The Revenue-Focused Marketer

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Transcript

0:05
Hello, everyone and welcome back to another episode of the Revenue focused Marketer where we discuss anything and everything related to marketing as well as data.

0:14
Our episode today is gonna be definitely more data focused and we have a special guest today and her name is Ee who will be sharing a lot of insights with us.

0:26
So thank you for joining us today.

0:29
Thank you.

0:30
Thanks for hosting me on the podcast.

0:32
Yeah.

0:33
So just a little bit background about our guest today.

0:36
She has had over 15 years of industry experience with expertise in planning and delivering customer custom analytic solutions for telecom financial detail and other domains as well.

0:49
So she specializes in defining the measurement of strategies for businesses to help with their impact assessment and make data driven decisions.

0:58
She also has a lot of interest in building methods for different business development and also has had experience in managing medium to large size teams.

1:08
So we’re very lucky to have this time with you today and hope to really dig a lot of information and insights from you.

1:16
So to get started, I know that you started off as a Java developer and now you’ve been in the data field for so long.

1:24
So would you like to share how did you go about choosing this field and how your journey has been so far?

1:32
So I guess for me, rather than me choosing the field, my destiny took me in the right direction, I would say.

1:40
so I had been doing Java J two e development for many years.

1:45
Then there was a life changing event.

1:48
I became a mother.

1:50
And then I thought, why not do something different now?

1:54
Technology I had been doing for so much time.

1:57
Can I do something where I can give a little more time to my kid who was like just a few months at that time, when I started working to be precise, she was four months only.

2:07
So I thought I should give time to my daughter and I should continue working as well.

2:11
So let me try something different and that is how an opportunity came to me in the data field.

2:16
And it was the data analytics work that I started doing with commitment of say 6 to 8 months.

2:23
But once I got into it, I realized that it is a very, very interesting field and I got to know about the other side of the application development.

2:32
So how do you get to know how users are using your application?

2:36
Are they even engaging with the features that you have built.

2:38
So when I looked at the other side, it was really, really interesting.

2:41
And then I thought this is the way forward.

2:43
There is no going back.

2:44
Let me continue and stick to this field only.

2:47
So in my case, it just happened by chance.

2:49
Oh, that’s wonderful.

2:51
And how has your journey been so far in data?

2:53
Do you love it?

2:54
Do you hate it?

2:54
Most days are you happy?

2:56
Satisfied?

2:58
So with data, I’m like always happy.

3:01
If there is data, I have to work with it.

3:03
Even if it is something new, I have to learn something new.

3:06
I’m always always happy.

3:08
So it is something that gives me a boost for the day when I wake up in the morning that gives me a boost for the rest of the day that here are like five things I need to achieve in the day.

3:17
So let’s get on to it.

3:18
That’s one thing.

3:20
Yeah, that’s wonderful.

3:21
And I think that’s something we all seek in our jobs, right?

3:24
Something that gives us joy and want like we want to want to be there working instead of being forced to work.

3:30
So I’m glad that you found that with data diving a little deeper into this, there’s so many different functions of data in today’s world.

3:39
There’s data analytics that you said that you started off with.

3:42
But then there’s also data science and engineering.

3:45
So would you be able to help our users sort of understand users, I’m going data users, the audience.

3:55
So would you be able to help our audience really understand the difference between these different functions?

4:02
And how do you think they can sort of work together to make life better for like, you know, with the usage of it?

4:11
Yeah.

4:11
So see in, in the world of data, there are so many different fields that have evolved.

4:18
My journey started with analytics by chance.

4:21
But then within data, if you look at it, the first thing is you need to collect data and you need to have platforms where you can have this data stored and then start doing something on top of it.

4:34
That is where your engineering systems come into play.

4:36
You have data engineering where we build platforms where you can ingest data, you can start connecting data, connecting the dots seeing how this what story this data is telling and that is where then your analytics starts.

4:49
So I’m just telling you in a very, very brief manner.

4:51
There are so many processes that happen in between.

4:54
But yeah, once you have that connected view with the data, that is when you can start analyzing it and that is where analysis comes into play.

