Does Your Nonprofit Have a Data Culture?
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What is a data culture? When we talk about culture, it's about an environment. It's about practices. It's about habits. It's kind of like the air you breathe—the part of an organization that's sometimes hard to pinpoint but is always there.
A data culture means creating an environment where the use of data is a priority in decision-making and is part of everything you do. You gather evidence, collect data, evaluate programs, and use this information to make decisions about management, fundraising, and more.
A data culture has several key elements, and we’ll cover five of them so you can understand what’s important for building an organization that uses data in everything it does. Data should not be an afterthought but a central part of how an organization operates, makes decisions, and evaluates its impact.
You’ll hear:
(03:11) How strong commitment from leadership drives a data culture
(05:52) Why data literacy is crucial across your organization
(07:10) What it means to make data accessible and usable throughout the organization
(08:59) The importance of establishing a framework for effective data management
(11:24) How to integrate data into daily decision-making processes
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Drew Reynolds: Hello and welcome to the Common Good Data podcast. My name is Drew Reynolds. Today, we are going to be asking the question, does your nonprofit have a data culture and the focus is going to be thinking about the characteristics of organizations that have a data culture. What does it mean to be an organization that is data driven?
That uses evidence to make decisions and that really lives and breathes data throughout everything it does. Uh, before we dive in, I want to do a quick reminder for those of you who are listening, uh, through podcast format that we are now on YouTube and we have a you, a video version of this podcast. Uh, so you can navigate to youtube.
com and check out our handle @commongooddata to follow these podcasts in video format as well. And of course. We always appreciate it when folks review us on Apple Podcasts. That does so much to help us continue to the work and sustain this podcast into the future. So what is a data culture? Well, when we talk about culture, it's about an environment.
It's about practices. It's about habits. It's kind of like the air you breathe. The, the part of an organization that sometimes it's hard to put a finger on, but you know, it's there, right? And a data culture is when you have a culture. Which is this environment, practices, habits, whereby the use of data is prioritized in decision making where it's a part of everything you're doing.
You're gathering evidence, you're gathering data, you're evaluating programs and services. And you're using data to make decisions about organizations, about management, about fundraising and programs, so on and so forth, a data culture encompasses. A number of key elements and today we're going to cover actually five of them, uh, just so you can get a sense of, okay, what are the things that might be important to consider when trying to build an organization that uses data and everything that it does a key part of this to when we think about data or a data culture?
is that data is not seen as something that's an afterthought, but rather a central component of how an organization operates, how it makes decisions, how it evaluates its impact. Um, I, you know, a good example of this, I have one organization that I've worked with where they would start every monthly meeting with the question, Where are we on our core metrics?
And they had identified over the course of, um, a couple of years, uh, key metrics that they were going to use to, uh, understand how their programs were operating and functioning. And then sharing that with their leaders, their organizational leadership. To be able to make decisions about how to, where to emphasize time, effort, program resources, uh, to best serve the community.
So thinking about that, you know, what are the ways in your organization, perhaps that you incorporate data on a regular and habitual basis? Are there meetings or regular things that you're doing where you're bringing data and evidence to the table to guide discussion and decision making about the core strategic areas of interest in your organization?
Okay, so as I shared before, we're going to talk about five key components of a data culture. Um, the first of these is having strong commitment from leadership. So first component, strong commitment from leadership. And that is where the leadership of your organization actively supports and promotes a data driven approach.
And they kind of set the tone for a data centric culture all across the organization. In an example like this, you'll see that leaders are often models and embed leadership, sorry, data into the culture of the organization. Leaders like that are always asking the question, do you have any information or data or evidence about that?
When a staff member brings a new idea or a problem or a concern, their first question isn't yes, no, or what their armchair thoughts are. The question is, is what data or evidence can we bring into this conversation? to help us make an informed decision about where we want to go. That's a key component and it has to come from the leader.
