S4 | E2 | AI for Frontline Workers with Arjun Vora – Co-Founder @ Teambridge

Welcome to the Think Data podcast brought to you in partnership with Mydataworks. If you want to stay up to date with the latest breakthroughs and trends in the world of data and artificial intelligence, and if you're curious about some of the strategies that companies and founders use to launch data and AI products, then you're in the right place. Our aim is to bring together a diverse lineup of fantastic guests from the founders, through to accomplished leaders and product owners at some of the most fascinating data and AI companies worldwide. They will each offer you their own unique insight into what it takes to launch and scale a great data business. Thanks for tuning in and I hope you enjoy the episode. Welcome to the Think Data podcast and today I'm really excited to be joined by Arjun Vora. Here's the... the co-founder of Teambridge and they are a series B startup that's redefining frontline workforce management. Arjun has a super interesting background which we're going to obviously dig on in due course but Teambridge really helps businesses run smoother and smarter operations by giving those teams a single hub for scheduling, communication and real-time insights. They've got a really clear vision it's really to make managing people easier and make work better for the people that are doing it. So yeah, really good to have you on. And when was that light bulb moment to kind of setting up Team Bridge?

If you think about it, like if you take a step back and like you look at the workforce of the world, 60% of the world's workforce is hourly. We got to remember that, right? Most of us, you know, are, you know, in our vicinity or the folks that we kind of communicate with are what do you call the desk workforce? You know, oftentimes known as the white collar workforce. But the majority is actually the hourly workforce that's on the ground running the world. These are, you know, think about the hospitality industry, right? You have the house housemaids and the you have the construction industry. You have construction workers, your foreman. You have food and beverage industries, bartenders, servers. You have hospitals. We have nurses. Right. You have janitors, plumbers. Right. That's the majority of the world's workforce. They are experienced day-to-day is lacking flexibility, reliability. They are shift-based hourly workers. You know, we are nine to five jobs oftentimes, most of the times, or at least we have predictable schedules, right? You know, when you're coming in on a Monday versus a Tuesday versus Wednesday, Thursday, you have a family, you know exactly when you can go pick up your family and so forth. Versus in this hourly workforce, it's not very predictable, right? you might need to come in tomorrow to fill in a shift because of, you know, peak demand at, you know, the nearest place that you work at. We saw this problem firsthand at Uber, right? You know, Uber was solving, if you think about it, you had two sides to Uber. You had the riders, but more importantly, you had, you know, the drivers who were working for, you know, driving their cars to pick up the rides that they were getting. And remember, 4 million people that eventually signed up to drive for Uber, won't? signing up to be taxi drivers. They were signing up mainly for the flexibility, for the agency, for the control over their own time, right? They could come in at any time, they could open up their Uber app, clock in and start working. And that's why they drove for Uber, right? It was less about the money. In fact, oftentimes they made less money every year, you know, as Uber tightened the screws towards profitability. But they got that, you know, they had more control over their schedules. So, you know, me and my co-founder, as we kind of... spent about five years at Uber each, we realized that what we've built at Uber primarily was this phenomenal driver product, right? When they could come in, they could download the app, they could onboard onto it, they could clock in, and at the end of their shift, they could get paid, right? So that was the real magic of Uber. It isn't the rider app that we use to request the Uber. That's actually a pretty simple app, right? You put in a destination, you choose what Uber you want, you spend about... 10 seconds on it. And then you put your phone in your purse or pocket. But the drivers were spending four, six, eight hours a day on the driver app. And if you take a step back, it's a workforce management app for an hourly workforce, right? So that was the light bulb moment. We were like, hey, there are all these other businesses that have a massive hourly workforce. It's 60% of the world's workforce. How do we give them a platform where they can... uberify their business where they can provide that agency that you know self-service experience you know that reliability the ability to come in and pick up shifts that you know suit their personal needs And then eventually, you know, have a much better life than they are having today.

