, who has ascribed to white ways of thinking and white ways of doing, we're recognizing that the processes we have used in evaluation are perpetuating a lot of the harms that we thought we were helping with problems like poverty tourism, problems like the white savior complex.

Anna Rebecca Lopez (13:18):

And so the field as a whole is really at this place at this precipice where we're really having to think critically about our own practices, the ways we go about implementing evaluation, not just implementing evaluation, but the ways what we're asking questions, why are we doing this? Who are we doing this for? Who does this benefit? Who has power? We're being forced to realize that we are complicit in harm. And what's happening now, is that A, there's an awareness that we're causing harm, B recognizing that there's so many people of color out there who have been telling us we've been doing harm for so many years, and now we're listening to them. And see we're in this state of ambiguity almost, where we know we've caused harm. We know we've been complicit, but we don't know necessarily how to move forward. And I think as evaluators, we, I myself included, I like frameworks, I like processes. But most of those frameworks and processes come from white evaluators.

Anna Rebecca Lopez (14:31):

It's really at least for myself sitting in that same state of praxis, how do I implement and lead with culturally responsive evaluation? How do I lead with racial equity lens? How do I lead with a social justice lens? And implement this in my work, knowing that it's going to take time, knowing that I have to change the way I do my practice and that it's going to be a couple of years, hopefully less, but it'll be time before we actually get to a point in the field where we can name, that hopefully the good that we're doing and mitigate the harm that we're doing as well.

Michelle Shireen Muri (15:19):

Ooh, that's so good. That's juicy. Thank you so much for talking about that. I think it's for a long time, we've known those of us working in nonprofit, those of us who identify maybe as people of color or have worked in racial justice organizations or immigrant rights organizations like I have personally. I think we have seen the way that white supremacy has played an influential role and, or is, how data analysis, the questions we ask et cetera, are all housed and have been so uncomfortable. And so upset by that process, by that inequity. And also haven't necessarily known, I can speak for myself I haven't known what other questions to ask or how we should be interrogating that data or how we should be talking with our funders, for example, when they ask us for things that are coming from that frame.

Michelle Shireen Muri (16:24):

We're exploring issues around how data is gathered and how it can be weaponized and manipulated with Anna Rebecca Lopez and Vu Le right now on the Ethical Rainmaker. What gaps exist in your knowledge? Hit us up at or contact us through our website. Do you love the topics we're bringing you? The best way to support this pod is by subscribing, sharing it with your colleagues and contributing to our new Patreon, learn more at Vu, I'm curious to know, I know you've written so many articles. Your blog has been going for over eight years now, and you've toured the world, speaking about non-profit issues. I love your article about the over-intellectualization of our sector. And I'm wondering, what do you see about data the way it's being used and how it's harming us?

Vu Le (17:21):

Yeah. I wrote a blog post a while ago called Weaponized Data, which is a term that I learned from Dr. John Doe Chen, from a researcher at UW and generally cool guy. But it's talking about how we still have this issue in the sector. Just a few years ago, I remember an Executive Director, a woman of color coming to me and saying, I don't know how to do a logic model. This grant I have to apply for requires us to have a logic model. I spent like four hours with her and her board trying to determine this logic model. And at the end of it, it was just basically, what are you trying to do? What are the short and longterm outcomes of this, right? But they want this to be used in a particular way.

Vu Le (18:06):

And it was not satisfactory to this funder. And they rejected this grant because they're like, "Sorry, your logic model is not good enough". We weaponize these concepts, which often like A.R said, it's from people in power and who are people in power? It's going to be white folks. Who are the people at research institutions who were getting paid to throw the sort of terminologies and concepts and tools into the sector? It's mostly white elite educated individuals. And so this is a huge problem when funders are using this to gate keep funding, go into the community when they're like, "Sorry, you don't have a good enough data for us to fund you. You're out of luck". Well, how are organizations going to get good data if they don't get funding? So they're stuck in this data resource paradox. You can't get good funding unless you have good data, but you can't get good data unless you have good funding.