Leaders in this, uh, scenario too, um, are also transparent and accountable. And I can tell you there's nothing that a leader can do that perhaps does a better job of communicating the importance of data when leaders share transparently information about the organization and even themselves that may show even areas of improvement or weakness.
So a leader who says, you know, this is the metric that we have for this year. This is where we are. We aren't quite there yet. Right. That's one approach. Another one might say, Hey, this was something that was. Primarily my responsibility, but I didn't get there. I was missing on it. Right. When you do that, you're, you're modeling for your organization.
That data is being used as a way to inform decisions as a way to stretch as a way to, to push yourself towards a goal. Um, but it emphasizes learning and. Um, how to, uh, make changes in light of where you, maybe you didn't quite make the mark over an accountability framework that only holds people accountable.
And that only, uh, brings negative consequences for not meeting such a thing. Right. So if data is only seen as something that's holding people accountable, that's something negative. That's something that is only going to serve to hurt an employee or a staff member over time. They're probably not going to buy in, but when leaders show that data is, can be used to drive learning and insights, um, and ways to change.
Uh, practices and behaviors in an organization for the better, it can make a huge difference. So leaders really need to bring that data driven approach, always asking for evidence and data when trying to make decisions. A second key component of an organization with a strong data culture is having strong data literacy across your organization, which is making sure that staff have the skills to be able to understand and use data.
And this can come in a variety of ways. It comes by recruiting individuals into the organization who come with strong data and analysis skills. Maybe they're not, you know, statistical experts, but they should have some comfort and familiarity with, for example, Excel and using a spreadsheet. Or being able to look at percentages and fractions and things like that and be able to understand those basic mathematical concepts to be able to make decisions.
There's also, I think, um, an opportunity for lots of organizations to consider training in the use of data. And even if it's not training in doing a whole in depth analysis on how to Manage a spreadsheet or manage data in a particular way. You can have really effective trainings around things like planning using data.
How about gathering data and evidence? What does evidence based practices mean? Things like that, that can help your organization have enough of the background it needs to be able to make good decisions with data. So the first one is commitment from leadership. Second is data literacy. The third area, um, or component of a data driven organization is around data accessibility, making data available and usable across the organization. And here's one of those things where it's really not useful to have a ton of data.
If you can't access it and if you can't use it, and this can be really challenging for organizations because sometimes you feel like you're in a situation where you're collecting tons of data, but it's all in a bunch of separate spreadsheets and it's not integrated or usable in ways that you can get information from it.
Uh, in a timely or useful way, sometimes you'll run into the problem where organizations will be collecting data, but no one's really monitoring it until maybe at the end of the year or when they, when the reporting time comes. And so the ability to do continuous improvement, to be able to evaluate progress on a monthly or quarterly basis.
So you can make changes and updates to programs and services while they're being operated gets lost because you're only doing it maybe once a year or once a reporting cycle. So having data be not just something you collect, but something that you can actually use and access is also critical. And here's where you want to be thinking about a couple of things.
One is, is helping the staff members that you have become familiar with the organ, sorry, the tools and the, um, In different ways that you're collecting and using and representing data, having enough training and fluency in those is going to be really important. It's also going to be good to be thinking about data privacy issues that may come up and confidentiality issues, and we'll get to that in the next one as well.
But knowing and helping to inform staff about how data can be responsibly accessed but also responsibly secured. So the fourth one we'll talk about is data governance, and this one is so critically important. And for those of you nonprofit executive directors out there or leaders who are regularly interacting with board members, this is a good conversation for you to have with board members, which is developing some type of framework to ensure that data is managed appropriately.
And that employees and really anyone involved in the organization is using data in the right way. So you should have at minimum, some type of organizing document talks about data, privacy, confidentiality, and governance, and this would cover things like. How do you handle data sharing with third parties?
Uh, if you're an organization that makes referrals to others, especially when the referrals involve sensitive information or information related to health, for example, you're going to want to have some conversations about data privacy and confidentiality so that you are ensuring that you are, um, in compliance with local and federal laws.