I love it. Yeah, it's so interesting that you're kind of, let's be honest, Uber back then, we've been Uber now to a certain degree, was so ahead of its time when obviously that kind of gig economy and then all of a sudden, I know we've only used it, well, certainly me on the booking a driver, but actually speaking to drivers and just having that flexibility to that gig economy and actually you centralizing that so they had full control over there. their life that that's huge and i i'm really interested because when you're at uber was it the product was it the team was it just what made uber so good you know in silicon valley we are building software mostly for each other right

if you think about it you know you look at the you know the big massive companies out here you're building software to improve the lives of the white collar sales people marketing people engineers, finance folks, wonderful companies now helping lawyers, you know, help automate a lot of the work. The way you think about it is like you solve problems that are in front of you, right? So if I'm an engineer, I'm trying to write code every day. I'm like, hey, you know what, I could maybe build a better ID, a better coding environment. And, you know, if I'm a salesperson, I'm like, hey, you know, maybe I could do something that's on the cloud, more automated with, you know, AI sending out, you know, my lead generation email. So you're solving you problems that you face day to day or people around you face. And hence, Silicon Valley has consistently helped improve the life of the already privileged folks, right? Uber was one of them where they set out to improve, you know, the lives using technology of the blue collar worker of the hour. So I don't think it was necessarily anything special that Uber did, you know, in its product management. It just... focused, you know, which has been very rare in Silicon Valley, on a demographic that technology has predominantly forgotten.

Do you know what, I've been in tech for a long time, and I never thought of it that way. So in your opinion, then, why have frontline workers been kind of forgotten for so long? Talking about like healthcare, the nursing, you know, anyone on that kind of hourly rate, why do you think it's taken so long?

I don't think it's an intentional or nefarious reason why. It's just that it's not a problem that's in front of us. So we... don't think about solving it. It's kind of this, you know, vicious loop. And look, the thing that you realize with what these businesses end up doing is they believe, you know, we interviewed, you know, we have hundreds of thousands of hourly workers on our platform, right? We do surveys and we interview them and we learn from them about their problems, about what they're going through. Only 29% of the people that we surveyed are going to continue. to work for their current employer in the next year. That's a fairly low number, right?

So 71% are going to leave. They're going to leave. Wow.

And businesses often feel that either I win or my blue collar employee wins. I have to choose between one of them. And, you know, they feel they can solve retention with perks and pay. Like that's the two options that I have, right? But that's not why you actually lose people. You know, when we, again, When we survey them, you're going to lose them because of unpredictable schedules, inconsistent policies, right? Slow processes. That's why, you know, you're losing people.

So,

you know, when you bring in technology that helps fix that, that's where you are actually benefiting the worker, right? And that's exactly what Uber did.

So let's talk about the solution because obviously AI is front and center of a lot of companies now. but in terms of the product, So talk me through a typical use case of, you know, I'm a worker working for said sector. How does that work both in terms of me as the employee, but also, you know, be the actual employer? How does it work?

So look, I'll give you a real world example. It'll be easy to explain. One of the biggest football teams, American football teams in, you know, the Silicon Valley is on Team Bridge. They used to manage their entire stadium with... pretty old school technology. And, you know, when you have old school technology that doesn't work, you invariably end up relying on Excel and email and phone calls and text messages. Now in a stadium, you have parking associates to help make sure the fan experience while parking is, you know, great and precise. You have janitors, you have security people, you have folks on the concession stands, you have guest services, ticketing, right? So you have... all these different roles that you need to make sure are well-staffed, they're trained, and they are performing efficiently on game day. Now, in the absence of strong technology, They were sending out emails and texting these folks, making sure they have 1,500 people on game day ready to service the fans. The company used to oftentimes send Ubers and buses to different neighborhoods trying to get staff in and make sure on game day. They didn't even know, Alex, 30 minutes before game day, how many people are actually going to show up to work.

Wow.

