Redefining Learning Technology w/ Ryan Findley
Episode Overview
Welcome back to another episode of 'Making Better'. Today, in episode 48, we have the pleasure of diving into a thought-provoking discussion with Ryan Findley, Chief Learning Strategist at Learn to Win. We dig into Ryan's journey from founding educational institutions to a riveting conversation on the necessity of technology in education. We'll also talk about his bold transition of moving to the Bay Area and starting a family while getting a startup off the ground, and the insights he's gained along the way.
We will touch on core themes such as the importance of resourcefulness, the pivotal role of data in learning and talent development, and the potential of assessing learners' confidence alongside their knowledge. Our conversation will take a deep dive into the promise AI and analytics hold for revolutionizing learning techniques, especially in the field of sales. You'll gain a new perspective on learning technology and see how it's not just about compliance and completion, but how it can be a strategic function shaping performance outcomes. So sit back, tune in, and let's get making better.
Checkout these book recommendations from the episode:
Thinking In Bets by Annie Duke
What’s Our Problem?: A Self-Help Book for Societies by Tim Urban
Reach out to Ryan on LinkedIn: www.linkedin.com/in/ryanfindley
About Ryan Findley
Ryan Findley is a strategist, product leader, designer (product & learning experience), and lifelong educator. He has served as a C-Suite leader for over 10 years between pre-seed start-up stage and Series B+ scale-up stage. A builder and creator at heart, Ryan has created everything from course curricula and end-to-end programs to entire schools and learning tech products.
Full Transcript
-
Ryan Findley [00:00:00]:
So we've tried to focus in on areas where knowing something and being able to confidently do it is the metric of success. And so the the leading indicator of being able to actually do something, which is something that's going to have to be observed on the job in most cases, is if somebody is, is confident in their mindset around it and the story they tell themselves, their ability to do it will be more predictive than just like. Could you answer a multiple choice question?
Matt Gjertsen [00:00:30]:
Hello and welcome to the Making Better podcast, where we talk about how to make ourselves, our teams, and our organizations better. Whether you are a business owner, a manager, or a learning development professional, this show will give you actionable insights of how to improve your own performance and the performance of those around you. Our guest today is Ryan Finley. Ryan is a strategist, product leader, designer and lifelong educator. He is currently the Chief Learning strategist at Learn to Win, a learning platform focused on delivering more actionable and focused learning experiences. In today's discussion, we touch on Ryan's time leading learning programs in Africa and what technology can do to improve learning outcomes. Before we get into the discussion, I want to remind you that if this is your first time watching the show, I highly recommend you subscribe so that you never miss a future episode. And if you're already subscribed, then I would ask that you share this show with at least one other person because that is how we grow.
Matt Gjertsen [00:01:34]:
I can't tell you how much it means to me. And so with that, let's get into the discussion. Ryan, welcome to the Making Better podcast. How are you doing today?
Ryan Findley [00:01:45]:
Good. Thanks for having me. It's good to connect in this way, I guess. We've been chatting for, I don't know, emailing, chatting for almost a couple of years by now, so it's fun to connect on.
Matt Gjertsen [00:01:56]:
Yeah, it's been a little while on.
Ryan Findley [00:01:57]:
Your show, but yeah, I'm doing good.
Matt Gjertsen [00:01:59]:
Yeah. Excellent. That's good.
Ryan Findley [00:02:02]:
Yeah.
Matt Gjertsen [00:02:02]:
And we even got to meet in person once and chat about some stuff, which was great. Yeah, exactly. This is one of those situations where the online relationship came into an IRL relationship a little bit. So, yeah, it's always great to chat with you. I gave a little bit of an intro to the listeners beforehand, but I think we got to start with anybody who looks you up on LinkedIn is going to see you spent a bunch of time doing work in Africa and learning in Africa, and that's a very different direction for a lot of people to come from. How did you get involved with that and what did you learn there?
