How HR Builds Credibility With Finance Leaders

[00:00:00] To me the big barrier that's important to overcome in these relationships is the credibility barrier. I think HR in particular has a challenge that other functions don't have. And that is that everybody thinks they can do our job. Particularly in recruiting, everybody thinks they can do recruiting barriers. Don't conduct your analysis in isolation because data is so incredibly powerful. Not defending just the tribe but defending the organization.

[00:00:24] Those creative people that you really want to keep empowered, keep excited, keep motivated, keep thinking. A good experience pays dividends down the line. HR tend to break down on proximity. Welcome to We're Only Human, a podcast about human resources, business, technology and workplace. My name is Ben Eubanks, your host, and I'm so glad you're here.

[00:00:49] I think one of the hardest questions that's been around for a long time is how do you actually measure productivity? I don't. I've yet to see a really compelling answer to that for most roles. Sales, it's easy. Everything else is difficult. Everything else is difficult. You customer support, you can look at tickets and thumbs up, thumbs down ratings. But like software development, okay, you can look at code submissions. How much work are they? You can look at the volume and the length of these code submissions. Are they good code?

[00:01:18] At the end of the day, it all comes down to this different layers of subjectivity. Yes. And there are solutions now with AI, especially with some of these work operating systems like your notions and your click-ups. If you have fully integrated your work into these, you can do some magic to try to figure that out. The problem is it's so invasive, right?

[00:01:40] If you gave me all of your tasks, all of your comments, all of your email, all of your calendar, and let me put a recording device on you so I could hear you all day, AI could probably figure out where you stack in terms of your productivity. You know what's wild? So, there's a company called ProtoScore that does that. Yeah. And when I talked to them the very first time, they were showing me all the stuff that they capture and said, what is your protection against bad actors? What do you mean?

[00:02:08] There are managers, micromanagers that would kill to have this kind of stuff and nitpick it to death. No one's, we don't think we're going to do that. I said, by the end of the day, you need a statement on your website. This is our stance on this. Yeah. This is for helping people do better work. This is for us helping people proactively if we see there's an issue for something, right? Or helping, hey, this person's killing it. What are they doing differently than everybody else that we can level everyone up? Yeah. I said, you need some sort of statement in your position on that. And to their credit, they did. Good. But then they were saying, this is our, the reason for this is this.

[00:02:37] Because I said, I've seen too many managers that would take them away. Now, do you think the employees believe that statement? That's the hard part. So, I was going to tell you that before I forgot. It's like they are doing cool stuff. They hook in all these systems. The more technology we'll use, the better they can give you a picture of what they're doing and take care of. I saw a post this morning on LinkedIn, a startup CEO was saying, I use AI to do all performance reviews from all people. And I go back to what you just said.

[00:03:06] How clearly can it see all that? Is it in every single possible meeting? Is it seeing all their private traffic with the other people that they're supporting in the business? That's, you have to get to that level for it to be able to do it on an automated basis. Also, what's the training set? If I, let's say you did give into the surveillance state and you had all of this info. What are you then training it against to determine if the person is good or not? It's going to be a subjective performance rating. Yes. I guess you can maybe take it in sales and then you have something a little more quantitative.

[00:03:36] Maybe you create a model that works for other teams. But I just, I haven't found a good answer yet as to how to get away from the subjectivity of measuring these things. I was thinking of the performance potential grid. Yeah. But performance. No, for potential. As you ask enough questions, it's like another layer of performance. And even that is subjective. So like potential feels like a quagmire for bias also. Like that guy's a straight shooter with upper management written all over him. It's like, why?

[00:04:06] There are three or four things in that statement right now that my skin crawl a little bit. That was an Office Space quote, by the way, if you didn't catch it. Oh, my goodness. TPS reports on Modestment in the day. Yeah, we can throw some good Office Space stuff around. I'm at the age now where if I make these references, I have to be conscious of how old the person I'm talking to is. This is for my movie called Office Space. I have the DVD. That's a round thing. Yeah. Okay, let me...

[00:04:37] I'll have to figure out how to fit that into the conversation if you're dealing with that. Sure, yeah, up to you, however you want to cut it. I wanted to make sure it was recording and capturing everything, but that was a great way to start. Off the bow, goodness. All right, quick housekeeping, and then last name? Noe? Noe. I had a guy that I grew up with, Noe. San Francisco is the only place they pronounce it right because we have a Noe Valley. Where else it's Noe. Okay. They did his name wrong every time there was a substitute teacher. He was just like, yes, that's me.

