I grew up largely in the Gulf. So when I'd come
in for my 11th and 12th, and we had a long interview
for selection in my 11th grade. At the end of
it, I remember my mentor, then Suvidhaka, who
came up and said, I've interviewed kids over
my 15 years of experience in school. And you're
the first girl who came up to me after a four
-hour interview and said, I want to do social
work. I have never heard that answer. So that's
where it started. It started with saying social
work I have to do. I was a proper social activist,
walked across this country. you know lived off
highways lived off sleeping bags and you know
in jantar mantras screamed on top climbed poles
done all of that at one point of time welcome
to another session of the my first job each week
we look at a different career profile we look
at a different field of work altogether i have
a young vibrant entrepreneur. Rajashree Sai of
Rarfana heads ImpactTree .ai, a company which
is into data analytics, and she's examining ways
in which data can be used to assess impact on
the ground. There is one thing about planning
and policies and money actually being spent on
programs. But what happens to the lives of the
people who are a part of this is really what
Rajashree is looking at. Good afternoon. So great
to have you on the show, Rajashree. I know that
there's a lot you've been doing. So like you
just said, I'm the founder of impactree .ai.
And we started impactree with a mission of impacting
about 1 million people way back in 2017 when
we started it. So far, we've been part of initiatives
that have impacted about over 2 million people
across this country, and we operate in India
and Saudi Arabia. And what we do is very simple.
We build technology platforms that is focused
at enhancing decision -making on the ground in
two key sectors. So we largely operate in the
sustainability space, that is that you would
have heard buzzwords around ESG, you would have
heard around social impact. All of this falls
under sustainability today. But what we've realized
through our experience is that, you know, this
is all great at a mission level, right? At the
founders levels, organizations say net carbon
zero, someone is saying impacting 70 million
people. What does it mean for the ground level
operators? How do they translate that word net
carbon zero or impacting someone in sanitation
or water? How do they perceive it? Because these
are the people who are implementing it on the
ground day in and day out. If it's an NGO, it's
a block level officer. If it's a corporate, which
is a listed entity, which has set this mission,
it is their factory worker, their operational
heads. They are the ones who are actually going
about implementing this mission. So our platforms
that we build, SaaS -based platforms, we sell
it and retain it for a license basis. It's a
technology product that we sell to these two
customers, whether it's a corporate or an NGO
largely. And they fit it into their stream to
collect data. So through their organization,
they're able to implement it, collect matrices
that make sense to them. And that way scale better
programs. So that's what we are focused on on
most part of our day is what we are working on
is that. Of course, the other initiatives that
we do run is Neti, which is our platform for
women entrepreneurs in rural India, largely.
So that's the second big initiative that we work
on. What has led to this decision? In some time
in college, did you have a problem or did you
understand what is it that you wanted to be doing?
If you ask me. When I was in college, did I know
what I was doing or I would set up Impactry?
The answer is absolutely not. In college, I was
an economic student. One thing that I was very,
very clear of right from the beginning is that
I wanted to pursue a career in social impact
or social development. And that was something
which was like a no -brainer. It was something
I wanted to do. So very much when I was I was
doing my school with the school KFI, which is
it was it was here in Chennai. I grew up largely
in the Gulf. So when I come in for my 11th and
12th and we had a long interview for selection
in my 11th grade. At the end of it, I remember
my mentor then came up and said, I've interviewed
kids over my 15 years of experience in school.
And you're the first girl who came up to me after
a four hour interview and said, I want to do
social work. I have never heard that answer.
So that's where it started. It started with saying
social work I have to do. I was a proper social
activist, walked across this country, you know,
lived off highways, lived off sleeping bags and,
you know, in jantar mantas, screamed on top,
climbed poles, done all of that at one point
of time. And then along the way, I think what
was my pivotal turning point is when I was doing
economics, I said, hey, I want to do Indian economic
services. So that's one thing that I always thought.
He said, whatever you do, you excel. But you
make sure it's very different, right? So even
as I said, no IAS, I'll do IES. Why? Because
no one knew IES. It was Indian Economic Services.
No one did. So I said, I'll do Indian Economic
Services. I did choose a career in arts for that
also, that primary reason. But then halfway through
trying to prep for that, I realized that I may
not be very suited for a career in the civil
services. And at that point of time, I did. Quit.
And then the next thought that came into me,
because I didn't want to pursue economics, which
I was pursuing then, I told my dad, I'm going
to quit everything. I'm going to become a lawyer.
He said, hold it. No, you don't quit halfway
through your graduation. You finish your graduation
that I've paid for. So, you know, he said, law
equals company secretaryship for CS. Pause. You
have done year one of graduation. Finish that
and do a CS degree. Again, I didn't have a clue
why I did it. Took up CS. Did it. I wrote all
the exams in first attempt. And like, you know,
again, I like setting up goals. So that time
the goal was clear CS. I will distribute sweets
to everyone in the town and all of that. Cleared,
got into a listed company, sitting in there.
And then the question hit me. And now what? Let
your done it. So that's where I think the most
interesting turn happened for me. That's where
I tell in many places I'm a recession entrepreneur.
Because what happened is the year I got into
my listed company, for which I struggled three
years. you know, multiple exams was the year
that recession hit. So in 2010, I remember around
April, around March 10th is when I joined a very
large listed company here in Chennai. At that
point of time when recession hit, you don't,
you realize that there's no legal work to do,
right? So that was a very large, significantly
large project for merger and acquisition that
the company was, you know, actually had entrusted
me with. there wasn't any work because if no
business happens there's no documentation and
if there's no documentation what does a team
of 15 lawyers do other than sit and play minesweeper
so those days we didn't have geo so we were sitting
here playing minesweeper reading newspaper going
for lunches i mean there's only that much you
can do right after 10 months of recession i just
told my dad you know i can do something i'm quitting
i can't take this anymore so that's when i put
a bet with myself I said that, hey, if I get
through the Jagrati Yatra, that was again a way
I'd applied for the Jagrati Yatra. It's the train
journey where 500 entrepreneurs go on a train
journey across India. This year, in fact, the
applications for the G20 Yatra, I think, are
still open. And it's pretty interesting because
you get 500 perspectives of entrepreneurs, those
who are career, you know, very senior AVP level
people across the world to come on the Yatra.