Ryan Findley [00:02:42]:
Yeah, it really was a rich season of my career. It was almost ten years of working in, or kind of on different projects in Africa. So it was a huge chunk of my life and of my career actually started. My first foray into working on the continent was through, of all things, an apparel company. A couple of friends and I started, and we wanted to be a social business kind of growing in Africa, cutting, sewing, printing and shipping from the continent, and really trying to kind of rebuild what was once a pretty robust industrial base on the continent. And they kind of went through, they had a rust belt kind of situation like we did in the US. And a lot of the manufacturing jobs went to Southeast Asia. And so it was almost like, at first, it was kind of an academic problem.
Ryan Findley [00:03:50]:
Could you just reestablish those factories and those sort of shipping and logistics sort of pieces and rebuild those industries? And what we found out through a couple of years of this pilot project was, you could. But the biggest problem we had was when we got to port, which was one of our biggest markets to sell. So you can make a cheaper shirt or sweatshirt or whatever in Africa, if it's all African cotton and you kind of aren't shipping it all over the world. The problem is that by the time it gets to the US, because of the transportation costs just being so astronomical, that now you're selling something at 1.5 or two X, what it would cost from Southeast Asia, China, is that just.
Matt Gjertsen [00:04:51]:
Because there aren't as many established channels, like, there's just not as much traffic going that direction, so the costs aren't as low.
Ryan Findley [00:04:58]:
Yeah, I mean, the biggest one is basically that you can put it on a plane and have it in two days, but now a $3 shirt, what might be a cost $3 is now $9 because you just had to absorb that cost. You could put it on a ship and that maybe only adds like one dollars or something to the cost, but you're not going to see it for sometimes six weeks, because a lot of times the lady's shipping lines work is that they've got a box and they're saying, okay, we're going to fill this box with whatever needs to get imported to the US, and your box doesn't leave until it's full. So you could be the first person into that box with all your shirts and sweatshirts and whatever else, and it could just sit there and they will make no promises about when that thing will get filled up, because for them, it doesn't make sense to ship an empty or half empty box. So you're counting on all these other people to fill it with pottery or with anything they're making on the continent. And you're hopeful that everyone will do it in this short period of time so that you can get your goods, but at least these really long lead times, and you have no predictability around when things will come in or when you can then start advertising them and printing on all these things. So it ended up being a lot more complex than I had any idea. But through that, I fell in love with just working with the different cultures and variety of just the nuance of working in Africa. And that led to me going and taking a job teaching kids how to build businesses and pursue entrepreneurial ventures in Africa.
Ryan Findley [00:06:41]:
And so I was teaching at a really cool school down there called African Leadership Academy, which I still think is one of the coolest places in the world. The best and brightest from all over Africa. These kids are 16 to 18, and all of them who are really chosen because they want to change the face of the continent. And so I was really very lucky and blessed to get to teach there for a couple of years.
Matt Gjertsen [00:07:04]:
That's awesome. So I noticed one of your last locations, at least what you have on LinkedIn, was on Mauritius. Did you live there?
Ryan Findley [00:07:10]:
Yeah, I got to live in Mauritius for. We were there about a year and a quarter, maybe almost a year and a half.
Matt Gjertsen [00:07:17]:
Okay.
Ryan Findley [00:07:17]:
Yeah. So that was one of my last.
Matt Gjertsen [00:07:20]:
Yeah. For anybody who doesn't know, make sure to look it up on the map because it's kind of out in the middle of the Indian Ocean. The only reason I know about it is because there's like a satellite communication station out there and so on. Every SpaceX launch, something like 20 minutes after launch, there's always signal acquisition. Mauritius is a call out as it gets over the island.
Ryan Findley [00:07:41]:
That's so funny. I didn't know that.
Matt Gjertsen [00:07:43]:
Yeah. If you watch a SpaceX launch, almost everyone that's cool calls it out in there.
Ryan Findley [00:07:49]:
I didn't know that. It's well known in the military community because there's a big thing out there that nobody can.
