Podcast: From Spoke To Hub – Derek Drockelman On Data’s New Role

Listen to Podcast

Our podcasts are designed for audiences with varied experiences with technology. In this podcast with Ryan Ozimek and Ryan Singh on the rise of the AI agents, learn more about how to lead nonprofits by understanding new technologies as they emerge, and how those new tools can fit your use case.

Like podcasts? Find our full archive here or anywhere you listen to podcasts. Or ask your smart speaker.

Transcription

Kyle Haines: Welcome back to Transforming Nonprofits. I’m Kyle Haines with Build Consulting, and in this episode, I get to talk to Derek Drockelman. Derek and I have known each other for decades, and for about a year, we’ve been having conversations about how technology is becoming less important and data is becoming increasingly important.

We’ll get into that a little bit more in this episode. I’m really excited for you to learn more about how Derek’s thinking about data, and I did ask Derek to keep this conversation to PG-13, and Derek did remind me of what’s included in PG-13. So, there’s a couple of expletives along the way, but they’re all in service of our energy and passion for this topic.

With that, let’s get into the conversation. Thank you for joining Transforming Nonprofits.

Derek, I don’t know where to start this conversation. You and I have known each other for a long time. And I think it’s important context for the conversation I wanted to have with you. You and I both started at Blackbaud, which at the time was a really small company. It’s now a big behemoth of a company that we could probably do a different podcast about our thoughts on Blackbaud.

You now work for Roy Solutions, which you can do a much better job talking about what Roy does, but you know you’re not allowed to in this podcast.

Derek Drockelman: Right. Yeah, exactly. I’ll keep it generic.

What we talk about can work on any platform, any solution. Well, except for maybe some, but I won’t name them. How about that?

Kyle Haines: You and I have been talking for, it feels like more than a year, about this idea of data and about this future in which data becomes much more important than a single application. And what I wanted to talk to you about today is to try to bring some of the conversations that we’ve had in the past, hopefully make them cogent and understandable for the audience. And really explore this idea of maybe, and I didn’t even think of this until now, a post app future, where did I coin something new or did I just rip you off for something you’ve said?

Derek Drockelman: No, you didn’t rip me off. No, it’s so funny, because I’ve had so many of these conversations about data platform as a hub, thinking about your data as its own entity, that everything orbits this big cloud of data.

It’s always fun at a conference or group setting to see people jump ahead to basically the post app world where they’re like, so basically, I want a headless CRM. I want all the data and I want a way to query it or ask it, basic language questions. Tell me about Kyle Haines. And my little bot friend, my little Wally, Wally will go in and grab all the cogent information about that person.

And so it’s funny that a few conversations I’ve had have now started to go to that app-less or headless CRM future, which I’m not willing to say that we’ll get there in the next couple of years, but when you think about throwing AI and query at this big cloud of hopefully organized data, it starts to feel like something that could actually happen, which is kind of cool.

Kyle Haines: Yeah. And for listeners, I think we jumped into this idea of a post-app future. I think what you and I are talking about is we can see a future in which it’s less about what the app, how the app structures data and displays data and shows data and can it capture this data, and how do I bring survey data into this app?

Apps do the things that they do best, and there’s a centralized data platform where you’re getting answers to the questions about individuals or groups or the entire data set in a much more agnosticized way. Is that your definition too?

Derek Drockelman: Yeah. Yeah, it is. And I think you and I have talked about this, about CRMs and ERPs becoming secondary to the data, right? I think we’ve all been following the CRM as the hub model for a while, right? And I think we’re finally in a position where technology allows us to flip that. At our time at Blackbaud, right, when we were consultants, it was if it wasn’t in the razor’s edge, it didn’t happen, or in Blackbaud CRM or Salesforce or whatever, right?

And that was a smart direction, right? And that’s actually before you called anything a CRM, right? It was the fundraising database or depending on kind of where you lived, and it made sense to try to get all that data in one place to get at it.

But I think in many cases, and I think especially a lot of the larger organizations, we’ve been using CRM almost as its own data warehouse, and we’re turning the CRM into a data swamp. And I get RFPs, you work with people to make selections, that kind of thing where they come in and say, I would prefer one platform to do everything, right?

I want it to do my fundraising and my case management and my medical record stuff and program like everything, right? And I just don’t think one platform exists that can do everything. Maybe if you’re a smaller organization, that exists.