Vu Le (18:54):

And this is echoes with the capacity paradox when you don't get funded, because you don't have the capacity is really insidious across the board. And then we think about who gets to determine what is good data as A.R said, right? Because right now the data that's being determined that to be good data or quantitative data, short-term data. And I think it's really dangerous to the sector. When we focus on these short term, easily measurable, tangible things that make people feel good. They're like, "Oh, look, we've got some data". Well, some of the work that we're doing in the sector, it's going to take forever to actually collect the data. But we are gravitating towards, short-term not longitudinal data. Funders are not going to fund for 10 years, so they can see how long it's going to take. So we are biased towards short term, white lead, tangible, easily measurable data and metrics and outcomes. And I think that causes a lot of harm.

Michelle Shireen Muri (19:49):

Thank you. I agree. This is a question for both of you. What do you think we're taking for granted when we're dealing with these processes?

Anna Rebecca Lopez (20:00):

I think we're taking for granted how much communities know about themselves, and how much communities really know what is needed for their communities to thrive. Even thinking about impacts and outcomes who defines those, often those are defined by organizations, sometimes defined by the funder themselves, where they say these are the outcomes that we want. Develop a program that will align with these outcomes. And now an organization has to go find a community, tokenizing the community in order to receive funding from the funder. And I think we take for granted that communities know what it is to healthy and what it is to be thriving, but we rarely give them the opportunity to share that, to lead their own journeys.

Anna Rebecca Lopez (20:56):

And instead we go in a very extractive manner to perpetuate a donor paternalism and say, this is what we think you need. This is the problem we're observing in your community and not providing space for these communities to speak for themselves. We look at these communities in a deficit perspective, rather than this asset-based perspective. What are the resources that they're bringing? What is it that makes this community so powerful and so beautiful? Instead, we currently look at what is the problem that they're experiencing. And so yeah, we take for granted the community's knowledge of themselves and their agency.

Michelle Shireen Muri (21:37):

Thank you. That's gorgeous.

Vu Le (21:39):

We tend to infantilize communities. We think that they don't actually know what is good for them and what solutions would be best for these communities. I remember a colleague telling me that she attended a meeting where it was like a group of powerful, mostly white people again. And I think it was a foundation, and it was some trustees and someone brought up." Hey, we need to trust our community members, let's ask them what they think would be needed and what we should be funding?" And one person, a board member said, "But what if they're wrong?" This is what we're dealing with, but it's pervasive across the entire sector. And then data has been used to reinforce these narratives. Even if there's data, if you cannot see it, I think there is like, I call it solutions privilege, and it manifests in that you cannot perceive solutions that challenge your privilege or your existing worldviews.

Vu Le (22:41):

Even if a community member brings up data is like, "Look, we've had lived experience with poverty, with homelessness or whatever. This is what will actually work for us." It cannot be perceived. Right?. And that dissonance causes people to be like, well, I mean, someone brought this up to me and I just don't agree with it. Let's go find some data that would discredit that, or let's find something that would confirm my own narratives of it. This is another way that data has been weaponized. It's used to cherry pick the things that would align with what the people in power think is what's necessary and what should be done.

Michelle Shireen Muri (23:18):

VU, you told us a story recently, actually. And I'm wondering if you wouldn't mind telling it again about how sometimes when we use research tools like surveys, that is also based around white culture and white supremacy and centering whiteness.

Vu Le (23:37):

Yeah. Actually it's not my example. It's Dr. Jondou Chen's example, but he's just so cool. I'm just going to pretend that is my example. But we were working at my last organization RVC and we were trying to just assess how the program was going right with our fellows, that we were sending to these organizations. And we were working with John Doe on creating these surveys. We created a survey in English and then translated it into different languages and then went out to the communities and asked them to fill out the surveys. Well, we talked to a community leader from the Somali community who said, what is this? And we say, well, it's a survey that we translated into Somali. We just try and he's like, "This is not a Somali survey. This is an English survey, a white survey that you translated into Somali. And if you were trying to make this culturally responsive, then you would cut out half of these questions. You would be a lot more direct. You don't beat around the bush because this is not how we communicate."