Right? Now you think about what if you Uberified that? What if anybody who wants to work at that particular stadium can just download that app, onboard themselves, put in their documents? Now, what is that doing? That's improving processes and making things faster for the worker. The worker doesn't want to go in and fax something and download it and print it out and sign it. They all, most of them, about 98% have smartphones in their pockets and purses. They go in, they open it, they complete their entire onboarding. There was a time, Alex, where you even start doing vehicle inspection on the phone, right? It's like, hey, you know, I need something that requires my vehicle. I'm going to inspect my vehicle on the phone. Everything's good to go. You're making their lives easier. You're making their ability to get a new job so much faster, right? On the other hand, for the manager, you're reducing the time to fill a shift, right? So we reduce time to fill a shift by 40 to 50% because these folks, they're tech savvy now. Most of the people getting into the workforce now are Gen Zs and millennials. Of course,

yeah.

They are using Snapchat, Instagram, WhatsApp. They're using all these beautiful apps outside of work. In fact, their work app should be the best designed app because that's what they're using to put food on the table for their families. So now these businesses are able to give their workers that. They're able to make sure they have a qualified workforce. Their training happens on the app. Now they can put in their time preferences on the app. Hey, you know what? I need to tell the business through the app, I need to pick up my daughter every weekday from 4 to 6 p.m. And I need to go there. And now automatically using AI matching, the right shifts get sent out to the right people based on what the preferences are, based on who's close by, based on, you know, what training modules they've completed. And as you complete more, as you perform better, there is upward mobility, right? Because you're like, hey, Alex, congratulations, you've completed. 10 games you've showed up on time you completed all the tasks in the right manner now you know what you are now a gold employee now you're going to get three dollars more on your shift for our employee management system as well it's starting to kind of help those organizations get a better workforce you you're it's a win-win right that's what i'm saying businesses today in the absence of technology think only one side can win right but it's actually If you have the right technology, you can make it a win-win for businesses and the employee. The employee gets upward mobility. Think about it, Alex. If you do a really good job as a salesperson, you can get promoted to a director of sales. One day you can become the CRO of the company, maybe even CEO, right? If a plumber does very well at their job, they don't become VP of plumbing, right? They don't become a senior plumber. So, you know, these technologies also allow you to disseminate consistent policies. and then provide that upward mobility.

Yeah, it's really fascinating. Actually, the more you think about it, I think actually that example you gave, I think maybe it was on your website, because when I looked at some of the case studies and some of the references, it is really intelligent, and obviously it just makes sense. Obviously, it sounds great. You know, it's evidently needed. Companies are obviously benefiting, but it's obviously not been that easy, right? Kind of getting to this point. So talk to me about some of those. maybe it's early stage or it could be even recent in terms of some of those challenges of actually getting that product, getting that messaging to market and getting product market fit. Talk to me about that because that's where a lot of companies, even though they get good investment, actually sometimes they fall short because they just can't scale.

Yeah. Look, I think one of the interesting learnings for our team and we kind of embedded one of our cultural values right from the hiring process. And one of them is... There just needs to be a strong passion or we look for a background or a family story or a childhood story, something around their passion for the hourly worker. You know, we have folks who have worked in ticketing at stadiums at a blue collar job for many years, and now they're on the sales team at Team Bridge. You have someone whose family member came from, they came from humble beginnings. and they've seen their mom or dad be a nurse and have had to go through the unpredictable schedules of mom having to leave at 8 p.m. in the night to fill in a last minute shift and not being there until next morning, right? So you look for... people who have that innate passion. And the reason is every step in the way dealing with a blue collar workforce customer is very different than dealing with a very tech savvy, you know, white collar business. And I'll tell you some examples, like when you're talking about sales, for example, in, you know, when I used to work at Uber and before Uber has to work at Salesforce, Salesforce was oftentimes selling mostly into, you know. established businesses that have, you know, very tech savvy workforce. In our world, when I am selling the product, I can't use fancy tech jargon. You know, oftentimes, you know, if I get too heavy on trying to sell AI, you're going to put off, you know, the manager of janitorial at a particular stadium, right? Because, you know, the more fancy you get, with your lingo, the more you're going to scare them away. Yeah,

it's going to alienate them, isn't it? It's kind of the adverse effect.

