Peter Riggs | What If Restaurant Employees Were Paid to Think Like Owners? | ChatGTM S2 E47

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Video ID: ufEcPmK4EQ4
Language: en
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[0:01] Hey everybody, good afternoon, good
[0:02] morning, good evening, or whatever time
[0:04] you happen to be chiming into the Chad
[0:06] GTM podcast. I'm your host Michael Beck.
[0:08] Joined with me is my co-host. And you
[0:10] know what? Today I'm going to call you
[0:11] Chad, I'm going to call you my
[0:12] inspiration. You're a guy that I have
[0:15] levels of EQ I only aspire to have.
[0:18] These days when I I I mess with AI and I
[0:20] melt downs, I start going, "Well, what
[0:22] would Chad do?"
[0:23] >> Well, today isn't about the EQ, it's
[0:25] about the technical quotient because
[0:27] >> The TQ.
[0:29] >> I pointed to a button or a thing on on
[0:32] our platform today that we are putting
[0:34] in use right now.
[0:36] >> This is a concept called Kaizen.
[0:39] >> [laughter]
[0:39] >> Incremental improvements. And so for
[0:42] we're 40 episodes into the season and it
[0:44] took us What's that say phrase phrase
[0:47] they say you were this old when you
[0:48] found out?
[0:49] >> Mhm.
[0:50] >> Yeah, I I was 55 I was 55 years old when
[0:52] I found out we actually had a green
[0:53] room. We didn't have to make our our
[0:54] guests have to
[0:55] >> is new again.
[0:56] >> Yes. Yes, we we are refreshed and this
[0:59] is this is a brand new day. Um Chad, you
[1:02] I think you set this up. Who who's our
[1:03] guest today?
[1:05] >> Our guest is Pete Ricks. I won't go too
[1:06] long because you got a great reading
[1:09] coming.
[1:09] >> hope it's a great reading.
[1:11] >> Uh industry friend operator that has
[1:13] turned innovator.
[1:15] >> And so we're going to learn about these
[1:16] >> Turn You made it sound like it was a
[1:17] vampire that got bit.
[1:19] >> A little bit. Kind of what it's like.
[1:21] >> Okay.
[1:23] I'm an innovator.
[1:24] >> Some of his you know, operator buddies
[1:26] are probably going to treat him like a
[1:27] vampire now.
[1:28] >> He's probably wondering why he got that
[1:29] stake in
[1:29] >> with it.
[1:30] >> But it it'll happen.
[1:31] >> That's all right. That's all right. I I
[1:33] love where he came from. I think there
[1:34] there is a really good story to be told.
[1:35] And the fact that he's from my neck of
[1:37] the woods, which not many people are.
[1:39] I think you can count on one hand how
[1:40] many people live in the state Idaho.
[1:42] Well, that's not true, but it feels that
[1:43] way sometimes. Anyways, but um let's do
[1:45] our reading and get going. So today's
[1:47] guest is Mr. Peter Riggs. He's the
[1:49] founder of Wage Wave. This is a guy
[1:52] who's seen how restaurants are losing
[1:53] profitable sales every single night
[1:55] because employees have no incentive to
[1:57] sell during the last hour before
[1:59] closing. I'm sure we all know that
[2:01] moment. Hey kid, we No, we're shutting
[2:02] down. We're getting out of here.
[2:03] Anyways, here comes this problem with
[2:05] some serious restaurant credibility. And
[2:07] if you think about it, you know, if
[2:09] somebody's going to make a piece of
[2:10] software, they really have to have
[2:11] earned
[2:13] the authority to make something. And I
[2:14] think what what really gives Peter the
[2:16] chops here is he started as a Pita Pit
[2:18] franchisee and eventually helped take
[2:20] over the US business, grew the system to
[2:22] roughly 250 locations, and has served as
[2:24] president and CEO of Pita Pit USA. Along
[2:27] the way, he saw a problem that every
[2:29] restaurant operator recognizes, that
[2:31] last hour before closing when the crew
[2:33] wants to go home, customers are still
[2:35] coming in, and the revenue starts
[2:37] slipping away.
[2:38] I'm going to say hi to Chad GPT in a
[2:40] second, Chad. In a world of We're in a
[2:42] world where 45% of restaurants did not
[2:44] turn a profit last year, according to
[2:46] this Technomic report. I think Peter's
[2:49] the man of the hour because he built
[2:50] WageWave to change the incentive, giving
[2:53] operators a way to turn the measurable
[2:55] performance into real cash bonuses for
[2:57] their people.
[2:58] Peter, welcome to the Chat GPT Uncorked
[3:00] podcast, and I am now going to hurry to
[3:02] get him to the stage.
[3:08] Fanfare. That was awesome. We did it. We
[3:11] did it. You're here.
[3:13] >> And let let's be clear, is the company
[3:15] Wave Wage or Wage Wave? Cuz I I'm not
[3:17] positive.
[3:18] >> And I am dyslexic. WaveWage.
[3:21] >> WaveWage.
[3:22] >> How many times did I ruin it during that
[3:23] intro?
[3:24] >> I don't know. Just once right now.
[3:25] >> That's all right. This This is actually
[3:27] called marketing. We're We're imprinting
[3:29] on the actual name. You now know it is
[3:31] WaveWage. So, yeah.
[3:33] >> Yep, because you get that You get that
[3:35] wave of the wage bonus that comes
[3:38] crashing into your paycheck.
[3:41] >> Surfing the nar nar of wages. Love it.
[3:44] So, how are you today, Peter? Thank you
[3:46] for coming on during my more manic
[3:47] moment.
[3:49] >> [laughter]
[3:50] >> I'm good.
[3:51] >> Um
[3:53] And I I guess this is kind of get going
[3:54] here cuz I I think there's a lot to
[3:56] unpack especially in the short amount of
[3:57] time that we have, right? And and you
[4:00] know, I I I think every operator has
[4:01] thought about if I had a magic wand, if
[4:04] I could make some stuff,
[4:06] uh or or the even worse one, they see a
[4:08] piece of software coming out going, "I
[4:09] invented that month yeah 2 years ago. I
[4:11] just never got on it, right?"
[4:13] And so now we're looking at a guy that
[4:16] that, you know, went from a franchisee
[4:18] to becoming the leader of a brand now to
[4:21] becoming a software developer.
[4:24] How'd that work? How'd that even happen?
[4:26] Like something must have kept you up at
[4:27] night.
[4:28] >> Unintentionally is how it is how it
[4:30] happened. And and actually before even a
[4:33] franchisee, I was a customer because the
[4:35] second store in the US was in Moscow,
[4:38] Idaho when I was going to school there.
[4:41] >> Yep.
[4:41] >> And and so that's where I first became a
[4:44] a fan of it and then
[4:47] uh me and some other buddies that I knew
[4:48] from college, we started opening some
[4:50] restaurants and then that snowballed
[4:52] into
[4:53] us uh acquiring the US company in '05
[4:57] and we grew it from there and I think
[4:59] that's that's actually what led me to
[5:01] this because the reality is I think as
[5:03] an operator you you can only be an
[5:06] operator so long before you have to
[5:08] either become an innovator or you just
[5:12] give up and die as a shriveled husk of a
[5:15] human
[5:16] cuz the restaurant industry takes its
[5:18] toll on you for sure and you sit there
[5:20] and you go, "Why am I doing this?" And
[5:23] the majority of people either burn out
[5:25] or they go, "I got to find a better way
[5:26] to do this."
