Is your data supporting your strategy? Is it aligned with your mission? Last week, we chatted with Joanna Fulford, founder of Fruitful Data about creating a data strategy. What's that you ask? It's a way of planning for your data so that you get the most value out of it. It's about getting more value out of the data you have, rather than getting more data. Joanna told us:
  • How to plan for data so that the data we have supports our mission
  • The questions to ask before we even think about designing a survey or a form
  • Why better data doesn't mean more data
Join the conversation live on Facebook at: https://www.facebook.com/groups/DataInformedPrograms/ Transcript Cynthia Rojas: Hi, everybody. Oh, wow, it's Friday and that means Coffee Time with Masterminds. Well, being strategic is important at every level, and in the past few weeks we've been talking about developing an organizational strategy and maintaining that vision through a time of crisis. Today, we're going to get granular and talk about data, my favorite topic. Joanna Fulford, the Founder and Consultant to Fruitful Data will be joining us to talk about what it means to think about your data carefully, systematically as we do our programming. Joanna helps non-profit organizations align their data so that they can focus on delivering on their mission with reliable information and tools. I can't wait for this conversation. I also want to acknowledge that today is September 11. It is a day that our country still mourns for the lives that we've lost and for the lives that have been affected. And on behalf of the executive producers of Coffee Time with Masterminds, our hearts go out to the families who are still impacted by these terrible, terrible attacks that happened to us on September 11. All right. Well, hello, everyone. Welcome to Coffee Time with Masterminds, which is a 30-minute conversation with leaders of mission-based organizations. And I am here to introduce our other co-hosts. And if you are watching, please put your name in the comments and tell us where you're from. So my name is Cynthia Rojas and I am the Founder and Principal of To Your Growth. And joining me today is Rebecca. Hi, Rebecca, how are you? Rebecca Tuttle: Good morning, Cynthia. I'm well. How are you? Cynthia Rojas: I'm really great today. I'm really great. Rebecca Tuttle: I know. TGIF. Cynthia Rojas: I know. Rebecca Tuttle: I'm Rebecca Tuttle. I'm the Founder and Creator of Grant Write Now and Grant Writing for Good. Cynthia Rojas: Great. Thank you. We are also joined with Pieta. Pieta Blakely, how are you? Pieta Blakely: Good, thank you. How are you? Cynthia Rojas: I'm good. We're good. Pieta Blakely: My name is Pieta Blakely, and I am the Founder and Principal of Blakely Consulting. Cynthia Rojas: Nice. Nice. Welcome. Pieta Blakely: Thank you. Cynthia Rojas: All right. Pieta Blakely: We have all heard about how important it is to create good and effective feedback loops in order to manage our programs well. Underlying that, and a lot more is having a strategy for our data. So today we have invited Joanna Fulford, who is a data consultant and Founder of Fruitful Data to join us, to talk about strategy. Good morning, Joanna. Joanna Fulford: Hello there. Good morning to everybody. Rebecca Tuttle: Good morning. Pieta Blakely: Thank you so much for joining us. Joanna Fulford: You're welcome. Pieta Blakely: So tell us what a data strategy is. What does that mean? Joanna Fulford: Sure. So it's really a high-level plan to align your organization's data with the delivery of its mission. So it's very much at a strategic level, but then from that you can then sort of drill down and think about how you're going to actually deliver what you need. Pieta Blakely: And why is this important? What happens when we don't have one? Joanna Fulford: Well, it's important for a number of reasons. I'm broadly speaking, it can help you improve the experience of your stakeholders because you really know what it is that they need. It can help you provide evidence of having actually delivered your objectives, because you're thinking about that right from the outset. It can help you make really well-informed decisions because you have access to really reliable and accurate information. It can help you be more efficient. So if you think about things like producing letters and reports, you want to be able to do that really easily and effectively, and perhaps even automatically. It may also be helping you with compliance and other sort of needs that your organization has to be accountable. So whether that's how you are keeping data secure or private, how you're sharing it, who's accessing it, that kind of thing. And also it can help you sort of keep your focus on, are you delivering return on investment? Some not-for-profits actually do try to generate income rather than just being funded by grants and so on. So that's going to be a concern. So without having a strategy, you may be struggling with some of those things, but by thinking about how your data is going to support