← Using AI at Work: AI in the Workplace & Generative AI for Business Leaders
Using AI at Work: AI in the Workplace & Generative AI for Business Leaders
84: Using AI at Work to Optimize Workforce Scheduling and Planning with Mohamed Yousuf
00:43:19
Loading summary
Transcript74 lines
- [00:00]
A
In Canada, about 40% of nurses below the age of 35, they change careers completely due to burnout.
- [00:06]
B
What is your research showing as far as the economic impact of AI enabled smarter workforce scheduling?
- [00:12]
A
For example, there's one cleaning company here in Ontario, they have 100 employees, did about a four month study on them just in labor cost. In a year they saved 500,000. In productivity gains they gain about 900,000. And the turnover, you're saving almost 250,000. So you're looking at a saving of 1.65 million USD. Right.
- [00:29]
B
What might be some of the other industries that you expect are going to get the biggest lift from using a tool like this?
- [00:35]
A
I believe hospitality.
- [00:36]
B
Yes. Restaurants, hotels.
- [00:38]
A
Yeah, they're very seasonal. And especially if you can come to a point where you can exactly know when to hire part timers, when to let them go. If you're just going to be that company known to panic hire and panic fire, people won't want to work for you.
- [00:50]
B
Mohamed Yousef is the CEO of Smart Workforce AI a global leader rethinking how we schedule and manage teams with AI. With over 15 years in workforce planning, he's not just optimizing shift, he's giving people their time and sanity back. Welcome to Using AI at Work. I'm your host Chris Daigle. Each week we'll be learning how today's business owners, entrepreneurs and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now, every business leader is asking the same question. What are we going to do about AI? If this is you, chiefaiofficer.com has the answer. We give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day to day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also guide company wide transformation so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficer.com and see how we're helping companies of all sizes finally get results from AI. Hey everybody and welcome to another episode episode of Using AI at Work. My name is Chris Daigle and I'm the host of the podcast and our guest today is Mohammed Yousef from SmartWorkforce IO. This is an interesting topic because you know, sometimes we cover like the last episode I just recorded was on SEO and maybe we'll talk about a certain tool, but what we're going to be talking about today is something that applies to every business regardless. I mean, except for solo solopreneurs, I guess. And that is how do we leverage AI to manage the workforce as far as scheduling, preventing unnecessary overtime, making sure that we've got the right people in the right place, that we're predicting demand and all those sorts of things. And the guest that we have today, based on the conversations we've had in the past, is certainly an expert at this. So Mohamed, welcome to the show. And before we get started, you know, you shared with me in a past conversation about this, this journey that you took to get to where you realized this was a big opportunity. So kind of walk us through what the, what your work history has looked like that led you to being the founder of Smart Workforce IO thank you.
- [03:11]
A
So much, Chris for the intro. So, as you mentioned, my name is Mohamed Yousef, CEO of Smart Workforce AI. So it all started a little bit of my background. I've been in the workforce and scheduling industry for about 15 years now. I started out as a scheduler, the day to day operational, you know, firefighting. I went into planning schedules on a month to month basis and eventually got into the role where I'll be, you know, making budgets for manpower for large airlines. I started off first at Air Canada, got the experience, went out to the Middle east when there was that boom in Dubai and Abu Dhabi for all these new, these new expanding airlines. I worked there. Then I went to a, to a startup where again, I had to do everything from A to Z. So it was managing the whole department from scheduling to planning to manpower. So you've always known that in a system you've always, if, if the manpower is correct, the scheduling gets easier and the day to day firefighting is less. Right. But no one can ever get that number very, you know, correct. It's very, you know, up and down. Things change. But what happened was about four years ago I, one of my old bosses from the airline I work for, he went into the filming industry. So it was more into the vfx. So it was, at first I was a bit scared. I'm like, okay, it's a completely different industry. I was in airlines for like 10, 11. Now I'm going to filming. When I went there, it was similar. So you get the shots from the directors or the movie companies in Hollywood or wherever they are. They send it out to their partner VFX studios. And then you get that demand. And now you need to look at the calculation. So what can everyone do? What, what each VFX artist can do to, you know, to clean up those shots. And then it hit me, I was like, at the end of the day, in every industry, it's always the demand supply. What are the performance metrics to determine what each person can do? And, and a lot of it could be automated. I'm not trying to say like it's going to take everyone's job. No, it's going to complement their jobs.
- [04:57]
B
There you go.