But, you know, again, CRM, Montero, Blackbaud CRM, Salesforce, Virtuous, none of these, and even our own Revolution CRM, we can’t pretend to do it all. Because you’re always making some kind of, I think, a requirement trade-off of, well, we need to put more weight on the digital. We’re willing to take a little bit less over on this other piece of the business, in the interest of getting everybody to one place.

But I think if you get into a world, right, and, you know, whether you want to call it a data platform or data warehouse, data lake house, data lake, you know, everybody’s using kind of fairly different terminology sometimes to mean the same thing. If you have the ability to get all of that data there, I mean, I think about all the information, all the data I used to dump into attributes in a Blackbaud world or in custom fields in a Revolution CRM world or in a Salesforce world. And you’d get the data there, but it was unusable.

And so you’d get it in there, and then you’d have to get it back out and do some kind of a lookup or, you know, kind of tabulated kind of a spreadsheet so that you could actually work with it. And that just gets, you know, really difficult.

So if, I guess my vision is right, that you’ve got this warehouse, think about it, this lake house, data platform, think about it as the center of your universe, and the CRM is orbiting that, and all of your digital tools, and all the other point solutions that you have, and they are looking at and considering and consuming the data that’s required to do the job that you’re trying to do in each system.

We’ve spent so much time – I’m getting a long winded, I know – trying to replicate data from point A to point B. And there’s always some degradation of that, and you’re using different duplicate criteria. And I’ve worked with so many organizations where you end up stomping good data with bad data coming from another one. I think you can put more rigor around that in a data-centric kind of world.

Kyle Haines: Yeah. And you touched on this. I think it impacts one of the questions I had is— or maybe it’s an observation.

There’s a question layered in there, is that so many of our projects historically have been about identifying all of the requirements. So this CRM swamp—I love that term— can hold every single piece of data and do every single thing. And it’s reall, there’s been tradeoffs and costs associated with that, costs associated with maintaining data and bringing data in, cleaning it, deduping it, all of those things, that it never really does a good job of that.

It does an okay job of that.

Derek Drockelman: It does an okay job. And it’s always going to be slightly better okay for one group instead of another. There’s always somebody that’s paying the price for landing on that does-it-all kind of platform. And it’s all about kind of how you weight the problems that you’re trying to solve, right, when you’re making that selection.

I get into so many conversations with folks where they’re like, look, we know that we’ve got a data problem. We know we have a lot of different point solutions. We know we have a pretty deep stack of stuff. We have all this data. Like, we just don’t even know how to get started in coming up with an actual strategy to think about it in a holistic way.

I think there are always clients that are going to approach something like this as a technical problem to be solved. It’s like, I want my shiny thing. I want to get all the data together because then I’ll know what to do with it. And some organizations can do that.

And, you know, we have our own data platform, and I’m finding that about half the organizations that are using it come in with a fairly decent idea of the questions that they’re trying to answer, or the insights they’re trying to divine from the data. And it is for them a technical project because they’ve never had an opportunity to get all the data together to knit.

There are other organizations, though, where they say, you could solve the data technical problem for me of pulling it all together, but I would not know what to do with it. I would not know. We do not have the people here that know how to think about it, who know how to analyze it, who know how to divine insight from it.

And so a lot of what I do with folks is try to figure out kind of where are they in terms of having an overall data strategy in the organization, or at least do you get along with others in the organization so that as we’re talking about getting all this data together for this magical, holistic view, is it something that’s even feasible politically? You know, it’s your organization. Let’s take baby steps when it comes to, you know, developing a data strategy.

I kind of start with what’s the data that we have. Inventorying that, what’s the data that we want or we think we want? What’s the data that we need? What do we think that’s going to give us? What’s that going to tell us? And then the data to act.

All right, once I’ve answered that question, what am I going to do about it?

That to me is like very much the kind of the bargain basement kind of data strategy, where if you can at least start to chunk out kind of the issues like that, that helps an organization to start thinking about how would we pull all of our data together and work together, you know, kind of across boundaries of the organization.

Kyle Haines: Yeah. I think you said something interesting about this idea of questions, and I’m going to rely on something that a client of ours said, that like dashboards and reports, I know what they’re going to tell me. Of course, they’re important, but data answers questions. And I want the data, I want data accessible so that I can ask questions of it and see how it answers them.