[5:28] >> Yeah, that that's funny.
[5:30] That is a that that that's very true
[5:31] statement. For some reason Highlander
[5:33] came in my head, "It's better to burn
[5:34] out than to fade away." But I don't
[5:35] think we want to do either.
[5:37] Are you still with Pita Pit as a brand
[5:39] or have you moved on? This is your own
[5:40] own just endeavor you're doing with
[5:43] absent that?
[5:44] >> A little little bit of both. So so
[5:47] recently we've made some changes there
[5:49] trying to to get Pita Pit back to the
[5:51] place where uh where it can be.
[5:53] Obviously, you know, COVID was a
[5:55] struggle for everyone. We happened to
[5:57] have some other stuff going on at that
[6:00] time that compounded and made a bad
[6:02] situation worse and we've spent the last
[6:05] few years trying to help that kind of
[6:08] beloved legacy brand kind of live up to
[6:11] its former glory and continue on kind of
[6:14] in its new iteration. And so, I actually
[6:17] recently stepped down as uh CEO,
[6:20] promoted uh John Sooker who's got good
[6:23] culinary chops and he's in there making
[6:27] a lot of important operational changes
[6:29] and I'm focusing now on Wave Wage
[6:32] uh because it's something that I ideated
[6:34] originally for the Pita Pit employees
[6:37] and franchisees and our needs there.
[6:39] But, like I said, I've been in this
[6:41] industry a long time and I've got a lot
[6:43] of friends who I was like, "Man, these
[6:44] guys need this, too." And so, it quickly
[6:47] started to to become bigger than just
[6:49] what I needed for Pita Pit. And so, I've
[6:51] tapped some of those guys for
[6:53] diagnostics and analysis and and they're
[6:56] going to be doing some pilot testing as
[6:58] well
[6:59] uh because this is an operator system
[7:02] built for operators to kind of cut
[7:04] through a lot of the other garbage that
[7:06] we are dealing with cuz we all know that
[7:08] we need more technology to help us run
[7:10] our businesses better. But, for those of
[7:13] us that are pure operators, there's a
[7:15] lot of times we don't we don't
[7:16] understand
[7:17] what it does or why we need it. We know
[7:19] we kind of probably do, but we also lack
[7:23] the fundamental ability to understand it
[7:24] well enough to make sure that it's truly
[7:26] integrated into our operations. So, we
[7:28] really need to kind of take a step back
[7:30] and look at things and say,
[7:32] "How do we fix this as an operator first
[7:34] and then apply technology to it to do
[7:37] that in a more effective way?"
[7:40] >> Right.
[7:41] Chad?
[7:42] Before we get into the tech and you
[7:44] know, the origin of Wave Wage, I wanted
[7:46] to ask you this, which is
[7:49] what is for people who haven't ever
[7:51] employed people or haven't been a
[7:52] restaurant operator, what are some
[7:54] fundamental truths about employee
[7:57] engagement that they need to know?
[8:00] >> That's a that's a great question. Um and
[8:02] the the biggest thing about employee
[8:04] engagement just comes down to the
[8:06] fundamental aspects of human nature.
[8:09] Especially at that age where you're kind
[8:11] of an hourly employee at a restaurant,
[8:13] places like that, you've got dreams.
[8:15] You've got big dreams and hopefully
[8:18] those come true for you. But uh a lot of
[8:20] times they don't, but you don't know
[8:22] that then. You're still 18, 22, 30 and
[8:27] you've still got a lot of time to make a
[8:29] lot of moves and so
[8:32] that these people are the main character
[8:34] in their story. Your restaurant is not.
[8:37] Your business is not. And so if that if
[8:41] if an opportunity comes along for them
[8:43] to have a chance to to you know, seize
[8:46] that greatness opportunity, then they
[8:49] might just not show up. And they don't
[8:52] realize kind of what kind of an impact
[8:54] that has on you, the other staff and
[8:56] kind of the flow of everything there.
[8:58] And it's kind of hard to blame them
[9:00] because
[9:01] that's what they're living with. That's
[9:03] their life and that's what they're
[9:04] dealing with and let's be honest, most
[9:07] people don't hire workers in restaurants
[9:11] like ours as a career. They know that
[9:13] they're going somewhere else. Maybe some
[9:15] of them are going to love it, stick on
[9:17] through management, maybe become their
[9:19] own restaurant owner. But that's all
[9:21] kind of a long tail process and isn't
[9:24] necessarily what most of the hourly
[9:26] workers do. So it's a different
[9:28] landscape and that's what causes us to
[9:30] have a 90 to 110% turnover rate because
[9:35] people are moving on for that chance at
[9:38] greatness and that's okay, but we need
[9:40] to make sure that as operators who are
[9:41] going to be around for the long haul,
[9:43] that we've got systems in place to help
[9:46] reward and recognize the people that are
[9:48] there to help run our businesses better
[9:50] and give a better overall customer
[9:51] experience.
[9:53] >> So Peter, before we go too much further
[9:55] into the subject, let's let's spend a
[9:57] minute defining
[9:58] the thing that what wage what wave wage
[10:00] is. Let's define what it does,
[10:03] where it lives in the store, kind of
[10:05] what that experience is like, and then
[10:07] we can go a little further cuz I want
[10:08] the the audience to go, "Oh, this is
[10:10] what we're talking about." and start
[10:11] cementing that. So what what is what is
[10:13] wave wage if you define it?
[10:16] >> In in essence, it's performance pay for
[10:18] hourly workers based on the sales that
[10:21] they bring in during a specified period.
[10:24] >> Okay.
[10:24] >> And so in essence, it it allows us to
[10:28] use technology to track and reward
[10:31] certain scenarios that will
[10:34] give employees the motivation and desire
[10:37] to kind of think and act like an owner
[10:39] because they have a stake in the sales
[10:41] that are actually walking through or
[10:43] walking out of the door uh while they're
[10:46] on shift. It makes them an active
[10:48] participant in the business.
[10:51] >> Awesome. Was there
[10:53] an exact moment that that in your
[10:55] restaurants that you something you saw
[10:56] that brought this to life or was it more
[10:59] just a pattern over time?
[11:01] >> Well, coincidentally, it wasn't in my
[11:03] restaurant that I saw it, but I knew
[11:05] that it but I knew that it occurred in
[11:06] my restaurants as well. In fact, this
[11:08] was back um in uh in 2023 when I had uh
[11:13] just kind of taken Pita Pit back um and
[11:16] I was doing a big road show. I got a van
[11:19] and I was driving around to visit every
[11:21] single location that we had to kind of
[11:23] help explain kind of what transition was
[11:25] about to take place, the efforts we were
[11:27] going to put in place to try to help
[11:28] them get things back on track, and I was
[11:32] I had just finished visiting with one
[11:34] franchisee and I was getting ready to
[11:35] hit the road and head out, and I wanted
[11:37] to grab some some dinner before I left.
