186: Tap into an Instant Workforce with Scott Absher

Scott Absher is the Co-Founder and Chief Executive Officer at ShiftPixy, a next-gen gig economy platform revolutionizing today’s shift workforce. We discuss the future of the shift economy, how to use AI to manage your workforce, and ways to get an endless supply of shift workers. 

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Tap into an Instant Workforce with Scott Absher

Our guest is Scott Absher, the co-founder and CEO of ShiftPixy, a company seeking work opportunities from job providers with the open time slots of available shift workers. Scott, welcome to the show.

Thank you, Steve. Good to be with you.

Well, it’s going to be an exciting conversation because you have developed an interesting application that I’ve not heard about before. And that could be a great framework for a lot of businesses that need the shift workers that we are talking about. So before we talk about your framework, let’s just talk a little bit about your background and how ShiftPixy come about and how did you land in the CEO job?

I had an unusual background in that I grew up in the human capital management space in the early 90s. Kind of started at the same time. I was a technology hobbyist. I wrote code and used to I designed technology as a hobby, and then that morphed into a part of my career. And then there came a time where those two passions kind of collided. Back in 2015, I was approached by my co-founder about a problem that he was seeing in his part of the human capital management world.

And in his particular part of the world, he focused on part-time labor driven industries. And in particular for him, it was fast food, chain fast food restaurants and pizza operators. What he was feeling from his clients was a problem that he’d never asked for their help on. And it was about finding people. And what he learned was that in that tradition, especially with restaurants or actually any industry that relied heavily on part-time labor. The tradition was you could expect 100% turnover.

So somebody that started in December or January would likely not be there in December. And when you’re charged with handling the human capital, that means all these onboarding and offboarding exits and that sort of thing, you have to handle the paperwork, documentation, administration for, it’s hard to make money with any group that has high part-time labor concentrations. But the question that he was being asked, and can you help me find people, was kind of made on an assumption that he was working with so many restaurant operators that he’d have a population, but that’s not the way the industry worked at the time.

And what we came to learn later was that the tradition of 100% turnover had actually escalated to 300% and 400%. And when we looked at that, we also learned that the attribution for that was that now all of these from 2015 on, because of smartphone adoption, that all of a sudden a lot of different gig platforms and opportunities started to emerge that were creating new opportunities and appealing to this fixed part-time workforce in the US in particular. So all of a sudden now the brick and mortar guys, all these operators were now struggling to try and keep a full bench. And that was really the problem that we merged into trying to fix.

So, you basically have to respond, you have to respond to the challenge of the gig economy emerging and how do you actually play in the gig economy so that you don’t lose out to other people who provide the flexibility.

That’s right.

That is fascinating. So let’s talk about the framework that pertains to this topic, which I think we called it the load balancing framework. So what does it mean, load balancing, and how do the companies that need shift workers, how do they come together with these mostly unqualified shift workers for opportunities?

Well, it starts in our particular case that load balancing is not a new concept. It’s been used in technology for a long time and engineering for a long time, but never really in human capital. What we’ve learned in our work in the industry since 2015 is that it’s not just these industries like I described restaurant and hospitality that rely on part-time labor.

Really the Fortune 1000 relies on even a contingent side of the workforce where they’re actually extremely reliant on having this workforce that can kind of fill in around the edges that’s not part of their fixed overhead to make sure that their business keeps moving forward. You can imagine that being somebody like an e-commerce company that has to gear up around the holidays because gift purchasing is going up. Could be other seasonal aspects of their business, could be people that are in a seasonal food processing operation where they have a surge at particular points in time where they’ve got to access human capital.

And the load balancing concept for us is that our platform would allow these types of employers, these types of customers to have a ready bench that they can access and deploy to work. So that the idea is that they don’t have to worry about these imbalances of human capital that on a platform like ShiftPixy, they could actually access a nationwide workforce and fix problems in any part of the market that they needed to and do so compliantly. And that’s the big contrast between what we do in the gig and the gig counting platforms. These are treated as W2 employees on our platform.

In the world of human capital, as in technology and engineering, load balancing is the key to success. Shift your focus, find your balance, and keep your workforce in motion. Share on X

So how do these people even know what they need to do? So they show up, they get pulled in, there is maybe a seasonal imbalance, there’s a holiday season and Amazon pulls these people in.


How can they be deployed this fast without any training or do they get training as well?