So I said, if I get through the Yatra, quit.
So fortunately, unfortunately, I got through.
So I quit. after that and that's when I think
my real journey began when you know as a CS I
started working with a bunch of people I came
upon NGOs was doing compliance for NGOs and someone
said hey I think you'll do way better as a partnership
manager as a donor manager or implementer why
you know compliance is paperwork you can't do
anything so but then our advisory board member
Prema Gopalan of course she's no more there right
now but she had told me I feel you have way more
talent and reading legal documents come on to
implementation. So I did my first project. We
did a very large project to implement in creating
women entrepreneurs in rural India, selling clean
energy products all across Maharashtra. We scaled
that network across Indonesia and Africa. And
that's where the story of the sector must be.
So from there, it has been a journey where, you
know, I dived into data with my co -founder Vivek
and well, Impact Rewards won. That's very okay.
So this Jagruti Yatra, by itself, it's a really
different format, right? It's 500 entrepreneurs.
And how long does the Yatra last? So it starts
on the 24th of December every year. And then
it goes all across. It starts from Bombay. And
the Yatra is a period of 15 given 20 days. So
it will be 15 to 20 days. So as young entrepreneurs,
you will live off a trade. So it goes from Bombay
to, you know, Kanyakumari to... then you're going
to Bihar, UP, then coming to Rajasthan, and then
you finally come back to Maharashtra. So it's
a literal circle across the country in a sense.
And it's very interesting as a format because
I think what I chief took away out of it was
that there are, and I'm sorry to use the word,
but there are many more idiots like me who also
want to jump and try figuring it out. So, you
know, till then as a lawyer and a company secretary,
you're pretty shielded, right? You're almost
like corporate job, nine to five desk. You know,
after that, most of the friends who are in traditional
careers, it's relatively paved, right? You have
your house, you have your two children, you have
your vacations, you set it all up, right? It's
a nice pack of building blocks. And then I think
in the Yatra, what I took away was there are
a lot more people who are trying to see what's
the meaning of my life. Let me try doing something.
And even if I fail, it's okay. I think there
is a lot of wisdom in collective failure. You
find more ways to fail faster. And then after
that... Get yourself up and build yourself up.
So I think that was my biggest takeaway when
I went through the yatra, that there were more
people like me aspiring to do something different.
And I think more importantly, choose, find your
passion. Like I remember one of my earliest mentors,
Krishna sir from here in Chennai, he told me,
we're all born with a purpose. What's your purpose,
Lakshmi? And he told me this when I think it
was about 20s, just out of college. For a very
long time, I kept thinking, what's my passion?
What's my purpose? What's my purpose? It has
almost taken me close to 12 to 15 years to finding
the purpose. But I think that, you know, the
part is the journey that actually gets you there.
And the other great thing when I was thinking
about the Yatra is, I think all of us have had
train journeys. Now, of course, the current generation
doesn't really need to go on those 48, 72 hour
trips anymore. But that is a time when you made
another set of friends because you were thrown
into very close quarters with people. And you
got to know them better in three or four days
than you would know some of your friends who
met only in the evenings or on weekends and things
like that. So I think whoever has come up with
this idea, it's a fantastic idea to bring together
extremely committed and driven people. And then
Sashank Manitrapati is the founder of it. So
you can definitely check him out. There's a whole
TEDx talk that he's also given on the Chakrati
Yadda and how he created it. I mean, he's a contesting
MP from Uttar Pradesh and Purvanchal right now.
But I'm in this phenomenon because I agree with
you. In those days, and I remember till 2008
-9, we still used to do the train, right? That
was if you get into a train, most people just
cover, you know, they go up to the bunker, cover
themselves, put their iPods and, you know, everyone
is streaming. And I remember, you know, I was
in Chennai, Bombay sometime back. In 2008 -9,
and you know, there were four uncles, very sweet.
We chatted about politics, India, geopolitical
situation, wars at that particular moment, economy.
Then the uncles actually called his relative
who was getting a breakfast in Pune and said,
you know what, they have two youngsters here.
They don't have food. Get them food. So, you
know, those relatives bought the food the next
day. It's a whole community you build, actually.
Yeah, yeah, that's right. And those, I think,
are the real learning points because it's learning
by actually getting immersed. Now they call it
immersive, but an evening of immersion is nothing.
This, like you said, you have to be on the train
and you have to get. The reason I'm going into
this also is because I think apart from learning
in a regular environment, which is like school
and college, something like this, which takes
two weeks is. defines, like you said, you were
thrown into close quarters with people from so
many backgrounds and so many different points
of view that it's like that friction leads to
another set of sparks, which you may not have
actually, you know, at that point in time said,
okay, that's the crazy part, isn't it? That you
go for a program and then when you ask, what
did you learn from it? It's very difficult to
articulate. no but i wouldn't agree with that
because i think it's the yatra the way it's built
and at least it was you know at that point of
time when i went i remember you know someone
to i mean someone once told me that you set a
lot of goals in your life yes i do because i
remember when i went on the yatra i was just
you know person who quit her job you know literally
threw away a very promising career in legal and
i possibly got there even my mentors then said
why because you know First attempt, gold medalist,
you're sitting here, you've got the position
you want. At a ripe age of 22, they gave me an
M &A project, right, which was just an acquisition.