- [04:57]
A
So about two years ago, I remember when ChatGPT first came out, I was like, okay, you know what, it's a big hype. AI. AI's been here for a while. But that's when everyone just started saying, AI, AI, AI. So I was, I was learning just by myself on YouTube and I wouldn't find anything. I was always finding like, AI for marketing, content creation, AI for like legal, to make, you know, analyze documents faster. And I kept trying to learn to see what I could do, maybe I could start something, but never really, you know, stuck with me. And I remember I was on vacation and it just hit me and it was like, everyone is using AI to simplify their job and their experience. Why am I looking at, you know, YouTube videos on marketing or legal or that and trying to open something there? Good point. What do we do in manpower and scheduling? And what do we do that's so repetitive? A lot of the stuff we do is forecasting, which if you already have all the data or the inputs, that can be automated. Right. The monthly schedule build, if you have all the parameters already from every company might say, okay, the labor laws say they can only work, you know, 140 hours. You know that, you know what the limits are for rest. You know that can also be automated. Right. And the day to day is where it gets a little trickier. This one I believe we're working on eventually can be automated with like a. It's when someone calls sick, someone gets replaced. That's also something we're working on. But then I was like, you know what, we're not just, we're not just here just to build another scheduling tool. We're trying to build an intel intelligent decision making tool that can complement the people who are working. So for example, in scheduling, they could be working through a disruption. An airline, a flight's delayed, the pilots or the cabin crew are not able to move on to the next flight. The AI could give you suggestions right there like, here's our suggestion. You have these people, then the human can say, okay, you know what, this could work. This could work. You click on it from a monthly plan, it can learn, right? So it can learn how people bid, how, which, which for example, schedules people usually call sick for maybe the midnight, the graveyard shift. You know what, these need to be balanced out more because we see like an 80% sickness rate. We use AI, we use large language model tools to, you know, analyze these, these tools and also recommend to the planners, like you've built a schedule like this. Here's an optimized way where we feel that we can get more out of the staff. So it was, it was something that I still see until today. There's, it's, it's, there's not many tools out there. There's a lot of the bigger companies who are starting to use AI. But when I played around with it, it's just like you're trying to cover a shift for the next week. Here's our suggestion. This person's off. Do you want to proceed with it? It's not. We're trying to make it from end to end, from the day to day struggles due to, until the manpower. So from the top to the bottom, it's completely. You have an AI co pilot with you.
- [07:54]
B
So this is something that, you know, I love to address issues and challenges with business that I can support that tend to be universal issues.
- [08:03]
A
Right.
- [08:03]
B
In our consulting side, we tend to target knowledge work. Right. Because that's. AI can gobble that stuff up. Yeah. This is an area that I haven't really addressed much before, but considering who our clients are for our services, they've got big workforces and I hadn't, prior to this conversation that we've had, I, I hadn't considered the impact that AI could have with what sounds like what could be a huge headache for a lot of companies. We talked about construction earlier, before we started recording. Say a construction company's got a couple hundred people out there in the field. I would imagine that in that environment there's a lot of turnover, there's the sickness issue and stuff like that. How are those companies probably doing it now as compared to what it would look like if it was supported by a tool like what you've created.
- [08:49]
A
So we did one study actually with, with the healthcare industry. I'm not sure how it is in the States over there, but in Canada we have a huge healthcare crisis at the moment where people are dying, waiting for appointments, people are waiting. I went to once for an emergency. It was. I was there for about 10 hours. And when you speak with the nurses, they're all saying the same thing. We're over exhausted, we're burnt out. And I read somewhere it said that In Canada, about 40% of nurses below the age of 35 resigned due to, they changed careers completely due to burnout. But what I noticed is a lot of the systems they use is very outdated. Outdated. And a lot of times they try to build their own systems which, which they don't seem to work. They're very like prehistoric when you see that, even ui. But what we were doing, what, how AI will help. First of all, again, like if they have a, if it's a hospital that has a lot of data and they work with a lot of data analysts, they probably can get past this part. But we look at historical data, right. So people don't look at, okay, there's also, there's trends, right? The flu season, things pick up.
- [09:50]
B
Sure.