Matt Gjertsen [00:08:02]:
That's really. That's really neat. That had to have been just such an inspiring kind of experience to be doing that kind of work out there. It must have been, right?
Ryan Findley [00:08:16]:
It was. I was just working with the most incredible people. The kids were amazing. My colleagues were just always so invested, so passionate, so intelligent. Everybody that worked there could have been doing any other job. But I mean, by that, I mean, they were just so incredibly talented at what they did and the fact that everyone took a pay cut and sort of just like a left turn to go work at the school or with this kind of sister organizations. And because of that, it was just the cream of the crop when it came to the people I was working with and the kind of stuff that we got to do every day. And I was there at an opportune time when one of our founders wanted to create a new college out of thin air.
Ryan Findley [00:09:16]:
And so I got to be there working on the founding of a college, which most people just aren't lucky enough to be in the right place, right time to do, and then the founding of an MBA program and Then an undergraduate degree program. I was just in the sort of right place, right time for so many cool things that were just happening, and I just got to be involved because I was there. But, yeah, it was the kind of thing where for those years, I barely register it as work. It was really just kind of like different ways to kind of live out a passion and kind of a vigor for doing good things in the world.
Matt Gjertsen [00:09:58]:
Yeah, that's awesome. So then you went from there to learn to win, which is a learning technology platform. How did that come about? How did that move come about?
Ryan Findley [00:10:09]:
Yeah, actually, so one of the guys I was working with at ALA, which was the high school, and ALU, which was the university, he and I stayed in touch and we were working together. We were together in Mauritius one time, and we were talking about what we were learning at the university level, which was we were trying to have a high access, low cost university, which meant we wanted to have a quarter of a million students at all times across 25 countries or campuses at least. And we want to do a whole college degree for like 10,000, $5,000 total, not per year total. And the way you do that, the only way you get anywhere close to doing that is if you have a really strong technology that helps, you can basically take a lot of your recurring costs and push it to the technology. Of course, it's things like student information systems and registrar and stuff like that that you need to automate admissions, some of those things. But it got to the point where we realized, okay, we've really got to somehow automate the learning. And so we were talking know, Andrew and I were just talking about, wow, if you could really automate learning at the university level, not entirely taking professors out or anything like that, but use technology in ways that know where technology is effective and use humans where humans are effective, if you can build a tool like that, like a duolingo, but for a whole college degree, all things well. Wow, that seems like that solves a big problem in the world, right? Not just for us at ALU, but for other colleges, and, wow, for who else could benefit from that? Companies, et cetera.
Ryan Findley [00:11:59]:
And so we were just kind of just literally just driving through sugarcane fields, just kind of spitballing ideas and things. And he just kind of had this line of know. Yeah, my budy Sasha and I. Andrew went to North Carolina, and his budy Sasha played basketball there and said he always found it. It was really hard to learn the playbook at this university. Great basketball program, really complicated playbook. And he was like, they talked about what if there was an app to help players learn their Playbook? And I was like, oh, that actually would be really fun to work on. It's kind of a micro version of that same problem.
Ryan Findley [00:12:40]:
And I was like, if you guys ever work on that, let me know, because that would be fun. And, like, six months later, they called me and they're like, hey, we're getting a working group together if you want to join in. And so we started doing nights and weekends, kicking around PowerPoints and mockups and things like, know. Within a year, we had an MVP, and Andrew and Sasha were off to the races at Stanford. Both, like, selling, but know, getting connections in the Silicon Valley area. Pretty soon, Andrew called me and he's like, hey, so we just got a big chunk of funding. We're in the middle of grad come. Could you leave Mauritius and Alu and come learn to win going.
Ryan Findley [00:13:27]:
And I was like, yeah, let's do it. I ended up joining full time in early 2020, brought my wife and soon to be baby girl over to Bay Area in early 2020, and we started running learn to win. That's when I was working on learn to win full time.
Matt Gjertsen [00:13:51]:
So you moved to the Bay Area in early 2020. That must have been an experience right there.
