George Jagodzinski (00:00):
Today we learn about superworkers and how our guest is finding real practical ways to grow and empower more superworkers in the public sector. We also discuss product leadership and how we must rethink strategy and execution in today's fast moving world. Our guest today is Denise Hemke, Chief Product Officer at NEOGOV and host of the Products That Count podcast. Denise is a seasoned product leader whose journey from engineer to C-suite has spanned some of the most respected names in tech, including Salesforce, Workday, and Checker. Whether you're building software, leading teams, or just curious about how mission-driven tech can make a real impact, this one's a fun one. Please welcome Denise.
(00:35):
Welcome to Evolving Industry, a no BS podcast about business leaders who are successfully weaving technology into their company's DNA to forge a better path forward. If you're looking to actually move the ball forward rather than spinning around in a tornado of buzzwords, you're in the right place. I'm your host, George Jagodzinski. Denise, thanks so much for being here.
Denise Hemke (01:15):
George, I could not be happier to be here with you today. As you'll quickly find out, I'm a big nerd when it comes to serving the government, and so I'm excited to share that with you and your audience.
George Jagodzinski (01:25):
Yeah, I'm excited. And I figured we'd first start with a little bit of your career story. You went from engineer to chief product officer. When I look back at my career, I feel like I just kind of Forrest Gumped my way through it, but I'm curious, did you have pivotal moments in there that really stand out to you?
Denise Hemke (01:42):
Yeah. Certainly I do think in some ways I stumbled into it, but there was some intentionality along the way. So you're right. I spent first 12 years of my career in engineering. And actually as I was leaving Salesforce, I was toying with the idea of, do I move into product management or not? And I thought, well, you know what? I found this incredible startup. They have a mission that I really care about, big data analytics. Let me join there. And I joined as a front end engineering manager, went from managing a 50 plus person team to a seven person team, really scrappy, really lane, the typical Silicon Valley dream, I guess you would probably say. But then in doing that, what we found is we were just kind of struggling with product management because it was technical. It was a big data analytics company.
(02:26):
And that's actually the through line of my career is a lot of data and analytics. So there I started doing the product management job before I had the job. And then I officially threw my hat into the ring and said, "Hey, I want to do this." But I like to pretend that I went straight to chief product officer. That's certainly not the journey. I went back to being an individual contributor and I did that for many years there at that startup. And that was really incredible. I'm a big believer you got to hone your craft right before you can teach others how to do the craft. And then after doing that, I did go back to managing teams and I was lucky enough to build an acquisition that was made of my company at Workday, a team from zero to over 60. And then that's really where I fell in love with people and serving people and HR.
(03:12):
And so that is sense what led me to Checker and then ultimately to NEOGOV. So it's been an incredible journey, certainly some intentionality along the way, but certainly some of it kind of stumbling through it and realizing suddenly, wow, this thing that I thought I was going to do for the rest of my life isn't exactly what I want to do anymore.
George Jagodzinski (03:32):
That's great. There's some real resilience and flexibility there and all that change that you've pushed through. And I'm curious then as you move from the commercial world into now public sector world, what were the big surprises or the big differences for you?
Denise Hemke (03:47):
Yeah, I think one thing that I'll highlight is I've been lucky to work, and you heard some of the companies that I just worked for, Workday, Salesforce, these are incredible brands, right? But what they're also known for is having an incredible customer base. Customers who are really engaged, really active, want to propel the product forward. And moving into government, I guess I wasn't sure exactly what that would look like, but I had some inklings because I saw government customers out there educating on YouTube, other people on our product. And so I thought, wow, well, maybe these customers will be similar. And frankly, I'll say it's almost even better. And I know that that's hard to imagine, but I think what makes it better is that they're not competitive with one another. They want this rising tide raises all boats. And so I see that in the way that they show up at our customer conference, right?
(04:42):
They're not holding back. There's no trade secrets. And then, especially in the world of data and AI, I have this magical gift, which is this willingness to share. And we've recently launched a new AI feature called Smart Job Recommendations. And that really looks at a hiring funnel and starts to understand, hey, if somebody in a similar job is getting more applicants than you, what's different about that? Is it the pay that you're providing? Is it the educational experience? And if you go back to private sector, no company is going to disclose that data to their competitor to help their competitor land more hires. But in government, they want to raise the tide for everyone. And so I think that is really unique about this market. And AI is one example of how that shows up. It also shows up to processes and forms that they share all throughout our system.
