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Hey, what is up?
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Welcome to this episode of the Wantrepreneur to Entrepreneur podcast.
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As always, I'm your host, brian Lofermento, and, at the risk of sounding like a broken record, my favorite entrepreneurs are the ones that are the change that they wish to see in the world.
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I love entrepreneurs that take their professional careers and their experiences, their perspectives, their stories, their skills, their talents and bring it to a business that makes the world a better place, and that's exactly what today's guest has done.
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Let me perspectives their stories, their skills, their talents and bring it to a business that makes the world a better place, and that's exactly what today's guest has done.
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Let me introduce you to him.
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His name is Adam Serlin.
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Adam is a performance management and innovation professional with nearly two decades of experience in working to design and evaluate strategies to deliver public good.
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What an awesome cause and mission.
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As a frontline practitioner himself, adam spent over a decade designing and managing community-based programs to keep justice-involved youth out of juvenile detention and placement facilities, as well as to reduce instances of community gun violence.
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Again, you see how mission-driven Adam is.
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Wait till you hear all about his business.
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While some of these programs went on to win awards, adam grew increasingly uncomfortable with the lack of accountability being asked of him.
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Adam is Wait till you hear all about his business.
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While some of these programs went on to win awards, adam grew increasingly uncomfortable with the lack of accountability being asked of him by those awarding his contracts, and he began building software programs to better analyze his outcome data.
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This kicked off what has become Adam's lifelong and sometimes uncomfortable mission to deliver collaborative technology and data analytic systems to those working on tough societal problems in environments not traditionally built for transparency and innovation.
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Now, what I love is that Adam didn't just experience these things.
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He took action and that's why, in 2020, he launched his company Independent Variable, where he now works with his team of software developers and implementation strategists to spread his brand of social innovation across the country.
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We're all going to learn a lot, not only from Adam's story today, not only from his brilliance, but in the way that he operates, in the way that he sees the world.
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So I'm excited about this one.
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I'm not going to say anything else.
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Let's dive straight into my interview with Adam Serlin.
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All right, adam, I am so very excited that you're here with us today.
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First things first, welcome to the show.
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Thanks so much.
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Thanks for having me.
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I feel like we're both pretty high energy people, so I'll try and tone myself down so we don't overwhelm everyone with enthusiasm.
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Adam, it's funny.
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I always tell people.
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The thing I learned when I started a podcast is that when it's audio only, it actually gets diminished a little bit.
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So hey, our high energy, we're gonna carry it the whole way through.
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Adam, you're gonna kick things off by taking us beyond the bio.
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Give us that backstory.
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Who's adam?
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How'd you start doing all these cool things?
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yeah, I guess uh, an interesting thing uh to note about me is this uh whole thing I'm now I feel like I should not be doing this kind of happened almost entirely by accident.
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So I went to college, studied creative writing, moved back to Philadelphia for the purpose of what I thought was writing the next great American novel playing in a band, you know took a job as an independent contractor picking up kids who were on house arrest and they were only allowed out with.
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You know, we called ourselves advocates at the time and that kind of ended up kicking off what became a lifelong career.
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You would have I would have told you that you were insane if we had said all the way back then that my career now would be in data and technology.
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I really wanted to be a mentor for kids in the justice system, keep them out of the system.
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Started off in the nonprofit space and you know nonprofits can be a little messy Ended up being a supervisor of a program at the age of like 22, 23, with like six months experience, and kind of found my way into management and as I was managing programs kept kind of doing a lot of entrepreneurship right, like building new programs inside of a nonprofit.
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Those programs were kind of doing okay, winning some awards, but I started to feel like maybe they weren't doing as well as people said they were doing.
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So I took my little Excel spreadsheets, learned how to do some basic programming in Excel and you know, I remember producing my first pie chart and was like oh wow, it's actually not going as well as people say it's going.