Ryan Findley [00:14:00]:
Yeah, everyone has their own story around it, but for know, landing in a new place. I hadn't lived in the Bay Area before. Just about to have a baby, trying to get a startup off the ground. It was crazy for me, that version of it. We had an interesting, chaLlenging, but also rewarding time in the Bay a couple of years there.
Matt Gjertsen [00:14:36]:
Yeah, it's an interesting. You decided to do the same trial by fire that my wife and I did because we had our first child moved across the state, and I left the military all at the same time. You were probably one of the few people I've met that did a more extreme version of doing all three things at once because you didn't just move across a state, you moved halfway around the world.
Ryan Findley [00:15:04]:
New job, new country, which is my old country, new Family edition. It was a lot.
Matt Gjertsen [00:15:11]:
Yeah, that is a lot. Wow. Well, you made it through. I'm sure you've learned a lot. It's neat that you focused on that technology piece, which I think is so interesting. Now I'm imagining you've gotten to know quite a bit about the learning technology space and what it means for education. You highlighted how that technology piece is a really key piece for certainly enabling your originally envisioned in higher ed, but it's the same thing that's true in corporations. How have you found, what have you seen that things that need to change about learning technology in order to enable better learning inside organizations?
Ryan Findley [00:15:57]:
Yeah, it's a really good question. I think one of the things that we at learn to win really quickly sort of gravitated towards was the value of data in learning tech and just how, from our standpoint, there was a serious lack of insight from the data that was available in a lot of legacy tools. And I think, to be fair, I think a lot of early days of learning technology were really driven by scorm formats and things like that, as well as that sort of on one side and on the other side was sort of ERP SIs or HRIs systems or things that would evolve into LMSs. But we just sort of had these certain restrictions that came from being really just like enterprise. They were meant to be enterprise tools, not learning tools. Right. They were for the benefit of the organization, not for the learner. And so that's sort of these two insights around this was built for the company and not the learner.
Ryan Findley [00:17:20]:
And this was built without the ability to collect any meaningful data around. Where are students getting stuck? What content is effective, ineffective? Or where are the learning gaps that people could target and practice remediation on and then move past? So these are some of the things that we were seeing early on that they just weren't out there. And funny enough, it was some of our early customers in sports and military that helped us realize that, because they're the ones who were most interested in like, okay, so I did this. How do I know if it worked? Which it seems like an obvious question a lot of times, but if you look at the tools that a lot of learning designers or Clos or whatever were dealing with, it was the kinds of data they could get back was, well, they did it, or they didn't do it, or they got a 90% or they got a fail, or it took them 22 minutes and these things were not. You could maybe try to make them proxies for. Was it worth doing this? What should I take from these analytics? But a lot of times it was almost like they were meant to count something else, which was completion, basically, and compliance.
Matt Gjertsen [00:18:41]:
Yeah, I mean, like you mentioned before, since a lot of this stuff kind of evolved from existing HR tech or organizational tech, it really is very process driven rather than outcome driven. Totally. Which is an interesting way to. An interesting way to think about it.
Ryan Findley [00:19:00]:
Yeah. And no shade. Right. People were dealing with what they had. When I look at the things that people were creating with an articulate or something like that, these really robust learning experiences, and then you look at what was possible to get on the back end of that and it's just like there's such a mismatch with what the formats out there allowed. And I know that some of that's evolved with X API and things like that, but just think about the legacy of these things was still very much archaic and not built around I need data to make a decision. It's like learning was just a thing to do versus a strategic function. Right.