Vu Le (24:40):

And that was a really good lesson from Dr. Chen and obviously to learn, which is that we tend to think of whiteness as the default, and from whiteness everything stems, right? We create, we use these white tools, we try and we use them in English, in a very sort of white academic jargon. And then we translate it into communities and we expect communities to conform it and to learn how to this very white way of doing things. And this is again, pervasive across the sector in other ways as well in fundraising, where we train communities and fundraisers of color, to thank donors in a very white way or relate to people in the white way. And it does cause a lot of harm.

Michelle Shireen Muri (25:26):

Thank you for that. I'm Michelle Shireen Muri. The Ethical Rainmaker is brought to you by our consulting collective freedom conspiracy, visit to take your ethical fundraising to the next level, bring values aligned practices to your growth opportunities at hand. We're talking with Anna Rebecca Lopez, a researcher, evaluator and data nerd, and relay a nonprofit critic and author of popular blog, nonprofit AF right now on the Ethical Rainmaker. Learn more about Anna Rebecca and Vu in the show notes at Questions for both of you, do you have some examples of good use of data? Like how data has been used well and has benefited community use. And also what's the key to stemming the harm that data can do or what we what should we be doing differently? What should we be looking for? Two questions.

Anna Rebecca Lopez (26:26):

Yeah, I could try and answer that question. It's two questions, right? That's what we call a double barrel question Michelle. Yes. Yeah. Asking two questions in one. Examples of how we collect data. Well, I would definitely say in my own personal experience, that's still something that I'm practicing on, that still something that I'm working towards. Communities can also benefit from having this data. I think so often the experiences I've had has been, this is how we not do it. This is how we make sure we're not causing harm. And a part of that is making sure that when we even think about doing research, when we even think about doing a study, even before that, even when we think we're developing a program or initiative, our communities actively involved in that decision making process. Is the process participatory? And is it being led with, and by the communities? Who again, are going to be most impacted by this program or initiative. And I would say at least in my experience, that so rarely happens with many of the organizations that I have worked with, many of the clients that I've had, it is still very donor centered.

Anna Rebecca Lopez (27:57):

We act as if we're accountable to our donors, rather than being accountable to the communities intended to serve. Ways to mitigate that harm includes, being inclusive. Building relationship with the communities we are serving, having them be a part of the process, whether that's program development or research or evaluation. Having them decide how they want to go about doing that and making sure that we, and by we, I mean, the evaluator, the organization, the white lead organization that we provide the resources so that communities are leading their own work, that we are empowering them, that we're providing resources, that we are redistributing power so that they can own this data to benefit their own communities. And in turn, help benefit the work of the organization that so rarely happens.

Anna Rebecca Lopez (29:00):

I think that's a way to help mitigate, early on in the process. But as we continue in that process, at least with regards to evaluation, as we collect data, continue to have the community lead that process. And that means timelines have to change, right? Budgets have to be bigger, budgets have to account for us paying people in community to be able to do this work. Otherwise, the only thing we're doing is tokenizing these communities.

Anna Rebecca Lopez (29:29):

We have to make sure that timelines are extended so that we are building authentic relationships, rather than ones that are extractive and transactional. And in the ways that we analyze data and the ways we report back and tell stories ensuring that these communities are telling their own stories. I often think of myself as an evaluator, but all I am as a bridge. All I am is bridging communities and organizations and their donors. I am not the voice of the community. I shouldn't be the voice of the community. They have their own voice, they have their own narratives, but how do we make sure that those are being told in a way that is accountable and impactful in good and beneficial ways?

Michelle Shireen Muri (30:20):

That's awesome. Thank you.