I’m wondering, in what you talked about earlier, like do you encounter organizations that don’t even know the questions to ask at this point?

Derek Drockelman: Yeah. Yeah, definitely right. It’s with those organizations that say, hey, great, you’ve talked with us about a data platform. Sounds like a good idea. Let’s do it.

I’m like, you know, I also want you to be happy. You know, I pride myself in being consultative and not salesy. And so it’s, let’s talk about what you’re actually going to do with this thing before you get it. And try to back into what are some scenarios or use cases that you’re trying to solve.

A really good example of this, I won’t name them, but she wouldn’t mind if I did. I’ve been talking with one of our CRM clients now for about two and a half years about adopting our data platform. And they’ve thrown it in the budget. They’ve kind of thrown it around the organization, haven’t really been able to make a lot of progress on it.

And the Chief Development Officer brought the CIO to a call. I’m like, so maybe you’re just trying to do too much right now. You’re trying to boil the ocean. What are three or four use cases that we could brainstorm together that would, number one, enable you to show people internally that there’s value to this, and then number two, that you could actually make actionable, because that’s the thing, right?

There are all these benchmark reports. People have always gotten data from Target Analytics or Donor Search or whatever, right? And it’s, you get the data, you get the ratings on the people, and then you sit there and you don’t know what to do with it.

And so, for example, with this client that we’re working with through this 90-day proof of concept, is they’re a big sustainer organization, and they’re kind of the typical leaky bucket of big program, get some good acquisition, but they continue to kind of dribble over the edge and out of holes, you know, at the bottom of the bucket. And I’m like, so I know that about you, so let’s start with that.

So as a potential use case, if we could see, you say that your Sustainer Program is worse than it was three years ago, but you don’t have proof of that. So, what if we are able to pull together, you know, information reports, dashboards, right, that are, you know, that are interactive, that you could look at a rolling five years and also month over month to see what’s coming in and what’s going out. You know, you’re already getting our sustainer loyalty model that shows you who’s going to churn off in four months, but you’re not doing anything with it. Like, what if we also include that?

And then we’re using this to actually find those segments of people that you should really be paying attention to. And then we lift those out and you’re emailing or calling or, you know, taking some kind of intervention strategy with that. Would that be a good proof of concept?

And like, oh my god, yes, yes, like that alone. If we could move our Sustainer Program 2% conservatively, just based on anything that we can find from that, that would be $300,000.

I’m like, well, that more than pays for this project that we’re talking about. So like, I’m trying to, you know, where necessary, right, to help people break out those nuggets that would help them show some, maybe some faster progress while they’re still kind of coming up with what’s our grand vision. So that, you know, they’ve kind of got that, that momentum under their belt. They’ve got some muscle that they’re building. They’re determining, can we change? Will we really, are we really willing to be a data-oriented organization?

Kyle Haines: Yeah, I think about in that example, like one, it sort of aligns with things I’ve said in other places, like this idea of like, let’s just start with one thing.

Let’s not, and you said boil the ocean earlier. Let’s not try to like, let’s not map out the 40 questions that we think a data platform is going to answer. Let’s find the big question that we think, if we can answer it, it pays for the investment in time, energy, effort, whatever those costs are.

Derek Drockelman: Yeah, and I promise I’m not making this up just for the sake of the podcast, but I had a call at 9 this morning with one of our largest clients talking with VP of IT and their Chief Marketing Officer, and we set up a conversation about data platforms with them for next Friday. And I’ve seen now the invite list grow from four people to 25.

And I was just like, all right, I see executives, I see data gear heads, I see I don’t even know who some of these people are. So, could we maybe take a step back? I don’t want to look like a dick. I don’t want to make you look like a dick to the rest of the organization.

Can we talk about what we’re really trying to get out of this? And let’s script it out together. Let’s come up with the agenda together so that I’m hitting on your needs and not being perceived as being salesy or being kind of platform centric about our own stuff. I promise that when we walk out of the conversation, you will have answered some of your own questions that you could apply kind of wherever direction you decide to go.

But it was very much they’re on this, they’re on midway through this one year data strategy kind of project that they’re working on. And kind of ask them to describe that to me, like what does that work kind of look like? How is it showing up? And are there, but are there short term things that you’re also trying to solve? So let’s see if we can kind of talk to both of those in that conversation that we’re going to have next week.

