According to research by IBM, just 16% of AI initiatives have achieved scale. Why? Because few organizations have the structure and data to support long-term AI investments. So, how do you build an AI-ready system?
Riley Rogers: Welcome to the Win/Win Podcast. I’m your host, Riley Rogers. Join us as we dive into changing trends in the workplace and how to navigate them successfully. Here to discuss this topic is Rich Weymer, Senior Director of Go-To-Market Strategy and Transformation at Yubico. Thank you so much for joining us today, Rich. I’m super excited to have you here to dig into all the expertise that you’re gonna bring to the table.
As we’re kicking off, I’d love if you could just tell us a little bit about yourself, your background, and your role.
Rich Weymer: Yeah. First off, thanks for having me. A repeat customer with Highspot, so excited to get invited to this, as we’ve worked with your organization for some time now.
Like you said, Rich Weymer. I’ve spent time pretty much so in tech for most of my professional career in one form or fashion, from my earlier career days at Microsoft working in consumer goods, where I’ve worked on video games, your Office products, all your devices, through where I’m at today in the security world.
RR: Well, amazing, and bravo, tech veteran. Not easy.
RW: Yeah. It looks a lot different today than it did when I started, that’s for sure.
RR: And I think that is exactly what we’re gonna talk about today. But before we go into where the world of tech has been to where we are today, I’d love if you could give us a little bit of foundational context for folks who might not be familiar with Yubico.
Could you give us a little walkthrough of who your company is, what you do, who you serve?
RW: Yeah. So Yubico does phishing resistance hardware MFA, which basically means we ship you a little bitty key that helps control access to all your online portals and logins and everything along those lines.
RR: As somebody who is password challenged, I certainly see the value of that one. I wish we had a wonderful little bitty key that got me set up for success every single day.
One thing that I think you set up early on is that Yubico, and pretty much every other organization in the industry, is moving fast, and it has to. Security in this day and age is harder than ever.
And when it comes to working in a fast-moving organization, teams like yours also have to move fast. I’d guess that that pace of change is part of the reason why you have a really forward-looking approach to enablement and to go-to-market strategy. So why do you think it’s important to think critically about how technology can transform traditional workflows, processes that you’re accustomed to, things like that?
RW: Again, to your point, things are moving so fast right now. That’s the biggest underlying factor that organizations really need to think through. Decisions that you’re making today are almost obsolete by the time you’re done signing the paperwork on whatever decisions or procurement you’re going through.
So you need to be really thoughtful about the foundations that you’re building, the integrations that you’re gonna lean on, and the partners that you’re gonna select that are gonna be around for the long run. Measure twice, cut once, and also understand that there’s different types of decisions that you’re gonna be making.
I use the analogy of a hat, a haircut, or a tattoo. What type of decision are you making when you’re thinking about your technologies? If it’s a hat, you can switch it in and out real quick. If it’s a haircut, maybe it takes a little bit of time to unwind. And those tattoos are the ones that you just can’t change.
They’re gonna be– They’re– You’re gonna live with them forever. So you really gotta just understand the lens that you’re making the decisions through, as well as having an industry understanding of where things are heading. And as you look at your partners, thinking, “Hey, at the pace at which innovation is happening, is this someone that’s gonna be relevant six months, 12 months, 18 months from now?”
RR: I have not heard that decision-making framework before, hat, haircut, tattoo.
RW: It’s an easy one, yeah. A lot of organizations think everything’s a tattoo. So you make every decision like it’s the last decision you’re ever gonna make in that space. And it’s right for a lot of things, but framing it goes a long way, especially when you’re trying to move fast.
Being able to categorize those decisions pretty quickly goes a long way.
RR: Yeah. And it helps you avoid the problem of when everything’s important, nothing is. You mentioned systems, data, processes, having the right tools in place to move quickly. So with that perspective in mind, how are you thinking about layering on AI?
RW: I think about it every day and night, in every meeting I’m sitting in, and every conversation I’m having, and every free minute when I’m thinking about work. The big thing is automation and AI for the sake of AI, and automation for the sake of automation, it really doesn’t mean anything unless you have a strong foundation and an understanding of your data.
So to me, it all just boils down to a strong foundational data set and understanding what to measure and what moves your business, and then building around that first and foremost before you do anything else.
RR: What do you need in that foundation before you can start building AI on top of it in order for those initiatives to be successful?
RW: If I were to think through how I structure this, there’s no shortage of ways to measure the business, but landing on one that’s influential and helps you adjust the dials as you go is really important. So the way I operate is through the lens of sales velocity, which is a time-tested mathematical problem to give you a temperature check on how the business is doing.
It’ll let you know whether you’re going up, down, left, right, staying center, or whatever it is. But where organizations stop is they stop at the top four measurements, which, if you think of sales velocity, is open opportunities, average deal size, win rate, and then you divide that by your deal cycle length.