It has the adverse effect, right? And you have to talk about value. You have to understand their day-to-day. You know, I'll give you another example that as it relates to sales. I, you know, we have a lot of folks on our sales team. They've closed million dollar deals on Zoom calls, right? Because sometimes when you're selling to, let's say a tech team. The CTO is your buyer. They are not very social people. Oftentimes they're like, hey, you know what? I can close a million dollar deal on a Zoom call and it's great. The blue collar workforce is very different. They're very people, people. Think about it. They are, you know, on the front lines. Now we realize how important the hourly workforce is during COVID. The world stops running, right? Because they are the ones who are actually interfacing with people. And they are people, people. So we, you know, for even small deals, any deal about 20, 30K. We send the salesperson on site. They're very trust-based people, right? They want to shake your hand, right? They want to be like, hey, you know what? They want to cheers that beer with you before signing the deal, right? Because they're instilling a lot of faith and trust in you because they're oftentimes first-time buyer of technology. They've never bought tech before oftentimes. So you kind of have to guide them through the process. The same thing happens with customer support, similar kind of story. Because on customer support, you're dealing with the workers themselves. And they don't understand sometimes, you know, the basics of technology. The product is affected as well because you need to build extremely simple solutions. You can't build something overly complicated and expect, you know, a blue collar workforce to understand it. So I think in like every aspect of your functioning of the company, you have to think through things from the lens of that blue collar worker.

Yeah, it's a refreshing approach, actually, because you're right. I think people overlook that. I think in this day and age, people don't want more face time anyway. And I think you'll... point on blue collar workers is really valid. I think that's probably even more so, but I, is that you can actually differentiate yourselves by actually putting those people in front of them and actually having that face time. And from a sales and go to market motion, then are you targeting specific States in the United States or are you really across the whole of the US?

Yeah. So the way we target is we are going one industry after another.

Okay.

So the States themselves, you know, doesn't matter that much. What matters more is you speak their language and in order to speak their language you need to understand that industry in and out right so if i'm going after events and stadiums i need to now make sure i understand the problems that stadiums have running a massive workforce across the different functions they don't they don't have oftentimes a full-time workforce because certain stadiums have about 50 events a year so you have to restaff for every game Because you can't keep them on a full-time payroll. So once you understand the nuances of an industry, you can speak the language, you can make sure your product is tailor-made for them, you can make sure your value that you're delivering is tailor-made for them, you have case studies ready, if you have references, I can make one stadium owner talk to another stadium owner that's already on Team Bridge. So when we focus, it's industry by industry by industry.

Very interesting. And what's the best bit of feedback you've had about the product? whether that's from someone who's being paid through it or someone who's kind of managing it to manage their workforce. What's the kind of one bit of feedback that stands out for you?

Yeah, so look, I think one bit of feedback, and we took it to heart from the, it was from one of the supervisors at one of our businesses. We were in this business that had multiple types of workers, right? And, you know, if you go back to the events and stadiums, you know, like I said, you have janitor, you have the... You have the security person, you have the parking person, you have the guest services person. Each of them have very different roles that they have to play, right? If you look at hospitality, it's very, you know, front desk receptionist, you have the housekeeper. You know, you have, you know, the person who's the technician on hand. They have different roles. How can you make sure your product is composable in a manner where if Alex, the janitor, opens up the app and Arjun, the security guy, opens up the app, the app is very tailored to each of their use cases so that you're not overwhelming them with. things that don't apply to them, right? Because these folks, again, like I said, are not often super tech savvy. So you want to make sure your experience that you're delivering to that worker is tailor-made to them. And if it's tailor-made to them, it can be very focused and simple. Hey, Alex, yours is, by the way, the next, you know, restroom that you need to clean. And here are the eight tasks that you need to check off once you've cleaned it. And then there's a picture that you need to upload in the end versus for arjun hey arjun if there is a security incident please click this button and we will automatically send a notification you know to the head of security letting them know an incident happened and let me know what type of incident it was right so you have very different tailored experiences for each of the worker types so that was like one of one of very very interesting pieces of feedback you know tito and me received very early on in our team bridge days and the way we incorporated it is we brought in a lot of composability into the product where Depending on what your business needs are and what your workers are supposed to do, each worker type sees an experience that's very tailor-made for them.