Vu Le (30:22):

Yeah. Every everything that Anna Rebecca said. But I do think that we tend to overthink things a bit and I'm seeing more hopeful signs of funders realizing this and changing. For example, certain funders are starting to dispense with the whole formal written report for grants, right? Where they're like, "Please report on this." And instead they just go and have coffee with a grantee and say, "Hey, what did you learn? Tell us what went well and what didn't go well. And what did you learn?" Instead of writing this like formal-ass report.

Vu Le (30:59):

I think there was one funder in New Zealand who got grantees together and they share the data, what they learn with one another because so many grant reports, it's just not being read. And what are they for? Right? What exactly are these reports for? They're going to sit on a shelf. They're not benefiting the people who should be learning from these reports are other practitioners in the field. We're starting to see more of that. I think there is more of a movement away from logic models and things. Do you really need to have a logic model if you just explain in a narrative paragraph what you're trying to do.

Vu Le (31:38):

I think there's some hope of there're more conversations at least. I was attending a workshop I think by Milwaukee Evaluation where one of the workshops was Decolonizing Outcomes, where we talk about who gets to determine which outcomes are good and who gets to measure this. And one time I was talking to a major funder of RBCs and just report it. I provided a three page list of all the outcomes that we had achieved. And the program officer literally said to me, are these the outcomes you and your community want to share, or are these outcomes that you think that we as funders want to see and be impressed by? And that was a really good question. And I think in the past, funders would never ask that. And that really made me think like if I, wasn't trying to think about how to impress the funders, what are the outcomes we would be focusing on?

Michelle Shireen Muri (32:36):

Oh, I love it. Just going back a little bit, I've heard you talk about the over intellectualization of our work. Do you think that data, maybe isn't as important as we think?

Anna Rebecca Lopez (32:50):

That is a great question. And as a data nerd, a little part of me was like, Ooh. I love data. I think that's a good question. I think one of the reasons we try and justify data is so that we have more numbers, right? It's not...One of the things that we're taught in statistics, is if only one person is saying something, does it weigh as much as a hundred people saying something else? And, typically we go to the hundred, we go to the masses, we go to the numbers, the quantity, but can we say the same thing when it comes to racial oppression? Can we say the same things when it comes to systemic oppression? That one person matters that one person's experience matters and their narrative matters. And so I would say, is data important? Yes, but not to the detriment of the one person who's being oppressed and maybe they are one data point outweighs the 100, because of the systemic imbalances that just exist in our society, in our culture. And that's where I would say, as I mentioned before, data is people, and we need to remind ourselves of that is that when we talk about data, when we're talking about a mass percentage or a mass number, these are people. And when we're talking about small percentages and small numbers, those are people too.

Michelle Shireen Muri (34:45):

Thank you.

Anna Rebecca Lopez (34:46):

I would say it's, yes, data is important, but for whom and by whom and who is using it are also important questions to consider when working with data.

Michelle Shireen Muri (35:01):


Vu Le (35:05):

I agree. I think data is important. But I think like anything else, it could be weaponized, right? If there's too much, or the pendulum swings way too far in one direction or the other. And right now it is as has one way into the territory of elite white, mainstream institutions who get to decide, what is good data and then neglect. And the people are marginalized and their data, their stories and anecdotes and stuff are considered like anecdotal evidence or whatever, which is not given the same weight. And this affects things. It affects funding, it affects reputation. It affects who gets to control what decisions in our field. There is this imbalance in how we use data in the sector, just like there's an imbalance and everything else that we need to think about.

Michelle Shireen Muri (36:00):

Is there anything that we didn't talk about that you wanted to mention?

Vu Le (36:03):

I would say that we should examine how progressives and conservatives use data, there is a difference. We on the progressive side tend to be very intellectualizing, and short-term focus and we're just like, we need this data and all this stuff. Whereas I feel like a lot of conservatives are like, "Hey, let's just go and do this thing. Let's make sure that we get conservative judges on all the seats and the Supreme Court and everything. That's going to be our data. Our data is like 30 years in the future." Right? And over here, we're like, "Nah, sorry."