Well, you got to remember that a lot of these jobs, especially the ones that we’re focused around in the part-time, these are non-skilled jobs. These are not like accounting, finance professionals, engineering professionals, etc. We’re really focused on people that are doing labor. They’re lifting boxes, they’re packing boxes, they’re loading trucks, they’re flipping burgers. All things with very low skill levels, but work that still needs to be done.

The idea is that, let’s think about finding ourselves in a planning meeting and we’re a big box retailer. And we just learned that we’re opening a new distribution center in Biloxi, Mississippi. And all of a sudden, I’m in charge of human capital. I’m starting to think in Biloxi, Biloxi, who do I know? One of the things that we ran into as we were building our platform, we learned that very large companies have the way they fix their content or manage their contingent workforce is with distributed relationships around the country.

So when Biloxi would come up, they’d say, oh, no, I don’t have a temporary worker pool or a relationship in Biloxi. I need to find one and also manage that. In our ecosystem, you can actually go into Biloxi and see how many people are in our workers population. You can see what they’ve done, what skills they’ve done, what their average hourly wage has been on our platform, and you can communicate with them directly. You can open up an opportunity for them to go to work. So that’s where this idea of load balancing comes in, where I’ve got an imbalance, I can go in there and I can, with real-time business intelligence and my own smartphone, I can do my own load balancing.

And to take that concept a step further, Steve, we’re employing behind the scenes a lot of AI to manage those workflows that would traditionally be managed by people, which might be a friction point. Somebody may forget to do something or didn’t get it done or has to repeat a task over and over again, whether it’s a phone call, a text, an email. Our AI actually intervenes and actually continues the conversation, continues the momentum and keeps people in motion. And to the extent that we’re applying this to the load balancing concept, it’s it becomes more of an automatic function rather than a semi-automatic function.

AI isn't just for tech; it's your ally in workforce management. Let technology handle the repetitive tasks, manage workflows, and keep the momentum going. Share on X

So is this task management that keeps people in motion or is it?

If you think about it, even in hiring, there’s task management. Number one, I’ve got to locate a pool of candidates. Number two, I’ve got to screen the candidates. Task two is screening them for their capabilities and their geographic fit. Third thing is, third task is I’ve got to do outreach. Once I’ve decided who I’m going to call, I’ve got to do outreach now. And that outreach becomes a task, a repetitive task on its own. One conversation to get to one person, it may take many calls, many attempts, many missed opportunities, many missed connections.

The rule of thumb in the staffing world is that for every one position that you have open or every shift opportunity that you have open, you get to have 10 candidates that you’re pursuing to get that one filled. That shows you how the fill rate is pretty narrow. And so with technology, all those workflow steps that I described, those tasks, then that task management process all becomes the realm of the artificial intelligence. The robot actually does it for you.

That’s fantastic. So what’s the psychographics of the population of shift workers who are working through a platform like this as opposed to trying to get a job or, or finding work in other ways.

You know, the psychographic for that population has not changed too much. You’re gonna find in that population that it would start as early as kids in high school that need to make money to pay their bills and to pay for their fun. That’s part of the early stage of the population. Then even in college, you’ve got a lot of people that are working their way through college and they need flexibility and they generally gravitate to one or more part-time jobs.

And obviously today it’s much easier with all the platforms we talked about. But then even in people that are in transition, maybe they’re transitioning out, maybe the company that they worked for went through a series of layoffs. They still got to keep food on the table and they’ll pursue some of these types of opportunities. And it could also be people in retirement. What’s one of the crunch points now that I think you’re going to start hearing a lot more of is there are a lot of people that are retired from that are now in a financial pinch because their retirement income isn’t quite making paying the bills.

And so you’re going to start seeing a larger and larger percentage of that population pursuing these types of part-time opportunities. They’re probably not in a position or not interested in jumping into another full-time job, but the idea of being flexible, moving from one part-time opportunity to the other. So it is a pretty wide range of people and positions in life that make up that psychographic.

What about the demand side? So is it just the companies that can afford to do this, who basically have a volume of positions to fill and some people don’t show up, it doesn’t matter because they overbook or even small to medium-sized businesses could do this for particular positions, one or two positions here and there. Could they reliably use the system?

They could and the way it sets up it aligns with kind of the market demand. So what we’re trying to provide that real time business intelligence and the ability to do things nationally with a single source at scale to appeal to the large buyers. We have several large national accounts that are starting to roll onto our platform and there’s a big appeal for them. But by contrast, on the other side of the market, you’ve got some smaller companies that like to stay agile, like to stay nimble, and they do project work.