You'll also want to talk about things like how you define sensitive data. Um, sometimes you hear the term PII for personally identifiable information. or personal health information. So having a sense of what that is, making sure that your whole organization knows what those things are and how to protect those appropriately is an important component of data governance.
You can also talk about how data are protected and used. So when do you use data and where it can be used is important. Um, how to handle data breaches, should they occur? Um, and then any type of examples of. Employee training, uh, that you might use or some type of policies around how often you ensure.
That the staff members of your organization are familiar with that data governance or data privacy and confidentiality policies So that they are up to date on what they need to know to do the work effectively Now data governance can be tricky. It involves legal work typically and so it's good to engage your board members uh, particularly if they have either legal expertise themselves or if they know someone who can connect you as a non profit leader to someone who has Some background in data governance work to be able to help you draft documentation, um, policies and frameworks for your organizations that best suit your needs and that are in compliance, uh, with, uh, the local and federal laws.
So lastly, let's talk a little bit about data driven decision making. This is the fifth component, data driven decision making. And this is where you take each of those other things, right? The first four being, Commitment from leadership, data literacy, data accessibility, data governance. And then lastly, data driven decision making to figure out ways to integrate data into daily decision making processes.
And this is one of those things we're coming back to the beginning of this conversation. The question you always want to be asking is what data or information do we have? on this topic that can help inform this decision? Do we have, and data can be used pretty expansively here. You don't have to think about always starting a new survey or finding some new data collection element.
You know, you can gather information from conversations that you have anecdotally with, uh, you know, clients or participants in your programs. You can gather information from your staff members about their experiences and focus groups and interviews. You can gather information from social media about how people are engaging with you online.
Really, information that you gather and evidence that you gather to be data driven can really be expansive, to allow you to use information from all different types of formats and all different types of approaches. And I would say that most organizations actually have a lot more data and evidence out there than they think.
think to be able to inform their decisions, and you're probably already using it in some kind of way in your organization, maybe without realizing it or naming it as being data driven or using evidence in your decision making. So the key here then is to think, what is the data and evidence that we can gather about this particular topic?
Um, and then Using a data driven approach says, how can that data then inform this conversation to help us make a better informed decision? This is where the leader, again, must be the model and to model the data driven decision making across the organization to lead with it, to constantly be bringing back, what is data and evidence going to have to say to help us make this decision.
And I think where leaders sometimes get into trouble is when they don't do this, when they make decisions based on their gut reaction. On what they are thinking or maybe they aren't, maybe they're using data and evidence in their head, but they haven't laid it out for their staff to see how they're using data and evidence in their head.
And it comes off as a leader making kind of like a knee jerk reaction or a, um, you know, a quick decision, without taking that thoughtful or deliberate approach, uh, that can sometimes, uh, be required from taking a data driven lens to the work.
One more thing I want to mention about data driven decision making is that data should always be, and evidence should always be a part of, especially your big decisions in an organization. But that does not mean that data and evidence are the determining factor in decisions that you make. And this is where it's really important to consider not just data and evidence, but also your lived experience as a person who's been doing the work, um, someone who has been out there in the field, uh, who has lived experience, who has engaged in delivering programs and services, who knows the clients and the programs and the communities well, that information is really important too.
And so sometimes we get a little too data heavy and we just focus on one metric or one indicator. And we really want that one indicator to drive everything that you do. And there's some advantages to that, but it can come with some costs. And sometimes it's important to weigh whether or not that one indicator should have such a primacy in the decision making process that you're making.
Um, so I think the key there is to say, don't forget about your own lived experience as someone who has been doing the work before, and with that lived experience, I think also comes in to think about what are the cultural, uh, racial gender factors that may impact how you interpret and make light or sorry interpret make sense of and understand the data in the context where you're working.