It's like continuous reiterations of the product and that continuous product, that open feedback loop, isn't it? I'm guessing of all that feedback you're getting, all that data, it can just lead to more product ideas and the product just takes on its own kind of form, I'm guessing. So how do you prioritize what product? product enhancements to put into the roadmap versus the ones that sounds like a great idea? Do you take it back on how many people have requested a certain change to a feature or is it is it more formed the part of a wider product roadmap?

Look when you're building product you're I think your product ideas usually fall in one of three buckets. One is hey it's a big bet that the company wants to take or it's it's it's the future of the world that the company wants to see. It's not any feedback from anyone. It's just that we believe the future of blue collar workforce should go in this direction. And hence, we are putting that into the app, into the product. So that's one. It's very usually coming from the company, oftentimes coming from the founders themselves. It's the future that they want to unlock for the world. Another bucket is your existing customers, you know, clamoring on the door, asking you to build something. Otherwise, they will leave you. It's like, hey, I need to build this. Otherwise, you know, these big customers of ours will churn. It's a problem that the customers are facing on the ground. And then a third bucket is what your sales team is telling you to help unlock new business.

The reason they're not landing something is because something's missing and they're feeling that.

They're not landing. Either a competitor has it or they want to break into a new industry. And they're like, hey, you know, this particular industry requires. So, you know, you're... The product ideas usually fall into one of these three buckets. When you're, by the way, building a new company, you're mostly doing bucket number one, right? You have no customers, you have no sales. It's basically a future direction that the founders have, you know, one-to-one rock for the world and they do a lot of number one, right? When companies usually, you know, get too complacent and, you know, run out of, you know, like the Kodak moment that you have is when you're doing too much of number two. You're just building for your existing customers. And then, you know, someone comes in and completely disrupts you, right? So we are very like focused on trying to make sure there is the right balance depending on what stage of the company you are in. So that's a kind of, you know, higher level outlook at what we build. But then in the end, you're building for two sides. You're building for the managers and the admins and the businesses and unlocking new levels of efficiencies for them with AI, with automations. But then you're also building to help improve the life of that hourly worker. Sometimes what you build is beneficial to both, right? So I'll give you an example of something that we built that was beneficial to both. When you look at payroll, right? Most of us get paid either weekly or bi-weekly, right? And, you know, there are all these massive companies like ADP and others that have been built around, you know, the weekly, bi-weekly payroll that, you know, workers expect. Now, think about it. We are... you know, again, on the white collar worker, the rest workforce, we know how much we're going to be making at the end of the week, usually, right? Because, you know, you have a fixed salary and you're making that amount. That means you can plan your finances, right? We don't realize how privileged we are that we can plan our finances because our pay is fixed. We also, most of the time, don't live paycheck to paycheck, right? You know, the desk, white collar workforce is financially more healthy and stable. The blue collar worker, the hourly worker, if you think about it, it's kind of the opposite. They don't even know how much they're going to make at the end of the week because it will depend on the hours that they get. One week you might get 30 hours, the next week you might only get 10 hours. Imagine living in a world where you don't know how much you're going to make at the end of the week. Imagine worrying about your bills, your utilities, your school fees, right? Number two, they oftentimes lift paycheck to paycheck. So if they have, you know, if my daughter's birthday is on Sunday, I don't even know how much I can budget for that gift, let alone I can't even get that gift until my paycheck comes in. So one feature that we built was... hey, let's rethink how these workers should get paid, right? When they clock out of their shift, why can't they instantly get paid? Why do they have to wait until the end of the week? Because this is already wages they've earned. So we built instant pay at Team Bridge. And now that increased the finance, improved the financial health of the workers. And we surveyed them. You know what they were cashing out money for? They were at the gas station and their credit card got declined. You know, they had an unexpected utility or medical bill that came in. They were at the grocery store and, you know, they bought a few more items than they expected to buy. And they just went into the TeamBridge app, cashed out their earnings from that day and were able to pay those. Now, the benefit for the business is their workers now stay with them longer. Their workers are happy.