It's pretty large for a kid to handle at that
point of time. So I really think that the company
also saw potential. So even they didn't want
to let me go and they said bye. But I remember
when I was confused and I was sitting at the
Yatra and, you know, it's something that Shashank
kept telling me. He said, if I wake you up at
two in the morning, you should be able to give
me your five minute elevator pitch. What you're
doing, why you're here, where do you want to
head, right? And I did practice and he did ask
us one day. So our one pitch that we do through
train car sessions was something at ridiculous
2 .33 in the morning, okay? Because there was
no time in the rest of the day to do those pitches.
But I think that, you know, those things also,
the way it's structured, it helps you kind of
also start, you may not know where you're going,
but start to also putting to... what do you want
to pull out of that experience, right? Like different
people might pull different things out of it.
But the more important thing is to also be able
to direct to say that, you know, why don't you
start thinking down this path? Because otherwise
you can also end up going so broad, you may not
really know where you want to start focusing
on. So when you talked about the project which
you helped set up with Swam Section with Prema
Gopalan, what exactly did you have to do to set
up this whole thing? So in that project, I was
largely, so I was handling Swaim Section Prayog's
legal documentation before that period of a year.
Before Prema kind of, you know, took me aside
and said, hey, so this is a project with USAID.
And the whole mandate under the project was to
create, within a period of three years, we had
to create a network of thousand women entrepreneurs
across six districts of Maharashtra and three
districts of Bihar. who were capable of retailing
clean energy products. So all the way from your
solar lamps to your water pumps to your, you
know, biogas units, you know, home biogas units
of Kirloskar or up to, you know, even those times
at that point of time, very high -ended home
lighting systems with solar. So they had to look
at the entire value chain of products and start
retailing it to rural households. So I was the
partnership manager and implementer that I went
on in the project as a consultant. And my role
was largely to see that all across the pipeline.
So all the way from the training and initiation
of these women to what are the roadblocks they
face while they are scaling their businesses
to actually creating the pipeline of partners
who can keep pushing products to these women.
Because, you know, creating a network is one
thing, but the network doesn't have enough deep
partnerships to sell. then you're not on all
products to sell, right? Like, you know, for
example, Amway has a bucket of products, right?
So we did a bucket of clean energy products at
that point of time, all the way from your 500
to 24 ,000 rupees, right? Across the spectrum
of products that women can retail. And how do
you get them to retail it in total households?
So that was the whole aim of the project. So
at the end of three years, we had actually leveraged
the project almost four times over in terms of
partnerships. So partnerships. partners not only
put gave products they put in money they gave
grants but they also gave free products to these
women they you know helped them set up manufacturing
units off you know small small things like solar
repair shops solar lamps all those kind of things
that they were actually partnering with the women
because they saw value to start looking at working
with these women as their last mile point and
that's what did you have Yeah. Sorry. So did
you come across any particular incidents of women
who stood out? How would you know that a woman
is an entrepreneur, for example, or capable of
being an entrepreneur? So I would think that
there, see the, as I've seen, we know that often
across is that most women in India are entrepreneurs,
right? It is just that like. we don't recognize
entrepreneurship or define it very differently.
That's why if you see every day, you know, you
have the unicorn, the decalcon, the sunicons
and the endless cons that we keep throwing out
there. These are all Silicon Valley definitions
of entrepreneurs. And I don't think that's how
Indian enterprises operate. So the women, the
metrics that you cure everywhere, 14 % of India
has women entrepreneurs. I think it's a very,
very underreported number because our metrics
are not right. In most of the Indian context,
if you see across India, there are in every household
entrepreneurs. Now, the thing is, most of rural
India, 70 % of rural India gets their primary
income from agriculture. Agriculture is one of
the most hardest enterprises in this country.
And the problem is we don't give it its due because
you need to think of it just as an enterprise.
There's so much that... People like you and me
who run data or service businesses can control,
right? You can control the client, you can control
the delivery. In agriculture, you can control
nothing. You have to wait for the water to fall
or you have to use the reserve of water passingly
at the right moment so that you hope for the
right crop, right? The saddest part is you don't
recognize this as entrepreneurs and you don't
recognize this as an enterprise, right? So that's
where the fundamental problem starts of where
do you find these entrepreneurs? They exist.
They're already doing something entrepreneurial
way harder than what we all do regularly. Like
I remember someone once I told someone, oh, I
know agriculture in and out. I've been doing
it for 15 years. They're like, yeah, have you
tried growing? I said, no, that's where I don't
know agriculture. I stand corrected. Right. I
definitely think if I went to the field, I possibly
will fail. Right. So it's one thing to have the
theory. It's another thing to grow something
based on a nature thing and and grow it up. So
I think the first point is there are entrepreneurs.
The second point is many of them are doing agricultural
livelihoods, businesses. Many of these are family
businesses. Unfortunately, in all your definition
of unicorn, decalcon, family businesses is not
counted. And who isn't a family business in this
country? Everyone is, right? You name one top
NSE company from Reliance to Aditya Billa, everyone
is an entrepreneur since generations in this
country. Even take Coimbatore, right? recall
so many of them rnkvs all of these are family
enterprises we are a nation of family enterprises
so the reality is many of them do agriculture
they have family enterprises where the definition
goes against them is many times family enterprises
in agriculture called subsistence by subsistence
simply mean it just enough to survive and that's
where we have taken a western definition and
we have gone wrong we have taken a western definition
and i remember a few republic days ago you know
our chief prime minister modi had actually said
we need to be proud as indians and have indian
definitions to what we do he's right we took
our definition subsistence we didn't understand
it much and we put it in agriculture now every
woman in who's working in agriculture and doing
multi -livelihood which case she's doing poultry
coterie vermicompost food businesses and agriculture
is called subsistence level entrepreneur so she's
not even considered an entrepreneur so the thing
is when you change the definition And you say,
remove the word subsistence. They're doing an
enterprise to survive. They have their own family
dynamics. They may not have external employees,
but if I have been able to trust and get my husband
in a job and make sure he leaves his job, you
imagine the trust I have in my own business plan.