[11:40] And so, I just placed a to-go order at a
[11:42] sushi place, and I was waiting in the
[11:44] the front lobby area to to for them to
[11:47] finish the order. And it was about 45
[11:49] minutes to close when I placed the
[11:51] order. So, I felt no problem cuz I was
[11:52] just grab and go. But about 30 minutes
[11:55] to close, this younger couple walk in
[11:57] cuz it was a college town, and
[11:59] they asked if they could get a table for
[12:00] two, and the hostess just kind of
[12:02] sighed, picked up two menus and said,
[12:04] "Yeah, but we close in like 30 minutes,
[12:07] so you're going to have to be fast with
[12:08] the menu."
[12:09] >> Yeah.
[12:10] >> And the guy was like, "Oh, um I didn't
[12:12] I'm sorry. We didn't realize that you
[12:14] close so soon. We don't want to I don't
[12:15] want to be a burden. We can We can eat
[12:17] somewhere else if you want." And she
[12:18] goes, "That'd be great. Thanks." And
[12:20] sets the menu down.
[12:22] And I'm sitting there just my jaw's on
[12:25] the floor going, "I can't believe I just
[12:27] witnessed that in real life." It's like
[12:29] you hear about these stories happening.
[12:31] Yeah. You hear about those stories, but
[12:33] you don't like you're not sitting there
[12:34] front row center for it to actually play
[12:36] out in front of you.
[12:37] >> Yeah.
[12:38] >> And it just it just sat there and it
[12:39] chewed at my brain the whole next
[12:41] several hours as I was driving down the
[12:43] road, and I was just thinking,
[12:44] "If that was my location, I mean,
[12:46] besides the fact that I'd be furious, if
[12:48] that was my location, what would I do to
[12:51] get them to not do that?"
[12:53] I'd tell them that they could have some
[12:55] of the money. They can have all the
[12:56] money from the last hour of sales if
[12:59] they just treat people well and invite
[13:02] them in and be hospitable and and kind
[13:05] of really help us and call it brand
[13:07] insurance. Uh cuz the reality is it's
[13:10] like she's sitting there and she sees
[13:11] these people come in, and it's like she
[13:13] might get some share of the tip that's
[13:16] going to split between how many people,
[13:17] but it's just not worth the effort. It's
[13:20] really not worth it for any of them. But
[13:22] if all of a sudden you say, "Man,
[13:24] I know I'm going to get the all of the
[13:26] the food revenue, the incremental
[13:28] revenue that comes in from this order
[13:30] because it's coming in in the last hour.
[13:33] Not only am I going to be pleasant and
[13:34] hospitable, I'm going to suggest some
[13:36] extra rolls, a starter, and make sure
[13:39] that they have
[13:40] tried our legendary dessert. Because
[13:43] even though it's a bit more work,
[13:45] what they can do from tacking on those
[13:48] sales becomes a genuine benefit to them
[13:51] financially, and all of a sudden they've
[13:53] got motivation to really sell like an
[13:55] owner. And you, as the operator of the
[13:58] restaurant, you're giving more of that
[13:59] revenue away, but it was totally lost at
[14:03] this point. And it's also one of those
[14:05] things where the revenue that is
[14:06] generated there is also going to go
[14:09] They're They're going to say, "Man, we
[14:10] walked in, we were a little bit nervous
[14:12] cuz it was kind of close to close We had
[14:13] the most amazing experience. They were
[14:15] so nice. I would go there 10 times out
[14:18] of 10." As opposed to, "I'm never going
[14:20] back there again, and I blame brand
[14:23] whatever because they don't know They
[14:25] don't know who Jessica is at the hostess
[14:28] station that's the one that actually
[14:29] turned them away. They just remember
[14:31] that your brand turned me away.
[14:34] >> Yeah, I think anybody that's worked in
[14:37] in hospitality as a server or front or
[14:39] back of house as well,
[14:41] there's that existential dread that you
[14:43] know, 10 minutes before closing, and
[14:45] there comes the the the party of five
[14:47] that comes walking in the door.
[14:49] Um
[14:50] the thing that occurs to me I love to
[14:51] pressure test your thinking on this is
[14:53] so the the front of house they're all
[14:55] about it. You know what? Let's see Let's
[14:56] see Let's see them. We're going to get
[14:58] our bonus out of that. Back of house
[15:00] might be a different reality cuz they're
[15:01] they're shutting down grills, they're
[15:03] going in sanitize sanitizing processes
[15:05] and stuff like that.
[15:07] Tell me about how that interplay works
[15:08] and how you look at that.
[15:11] >> The same way. It's It's divided across
[15:13] the shift.
[15:14] It's basically goes across whoever is
[15:17] has worked that shift. And that's where
[15:20] That's where things got interesting and
[15:21] I started to build something more than
[15:23] just a one shift tool and started
[15:25] building something that was an actual
[15:27] business because as I started to ask
[15:29] those same questions, it became
[15:31] important to cover all the other
[15:34] scenarios where things like this happen.
[15:36] It's not just this last hour. It's
[15:38] >> Right.
[15:39] >> It's when it's when a a busload of
[15:41] volleyball players shows up and all of a
[15:43] sudden your forecast hour is going to be
[15:47] double or triple what it was before. You
[15:49] can't call in more people cuz it's going
[15:51] to be over by by the time somebody gets
[15:52] there. But what happens is a coach walks
[15:56] in and says, "Hey, can I Can my team eat
[15:58] here?" And you go, "Yeah, no problem."
[15:59] And he goes, "Just take the orders. I'll
[16:01] pay at the end." And they just start
[16:04] placing orders, but you just want to get
[16:05] them through the line.
[16:06] >> Mhm.
[16:07] >> But if you had surge hours set up where
[16:09] you could share in the benefit, now
[16:11] there's other rules in addition that can
[16:13] be
[16:14] beneficial to all the employees. And
[16:16] then that just keeps kind of going with
[16:18] a bunch of rules that we can set so that
[16:20] really there are ways to take every
[16:22] aspect of what we do inside an operation
[16:25] and we can have custom rules for
[16:28] different departments as well as bundle
[16:30] them together with capped rules for the
[16:31] whole thing. And it's all set knowing
[16:34] that we got to make our we got to make
[16:36] this much at the end of the day. So if
[16:37] we don't get here in sales,
[16:39] >> Right.
[16:40] >> none of none of these rules fire. So
[16:42] it's like they're all they're all you're
[16:44] earning them. It's like think of it like
[16:45] owning uh hit hit bonuses in a video
[16:48] game. But then you get hit, you lose
[16:50] that combo. And it's a little bit the
[16:52] same way here where you got to keep
[16:53] pushing all day because it's not enough
[16:55] to have a good hour or a good moment. If
[16:58] we don't get above profitability, none
[17:00] of us are going to actually recognize
[17:02] these bonuses.
[17:03] >> Mhm. Is it pulling things like CSAT,
[17:06] too? Like if you want if you're saying
[17:07] like we're looking at this at a
[17:08] different dimension of time and say over
[17:10] the month we see these these these
[17:11] spikes that occur past the past the the
[17:14] standard business hours and there's a
[17:16] correlation of CSAT against the
[17:17] transaction record in the POS saying,
[17:19] "Hey, after 5:00, we are getting these
[17:21] scores and it's
[17:23] directly correlated with these these
[17:25] types of transactions."