They feel loyal, don't they? They feel like they're looked after.

So this is an example of something that you would never think about building for the white collar worker, right? Because they don't have those problems. You built it for this, but you're benefiting, again, because of technology. Here's a scenario where it's a win-win.

Yeah. And it goes back to your point right at the beginning where you're here to kind of really invest the efforts to make this frontline worker economy better, more stable. And actually, it ties nicely into that. My final question for you, obviously, with regards to... AI specifically, what do you think in your opinion, whether it's TeamBridge specifically or across the sector, what do you think is the biggest opportunity for AI in this space? I know you touched on that really nice point about kind of cashing out pay, you know, and actually these are reiterations of the product, but AI specifically, what do you think can make this space better?

Yeah, great question. So look, AI is great when you have large volumes of data. And you have large volume of players. So, you know, you see AI being really beneficial in an industry or in a use case like customer support, right? You know, you have, you know, these companies doing very well because, you know, customer support for these big companies, they have thousands of tickets coming in every day. That means you're able to learn about, you know, what's working, you know, an interaction and you're able to automate the interactions using agents. Right. Now think about this, right? In an hourly workforce business, there are a large number of workers. And this is not, again, in a white collar world. You know, if you are the head of sales, you sometimes have, you know, what, 8, 10, 15 people reporting into you who are the VPs. Then the VPs have, you know, maybe 10, 15 people reporting into them who are directors. So you usually have about a 10 person team directly reporting into you. In a blue collar workforce, the head of parking at Levi's Stadium has 600 people. that they need to manage, right? So you have a large workforce. So the employee-to-manager ratio is very high. And that's where AI really comes in well. So I'll give you an example. If you have a last-minute cancellation at a hospital of a nurse, she's an RN, registered nurse in the ER department, extremely important role, right? They need somebody at 7 p.m. The person who was supposed to show up at 7 p.m. last minute had a flat. tire or their kid got sick. Something happened, right? That was real. And they can't show up now. What do you do, right? Because you have so many other nurses that might be the right fit for this. You don't know who's nearby. You don't know who's credentialed, who's nursing license is valid right now. Today, it was a manual task. And because it was manual, you sometimes can't even find that replacement. Who suffers? The patient suffers in the end. AI can do this really well because AI knows all the policies. TeamBridge policies behind the scenes that that particular account has set up. That I need the last license valid. They need to be in California. They need to have, you know, so much work experience. They should have worked at that facility before in the last month, whatever it may be, right? And then is able to make calls to all the top people that they believe are the right folks who can fill in that last minute replacement. If it is an urgent shift, they're even, you know, a lot of our customers even codify the AI to allow it to add a bonus on that shift, right? So you think about it from the Uber perspective, you're surging it, you're surging it because there is, you know, lesser supply and higher demand, right? So the AI can do that and then make those calls now, right? The AI can even do that, and then find that replacement. So now the hospital is at lesser risk. For them, somebody canceled, TeamBridge AI, you know, took care of the cancellation, but also found the right replacement and that next nurse showed up.

Look, it's no surprise you guys have had the success. I think the backstory, the vision, that light bulb moment for me when I got the brief to have you on and actually looking into it, I thought this is fascinating, actually. I think we look at those, you referenced stadium a couple of times, but actually just all the use cases beyond that. It's just, it's a product that makes sense. So Arjun, it's been really interesting. Actually, I know your website's great and people can log on, check out some of the case studies. There is a reference to that football stadium on there. um but arjun yeah really super interesting and i i wish you and the team a huge success on this because it's a fascinating solution thanks appreciate alex look in the end what we're looking to do is we're looking to you know i told you the biggest problems the world faces right all we're looking to do is bridge that gap right

like you know as a founder you work very hard and my kid and she's like hey dad like why what do you do every day like why do you go to work like hey you know i'm looking to bridge that gap between the two demographics and And I really do believe technology can play a big part.

Yeah, and you're leading that. I think it's really interesting and huge, huge luck to you and the team anyway.

Appreciate it. Thanks, Alex. Pleasure.

Thank you.