I'm putting all my eggs in one basket. That's
a huge amount of risk taking. So if they have
their family in their enterprise, they're doing
subsistence level work, but... Removing the word
subsistence, they're doing multi -livelihood
as we call them. They're doing multi -livelihood
work. Is there a way to take them, add some more
dimensions, teach them how to go to market better?
The minute we just took that, we found many entrepreneurs
across the country. Our job was only to help
them get to market. And you'll see, if they implement
something in clean energy works, you'll see them
the next day implementing it themselves in agriculture.
They will scale their private business also.
So you don't have to worry. It's just about giving
them the right skills to think of scale. Okay.
Okay. So Impact Tree came out of an understanding
of what needed to be done on the ground. Why
did you think that you needed to measure impact?
Well, it came largely actually also came from
the USAID project. And I'll tell you why. Because
what has to happen is that we used to have a
lot of consultants who did very good work with
us. But unfortunately, by the time these consultants
would go into the field and give us a report
of what was happening on the ground, and we would
actually go about implementing it, the time to
implementation sometimes would take six months,
right? And to give you an example, right, if
I've done a training in implementation and, you
know, onboarded a particular women, you know,
we onboarded women and we used to offer training
in the morning, right? So we used to tell our
trainers were available in the morning, they
were employed with us. So we said 10 to 2 o 'clock.
we would call you for training and after two
o 'clock please go sell your product outside
okay and i expect you to sell your product till
six o 'clock when it's dusk makes perfect sense
from an urban mindset you have four hours to
sell give and take training you still have six
hours to sell women should be able to really
sell it was a massive failure i'll tell you why
because we didn't factor into account how the
women's clock worked So till 10 o 'clock in the
morning, they generally would send their children.
They would prepare all the, you know, whatever
they had to prepare for the day. And then after
that, when they would come out for training,
they would be tired by 2 o 'clock. And 2 o 'clock,
when they would go into households to sell, there
weren't enough decision makers at 2 to 6 in the
household. So there would be the wife or there
may be old people or their children. None who
can take concrete decision on anything more than
200, 300 rupees to buy. And the products that
we were trying to retail were close to 15 ,000,
20 ,000 on EMI, of course, but sizable scales,
right? So we started, by the time we got this
very important input from one of our data partners
on the ground, we had finished eight to nine
months of training and implementation. Then for
us to go back and recover the time was a real
large challenge. The second challenge, for example,
we said, We figured was that, you know, we said
that women have to be empowered. So, you know,
you break away from your families, you go, you
sell, you become a retail salesperson. We did
a lot of marketing campaigns around that. Most
successful women, we realized after six months,
were whose husbands accompanied them to sell.
And the husbands started pushing them. So after
six, the husbands would take the bike out with
the women, give them ideas for marketing and
taking them into the villages. Some husbands
even retail their products in their own shops.
And then the women would be given training by
the husband saying, and try selling. These dynamics
we realized very late, right? And we started
off in hindsight. I realized that was also because
we didn't have the tools to capture this data
as it happened on the ground. So we relied on
consultants who would come to us and give us
this data periodically. But by the time the whole
synthesis would happen, I would get it at a boat
level. It would percolate further to the ground.
It would just take months and implementation
period would be over. So that's when actually
Vivek, my co -founder, came into the picture
because he comes from a manufacturing background,
right? So for him, he was working at that point
of time with Reliance and leading some of their
biggest technology plants. And the data was everything
for him, right? He would get mini -level, mini
-second level data. And here I was not able to
figure out, you know, how do I reconsider? It
happened over months. Yeah. But then it started
with a small thing saying. Can you, some of the
things you implement in manufacturing, can we
try it in the social sector? That's where we
started. We spent an entire year doing that.
Where we would collect data, Vivek and, you know,
would synthesize it. He'd help us, give us models
to build it up. And then we started seeing field
level efficiency improve. Because the first thing
that we understood, we realized it because of
three nuances. And that's what we built our platform,
Prabhav and Aathri, which is Prabhav, which is
our social impact platform. Aathri, which is
our ESG platform, is built on this basis, okay?
First is we have realized Excel means a lot to
me and you. It means nothing on the ground. 80
% of this country doesn't understand Excel. It's
only we talk 20 % who can keep learning micros,
macros and all of that and figure things out.
So we realized data has to be visual. So we took
out data and we said, I'll give you a pie. I
will give you a bar. I'll give you some dancing,
you know, horizontal, straight pies. Then you
start understanding data because your eye is
able to perceive something. The second thing
we realized very closely. Sabhi, can you go a
little deeper into that strategy? What exactly,
how did you visualize the data? So how we visualize
the data is if I have to say a male and female,
right? A number 24 and 25 doesn't mean anything.
Your head will not automatically add it in most
cases and say that, okay, these are the, you
know, 49 people that we're talking about. But
when you see a five, right? And you say, okay,
40%, 50%, and it adds up or it shows you two
bars. You're able to visualize more male, less
female, right? Those visualization nuances changes
for you, right? So that is the first thing we
cracked. We said that let's make data visual.
Can we have a platform where you can start visualizing
data? You want to compare this year with next
year? Compare. Everything will come to you as
a visual. It will not come as a box in a four
by four number. It is very difficult to understand
numbers. The second thing we realized is. Remove
this whole madness of English. If English is
again known by only 2 or 4 % of the population,
as fluently as we both are speaking here, the
rest of the population speaks a vernacular language.
So why can't data be collected and represented
in vernacular language form? So most of our platform
is built on a vernacular language base. You see
it in the language, you understand. We will collect
all the data in vernacular language. If you want
for synthesis, yes, it comes in English. you
know, at the analytical level of those who see
those data. But everyone can visualize and look
at data in vernacular language. And that's why
we started looking at data. When we saw these
two challenges, we started seeing a lot of field
-level implementation challenges coming down.