[00:05:05] They just gave up trying to correct everybody else. All right. Okay, welcome to today's episode of We're Only Human. This episode is part of our series on measuring the human impact of work. I am recording on-site here at the People Analytics World event in San Francisco today. Thank you to their team for supporting the series and the show. Thank you to Richard and the Icon Analytics team for making this possible. And now let's get to our guest. I'm here with Shane Noe from Astronis Space Technologies. We are talking about, goodness, he has a checkered past as a former finance practitioner now on the HR side.

[00:05:35] And we're going to be talking about how do we measure some of the things, the lessons he's learned there that he can bring into this work. And really, honestly, we're going to have some fun. Shane, glad you're here. Yeah, Ben, thank you so much for having me. I've been looking forward to this podcast for a while. Great to talk to you. You are not a new friend to the Lighthouse community, right? You were on HR Summer School last year. I had a great session there. You and I have been on webinars and stuff. So I knew I could ask you and you would say yes because hopefully it was going to be fun. Every time we chat, we have a great conversation, whether online or offline. We're just sharing office-based quotes.

[00:06:05] We're long-lost brothers, apparently. So before we get into some of the fun stuff we're going to talk about, would you take a minute and tell the audience more about who you are and what you do, please? Yeah. So my name is Shane Noe. I describe myself as a recovering finance guy. Started my career on what I thought was the CFO track. I was in the rotational program at Apple. I went and worked for capital markets at Google. Then I went into corporate finance and went a little smaller. So I worked on the strategic planning analysis team at Box. And it was at Box that I got my first exposure to HR.

[00:06:33] And what I saw was surprising to me. Having been in these rotational programs and had the perspective of how other business units run, 10 years ago, HR was not a very data-driven function in general. That was one thing I learned. The other thing I learned is that HR is so much fun. There's no better group of people to work with than recruiters, second only to salespeople in terms of the amount of fun that you have at work. So when the opportunity came to make the switch, I thought there was an opportunity for someone with more of a quantitative background

[00:07:01] to help bring the function along and really run HR in a data-driven fashion. Today I'm at Astronis. We manufacture high-orbit satellites. We're going to do a tour later. I'm excited to show you the HQ. I'm a big space nerd, so it's been a real dream come true to get to work at this company. The talent density of this company is insane. We're like literal rocket scientists walking around. And they're doing some very exciting stuff in this new commercial space frontier, which as a kid I always hoped one day would become a reality. Yes, yes.

[00:07:30] That is, again, just watching the news headlines, things that I see from my side, I'm super excited about it, curious about it. As I told you earlier, I'm based in Huntsville, Alabama, and so the Rocket City, anything space-related is very near and dear to my heart. So when you said, hey, if you ever come around, would you like to swing by? I'm like, yes, yes, and sign me up. Okay, so one of the things that you just talked about there a little bit is there was an opportunity to bring some of that data-driven approach to the HR function to try to level it up.

[00:07:59] One of the things that I have felt like in the past is there was this sort of tension where you had to either be really people-oriented and darn the numbers. We just care about people. Hugs for everybody. Or the other side, where everything is measured, everything is calculated, everything is very down to the number, and whatever. There's people, right? There's numbers. And what I found to be true is it's probably a spectrum, right? There's somewhere in the middle there.

[00:08:29] Where would you fall on that spectrum? Oh, man. I have been on both sides. I remember getting some feedback early in my career when I was in corporate finance from somebody who said, Shane, you really need to go spend some time in the business unit so you can really see what's happening at the ground level before you set these headcount targets and hold people to them. I forget exactly who said that, but fast forward, definitely have done that now. I think the right answer is somewhere in the middle. You need the data in the business foundation. At the end of the day, we're running companies,

[00:08:57] and you have to run it like a business. But that only tells half the story. You need to understand the human element, talent in particular, providing career paths and employee experience that's compelling, the employee value proposition of a company. When you marry those two things together, I think is where the real magic happens. Yeah. That's where I like to hover. Do you feel like a lot of the numbers that, I'm not going to put you on the spot for Ashana specifically, but for a lot of our friends that are in the HR community,

[00:09:25] do they rely on things that are too vague, too fluffy, too immeasurable? We were talking about productivity even a minute ago and how it's hard to get at something like that. What are your thoughts on that? Yeah. If you ask any CEO what they care about, it's attrition and performance ratings. And if you're not hiring, then they care about hiring. I think our lean on the HR side is very much the personal stories and the personnel, and I think that's really important. It's important that at least one of the executives at that table is bringing that to the table and talking about it.