[17:27] >> Yes, and in fact, we go kind of a step
[17:29] further than that. We're We're We're
[17:31] trying to take
[17:32] We don't want to make opinions on the
[17:34] data we gather yet. We just want to
[17:36] gather data. So, what we're doing is
[17:38] we're looking for all of those points of
[17:40] data, but we're also looking for the
[17:42] dark spots, the parts that aren't being
[17:44] measured. Um and so, if you start to
[17:46] find big gaps in areas that aren't being
[17:49] measured, late night, uh last hour
[17:52] stuff, like if you look for last hour
[17:53] studies and things like that, they just
[17:55] simply don't exist. Nobody's really
[17:57] measuring that stuff. So, as we look at
[17:59] these businesses and their actual
[18:01] transactions, we're not looking for just
[18:03] what occurred, but also we're feeding
[18:05] that in to an expectation that then
[18:08] tells us whether or not there are gaps.
[18:10] And so, that's part of our gap analysis
[18:12] system that says,
[18:14] "Based on the other trans Based on your
[18:16] attach rate for sodas and this and other
[18:18] things, you you're soft between 5:00 and
[18:20] 7:00 p.m. on Tuesdays and Thursdays. You
[18:23] might want to look into that because
[18:25] it's going to recognize kind of not just
[18:27] potential in the the data, but also
[18:29] where there's gaps that need to be
[18:30] explored. And then you can start to find
[18:32] things like, "Oh, well, Tony always
[18:34] works those shifts." So, what what
[18:35] what's Tony doing? Why is he not, you
[18:37] know, selling like he's supposed to?"
[18:39] And you can start to figure out not only
[18:41] where you can do more to encourage
[18:43] employees, but you also might find some
[18:45] bright spots where you've got a really
[18:47] good rockstar employee that you didn't
[18:48] realize was there.
[18:49] >> that.
[18:50] >> Exactly. And what are they doing and how
[18:52] do we turn that into a better part of
[18:54] the system?
[18:55] >> Mhm.
[18:56] >> Tim?
[18:57] >> Hey, why do you think nobody has built
[19:00] Wave Wage before? I mean, something that
[19:03] always goes through our heads when we're
[19:04] finding something unique like that.
[19:07] >> It's very complicated. It's It's very
[19:10] complicated to do it in
[19:13] a layered way that can start to
[19:15] understand and look for the
[19:17] deficiencies, figure out how to correct
[19:20] them, account for
[19:24] specific data at that individual
[19:26] location, and then adjust to be
[19:30] functional for those employees. Cuz even
[19:33] the same brand in a Pita Pit in downtown
[19:37] Coeur d'Alene is going to be very
[19:38] tourist-centric, and a Pita Pit in
[19:41] Syracuse, New York is going to be at the
[19:43] college, and you know,
[19:45] a totally different clientele, different
[19:47] time, all those types of things. And so,
[19:50] it has to be semi-universal, but that
[19:53] last 20% has to be adjustable to the
[19:55] individual locations, the individual
[19:57] needs, and things like that. And so,
[20:00] that the level of complexity of kind of
[20:02] weaving that together on the back end is
[20:05] not simple. And it took me having to go
[20:09] at it from the the other side of it.
[20:11] Say, try to think up every single
[20:13] problem I've had as an operator,
[20:16] whether it's employees, whether it's
[20:18] food, whether it's uh order accuracy,
[20:20] whether it's difficult customers, all
[20:22] that, and figure out how to build
[20:25] a kind of a very complicated if-then
[20:28] scenario that that that triggers these
[20:31] different levers to decide what should
[20:33] happen when and how much, all kind of
[20:36] controlled and signed off on by the
[20:38] client, but basically we've built this
[20:41] kind of we've we've we've embedded it
[20:44] with all of our learnings from
[20:47] challenges across years from myself, and
[20:50] like I said, some of my other friends,
[20:52] and said, "What are some scenarios that
[20:54] we can continue to throw at this thing
[20:56] to try to make it think like an
[20:58] operator?" And that just takes a lot of
[21:01] time and a level of
[21:03] kind of interconnected thinking that I
[21:05] think a lot of operators just aren't
[21:09] they're not tuned up for.
[21:11] >> This episode of the Chat GTM podcast is
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[21:29] LinkedIn. [music] And now, it's time for
[21:31] the show.
[21:35] >> Peter, without knowing much about your
[21:36] your solution, it occurs to me a little
[21:39] bit that, you know, in gamification and
[21:41] incentives,
[21:42] out of sight, out of mind is kind of a
[21:44] thing that if it's not in front of you
[21:46] and present, it's hard to be excited
[21:48] about your score, so to speak. If you
[21:49] think of sports, the big scoreboard
[21:50] that's running. How are the employees
[21:53] engaging with any with it, seeing it,
[21:55] that that that accumulation of points or
[21:58] what they're moving toward their goal?
[21:59] And how does that how how does how do
[22:00] you motivate them knowing it's there by
[22:02] keeping it present or top of mind?
[22:04] >> Yeah, that's a great question. We we
[22:06] wanted to make sure that cuz yeah, we
[22:08] agree. The the buy-in is kind of where
[22:10] it's at with the employees.
[22:12] And so, we designed a very shareable
[22:16] kind of application interface where they
[22:19] can basically see what rules are active,
[22:22] how close they are to those, what's
[22:23] triggered already, where their sales are
[22:26] at, and what they've potentially banked
[22:28] in wave bonuses already. And so, it
[22:31] shows them kind of where they're at for
[22:33] each of these categories that's live. It
[22:35] shows them, man, we are we're almost to
[22:37] this uh to this next goal. Let's push a
[22:40] little bit harder and we'll get to this
[22:41] place.
[22:42] Um and it so, it gives them the ability
[22:44] to kind of see where they're at, but
[22:46] then also, we want them to take
[22:48] screenshots of it and share it with
[22:50] their friends and say, "Look what I did.
[22:51] Look at the Look at the wave bonus I got
[22:53] working here and things like that." And
[22:55] that's where we also decided it was
[22:57] important to have non-financial metrics
[23:00] that are in there as well cuz there are
[23:01] a lot of things that you can't reward
[23:03] financially the same way you would like
[23:05] a surge hour or the closing hour.
[23:07] >> Sure.
[23:08] >> Like uh like order accuracy and and and
[23:11] showing up for all your shifts on time
[23:13] and things like that. So, we've put in
[23:16] some some tools to to do endorsements
[23:18] and badging. Uh so that they can
[23:21] so that they can earn things like
[23:23] being great at accuracy, being super
[23:26] great at at They they get mentioned all
[23:28] the time by name in in um reviews and
[23:33] things like that, positive reviews. And
[23:35] so as those things accumulate and are
[23:37] tracked in the back end, they eventually
[23:38] trigger uh these badges and
[23:41] endorsements. And they're they're kind
[23:42] of surprise and delight ones. You don't
[23:44] know You don't see like I got positive
[23:46] reviews here. I'm three points away.