you in doing all of those things, you'll be much better placed to get to that end point and have the information that you need. Cynthia Rojas: Joanna, I have a question. So I've worked in nonprofit for a very, very long time, almost two decades. And I have found that people are intimidated by data and the depths in which you should really look into your data and develop a strategy much like you're saying. Joanna Fulford: Yeah. Cynthia Rojas: And so I think some of this is also that data is also a discipline. People get degrees- Joanna Fulford: Yeah. Pieta Blakely: Yeah. [Crosstalk 00:06:06]. Cynthia Rojas: ... and learn about data. Pieta's a researcher, I'm a researcher. And so how do you come into an organization that may not have a researcher or evaluator on staff and get them to the point that they're developing strategies and variables like someone who does this for a living? Joanna Fulford: Yeah, sure. So I guess you're absolutely right. There is this whole professional discipline that's really developed over the last few decades. And there are data scientists and data analysts and people that just can do these incredible statistical pieces of work that are just sort of mind-boggling to most of us. And that's brilliant in a big data scenario where, if you think about the likes of the supermarkets and Amazon and all those sort of things, it's absolutely essential and it's how they're really successful. But in much smaller organizations, there's still everybody has data of some sort. And it's really just about sort of thinking about things from that perspective, rather than data being a bit of an afterthought. So it doesn't necessarily need to be really technical, really complicated. It doesn't need to involve complex systems that require a lot of training and technical knowledge. It's really about simplifying it down to what you absolutely need to fulfill your objectives. So for a smaller organization thinking about, okay, what are the things that we need to do? We need to produce some reports to our funders. We need to mail-merge some letters to people that have maybe made donations. We need to keep track of who uses our services. And so really it's thinking about what is the purpose of data to our organization and then sort of working backwards and thinking, well, where are we going to get that data from? How are we going to gather it? Where are we going to store it? Who's going to use it and get value out of it? How's that going to be done? And so it doesn't actually need to be this professional, technical level of skill. It's just about being really well organized with what you're doing and this is the information that you're working with, and structuring it so that it's going to enable you to do these things that you want. And I actually just, I really, really like working with people that don't have a data management background, because as you said, Cynthia, a lot of people are actually quite terrified of data and think it's this big, scary thing. And just have that sense of dread like, oh no, I've got to do the reports or, oh, our database is a mess. And like, oh, I don't even know where to start. [crosstalk 00:09:40]. And it's just overwhelming. But if you just think about what is it that we do, what do we need in order to do it, and then get into a bit more detail rather than the starting point being we've got this system and we have to fill it with information and keep chucking stuff in. I have a client and one of the lovely things they once said is, "We keep feeding the machine, but we get nothing out of it." Pieta Blakely: Right. And that leads to so many barriers in terms of cultural buy-in in an organization, when staff are being asked to put data into the system, but nothing comes back out. Joanna Fulford: Yeah. Yeah. Yeah. And again, by shifting the focus on to what do we want to get out of this and therefore, what do we need to put in, it then makes sense to people. Whereas typically what would happen is people would get kind of like a CRM system. And then there's 30 boxes that you can fill in and they feel obliged to stick something in every box. But if nobody's using that data, it's pointless. And actually you just need to really, really think about what do we need? What format is it going to be? Does it have to be mandatory or is it going to be a list or is it something that people can type in? Really, really thinking about that level of detail once you've worked out what data you need, and then it all links then directly to what you're going to use it as an output for. So it doesn't need to be technical and scary. And even if you're completely paper-based, like working out in the field, you're not actually using technology in any way, it's still exactly the same questions as to whether you're like a really, really big multinational company. It's what are we using it for? Where are we going to get it from? Who's going to gather it? How are we going to gather it? Where are we going to store it? And how are we going to get that value out of it? Pieta Blakely: You