Better place pravin
During their research, the duo realised that one of the major challenges was billing data about blue-collar workers. Providing workforce management solutions Pravin explains that the startup works to solve five problem categories. Firstly, it addresses the issue of sourcing and onboarding workers through its digital solution. The company facilitates the entire process using a mobile app without the need for any physical or manual intervention.
Now that I have hired the person, how do I increase productivity? So we created a bot-based mobile app. The bot takes care of upscaling the person based on their need. It could be learning something as simple as English words, to financial literacy, to how to manage your work, or learning something different that you would like to write. No employee wants to give some benefits to the individual like insurance, they can do it to us. Now, what was the challenge in giving these insurances of credit and all these things, there was no data.
So, if you have to give a credit, there is no credit underwriting algorithm, right? Because there is no data. Now, as we provide the solutions, we build a lot of data about individuals. And we use this data for the distribution of services. So, we partner with banks, we partner with insurance companies, we partner with health companies, and distribute services to the individual right.
Now, these services can also be distributed directly to the individual. So, this is done through a business. So, a company, for example, you can buy for your employees, but the individual can buy directly, as well, directly through the mobile app that we provide to the individual, right.
And so, we provide individuals a mobile app where they can build their profile, they can learn things they can apply for loan, credit insurance, and all the other components that we offer. What was the first hope that got you started? What was the first hook that you work with first? Siddhartha, you cannot do you cannot boil the ocean. Even now, while we talk about all the models, there are a lot of enhancements that we keep doing, we have a two years clear roadmap, what we will do, we looked at the lowest hanging opportunity, and the biggest problem.
So, we identified two biggest problem in this space. And the second problem was attendance and payroll, right? And it is not as simple as in white collar that we do any now. So, we decided to go with onboarding solution integrated with background verification. We continued doing that for three and a half years before bringing in a new module.
So, we continue doing that we want it to be master node that today, we are the largest in the country, when it comes to onboarding and background verification. And once we were clear, we had customer engagement and who then only we started picking up the next module. So, on the journey is still continue. So, while all the components I mentioned, there are things which we have basic version, there are a lot of enhancements happening.
Siddhartha Ahluwalia Can you tell us tell us about you know, your current metrics and milestones of the audio scanner understand the context? Pravin Agarwala Today, we work with roughly different customers in multiple different segments, out of which some of them are using our freemium model. So, we also provide some services, roughly half of them is using our paid model. We manage roughly 20 lakh people through our platform here on the right now to acquire our customers, right.
And, and they use different models. So not necessarily that every customer is using all the models. And we do revenue of roughly 10 million in ARR today. On the other hand, we also have job seekers on our platform, who are looking for a new job, we have roughly 1. So, number of customers revenue, number of people that we manage, and the services that we distribute to our division. These are the four key metrices that we measure.
Siddhartha Ahluwalia And can you share your fundraising journey like when was the time you raise your first round? And what happened? The subsequent rounds? What are the challenges in that journey? Pravin Agarwala So, let me start with the challenges right, blue collar is not a glamorous area it is not the sexiest area.
And when we started in , there were not many companies doing anything in the blue-collar space right. Today, fortunately, you see many more companies like Work India and Apna. And there are FinTech companies shubhloan, there are training companies and so on, but those days there was hardly anything. So, the challenge for us was educating the investors that there is a play while there is a purpose in our mind to impact the life of 15 crore people in the country.
But there is a business as well, right? So, we have to take our time educate people on how this business will run, because they have no role models, there is no company that can be say that, okay, it is how done in USA or China, and no reference in India itself. So, we were the first ones to come into this space. So that was the challenge.
But fortunately, in last year and a half, that is gone. We started out fundraise. So, we first we funded ourselves Both Saurav and I did the initial funding in the company, and we continued running it, we did our first institutional raise in with United capital and Lalitesh, Lalitesh is the guy who was head of Google India earlier and he is also known as the creator of Google Maps.
So, he brought in a lot of interest, and then Neeraj Arora also participated, Neeraj, who is the WhatsApp guy. So, they also helped us in building the company over time, we raised our series A in through 3one4, where all existing guys participated, and then we did our Series B last year, in October in during the pandemic time when everybody was hit with the business right there was job losses people were migrating back, especially in our segment, unfortunately, we could show growth and there was investment coming in and we have done an altogether roughly 17 million have raised so far.