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So I had my little projector and I would go to the courthouse and project outcomes in these rooms that didn't have even screens and say like, hey, I guess our programs are doing okay, but maybe look at this outcome and you can yell at us if it's not going as well as we think it's going to be going as we think it's going.
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But while you're yelling at us, let's also look at hey, how does it happen when this judge puts this kid in a room versus this judge?
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That was not met with a ton of enthusiasm at the time.
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I learned quickly that some of these systems perhaps don't have data.
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Maybe that's not a bug of the system but a feature of the system.
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Right, transparency hasn't been built into these systems a lot into these systems, a lot.
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So that kind of kicked off this mission to help people look at data and systems where there isn't a lot of data, and then not just look at the data but see how we could take that data and improve our outcomes and just try and do a little bit better each day.
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Yeah, I love it, adam.
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I'll tell you why.
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It's because I always hear it's one or the other.
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It's either someone says I always knew I wanted to be an entrepreneur or it's someone who says, yeah, this kind of happened by accident.
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I'm particularly interested in the latter, because you say that it happened by accident.
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Obviously, you had a really cool and interesting career leading up to the launch of your business, but a business doesn't launch itself, adam.
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There is a very strategic decision and there's a lot of intentionality behind making it happen.
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Especially I'm going to toot your horn here publicly while we're on the air your brand, your website, the way that you operate your mission, what you've brought into the world those things don't happen by accident.
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They're, of course, supported by very intentional actions.
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What did that transition look like?
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Somewhere along the way, you must have said, yeah, I didn't really plan on going here with regards to data and technology, but here we are and I'm going to do something about it.
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What did that transition look like?
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Yeah, you know I kept.
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I think I'm just now getting to the point where I feel like I'm not a fraud.
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You know, I kept thinking, hey, there's, there's someone better at this than me or someone else is going to come along and introduce better data or another system.
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And it just kind of never happened.
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So we kept pushing on it.
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I was fortunate enough, after running programs, I got a fellowship from a foundation called the Stonely Foundation and got housed at Johns Hopkins Center for Government Excellence for three years, kind of trying to be able to think about how we could use data in some of these public systems.
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I had some really good partners in public sector and government who let me go inside of their offices and kind of tinker around with you know what, if we could track everything, what would that look like?
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So I got really fortunate in that regard to have really good partners and people that were willing to be transparent with certain things.
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And then, yeah, as we continue to proceed, just kind of kept that mindset that we weren't necessarily the experts in every space.
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Right, the people we partner with are the experts in their own space.
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A lot of people come in and evaluate services and say, hey, I heard that this is what is happening in Oakland or this is what's happening in you know, somewhere down in Georgia.
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You should try it here.
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The approach we've kind of taken is like, hey, tell us what you're trying to do, and the first step we're going to do is like let's hold ourselves accountable to just doing what we say we're trying to do, and then we can talk about if it's effective or as effective as other places.
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So that was kind of the brand, I guess, like let's try and do something new.
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When you're dealing with a lot of these systems, these are problems that have existed for a long time.
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So let's just take a breath and say, hey, we don't need to act like it's going perfectly, because objectively, it kind of seems like it's not.
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So let's just try and acknowledge that and then move forward a little bit.
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Yeah, so let's just try and acknowledge that and then move forward a little bit.
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Yeah, Adam, I love the fact that you brought up that big A word here already in our conversation of accountability, because it's so clear how much that drives you to make a positive difference, and I would argue it's something that impacts all of us, not only as entrepreneurs but, of course, as people.
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And it's something you said in your overview about the lack of data.
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You realize it might be a feature, not a bug, and I feel like as business owners, as people, a lot of times we love data when it shows how awesome we are.
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I'll call out the podcasting world.
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We love bragging.
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We're a top 200 podcast in our given top charts.
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We all love those aspects of data.
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But it seems to me like you love and embrace leaning into the data that shines a light on.
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Hey, there's room for opportunities here.
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Talk to us about that side of data, because a lot of entrepreneurs they ignore data when it doesn't suit their desires, their wishes, the progress that they're hoping for.