Ryan Findley [00:19:43]:
And I think that's sort of philosophically how we see learning in organizations as using it as a strategic function, a thing that could be even like a leading indicator or a predictor of how someone might do, and not in a way that's going to make predictions of, like, this person can't do their job, and so, you know, bad things happen to them. It's more like, hey, if you're a manager and we think there's a 30% chance that people don't know how to run an emergency procedure or something. Like, if you're on a medical floor and there's 30% chance that not everybody knows how to run a code blue, you could just say like, hey, let's take three minutes at the beginning of the shift and just make sure that we cover code blue again. Or here are the emergency exits, or here's what you do if your rudder isn't working or, I don't know, this sort of machine, your mid surgery, and this sort of thing just doesn't work anymore, what then should we do? We think there's a world in which learning and assessment is on the front end of these things and is actually a contributor to getting out ahead of mistakes or just compromising situations.
Matt Gjertsen [00:21:06]:
Yeah, because I don't know how much you've dove into, you mentioned X API, how much you've dove into that or that world. Because I know from my perspective, I feel like one of the reasons, there's probably many, but one of the reasons why XAPI has had trouble gaining traction and wide usage is kind of because it's such a wide open field, like you can really do anything with it, you can track whatever you want. And so it's just like, if I'm a learning designer and all I've ever done is completions and maybe score percentages, then it's almost too much. Whereas it feels like with learn to win, at least the last time I saw it, you all centered in on this idea of confidence, confidence of the learner, where that was the big additional data point that you're using as a strong proxy to do they truly understand it and asking them just how confident are you in your knowledge? Is that paring down? How is that process done? Is that part of the reason why you selected it, to kind of just eliminate these many choices?
Ryan Findley [00:22:12]:
Yeah, you're totally right. I mean, X API is amazing in that way and also probably just kind of like paralyzing in that way.
Matt Gjertsen [00:22:19]:
Because.
Ryan Findley [00:22:23]:
If you're in the Navy or the Air Force, there's maybe a lot of things you might want to track from simulators and from different things, but most people, there are only a couple extra things they might want to. But then it can also get complicated. I think there's a lot possible. There's not necessarily clarity around it or strategic thinking around it. Always, I think it'll be emerging, but it's murky. What we've done with that is we've said, okay, well, what's one of the most important things that we can capture very easily? And one of those things is we think confidence, because in almost every field that we work in, the ability to perform the work is incredibly important. We don't really serve industries where you want people to know trivia.
Matt Gjertsen [00:23:19]:
You're not a compliance tool.
Ryan Findley [00:23:20]:
No. And I would challenge that. Most people, outside of compliance laws, most companies do not have the time or capacity for trivia. It's something that just has kind of happened because, well, Trivia is something we could count. And if somebody knows what year the company was founded, well, I could give you a quiz on that.
Matt Gjertsen [00:23:40]:
Okay.
Ryan Findley [00:23:41]:
Yeah, they know that the company was founded in 2001, but does that help them do their job right? Not usually. So we've tried to focus in on areas where knowing something and being able to confidently do it is the metric of success. And so the leading indicator of being able to actually do something, which is something that's going to have to be observed on the job in most cases, is if somebody is confident in their mindset around it, and the story they tell themselves about their ability to do it will be more predictive than just like, could you answer a multiple choice question? So with our asking people not only what their answer is, but how confident they are in their answer, we're kind of able to add the second dimension of learning data that hasn't existed for most time in most places. It gives you that second place to say, okay, well, they know it, but they don't think that they know it. Right. Which is a very different problem. It's a very different problem from somebody who doesn't know the answer, and they're 100% sure that they know it. Right.
Ryan Findley [00:24:49]:
Those are like two different humans, basically. But if you imagine your average classroom, that's just like, a right answer and a wrong answer. You don't necessarily see it with the color, but when you see somebody who's right, but they didn't even know that, and somebody who's wrong, but they believed it in their heart and their soul, you can just imagine those two people in your mind and being like, oh, man, I need to put them in different corners of the room and take totally different steps with them to get them to where they need to be, which is everyone wants their learners to be confidently.
Matt Gjertsen [00:25:28]:
And you reminded me of Annie Duke's book, Thinking in Bets, and she's a former professional poker player, and she always talks about how you can be right for the wrong reasons and you can be wrong for the right reasons. Like, you can get something wrong, but still you were thinking the right way when you got it wrong.