Kyle Haines: Yeah. I wonder about this piece, and I wonder how organizations do this, that I think about a specific client where, and I’m also thinking about the leaky sustainers, is that sometimes these projects give you invaluable insights and they might even provide insights that you’re trying to change a dynamic that’s not possible to change.

So not knowing the client, maybe they’ve had unrealistic expectations about how long somebody stays a sustainer. There’s not much to move the needle. So we’re emphasizing growing the sustainer pool, and rather than emphasizing trying to retain them in the same ways, more energy should be put on acquisition because you know they’re going to leak out.

And I think about a specific lesson on the fundraising side, the organization I worked with made a big assumption that people calling for support services around a rare cancer diagnosis would immediately attend an educational event.

And lacking the data, that was just an anecdotal assumption. But what we learned is it was less than 2 percent of people were doing that.

And then, so that began to raise really fundamental questions about, were the programs the right programs to offer? Is that just acceptable? Like, is it just a different audience that are calling that for support services?

And so it just began to challenge assumptions that the organization had and then act on them, right? It was better than continuing to operate it blindly and make the assumption that every time somebody calls for support, we’ll plug an event and they’re going to come. It doesn’t happen that way.

Derek Drockelman: Right. And that’s always cool, right? I love moments like that, where the findings kind of turn the conventional wisdom on its head, or a way that an organization has oriented itself about its approach to programs or outreach or what have you, and then find out that, oh shit, like that actually… There’s no correlation at all. That’s very interesting. And yeah. And then it’s a… Well, does it matter?  Or is that all right?

But at least you’re getting someone to say, all right, what are we expecting to get out of this? And all right, this isn’t meeting that. And so do you change it? Do we change our approach? Like, what are we going to do? Or was that just a bad assumption all along that we’ve had, right?

And that can get a little touchy sometimes, right? Depending on whose baby it is, and who owns it, and who’s put their blood, sweat, and tears into something too, right? To hear that this thing that I’ve maybe poured my heart into isn’t the thing that we thought we needed is, you know, whether it could be…

It’s both, you know, I think it’s an epiphany, right? And it’s a good and bad one sometimes.

I think the more organizations can kind of understand and be clear about what are our expectations, that’s frequently like the part that’s never defined, right?

Kyle Haines: Yeah. Yeah. I mean, the interesting thing is this led to a change in strategy. It led to increased social and Google ads, right? And because they wanted to get people in these programs and saying like, look, the people calling our support services is not a meaningful way to grow the reach of these programs.

And bringing it full circle. Well, I think I’m bringing it full circle. You can evaluate whether I’m bringing it full circle. How do we guard against the instinct – well, oh my gosh, now we have new data. It’s Google Analytics data and Google Tag Manager data. I got to bring that into the CRM so that I can tell where those people came from. And it’s got to live on an event registration record.

And I think what you and I see is a future like, no, no, no, no. Like, you need a place for the Google Tag Manager data to live, to analyze it, and a place certainly for event registrations. And there’s also host event surveys and constituent records on and on and on. Let’s stop bringing this all into a unified data CRM data swamp. I love that expression.

Derek Drockelman: Right? Again, it’s just where it’s, you know, yes, you’re, you know, you think you’re clever parking all the data there because, yes, I can see it, but it’s, but again, it’s not very actionable sometimes in the way that it ends up getting structured.

And so, you know, the way I think about it right is, yeah, if you keep data separated sometimes, and, you know, you’re using identity resolution in the middle to pull it all together, you end up getting a better result to, you know, seeing that kind of that full view of Kyle Haines and his interaction at that event and with our programs and with the survey results, then I would bet, you know, then I would be able to divine by looking at your record and seeing that data chunked out in lots of different places.

Kyle Haines: So how, for people listening, how would, like, an executive that’s listening to this, how would they bring this, other than saying this is the best podcast they’ve ever heard? I mean, that’s step one.

Derek Drockelman: Yeah, step one.

Kyle Haines: What’s step two? Like, how do they begin to create this idea of a data-centric culture? Because I would imagine that it’s difficult as vendors for either you or I to begin to introduce that idea. So, we need executives to champion it.

How do they begin to bring people along? What have you seen work well?

Derek Drockelman: Yeah. So, again, sometimes it’s the proof of concept. It’s getting a little help with figuring out, you know, how do you get started?