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But it seems to me like you find actionable things in data, regardless of which side it's on.
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Yeah, you know, it's interesting when you, you, we try and actually take this entrepreneurship lens and and lend it to, you know, nonprofits and also some government clients.
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You know, for entrepreneurs, obviously it's super important because if we don't properly look at our data and see what is or is not working, like we're going to go out of business quickly.
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Right, it's less relevant what is going great.
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We want to see very quickly what's not going great and where we need to improve in some sectors that have not.
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You know, when the payer is not the user in some of these places, right?
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So like, if I'm running, let's say, a probation department, the people who are on probation aren't paying me to run probation, and so there's a way where outcomes are a little bit separate, right?
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So like they can't just take their business and go elsewhere because they're going to get in trouble if they do so.
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That would be a violation of probation, and so it's a thing we do a lot in rooms.
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Say, like if the next person in your business didn't succeed, or like the next person put on probation didn't succeed, if you were to lose your house, for example, would you still do probation the same way?
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And oftentimes people laughed like, oh no, I wouldn't do it that way, but there's not quite that same accountability structure in place in some of these organizations.
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So the question is like, well, why do we do it this way?
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We don't have to do it this way.
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And so, yeah, accountability is super important and, yeah, data.
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Obviously, when you're working with folks, you want to find the thing that works.
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But if we're doing our job well, right, you don't pay us just to tell you everything is going great, because that wouldn't be doing you a great service.
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We should try and figure out what we can improve first and then, and that will ultimately help your business and help the people you're trying to serve.
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Yeah, adam, hearing you say that the payer is not the consumer in your line of work, of course that's very common in governmental services and in the nonprofit world.
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Well, it makes me think about your business and I'm thinking wait.
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So then you successfully convince people to pay you to show them how bad of a job that they're doing?
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What are those conversations like?
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What are these people's interpretations?
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And really, are they excited about the nature of the work that you're doing?
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I'm sure a lot of it is.
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You're great at framing it and telling a story and obviously you're doing all of this for a positive outcome in the end.
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But what are those conversations look like and what are the reactions like?
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Yeah.
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So we try and be pretty selective, like we won't just work with anyone who's willing to pay money, right, so like that's.
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We do have a kind of an ethos to us and we really do want to work with people who are trying to change things or change their systems or do things for the better.
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That's why kind of our tagline is like helping people be the variable for change.
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Right, the independent variable is the variable that acts on a dependent variable to cause a change.
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Variable is the variable that acts on a dependent variable to cause a change.
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So some of our messaging in general, like what we're trying to do with a lot of our technology is you know we don't charge people.
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You know we can get into later about specifically what we do, but a lot of software as service models is charging people per user per day.
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You know, own your data.
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We're actually trying to be more collaborative and give people access to the back end of their technology systems, build stuff that lives on their own networks, hopefully come in under cost over deliver.
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But as part of that it's a two-way street.
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We'll try really hard for our clients to help them make a difference and in turn for us to work together.
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Some folks just need to acknowledge like, hey, we're going to try to also be more transparent, we're going to try and hold ourselves accountable to things.
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So it's kind of a two way street with us, like it's not just pay us money and we're going to do anything.
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It's like let's see if we're even the right fit for you, and that goes two ways.
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So we'll give you some stuff that maybe some other people wouldn't give you and in return, like you're going to also agree to let us come in and have some tough conversations where necessary.
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Yeah, I really love that answer, adam, and I appreciate the insights into the way that you think as a business owner, because listeners, you see how Adam not only has his values, but he loves working with clients who share those types of values, and that's why I've always loved that simple quote of your vibe attracts your tribe.
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So, adam, it's really cool to see how that plays out in the way that you attract your clients as well.
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Speaking of which, obviously we're talking about data here today and you talked about the unlikely pivot that you made into the world of data and tech.