- [09:50]
A
Yep. There's a lot of things that they might miss. And they can also plan in advance because there's a lot of freelance nurses. There's a lot of, I don't really call them, they're like traveling nurses, right. You can forecast, okay, during these peaks, instead of calling them out last minute, you can prepare, prepare months in advance. Say, hey, because a lot of times they can't get last minute nurses. Right? Yeah, we have bike and you know, patient intake. We need you guys from November 10th to December 25th or during the holidays when people have more time, maybe they get more sick. So there's a lot of things that it will look at. Say it go back five years and it'll automatically have these suggestions. Another thing that we were looking at is also the future, right? So a lot of the times what they look at is, okay, let's look at walk ins. So emergency room walk, emergency walk ins. And they look at patient bookings, right. And they can forecast. What they don't look at also are aging trends. Okay. Maybe as people get older, maybe you have an aging population, you'll need people to, that will come to the hospital. AI will look at different large length models, will look at different statistics online. It'll look at, you know, the government pages. It'll also know, okay, you know what, the population is aging by X amount of percent. You're going to probably have an X amount of increased intake. Another thing also is what they don't look at is immigration. Right. We've had one of the largest immigration trends in the last few years. And no hospital prepared for it and that was one of the main reasons we are in a health healthcare crisis. We've got millions of people coming in and yet they never planned for it. So what our language, our model looks at is okay, you know what, what are the government's predictions for immigration in the next couple of years? It will say, okay, you know what, due to these trends you guys are going to have to increase your manpower by X amount and it gives them enough time to reach out to maybe graduating students. Look at, you know, problem is it's very reactive here. I don't blame. There's not a lot of forecasting tools and even with AI, you can link your forecasting tools with this thing called Profit. It's by Facebook, by Metam, where it just can quickly take a lot of data, a lot of times your forecast and, and it can look at seasonal trends, labor peaks and then you can plug it into your system and you can just make it into an easy to use system that you can connect with your HR portal which can, you know, flag. Okay, you know what, you guys need to recruit these people and just make the process a lot faster than it is today.
- [12:08]
B
You know, it's fascinating all the applications of AI, right?
- [12:12]
A
Yeah.
- [12:12]
B
So this not only can help with a perfect example I would imagine would be there's probably a lot of call outs for that graveyard shift regardless of what your industry is.
- [12:21]
A
Right.
- [12:22]
B
If we can see that trend, then we can have a couple in the chamber ready to go. Right?
- [12:27]
A
Correct. Correct.
- [12:28]
B
That's handles today. I don't have to have a big headache like as of today, but the ability to strategically use AI to forecast. Okay, what does this mean as far as hiring trends for us next quarter, next year and beyond? That's like way beyond what I was thinking about and that's fantastic. So what are some of the industries that have been particularly impacted by or, or that you see could particularly be impacted by something like this? Like an AI enabled forecaster, predictor, scheduler. We've talked about medicine and that makes a lot of sense. But what might be some of the other industries that you expect that are going to get the biggest lift from using a tool like this?
- [13:17]
A
I believe hospitality, yes. Restaurants, yeah, they're very seasonal and especially if you can, it can come to a point where you can exactly know when to hire part timers, when to let them go, what, what your base full time because you never want to have a high base. And then during, you know, the sea, when the season drops, you know, you're either going to let people down by letting them go or, or be too short. Right. Or last minute, you know, so hotels are a good one. And also what the system will also let them know in advance what are big summits that are coming into your city. Right. What are big events? Like for now, we have the World cup coming up. So yeah, again, they should know exactly. Okay. What to expect. Like for example, in Vancouver, what happened now? Again, they. Again lastminute.com yeah, in residents to, they're asking, hey, can you guys sign up so you guys can get permits to rent out your rooms for the World Cup? Rent out, you know, extra spare bedrooms because they don't have enough, you know, hotel spaces or, or such. Again, it could have been planned out better if they, you know, if it was because this is not like it was announced yesterday, right? Yeah. So there's hospitality hotels. Whenever there's concerts, this will look at all of that and let them know in advance to know when to hire part timers. And again, I always mention that base. They always need to get it right because what a lot of companies do wrong, and I don't support it at all, is they panic higher. Panic fire. Right. What happens usually is when as soon as they see like sales are dropping or money's not there, they hire these big, you know, these guys to come in. They come and look at their books. They tell them, okay, you know what you need to get rid of, you know, 20% of your manpower. And then slowly after that, economy picks up a year later and they're rushing around. So people are like, you just fired me a year ago and now you're hiring, you know, yeah, you don't, you don't want to do that. You want to go as far as possible to even look at potential economics, ups and downs. You need to make sure. Because the thing is, you're like, you know, man, it's, you're playing with that. This, this is why it's a very, like a very sensitive thing because you're playing with people's lives, right? People, their livelihood, but their, their schedule, which is when they can go out with family, when they can, you know, if they're burnt out, they're not going to enjoy that free time. And on top of that, if you're just going to be that company known to panic hire and panic fire, people won't want to work for you.
- [15:41]
B
Yeah, Yep. The word will get out. So this is interesting. We don't have a big team here. We're leveraging AI successfully, so we don't need a big team. But for most companies that haven't made that leap yet, that want to expand, this is obviously an important issue. What does the impact look like for them on the economics of this? I mean if I'm understaffed and I got to pay my people overtime, that gets very expensive. If I'm understaffed and can't, can't fulfill the demand for my services or my business, that's lost revenue that I, there's no chance for me to get that back. That's perishable. What is your research showing as far as the economic impact of AI enabled smarter workforce scheduling?
