A (2:59)

It might be awesome. Thank you for sharing. Yeah, I mean, sometimes it'd be nice to have that business model where you assign something, you're done. But I do know with people, right, hr, tech, staffing, a lot of moving people parts and heavier operational overhead. So I appreciate the insights.

B (3:17)

Yeah, that's really what makes our company very fun is, you know, our motto is we help people get jobs instantly. And you can say that and bit flippantly, but there's a lot that goes into that. It's ensuring that you have the right people with the right skill sets in the right locations and ensuring that at the end of the day you're, even though you're providing staff that might be indeed Flex workers, it really, when it comes down to it, these people, when they go on site working for another company, they're representing that company. And so it's really important to make sure that you're getting it right. There's very small margin for error in the industry.

A (3:52)

Absolutely. Thank you so much, James. Indeed, Flex emphasizes smart matching technology to fill roles faster. What are the biggest technical or operational challenges you've grappled with in matching supply like workers and demands the shifts in real time. How do you calibrate for fairness, speed and accuracy?

B (4:11)

So the smart matching technology that we have is a really interesting component of our technology where essentially what it does is it allows as workers get onboarded and they start to work with us at more and more shifts and more opportunities, what happens is we understand how strong is the worker, how consistent are they? Do they cancel at the last minute? Do they no show sometimes on their shifts? Or then that those are kind of the negative impacts or the positive ones? Are they consistent? Do they work very consistently with us? What is their star rating? We allow our clients to be able to rate the workers each time they work. And so as workers get better positive scores and minimize their negative scores, what happens is we're able to prioritize the best workers to be able to fill the best opportunities for our clients. And so what that does, it creates a really beautiful flywheel where the worker comes in, they do a good job, their rating goes up. And so ultimately, as our matching technology starts to offer the workout, it offers it out to the best workers. And that all sounds great, but at the end of the day, really, the fundamental part of our program and our product is that we don't assign workers to specific work. We allow them to choose. Because sometimes you have two locations you're looking at. One of them might be further away from you than the other. One of them might be climate controlled, and the other one might not be. One of them you're standing on your feet all day, the other one you're allowed to sit. And then there's also pay rate differences. And so within that, while we have this great technology that allows our, our system to match, we're giving fundamentally control and choice. And by the way, as a quick aside, the control and choice drives better outcomes for the customer and for the worker. Because when you're being told to do something, you're not as likely to be as excited about it as if you have the opportunity to decide if you want to do something. Does this opportunity match with my schedule? So on and so forth. And so a really important part of having of our matching technology is really the fundamental idea of a marketplace. A marketplace allows people to choose. And so when you have a marketplace, you need to have a really strong balance of the supply and the demand. If I have too many workers and not enough work for them, then these workers are going to become disengaged and they're going to churn. They're not going to work for us anymore. They're going to go find work elsewhere. If I have too many or not enough workers, sorry, and too many jobs, then you're going to have dissatisfied clients, those clients are going to churn. And so a really important component of our system, while the matching technology is great and helps to prioritize and give offers to the best workers, at the end of the day, having this really strong equilibrium of supply and demand is such a critical part of what we do, because it ensures that you've got the critical mass of the right number of workers and you've got the right number of clients and the right number of jobs. And it's not just jobs and workers, it's also the skill sets, it's also the location, it's also the pay rate. All of this stuff has to match. And when you have this matching happen, happen, and it happens effectively, then all of a sudden the workers, there's this clearing in the marketplace. All the workers that want to work are getting jobs. And not only are they getting jobs, but they're getting the right type of jobs in the right location with the right clients, and you have happy clients because they're getting better results. Ultimately, because we're prioritizing the best workforce for those clients.

A (7:41)

Amazing. I appreciate that. I like how that technology you have allows for the your workers that are onboarding. It analyzes the different metrics, what type of worker, if they're regular, they show up on time, et cetera. But again, this allows for your best workers to get the best jobs at the best clients.

B (7:58)

Exactly.

A (7:59)

The platform does great at matchmaking, which I think is cool. You highlighted that. But it also allows for the workers to choose opportunities and it's truly a marketplace. So I appreciate that. And James, as automation accelerates, where do you draw the line between machine decision and human intervention in staffing decisions? For example, what kinds of decisions or interactions should remain human led to preserve fairness, trust and candidate experience?