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I see such a stark contrast on the surface level, but I'm really excited to hear it from your perspective is that someone might look at your career and say, adam, you went from the most people-centric job function of working on the front lines in the nonprofit world and in the government sector world, where you directly were helping to guide people and the decisions they're making and keeping them out of trouble, to a world where you're crunching numbers you're looking at data, of course, for those positive outcomes.
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What did that transition look like for you?
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I guess, whether it's mentally, whether it's the way that you viewed it or the impact that you see that must have felt like a big transition, but I'm sure it all falls under one mission and umbrella that it is that you're working towards.
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Yeah, it feels a little bit like a transition, but honestly, I've been stunned with myself.
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So, like we design software, we look at data.
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But I think people get it confused sometimes, like who actually cares about data or who cares about technology.
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The only reason to care about it is if it is doing something for you.
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So there are these times where I feel like the most fortunate person in the world to get to do what I do, because we can go into places.
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You know, a lot of people are really trying their best, fantastic mission-driven people, really overworked, sometimes not even paid, paying their own money to do things, but don't have any data.
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So it's a little tough for them at times to say like, hey, could we do something more efficiently?
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Could we be doing better?
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So it feels almost like this amazing magic trick where you get to do a creative thing, like build a piece of software that aligns to somebody's workflow, and then they go in and they enter data and you pull it out and you make a graph Right, and it's just.
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It could be a simple graph, like, hey, here's a pie chart, here's a bar graph.
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In fact, it should be a simple graph Right, like if you're going to too much advanced statistical analysis for a nonprofit like that's probably not the answer, right?
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What lies at the end of your very fancy statistical analysis?
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Someone can't look at it as a practitioner, as a simple thing that they can continue to act upon.
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You probably haven't found the way to present it, but you know it's not just a graph, right?
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It says like hey, for example, you're supposed to touch base with this kid who is in the justice system within 24 hours.
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Let's say, we take a look at your average length of time and you're not getting to those kids until 72 hours, right?
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Or even, you know, five days, six days, seven days, or even five days, six days, seven days.
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You're not only out of compliance for your contract, but what if some of those kids go on and have a mental health issue in the house, get in a fight with their parents, run away from home?
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In fact, we could probably blame ourselves and our services for not getting out there quick enough, and that's a really bad outcome for a kid.
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And so that little graph that says like hey, you're out of compliance on what you're supposed to be doing.
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What can we do to get out to that house quicker?
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And then you can say like, oh wow, next quarter we got out to the house super quick and, look, none of these kids ran away, and that's like a pretty magical thing to me, I think, to be able to do, to just like take something on a piece of paper and it's not just about the data.
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But how do we then meet, come up with a strategy Like why didn't we get out to the house?
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Because we're given bad phone numbers to contact people.
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Okay, that's not a super sexy thing, but we actually need to talk to the people who are referring these kids to us and say we're getting bad numbers.
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Can we get two numbers in case the first one fails?
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And that actually has these really dramatic impacts in the real world, which is, you know, feels to me to be this kind of amazing thing I get to do every day.
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Yeah, and truly changing lives.
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You say it's kind of like a magic trick and it really is, and that's the power of great entrepreneurs in my belief.
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Obviously, I'm super biased as the host of this show, but I believe that entrepreneurship has the power to truly change society and it's really cool to see that you've built a business that helps all of these people who have these missions.
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You're helping them, empowering them to actually do the work that matters, and hearing these downstream effects is very cool.
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So introduce us to the player in the industry Independent Variable.
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It's really cool hearing you talk about statistics, because it's right in your name Clearly how much you love the numbers.
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You love the statistical side of it.
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You just showcased why because it has those real world implications when you mapped out independent variable and you said I want to create a business that helps other nonprofits, that helps other people do this good work.
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How did you lay that out?
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What is independent variable and how did you enter that marketplace?
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Yeah, you know it's funny, we're still working it all through as well.
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You know, we just figured we're going to do some cool stuff that we like to do and honestly, it was kind of a bit of a weird little business plan at first, but I guess we kind of have, let's say, like three major buckets of things that we do.