[00:09:55] Otherwise, it gets overlooked. How that translates into metrics is really difficult, particularly in HR. We were just talking about, I think, one of the biggest unanswered questions that a lot of people are looking to AI to answer is, how do you really measure productivity? There are certain organizations, sales being kind of the obvious candidate, where you do have a number associated with how valuable somebody is. You look at things like operations. You can look at ticket volumes, customer support. You can look at calls and customer satisfaction ratings.

[00:10:22] It's a spectrum of really easily measurable to very difficult to measure. How do you measure the impact of an HR business partner? You can look at attrition, but is the HR business partner really striving and responsible for attrition? I hope not. So I've thought a lot about this. I remember in past life, I had a people analytics team, and we did a bunch of whiteboarding sessions, function by function, coming up all this stuff. And at some point, someone stepped back and went like, why don't we just ask the managers?

[00:10:51] And I think that at the end of the day, today, that subjective measurement is the best thing that we have. And so enabling our managers to be good assessors of talent is even more critical in that regard. In the world of AI, we were just talking about this, but if you could capture someone's email, all their Slack correspondence, all the metadata in their calendar, you put a recording device on them, understood their conversations every day, added that to all the data on their work, I think there's a world where AI could actually get a pretty decent assessment

[00:11:21] of how productive someone is. One, that creates a real surveillance state vibe that I think would ruin the employee experience. But then two, the training set for that data, so you collect all this stuff and you try to determine who's productive or not, what are you going to measure that against? Do you train that using performance ratings for the most part? So I don't know if we can get away from that subjective assessment of talent. I think the goal is to make that more accurate. More objective. Yeah. Anything we can bring in that's an actual data point to prove that.

[00:11:50] I'm reminded we, one of the exercises I did with a CEO at a smaller company all these years ago, he said, Ben, I really want to tie everyone's bonus at the end of the year to something performance related. And for engineers, it came down to code and errors and bugs and all those sorts of things. Part of it was our core values were being innovation and so did they submit any ideas for improvements, things like that. But he got around to the front desk admin and he was stumped. Like, how did she smile enough?

[00:12:19] Did she answer the phone in two rings? How do we actually do this? And so that was my first exposure to, it's really hard in some jobs to define that and to hold people accountable. If we don't even know what it is as leaders, how are we going to hold them accountable to something on that? Yeah. I started off within a little bit of the script and went off completely. That's perfect. I've got some questions. This has been awesome. I love this. So knowing what you know about your background,

[00:12:48] if you're sitting in a room right now with a CFO or a leader in finance, do you think you use different language than someone would that came up purely in HR? And if so, what would that be? That is a great question. Language is part of it. I think anytime you can reference metrics, it's helpful with those folks. To me, the big barrier that's important to overcome in these relationships is the credibility barrier. I think HR in particular has a challenge that other functions don't have.

[00:13:17] And that is that everybody thinks they can do our job. Particularly in recruiting. Everybody thinks they can do recruiting barrier. Everybody has been hired for a job. I think, well, that was probably easy for them to find me. And so you're up against that in these conversations, especially early on. And the way that you create that foundation of credibility and get to be viewed as that expert is by really understanding your business, but really understanding your data. And so I think it's important to start establish yourself as the expert using those different tools.

[00:13:45] And then you can have much different conversations with these folks. ROI is something folks would love to talk about. And we'll probably talk a little bit about how you measure the ROI of some of these HR decisions. But capacity is a big one, right? The finance team, having been one of these people, trying to set headcount targets for the following year. You can look at seasonally adjusted trends. You can shoot ratio based. I think the... Oh man, I just lost my train of thought, Ben. It's all right. You're okay.

[00:14:17] So you're giving me some different things that you think about, like headcount planning, like some of those sorts of things that sort of touch both sides of that, right? There's an HR component. There's a finance component. But even knowing what you know, you're like, I've got to show up and be credible. That sort of ties back to your story early on where someone says, hey, before you tell them what to do, maybe you got to go figure out what they do first. And then you can help them with that. So that probably has a... You probably learned that early on. Yes. And that's followed you ever since. I love capacity planning as a place to start with that credibility.