Only because of the fact that data was more something
people could understand. They need not fear data.
It's a friend, right? And then when that happens,
you start seeing that how important it is to
take decisions. You know, a lot of, I was reading
an article somewhere where it said the world
is data, AI, everyone is, you know, there's an
old hype, chat GPT, we are going to lose jobs,
70 ,000, 80 ,000, 1 million jobs gone. But, you
know, when I keep reading all of this, I realized
that five years back, this is where the social
sector was. There was a lot of hype on data,
system, you name it, everything we were implementing
and still not getting through. But I know that
the whole hype will be there. Then the dust will
settle. And then at some point of time, we'll
get realistic on what these tools can do for
us. And at that point is when you will see the
magic starting to happen. Right. So when you
made the data visual, what is the change that
you noticed on the ground? What were the differences
in assessment that began to happen? So first
is when we made it visual, someone who is just
a 12th or a 5th or a graduate can start to understand
it. Right. When it's a number. and there is no
understanding of big or small, you start struggling
if you're not educated enough to understand what
is the association. When you start seeing it
in forms where something is big, something is
small, you start relating to it a lot easier.
So I'll give you an example. We were running
this project with one of our donors in about
24 villages in Nanday district. This is a project
with SSP only. Where the aim was to look at maternal
health. And this particular... Donor and SSP
had tried everything. I mean, they were seeing
that this particular district, these 24 villages
in the district were very backward. They had
a lot of challenges where, you know, the girls
are married very early. They had miscarriages,
heavy amount of abortions, stillbirths, all of
that. So they identified it to anemia. So then
they started saying, OK, girls are very young.
They're anemic. Let's start giving them supplements.
You know, a lot of investment went into. Fortified
products, fortified pills first. When people
stopped eating medicines or didn't eat medicine,
then fortified products started. So whether it
is biscuits, whether it is daily items that can
be fortified with iron, we used to give girls
that. We did all of this, put about a year, and
we were still not seeing results. Adoption was
not happening on the ground, right? So then this
data that we started collecting in 24 villages,
this was, you know, it was made available and
we sat down in a group with this data present
open on our platform. with a lot of Anganwadi
workers, ASHA workers. So in every village across
the country, there are health workers that the
government designates. Their main role is to
help in the case of act as a midwife or get people
to the PHC, etc. So you sat down with the ASHA
workers and Anganwadi workers who are like community
leaders in various villages. They, of course,
operate the daycare system, but they are de facto
community leaders. And we started showing this
to them and saying, we don't even understand
where we're going wrong. We've tried everything.
Why is this not reducing? And I remember some
Anganwadi workers in Ashabattas looked at the
data and they said, you got it all wrong. So
I said, okay, thank you. What did we do wrong?
We have spent a lot of hours on this. Where are
we going wrong? They said, you are going to the,
you're collecting all this data and you're trying
to find a solution without factoring into account
decision maker on what women eat. So I said,
okay, that is interesting. So what do you mean
by that? So they said, see, the person. It's
not the daughter -in -law who decides what she's
eating. It's the mother -in -law who decides.
And you're selling pretty much kids who are about
20, 25 with a heart in the right place. They
are social community workers. They are going
to mother -in -laws and say, And the lady is
humoring them because they're put in India. We're
not going to tell you that, you know, you're
bad or, you know, why are you wasting money?
We're not doing that. They were just nice people.
We're looking at the lady's story and go, please
give me the packet. Thank you. Thank you. And
all of that. And then she throws it on the side.
That's where the problem was. So we realized
that by the time the women ate, the husbands
would eat, the family would eat, the children
would eat. So even if it's a chicken curry, she's
eating the gravy. The pieces have gone. So she
has no nutrient value which is going into her
system. And they said that this health awareness
is not going to work. So I said, what will work?
They said, it's clearly you're able to see the
social dynamics in these villages. They are poor
villages. Why don't we develop a campaign? And
this the women came up with to say, how can you
benefit by the birth of a better, healthier child?
Right. We will show an economic angle to birth
and then this will move. And I said, this was
phenomenal. And they did a phenomenal job. They
went down and sat with some mother -in -laws
and said, Don't feed them eggs or chicken meat.
Don't give her the good stuff. It's okay. So
what will happen? She will go into a C -section.
And then C -section will happen. Then the child
will have a problem. It won't be solved in the
PHC because such complicated cases they won't
handle. So she will go to a private hospital.
So you will get a bill of 1 .5 lakhs. Approximately
when the child is born. Or you feed her now.
You know, if they made a calculation and gave
it to the mother -in -law, they said, egg for
a week, chicken for a week, and vegetables for
a week. After all this, you will get the maximum
expense in about seven months. Because in nine
months, she generally will go to her mother's
place. Seven months' expense is somewhere around
75 ,000. Then if she goes for a delivery, please
note she'll have normal. And India is obsessed
with normal, right? Rural India, everyone, even
people who have never given birth, men will tell
you, normal should be there, right? I said, that's
the biggest achievement of all day. It's a normal
delivery. So then 75, maximum another 20 -30
you would spend. 20 maximum, right? So 20 -30
in a PHC, it will get done. So in 1 lakh, your
child is safe, your mother is safe. So you decide,
do you want to spend 1 .5 then? Or spend it now,
your daughter -in -law will go for 7 months.
Literally, 8 -9 months. Kids were born in normal
delivery. Two households got implemented. 24
villages adopted it. It made socio -economic
sense to actually outgift the women. And my question
is, this insight, we cannot see. We are from
an urban context. This insight, only an Anganwadi
worker can tell you. Across India, when we have
seen, if you don't believe it, about 46 % of
this country operates in barter system. And we
don't even have a way of measuring it. Just today
morning, I had gone to a relative's place. They
said, oh, you're going to Kutralam tomorrow.