[23:48] Because what we don't what we don't want
[23:49] to do is we don't want to negatively
[23:51] incentivize them either. So,
[23:53] >> Right.
[23:54] >> get
[23:54] >> Gaming the system, right?
[23:55] >> Yeah. If you get named poorly in a
[23:57] review, that also counts against you,
[24:00] but you don't see that. And you don't
[24:02] ever earn a like this guy's a terrible
[24:04] employee badge. But it just kind of like
[24:06] it's tracking these commendations
[24:09] and it builds a real
[24:12] kind of like a a resume for these
[24:14] employees. And every employee that signs
[24:16] up, when they sign up they're get
[24:18] they're given a unique employee
[24:19] identifier. And so they can take their
[24:21] profile with them to another place that
[24:24] also uses Wave Wage. And they could say,
[24:26] "Here's why I'm worth a dollar an hour
[24:28] more than what you're saying you started
[24:30] at. And I've got the endorsements and
[24:33] the background right here to show you
[24:34] that I'm not just blowing smoke."
[24:37] >> From the way you're talking and and
[24:38] looking at your hand, this sounds like
[24:40] there's there's a it's a phone app that
[24:41] runs. Is there a way that you could pipe
[24:43] this to like say maybe a repurpose KDS
[24:45] screen or a screen in the inside the
[24:47] restaurant where people could monitor
[24:49] and police each other saying, "Hey,
[24:50] we're really close to our number, guys.
[24:52] Let's keep pushing."
[24:53] >> Yeah. We've built for for those that
[24:55] want it, we've built the ability to do
[24:57] kind of a back-end KDS that can show
[24:59] those things on a kind of a live display
[25:01] in the back of house
[25:03] and show kind of where they're at. And
[25:05] that'll show kind of the the more
[25:07] detailed dashboard including the the
[25:09] forecast and the trend analysis and
[25:11] where they're at in comparison and all
[25:12] that in even more detail of the holistic
[25:15] store picture as opposed to their
[25:17] individual shift picture.
[25:19] >> Very cool. Almost just like something
[25:20] you could publish to people's social
[25:21] media if they really cared about their
[25:23] job and saying they just they got their
[25:25] I'm picturing a
[25:27] wave wage or a Peter Pan Eagle Scout
[25:29] festooned with badges and right. Yeah.
[25:32] Chad, sorry about that.
[25:34] >> So, I'm glad you brought up the
[25:36] idea of unattended consequences cuz I
[25:39] remember when I first heard about that
[25:40] it's one of the things I asked you about
[25:42] and you you talked about how you have
[25:45] this rule system and a confidence
[25:47] system. So, my question is
[25:50] you know, you're going to tell me as an
[25:52] operator what I should do, right? You
[25:55] know,
[25:56] what I should try to
[25:58] grow revenue. But if that's the if
[26:00] that's the case, how should as an
[26:01] operator should I think about running
[26:02] experiments on something I think will
[26:05] work well?
[26:06] >> We we set up so part of our system too
[26:09] is we've got a an AI rule generator. So,
[26:12] basically it takes we've got our core
[26:14] bread and butter rules, things like the
[26:16] closing hour, the surge hour,
[26:19] the upsell rules, things like that where
[26:21] we say, "Look, if you just want to set
[26:23] it and forget it, we've got these ones
[26:24] they're going to cover almost
[26:25] everything. You just fine-tune it for
[26:27] your numbers and you're good to go." But
[26:29] there's some people that want to do a
[26:31] much more personalized
[26:34] set of rules. And sometimes those guys
[26:36] know what they're talking about and
[26:37] sometimes people go, "I've got this
[26:38] great idea."
[26:40] And everyone around them is like, "I
[26:41] don't know if it's as good as you think
[26:43] it is."
[26:44] Um and that's where our rule system will
[26:47] take rules and compare it against things
[26:50] that exist in the system and also rules
[26:52] that are in fact affect through other
[26:54] clients, and it'll give it a basically a
[26:56] confidence score. It'll say, "Look, you
[26:59] we see where you're going with this, but
[27:01] you're the numbers seem off to us, and
[27:04] we've never seen a rule like this
[27:06] before, so we're going to we're going to
[27:07] rate this with kind of a lower
[27:09] confidence score. You're free to use it.
[27:11] You're always you know, the the client's
[27:12] always free to
[27:14] set the rules that they want, but we
[27:17] don't see this working great. It's got a
[27:19] low confidence score. It's got a
[27:20] confidence score of 58%.
[27:23] >> Mhm.
[27:23] >> Whereas these other rules, this rule has
[27:26] been implemented by X number of
[27:29] locations. It's been deployed Y number
[27:31] of times, and it has a success rate of
[27:34] whatever, and so we have the a
[27:36] confidence score on this one of 98%.
[27:39] It's similar to kind of just ranking
[27:41] things um
[27:43] that we buy, you know, through Amazon,
[27:45] apps that we download, anything. It's
[27:47] like the more popular ones, they rise to
[27:50] the top, and
[27:52] it's important that
[27:54] other operators that hadn't necessarily
[27:56] thought of it a different way can look
[27:59] at other rules that other operators are
[28:00] putting in That actually That's what I'm
[28:02] looking for right there. And so we
[28:04] basically build a library, and are
[28:06] constantly checking the library against
[28:08] itself to develop that confidence score
[28:11] to show what rules are being used, how
[28:13] often, and what the likely success rate
[28:15] is, and compared to your numbers, we
[28:18] either predict high or low success from
[28:20] that.
[28:21] >> Mhm.
[28:22] Um and this might be answered in the
[28:24] rules side of things that you were just
[28:26] talking about, and Chad kind of you
[28:28] simulated this when you're saying
[28:29] unintended consequences. So let's let's
[28:31] have a scenario here. It's 5:00,
[28:34] and some some restaurant this restaurant
[28:35] decides it's it's hours, or it closes at
[28:37] 5:00. And the team rallies and says, "We
[28:40] got some people coming in. Let's just
[28:42] keep going. We go to 7:00." Or is that
[28:45] within the rules that the team can be
[28:46] dynamic and dictate how much longer they
[28:48] want to go or will the rules say hey
[28:50] this is our hard close we can't stay
[28:52] open cuz the unintended consequence side
[28:54] of things makes me go well they're open
[28:55] at 7:00 today how come they're not at
[28:57] 5:00 and now I'm ticked off.
[28:59] >> Yes, excellent question and the reality
[29:01] is that's up to the ops team. We we we
[29:04] make what you want to do possible. We
[29:08] don't we don't facilitate anything
[29:10] beyond that. So if your staff has the
[29:13] flexibility
[29:14] to do that
[29:16] >> Yeah.
[29:16] >> the system can support it but it doesn't
[29:19] it doesn't give them the opportunity to
[29:21] supersede their own rules and operations
[29:26] and so since those things are set by
[29:28] the the top levels they can try but and
[29:32] they could blame us for facilitating
[29:34] that.
[29:35] >> Right.
[29:35] >> I would say if they've got enough
[29:37] business to keep going for 2 more hours
[29:39] you might want Here's part of your gap
[29:40] analysis. We're going to say you should
[29:42] stay open longer.