said CRM. So case people aren't familiar with that term. I think it stands for client relationship management. Is that right? Joanna Fulford: Yes. [crosstalk 00:11:58]. Yeah. Pieta Blakely: An example is that you put people in. Joanna Fulford: Yeah. But by the term CRM, I mean the system that people will use to manage their contact records or clients [crosstalk 00:12:07] records. Pieta Blakely: When I'm talking to people who aren't on the analytics side, they spend a lot of time... They look at their CRM from the perspective of the front end and the forms and the fields. Joanna Fulford: Right. Pieta Blakely: And they do tend to put things in. But what you're saying is let's think twice as hard about what we get out in order to put it in correctly. I see this as an ethical issue as well. Every piece of data or information that we are asking one of our participants for, we have a requirement to make sure that we can use it. So this thought exercise is really valid. Joanna Fulford: Yeah. So in the UK, and in Europe, two years ago, we had these new GDPR privacy doors come in and it really, really sharpened the focus. And one of the requirements is that you don't gather personal data unless you have got a specific reason for it. So the one client that I worked with, they just always used to cut people's gender because the box was there in the system, so why not fill it in? And then when we were looking at what are we going to get rid of because we shouldn't be keeping stuff unless we've actually got reasons to use it, they realized that they just didn't need it. They could get an accurate enough sense from just looking at the very gender-specific titles that people might use Mr, Mrs, Miss. Pieta Blakely: Yeah. Joanna Fulford: Strip out all of the doctors and the reverends and all the other ones that could be either or people that haven't provided that information because it gave them enough of a sense. If it's kind of 50/50, 60/40 for the purposes of what they were doing, it didn't matter. [crosstalk 00:14:10]. They'd probably be concerned if it was 90/10, but once a year they could put a little bit of analysis on those titles, get the information they needed. And that was it. That's one less field to have to maintain and store data for and question, if it's accurate and fill in the gaps and all of that. So just even- Pieta Blakely: And even asking the question is complicated. There are ethical responsibilities in how you ask about gender specifically. Joanna Fulford: Yeah. Pieta Blakely: And this approach [crosstalk 00:14:41]. Joanna Fulford: Yeah. That wasn't really an issue like three years ago. That's something that's sort of really, really come along. Yeah. Rebecca Tuttle: It's interesting, you bring up a good point about the collection of data and helping organizations recognize what data is important to collect and what data you can sort of table or do away with altogether. I would imagine as you're helping organizations gain a better understanding of what data they should collect, they are also at the same time, gaining a better understanding and insight into why that data is important, but also how can they move their organization forward using this new data or this information. Do you see a lot of changes in the organization's delivery, following that exercise? Joanna Fulford: I think the main thing is it's around efficiency and streamlining and people having that real sense of purpose. And that then really kind of helps galvanize them in terms of doing a really good job because they don't feel like they're just inputting data and that it's a thankless task, but they really connect what they're doing with the purpose. And it's the why, why is this important? And all of a sudden, it all just becomes meaningful because they know that you've stripped out all of the stuff that is just a waste of time. Pieta Blakely: A theme that has come up over and over and over, probably in every episode of the show is stripping back and going to fundamentals. And we have talked in every context about how particularly right now, in a time of crisis and upheaval that organizations can't do all of the things they did. And it's a time to really examine your mission and think about the most effective way to deliver on that specifically. So it's really interesting to see this applied to our data collection itself. I'm a big proponent of aligning data collection with mission and thinking about our ethical responsibilities when we're collecting information. So it makes complete sense that we would look at our data strategy the same way we're looking at our organizational and program strategies, particularly right now. Joanna Fulford: Yeah. And I think quality is definitely better than quantity and it used to be much more, how many records have we got and how much information do we have? But unless you're using it, then it's pointless and it's much, much better to have a smaller number of records or pieces of information that are really, really watertight and directly serving what you need. Cynthia Rojas: I'm interested in maybe using an example, because I do think that most people are learning it on the job. And so I think an example, Pieta, do you have an example of [crosstalk 00:17:51]? Pieta Blakely: That didn't have a strategy? Cynthia Rojas: That didn't have a strategy and how people work [crosstalk 00:17:57] and making sure we're collecting the data that we want? Pieta Blakely: So here's one example from an organization I worked with years ago. We were having people fill in a long form and we were interested in people's ages. And I don't think a lot of thought went into how we were going to ask about age. We ended up going with a kind of marketing approach where people checked a box if they were under 18 or an older youth category or whatever. And so a few, I don't know, a couple of years of collecting data this way, we had another opportunity where we wanted to target youth under 18 for a specific program. And we knew that we had a lot of youth under 18 in our database, but we hadn't actually asked for their specific age when we put the information in the database and we hadn't asked for year of birth. So now we had no way of knowing if when people put this data in, if they were 17 and a half or 12, when they got put in the database. And so we couldn't effectively go back to this population with this other offering. And it meant that we either had to recruit for this program from scratch or send a message out to all of the people we thought might qualify and get more data from them to see if they did qualify for the program. And if we had thought more strategically about collecting this data point, we might've thought, do we just need to know how old they are right now, or do we want to create a variable here from which we know their age in real time? And what else are we going to do with it? So maybe we want year of birth. Maybe we actually want to send them a birthday card and we want the date of birth, et cetera. Joanna Fulford: That's a really good example. Pieta Blakely: Yeah. Rebecca Tuttle: We have some new viewers. Everyone's saying, "Good afternoon," which says that they're not [crosstalk 00:20:04]. I want to welcome [Baba 00:20:08] to the show from Dakar [crosstalk 00:20:10]. And also we have Thomas, I asked, "Where are you from?" But we haven't gotten a response yet. But they say, "Good afternoon." So we're expanding [crosstalk 00:20:22]. We have a question too, from May. I'm going to show it on the screen, Joanna. It may cover you a little. May asks, "What do you suggest if the data we collect from our schools becomes overwhelming to them?" Cynthia Rojas: That happens a lot. Pieta Blakely: It becomes overwhelming to everybody. Cynthia Rojas: Is it? Pieta Blakely: It's overwhelming to program participants and staff. So. Joanna Fulford: So do you mean overwhelming for the people that you're asking it from or overwhelming for the people that then have to go away and do something with it? Cynthia Rojas: I think that's a good question. She'll probably answer that in her next... So we can wait for that answer because I think that's a really great question. Pieta Blakely: Yeah. Rebecca Tuttle: Evan is joining us from Cambridge, Massachusetts. This is perfect. I love [Crosstalk 00:21:13]. May says, "Both." Joanna Fulford: Okay. Pieta Blakely: Yeah. Joanna Fulford: Again, if you can really sort of think ahead about why you're collecting the data and what you're using it for and then work backwards so that, then you're thinking about the collection point, hopefully that will minimize the number of questions you need to ask and the number of times you need to go back and go and collect the same information over and over again. So we've all been in situations where you deal with the same company or organization or service or whatever it is. And you just feel like you keep filling in the same information. I have it every time I go to the dentist, it's like, I've never, ever been there before. Like no, I still haven't had heart surgery or [crosstalk 00:22:03]. Rebecca Tuttle: Oh, yes. Joanna Fulford: So again, thinking about, so with that kind of example, can we provide them with the information that they gave us before, like a printout of what they gave us before, and then they tell us if any of it is incorrect or has changed since that last time. And it's much nicer to just review through what you've got. And again, with lots of online services now, you can go in and update your profile and opt in and out of things and update what you're interested in or so on. And I think, things like that make it much more sort of user friendly and everybody gets form-filling fatigue. [crosstalk 00:22:51]. And then the people that are in sort of the gathering and inputting, I mean, if you're able to take that kind of approach and looking at where you might be able to use technology or automation to just sort of try and minimize that amount of updating. So think about where are the possibilities for updating rather than starting from scratch every time Cynthia Rojas: I love that. Yeah. Pieta