Ryan Findley [00:25:50]:
That's a very good analogy. I see a lot of connections to poker there.
Matt Gjertsen [00:25:56]:
Yeah, absolutely.
Ryan Findley [00:26:00]:
When you start to start to see that, it's like, wow, okay, that actually is a really helpful dimension to knowing what then, should I do with this person? Right? Because the right and the wrong answer is just the first step. What comes next is what's really valuable. And again, we're trying to march these people along to being confidently correct and able to do that job and know that they can do whatever job is required of them.
Matt Gjertsen [00:26:26]:
Yeah, I love that approach, really, because it just accepts the fact that, let's be clear, most jobs actually, though, what we ultimately. So we ultimately care about, can somebody do a thing? And most things are just going to be too complicated for you to try to stuff into a learning platform and actually test. You got to go have them do it, watch them. So we're almost kind of just assuming that's something that's going to have to happen, be tested on the job. So what's the closest corollary we can get to that? It's not trivia, it's not multiple choice questions. It's just do you feel confident that you're going to be able to do this yes or no or how not yes or no, but the whole scale there. I love that approach.
Ryan Findley [00:27:17]:
Yeah.
Matt Gjertsen [00:27:17]:
So then we've briefly talked about AI a little bit in past conversations. I know you're thinking a little bit about it because I do think AI opens up a lot more possibilities with this idea of really testing people's understanding. Because now, instead of a multiple choice question, you can potentially, maybe not quite yet, but you can potentially create a scenario where you do ask somebody like tell us your sales pitch and then they speak it and then the AI can judge them in a realistic way. How are you starting to think about how AI is going to affect learning technology in that assessment part of it, because there's the whole creation piece, which a lot of people are utilizing. How do you see it affecting the assessment and the evaluation piece?
Ryan Findley [00:28:14]:
Yeah, I think that's, to be honest, more exciting than the creation stuff. There are really cool things on the creation side. And what I do like about the creation side is I think you're going to be able to assess where somebody is and auto generate questions that get people up to where they need to be and that will be cool and that will be really effective. I think on the analytics side, though, there's a lot that's going to be able to be learned about. When you have enough data, I think you're going to be able to start making some really strong predictions or very well informed guesses about where are pockets of people who are ready for a promotion or who would make great mentors or people who are maybe they're not being fully utilized in the company and being able to identify that within the realm of learning, but extrapolate it to the job or real world performance. Even somebody like, hey, based on what we're seeing from, if you've got a fairly extensive, you've got something like a financial plan or something where it's like a pretty extensive ramp up time to get somebody going. If you see somebody who's really shoots out of the gates and you know that for the last 50 people who've gone out like that, they've been top performing financial planners or something. Why would HR not want to know about that? Right? Why would that person's manager not want to know about that? It seems like obvious to me that these things can start to be predictors of and influencers of what happens in a person's career.
Ryan Findley [00:30:02]:
And similarly, if you see somebody who's, like, struggling out the gate and you know that 99% of people who start this way don't make it through, maybe there's a place to have a compassionate conversation early on there with that person to say, like, hey, we'd be happy to keep you around. We just want you to know that based on your trajectory, you may not make it in the way that you think. What adjustments can we make now to change your trajectory? Right? And someone might be like, holy Smokes, I didn't know that I was studying poorly or that the first three weeks were so crucial. I can really double down now. I think there are other things you can start to do with looking at groups of people and being able to predict performance. The people who are leading here, by a long shot, in my opinion, is the sales tech tools, because what they're looking at is they're looking at all this data that's coming in from outreach to how many times are they doing kind of a pulse with sales leads, with how confident are they on the phone, all these things, as well as learning in some of the tools, and they're starting to make predictions about what is the revenue that every rep is going to contribute, and rolling that up to the level of a CRo or a VP of sales to say, like, hey, this region is about to miss, because these three people who are specializing on this product is about to miss. If you're in sales, yeah, it's easy to fire people, but it's hard to replace them. It'd be much easier, if you can, to sort of do some targeted training, and if that can be highlighted for you five weeks before the quarter is over versus three weeks after the quarter is over, that is incredibly valuable.