Vu Le (36:40):

I always joke that if like MLK were here and he's like, "Hey, I have a dream you all." Our, response would be like, "What MLK, that's a really great dream that you have, but like, what is your data? Do you have a logic model? Do you have a theory of change? What is your outcome? What is your three month metric? What is the research behind this? Is this replicable? Is this scalable?" This is what we do. Instead of focusing on the long-term vision that the data's supposed to be supporting. We use data as a roadblock, to prevent progress from happening. And we lose a lot of visionary leaders and projects and movements because of this, like hyper-focused on data and especially short term, easily understood data that does not challenge people's privilege.

Michelle Shireen Muri (37:29):

Oh, that was bomb. Thank you for that. AR last words, anything that you wanted to talk about that we didn't cover?

Anna Rebecca Lopez (37:39):

I mean, how do I follow that up? That's so good. I think the last thing that I want to say is at least for me, when it comes to those long-term impacts, which is ultimately aware what evaluation wants to inform, what data wants to inform, we can't do that without relationships. And I would say relationships matter more than data. And if we truly want to have long-term systemic change, then we need to have relationships with the communities who are most oppressed by the systems we are actively working in and the systems that we are complicit in. And whether we think of data as something as a numerical value or as a person's story, that isn't more than the relationships we build and maintain and grow.

Michelle Shireen Muri (38:39):

And Rebecca Lopez is a data enthusiast, disruptor and social justice advocate at AR Lopez Consulting, their evaluation and Community Research Consultancy. Learn more about their work at Vu Le is a nonprofit critic and author of the popular blog Also, I'm so glad to call these people my friends and colleagues. It has been so fun to have us all on a podcast together and especially around this topic, which as a Community Centric Fundraising, as we were deciding how we wanted to launch the survey that we created together, implemented and then Anna Rebecca, you did all the analysis on to come up with these beautiful infographics and articles, has really just been informing our work. And I want to thank you for that.

Anna Rebecca Lopez (39:31):

My pleasure. It's been a fun two, three years.

Michelle Shireen Muri (39:36):

Yes it has. I appreciate the work that both of you do on behalf of our communities, to center communities and to talk about these issues. Data is one of these places where I think many of us know that something is not quite right, but don't know how to fix it. Don't know. And I feel like we don't know enough, even if we do. Thank you so much for talking about this today. I really appreciate it. Thanks for coming on.

Vu Le (40:03):

Thanks Michelle. Thanks Anna Rebecca.

Anna Rebecca Lopez (40:06):

Thanks Vu.

Michelle Shireen Muri (40:08):

That's it for the Ethical Rainmaker. I'm Michelle Shireen Muri. Thank you so much for being with us on this journey, deeper into the world of nonprofits and ethical fundraising, and in this case - data. There's a lot of information for you to dig into in the show notes and note here at the end, we are celebrating our first season with this episode.

Michelle Shireen Muri (40:28):

Woo. We're going to take a little break during the peak of fundraising season, and we'll be back with more great interviews and issues in January. Stay tuned, stay safe and stay in touch. Have a story to share on our next season? Send us an Don't forget to subscribe to this podcast so we can count you in for season two. And if you value these conversations and you want to offer financial support, you can join our growing base of supporters on our new Patreon. Please check out our new Thank you so much for our Patreon's this season. They include Zoe, Jill, Andrea, Rocky, Kim, Tiffany, Laura, Alex, Becca, and Farrah. Thank you so much. You all the Ethical Rainmaker is produced and edited in Seattle, Washington by Isaac Kaplan-Woolner with socials by Rochelle Pears. We're sponsored by my fundraising consulting, collective freedom conspiracy, which you can find at Special thank you to The Black Tones for letting us use their song, They Want us Dead. Listeners I so appreciate this community and the ongoing conversations that we're building together. And I'm looking forward to what we have in store in 2021. See you soon.