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First, we go into places where people are having a tough time even like collecting data, so we help build better data collection mechanisms.
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And we start from.
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You know, we've got these kind of really cool Excel-based tools that function like full case management systems, but it's just in Microsoft Excel, so you don't even need the internet, right?
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So we can deliver something to you that looks like a case management system but you can do it on any desktop that works on Microsoft Excel.
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And then we also have dashboards on that, so we have your data capture and then you can also analyze your data system.
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We might as well build an enterprise case management system.
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So now we can take you know, if you start off super low budget, off the shelf solution collect your data in Excel.
00:18:54.703 --> 00:19:02.667
We can then also take that, consume it up into, you know, an Amazon Web Services cloud with you know a nice enterprise cloud based case management system on the front of it.
00:19:03.635 --> 00:19:04.637
So we do that.
00:19:04.637 --> 00:19:10.297
That's like a shared source kind of application where we push a button, we deliver it to your organization.
00:19:10.297 --> 00:19:11.298
So you own your own data.
00:19:11.298 --> 00:19:22.183
You have full access to the back end of this customized case management system that's been built for you and you don't need to pay us these user based fees every day and, theoretically, you could kick us out if you want to as well.
00:19:22.183 --> 00:19:24.220
Like, hey, we don't like you anymore.
00:19:24.220 --> 00:19:26.366
You still get to keep your case management system.
00:19:26.366 --> 00:19:34.740
You could hire other people theoretically if you wanted to.
00:19:34.759 --> 00:19:37.210
So then we also have these data analytics dashboards where we can analyze the data from the data capture system.
00:19:37.210 --> 00:19:40.825
And then we have a side of the business that's all about human centered design, right?
00:19:40.825 --> 00:19:48.988
So like, how do we actually design better services and do performance management to make sure that our services are aligned to our outcomes?
00:19:48.988 --> 00:19:59.823
And then the final thing we do is, if folks want, we'll also partner with them to write research reports, write policy, actually do a lot of thought partnership as well.
00:19:59.823 --> 00:20:06.448
So we do the design work and then we can also actually write and do some more detailed policy analysis for you.
00:20:07.097 --> 00:20:08.170
Yeah, adam, I'll tell you what.
00:20:08.170 --> 00:20:25.780
You and I didn't talk off the air about this just yet, but as the founder of a nonprofit I so deeply appreciate the way that you're operating because even you just laying out kind of the back of the napkin initial business model but you do it so succinctly, by the way, that you obviously have pictured all of these different ways that you serve people.
00:20:25.780 --> 00:20:35.528
You already brought up earlier in the conversation kind of the SaaS model is one of those models that you said hey, let's make this better, let's make it more accessible to people who are doing good work.
00:20:35.528 --> 00:20:38.397
I always joked in the many months it took us to form the nonprofit.
00:20:38.397 --> 00:20:39.801
I always said it's not always.
00:20:39.801 --> 00:20:42.236
They don't make it easy to do good in the world.
00:20:42.236 --> 00:20:44.420
It's it's kind of hard to do good.
00:20:44.420 --> 00:20:50.469
Adam, talk to us about that accessibility and the model that you're using, because I love a little bit of shade thrown at the SaaS world.
00:20:50.469 --> 00:20:52.175
Talk to us about how you've laid it out.
00:20:54.279 --> 00:20:58.769
Yeah, so I mean, we try to be non-extractive in as many ways as possible.
00:20:58.769 --> 00:21:12.123
So, right, we do partner with folks who have gotten themselves into some bad contracts and have a tough time, you know, accessing their data and, or, right, like we always say, we try and build our data analytics.
00:21:12.123 --> 00:21:16.719
We use things like Microsoft Power BI, which people can have access to themselves.
00:21:16.719 --> 00:21:32.526
Once people build a case management system and then also have you pay them to model your pie charts and bar graphs, then every time you want a new pie chart or every time you want a new bar graph, you got to hire someone per hour on the other side to do something for you, right?
