On this episode of the RKD Group: Thinkers Podcast, we’re excited to sit down with Steve MacLaughlin, an accomplished leader in nonprofit technology, serving as Vice President of Client Success at SJ Consulting and author of the book, “Data Driven Nonprofits.”
His thought leadership has been featured in publications like The Washington Post and The Chronicle of Philanthropy, and he’s a regular contributor to discussions on how data and innovation shape the future of fundraising. In addition to his industry roles, Steve teaches at Columbia University and has served on the board of NTEN, furthering his commitment to advancing nonprofit impact.
In this conversation, MacLaughlin discusses his experience working with nonprofit organizations and the role of technology in solving problems. He emphasizes the importance of data and the need to turn data into information and insights. MacLaughlin also highlights the cultural challenges of implementing data-driven strategies and the resistance to change.
He shares:
Justin McCord
Okay, so I said that we should have hit record earlier. So I'm just gonna repeat the starting point that I, whenever I jumped on Steve, like, does it feel different or the same being like, back in this sector proper from your brief experience out of and now back in?
Steve MacLaughlin
I feel like I didn't really leave the sector. I've been working with nonprofit organizations for probably 20-plus years now and in various stages of metamorphosis career-wise. And then most recently, I've been really just focused on the higher education sector, which is its own little interesting animal in the ecosystem. But yeah, it's great to be back working every single day with nonprofit clients from a slightly different perspective.
I started out my career in consulting back in the late 90s, early 2000s. A lot of online, a lot of digital, was supposed to go to law school, took a left turn at the internet and spent a lot of years in that world. And I had some for-profit clients along the way, but I had some nonprofit organizations too. So, except for some tax status things and other nuances, similar problems, similar challenges, right? How do we achieve what we're trying to get accomplished? And really, what I've been focused on for most of my career is what's the role that technology plays in that? How do we solve a problem or take advantage of an opportunity using technology?
Justin McCord
Yeah.
Steve MacLaughlin
That's really what I think I've … yeah.
Justin McCord
What was that, what was that left turn at the internet?
Steve MacLaughlin
Well, Al Gore invented the internet, and then suddenly you just have a whole new way of being able to communicate and engage with people that didn't exist before. And so, I was supposed to go to law school. But when I was at college, I stumbled into this thing called the internet and started building online websites, learning HTML, all that stuff. And that just exploded, took off in ways that I hadn't expected. And I had a point somewhere along the way of it was to go to law school and forget about this internet thing and whatever. Had a job offer, I go work for Accenture in Chicago, which was with an obscene starting salary because I knew what I was doing, and they were trying to take advantage of this online stuff, but just ended up doing a lot of online web work late 90s, early 2000s, including some work with some nonprofits.
Spent some time working in higher education, went back and got a graduate degree, all that fun stuff. And then spent over 18 years at Blackbaud but working with nonprofits of all different shapes and sizes around the globe. And it was a lot of learning experiences. It was a really great experience.
Ronnie Richard
You called it a metamorphosis of changing roles in different points of your career. And for our listeners, I just want to run through some of them. You've done online design for websites, like you were just describing. You've done project management. You've done data and analytics. You've been in products. You're in client success now―all these different roles, all these different changes as you were going through them and each time learning, probably, some new processes, learning some new ways of doing these jobs … which, what were some of the things that challenged you along the way as you were trying out these new roles and moving into these new duties that you had?
Steve MacLaughlin
That's a great question. I mean, just being comfortable with being uncomfortable. You know? It’s true today, especially when I think about all that's happening with artificial intelligence. A lot of this reminds me of the early days of the web and digital―a lot of throwing spaghetti at the wall, trying to figure out what works, what doesn't work. You're making up as you go along.
You ultimately fall back on, I think, certain principles that you know work, right? Whether you're managing a project or you're trying to solve a problem. It may be new technology. There may be a lot of unknowns. You may be still trying to figure stuff out, but you still go back to, what's the goal? What's the objective here? What are we trying to accomplish? OK, let's that be our North Star for what we're trying to accomplish. How are we going to track our progress against whether we're being successful or not? So none of that's new. I mean, that stuff's been around for decades or hundreds or thousands of years in some way. We're just applying it to new technology.