[29:43] >> Yeah we have some hourly flexibility we
[29:45] need to look at or I'm Chad I'm thinking
[29:47] about our friends over at Snooze right
[29:48] and they just realized
[29:49] we don't have a dinner day part what's
[29:51] going on right?
[29:52] >> Yeah.
[29:53] >> Interesting. Chad
[29:55] >> So I want to ask you about pilots
[29:58] meaning
[30:00] what does it take to validate that this
[30:02] is working in a location or locations
[30:04] right because you want to attribute any
[30:07] sales lift to that employee behavior
[30:09] change and not
[30:11] weather change favorably or negatively
[30:14] or there's road work. How do you think
[30:16] about that?
[30:18] >> Very carefully and that's that's part of
[30:20] why when like as I was saying earlier we
[30:23] try not to be prejudiced about any of
[30:25] the data. We want to gather all the data
[30:28] that comes in first and then compare it
[30:30] against what we think it should be and
[30:32] then also especially with the pilots we
[30:34] work that against with our operator
[30:36] friends and say is this what you were
[30:38] expecting and why and did it show what
[30:41] we thought or not and figure out how to
[30:44] go from there because that's the
[30:47] that is the beauty and the complexity of
[30:50] what we're building here is the system
[30:53] is fine. The math works. The concept is
[30:56] fine.
[30:57] In the pilots, it's what does it
[31:00] actually do or not do to drive changes
[31:04] in employee behavior, in employee
[31:06] morale, in customer experience, in order
[31:09] volume, ticket size, all of that stuff.
[31:12] And those are are the actual results
[31:16] that are not only going to vary from
[31:17] location to location, but they're going
[31:18] to take some time to continue to figure
[31:21] out what the the the normal is for each
[31:24] brand and segment. And that's where
[31:27] working with folks that understand that
[31:30] they've got to have good good
[31:32] management, good ops in place to make
[31:35] best use of the tool itself. Uh cuz it's
[31:39] not a fix for poorly trained people or
[31:42] or staff that is running loose or giving
[31:44] away food or things like that. This
[31:46] isn't a let's use it to beg them to act
[31:49] right. They act right and get rewarded
[31:52] because of it. And that's where it's
[31:54] important to have people in the pilots
[31:56] that understand what these problems are,
[32:00] understand the solution set that's in
[32:03] front of them and then say, "As an
[32:04] operator, I now know how to I can take
[32:07] it and help execute this within my own
[32:10] operations, training, and employee
[32:12] expectations to to close that loop and
[32:15] change the actual human behavior that
[32:19] we're talking about in the first place."
[32:22] >> Um
[32:24] Peter, so part of this is you know, the
[32:26] badges obviously that that's that's
[32:28] that's more intrinsic than financial,
[32:30] right? But when we're talking about
[32:32] putting more money into an employee's
[32:34] paycheck,
[32:35] CFO zeros are going to immediately
[32:37] probably perk up and and and ask the the
[32:39] question like you know, if I'm paying my
[32:40] employees more money,
[32:42] how do you make sure the restaurant is
[32:43] actually making more money?
[32:45] >> Yeah. That's a fantastic question and
[32:47] that's that's the beauty of it. If you
[32:49] do this correctly, there's the
[32:51] opportunity for the restaurant to make
[32:54] more money, the employees to make more
[32:56] money, and the customer experience goes
[32:58] up because
[32:59] >> Right.
[32:59] >> what happens is
[33:01] like let's let's just use we'll go back
[33:03] to the the we'll I'll do upsell in the
[33:06] the last hour real quick. Yeah. The last
[33:08] hour
[33:09] it's people think well, jeez, if it's
[33:11] slow, you should just have them close
[33:13] early. It's like no, no, no, that's
[33:14] that's that's opposite thinking. It's
[33:16] actually the potential to be the most
[33:19] profitable hour of the day for you
[33:20] because you've already paid for the
[33:22] rent, the power, the employees, all of
[33:25] that stuff. All we're talking about is
[33:27] incremental food cost that you just
[33:29] covered in the transaction itself.
[33:31] >> Right.
[33:32] >> So of that of that margin for the
[33:35] excluding the food and paper cost of
[33:37] that I mean and you can go deeper than
[33:39] that, but let's say you want to still
[33:41] make money there.
[33:42] We're going to give that plus a small
[33:44] chunk to
[33:45] just to make sure that we're covered and
[33:46] then the rest gets split by the crew.
[33:49] You are you are spending more in labor
[33:52] dollars
[33:53] because you're giving them more money,
[33:55] but your actual labor percentage can go
[33:58] down because your revenue has increased
[34:01] by such that compared to the staff that
[34:03] was already on, you might be at a 26.2%
[34:07] labor cost, but by doing this now you're
[34:09] at a 24.8
[34:10] even though you spent more actual money
[34:13] because the the change to the revenue
[34:16] offsets that amount and drives the
[34:18] percentage the labor percentage lower.
[34:21] And so that's where when when from an
[34:24] ops and a CFO side, you can see look
[34:27] if we do a upsell
[34:28] >> spend. It would be categorized marketing
[34:30] spend if that's the case, right?
[34:31] >> If we can get our upsells on drinks from
[34:34] 40% to 65% to 80%, then
[34:40] let's share half of that
[34:43] with the employees. That's a genuine I
[34:45] mean, they're sitting there going, "Man,
[34:47] I could make I could make 25 cents out
[34:50] of every single one of these upsells I
[34:52] do."
[34:53] That starts to add up in their head.
[34:55] Meanwhile, you're actually making more
[34:57] money because they're actually driving
[34:59] new sales, new incremental sales that
[35:02] you weren't getting before. And so while
[35:04] you're technically putting out more in
[35:06] labor dollars, you're actually making
[35:08] more money and lowering your cost and or
[35:11] lowering your percentage. And the the
[35:13] customers are going, "Man, this place is
[35:15] great."
[35:15] >> Yeah.
[35:16] >> They treat me awesome here.
[35:18] >> Love it. Chad,
[35:21] what uh
[35:23] what should operators expect Wave Wage
[35:25] to integrate?
[35:27] >> Say that again, I'm sorry.
[35:29] >> What should what other platforms or
[35:30] pieces of their technology should
[35:32] operators expect Wave Wage to integrate
[35:34] to?
[35:35] >> Well, our goal is to try to be a good
[35:38] middleman across all of their systems.
[35:40] So basically, we sit between their POS
[35:43] system and the payroll system and just
[35:46] kind of recalculate the math based on
[35:48] the the settings and the caps that the
[35:50] clients put in place.
[35:52] And then those numbers are what gets
[35:54] sent to payroll with this kind of bonus
[35:57] line item down there. And it's all taxed
[35:59] the same as wages in the US, so it's a
[36:01] simple mathematical equation, but you
[36:03] can see the bonus line item there on the
[36:05] paycheck. And then uh from there, it
[36:09] allows us to start to integrate with
[36:13] other systems, other um HR systems,
[36:16] labor systems, and including uh we're
[36:18] working on some badging and endorsement
[36:21] stuff for operational components, too.