- [16:24]
A
Okay, I can give you some numbers I have here. So for example, there's one cleaning company here in Ontario, they have about 110 employees. But for to make the numbers easy, I'll just say 100. So what we did, they were actually a good example because they have full timers and they have contractors. So we took them, we did about a four month study on them and we looked at. And the good thing is because they're contractors, when we did the study and we gave them the new schedule, they didn't have to hire these extra people for the. So what they had the same schedule they had with the contracts that they had. I wrote it down here. So with labor costs they saved about 10%. So they didn't hire, they hired 10% less contractors. Their gains on the ones that they already had was about 18%. So even though they got rid of some people, they boosted the current guys by 18% and the turnover rate was at, was 10% less than what it was previously. So if you look at it, let's just say 100 employees have it here. So $25 per hour, let's say 40 hours a week. 40 hours per week and 50 hours a year, let's say two weeks vacation. So that's 5 million. Right. Just to make the numbers easy. So if you take these percentages, you're looking at just in labor costs in a year, they say 500,000 in productivity gains, they gain about 900,000 there just by bumping up that productivity and the turnover. If you say, let's say it costs 25,000 per employee times 10 employees, you're saving almost in 25,000, 250,000 in Turnover House. So you're looking at a saving of 1.65, 1.65 million USD. Right. And the thing is nobody sees that. Right? They don't see that, that your manpower is one of the biggest costs. You know, a Company can have and they look at oh, this guy's leaving or this guy's coming, oh, we're going to just put a quick schedule and we're just going to pump it out. But the thing is that as smart as we are, what we can do in probably in a week, an AI system can do it in a matter of hours. Right. So again, it's good that you have this tool because when you're a scheduler, when you're a planner, you can run scenarios, you can say, you know what, let me see, what can I do if I increase the hours a little or decrease that? So it gives you more time to actually do your real job, which is the creative side of it. Right. Look at different scenarios. What if we want to take on extra work, how much people need? So it gives you the, it's not going to like people say, oh, AI is going to take my job. It's not going to take your job. It's going to actually make you a better employee, better manager and you're actually going to see the company, you know, profit a lot more. And a lot of the problems. Why like say like a company that has 50 employees or 40 employees, a lot of the times they don't get scheduling systems is that if you look at like the larger companies, let's say they usually cost a lot of money and have a very high implementation cost, can be sometimes 50,000, 100,000. Then you look at, sometimes, you know, their monthly costs for these systems can be 100k plus. Then you usually sign, you know, long, long three year contracts. Yeah, but because with AI and all the like in the beginning when you onboard it, like some people say, some, there's some tools that say yeah, just onboard today. But we don't like to do that because we want the system to learn what your business is. So like a foot locker might need to look at their forecasting tools based on, you know, sales. Right. They want to make sure that right people and at the same time they don't want to have 100 salespeople, you know, sitting around waiting for one. They might want to, they might have that exact calculation where they will expect, you know, 5,000, 5,000 or $10,000 in sales. So we want system to learn that. So we should onboard them. We should say up to two weeks we can have the system live, but we want to onboard them so it's correct. So once we're done with the onboarding stage, all the inputs are in unless they want to add something or they have a new Recommendation or we have an update for them and we tell them, you know, what plug and play and we want it to be. Well, what I hope all future, you know, because of the. Because make it like it can be anyone. So you have it per, per user. So if you have a company of 50, 20 or 10, you could still afford it. You don't have that 50,000, 100,000 bill. You just have to pay per user. Like.
- [20:25]
B
Yeah. So, you know, in that example that you gave of the, you know, as someone who writes the paychecks for their team, I think about this stuff, the cleaning scenario, that $1.6 million in efficient capital allocation, most of that will probably hit the profit margin, correct? Yeah. So that's huge considering, I mean, especially considering I know what you charge. It's not that much. Yeah, it's like huge ROI for intelligent workforce planning here.
- [20:58]
A
And I've, and I remember like I worked in a company once and it shocked me because they were like, oh yeah, yeah, just hire more people. You know, fix the problem. But they don't realize that especially if you look at an airline outside of fuel, the second biggest cost is manpower. Right.
- [21:13]
B
Yeah.
- [21:13]
A
So if you just, you know, if you're, you can't have a rounding area in an airline because it's pilots, you know, they, there's a lot of wages because if you look at like you have what. Especially when I was in the Middle east, you have a triple seven you have on one flight, sometimes you have maybe 10 cabin crew and two pilots. So you have to always get that, that fine, fine spot.
- [21:34]
B
Yeah. So what about some of the larger businesses? I mean, obviously those numbers probably map out for bigger enterprise. Do you have any examples of what that would look like for maybe some nationally known brands?