Ryan Findley [00:31:47]:
And I think that's why these things are happening in sales first, because there's just so much money to gain or to lose. But I could see that stuff, those kinds of things, trickling into learning tech everywhere. And I really see an eventual merging of learning tech and enterprise software of all sorts. Because I think, again, I do think there's value in the predictive nature of what people know and can demonstrate in learning realms and how that translates to actual performance.
Matt Gjertsen [00:32:17]:
Yeah, I agree. I was actually on a call I'm part of the planning committee for ATD Technology, and we were talking about AI and how to have a conversation around AI, and we were just kind of struggling of how to have a better conversation or a different conversation than what is commonly happening at a lot of conferences. Because it's so new. It's kind of just like, oh, it's this big thing. We don't really know how it's going to affect us, or it's very focused on generative AI. And I think it's just because ultimately we might fight it. But learning isn't. There's a lot of money in learning.
Matt Gjertsen [00:32:52]:
You know that you started a learning tech company, so there is money in learning, but it is dwarfed by the money in sales or places like that. And so I do think you're 100% right that that's the place to look for advances in utilizing this stuff, and it's the closest corollary to how we're going to use it. Yeah, I 100% agree with that. That's awesome.
Ryan Findley [00:33:20]:
Yeah. And sales enablement tools are amazing. If you look at what they can do with pitch practice, role plays. I mean, all these things are being automated because for tHem, it's so expensive to have a rep wash out or to fly everybody to Vegas. Yeah, the reps loved it, but what did you get out of it? It's much more productive to say, hey, take 3 hours of an afternoon and work on your pitch for the next quarter's big product launch. And then managers are getting to see the roll up of how much talk time did people have? Or how confidently could they speak to the new tools or releases? And oh my gosh, the data around that and the ability of a sales leader to make pinpointed decisions and corrections based off that is just unreal.
Matt Gjertsen [00:34:10]:
It's a good point. I can see a world where sales enablement tools really leapfrog into a lot of learning tech, because my biggest problem with sales enablement tools, historically, when I've looked at them from a core learning perspective, is that they just tend to have a different expectation for the ratio of learning personnel to learners. Right. I've seen plenty of sales. When you look at the sales enablement team versus the sales team, it might be one to ten or one to 20, or on a high end, maybe like one to 50, whereas in the broader corporate learning world, it's like one.
Ryan Findley [00:34:49]:
To 1000 connects that.
Matt Gjertsen [00:34:52]:
Exactly. And so the scaling tools weren't there in the enablement tech, but those are probably the things that. But when they build AI into it. I can imagine a world where all those things that weren't scalable before become very scalable, which could solve a lot of those problems. That's interesting.
Ryan Findley [00:35:16]:
Yeah, well, I want to be respectful of your.
Matt Gjertsen [00:35:19]:
Yeah, no, please go ahead, finish your answer.
Ryan Findley [00:35:22]:
No, I was Just saying I've reviewed many sales management tools and some are clearly better than others. But there are a couple where I'm very impressed with what they're doing from a learning standpoint and I could even see them making legitimate plays to compete with LMS very Soon.
Matt Gjertsen [00:35:43]:
Yes, totally. Well, I want to be respectful of your time, so I want to finish this up. I think this has been a great, really interesting conversation on kind of the learning tech front. We usually finish up with three questions with kind of rapid fire questions. And so the first one is, what is one book or podcast that someone should read or listen to? And.
Ryan Findley [00:36:11]:
Great. It's been a great read. It's called what's Our problem? And it's a really interesting sort of meta analysis of what's going on in society. So Kim Urban is the author. Just like a really interesting read from a very zoomed out perspective. He's kind of like a social commentator. I think he has other formal training as like a software guy or something, but has been writing. Okay, I think it's weight, but why for a very long time and just take these long form breakdowns of like, why is this like, know and just going into all the facets of it, so really interesting writing.