Blakely: And I think a lot of times people feel like collecting the information is intruding on the limited time that they might have with a client or a participant. And they don't want to be data collection staff. They want to do their job. Joanna Fulford: Yeah. And there can be a real resistance to that because people are like, well, that's not my job. I'm not about data entry. That's something somebody else is [crosstalk 00:23:42]. Pieta Blakely: I'm a youth worker. I'm supposed to be hanging out with [crosstalk 00:23:45]. Joanna Fulford: Yeah. And these people show really valuable skills and services that they're offering. And yes, they shouldn't be spending time doing things that they feel are not contributing value, but if they can see that direct alignment through leadership of what you're collecting and why and how it's then securing the funding for your post. It's making sure that you are being consistent with the offering that you're giving to your clients, customers, supporters, whether it is your stakeholders, if they know then that you're able to make really good decisions about who does or doesn't qualify for the provisions that you're making. If they know then that's going to mean that your organization isn't going to get into trouble with the authorities for not dealing with things the right way, hopefully then they can appreciate the value. But yeah, it really is so key to sort of minimize the amount of effort that's required and make that connection all the time with why it's important. Why, why, why, why, why? Pieta Blakely: Yeah. Cynthia Rojas: Yeah. May mentioned that she liked the backwards strategy and it's the mantra that Pieta has been telling us over and over again, to start with the end in mind. Joanna Fulford: Yeah. Pieta Blakely: Yeah, that's right. Cynthia Rojas: And the longterm, right? The future. So I wanted to study where... Talk about date of birth, we had different data points, six months out, 13 months out and 27 months out. And because we gathered date of birth, I could figure out the age at the time of the data point. Pieta Blakely: Right. Cynthia Rojas: And I didn't have to ask how old are you today? And so that made it much more efficient. So looking at the future needs. Joanna Fulford: Yeah. And similarly, if you then can communicate to that person, "Right, so you're 19 now, right?" And they're like, "Okay. Yeah. Yeah. Yeah. I'm really impressed [crosstalk 00:25:53]. Then people can be really reassured that you're using their information well. Cynthia Rojas: Right. Rebecca Tuttle: [crosstalk 00:26:02] you're getting to know them and you care for them. Cynthia Rojas: Yeah. Rebecca Tuttle: You're not just another person in the door. This reminds me of the saying, stay in your lane, know what you do, know what you're about, serve the people to the best of your ability in the lane that you're really driving in. Don't just apply for funding and say, you do this, this and this when you really maybe do a fraction of it here, but you're primarily focused over here. Stay in your lane, stay where you're focused and do it really well and use your data to do it really well, but also show your community how well you're doing it. Cynthia Rojas: Yeah. Organizations could reframe how they think about data because there is nothing more powerful than getting up in front of people and saying, my program works and we know this because of X, Y, Z, [crosstalk 00:26:51] from the numbers. And that's such a powerful stand. Yes, the stories are important. But also when you have data that can show the proportion of people who are improving their lives because of your services, you have an extraordinary program. And standing up in front of people and telling that story is just amazing and extraordinary. So, that's reframing. [crosstalk 00:27:17]. Go ahead, Pieta. Pieta Blakely: That's the goal, I think particularly with economically disadvantaged and minoritized populations and people who are vulnerable, they spend so much time filling in forms and it feels like a barrier and a gate. So the more that we can reduce that- Cynthia Rojas: Right. Pieta Blakely: ... I think it goes to really treating people with dignity, as Rebecca said. Cynthia Rojas: Yes. Rebecca Tuttle: [crosstalk 00:27:44] minutes in, I just want to be mindful of the time. Pieta Blakely: Joanna, right now, right, our organizations are in crisis or transition. There is a light going on. Is right now the time to think about data strategy? Joanna Fulford: I think a lot of organizations obviously sort of really having to sort of really focus and prioritize what are the most critical things we should be doing that our clients, beneficiaries, stakeholders really, really need the most? And again, I just think it's absolutely critical that if you're sort of having that refocus exercise back it up with thinking about more, how is data going to enable us to get to deliver that as quickly and efficiently and as consistently and as accurately as possible? Because I think if you don't do that, then it's really easy to