I think the other thing I learned along the way was personally figuring out what am I good at, and where can I hire or bring on people who are better, smarter, faster at these things than I am, right? I started out building and designing websites, than I hired designers who were infinitely better designers than I would ever be, or developers who were better developers than I ever would be. And I could focus more on what are we trying to accomplish? How are we driving that outcome as opposed to hands-on keyboard, writing code? I know what the code looks like. I know how it operates. I know how it works. You don't want me getting anywhere near that, but do I understand it enough to figure out we’re doing what we're supposed to be doing? Is this going to be successful?
And similar, when I did a lot of work with data and analytics―we weren't supposed to talk about this topic, but I'll bring it up: So I'm a D-calculus student. I have no business dealing with all the data and data analysis stuff that I've dealt with in my career, strictly speaking from a mathematical perspective. But I've worked with data scientists who absolutely like … you I know what a regression is. Data scientists know how to run that, know what endogeneity is; know where you get into problems with data. I can't fix that with my hands on a keyboard, but I understand it enough to know, when I'm talking with data scientists or talking with analysts, how to guide and how to direct them.
So I think part of it was knowing enough about the subject matter to have street cred with the people you work with, but you know, but I can't do it, right? I can't build a data model with 18 different variables in it and, you know, produce the right outcome. But I can help guide a group of people to get to that destination. And I can ask questions about how do we know? How do we validate it? How do we know for sure this is working? So that's been one of the key skills, I think, over the years to pick up, right? Have a natural sense of curiosity. Like, really be very curious about how does something work? How might we get something to work? I used to drive my professors in grad school crazy because I was always trying to take the theory and apply it. Wow, that's an amazing theory. Someone did a research study on …. How can we actually apply that? And that's pretty much what I've been doing for the past 20-plus years is, that's an interesting idea. Let's find out if it works or not. How would we test it? How would we apply it? How do we adjust and move on from there?
Justin McCord
Yeah. The, I find it fascinating, your admission of your calculus grade and calculus cred. But then also, I gotta tell you, when I came into the sector, close to a decade and a half ago, you were one of the, at the time, early, for me at least, early thought leaders that was … you had a very public persona around data and analytics. And it was easy for me to see that persona and think, man, this dude is the wizard on the keyboard. And so I just love the idea that, as you're saying, maybe a little bit of your superpower that you have honed in over the time has been being the person to connect and translate and tie together versus being the person in the connections and in the translations, that kind of aspect. You published your book, “Data-Driven Nonprofits,” in 2016. You're almost a decade past that book originally being published, which is probably a thread that we can go down. What's changed since then, since 2016?
Steve MacLaughlin
Wow, that's a great question. What's changed?
Let me start with what hasn't changed, and then I'll switch gears and actually answer your question. So, what hasn't changed is data is still an immensely important asset for nonprofit organizations. And the only reason I wrote that book was no one else had tackled the subject in a way that would work for nonprofits. So the more work I was doing with data and analytics, asking, you know, what would you read? What would you, how would, how would other people figure out how to embrace this more? And there really wasn't anything. And so that's partly what led to, to writing the book and some things that just haven't changed since then. It's, data is still important, and it's in a lot of cases undervalued or underappreciated by organizations, and you don't have to be a data scientist, and you don't have to be someone who writes your own algorithms and does your own models to be able to get value from it.
From a leadership perspective, whether you're a leader of a department or a team or you're the executive director or the CEO of an organization, it's more now of how do you understand the potential for data and what it can do to help lead to insights in your organization's breakthroughs? And then, how do you create a culture that makes it work? That would be, so the data, so the thing hasn't changed, data is still super important.
Two, one of the big conclusions from the book is there's no secret sauce over what makes organizations really successful, the use of data versus those that struggle, other than a lot of it just comes down to organizational culture. Are you in a culture that thrives on change, experimentation, getting to the right results? That has not changed, right? What's the old adage from …
Justin McCord
Yeah.