So data and evidence You know, can sometimes in organizations when you emphasize it too much, kind of be dismissive of or ignore the local context and the factors, um, that are related to issues of race, gender, social class, and other forms of difference that can really, um, sometimes come into conflict.
And so a good decision making process is going to bring all those things together. and see each of them as a piece of a larger puzzle in decision making rather than having one, uh, of those just sort of dominate the entire conversation. So to review, we talked about a commitment from leadership. We talked about data literacy being important.
We talked about data accessibility being important. We talked about data governance, and then lastly, bringing that all together. And engaging in regular data, data driven decision making. And so that's what you want to see in an organization that's truly being data driven that has built out that data culture.
Now, when you have accomplished this, you're going to start to see some really strong benefits in your organization. First, you're going to start to see improvements in the programs and services that your organization is offering. You're going to have a better understanding of what's working and what isn't.
Now, a good example of this is, I do a lot of work in substance use prevention, and recently we've seen a huge shift in how youth are using substances underage. Shifting from traditional cigarettes to e cigarettes and actually having such an emphasis on e cigarettes and vaping even more so than alcohol or other substances.
And this has been a trend that's been showing up in both national as well as local data. If you're an organization that has been, uh, focused so much on alcohol or on traditional cigarettes, you really have to shift focus to, uh, understand the current, how the landscape of substance use has changed.
And to do that, you have to have some local data about how youth are using sick, using, um, uh, drugs and alcohol. So that's a good example of how organizations might shift their priorities based on what they're observing. Um, in. The, and the communities in which they serve.
So for example, I know there's one organization that I've worked with. That does a lot of decision making around reach. They're trying to figure out what data and information they can gather about the reach of their programs and services. How many people are they reaching? Um, what is the nature of the receipt?
Are the people excited about the programs and services being offered? Um, and to use those. That data and information to help not only just motivate, but also focus staff on key areas of programs and services. So they're asking questions like, Hey, in one month or in three months or in six months, how many people can we reach in this particular area and sending those goals can be helpful to staff to help orient them, you know, what is, what should I be focusing and spending my time on, you know, where do we want to see success as an organization?
And so using data in that way can be helpful to improve your programs and services. In addition, you're also going to see with a data culture, better reporting and accountability. So for example, you're going to see your ability as an organization to gather information about impact improve. You're going to be able to use data to demonstrate impact, to gather information about your organization, to demonstrate the effectiveness of your programs.
And when you start to do that, you build accountability and you build trust. It helps communicate with people who are interested in supporting your work. What it is that their dollars are going to in turn, be able to support. How does my funding contribution as a grant maker or as an individual donor, or as a community foundation translate into community impact.
And once you start doing that, you're going to see big changes in fundraising for your organization because strong evaluation leads to the type of big six and seven figure grant opportunities. That's a stain organizations over multiple years in the long term. And it's absolutely essential for those of you who are interested in seeking federal funding in particular, I tell organizations that evaluation work can sometimes be one of the ways you best distinguish yourself from others in grant applications, because that's one of the areas where.
A lot of organizations still need additional work and support. And it's one of the areas that's most important when grant makers and decision makers are making discernmentations about how they're going to fund the resource, uh, fund programs and services. So lots of benefits that come from building out a data culture.
So in conclusion, Data culture is super important. You, uh, take a minute to review some of the five topics that we talked about today and reflect on them a little bit. What are the ways in which you feel like those are reflected in your culture of your organization or not reflected? And then thinking too, in terms of the benefits, you know, what.
Why would it be important to have a data culture at your organization? In the next episode, we're also going to talk a little bit then about how to build and enhance your data culture. So taking from what you already have, what can be a next good step to help improve your organization's ability to use data and evidence and decision making.
So stay tuned for our next podcast. As we wrap up here, we'll go ahead and ask you, I'll ask you to check us out at www.commongooddata.com/podcast. Like us, um, and follow us on LinkedIn, Facebook, and YouTube. And of course, if you can submit a review on Apple podcasts, we greatly appreciate it. Have a great day.