[36:23] So, if somebody, you know, their prep
[36:25] list can be uploaded into the into the
[36:29] app and they can say
[36:30] um the three of us are working and you
[36:33] two complain about chopping the onions
[36:35] cuz it always makes you cry. You don't
[36:36] want to do it. So, I go, "Fine, I'll
[36:37] chop the onions." So, I prep the onions.
[36:40] I take a photo of the prepped onions
[36:41] finished and I log it to my profile and
[36:44] the manager signs off that I did the
[36:46] prep. You guys didn't. You're fine with
[36:48] that, but potentially I get either more
[36:51] endorsement or even an extra bonus that
[36:53] goes into who did what parts of the prep
[36:56] list. And so, you expand that to
[36:59] checking the bathrooms, cleaning the
[37:00] lobby, doing other things like that and
[37:02] all of a sudden you've got the ability
[37:04] to motivate and gamify and reward your
[37:07] employees to do not just the
[37:10] public-facing stuff, but also a lot of
[37:12] the operational stuff in the back, but
[37:14] then divide it in a way that really
[37:16] shows kind of who who did the work and
[37:18] who didn't.
[37:20] >> Mhm.
[37:22] Um Peter, thinking about tech companies,
[37:25] you know, a lot of our audience are are
[37:28] are our brand or companies that are
[37:29] selling technology in our restaurants
[37:31] and and retail and other hospitality
[37:33] outlets.
[37:34] And I think you have an interesting
[37:35] perspective that that people could learn
[37:37] from, which is, you know, you've been a
[37:38] franchisee and an executive responsible
[37:41] for hundreds of restaurants and now a
[37:42] founder building technology for
[37:44] operators.
[37:46] What technology What do technology
[37:48] companies consistently misunderstand
[37:50] about the people actually running
[37:51] restaurants? Cuz you've been sold to so
[37:53] heavily so much until you stepped onto
[37:56] this side of the fence. What what what
[37:57] advice could you give those people that
[37:58] just keep knocking on these doors,
[38:00] blasting emails, and and and just, "Let
[38:02] me show you something."
[38:05] You know.
[38:05] >> Just be Just because your tech works
[38:08] doesn't mean we can put it to work.
[38:11] Um I've had guys I've had guys before
[38:13] that come up to me. Right?
[38:15] >> [laughter]
[38:15] >> I
[38:16] I just I just came up with that. That's
[38:17] a You can You can You can make that a an
[38:19] Inktank uh t-shirt there. And the
[38:21] reality is
[38:22] >> What What was it one more time?
[38:23] >> I don't I remember. We'll have to read
[38:24] it. We'll have to watch it again.
[38:26] >> [laughter]
[38:29] >> I I I think it was just cuz their tech
[38:31] works doesn't mean it works for that you
[38:33] can work it. Because the reality is like
[38:35] I've had guys that show me dashboards
[38:36] and they're like, you all you'll be able
[38:37] to see everything here. It's like I
[38:39] don't have a person to put in front of
[38:41] this to tease out what I need from it. I
[38:44] have no doubt that it works, but it's
[38:46] going to sit there gathering dust
[38:47] because man, we are just trying to make
[38:50] sandwiches and get people out the door.
[38:52] And that's where I think a lot of the
[38:54] the tech guys are a little too
[38:57] sophisticated
[38:59] when it comes to
[39:00] the nuts and bolts that it requires to
[39:03] run an actual restaurant. And I think I
[39:06] think a lot of tech guys would get a lot
[39:09] further with their products if they
[39:10] would spend time in restaurants, in the
[39:13] operations and say,
[39:15] "Here's [snorts] how I think we could
[39:17] tweak our product to work better for
[39:19] what's actually happening here instead
[39:21] of just saying, here's a here's another
[39:25] $100 a month solution." Because it's
[39:27] like we're already it's restaurants were
[39:29] thin margins before technology even
[39:31] exist when we were just running tech
[39:33] Casio cash registers.
[39:36] Like it was still thin margins back then
[39:38] and now we've got to have every every
[39:43] And so that's as big a problem for the
[39:45] cost of food, the cost of going out to
[39:48] eat, the cost of labor as anything else.
[39:51] And so it's not that we don't need or
[39:54] want the tech that they have, but it's
[39:56] gotten to a point where it's like
[39:58] they've got to make it a little bit
[39:59] easier to to execute in a live-fire
[40:02] restaurant that is that is that does not
[40:05] have a bunch of people sitting in an
[40:07] office somewhere managing this for them.
[40:09] It's that mid-tier stuff. It's that 100
[40:12] to 500 locations and it's the
[40:14] mom-and-pops that want to get to a place
[40:16] where they're, you know, a franchise.
[40:18] It's how do you help make that happen
[40:20] for people? Yeah.
[40:22] And that's what we need.
[40:24] >> Love it. Chad, last question before we
[40:26] go to rapid fire.
[40:28] Similar to Beck's question, is there
[40:30] something you now empathize
[40:33] with with these tech companies now that
[40:35] you are with one?
[40:38] >> Um yeah, it's like scary to talk to
[40:41] operators that you know are beleaguered
[40:44] from being assaulted by questions about
[40:46] tech and things like that.
[40:48] That's why I've been That's why a lot of
[40:50] this has just been kind of been built in
[40:53] a little bit of stealth mode and quietly
[40:57] because again, like I wanted to work
[40:59] with these guys to learn more about ways
[41:02] that I could fill in gaps in my own not
[41:04] in knowledge and experience. Make sure
[41:07] we've covered everything, really build
[41:09] an incredibly functional
[41:12] back end and then offer it with no no
[41:17] onboarding fees, no contracts, just a
[41:19] monthly a straight monthly per employee.
[41:23] Um
[41:24] to make it simple enough because I
[41:26] basically I put myself in back in my own
[41:28] shoes and I said,
[41:30] "I'm going to sell this to myself and I
[41:33] am going to use every answer I've ever
[41:35] had to say no. And when I finish
[41:39] when I finish refuting myself, then I
[41:42] will know that the product is ready to
[41:44] be shopped around to other folks." And
[41:46] so, I just kept beating myself up about
[41:49] it until I was like, "I can't say no to
[41:51] this anymore."
[41:52] >> Mhm.
[41:53] It's funny you say that cuz that was
[41:54] literally my last question before we
[41:56] went to rapid fire, which was if you
[41:57] could sit across from Peter Riggs,
[42:00] the franchisee today and show him Wave
[42:03] Wave Wage, what would that version of
[42:05] you immediately understand about it?
[42:08] >> All the bits of it now because I I
[42:10] literally used myself in in the most
[42:12] adversarial way I could to say like,
[42:15] "Look, I've rejected a bunch of people
[42:16] over the last two decades. I'm going to
[42:18] use everything. I'm going to be
[42:19] intractable."
[42:21] And I finally just kept going until I
[42:23] was like, "I literally can't say no to
[42:25] this anymore."
[42:26] >> This is a drive-by shooter.
[42:28] >> Yeah, so that's so that's where we're
[42:30] at. And then I was like, "Now that
[42:32] that's done, I'm ready to go on the Chat
[42:34] GTM podcast."