(05:43):
And I don't mean like on some separate community site or some inkling of something. I mean, literally, here's a form to use. And that's great because it helps our customers get implemented faster. It helps them implement best practices for these small agencies. It gives them access to resources they maybe wouldn't otherwise have access to. And so I think that's been what has been really eyeopening for me. Lastly, and I'm sure we're going to get a lot into this today, so I won't deep dive too much on it in the moment until you're ready to go there, is I do think there's this belief that government is a laggard market in adopting things like AI. And frankly, I have found kind of the contrary, right? It's not that they don't have the want to, right? It's that they need the help, but the want to is certainly there.
(06:29):
That's something I'm personally really excited about, which is to help them use data and insights better to drive efficiency, to drive better decision making. I think there's a huge opportunity, and I found our customers to be incredibly receptive.
George Jagodzinski (06:45):
That's interesting. Yeah, teaser on that. We'll definitely get into that. But what I'm hearing in there is even in your career, there's a lot of focus on people and the humans. And I think when people think public sector versus private, they think of government as just this thing versus the fact that those are still people. They're still humans that have the same needs and the same biases and the same motivations that anyone has. And I find in the private world, some of my customers, they're lonely in their roles because they can't collaborate with their peers at their competitors, where in the public sector, it's innate to have that collaboration. So I think that's fantastic.
Denise Hemke (07:25):
Yeah. Yeah. You're 100% right. I sometimes even say, "This is a lonely job because you don't have the kind of that equivalency and you've got to find your people." So I think you nailed it.
George Jagodzinski (07:37):
I figured a good place to start was superworker. You guys are helping create more superworkers. Maybe just expand on what exactly does that mean and then ground it a little bit with how's that actually playing out on the streets?
Denise Hemke (07:51):
Absolutely. So Josh Berson, who is a leading HCM analyst, really coined this term, the superworker. And the idea behind the superworker was to say, how do you take an individual worker and then give them these super skills through the use of AI? So I'll give you an example that I used actually, frankly, for myself, because I turned to things like ChatGPT on a daily basis, frankly, throughout the day. But as I was actually working on my keynote speech for Ignite, one late Friday afternoon, found myself in an interesting rabbit hole where I thought, wow, how do I make this a more compelling story? How do I really engage the audience? And I'm lucky enough that I've got an eight-year-old daughter who loves to read and she's into these graphic comics and that's great because it engages young children in reading. And I thought, what if I take this whole keynote and I turn it into a graphic novel?
George Jagodzinski (08:45):
That's cool.
Denise Hemke (08:46):
It was really fun. And so I asked ChatGPT and I iterated with it a lot on how to create these images and I used all of those images. I didn't turn to a marketing person. I didn't turn to a graphic designer to do this. I turned to this tool that I have access to. And so AI made me a superworker, that I could create all this content in a way that I don't have the skills to do otherwise. And so taking that same idea of how do you equip an individual with these super skills, that's what we're doing in government, right? Kind of putting a cape around their neck to make them a superworker. And so we've been heavily focused on AI and we're doing that in a number of different ways. I mentioned smart job recommendations a moment ago. There is a real need in government to get people into the seat, especially in what I would say are these really hard to fill roles.
(09:41):
That is certainly challenging. If you look at the number of applicants overall, the number of applicants has gone up. Yet, if you dig into the data, most of those applicants are going to the jobs that frankly are already getting enough applicants. So we break it typically down into quartiles or octiles, right? Chunks of four or chunks of eight. And if you look at those highest performing jobs, they're the ones that are getting more people, but that's not who needs people, right? It's these lower performing jobs. Do you know a traffic light engineer? People are hard to find, right? And so when you have a hard to find role like that, that is where, again, we can make people superworkers. We can make those recruiters and hiring managers, superworkers by saying, hey, if we surface to you through that smart job recommendation, that if you lower the degree requirement from a four-year degree to a two-year degree, then you're likely to get more applicants.
(10:40):
And by the way, another agency is doing it. So you've got social proof that it's working. Those are the types of things that turn that recruiter into a superworker because they can have that conversation with that hiring manager. And the hiring manager can say, "Yes, absolutely. We will lower that degree requirement." And now they're getting an influx of applicants and because of that influx, they're able to get somebody in a position to do the work that our government needs. So that's one, I think, great example of how we're empowering that group of people to become the superworker by equipping them with data to have a meaningful conversation. The other side of our market, because we service both the human capital management side of the market, and I should probably pause and talk about that piece, right? Everything from governmentjobs.com, we do a large, significant portion of all state and local hiring, all the way through to things like payroll and benefits elections, right?