00:21:32.526 --> 00:21:40.699
And so what we really try and do is build a custom application, set it up for you so you have access directly to your own data.
00:21:40.699 --> 00:21:45.998
Let's say you want to hire a third party researcher to come in and write some code on your own data.
00:21:45.998 --> 00:21:55.704
You have access to the back end of your data, right, so somebody else could go in and look at the back end of our system, understand how we're pulling things and pull some stuff themselves, right?
00:21:55.704 --> 00:22:03.135
And then we build you some you know data analytics dashboards that you can go in and Google.
00:22:03.135 --> 00:22:16.278
How do I make a pie chart in Microsoft Excel or Microsoft Power BI or any of these other services and start to build out your data platforms yourself without needing to come pay us per hour for everything that you want to do.
00:22:16.338 --> 00:22:23.881
So it's kind of granting some more ownership over data and the general idea is hopefully we can start to build.
00:22:23.881 --> 00:22:25.705
We do a lot of work with collectives, right.
00:22:25.705 --> 00:22:51.749
So like what happens if four places that are trying to reduce gun violence, for example, start working together and using a shared source application for reducing gun violence, if all four of those folks say we want to hire a full-time software developer and we give somebody an application and access to the back end of their code, they could theoretically all have a full-time software developer at a quarter of the cost if they agree to split the cost of a software developer.
00:22:51.749 --> 00:23:00.865
So we're really interested in how we can use technology to build some more of these collective solutions that can scale a little bit.
00:23:00.865 --> 00:23:04.236
That is beyond any individual service model and things like that.
00:23:04.236 --> 00:23:18.143
So we're hoping, if we put some good tech into the world and align it to some missions, that that can scale in a way that doesn't necessarily require somebody to pay us all the time for every hour of service that we're doing.
00:23:18.865 --> 00:23:20.131
Ooh, adam, I love that.
00:23:20.131 --> 00:23:20.792
It's funny.
00:23:20.792 --> 00:23:22.238
I interview entrepreneurs for a living.
00:23:22.238 --> 00:23:23.761
We're over 1100 episodes in.
00:23:23.761 --> 00:23:34.736
I've never heard anyone talk about that collective approach and so it just seems so aligned with your mission, your vision and the budgets and the missions and visions of those that you serve.
00:23:34.736 --> 00:23:46.766
So I really appreciate the way that you share that and obviously it's at the core of the way you think about things, because you're clear on who it is that you want to serve and you also come from that world, so you understand the intricacies of the nonprofit world better than most.
00:23:46.766 --> 00:23:48.734
So when we have technology conversations of the nonprofit world better than most.
00:23:48.734 --> 00:23:55.608
So when we have technology conversations, especially this year, they quite frequently teeter on the edge and talk about AI.
00:23:55.608 --> 00:23:58.044
How's AI factoring into the work that you're doing?
00:23:58.044 --> 00:24:03.407
Are there cool use cases on the client side or internally, business owner to business owner?
00:24:03.407 --> 00:24:06.006
Adam, I'd love to hear some of your perspectives on AI.
00:24:08.511 --> 00:24:19.885
This may be a bit of a detour, but a thing that I'm thinking a lot about with AI is we do a lot of work.
00:24:19.885 --> 00:24:32.832
You know a lot of people evaluate programs, or you know we have a lot of experts that have written papers about what works or what doesn't work, and in social services we've moved towards a lot of.
00:24:32.832 --> 00:24:36.842
We want evidence-based programs and something gets certified as evidence-based.
00:24:36.842 --> 00:24:39.903
If someone has come in and done a study about it, published it somewhere.
00:24:39.903 --> 00:24:54.609
I think the important thing to acknowledge with AI is that a lot of it's a language-based model, so it's training itself on the existence of everything that has been that has been published on the Internet, but there's a lot of stuff that doesn't get published.