But like I said, that call I had earlier this morning, the Chief Marketing Officer came in to the call with some pretty specific things that he’s hoping to be able to do, right? Just kind of show where people enter that organization sphere, where they, you know, kind of where they go, being able to plot out, you know, the directions that people take.

So, some folks are able to kind of come in and understand what it is they’re trying to see, so that they can do something with it, and others aren’t.

I think where it would start, right, is if we’re starting at the executive level, is to say, how are we doing as an organization, and what would help us be better?

And in thinking about what would make us better, how will we measure that, and how will we know? And if we actually get there, what would we do with it?

So again, it’s like, it’s kind of coming back to that. The data we have, the data we want, the data we need, and the data to act is an easy way to kind of think about what’s all the stuff?

Are there perceived gaps, like things, questions that we’re trying to answer that we can’t?  

But ultimately, what would we do different? What would we do differently if we actually had the answers to those questions? I mean, that’s where I would start.

Sometimes I think it helps, right, if that’s part of a three or five year strategy planning kind of process, right, where you’re coming up with what are the key metrics, right, for the next three to five years, what are we hoping to accomplish?

If you’re at least able to make that less completely qualitative and make it somewhat quantitative to know how we’ll measure that we’re making that progress, whenever you can tie it there right, it’s a lot easier to kind of get the organizational buy-in.

That’s assuming that somebody actually reads the three to five year plan. I once went in to do a presentation at a former employer for an organization about the joy and the power of this CRM solution that we were bringing. And I thought I was being really cool by having found their five year strategy on their website and kind of broke it apart into different slides and talked about how the solution would meet that. And the first question I got was, what the hell is that? I’m like, oh, this is your strategic plan that was approved by your board last year. It’s on your website. It’s on this page. And people were like, oh my god. So, you know.

Kyle Haines: Yeah. I mean, I think about, I think in both of our examples, it’s not just about the data that you currently have to answer questions, like what data is missing.

Derek Drockelman: Right. What data is missing or it’s there, but it’s in the wrong place. Yeah, you can’t coordinate that data with the data that’s over here. So it’s either sometimes I find, right, when people talk about data that they think is missing, they’re like, you know, one person raises their hand, oh, no, I’ve got that over here in these surveys. Like, we’ve actually been asking this for 10 years. We’ve just never actually put it anywhere.

And so sometimes it’s, you know, you kind of find going through the process that there are pockets of that data. And then it’s, you know, determining, right, how usable is it? How reliable is it? How frequently is it being updated?

Just the very act of asking about it sometimes kind of points you to these missing caches of data you never knew existed.

Kyle Haines: And I think you and I, what we’re saying is, because I would use, I would almost use an identical scenario. If you have 10 years of survey data, don’t leap to how do we bring that all into the CRM?

The first question is, how durable and valuable and accurate is that data? And what are we going to do with it? Like, what is the ongoing value of it? And how are we going to, is it valuable to continue to use it?

The answer is not to hand it off to somebody and say, import this all into the CRM and then export it back out and then run an analysis on it.

Derek Drockelman: Yeah, that’s right. That’s right.

Kyle Haines: Yeah. Derek, I feel like, I feel like we could do a two-hour podcast on this topic.

Derek Drockelman: I’m sure we could. Whenever we see each other in person, we end up hanging out and talking like this for two hours. So it’s great.

Kyle Haines: People should know that Derek and I were scheduled to record this like a week ago, and we blocked out an hour, and 45 minutes into it, we realized that we were just talking about the podcast without recording it. So we had to reschedule for today. So it’s something he and I love talking about.

And I just always really appreciated your perspective and your experience, and just through the entire time I’ve known you, like this idea of being honest with people and asking hard questions. It’s something I so enjoy in our conversations.

Derek Drockelman: Me too. Right back at you.

Kyle Haines: Yeah. Well, thank you again for joining us today. I can’t promise this is not going to be the last time I invite you, especially when the whole world gets upended by the next big shift in technology in the next four months or whenever it comes.

Derek Drockelman: Yeah. Well, you know, I’m just trying to keep up with the kids, you know? Like we talked about, I’m in my 50s, right? It’s like there’s going to come a point where I’m going to tap out at some point, but I love all this stuff.

Kyle Haines: Yeah. It’s fun to try to keep up. Well, thank you again for joining us and I appreciate you being here.

Derek Drockelman: Thanks a lot.