Steve MacLaughlin
… Peter Drucker: “Culture eats strategy for breakfast.” Still true, right? That has not changed. What has changed, or if there was an updated edition or even in some of the updated talks that I do these days based on some of the content from the book, is I introduce the fact that we now need to move from just looking at the data to turning that data into information and turning that information into insights. Like we've got to ...
Justin McCord
Mm-hmm.
Steve MacLaughlin
… we’ve gotta level up, right? The book was about how do you get to the base level of where you and your organization need to be now. We need to move beyond just the data. We've gotta move to turn data into information and information into insights. And then, obviously, the second big thing is the artificial-intelligence whirlwind that we're living in.
Justin McCord
Yeah.
Steve MacLaughlin
You know, I've talked about this in the past, AI is not new. There's experimentation with AI that goes back to the 1950s where they were translating languages. It's just … and it's gone through a bunch of dips and dives and peak of inflated expectations. And here we are now, right? We're 20 years past Clippy. Clippy was AI―crappy AI, but it was, it was AI. Now if you look around the world we live in today, it's all the digital assistants we live in; it's all the language translation; it's the things like ChatGPT. AI, obviously, is a big, is sort of a bigger inflection point that we're living through right now. Although I believe we're approaching the hype peak of inflated expectations and …
Justin McCord
Right?
Steve MacLaughlin
… if this is like any other technology curve, we're gonna go ride the downslope for a little bit where people will say, well, I thought AI was gonna solve all my fundraising problems, make my grass greener and allow me to achieve my goals and objectives. You know, this stuff's crap; it's not working. Likely because we've inflated the expectations for other reasons we could get into, but, but AI is an inflection point that we're at today, for sure. Ultimately, AI, any type of artificial intelligence, whether we're talking about machine learning or large language models, it's all based on the fact that you feed it a lot of data, and it develops patterns, and it does things. And so, we still come back to, at the end of the day―I was just saying this to some clients last week―at the end of the day, no matter what happens or doesn't happen with AI, it's going to be the quality of the AI is based on the quality of the underlying data, right? You get bad data results in bad robots. We get the Terminator because of bad data. If we get bad AI in the nonprofit sector, it will be down to bad data in large part.
Justin McCord
Yeah. Yeah, the man … first of all, well done on the Drucker reference. I don't think enough people live off of that in the way that they think about their organizations. Like, it's so, so true that culture eats strategy for breakfast over and over and over. Something that I find interesting I would love your take on is, you're right that data and data culture, like, the need for that has not changed. Data has evolved, and now we have a better sense on structured data and a massive amount of unstructured data in so many different areas. Like―and now I'm thinking about specifically in the way that a nonprofit goes to market in their fundraising efforts―all the unstructured data that lives in point solutions, and on Post-it notes on people's desktops and like, all over the place. And so it's like, in some ways I feel like we haven't figured out how to even be our best at data culture because data has evolved and spun out into so many additional forms of usefulness now, and we're still trying to figure out like, the foundational forms of the structured data that we do have around transactions, and demographics, and promotional history and those sorts of pieces.
Steve MacLaughlin
Yeah, there's a lot of time today still spent on the highly structured data. You know, the, where did that data come from? What's the quality of that data? How are we using it in reporting? How are we using it in segmentation? How are we using it to determine who do we engage with, at what time, using what channel, and what was the result, that you're right. We, we spent a lot of time doing that that prevents us from getting into the unstructured piece, which was, you know, what's the tonality of our messaging and are there certain types of supporters where this tone resonates better than other things that we've tried before? In some ways, AI technology can help answer those questions, for sure.
And with a lot of these things, right, technology is no longer the limiting factor. You know, this isn't ... we're not talking about flying cars, and food pellets and the Jetsons here. We're not talking about things that are some futuristic world that you should imagine and wait for. Most of this is with us today and, in fact, in many cases has been around for quite a while. It's just, you know, certainly―and I see this today, you know, in SJ Consulting where there's not a day that goes by where I don't work with a client about some project that we're working on. And I see a little bit of the other side of the fence, which is all of these organizations are enabled and powered with amazing technology, but they still just have a lot of things that they're trying to accomplish. And sometimes it's a challenge, right? How do we, how do we … we have all these things that we need to do. How do we prioritize our time, our resources, our effort to focus on the things that are likely to yield the best results? And that's often easier said than done, despite the fact that we’ve all of this technology. There are still limitations to how much change we can drive or how much time or energy we can put into any one of our initiatives.