then end up sort of floundering around, not really sure what you should be asking people and what you should be recording in your system. And then you haven't maybe thought about your sort of really key area, but really thought about how you're then going to say, we went through this really difficult time, we refocused. These are the things that we really focused on delivering. And we went from this to that. We unfortunately had to sacrifice these things, but as a consequence, we were able to make this really dramatic impact in this area. Cynthia Rojas: Great. Joanna Fulford: So yeah, still thinking about the data. Just pare it back to what you really, really need. Pieta Blakely: Yeah. Cynthia Rojas: I love that. I love that. Pieta's been telling us that since day one, so thank you for validating that, Joanna. Pieta Blakely: I'm glad we brought Joanna on [crosstalk 00:29:38]. Joanna Fulford: I think that's why I got invited on the show. We're singing from the same song sheet. Cynthia Rojas: Yes. Yes. Pieta Blakely: Yeah. Cynthia Rojas: It's been awesome. But it's great to hear it from someone else. Pieta Blakely: Yeah. [crosstalk 00:29:46]. It's great to hear it, right, in such a concrete way. Cynthia Rojas: Yeah. Pieta Blakely: I think that's really helpful. Cynthia Rojas: All right. Pieta Blakely: So Joanna, if you wanted to leave people with one takeaway or one thing that they should be doing right now, where would an organization start? Joanna Fulford: I think the really sort of key point, the key takeaway is always think about what you want the output to be. So whether it's reports, whether it's mail-merged letters, whether it's analysis, start on that end point and think about how does that actually need to look? What needs to be included? And it can be really, really useful to actually draw it out. So if you say, I want to have a chart that shows the number of people that have used this, draw it out, that you're actually showing how you want the data to look, because that really helps you then, helps inform how you're going to gather and store it and record it. And if people want a bit more sort of information, on my website, I have a free introductory course about data strategy. And it basically just, it's a bit of a reminder of what a data strategy is, reasons you should have one and what typically would be in one. And it's really for small organizations. If you go through those materials, it'll take you about an hour, it's little videos and some downloads, I think for small organizations, you'll have all the information you need to then be able to sort of think about data from that slightly different perspective. Creating a data strategy for a small organization really doesn't need to be a big, complex technical thing. It's really about how are we going to manage, how are we going to organize ourselves to make sure that our data is supporting us in delivering our mission. But the course just kind of takes you through the different things to think about, sort of questions to ask so that you're geared up for what you need to do and know where your areas of weakness are. Cynthia Rojas: Great. Pieta Blakely: We've got a link to that course under this video, on all our platforms. Joanna Fulford: Okay. Pieta Blakely: It's very useful. Cynthia Rojas: All right. All right. So I have a ton of takeaways, but one sentence that sticks out for me is when you said there are organizations that say, I keep feeding the machine, but nothing comes out. Love that. Love that statement. Thank you. Thank you. Pieta Blakely: Yeah. Wait, I think my big takeaway is that, once again, it's data in service of the program and program delivery, but how much more thoughtful we should be about every data point. And it seems like a lot of work on the front end, but it's all in service of creating a data point that is really useful ultimately to the people that you're serving and to your programs. Joanna Fulford: Yeah. Cynthia Rojas: Right. Joanna Fulford: It's a different way of thinking and a different emphasis, but once you've cracked it, it then simplifies things massively. Cynthia Rojas: Great. Pieta Blakely: Yeah. Cynthia Rojas: Rebecca, your takeaway? Rebecca Tuttle: My takeaway is there are several reasons why we collect data. We collect data to test things out. So don't be afraid to collect data and test something. Pieta Blakely: Yeah. Rebecca Tuttle: We collect data to address challenges and find solutions. And we also collect data to demonstrate our success. The more you can understand about data, as Joanna was explaining, the more you can put it to good use for one of those areas of why you're actually collecting it and using it. Cynthia Rojas: Awesome. All right. Well, we are a couple of minutes over. We've come to the end. These conversations can always go on forever, but we do want to start our weekend or our day for those of us who are just starting their workday. And we'll see you next week, same time, same place. Thank you, everyone. Pieta Blakely: Have a great weekend. Rebecca Tuttle: Bye.