- [21:46]
A
Oh, yeah. So if you look at companies that are over, they'll, they'll save in much. A lot more than this. You can, you know, times it depends on how much employees they have. But a lot of the things also is that the bigger companies, what they also a lot of the questions we get from them is. But you know, I have all of these. Like, you know, I have my, I use my. I use a HR payroll system with this or I use this one for that. So the good thing also that really matters is a lot of the questions they ask is more about integration because they want it to go. They want it straight from the system into their payroll. Or we have an option for like a timesheet. So clock in, clock out. Yeah. A lot of the options ask today we already have this function. So we tell them, no problem, you just add yours into our system. So the plugin. Mostly the plugin. But the thing is, like we're saying as we're growing, we're trying to educate people more than. It's harder to. A lot of the times you'll see, like, some of the times, oh, no, no, we're okay what we have. But I'm telling them, like, we're trying to actually, you will save money. Like, just give us a pilot program, for example, keep your system running. We work with our system and see like in the exact same amount of work, how much less people you needed to do it. Right. And yeah, it's, it's. Yeah, it's been. It's the educational part is what we're trying to get to.
- [23:04]
B
So, you know, I'm thinking about some, some of our clients that I already mentioned I want to refer you to, like, what is the onboarding or the ramp up before somebody would actually start to see benefit? Like, oh, this is where. Oh, this is helping.
- [23:16]
A
We always say give it two to three months. And I'm only saying that because you could see it from the first month. But the thing is, we want the system to learn your system's design, how it works. Some companies might have it a little bit more strict, Right. They might have a bidding system. So whether the system sees things that are fair, it might not work against their. Like, if you look a lot of like metro drivers or like even airlines, if you've been there longer, you're going to get the best schedule that you want. Right. So there's not a lot I can do there. But it can also, like, it can help you in other things. So the system will have to learn. It needs a few months, let's say a month or two to learn your company's, you know, the way of. The way of. The way of business. Yeah, yeah, exactly. And then after that we can say, like, by the third month, we. That's why we always like to say, you know what, try it for two months, try for three months. Then we work closely with them and we just want to show them, okay, here's what we got. What do you think? And all. Most of the time, they're happy with it.
- [24:15]
B
So, you know, we're working again, when we're working with clients, we target kind of the knowledge workers. And HR is certainly part of that, that knowledge work. Some of the companies that we work with, they're in states like California where the labor laws are very extensive.
- [24:30]
A
Yes.
- [24:31]
B
How does somebody Accommodate those like statutory requirements into the scheduling tool like this.
- [24:39]
A
So the cool thing is before and the systems I've used in the past, they were like very like you had to actually go and put like a rule, right? Rule set. It cannot work more than many hours or it's overtime. And everyone was different. Like if you came on contract or you came on that contract. The good thing is what we created, what's really helpful is we have a drag and drop. So you can take the California labor law, drag all of the documents, put it into, into like a attachment into the system, take all the company rules, put it into that system.
- [25:13]
B
Wow.
- [25:14]
A
If there's like five different contract types, like you're, you came in 2002, you have one contract, another contract, we will just put the whole contract, all the contracts into the system. But then when it came to your personal profile, we'll have an option saying contact RT1 and I'm contract RT. The system will automatically read your file based on what, what documents have been uploaded. And you won't be able to get like if you had a different overtime pay, your pay will be different. So this, this is the one thing I really pushed because I knew how I used to hate it when I was in scheduling. And I would have to put everyone individually, okay. All different, all the rule sets, okay. This guy can fly this many hours. Put a max, put a min, put this, put that. I was like, I just wish we could just categorize everyone by okay, he's RT his, he's by this contract, this contract. So we have a draft of options. So any company that joins us, everyone's going to be different, right? Like whether there is like a provincial or state or government labor law, sometimes the companies go above and beyond. So the, you know, the United States or let's say the California state, they say you can work a maximum of 200 hours a month. Right. But the company cares for the well being. They might say we need 160 as a company rule. However, with approval or if need be, we can go up to 200. So you want to put both and you can just put like a simple override for one. When push comes to sub and you want to, you don't want to cancel the shift. So we're testing it. So this is what we're trying to make it just a drag and drop and let the system.
- [26:41]
B
This is interesting.
- [26:42]
A
Yeah, go ahead. Yeah. One thing why, why we introduced this drag and drop is we created this thing called the Smart AI Assistant. So this is exactly why I Did this personally for me because I knew trouble I got. What happens is you can talk to the smart assistant. So what happens is right now I don't want to go and pull up like 10 reports or pull up a report. I just want a quick, Someone's asked me a question. I just go to the smart assistant. How much sickness did we have last month? We'll say, okay, you had, you know, 54 people sick last month. Okay. Out of all the total duties that we had last month, all shifts, what's the percentage? So you can talk to it and it can. Or if you want to know, like, what's the entitlement for leave?