(11:36):
So the whole HCM suite. So that's what NEOGOV offers on that side of the house. We also focus on public safety. So think about law enforcement, EMS, corrections, 911, fire, all of these really critical services. And we're making those people superworkers too, and we're doing it in different ways, right? Its efficiency is one of the ways that we drive it. Again, insights through data is the other way that we're driving it, like that example I just gave you. And so there's a lot of scenarios like that where we're saying, how can we help them do it better, faster, and with more confidence? And that's really what being a superworker is about.
George Jagodzinski (12:14):
I love that. Let's dig into maybe some more examples on the public safety side of things where, what's a good example on the public safety side where you're creating superworkers?
Denise Hemke (12:25):
Yeah. I think on the public safety side, one pretty amazing example is a product that we built last year called recall. So this product is in market today with many of our customers. And so backing up on to public safety, kind of the core of public safety, the flagship product that we have in that space is policy management. So if you're a police officer and you need to engage in a high speed pursuit, you need to know when can I engage? When can I not engage? How do I engage? What's the role of maybe the lead car? All of that is sitting in a policy management application, our policy management application. You're acknowledging that you know that policy. And for something like a high speed chase, which is really critical or something that maybe you do very frequently, of course all of those policies are top of mind.
(13:13):
And that same policy management software serves, let's say 911, right? There, they're calling them standard operating procedures. Same thing, but stored in the same system, but slightly different name. So in the case of 911, what we found with one of our customers out of Cincinnati was that they were finding that in these scenarios that they were doing less frequently, that maybe the policy wasn't always top of mind. And how do they get people to know that so that they can service the community better and faster?
(13:43):
So our recall product sits on top of policy and through AI, it creates a deck of cards. So you don't have to say, "Hey, what are the things that somebody needs to know about the policy?" You can just point it at the policy and it will auto generate those decks of cards. Now, of course, a human is in the loop, and so they're going to review them and say, "This is good. Let me publish that thing." Or they can make a modification. But after that deck is published, then what we do is we deal those cards out to the organization. And if you prove that you know something, we'll deal it to you less often. If you don't know something, we're going to deal it to you more often to encourage you to learn it.
(14:21):
And so what we found with that particular agency is, number one, they created 600 cards in a short period of timeframe because they could with AI, something that would've been very challenging for a human to do. And then over a hundred-day period, they brought everybody's scores on those decks up by 10 percentage points. And so this isn't just like you went from a C to a B or you went from a B to an A, right? This is the whole agency lifted up that much. That's the first step, right?
(14:50):
And so that's a huge outcome and a great leading indicator that the quality of service is going to improve. That is the thing that's really enabling them to be more responsive when they're on the phone with that person in this critical moment in time, because these are split second decisions that these people have to make and engage with. And so I think that that's the type of example that we're talking about when we're talking about superworkers in public safety.
George Jagodzinski (15:14):
That's fantastic. And in the world of AI buzz, it's great to hear just a real concrete example of where it's helping because I would imagine before it's probably like some boring annual training or some mountain of documentation that you have to read through. And these edge cases are probably the ones that matter the most. If something doesn't happen that often, when it does, that's the most impactful, important time for something to happen. And so that's fantastic.
Denise Hemke (15:38):
Yeah. And I think to me, I always see it as like, I always give the analogy of like, it's like your braces, right? You still might need to do that annual training, but if you don't wear the retainer and I didn't twice, then you're not going to have perfectly straight teeth. And so this is really great reinforcement learning on a continuous basis. And the best part of it too is you don't have to set this time aside. We make it fun, we gamify it. So it's engaging for those folks. And that's one great example. Maybe another one I'll share with you if you're up for another example.
George Jagodzinski (16:06):
Yeah, I love it.
Denise Hemke (16:06):
... is on conversational policy search, right? That's a lot. That's a mouthful. But back to that piece about policy, if you really want to know what a law enforcement officer is thinking, then what you can do is frankly, from our case, look at what they're searching for because it's not that they're Googling or searching for random things. I wouldn't say not Googling obviously in our system, but searching for random things, they're really trying to discern how can I be compliant? Because this is so critical for them because if they aren't compliant, they risk public safety, right? They risk potentially their own career. There's a lot of impacts that come downstream from a lack of compliance. And so it's critical that they know. And so we recently launched this search capability so that they could get to that answer faster.