[00:14:43] I've done some talks that are out there on how you build a capacity plan brick by brick. But if you can really predict your staffing, that's instant credibility for your finance team. Because that's usually their biggest expense line item. If you can make their lives easier in that regard, you get a lot more leeway to push in other areas. What's wild to me is when we look at our research on talent acquisition, we ask about, did you do a forecast? How close was the forecast? Yeah. There's a surprising thing that don't do it at all. Yeah.

[00:15:13] And for the ones that do, they're like, ah, way over, way under. A number of people hit right on. But even showing up with that, starting that conversation, you're like, hey, if we're 10% off, that's fine. But I know we won't be 50% off. And being able to have those conversations. Yeah. There was a particular moment in time, I think it was at Okta, we were hiring a lot. I think we were hiring 600 people a quarter. There was one quarter where my forecast was like 568. We wound up at 571. I walked right into the finance team's office and put it down on the desk.

[00:15:43] Like, boom. Nailed it. Pumped out your chest. We were much less resistant to our new recruiter requests when we needed to staff up for more hiring. All like that. Have I told, again, I forget who I've told this story to. I've mentioned on the podcast at some point in the past. But I had a chance to talk to the head of recruiting for H&R Block at one point. Oh, cool. She said, we have very weird seasonal hiring because of the tax season. Yeah. And she said, we always had this manager that would come in and say, hey, I need this many people to start on this day.

[00:16:12] And it was something unreasonable. And she said, we kept doing this button heads thing over and over. And they thought that we were just being hard to get along with. And so she said, next time they came in, she said, okay, I want you to look. We've put on the whiteboard what this looks like. This is the number of people you want to start and the date. This is how many people we had to actually interview. This is how many people we have to screen. And she backed into the funnel. Yeah. And they're like, oh, wait a minute. To hire 60 people, you need 800 resumes? Yep.

[00:16:38] And so how soon should I tell you next time you need to hire? They completely changed their narrative because they realized this isn't them just being difficult. This is, I see the numbers and it makes it real to me suddenly. Yeah. I love doing that reverse funnel analysis. The other thing that's always eye-opening is when you talk them through how important it is to resource recruiting ahead of time. Right? Because let's say you don't believe me and we get into the quarter and we're trending and we're going to miss our hiring target by 20%. Okay, now I got to go out and hire recruiters.

[00:17:07] That's going to take me 65 days or something along those lines from start to finish. From when the rec opens to when they actually start. And then I got to ramp those recruiters. And then those recruiters have to open their own recs. And then they have to hire. We're talking about a six-month problem here. Laying that out for them is always eye-opening. It creates a different conversation than just, hey, I need people. Why aren't you doing it faster? Again, wrong questions to be asking. Yeah. How can we be more aligned so that we're both on the same page? Yeah.

[00:17:37] Vacancies are expensive. Right? It costs the company money. They do. At the same time, I had a leader at one point that told me we were trying to hire for this role and they kept pushing it off. And I kept, I thought you needed them. If you don't need them, we'll close the recs. Like, no, we need them. And so we kept stringing along. And finally, we get started. He's like, I saved the company some money. We didn't even have a person to pay in this job for three months. This is a billable job. We would have made more. Oh. I shouldn't be teaching you that one.

[00:18:07] I thought that you would be ahead of me on that curve. So when it comes to finance, I would love for us to steal something from their playbook maybe. So it's something that you've learned when you got your initiation into that club. So when it comes to finance, when they're making a decision, they think about the P&L. They think about the balance sheet. It's got to connect back to something. We don't just do stuff to do it. Again, I've been in HR. I'll point the fingers at me.

[00:18:37] We do sometimes do stuff to do it. And is there a parallel in HR? Is there a thing that we should be doing here to tie back to everything? You mentioned productivity. You mentioned attrition. Is it one of those sort of things? It's something else. I don't want to say the E word for engagement. What is the thing that we need to be tying back to when it comes to the stuff we're doing that would be parallel for what they're doing on the finance side?