- [27:27]
B
Yeah.
- [27:27]
A
So this from an admin side, from an employee side, it's even a little. A lot cooler. Well, there's one thing we have now, one thing we're working on. They can talk to it like this. Like, hey, can you report me sick for tomorrow's duty? It will come back. Okay, confirming the duty on the 20 on the 1st of November. They'll say, say, yes. Another thing is, hey, I have. How many vacation days do I have left for the remaining of the year? They'll say, hey, you have four vacation days. Okay. Yeah. So you just talk to it. And what we're trying to do, actually, I don't know how big, because I know WhatsApp is getting bigger and bigger. It's bigger around the world. It's not in North America, people use iMessage. We're trying to make it so you can just have a smart, smart AI assistant as an API into your WhatsApp. So you can just send voice notes. That's the plan, to make it as simple as possible. Because one thing I noticed is when you don't give people control, and this is the problem I've seen in the past where the company would say, you have to fly the schedule. I have, you know, my daughter's play, or I have this. They don't give you that option. They just say, you know what, you know, tough love. And the problem is, I don't blame them. Sometimes you have one manager or shift manager, let's say, for a hospital, and you're managing 50 nurses, you can't take everyone's requests. You know, you can try your best, but unfortunately, a lot of times it's rejected. Not because of that the system can't do it or they don't have availability, but more because the manager himself doesn't have time to go through all of these requests. So what we're trying to do is we're going to try to give it two options where swap requests can be done between the two. And if they still want a manager's approval, they can have that. Because sometimes the manager wants to know and set parameters like, we don't. In all swaps, you can't go into overtime and you can't go below X amount because if you go below, like, you can swap all your shifts, get the company benefits and work zero hours. Right? Yeah, yeah. So that's what we work with. That's why the onboarding, we want to get as much details as possible. So once we leave it, the system and them can just play around with it.
- [29:26]
B
You know, this has been very enlightening to me because earlier, you know, I think in my early 20s, I managed a restaurant. Everybody's flaky in a restaurant, right. And I remember this, this was like a constant conversation every single day. There was some sort of juggling of the calendar, right. And that was with, I don't know, 20 waiters across two or three ships. Not a big deal. And kind of how I look at businesses, it's, it's a million tiny actions that have to occur, right? Like, yeah, oh, I got the email. Well, if I get distracted and don't, don't open the email, you know, we've just delayed the, the deliverable being produced, right?
- [30:03]
A
Yeah.
- [30:03]
B
Oh, and then I've got it. Oh, but I need to send it to this person. And then there's a, you know, friction there because they're not at their desk right now. It's going to be another 20 minutes before they see the email. All of these steps, what you've just described, right? There is an infinite amount of these. Okay, I gotta, I gotta be there to take the call if I'm in HR or whatever. I have to. Okay, hold on, let me, let me find the time to be able to go and look at the schedule. Oh, now let me reach out to a couple of people who I think can handle this kind of stuff. It just becomes like, I get it now. I get why some of These companies leveraging AIs, particularly in HR, they're right. Sizing, they're, they just don't need as many people anymore to be able to give faster and more accurate workforce scheduling or shifting the, the, the, you know, the staffing issues out and all this kind of stuff. So I, I love doing this podcast because I get exposed to all these different areas that I don't even have any perspective or foundation in. Now, airlines, obvious, we got hundreds of thousands of employees healthcare obvious. It's 24 7. It's got to be covered like it's, it's life or death, literally. How big of a company do I need to be to be able to benefit from some, from AI enabled supporting the, the staffing and the, the requests off and all that kind of stuff?
- [31:28]
A
I would say again, it's a bit of a, it's a low number, but I would say 30 plus. I would say, and I'll only say that because in companies that have 30 or less employees, they don't have like a shift scheduler or any of that. They have the general manager, the store manager. If it's a retail store or department store, what I always say is let the manager manage, right? Don't let him caught up with the, with the inside, oh, can I request a swap or not? So he can look at actual strategies that will benefit the company. You know, look at ways to make the company money. Because at the end of the day, employees are an expense. It's not, they're not, they're actually, they're wasting their time on something that actually is an expense, right. Rather than looking at strategies to move forward. So like for example, a retail store, right, Might have, you know, 20, 25 people, right? But if they get their seasonal seasonalities correct with this, have their base and then have the seasons correct, they can. Because, you know, back to school, let's say like a small retail shopping, let's say Aldo. A small, not a. They'll. They have the back to school, they have Christmas, they have Black Friday. They have all of these things that they want to be well prepared. So the system can automatically let them know three months, four months in advance. Hey, last couple of years you had an uptick in sales here. Start recruiting these part timers from now, you know, so they will benefit from time saved there. They'll benefit from the day to day, hey, I'm sick, I can't make it to work. Our end goal, and this is what we're putting a lot of time into is, and it's a lot harder than I thought. So we want to automate even that part of it. So at this moment, if someone calls sick, someone can pick up the schedule. But we want to make it where if I was to call sick for tomorrow, we wanted to ping everyone who's legal and available on my category. So you can't have like a cashier, you know, end up doing sales, everyone who's legal, thinking like, like when you book an Uber, the Uber pings the closest drivers and they accept it, right? Love it. Our goal is. So when I call tomorrow, you might just get a thing. Hey, would you like to take this overtime shift tomorrow? And you'll say, oh, you know what, I'm not doing anything. Accept. And that's it. And just a notification will go to the manager. Shift was called in sick.