So in Kutralam, when I grew up, it was, if you
wanted to Maligapu, the flower garden, we would
give one tub of rice. And she's just a six -year
-old. Forty years back, we used to measure life
with one or two glasses of rice. Today, we are
pegging it with the dollar and the rupee and
all of that. It's not sunk that down inside.
How do people understand these nuances? It's
only when they see data. We cannot, because of
our urban understanding, our urban upbringing,
our exposure to the world, which has its own
pluses. That's why it allows us to work at it
with a different technology lens. But we can't
understand what they go through. And who better
to actually give better solutions than them on
the ground? No, this is really informative, Rajshri,
because... I don't think I was, you know, when
it came to data again, it was the same thing
that you spoke about. It's all bar charts and
figures. And then suddenly you begin to see how
the implementation of something on the ground
changes. And then when you measure it in numbers
again, people say, oh, and then the connecting
link is gone. What is it that people actually
did? In this case, you brought out the connection
link that the Anganwadi people had the. you know,
insight to say, link this to the health of the
child, as opposed to saying, look after your
daughter -in -law. I mean, it's such a sea change
in how they think. Wow. So when you, are you
finding these kinds of examples practically on
every project that you work in when it comes
down to looking at data points? Completely. Because
like I'll tell you, it's just not an NGO perspective.
And that's where... You know, I have a great
management team and I have a great board. I'm
very lucky to have them. When we were working
on a corporate project in Saudi Arabia, we again
understood that most of India, forget India,
most of the world operates on socio -cultural
nuances. As human, we collectively like to believe
it's all economics. But the reality is most of
our decisions are socio -cultural more than economics.
And we realized that when we were working with
a large, it's a huge multi -billion dollar company
there. And they were having a large problem of
attrition, right? So they used to have people
who used to come as migratory population and
then, you know, they would be able to put them
through the process. They were serving certain
things to the, you know, Saudi government. It's
a service -oriented manufacturing company, installation
service system company, to put it that way. So
when we started using the same lens there on
their data, we started realizing they had a unique
problem, right? So Saudiization mandates that
if they have to actually get X percent of government
contracts. They need to employ people who are
Saudis. Now, Saudis are used to a different work
pattern than migratory workforce. So migratory
workforce have come there only for a reason that
they need to earn money. So they will pack in
that 24 hours for four days and it wouldn't make
a difference. A Saudi local is not going to be
doing that because he lives there, right? He
comes with a difference to cultural dynamics.
So there my team was led by Vivek, were able
to optimize work schedules around sociocultural
elements. which allowed them to actually improve
their efficiency as an organization by 37%. And
it actually allowed them to increase a considerable
amount of their turnover. Because we were able
to look at the workflow and we realized it was
all built to a migratory population and it was
built by someone from the West. So everything
was scheduled without actually thinking how a
Sri Lankan or a Filipino or an Indian would work.
And then adding an element, a Saudi managerial
person, right? So even the whole... work process
system we had to optimize from a point of view
of what are the social cultural dynamics which
are nuance to each culture or sector and then
how can you optimize that into a system or a
data point and that way we are now able to improve
in efficiency so we see that in most of our projects
it's not only about the fact you know how much
economics you look at it you take away that lens
of economics and you put in socio -cultural aspects
And that is, which is endemic to that area. You
will start to see similarity. And then you will
see similarity, like from the Persian side to
the, you know, till about China border, we are
very similar. Most of us, socio -culturally,
till even Indonesia. Then from Korea, it's another
segment all the way up to Japan, right? With
different ethos, different cultures. But if you're
able to take that 80%, which is similar and standardize
it, then you have to only work with the 20%,
which is different to optimize. Amazing. I think
we've hardly covered your career and talked more
about a couple of projects, but I think it throws
light on something that you started off with,
the conversation we had just before where you
said analysis is not just taking in figures that
exist and trying to make sense of those figures
because the background of how those figures came
to be and what is the process that was put in
place is not understood. So then try to draw
inferences from that. Like you said, in the case
of whether it was the Saudi European company
or the village, without having that insight,
how do you even begin to understand that this
is how we solve the problem? Because you can
say that they need nutrition, but that is like
the most basic inference that you can draw. But
how do you break this, Rajshri? How do you break...
Some of these things which are so deeply ingrained
in how data is collected that you have to bring
about a change as you go forward. I think the
first step of process is standardization, right?
And then we have also seen everything is not
very disparate. When you start looking at data
and you start working on data analytics, you
will start seeing similarity more than dissimilarity,
right? Everyone likes to think they're very unique.
We are not. And we are very similar, more similar
than we realize, given the similar backgrounds
we might come from. Because if you have similar
backgrounds, you have similar networks, similar
upbringing, similar ethical values, and similar
exposure. So that way, these are broad benchmarks
that help you to start condensing data, which
might seem very all over the place, to a level
that it is understandable. The first step is
standardization. So being able to call out that
standardization across data is important. The
second step that, of course, that we've built
in is using technology. So technology, once you
standardize, is a very good medium to scale because
you can take something which is standardized,
process it into a system and the system will
replicate. And hence, if you see, we took a decision
of keeping it as a SaaS or a licensed platform.
You use Google, you pay a monthly subscription,
you can pay a monthly subscription for all our
data platforms so that it's affordable and cheap.
And then as the system gets more and more and
more data that comes into the system, the system
will start to learn. That's what ChatGPT did.
And that is precisely how we are driving and
looking at our data platforms growing at that
sense. And with reference to, of course, like
what we talked earlier in careers in data, right?
I would think that, you know, I mean, there are
and we hire a lot of interns in data analytics.
We hire from economics. We hire from engineering.