[00:19:02] Yeah, I think the thing I learned most from finance that you apply to HR is how to structure a problem. And I joke around that I think in Excel sometimes. How do I take this problem, put it into a grid, try to assign some values to it, and then solve it? You mentioned earlier that vacancies are expensive. I think one of the questions that comes up a lot is how expensive, right? Like what is the cost of not staffing this team? The analogy I like to think about is the military.

[00:19:32] There's some stat out there. It's like for every one person on the front lines, we have 12 people behind them supporting them. So do you judge battlefield gains just based on the number of soldiers, or do you distribute that across the whole stat? And so one way to think about the cost of a vacancy is to take the revenue of the company and divide it by all the employees. Maybe that's the cost of the vacancy. Do things like you can adjust this for seniority. Presumably a more senior person has a bigger impact than a more junior person.

[00:20:01] So maybe you're prorating that share of revenue by level, or even by salary. Yes. If you can articulate the rationale behind your crazy projection step by step in such a way where each step seems to make sense, you can get people along the story to the end goal. You talked earlier about having credibility, though. Like that sort of root of all of this. Yeah. Because there are plenty of people, I think, that would say, hey, vacancy's expensive.

[00:20:30] And someone might say, yeah, yeah, it is. And then stop. But the how expensive is an opportunity where you get to go and try to prove that. And so I know some people hearing us right now, if their leaders came in and said, hey, how expensive is that? Start sweating a little bit. You're kind of put on the spot to figure that out. But it's an opportunity to start building inroads, building connections, show that you're truly partnering and not just go through the motions, running HR programs.

[00:20:56] And again, all the negative stereotypes that HR gets called out for, you're actually proving that you're bringing the real things that the business needs. On a similar note, one of the things I was thinking about is the funding example I gave a minute ago on filling that vacancy for a billable job. Some jobs, some skills, some positions in the business are like revenue critical ones. Maybe your example on the military thing gave me that one. There are other ones that are just useful.

[00:21:24] When it comes to, I'm going to skip that one. I don't like that one. I'm trying to figure out where I want to take it. Training development. We talked about hiring. We talked about retention. Let's want training for a second. A lot of companies say, hey, we're going to train these people on this thing for this reason. And they stop there. And in the whole world of training, there's been a lot of conversations over the years about getting close to measurement and proving that value and really knowing the skills you're building and why that matters.

[00:21:55] If I said, take the things you learn in finance around funding a project or funding some improvement and said, apply that to developing skills on our people. How would you think about that? Yeah, this is a hard one. Usually in times of crisis, L&D is the first thing to get cut because it's one of the harder things to measure. L&D is a tough one. I think in a resource constrained environment, there's a couple of places where I like to focus L&D.

[00:22:23] The first one is management. I think if you can enable your managers, that improves employee experience first and foremost. It improves your ability to performance manage, which improves your talent bar. That one to me, especially if you're at a company that has a high internal promotion rate and you have a lot of first-time managers, it's a really great area to focus. I've had mixed feelings about internal L&D departments. And I'll tell you, especially at smaller companies,

[00:22:52] I've been at companies that have invested a lot in curriculum to find that nobody actually takes the courses. The reality is today that you can find world-leading experts giving keynotes on YouTube that are going to be far more impactful than some in-house training developed on the same topic. So I think the key is finding what are those key critical pinch points. Maybe it's first-time managers.

[00:23:16] Maybe it's AI and actually getting people to adopt AI and going after those first. And then how do you measure success? I think with the AI front, you can look at adoption. You can look at some of the use cases that come out of it. There's different ways to measure ROI and some of these AI cases. How many hours are we saving? Value creation. Yeah. In some form of fact. But generally, L&D is one that I think finance folks are usually pretty skeptical of.

[00:23:44] And I've not found a great gotcha where I can really nail them on that question. Okay. So we'll keep searching for that one. Yeah. I think anyone who's listening that's trying to justify those, that's the same answer, right? We talked about it earlier. You heard a session. You were like, they defined the problem really well that I also have, and I didn't get an answer. And I think that's how some of these are, is there's not a clear path to that. I think there's a similar thing you can apply here, which is build the credibility first, right?

[00:24:12] Start with that training that you know you can measure the impact of. Do that well. And then if your gut is telling you that this is the next thing, but maybe it's less measurable, and you really believe in it, you have the time to pursue that. We've talked about a couple different metrics in the last little bit. If you were talking to a CHRO, which you are, they're listening right now, what metric would you tell them to start tracking tomorrow?