- [33:39]
B
Sh.
- [33:39]
A
Shift covered. Because the manager needs to know, come up and just I thought, well, you know, at the end of the day also for appreciation when someone comes in to help or from an off day, they just need to keep these and track. And again, one thing I also say is from everything I've saw in scheduling, the biggest, one of the biggest turnovers is that they have no control over their life. Right. And unfortunately I was one of the guys who always used to say, I can't, I'm sorry, no, talk to your manager, come back to me. But at the end of the day, if the company's making money, not giving overtime, I'm meeting my minimum hours. Do you really care what goes on over here? Yeah, I should be able to swap my shift four hours, you know, before. Three hours before. If I know, like obviously once I hand over my shift to you and you accept it now you're responsible so you can't be late or anything.
- [34:23]
B
Yeah.
- [34:24]
A
Let the managers manage. Let the employees, you know, enjoy their life. And there's something new that I actually wrote an article about and something that. Not now, it could be in the future when there's more AI and more freedom in the workplace. Some. Why don't you introduce something like micro shifts, right? Like say you have a 12 hour shift tomorrow. I have a 12 hour shift, like four days down. Something came up. You're at a party with friends and you want to stay longer. Right. What is it not stopping you from? That's why we need the right AI tools because it's very complex. Yeah, yeah, yeah. I can't just say, you know what, I want to go out, you know, have a couple of drinks with friends. I have a 6am, let me see if I can swap the first four so I can properly, you know, again, like I could say, you know what, take the first four. Here, take my first four. This is something that, it's a, it's an R D, let's say.
- [35:09]
B
But this is, yeah, I like it.
- [35:11]
A
My dream. Because this look, everything will be done through the AI all. You're the manager, everything's being covered. They're going to be happy. They're not gonna. If they know they have the freedom to. If to go to their child's play. To go to the, you know, the Blue Jays game like we have, you know, today. Yeah. No one's gonna quit or not. No one. But nutrition will not be. Because of.
- [35:33]
B
Which is very. Attrition's very expensive.
- [35:35]
A
Yeah.
- [35:36]
B
Yeah. So this has been really good for me because now I'm. I had no idea how much inefficiency is possible in this environment.
- [35:46]
A
Right.
- [35:48]
B
It's obvious. You know, once you start thinking about it, how much time, like somebody. I don't want that job where I'm getting all the calls and I can't make it in. Like, the amount of human energy required just to herd all the cats is huge. And what I like about what you're doing is that I could see at an airline, they've probably spent tens of millions of dollars building these things out for themselves. Yeah, I don't have tens of millions of dollars. And it's not as big of an issue for me.
- [36:18]
A
But.
- [36:18]
B
But if I ran, you know, a livery service or I ran, you know, a private clinic or something like that where, like, this was a big issue, this would be something that previously, before AI, I wouldn't have been able to afford the expertise. I wouldn't have been able to afford the software. But now with the introduction of AI and this concept of it's scanning the event calendar for the next 12 months. Like, I had no idea that the. I'm in Albuquerque today, that the balloon fiesta. Oh, yeah, I forgot about that.
- [36:52]
A
Right.
- [36:53]
B
But huge influx of people. So I could see this being extremely helpful for multiple industries. But what fascinated me the most was I don't have tens of millions of dollars, but I do have the fees that you guys charge. That really blew me away at the.
- [37:08]
A
The.
- [37:08]
B
The pricing that this becomes accessible to everybody. What does it cost? If I've got that, I've got 30. Let's say it's cleaners. I got a house cleaning service and I've got 30 cleaners. What is it going to cost me to introduce this level of technology into my small business?