I think there is a three, you know, three step
process that I might use for evaluation and maybe
it might help some candidates for thinking of
careers because. I now see that increasingly
you open any YouTube academy, everyone is throwing
a data analytical career of some sort at you,
right? So everyone is saying this is the in thing.
This is the only career where you will possibly
never be let go. All kinds of tall promises,
right? I think we use a simple three -state process.
First is when you're looking at data, you need
to love math. That's the basic. You need to be
excited by numbers, right? Understand whether
your numbers are naturally you want to pull them
into things, want to compare them, see is there
some trend that is going. You may not do it for
numbers, but this causation habit, right? What
caused this? Why is this happening? Are you a
person who thinks at that level? Even if you
start thinking at causation, math is an easier
problem to solve. We have enough and more models
which will help you solve math. You plug it in,
it will vomit enough things at you at any engine.
So it's not a problem. But do you want, are you
a person who likes causation and wanting to keep
on thinking? So the creative types, right, who
like to find out why, those are very inquisitive.
That's the first benchmark we look at. When we
look at people, we hire for data. The second
most important thing that we look at also, at
the same time, how much of a big picture person
are you? Okay, so when you look at data, it can
get very micro, right? So I hear a lot of people
saying, I want to do a career in data analytics.
Why? I think it's cool. What are you doing right
now? I'm coding somewhere. And okay, great. So
do you want to code with us? No, I want a career
in data analytics. Do you want to do operations?
No, I don't want to travel. So I said, then what
does data mean? I mean, I can't get you to code.
I can't get you to travel. So which means you
want to be in front of a system and look at a
bunch of numbers. That's not data analytics.
That's not how it works. Most people who do data
analytics go to the field. You have to be able
to talk to people, hold a conversation because
the insights you get from there is where you
can train a model. So the maximum money you will
make in a career is when you have or develop
the ability, use your causation skills to start
going into the depth of what causes even through
global things. So you should have the ability
to read, right? So if you're able to go look
at causation, communicate and read, it's very
good to start a career in data analytics. Believe
me, this is what I tell most of my team. I say,
today Google does everything. So make sure you're
able to read and get the right insight. So that's
where you will make your money in the future.
Right. And I think another thing that you started
this off, that you're understanding that vernacular,
a whole lot of data, like you said, is so how
have you done that? You've managed to connect
vernacular interface to most of the data that
you display? And in how many languages? How do
you see that change? So right now, all our platforms,
so the data collection happens fully in vernacular.
So that's like a survey link or a form or whatever
it is that goes out. That'll be first in the
vernacular language. We get that because Google's
vernacular engines are not properly trained yet.
So unfortunately, we can't directly Google translate.
We use the help of people on the ground to refine
that, you know, nuance on to get it contextually
right. The second thing is that our display features
in about 10 languages we've programmed it for
it to display. So there we are using a bit of
Google Analytics and our own question bank. So
one feature that we've built is we have our own
question bank and our platform where a lot of
the data, a lot of the questions are already
translated in vernacular language. So you can
adopt some of that so that you get a constant,
you know, context, actualization right. And that
way, that is a longer haul thing where we are
slowly building to. Because the reality is...
Vernacular, it says there are very few companies
in India who are operating on vernacular language
mediums, right? And I think that will still take
time because I still see it about two or three
years away where we will actually have a recognition
for Indian languages and then we are able to
build on it. Because there is also a lot of dialect
issues, right? If I go to an Ajmer, the way Rajasthani,
Marwari or whatever the local dialect is spoken
there, it's a form of Hindi, it's very different
from when you go to Jaipur. So there is an element
of localization there still. And that's really
another aspect of this entire thing, because
once you crack this in this particular field,
there are so many other places, like you said,
where it can be applied to and how it goes. OK,
so how do you see Impact Tree changing over the
next few years? What are the next milestones
that you have kind of seen for yourself? So we
are right now largely a B2B company. And as we
operate, all our technology platforms are being
used by either field level operators or at the
board level. So as we scale and grow, we see
ourselves very clearly growing much. We were
one of the eight enterprises to go to the World
Economic Forum. That was huge that you got to
diverse. Wonderful. That's an amazing achievement
at this early stage. Wonderful. Yes. Yeah. Having
gone there, we now have exposure to international
markets. So the idea is to take our social impact
platforms and start scaling it vertically across
countries. But at the same time, we are using
a lot of the insights we built in our social
impact to build a platform much faster in the
ESG space called Aarti. So that is the ESG platform.
So, you know, I've used ESG once or twice on
this. you know the session so just to demystify
it for people who are here ESG is environmental
social and governance and now most companies
in the world are mandating that people have sustainability
plans companies have sustainability plans on
how they grow largely because of the point that
we all have realized resources are not infinite
at some point we're going to start running out
of crucial resources and somewhere companies
need to be prepared for that eventuality if they
need to survive at that point of time So we've
started working on an interesting platform there,
which we've already implemented. We're two companies
and, you know, we're slowly scaling it up as
a pilot. Largely from a point of view of seeing
how does, you know, at the ground level operators
and senior operational level managers understand
data across ESG spectrum. How can they actually
conserve in places? How can they, you know, spend
better in certain places and that way neutralize
their sustainability score, right? So that platform
which we're developing very fast right now. We
are actually scaling it through partners in Middle
East and Southeast Asia. So the next two, three
years is going to be really dedicated to scaling
this B2B offering for us. And then beyond that,
of course, we have certain B2C verticals which
are coming up, but that is more, you know, experimental
at this point of time. Like I said, we're building
a network of rural women entrepreneurs and seeing
what is the technology product that can help
them scale social and economically. retaining
intact their cultural nuances, of course. So
then in that end, we are working with traditional
value trade businesses, whether it's textile
or agriculture. And we are closer to now coming
to a point where we are starting to think what
is the platform solution offering to a B2C space.