(17:01):
I'll give you a great example. The word taser, you're never going to see it inside of a policy because it's a brand. But if an officer were to ask a question, "Hey, when can I use my taser?" It will pull up all of the policies that reference what's called an ECW, electronic control device, which is what a taser is. And so I don't need to try again multiple times to get to the right answer. The system is going to help me get to the right answer because it knows what I'm looking for. And that is the power of what AI is doing. We recently launched this to Alpha with our customers, and so what's been incredible is actually to look at the types of questions that they're asking. And I would break that into four categories. The first is the rules. The second maybe is the bureaucracy. The third is the human side.
(17:49):
And the last I'll say is this idea of kind of leaders and learners. So if I break that down a little bit, the first one, the rules, right? An officer might be asking a question like, "Can I carry two guns?" These are things that they need to know. They're not looking for loopholes in the system. They are looking to be compliant and they need to make sure that they have that clarity on if this is acceptable or not. And so that's the first class of questions that they're asking, which I think is really interesting. And then there's sort of this bureaucracy piece. We all know that officers have to do a lot of paperwork, and if they don't do paperwork right, then that keeps us from putting the bad guys in jail. And so that's important that they get that done properly. And so they're asking questions like, hey, do I have to store records in a particular way? Because there might be some nuance to that again, where if this isn't something I deal with frequently, then I might need to know, do I need to do something different?
(18:46):
And I think modern policing has become just as much about data stewardship as it has about public safety, so that we can actually see those outcomes all the way through. Then there's that human side of things. They might be asking questions like, "Hey, what are the rules on relationships here?" That's the other challenge in policing is like, I don't get to just take off my uniform in a badge and go back to sort of living my normal life. I have to, just like all of us, even in the private sector, I have to know what those rules are for how I'm engaging in my life outside of work so that I am compliant to what the organizational rules are. And so there's that human side of things. And then the last thing I'll say is these leaders and learners, right? And it might be people asking questions like, "How do I become a member of an emergency response team? What's required for promotion to a particular level?"
(19:38):
And so that tells me these aren't just compliance related questions, right? These are career related questions. This is a workforce who doesn't want to just do better. They want to do more. And so I love looking at these questions and kind of seeing the types of things that they're asking because when I see that superworker, I think we're looking at that whole person and saying, "Hey, how can I help you learn more? How can I help you be compliant and help keep the public safe? How can I also allow you to be a person in your job and make sure that I'm supporting you in that?" It's that human side that we talked about. And so these are people in very difficult, complex jobs and they're seeking clarity, accountability, and sometimes maybe a little reassurance that they're doing it right.
George Jagodzinski (20:26):
That's great. Yeah. It's a mix of advisor mentor and a little bit therapist in there. I think one of the great AI examples in there is something that it's great for is it's hard to put pen to paper on something in general and AI is great for just getting ideas out there. But I had never thought about the like, "Hey, what should I be doing with my career next?" We started off this conversation talking about how I forced up my way to where I am, but being able to look at what's out there in the market and what you've been doing in your career a few different paths has got to be really useful.
Denise Hemke (20:58):
And especially in public safety, it's highly structured, right? They know that there's certain markers that they've got to hit to get to that next level in their career. And so that is in a policy, right? And so luckily, unlike you and I who had to kind of meander through it is there. And frankly, they can also use the recall cards to help them test so that when they try to take the test to get there, that they've learned what they need to learn in order to do well. So I love that there's lots of ways that AI can really help them in their career and really help keep our safety, our community safe and make sure that these public safety agencies are able to best serve the community in every way possible.
George Jagodzinski (21:40):
A funny thing that keeps coming to mind as you're talking about this is, I don't know how regional this is, but I'm in New England and there was the big Karen Reid trial and it's like, I keep imagining those police officers, if they just could have had that recall app and say, "Hey, should I put evidence in red Solo party cups?" And they'd probably be like, "No, not a good idea." That would've saved them a lot of heartache.
Denise Hemke (21:55):
Yeah. Well, and I'll tell you one last thing because you got to open the door for it too. So we've got some great partners out there, right? I love to say that if you think of a sports analogy, we're often doing all the pre-game work, the policy, the prep to get them there, the training to make sure that they know the policy. We do things like field training to make sure that an officer coming out of academy gets equipped with the skills that they need through on the job training.