- [37:26]
A
Yeah. So at the moment we have three tiers. Right. So we've got the basic one where people just want their schedules on a monthly basis. They want the staff to have access to their. To the application. There's a few things there, but like, for example, that one we're charging about $7 per, totally accessible. The other one where it's more advanced. So you get like the. I believe it was the AI forecast. You get some of the data analytics that we offer. This one, smart assistant. This one's about $10 per user. And there's the enterprise level, the enterprise level. This one we have to go into discussion. It's only because there's a lot more integrations when it comes to payroll. They have their own timesheets, their own. So with enterprise, we won't be looking more than like, maybe not more than double than that, but there's also a little more, A lot more. A lot more. Data set. Data set. So this is why enterprise, we, if you look at it, we haven't added a price.
- [38:29]
B
Yeah.
- [38:29]
A
And yeah, this is, we want it to be affordable for everybody. Again, like basically this is going to be your co pilot. You know there's a co pilot for everything, right. You know, AI, this is going to be your scheduling and planning co pilot. Because at the end of the day everyone doesn't, everyone wants to save time. And actually the ones who have the managers doing the schedules, they're going to save the most because they're not forget that day to day, you know, especially like you said, like a restaurant, right. You're mostly firefighting with schedules. This guy calls sick, oh, I need three guys in the back or I need this. Right. But imagine you didn't have to worry about any of that and you can start looking at sales strategy. How can, how can we get more, you know, more people to our restaurants? Work with the marketing team and yeah, I love it.
- [39:10]
B
So I think for the listeners, a couple things A, now you understand if you're not doing this in your own business and the person that is, give them a pat on the back. This is a lot of work to, to make sure that your business is staffed and that you've got the right coverage regardless of if it's knowledge work, if it's labor, doesn't matter. Two, this was previously like you just had to pay somebody and they had to suck it up and just do the hard work to get this done. Huge pain in the neck. Probably not the most favorite part of their job. Now for as little as seven bucks a month, I've got, not only do I have, I'm giving that subject matter expert in my business a little relief. But I mean I've got the example that we saw earlier with the, the cleaning company, that's $1.6 million across, you know, a hundred not extremely high paid laborers. If you've got, you know, if you, especially if you're in knowledge work and this is a big issue for you, that could be way bigger than that. And all at the Cost of anywhere from seven to ten bucks a month. AI has now made this level of sophistication coming from an expert who's got a decade plus in the space at enterprise level. Like to be able to have that level of support for your, your scheduling, staffing and optimization of your workflow is. I mean, that's the promise of AI. So, Mohammed, where should people go? And honestly, any of you, if this sounds like a known issue in your business, I would encourage you to look at this. I haven't looked at a lot of tools, but this certainly sounds like a solution for it. Where should they go to find out more? To maybe sign up for one of those pilots or just enroll as a client?
- [40:43]
A
Yeah, yeah, for sure. So SmartWorkforce IO over there, they can click that, you know, they can go talk to us over there. We'll happily, you know, show them everything. At the moment we're also taking some pilot clients, so we will also show. We will work with you. You know, we want to see the results in the next, in a few months. So we're looking for some pilot clients as well. But the website is the easiest way if you want to, if they want to connect on LinkedIn, you can just find me. I'm the CEO of Smart Workforce. AI Mohammed a Yousef so m o h A M E D space A and then Y O u S U F Yep.
- [41:24]
B
And we'll add those links to the show notes. But you know, we talk about, on the show, we talk about how Companies are using LLMs to do all kinds of stuff. This is something that we've never covered before. And prior to this conversation, I didn't realize, you know, just because I'm not, I'm not, I don't do it. I didn't realize how much of a like burden this is on the staff that has to manage it. And I honestly, I didn't realize how much of an impact that optimization supported by AI could have on your bottom line. So fantastic. And this is universal. I've got so many ideas and, and actually so many clients that I think should probably be talking to you. So I'll be sending some introductions to some emails. So Muhammad, thank you so much. I know that this has been an episode that's been in the works for a while and I'm glad we finally got to do it. And fantastic. I don't have a dog in the fight, so I'll go ahead and say go Jays. Yeah, this could be big for Toronto for sure.
- [42:17]
A
So, yep, good luck. Tonight on the game, the last three championships that we've won, as in Toronto in general. So whether it be the Raptors or the Blue Jays, we've always won on Game six. So today is Game six and we had the chance to clinch it. So let's go.
- [42:30]
B
Go. I'll be thinking about you guys then. All right, buddy. Thank you so much for being on the show and everybody, thank you so much for listening to it. We'll have a new episode for you next week on how others are using AI at work. Thanks for tuning in to Using AI at Work. Don't forget to subscribe for more conversations about how to use AI at work and a special thank you to our sponsor, Chief AI Officer for empowering businesses with AI education and training. This Visit their website for a free AI readiness assessment and AI strategy guide to help you get started using AI at work. That's www.chiefaiofficer.com. follow us on Twitter at the handle usingaiatwork and visit www.usingaiatwork.com for free resources to help you harness AI in your role.