That gives you a daily throughput, which tells you part of the story because you can help understand your forecasting. When you take your close one business, you can use that to forecast days left in the quarter, what those numbers would look like. But where it gets really powerful, and what I think a lot of organizations haven’t spent the time to do, is go deeper on the leveling of those metrics.
So if you think through the process lines, L1 is your executive metric. That’s the all-up number. Your L2s are your leadership numbers, where your managers need to understand those. But your L3, four, five, six, and you can keep going down the rabbit hole, really start impacting how your frontline folks operate.
One of the things we’ll talk about today is AI Role Play, and when we think of it, we look at diagnosing issues in our win rates, and we think, “How is our competitive wins doing? What are we, we get very, very granular in how we look at those.” And then we can actually start layering on recommendations and automation.
So we do that across probably close to 100 different metrics through the various layers that are our leading indicators. And this really helps us when we think through automation of where we go from here, ’cause once we understand those, we know how are we doing against certain competitors?
Are we getting the right amount of MQLs? Are we talking about the right things? Do we get caught up in legal, security? We can understand all those different variables of the business, and then we can take a proactive approach to coaching where we need to coach, and then adjusting the business where we need to adjust the business.
And you can’t really do that unless you have that entire foundation laid out and actually understand what all those levers are. So to me, taking the time to do that is really just beyond critical.
RR: Yeah. Yeah. You know what you need to do, and you can start driving really aggressively against it, which I– it sounds like you alluded to an example there with AI Role Play, you’re doing the work to do.
In that, you’re beginning to layer some of these new technologies, new tools on top of that foundation.
What were some of those first use cases that you prioritized, and why did you start where you did?
RW: I think the first win you always wanna go for is really a practical application of any new technology and how that can move the needle for the business.
So when I think of practical applications, I think of AI Role Play as being a very early one. As an enablement team and a training team, how many times have people walked through certification programs, the one-on-ones with managers, all the Role Plays, all the back and forth and the headaches and the objectivity that goes into those exercises.
That’s just a quick win that you can pick up and take care of almost all of that. The time saving alone and the cost of having a manager do these one-on-ones time and time again, it just drains an organization when every organization right now is trying to be lean, mean, focused on sales efficiency.
So anything we can do to give back and level the team up, I think is just a no-brainer. So AI Role Play is a huge one for us. We looked at a lot of different places. We tried a lot of different things, and we landed on the Highspot implementation of that because it’s important to be able to do that stuff, but also it has to be within the context of everything you’re doing and all the content and everything that you do have.
It can’t be this standalone siloed thing that happens in the background. We need to bring it to the forefront. Yeah, those are the really practical first-step wins that I’ve been excited about.
RR: Yeah, and that’s such a good example of mapping it back to those foundational levers. The path there is very clear, I think.
RW: Yeah, absolutely. Think of a competitive– your competitive intelligence programs. You do all this work understanding your competitors. Now you can understand when a seller of yours struggles with insert competitor X, Y, or Z. You can identify those trainings, you can recommend the trainings, you can verify they’ve been through them, and then if that’s not working, then you can escalate to coaching and go a little bit deeper from there.
So the foundation of the data will help you identify that stuff, and then you start applying the technologies. That’s how you go fix the gap. And then you can monitor it and just keep it going, almost near real time, which is incredible. A lot of the time, organizations are really spending most of their time hearing yesterday’s weather.
And when I mean that, I think of, you do a QBR, you go through a quarter, you spend 30 days doing the QBR. At the end of the QBR, you find the problems, you take 30 more days to figure out what the underlying problems are, then you spend 120 days fixing those problems. Then you’re six months removed from what the problem was, and now you got a whole new set of problems that you’re not even keeping up with the business.
So being able to identify these things, move quickly, and make recommendations really fast is incredible in the amount of time it buys back an organization to execute, and that you’re focused on the right things at the right time.
RR: I’d be curious to hear a little bit about, you mentioned a handful of teams there in some of the early AI Role Play rollout and piloting.
How did you start thinking about who you wanted to test this with, the kinds of pilots you wanted to build, and how has that going so far?
RW: We tested globally as a global organization. We tried US-based, EMEA, APJ folks. We took a look at various groups from various geographical regions because adoption’s an uptick, and accountability is different at the global scale.
The use cases really were tied around what’s our biggest blind spots, and what do we not know, and how do we validate that? As a group that has a BDR team, an SDR team as an example, if you have sellers that don’t wanna work with their BDRs ’cause they’re not confident that their BDRs are competent, then here’s a great way to say, “Hey, actually, we’ve already been them– we’ve taken them through the ringer. We’ve seen that they’re able to demonstrate this stuff, and honestly, we’re building scenarios that are harder for them to get through than you actually deal with, with customers.”