Then we looked at the numbers that the companies are spending today that companies are spending roughly 20, rupees per person per year already spending. So, we are not asking for the new money this is the money being spent.
So, we went to the companies some of these companies as part of our research and said Why are you spending 20,, I will do this thing at , rupees or so right and you will save 10, rupees. Now we will look at 15 crore people. Right and the countries developed countries where the pricing point is very high, the margins could go up the gross margin, India is always a challenge compared to other countries.
In the beginning, we believe that if we can solve the problem here, at scale, we will be able to solve the problem in all the other places as well. But yeah, I mean, everybody asked this question and typically you have not seen in past that SAAS companies have built only for India, they have built in India for outside world right. And you will see many examples of but within India for India, very few.
So, the opportunity size per customer is pretty large, it is not a small opportunity, I mean, there are companies, I was surprised when I was doing my research and I never expected that, but this is what the situation is there are security companies with 10, employees and there are many of those right?
There are companies with 20,, employees, if you look at the New Age aggregators or delivery companies, they have , plus employees right, our food delivery company or ecommerce company or a cap company and the opportunity size become very, very large with them right. So, there is no dearth of opportunity in this space for sure. Siddhartha Ahluwalia And typically, how on the SAAS Company even valued like how in your journey, how are you valued by investors, whether it be on ARR or this current climate transfer or bull market, in spite of pandemic, how are companies and 10 mil ARR are building for India, for example, you valued in the market.
Pravin Agarwala So, in the early days, it is not by ARR because that is not the right parameter to look into. Right, that was more done based on the potential of the company. So, Seed Fund is completely based on potential you come up with a number. Is there real science behind it?
Honestly speaking, no, right? You just do it. Series A, you bring some science behind it. But still there is a potential by Series B onwards, you start looking at multiple SAAS multiple could vary depending on the margin, the gross margin and other things could vary between eight to If you have exponential growth, then it could go up to 15x as well, that depends on depends on your revenue, it depends on the gross margin and the growth, yearly growth. And the variation could be between eight to On average in the market that you will see where the companies are listed and so on.
On ARR, it will be around six to eight. So, anything between eight and above is a very good number to get as a multiple in a SaaS business. Pravin Agarwala No, there are no companies it depends on this.

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All the software that we used to develop earlier was designed towards the white collar, like the HRM and so on so forth. He explained that the idea was to help the crore people who are part of the blue-collar economy. During their research, the duo realised that one of the major challenges was billing data about blue-collar workers. Providing workforce management solutions Pravin explains that the startup works to solve five problem categories.
Firstly, it addresses the issue of sourcing and onboarding workers through its digital solution. The company facilitates the entire process using a mobile app without the need for any physical or manual intervention. Now that I have hired the person, how do I increase productivity? So we created a bot-based mobile app. However, they eventually realized the need for an enabler to bridge existing demand and supply gaps in the ecosystem, thus moving to a B2B SaaS business model and creating a digital platform to enable the entire value chain.
Welcome to the things entrepreneur podcast. Today I have with me, Pravin founder of BetterPlace. Welcome, Pravin to the podcast Pravin Agarwala Hey Siddhartha, thank you so much for having me such a pleasure to talk to you and your audience Siddhartha Ahluwalia Pravin, would like to know you know, your own background to start with which city you come from your family background and your professional journey till now.
Pravin Agarwala Sure. I belong to a place called Dibrugarh, which is in the northeast of India in Assam, which is very close to the China border actually, right. Born and brought up there. So, anything and everything around that product was my responsibility within the organization.
In , I quit SAP, took a break, and then did my market research and started with a place in And for last six years, enjoying the roller coaster ride with better place Siddhartha Ahluwalia So how did your idea of better place come to you? So, what are different ideas were you considering before narrowing it down Better Place.
Pravin Agarwala I was very clear that this is what I want to do. And the reason I quit my job is to do this. So why this idea came at all. He was the group CEO of the company, we used to talk about blue collar and the challenges they face with all different respects, right. So, there were challenges from the individual in terms of opportunities, jobs, access, living conditions, and so on, right.
And these were alien to us, right, as a white-collar employee, we always took it for granted. And all the software that we used to develop earlier were designed towards the white collar, like the HRM is the access to benefits and so on so forth. And we said that we need to do something around this space, right?