[42:36] >> Oh, look at that. Good plug. One fun
[42:39] project could be taking all of your
[42:40] transcripts from calls with vendors as
[42:42] an operator, training an AI to be that
[42:45] expert right buyer, and that you have to
[42:48] sell for it.
[42:50] All right, you're ready for some rapid
[42:51] fire?
[42:52] >> Let's do it.
[42:53] >> All right, these are off the cuff. If
[42:54] there's anything that gets weird and
[42:55] squiggly, just say pass, but it should
[42:57] be pretty easy. All right.
[42:59] Best piece of advice you ever got from
[43:00] another restaurant operator?
[43:04] >> We're just making sandwiches.
[43:06] >> Ooh.
[43:06] >> Nobody's going to die.
[43:08] >> Love it. Worst restaurant shift you can
[43:10] remember?
[43:11] >> Worst restaurant shift Oh, I got hit by
[43:13] a car. I was doing deliveries. I was
[43:15] doing deliveries back at one of my
[43:16] original restaurants, and I was on the
[43:18] way back, and a guy I used to do all the
[43:20] deliveries on my Harley, and this was
[43:22] down in in LA, and a guy cut across my
[43:25] lane, and I had my leg smashed between
[43:28] my bike and his car, flew over the hood,
[43:30] and landed on the sidewalk about 60 ft
[43:32] away.
[43:33] >> Yeah, that kind of blows.
[43:34] >> That was the worst shift, I think.
[43:35] >> Yeah, I think yeah, I would probably
[43:36] agree. Customer walks in 2 minutes
[43:39] before closing. What are you thinking?
[43:43] >> Here's another dollar.
[43:45] >> Love it.
[43:45] >> And another satisfied customer.
[43:48] >> Um great employees, born that way or
[43:50] developed?
[43:52] >> Mostly born that way, but can be
[43:54] developed if you show them something and
[43:56] give them a sense of purpose on why they
[43:58] want to achieve it.
[43:59] >> Amen to that. One restaurant metric
[44:02] operators don't pay enough attention to.
[44:05] >> The customers that just walked by
[44:07] without even
[44:09] without even stepping in. We measure a
[44:11] lot of who ate there and who walked in
[44:13] and walked out or who had problems, but
[44:15] how many people when somebody says,
[44:17] "Hey, do you want to go eat here today?"
[44:19] are saying, "No, I don't want to go to
[44:20] that place." That's a number we never
[44:22] talk about and I think a lot of
[44:24] operators need to answer that question
[44:26] and if they did, they could figure out a
[44:27] lot more about how to make their
[44:29] restaurants more successful.
[44:31] >> Love it. One thing you'd eliminate from
[44:33] restaurant management forever?
[44:38] >> Um
[44:40] that's such a great question. Um
[44:45] >> Magic wand.
[44:46] >> Tips. Ooh. Ooh. Me likey. All right. 20
[44:50] years from now, what's one thing about
[44:51] restaurant work you hope we as a society
[44:54] have finally fixed?
[44:56] >> Uh the ability to treat restaurants as
[45:00] as the important part of a daily life
[45:03] cycle as they are. We treat them as kind
[45:06] of disposable people at disposable
[45:08] locations selling now
[45:11] kind of not necessarily good for you
[45:14] food and
[45:16] we can't survive like that. We have to
[45:18] eat multiple times every day and we
[45:20] Yeah, we treat eating like it's this
[45:23] throwaway burden and then we wonder why
[45:25] we're getting sick all the time. And so
[45:27] if we could treat the industry with a
[45:29] little bit more respect, it would I
[45:31] think it would trickle down through the
[45:33] operations, through the employees, and
[45:35] through the offerings and it could help
[45:37] us again pay attention to some things
[45:40] that I think have run away from us that
[45:42] have caused the hyper expenses
[45:44] that that we see around restaurants and
[45:47] make it difficult to to to afford to eat
[45:49] out and therefore afford to have a
[45:51] profitable restaurant.
[45:53] >> I'm just going to say I like you, Peter.
[45:55] I I like the way you think. I think
[45:56] that's awesome.
[45:57] >> Great answer.
[45:58] >> Yeah, absolutely. Well, I think that's
[46:00] an ideal to go at time and land the
[46:01] plane to make sure we get you out of
[46:02] here on time as well. But But Peter,
[46:04] thank you so much for joining us today.
[46:07] And to our audience and our community,
[46:08] thank you for tuning in and giving us a
[46:11] listener or a watch on YouTube wherever
[46:13] you happen to consume your podcast. Um
[46:16] you know, Chad and I spend a lot of time
[46:18] talking to founders and tech leaders and
[46:20] people that had that big idea that
[46:22] finally decided to take it to market.
[46:24] And I it's always refreshing when you
[46:26] hear one you're going
[46:28] that lands that's going to nail it. And
[46:29] I really do believe there's something
[46:31] very powerful there. I am curious if
[46:33] breakfast will start coming earlier
[46:35] because of that as well. We only talked
[46:36] about closing but not opening.
[46:38] Um but I I I I definitely want to stay
[46:40] tuned to how you and your team do,
[46:41] Peter, as you take this product to
[46:43] market and would love to chime in again
[46:44] in about 6 months and see it get another
[46:46] measure. Have your Have your theories
[46:48] been right? What have you learned along
[46:50] the way and and where have you grown in
[46:51] in some places that you didn't expect?
[46:53] Uh but for everybody, thank you so much
[46:55] for spending time with us. This is the
[46:57] Chad GTM podcast signing off with Peter
[47:00] back and Chad. And as always, we love to
[47:02] share [music] that thought which is and
[47:04] I think this is what Peter built his
[47:06] system on which is a It's not It's a
[47:07] deliberate act of kindness. It's not a
[47:08] random.
[47:10] It's a kindness to your employees to
[47:11] make them want to stay, to reduce your
[47:13] churn, to improve your profits, [music]
[47:15] and do the whole thing you built your
[47:16] whole restaurant for which is to serve
[47:17] guests, create a memorable experiences,
[47:19] and keep people coming back your
[47:21] employees [music] inside and your guests
[47:23] outside to that building that you call
[47:24] home that you love so much. And so, it's
[47:26] back Chad and and Peter signing off.
[47:28] We'll see you guys in the next one.
[47:30] Random [music] acts of kindness,
[47:31] sprinkle that stuff everywhere. You
[47:32] never know whose day you're going to
[47:33] make better.
[47:35] >> Thanks, everyone.
[47:37] Thanks for having me.
[47:38] >> Thank you for joining [music] us for
[47:39] this edition of the Chad GTM podcast.
[47:41] Every week we're sitting down with
[47:42] founders, operators, and the
[47:43] best-selling authors who are shaping the
[47:45] future of our industry. For more
[47:46] exclusive content, follow us on
[47:48] LinkedIn. [music] Subscribe on YouTube
[47:49] and be sure to listen wherever your pods
[47:51] are being served. A special thank you to
[47:52] our guests and partners for making the
[47:54] show possible. And remember, the best
[47:56] go-to-market strategy [music] isn't
[47:58] fitting in. It's giving people a reason
[47:59] to notice. So, embrace your weird,
[48:02] interrupt the pattern, and let your
[48:03] freak flag fly.