So we can stress test the teams, and then sellers don’t respond to customers with ABC answers. They have to be able to be versed in these conversations, so being able to do that was a huge unlock for us, because folks aren’t practicing with their paycheck.
Well, the worst place you wanna go figure this stuff out is in front of a customer, so give someone a very safe space to go practice and cut their teeth, and they will just accelerate if they get behind it and really try this stuff out. So yeah, find the high ROI cases, double down on those, share that experience, be vocal about it, and make sure others feel it. Then yeah, that’s how you just get that adoption and the needle moving.
RR: Something that I feel like is not as spoken about when it comes to training, Role Plays, et cetera, all of that stuff, is now you have this trust between your counterparts, and you have more of this connective tissue purely because of that, which is really interesting, and I’ve not, I don’t think, heard anyone speak to that element of it before.
So curious if you could give me a little bit more of a sense of what that has done for you guys.
RW: Yeah. And, as I mentioned, I’ve– I’m five-ish years into the security business, and this is just a business built on trust. So we have to gain the trust of our customers. It’s important in any sales cycle.
It’s a hundredfold more important when you’re talking about the security of your organization. So I think intrinsically our– the businesses are highly trust-driven with the folks that they work with, even internally. So, if you think through customer journeys, from trusting they’re landing the right messaging and marketing, to the right message that BDRs are delivering, our sellers deliver it, talking about the right things and delivering the proposals towards the outcomes that the customers are expecting, to how your account team then goes and manages that account or gets ready for renewals.
There has to be that thread of trust across those because each one sets one up for failure if not done correctly. And having a verified way of saying, “Hey, I can trust that my coworkers that are working upstream for me are doing the right things and they are competent,” that’s only gonna make you deliver and do better in your particular role, and it’s gonna want you to step your game up, too.
RR: Sometimes I feel like folks present a strategy the way it’s working out for them, and I have a thoughtful response to it. But in this case, the only thing I have to say is that’s so cool. It’s really, really cool to see all the different ways that this can show up for an organization beyond what we expect.
RW: If you were to turn the clock back two years, AI-based Role Play, that was beyond the bleeding edge.
There wasn’t even an edge. It was so far out of the realm. But these things come up quickly, and you wanna be able to jump on ’em and move on ’em. Again, it’s just moving so fast that you have to have that trust and have a team around you that’s willing to build on the successes you’ve had in a past life.
So it does take time to get to that point. It doesn’t happen overnight. It gets quicker, that’s the thing, ’cause now, if you think through how you go through a launch in a past life, go back two years: you spin up the marketing machine, they come up with the slides, you host a call, you do a webinar, you send the field out, say, “Go figure it out.”
If you’re lucky, you did Role Plays with the managers, you had a competency test, you sat down, maybe you brought some external resources in to actually manage this. And now with technology, you can scope it, build it, deploy it, have everybody through it in a few weeks, and you can actually verify that people can do these things, where in a past life, just none of that existed.
You can build trust faster and move quicker today because the technologies enable that stuff. It’s not the, I’ve got a six-month sales cycle, so I don’t know what my sales look like, or I don’t know how well things are going until six months down the line when you’re actually seeing the end-of-line conversions.
You just move so much faster right now. It’s, yeah, really exciting.
RR: Okay. So we’ve touched on, I think, a lot of some of the granular detail, and I think gotten a picture of what work at Yubico looks like right now. And I think it has been what sounds like a busy few months to get to this point.
So since making some of these changes, being really thoughtful about building out your foundation, starting to layer in those early AI use cases, what impact have you seen on things like seller efficiency, time savings, productivity, anything like that?
RW: We are cutting so much time out of the administrative burden of our team. It’s hard to put an exact number on it, but we’re looking at reducing sales cycles by upwards of 25% this year. Where if you think through a longer sales cycle on the security side, where things can take six, seven, eight months, if you can carve out a month back on those processes, it unlocks a lot of organizational capacity.
So we are heavy on how we are doing that this year, and sales efficiency is one of our big topics for this year. And ideally, in a perfect world, you have the right team that, as you give efficiency time back and give them time to focus on selling, they go out and sell more.
You can cut their day down to two hours a day, but what are they gonna do with the rest of the hours of those days to actually go get after it? So we’re cutting time out of their workload, making things easier on them, and then how are we surfacing the latest and greatest new opportunities and more guidance to them, to be a little bit more honed on where to go and focus on the stuff that technology’s not replacing right now, which is the human interaction and the conversations you have to have with your buyers.
So that’s our goal today, it’s just every single day, how do we chip away, chip away, chip away? And I think we’re doing a pretty, pretty solid job of that right now. And things that take hours, three, four, five hours to do, you can do in a button click these days. So on a 40-hour week, if that’s all you work, that would be nice.