And then there was an Aadhar right to the identity, basic identity was solved with Aadhar principle, then we said, what is missing on top of Aadhaar is a score of that individual, right? If I go to a insurance company, I can show that data. If I go to a credit company, I can get a credit and so on so forth. We will talk about that as we go along. But the idea was that how can we help those crore people who are in the blue-collar economy, who do not have access to opportunities.
And while doing the research, we realize that the biggest challenge is billing the data about those individuals, right. So, what we do is that we provide a workforce management solution using that we build the data, and then we provide access as a platform to individuals to access various opportunities.
Siddhartha Ahluwalia Can you share in detail what are the different problems you solve with our workforce management solution? And also, how you solve it? So, we define workforce management solution from blue collar enterprise into five categories, right? The first problem is, how do you source and onboard an individual right? And attrition is very high. It is not scalable, right. And that challenge was actually becoming multi fold in the given situation of COVID and Corona, where people still want to hire but they cannot reach out, right.
So, we convert that sourcing and onboarding to a digital program. And then the whole process is done right? Including integration with garment system psi. So, everything that you need to do is taken care of is that the sourcing and onboarding? The second problem that the organization face is about productivity, right? Now that I have hired the person, how do I increase the productivity? How do you ensure that the person is already skilled or skilled in a distributed environment?
So, when we look into the program, we saw that a lot of people are coming, there is a classroom, companies are struggling to train them. So, we created a mobile app, which is based on a bot right. And now that bot takes care of upscaling the person based on their need, right?
It could be learning as simple as English words, to financial literacy, to how to manage your work, app or work or, or learning something different that you would like to write. And this is done through a bot an interactive model. So, a person can learn whenever they want. But skilling is not the only thing.
So how do you ensure flexible resource availability to an enterprise? Like, I get it when I need it? So, Friday and Saturday, they need more people during that time, rather than having them every day right. Now, how do you ensure that I have the people during that time. So, we take care of that part as well. The third thing is about time and attendance. You go for a job, you are paid by the month you do your tasks, you are done right in blue collar, it has to be done by the hour, people are supposed to work for eight hours, if they work for 10 hours, you have to pay for those additional two hours, there is shift which is happening morning shift, Night Shift, evening shift, and so on.
So there is an auto rostering happening, depending on your history, the system immediately suggests that these are the guys who should work in the morning shift. These are the guys who should work in the night shift. That also take care of the requirement because some people are supposed to work only 12 hours a day, you cannot force them to work 18 hours a day, you cannot make them work every day extra hours for them for the whole month, because there are compliance requirements. So the system takes care of all those things, right?
Based on that we provide official base attendance solution. So the complete attendance can be done based on your geo fenced facial recognition system. So you go to a particular site, like you work in Amazon, you are in that location, then only the app gets activated, you capture it and then you can do lead management regularization, the whole complete workflow is taken care of.
And this is one of the biggest challenges that all the organizations are facing right. Because if you do attendance through manually, the reconciliation of attendance takes a month right because you have multiple locations, you have to collect the data, you have to transfer it to an Excel, the principal employer has to approve it and some stuff.
Then the next step comes the fourth component is about is getting the salary within the time frame define with the right overtime pay the deductions down the PFA si paid and so on, so forth. Again, these things were happening manually, largely you have to register, convert this into an Excel, then Excel, you use the system, calculate the salary, then go to the bank, disburse the amount into the bank and, and then go to a PF side. And the fourth thing is about benefits. No employee wants to give some benefits to the individual like insurance, they can do it to us.
Now, what was the challenge in giving these insurances of credit and all these things, there was no data. So, if you have to give a credit, there is no credit underwriting algorithm, right? Because there is no data. Now, as we provide the solutions, we build a lot of data about individuals.
And we use this data for the distribution of services. So, we partner with banks, we partner with insurance companies, we partner with health companies, and distribute services to the individual right. Now, these services can also be distributed directly to the individual. So, this is done through a business. So, a company, for example, you can buy for your employees, but the individual can buy directly, as well, directly through the mobile app that we provide to the individual, right.
And so, we provide individuals a mobile app where they can build their profile, they can learn things they can apply for loan, credit insurance, and all the other components that we offer. What was the first hope that got you started?
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