Ronnie Richard
Do you think the reception of the message that you were putting out in the book about the importance of data and the importance of it in the nonprofit sector, has the reception of that message changed? I feel like we all know now the importance of data; that back when you wrote that in 2016, that, did you feel like that was a message you had to get out there and tell them that, hey, you need to pay attention to this? And now it's more, I'm glad you're paying attention to this, now let's take it to the next level?
Steve MacLaughlin
It could be a bit of that. I, I was … the audience for the book was not the person who was already a member of the choir and already could, you know, sing all the notes and knew exactly that this is what had to happen because that's, that they already know it. The audience was those who don't understand this, are confused by it. To understand it better, I mean, one thing I think―Justin, you touched on this―if there's one superpower skill I've developed over 20-plus years, it’s how to take really complicated, gnarly concepts and simplify them for people to understand because that's what I have to do with it, right? I take these complex things, man, this doesn't make sense. How does this work? How does this work? That's how this works. Gotcha. Because again, trying to translate in non-technological terms to the rest of us is really valuable, especially when, you know, decision makers, people who are in leadership roles, they're not, it's not tech savvy. Like, we're all tech savvy. That's over; that term's overused. It's just having a sense of how do you connect the dots? Like, why? So what? Who cares? Steve, why does this matter? And so, even to this day, taking simple examples of, well, yeah, I hear what you're saying, but I'm not convinced all this stuff always matters all the time.
Justin McCord
Yeah.
Steve MacLaughlin
And so oftentimes, you've got to quantify it in stories that resonate. And the one I use to this day is still, does misspelling your donors’ names make a difference? Don't know. We should go find out. Well, it turns out, we did some research, and we found out that when you misspell donors' names, you lose 10% of them through retention. And those who keep giving to you, despite the fact that you misspell their name, give you 12% less. Now, somebody finally wants to have a conversation about the quality of data, and typos and how do we do a better job. Because now I suddenly know what it's costing me.
And with a lot of things, it's a fair statement. If you can't tell me how this is helping me or how this is costing me, I got a lot of other stuff going on, Steve. I got to move on to another top. Now suddenly, wow, that's a lot. And that's a totally curable, totally preventable thing. But it's a culture thing because there's no vice president of typos at your local nonprofit who makes sure that all this stuff gets done correctly. It's everyone's job, which is a cultural thing.
And so, that's just one example of when you paint that in a very understandable, graspable, whatever the word is, story that's based on real, true research, then people are like, okay, wow, got it. And then in terms of what else, okay, we fixed typos, pay attention to that. What else would we do that maybe we're not doing today?
Justin McCord
The totally with you on it. I think it's funny as you're sharing that just about even, like, typos. We had an event in the spring that we did, and we brought clients together, and we brought other industry folks together, and we had a block of hotel rooms, and, and we had a member of our team who had organized those hotel rooms and had been working primarily with the, the hotel, and we had some important guests when they checked in. The beginning of their experience was jarring because as they got into their room, it didn't say, “Welcome, Steve” on their screen. It said, “Welcome, Pam. Like, it had the member, it had our team member's name. And it's so interesting, like, it was such an important event that, even out of the gate, we were putting ourselves at, at some level of quantifiable risk by something so small.
And as you're talking about it, man, I just can't help but think that the way that we get better today around data focus is the same as it was in 2016 or in 2006. And we still haven't figured it out. And it's about, like, focus. Like, to your point about, you know, a leader who's making decisions, and they don't need to be under the hood, inspecting how a carburetor is performing. They need to understand the insight from said performance so that they can make whatever decisions that they need to make. Someone else needs to focus on the performance of the carburetor. And it seems like there may be, in our exceptionally pressure-packed sector at the moment, that it may be more difficult to focus on enabling data culture than, than it ever has been.