[00:24:41] The big one for me is retention by performance grade. So are we retaining our top performers? And almost as importantly, what are we doing with our bottom performers? Are we getting them up in performance over time? And if we're not, are we managing them out? I think monitoring non-regretted attrition is important, and making sure that your top performers are staying at the company, that they have a career path. That's really critical. If that was the one analysis I could do, that's where I would start,

[00:25:10] is that performance lens. From that, do you have other things that tie into that? It sounds like it, right? Helping to level them up, helping to move them out if you need to. Do you have other things from the talent perspective, talent programs, or other initiatives that are in that to help continue that? One of my favorite charts that I've done was taking a look at org shape. So if you can imagine, again, I'm now thinking in Excel again,

[00:25:36] a horizontal bar graph where your y-axis is the different levels, senior manager, senior IC. And the mapping that so you have the shape of the org, and then color coding this by time and role. What you hope to see is that the lower levels, you don't have folks who have been in that role for three, four years. But putting that graph together, first just understanding your org shape is interesting, but then understanding who are these people who are in the yellow, orange, red categories in terms of tenure,

[00:26:04] and then pointing your employee success team or your HRPP team at those folks and saying, hey, why are they stuck here? Is it because this is their destination, and they've reached kind of their talent cap, and that's okay, we need those folks? Or is it because there's an unclear path to the next level? Let's go talk to the next level. Structural issue or something else? How that plays out in real life is re-evaluating your competency matrix. In this particular case, we found that between right before our staff level, there was a requirement to get to staff. It really shouldn't have been there,

[00:26:34] and it was blocking a lot of these really good folks from getting to the staff level. So we fixed it. I have a good friend. He's actually based here in San Francisco, and that reminds me of him because one of the changes they made in one of the talent processes, he said, we're lowering a barrier, but we're not lowering the bar. You still have to be at this level of excellence to do this staff level position. We're going to lower one of the barriers that keeps people out unnecessarily. So that's what's good from it. I can elaborate a little bit more on this answer because there's a couple other interesting points. I'm sure you can cut this around. But that particular point in the competency matrix

[00:27:03] was a requirement for cross-discipline engineering expertise. And so what we realized is that prohibits us from having career experts in a single discipline. We're saying you can't get to staff without broadening your engineering expertise, and that's not what we wanted. Another thing we saw in that analysis was that we had a bunch of people at our first level of manager, more than I would expect. And a lot of these people have been there for a while. And so upon further investigation, when we were hiring people from outside of the company,

[00:27:32] it was, we were looking at people with two plus years of experience. So our bar was, for this level, was somebody who's an established manager, knows what to do as a manager. But when we were promoting internally, we were throwing these folks right into the same categories as established managers. So it takes them two years to build that up from which they can then go to the next level. So we split that into two manager levels. But I love that org shape analysis by 10 years. That sort of changed me. Again, if you just said,

[00:28:01] hey, if you went to a leadership team meeting and said, hey, we split this up and we changed the structure of this, that may or may not make anyone react. You say, hey, listen, we actually lowered the attrition rate of some of our top performers by making two of these changes. Suddenly it's relevant. It's interesting. That credibility you talked about is there. Oh, gosh. Okay. This has been so much fun. You and I could just keep going on this. If someone wants to connect with you, wants to learn more about, you just follow Shane. What's the best way for them to do that? Yeah, find me on LinkedIn. We'd love to connect. Thank you again for,

[00:28:31] in advance for the tour. Can't wait for that. Thank you for saying yes again to joining me on the podcast. To all of you out there listening in, I hope you got some good notes from today. I know I did. Thinking about this in finance terms is helpful because it helps us get past that stereotype of HR that's just about, again, hugs and rainbows. We've got to get to some of the numbers and impacts so that we can get that attention from leaders to drive those changes we're looking for. We'll see you all again next time on We Are Only Human. Thank you so much for joining me on the show today.

[00:29:02] I'm honored to have you as a listener. If you enjoyed this episode, please take 10 seconds to rate it at iTunes, Stitcher, or wherever you listen to your podcast. Also, if you know a friend that could benefit from today's conversation, please pass it their way. After all, a rising tide lifts all ships. To see show notes, sponsor information, and our full show archives, visit OnlyHumanShow.com.