B (8:25)

That's a really interesting one. And especially with the advent of AI that we've had in the last call it year or two, there's been a lot of questions in the market about how much are we using technology to be able to drive these really positive outcomes and ensure there is fairness and we don't have bias within the process. I'll take one example. So at Indeed Flex we've recently built and we also allow at Indeed Proper, our clients to utilize an AI interview system. And within this AI interview, you're essentially talking to an AI agent and they're asking you questions about the specific role. It's great because it asks second and third level questions and then essentially we'll score the candidate and then give the client the opportunity or our interviewers the opportunity to be able to look at the specific questions to ensure that the AI was working correctly and did prioritize and did rank the candidates or rate the candidates correctly. But one of the interesting parts about it is to your point, how much is too much and are we moving too fast? And so we do a lot of surveys for workers and actually the sia, which is an industry analyst group in the staffing industry, recently ran a survey and Brian, it was really interesting. They found that 88% of interviewees, 80%, 88% of candidates actually either prefer or are as happy with an AI interview process as they are with a human recruiter. And so you wonder, you say, wow, like that's pretty phenomenal. Like a huge majority of people are actually think it is as good, if not better to be interviewed by AI. And so you say, well, why is that? And you start to Dig into it. It's because a lot of the things that people initially look at as potential concerns, the biases as an example, are largely taken out by AI, right? Like AI isn't going to judge you for how you look or how you sound or anything like that, right. They're going to do it based on the true content of the answer that you're giving. And so we, in addition to that, if you think about it, if I work a night shift, when I start work at 8pm or and I end work at 5am or something like that, when I'm at the beginning or at the end of my shift, if I'm trying to get an interview to be able to find a job, most of these places, most of these recruitment firms are closed at that point. Whereas if I can just hop on and have an AI interview right off the bat, on demand, whenever I want to, and I don't have to wait to schedule a time for tomorrow or the next day or whatever it might be, it allows me to interact and essentially speed up the process of being able to find a job. And so we're finding that the convenience of being able to instantly interact with and be able to allow this system to run an interview at all hours of the day, day or. And that paired with the fact that you're missing the bias, you don't have that bias anymore. And then the third part that's I think really interesting component is that these AI agents, as they continue to get more and more advanced, they actually do a better job interviewing. What I mean by that is that they're not just going down a list of questions, they're actually asking follow ups, they're asking second and third level questions to be able to really dig into. Truly does this candidate know and do they fully understand the role that they're going to be getting and have they shown success in it before? And so you have a really strong interactive process that's being run. And so while the there's always fundamentally this is as I mentioned at the beginning staffing industry, it is a human process at the end of the day. If you can remove friction to allow people to get to work faster and on top of that at their own time and have the results be on par, if not better, it's a great value add for workers as well as for businesses that are looking for staff.

A (12:14)

Thank you, really appreciate that. And you did highlight some interesting things with an AI interview system. It is pretty thorough and it can do follow up and ask those second and third level questions of Course, I like the survey you mentioned that was done. 88% of candidates are as happy with an AI interviewer as as much as a human interviewer, which I thought was interesting. But I can see that with candidates not feeling that there won't probably be any bias with an AI interview. Of course. And of course the convenience 24 by 7, the speed, everything is going to move much more quickly in that process. So that's only a win win for both the client and the worker. And James, the last question of the day I have for you. Over the next five to 10 years, how do you see staffing platforms and the staffing model itself evolving? Like more gig work, micro work, fully on demand labor, what will indeed flex look like in that landscape and how should companies prepare?

B (13:12)