Steve MacLaughlin
It could be, you know, the word culture, admittedly, has a lot of weight placed on it. And even there, I would simplify culture as beliefs, habits and routines. Culture is what happens when no one's looking in your organization. When no one's looking, do you make sure that the gift-entry process is solid? Do you make sure that the stewardship and acknowledgement is working the way it's going? Do you do these things when, if no one was looking, would you still do it this way? That's at a high level of performance. And there's ways to check on that. Like that's, you know, those are the things you've got to look at across the board.
And I think part of it, too, is just, you know, the ability … there's so―this is true of every organization, regardless of your tax status, right?―there are lot of organizations where decisions are made based on personal preference, right? Sometimes we call this the hippo problem, the highest paid person's opinion, right? Why is the newsletter purple and green, and why do we do this this particular way? Well, because the hippo, you know, writes the checks and signs the checks. And so, we just go along and get along. And so, we just do it this way, right? We've always done it this way. Or someone has said this is how they want it to be done. So a lot of it is driven by personal perspective. And the element the data brings to this is that we actually have some statistically significant proof about what works and what doesn't work.
And I'm sure you've seen this. There are a lot of things in the sector that are still driven by, well, this is how we do it, right? Or―and one of the things I did when I wrote the book was, because I'm a bit of a history buff, I was digging back into like, why does modern fundraising work the way it works? Well, it works the way it works because of how it was largely designed and invented in the early 1900s.
Justin McCord
Mm-hmm
Steve MacLaughlin
And except for the fact that we've added technology, most of the practices come out of early 1900s philosophy, right? Set a goal, be data-driven, engage with people, follow up, have a clear mission statement, organize things this way. Like, that's not new. That's over 100 years old at this point. What's new is we have the technology that enables us to say, well, is that working? Is that the best approach that we should potentially take, or perhaps we should look at the data to inform our decision making? I'm not saying turn all the decision making over to the robots, but at least use data to inform our decision making to say, should we continue to do something in this way just because we always have versus taking a look at what does the data tell us? And I'll give you a ...
Justin McCord
Yeah.
Steve MacLaughlin
… perfect example I've been talking about a lot lately with clients and when I speak and do workshops. So, I've lived through this; I'm sure you have too. There's been a raging battle for 20 years over online versus offline. And it's usually jets and sharks. It's the offline people versus the online people.
Justin McCord
Yeah.
Steve MacLaughlin
And you show me your organization chart, and I can probably show you where the dysfunction is or why this isn't working. But, as it turns out, the online versus offline argument largely is pointless. The retention rates for both on first-year donors are bad. It's just bad, right? And so, if you do a little bit of research or, maybe treat my own here, if you take the data, turn the data into information, and push it a little bit more and get to an insight, what you would find is having discussions about online versus offline are almost entirely, we're talking about the wrong thing. That if we're looking at how, if the problem that we're trying to solve is how do we dramatically improve donor retention, then just looking at online versus offline is looking at the wrong thing. It turns out, there's something else in the data that has a much more profound difference, which is looking at the difference between the ways in which people give, not the channels they use. Because as it turns out, the channel of engagement and the channel of transaction is largely irrelevant when it comes to donor retention, right? The thing we want to achieve. And so, what the data reveals is we should really be having a conversation about single-gift versus recurring-gift donors because recurring-gift donors have a first-year retention rate in the 70%, and single-gift donors are still stuck in the 20%. That's a pretty big gap. That's a gap enough to say this isn't happenstance, and we're not talking about the difference between pink paper and brown paper. We're not talking about the difference between online versus offline. That's a big Delta. Something must be happening here.
Justin McCord
Yeah.
Steve MacLaughlin
And yet we'll get into a cultural battle where an organization will say, I only know this single-gift world. That's the world I came from. That's all I know. It's all I know how to do. You're now, in coming in here, Steve, telling me we need to build out a recurring-gift program. I don't know a whole lot about that. Therefore, I don't want to change. Despite the fact that the renewal rate, the lifetime value rate, all the metrics that you would want to be in positive territory are astronomically better recurring donors. I'm going to just stick to what I know.