It might be somebody that does home remodeling, might be somebody that does seasonal work, might be somebody that does… we have some clients that do exhibition work. In other words, when a trade show opens up, they’re in there and they staff it, they put it up, they break it down, but that’s not regular work. So there’s a large number of those types of companies that can benefit, again, by having a single relationship. They can tent up in any market they want and have access to a real time workforce.

That’s cool. That’s cool. So basically, it’s like an e-bay for for unskilled labor. If you have some time that you want to sell, basically you want to do some income and you want the flexibility, you jump on and see what’s available. And companies are essentially when they need someone for a short time, they can jump on. Now, when you use AI on this platform to create this load balancing, what is the mechanics of what the AI does? So how does this automatic load balancing even work?

So, what we do on the front side and the user experience for somebody that was coming in as a shift worker, it’s really a chatbot interface. So they don’t really recognize that they’re chatting with the AI, but to the conversation and the coalescing, the coercion in some cases, all those things that you need to move and motivate somebody through a process is all being run by AI. But on the backside, the AI is doing another very interesting thing. And what it’s doing is it’s looking at all the schedules and all the openings.

And as it’s monitoring and managing the schedule openings, if somebody decides they’re not going to show up on our platform, they would just check out. They just say, I can’t make it today. And what the AI automatically does is notify whoever’s managing that shift that, hey, you’ve got an opening now, and here are your options. Your A options are people from your home team that are already working and already on the payroll. But these are ones that are here’s the ones that are not working. Do you want to do an out call to them?

Second, it would in our ecosystem, it’s checking for overtime risk because that’s the problem is somebody steps out, somebody comes in. Am I going to be paying overtime? So it’s looking at that part of the load. But then it also has a larger population option where it can look at the population that’s locally available to that same shift operator and say, do you want to open the shift up for one of these people in the population?

The way it’s set up, and I call it semi-automatic, and in that it’s capturing the incident, showing you your options, and then asking you to select, it’s really set up in such a way that it can be done automatically. Once the shift operator comes to understand that and the AI gets to learn their preferences, it’ll automatically make those out calls and automatically do that research or outreach to fill those shift gaps. So that’s where on the backside is where you see more of the load balancing.

Life is a demand-and-supply game. When the supply of opportunities is low, let your value surge. Share on X

That’s fascinating. And what happens when you said it was it’s a demand and supply kind of game. So if there is low supply, is there a surge like you there that that wages surge and then you try to attract more workers by raising the value of the wages that are available?

Well, the way our system works, and that’s a good question. Fair question. What happens is that people are kind of rated in our system as they travel and what you’re going to find is that if somebody is at an overtime risk but they’re available so as an example in California anything over eight hours is overtime anything over 40 hours is overtime so if somebody is available and maybe they want to take some extra work but they’ve worked 40 hours for somebody else for the week, they have an opportunity to do so.

And then on our platform, they’d actually do it at a premium. If they’re available, they’d be presented at that overtime premium, and which is a good thing. You know, they’re a good worker, they’re getting a lot of hours, they’re in demand. There’s also some opportunities for the business operator to provide some incentives in there. In other words, they can say where they might normally be paying $15 an hour, then maybe they’re happy to pay $18 an hour or $20 an hour to cover that shift because they need the help. So it gives them a lot of flexibility in terms of when a surge happens, they can see what their options are.

Your value isn't determined by the hours you work, but by the impact you make. Share on X

Okay. So basically, it’s driven by or controlled by the employer, regular employee.

That’s right.

That makes sense. That’s kind of different from platform like your freelance platform like Upwork, where it’s the employee or the worker that controls the price rather than the hiring employer. That’s a really interesting dynamic. So, Scott, you know, so the listeners, they run a small business or videos as business and they want to tap into this resource. Where can they go? And also, if they want to reach out to you, how can they find you?

They can find me at ShiftPixy.com. You can always post on our marketing website there. If you’ve got an issue or you’d like to get to know us, you can certainly ping us there.

Okay, fantastic. Well, definitely do Scott Absher company, ShiftPixy. There’s also a link there if you want to reach out to him. And also make sure you check out the YouTube channel because we are there and the YouTube channel is growing. So check us out. We also have published shorts of every episode. So if you just want the framework or the very essence of the episode, just go there and you can watch those engaging videos as well.

So Scott, thank you for joining me today on the show. It was a very interesting business and it’s amazing that now these platforms cover all types of work and it also gives people the opportunity to work whenever they want to work and whenever they have spare capacity. I think that’s wonderful that this can be mobilized and used. Let’s talk soon. It sounds good. My pleasure.


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