(22:24):
And we do a lot of the post-game stuff, right? Whether that's reports they may complete or internal affairs or even officer wellness, which is another really great area where we're leveraging AI, but often we aren't on the field with them, but we've got great partners. And so Motorola's a great example of one of those partners we recently announced that actually on a Motorola SVX, which is I think kind of a fancy way to say a body-worn camera, but it does a little more than that, which is why they call it something different.
(22:51):
You can switch to a special channel and actually ask it, "Hey, what's our policy on a dog bite on a human?" And that's actually going to talk to our policy engine and using AI, we're going to serve that answer back and read it to the officer right then and there on the field. And so not only through that conversational search, are we giving them the answers that they need when they need it, but also with these integrations that we are building it, we're getting it where they need it. And so to me, that's the other piece that's really impactful. And then hopefully that won't be at a red Solo cup.
George Jagodzinski (23:22):
As you're talking about all these features that you're rolling out and since you're a self-professed data geek, I would imagine each new feature you're rolling out, you're getting that much more data that's coming in. The world's changing faster, at least it feels like that it has, or technology is. How are you managing as a chief product officer, your roadmap? It used to be three-year roadmaps and quarterly releases. How do you manage all that?
Denise Hemke (23:47):
Yeah, I'd like to say three-year strategy. I don't think we can predict the features that are going to be inside of it three years from now necessarily. There are certainly maybe some things that we know, but we do know what our strategy is. I think when it comes to the roadmap though, we typically work, depending upon the side of the business, either in a quarterly release cadence or we even do continuous delivery. And we do go through that and we plan at a quarterly level. But to me, I think maybe the fundamental question in there is what's changing about how you build that roadmap? And I think AI is changing a lot.
(24:23):
And so some examples that I will give you are certainly like I've got product managers who say, hey, I can use AI to help me write user stories inside of user stories, which is, for those of you may be less familiar with the ins and outs of building product, I want to do X so that I can achieve a particular outcome. And that's what product managers write when they're building out a feature. And inside of that, they'll write something called acceptance criteria that says it should do all of these things. We can use AI to help us build that. So that's really incredible. We can use AI and we are using AI to help publish things like release notes so that when we actually put things out there that we have the best up-to-date documentation for our customers.
(25:06):
One of the things that I'm personally very excited about though is even using rapid prototyping tools because I think one of the challenges when it comes to roadmap, anybody can list out a bunch of features. And frankly, you can build a lot of features, but it's, are we building the right set of features? I think judgment becomes more and more critical in this world of AI because it will become easier and easier to just push out more and more is not always better.
(25:36):
And so I think that piece of rapid prototyping allows my team to actually prompt their way. I was once an engineer, but nobody wants my code anymore, so I will leave a prompt, to prompt their way to what looks like a working product. And these things are actually very functional because it creates even data behind the scenes and sometimes even a database, you can actually interact with it. I mean, it's super cool. I actually built one with my daughter, which is quite fun to have her come and iterate on it. But what that allows us to do is really rapidly get to what we think is the right answer to meet our customer's needs and then put that in front of customers and say, is this what you meant? Is this going to solve your problem? And do we need less of this or more of this? Or should we scratch this idea altogether and go do something different?
(26:26):
Because oftentimes, until people really got to get this opportunity to touch and feel the system, unless you've been building these applications and you can kind of imagine what the world is going to look like after all these user stories come to life, it's hard for people to think about that. They know they've got this problem, but they're not always clear that what you're building is going to help solve their need. And so this is, I think, a really powerful tool that is really kind of now in our toolbox. And I love that it is just changing the way that we build software.
George Jagodzinski (27:00):
Oh, it's just the best. I'm just remembering back to the older days of building software and it's just these awful month long sagas of product design arguments and egos and trying to figure it out and making assumptions about the customers and then putting something in front of the customer that kind of gets the vision across, but not really. And so they don't understand it. And it's just, thank goodness all of that's behind us, right?