But if you’re doing 40 hours a week and you’re cutting four or five hours out, 10%, 12% of your week is a huge give back on a timing perspective. So we are, yeah, really excited about all that work right now.
RR: You mentioned that 25% reduction, which you said, “That’s a solid, that’s solid progress.”
I would call that more than solid progress, but that’s just me. Would you say that part of that or some of that could be attributed to that improved ability to practice those conversations and show up better when you’re actually having them live?
RW: Absolutely. There’s the process side of house, which is where we can carve a lot of time out, but the competency within that process goes a long way.
Just the basics. Can you get somebody to set that follow-up call? Don’t let the customer off the call until you have a next step booked. Even just little things like that, that you get off the call and then it takes you a couple days to schedule that next meeting. You just get rid of coaching that stuff out.
Those basics that every seller always knows about, that adds up when you’re thinking enterprise-wide. That goes a long way. So again, foundational data, even just looking at the basics and doing really good at the basics and training people to that, you’re gonna find time back.
RR: To my earlier point about a lot of people are excited but don’t quite know what to do, that’s a very specific example of what can you coach to meaningfully?
How can you use Role Play to help you train away those bad behaviors that decrease your velocity, decrease your momentum, and in turn cause that chain reaction down the line?
So with all this work in mind, what do you think the future of go-to-market, of enablement, looks like at Yubico? What’s next?
RW: Ooh, that’s the multi-multi-multi-million dollar question. Someone who’s been around tech for a while, you see patterns in where things are going. I challenge everybody that I talk to about some form of initiative, or obviously a lot of AI discussions today. But if you challenge things from a first-principles perspective, why are you even doing these things?
And I think that is a question that organizations need to ask themselves, is why are you doing this, and why are you doing it this way? Does that even make sense in tomorrow’s world of where things are heading? It’s how are you driving decisions? How are you recommending actions? And how are you actually activating on the data and the information that you have?
I think that’s where go-to-market goes. It becomes less understanding and reading yesterday’s weather, as I say, and it takes that data and makes it actionable and pushes us forward versus just catches us up, which is also very, very exciting because the things that we thought were out of reach six months ago are in reach now.
RR: For people listening who might be, with that last sentence, feeling a little bit inspired but also uncertain, like, oh gosh, how do I keep pace? What would you say to leaders in tech and in other spaces who feel pressured to do AI, perform the thing, layer it into their programs where they can, but aren’t sure where to start?
What would you– What advice would you give them, having done it yourself?
RW: Start. That’s the key. It sounds silly, but everybody kinda has this not really sure where to start, and that’s okay. I think you just gotta start. First and foremost, you have to just dabble a little bit, get your feet wet, and it all starts to come clear.
If you’re thinking through the models that are out there, ask it questions, use it to teach you what you don’t know and where to go. But really it’s your thought partner in how you use these things. You have questions? Ask it questions. You get stuck? Ask it why you’re stuck. Ask it wh– it can do a lot of the things that I think would really surprise people, that will help them head down the right direction.
And again, we’re– I say it jokingly, we’re not protein folding. It’s not that crazy, the stuff that we’re doing. You’ll see that there’s a lot of people that have been successful, and you can go a long way just asking the right questions. Don’t be afraid. Do things in a smart way. Make sure your identities are locked down.
Shout out, Yubico. Make sure that you’re working with your security teams and doing the right things, and you’ve got access controls in place, of course. But just start. That’s the biggest thing I could tell people, is just start. You’d be amazed how far you can go.
RR: Very inspirational to close with. And also, I think a bitter truth sometimes. It’s very much the best way to learn is by doing.
RW: Yeah, 100%. I always get the, “Rich, what should I do?” I’m like, “Well, just ask the question.” Just literally just start. Just start. Just get in there and do it, and get going. And really the other thing I would say, on the starting point, is try and build a system where you give people the guardrails to be successful, get the benefits of AI, but also don’t get in the way and stifle innovation.
You wanna empower people to go figure things out. Give them the chance to start as well. If you’re a leader in one of these organizations, empower the folks on the front lines to do these things, because this technology is just peeling out those middle layers. The closer you sit to the customers, the more impactful work you’re gonna be able to do.
So get your frontline people working on this stuff.
RR: I have to say, I think I said it a couple times, but some really interesting, very actionable things, I think, you shared today. So I really appreciate you taking the time to give us some of those recommendations on how to get started with AI, what’s working for you with AI Role Play, all of the goodness on how to not be scared to get started.
RW: Thank you again for having me. This has been a lot of fun.
RR: Yeah. To our audience, thank you for listening to this episode of the Win/Win Podcast. Be sure to tune in next time for more insights on how you can maximize go-to-market success with Highspot.