Justin McCord
Mm
Steve MacLaughlin
Like, that's where all this stuff comes together, right? Where it's a cultural issue; it's a data issue. And yet, when you present people with these facts and you say the discussion is no longer online versus offline, no one cares. It's largely irrelevant. You're doing a crappy job at both either way. What you probably should look at in the data is the fact that building a recurring-gift donor program will …
Justin McCord
That is ...
Steve MacLaughlin
… yield all these positive benefits, but the one side effect or one catch is you're likely going to have to change how you operate today, how you do things today. And that's scary. That's uncomfortable to people, especially if, you know, cranking the machine and just knowing how that machine operates is all you really, really know. It can be intimidating, for sure. Yeah.
Ronnie Richard
Yeah, it's, it's a big cultural change, and it's a big change in a lot of different ways because even thinking about how you budget, you know, we, how we talk about budgeting now often is, this amount goes to online; this amount goes to direct mail versus let's think about how we're budgeting to reach new donors. How are we budgeting to talk to recurring donors? Right? I mean, it's, it's a whole, I mean, almost, I don't want to say blow up the system, but it's, it's a big rearrangement, right?
Steve MacLaughlin
It definitely can be a big rearrangement, especially, again, if you're just not organized, from leadership to everyone who works on this stuff, to be clear about what is it we're trying to achieve here, and what are the tools that are available to us that we're going to leverage to drive that result? And yes, there will be change, and yes, we will make mistakes, and yes, occasionally we will get it wrong. But we can look at the, we can look at the reports to tell us whether or not we're achieving a better outcome or not. Otherwise, and again, look, I'm well past this. I can write as many pages as I want. I can do lots of talks. I can do podcasts like this. This is fun. I'm under no illusion or delusion that everyone will listen to this, and everyone will immediately go and do these things because that's not how the world operates.
But there will be organizations, there will be somebody out there, who hears this, or reads something or picks up on something from a talk and says, you know what, I'm gonna try that one thing, see if that works. And that's forward progress. And certainly, you know, there are organizations who run amazing fundraising programs today who know a lot of this and are doing this stuff today. And oftentimes, those are the ones that I look to to find out where's the innovation happening? What are the organizations who already do an amazing job at a lot of this? Those are the ones I love to talk to, to find out what are you guys experimenting with right now? Well, we're trying this to see if, okay, because likely that is a, that's a next practice that 10, 15 years from now probably becomes best practice because someone's already out there trying to attempt to do it, right? But it's based on the results, right?
Justin McCord
Yeah.
Steve MacLaughlin
And that is, I think, a definite thing that's changed in the past decade is a much more higher focus on let's measure the performance of how something works and decide whether we should continue to do it or whether we have to pivot and change direction.
Justin McCord
Steve, I don't know, I kind of want to believe that everyone that listens to this is going to immediately change how they budget and how they think about data. I don't know if it's on your radar, but whether or not you do an updated version of the book as you hit a 10-year mark or you create a podcast that is the updated version of the book, I just want to exhort you to continue beating the drum because it matters. And we're thankful for the leadership that you've had in the sector over these past two decades and continue to have now, visiting with individual organizations and helping them see that vision.
Steve MacLaughlin
No.
Justin McCord
This is our own point of inflection. And so, it's an important moment, and we're thankful for your part in it and for you to spend some time chatting with us about your journey today.
Steve MacLaughlin
Yeah, really appreciate it. No promises on new books or anything else, but absolutely will continue to be a champion for ways that organizations can improve. And I get a lot of both personal and professional ... do that drum solo in a second.
Justin McCord
Well, you got a lot of fellow drummers, right? And so, we're creating our own little, I don't know if it's a drum line because we tend to be at different parts at different times, but I know that we take a lot of solace in knowing that there are other folks that share that same spirit and passion for the progression of what we're doing and how we're doing it.
Steve MacLaughlin
Hahaha.
Justin McCord
Good to catch up, man. We look forward to, yeah, for continued conversation on this, and we'll talk to you again soon.
Steve MacLaughlin
Yeah, same here. Appreciate the opportunity. All righty. Thanks, guys.