Ryan Findley [00:36:53]:
And in this he sort of starts to unpack of know, what are we seeing in our world, in the US? And he talks mostly about the US, but what we can do to sort of start getting back to maybe where I think a lot of people would like to be.
Matt Gjertsen [00:37:09]:
Yeah, I've listened to a lot of interviews with him where he talks about the book and talks about kind of the larger concept of if all of human history, of modern human history was, I think he uses like a 500 page book and the Declaration of Independence was written like two thirds of the way down the last page or something crazy like that.
Ryan Findley [00:37:33]:
Yeah. Perspective of all the things that have happened and how he just has this visual of all these boxes of time. And it's like you only get to the very bottom of all these boxes and it's like the first evidence of human art or something. And it's just like, holy smokes, this is the last 10th of this page, or 100th of this page almost. And then you start to think about civil rights movement and all these things have happened in the last whatever, however many years for us are just like, in the scheme of known human history, a line you couldn't even see on the page and just sort of putting things into perspective is really interesting.
Matt Gjertsen [00:38:17]:
Yeah, super interesting. Awesome. That's a great one. Okay, second question. What is one skill that has helped you most succeed in your life?
Ryan Findley [00:38:31]:
I think resourcefulness is one of my favorite go to skills because it just sort of like, you're sort of never stuck if you're resourceful. There's always some maneuvering or some way to just think anew about a problem or a limitation or something. And so I think that's if you can just, like, I don't, and I don't even know. I'd love to figure out how to cultivate that in my kids, but I think resourcefulness is one of those skills that I've just benefited from time and again.
Matt Gjertsen [00:39:01]:
Awesome. That's a great one. And then final question that I think we've kind of touched on this a little bit throughout the episode or our discussion, and I'm sure you would have a great perspective on this since you talk to a lot of different organizations, but what is the most common opportunity you see for organizations to improve talent development?
Ryan Findley [00:39:28]:
I think I would come back to that data piece, you know, is really not just saying, like, what was our throughput, but what was our true success rate? And part of that is, let's define our success. What does success look like? What are we actually looking to do? In what ways are we trying to move the needle and then think about how do we measure those things? And I don't believe that maybe all those can be, all those data points can come necessarily from the learning realm, but at least more than the few or zero that they're getting now. And I think that if people are more intentional about the ways we want to improve performance or retention or whatever it is, call those out and work backwards from those. From a learning standpoint, I think there's a lot more. There's a lot that companies could gain from doing.
Matt Gjertsen [00:40:22]:
Awesome. Awesome. Well, Ryan, thank you so much for your time today. I thought this was a great discussion. I think. I'm sure it gave a little bit of a perspective. Learning technology is one of those things that, honestly, I really love talking about it, but I think a lot of people don't necessarily have time to think about it, or they don't get into the nitty gritty because it handles their systems or something like that, but it's an enabler for what we do. So I'm appreciative of you taking the time today.
Matt Gjertsen [00:40:53]:
I'm really excited about the work you and learn to win are doing to kind of advance this front of getting us thinking about this technology a little bit better. So thank you again so much and have a great rest of your day.
Ryan Findley [00:41:06]:
You got it. Thanks Matt. Cheers everybody.
Matt Gjertsen [00:41:08]:
Thank you so much for tuning in today. If you liked the discussion, make sure to hit like and subscribe so you never miss an episode. As a reminder, if your team is struggling keeping up with the training development demands of your organization, we want to help. Better Everyday Studios is a full service instructional design team that can help you with everything from ideation to actual content creation and delivery. Please reach out to us using the link in the episode notes below. Have a great day.
Thanks for Listening!
It means so much to me and the guests that you chose to spend your time with us. If you enjoyed listening, make sure you subscribe using your favorite player using the links below.