Denise Hemke (27:24):
Yeah. Yeah. Well, I'd like to say it's all behind us, but I think there's this piece of change because it is also going to change how we all work. It's going to change what roles look like in the future. And so I think there's certainly a lot that we still are going to learn. And I don't think we all know exactly what the future is going to foretell, but I think we have some incredible hints, right? I think these rapid prototyping tools will eventually get to a state where they can actually really put things into code that we can even take to production. That's my belief. That's my theory. I'm sure there's other theories out there, but I think there's hints where you see tools being kind of chained together to solve for that need.
(28:05):
And I think when we can really get to that point, that is when I think we can say it is all behind us. We can prototype it, we can launch it, and we can do that in a rapid way to really help customers get what they need.
George Jagodzinski (28:19):
Yeah, absolutely. And full circle, the user feedback and the user testing to just cycle right through that whole thing. Denise, as you talked about your career and what you're doing at NEOGOV, I hear a lot of passion around people and a lot of passion around mission. I'm curious, where does that come from and what drives that?
Denise Hemke (28:36):
Our mission at NEOGOV, if folks don't know it, is to serve the people who serve the people. And I think for me personally, I am the daughter of a retired teacher. Both my sisters teach one's kind of on the sidelines for a bit. She's got multiple kids, but she'll get back in the game. I've got a brother-in-law who is in law enforcement. He was a homicide detective until recently and then moved into fraud. And so I know it is near and dear to my heart how much work it is to be in these types of jobs. I think about them, right?
(29:11):
For me, they are the people who serve the people and my job is to serve them so that they can go home and take care of their family and do all the things that they want to do and so that my brother-in-law is safe every day and that he then can go home and again, take care of his family maybe in a different way, not because he's got all this paperwork to do, but also to just be able to be there for him because he is safe on the job.
(29:37):
And I think that to me is crucially important and why I touched on briefly things that we're doing in wellness. We're using AI in addition to human inputs to look at things like officer wellness, first responder wellness to say, hey, you've experienced a disproportionate amount of trauma, because things like suicide are prevalent in law enforcement and that is really Sad, but it happens. And so there's obviously the safety that they put themselves in by engaging in incidents every single day. But then there's also just the stress that it takes on them and that's work that they take home with them.
(30:13):
I was talking to a 911 operator at our conference and she said, "Hey, I've had people die on the phone with me. It's heartbreaking." And I think actually for folks at 911, oftentimes it's even harder because they don't get the closure that an officer might actually get. So they don't know what happened after that person hung up. And so I do think about that wellness side of things and how we can best help the community. And for me, my family is that archetype of who I'm serving. But when I talk to our customers, I'm serving all of them. I'm serving them, I'm serving their families, I'm serving their community. And so that's where that comes from for me personally.
George Jagodzinski (30:50):
That's a great mission. I love it. Denise, I could talk to you all day about this, but I know we're running up on time. I like to finish with the question, which is in your life, in your career, what's the best advice you've ever received?
Denise Hemke (31:04):
I think it is that feedback is a gift. When somebody gives you feedback to say thank you. I think oftentimes when we hear feedback, sometimes it can put us on the defensive. And instead, looking at that and saying, "what part of this is true? What part can I do differently? Maybe what part of this might be a misunderstanding or how I'm coming across to people. But I think always receiving that feedback, being willing to take it either as a person or for me to our products, and that's why my team, I think, quotes this a lot, that feedback is a gift. We want to hear it because I think that is the only way that we grow. And so I believe very strongly if you are a growth mindset person and I believe the day you stop learning is the day that you are dead, then feedback is the way that we grow.
George Jagodzinski (31:51):
I love that. Yeah. Otherwise, you're in a false harmony, which serves no one any good whatsoever.
Denise Hemke (31:57):
A bit of an echo chamber.
George Jagodzinski (31:58):
Yeah. Well, Denise, very impressive mission. I love it. It's fantastic. And I really enjoyed all of the learnings from your career. Thanks so much for being here.
Denise Hemke (32:06):
Yeah, thanks for having me. This was truly incredible.
George Jagodzinski (32:10):
Thanks for listening to Evolving Industry. For more, subscribe and follow us on your favorite podcast platform and pretty please drop us a review. We'd really appreciate it. If you're watching or listening on YouTube, hit that subscribe button and smash the bell button for notifications. If you know someone who's pushing the limits to evolve their business, reach out to the show at evolvingindustry@intevity.com. Reach out to me, George Jagodzinski on LinkedIn. I love speaking with people getting the hard work done. The business environment's always changing and you're either keeping up or going extinct. We'll catch you next time. And until then, keep evolving.