So that's the large way that we are going. And
we are very much, I mean, like I've said earlier,
we are very much as a company committed to listing
by August of 2028. And that's the benchmark we've
set internally. You know, that's something we're
working towards with a clear mindset that by
that time we would have built a company which
is capable of scaling on its own. And that's
the core of what we want to leave as promoters.
And you make it, I think it's obviously been
thought through very well. I just wanted, one,
the thing on what kind of conversations did you
have in Davos? Was it more of a presentation
of what you were doing? Or was there interest
in, you know, how is it that you guys are operating?
And what are the challenges? What are the conversations
about? So I think that was a very interesting
space for us, to be honest, because it was after
COVID. So there was a lot of networking, right?
After two years, people were like, we are finally
here. We can talk, right? Enough of this. But
I also think that it was very interesting because
we were eight startups in the Tamil Nadu government
at that point of time, you know, with another
organization led by Amit. which was you imagine,
they had, you imagine this, you know, finished
its final event in Tamil Nadu. So you imagine
a chosen eight of us ready to go to Davos. And
the amazing part, and there was another counterpart
there called Think Davos who helped us through
the whole process. But I think the amazing part
of it was that suddenly the bigwigs of the world
were like, why did these eight startups who people
barely knew about, I mean, how did they get to
crash our party? So there was a lot of curiosity
on that, on how did you get here, right? You're
not a unicorn. You're not a unicorn. Like, how?
What are you doing here? Exactly. So that was
a really nice icebreaker because a lot of people
wanted to know what you're doing. And I would
think from an Indian government perspective,
you know, it was very proud to also see the Indian
startup scene. We had the largest attendance
and divorce in that particular year. The largest.
arena of Indian startups that is a very proud
moment also for the government where they were
interacting very open with you trying to understand
okay can you solution for us can you work with
us so I think a lot of that was very interesting
from a startup in a learning curve perspective
I think personally as a founder I would think
how to create a large vision right and I don't
think there is enough mentorship around that
right when you interact with the richest of the
richest you always see that plethora of things
that they are working with And then how fast
do they build these systems to learn and fail
and learn again and be okay with failure? Often
what happens in India is people are not okay
with failure, right? Even when you hear the traditional
talk on careers, they'll say, you know, engineering,
everyone is like, and then you die, right? Like
it's, it's just well planned out all the way
till we go. And after death. Because you're gone,
we will plan a certain X things you do for you
after that. So we've got it planned to even an
afterlife level right now, right? But how do
you think that, what I learned from the rich
is how do you perceive something to grow at a
scale? I think that in India is definitely missing.
How do you start planning for scale? I think
that's the, you know, that's something I've really
picked up in terms of, you know, we may not exactly
hit our listening mark on that day and I'm okay
with it. But if we can envision that every person
in Impact Tree is thinking that every day and
we all are committed to listing, it will happen
at some point of time. It's just a question about
envisioning that at a scale and working towards
it and then hoping that the stacks will add up,
right? So I think that is a skill I definitely
learned in DevOps because when you walk through
the streets, you realize the planning people
put into that vision and that's why it works.
Wonderful. So, closing thoughts, Rajesh, because,
you know, I don't think we covered all the ground,
but I think we've touched upon some of the things
that really make you unique and how to look at
a career from a point of view that is not the
conventional one. Even though data analytics,
like you said, is a very hot thing right now,
but you've really shown why, what is it that
you can bring about and what is the change you
can bring. So, any closing thoughts and then...
yeah so closing thoughts would i would i i would
say for those who are tuning in who are really
thinking what would be you know your careers
i think the most important thing i learned is
and i'll be honest so i started as an economic
strat then i did my cs i did my law then i did
my mpa and today i'm an entrepreneur in data
right so there's no connection whatsoever to
where i started that's the reality of what it
is But what I've always learned in life is be
open to the change. So embrace it. As you're
changing, you may not know where it's heading.
There is a purpose it will add up in the end.
Where it adds up for me is that as a lawyer,
I can today speed range huge amount of data,
right? The skill I learned as a lawyer works
for me as a data analyst today, right? Because
I'm able to read 60, 70 pages in a matter of
like, you know, less than 20 minutes. It's a
skill I know it's very hard to translate to others,
but it's something I'm trained in. Right. And
causation is something I picked up as a lawyer.
What is the cause? What is the cause? So that
depth keeping in the larger perspective is a
skill you learn. So understand that whatever
career, whatever education you're picking up
today, there are certain skills that you're picking
up. And use those skills to the way that you're
able to figure your career. We get enough people.
My other partner, Shesha, is a chartered accountant.
Today, she heads our operations when it comes
to data analytics. There is no correlation to
where she started with. But what is important
is she went behind her passion and was willing
to make the sacrifices it took to find an end
to it. And she's still, you know, in the journey
to find. So I would say that start looking at
that and start speaking. That's the only way
you will be able to figure out where you're heading.
Because I often start seeing that when someone
takes career, first thing, Google it. Next thing,
read to a bunch of people who have given YouTube
talks. Last thing, make a list to go and, you
know, tell this to friends and make an informed
decision based on this limited scope of not even
going and speaking to a person who's living in
that career. I think that bridge students should
do. If you're thinking of a career, find a person
who's working in that career, go and talk to
him and understand what does his career entail.
Because without doing that crucial step, you've
got all the secondary data, right? But it may
not be enough. Wow. On that note, I think which
is you brought it full circle, started with where
you were and ended it with how data can be an
insight. Thank you, Rajashree, for coming on
the show. And here's wishing Impact Tree the
very best in the future. Thanks so much. Thank
you. That was Rajashree Sai. And she told us
about how impact can really be created through
data once you have the insights. which is the
important part. So next time, another guest,
another show, another interesting career. Thank
you for joining us. And here's wishing you the
very best in future.