So I think there's two main parts of it. Number one is the business side and then the other part of it is the worker side. So I'll start on the first part with the business side. Fundamentally, when you're doing staffing, as I mentioned, there's some complexity to it. Does the person have the right skill set? Do they have the experience? How far do they live from where my facility is located? Are they able to work the schedule that I've determined, whatever it might be? And do they have to have a background check and a drug test? And so, and what is the schedule and how do I actually access this location? There's fundamentally like when you're trying to get a person to come to your location who maybe hasn't been there before, there are a lot of questions that have to be answered. And so because of that, historically it's been a very manual process to be able to collect this information, ensure that it's getting from the business that needs these services over through the staffing company over to the worker. What our system has done is really simplified this. So now not only do we have this AI interview, but we also have an AI agent for our clients. So what this means fundamentally is a client can go on our system now and just type in, I need 10 servers or 10 picker packers or 10 call center agents to start next Monday at the A shift in location B, and the system will understand that and you press Enter and boom, you're done. So prior to that it was having to go to a number of different agencies and how many can you find? And let me make sure you understand what the A shift is and what are the hours and so on and so forth. And there was quite a bit of back and forth that was required. Whereas now it's as easy as just typing in one sentence, press Enter and you can kind of set it and forget it. And so you think about at the end of the day, having staff is a critical part of my business continuity. But really, bottom line, like there's friction in being able to find the right staff and send them the right places and whatnot. And so what our system does is makes it really easy. I mean, you're meeting people where they are, they want to be able to text message and say what they need. And now they have the ability to do that. That's on the client side, on, on the job seeker or the worker side. I think this is the really interesting part, Brian. If you think about it like now you can go online and order just about anything in the world to be delivered to you in the next five hours, right? Like 15 years ago, even 10 years ago, you couldn't even dream of this. You couldn't dream of being able to say, wow, I need some new cleaning detergent or I want to get a new pair of socks or whatever. And all of a sudden it's not just are you going to get socks in five hours, it's what design do you want on the socks? So things have changed so fundamentally. I mentioned that because those people that are working for you are also your consumers. And those consumers are demanding more choice. They want more flexibility in their personal life and that has started to bleed over into the work life as well. They demand more flexibility in their work life. And so as you're giving consumers more choice and more control in the way that they're interacting as consumers, they want the same type of flexibility when it comes to their work life. So the ability to be able to pick up a shift here or pick up a shift there is really important. When you have people that are working in the sub $20 an hour pay rate, quite often they have two or three jobs. So they're doing food delivery, they're doing rideshare and they're picking up work somewhere else. And so giving people the ability to be able to decide, hey, you know what, maybe I would love to work a full time job. But you know what, every Wednesday I have to take grandma to the doctor. That's something that people are not willing to make that trade off for anymore because fundamentally they don't have to other options now. And so it's really important that businesses understand that just because someone can't work on Wednesday at 2 o' clock because they have to take grandma to the doctor, that doesn't mean they're not a good employee. That just means that we need to be more flexible in the way that we're allowing them to interact with their work. And so being able to provide people this type of flexibility to choose when they work and where they work and how much they want to work is a net benefit. Because at the end of the day, Brian, this person might start working for you. And maybe we'll convince grandma to miss that doctor's appointment this first Wednesday, but in a couple of weeks, they just can't do that anymore. And they're gonna end up not showing up and they're gonna have to ask for forgiveness, not permission. And you're not gonna know until it's too late. And so why not from the very start, just give them this type of flexibility to allow them to choose, hey, I wanna work Monday, Tuesday, Thursday, Friday, or maybe I only wanna work Mondays and Fridays. And if I can just start to get the consistency of the workforce. And I know that person, but I know it's going to be someone that I know, right?

A (18:10)

It's.

B (18:10)

It might not always be James, but it might be James and Brian tag teaming on this role. Fundamentally, like you're going to get better outcomes. And at the end of the day, James and Brian are actually going to stay working for you for longer because you're offering, you're offering a differentiation in the fact that you're offering this type of flexible scheduling that a lot of other organizations are not yet offering.

A (18:31)

Thank you. Appreciate you breaking that apart. Obviously, let's highlight just the business side. We talked about that early on in the podcast. Lots of complexity, overhead, a lot of research, et cetera. And your platform has taken a lot of that overhead out of that work and built in a lot of efficiencies, which is great. On the worker side, I like your analogy of where you can now literally order something online and get it within five hours. Do it every day with Amazon. Right. But it's amazing how workers can now have that flexibility as well. And if they want to pick up something different type of shift and extra shift, et cetera, they can actually do that now, which again, just opens up the playing field for everybody, which I really love. So thank you for sharing.

B (19:15)

Of course, at the end of the day, like, especially in 2022, when there was such a staffing shortage, pay rates increased quite a bit. And fundamentally, like, how much you get paid obviously is always going to be such an important component of a worker deciding to work there or not, but there's a certain trade off, right. Like, at a certain point, if I can have that flexibility or it is closer to me or I have the ability to be able to not have to work on Wednesday. As I mentioned, that type of flexibility has a lot of value, and you're not always able to just compete on pay rate. Sometimes you have to have other types of benefits to workers that sets you apart from the rest of the field. And so having this type of flexibility is a really, really good way to offer a value proposition that differentiates yourself and makes you more of a sticky business that allows you to get a strong workforce despite the fact you might not be the highest payer in the market.

A (20:09)

Thank you. I really appreciate that. And James, it was such a pleasure having you on today, and I look forward to speaking with you real soon.

B (20:16)

Thanks so much for the opportunity, Brian.

A (20:18)

Bye for now.