5:02
Now, when you are analyzing this data, you may come across certain scenarios which are telling you that this is going well.

5:11
This is not going well or this may not go well in future.

5:15
So data has lots of hidden things in it if data is correct and it is being utilized in the right way, you can start seeing what happened in the past, what is happening now and what can happen in future.

5:26
So all of that is your analysis bit.

5:29
Now when you are dealing with data and doing analysis, if it is a small set of data, people can do something like very small simple tools.

5:37
maybe Excel has certain features to say do forecasting, do some kind of plotting of data.

5:43
But then more sophisticated ones you can use even from the B I standpoint, you can use certain tools in there to have huge amount of data that you can start visualizing and you can have storytelling coming out of it, right?

5:54
then comes where you have humongous data and you really want to analyze it.

6:00
And that is where your A IA I at scale that comes into picture, your machine learning comes into picture.

6:06
Now you need to have your models which are actually defining your business rules and then they are crunching that data to tell you what this data is telling for the business and what kind of actions can be taken.

6:18
So this is how this progressive journey happens in data from right, from the platform to analysis to machines learning A I models that can start learning on their own first, you train them and then you can have models in a way that they can start learning on their own and start giving you insights and recommendations for businesses to take action.

6:37
So, so this is where the whole journey comes.

6:39
All of these things come together to solve a bigger business problem.

6:44
Today.

6:44
If you look at like retailers or some leading health care industry companies, this is where they are sitting on the wealth of data.

6:53
Now when they have wealth of data and they are the place at a place where they want to know what their users need so that they can serve their needs in time.

7:02
So in the current time needs not served within milliseconds is like your user is gone because there’s so much competition, so many other vendors are there, they can go to them.

7:13
Yeah.

7:13
So that is where the importance of data and quick action has become even more important.

7:18
So that is where these are like different skills, there are different platforms, different skills that come into play and depending upon which area you are interested in, you can pick or start from one field and then start widening into the other fields as well of data.

7:34
Definitely, no, that was really very insightful.

7:38
I know it made like a lot of clarity for me now to understand the difference between these three as we know, tech is always evolving and like you know, I think data is one field where you can really see that, like, things happen really fast and how do you, like, you know, stay up to date with the latest developments and trends within this industry?

8:01
You’ve been in this industry for 15 years?

8:02
So I’m sure there’s been a lot of changes and like, no changes in trends.

8:06
So how do you sort of keep up with it?

8:09
So, I guess changes are there in every industry.

8:12
It’s that data has picked up really well in the past couple of years and it has become a mainstream conversation.

8:18
You talk of any business and this is like in the mainstream conversation, big data is a buzzword now.

8:24
So it’s always big data.

8:27
Yeah, it was a buzzword now.

8:29
It is T GP T which is the latest one people are talking about, right?

8:34
So at one point in time, Sophie was the most talked about stuff, right?

8:39
So, so there is always something new coming up.

8:42
And I think one thing which we all technology people have in common and should keep alive is that hunger to learn more and grow.

8:51
Because if you are not learning, if you say this is where I have achieved.

8:55
So what you knew it took you to where you are today.

8:59
But for tomorrow, you need to upskill and you need to learn and grow only then you can have the next ride for future.

9:06
So I think one of the key things is in spite of all your personal responsibilities, all your work related responsibilities, taking out time for yourself for X number of hours in a week should be the motto.

9:19
And I keep like X number of hours every week that I am going to study for these hours to upscale, to know more about what’s happening in the industry, even if I’m not able to spend time in the weekdays, but at weekend, then I’ll spend that time.

9:33
So if you build that planner in the beginning of the week, that I need five hours saved for myself in this week, you will make sure that you will take out five hours either within the work schedule during weekday or weekend.

9:46
But if you have the target, you will do it.

9:48
So do not go blank that I’ll do when I have time.

9:51
So do not go in that way, go more planned plan for your hours as well.

9:56
In addition to work, then there’s nothing that can stop you.

9:59
Yeah, they say failing to plan is planning to fail.

10:02
So I think you made a really good point about how adding it to sort of your schedule on a weekly basis is important.

10:08
You can’t just like, you know, keep the information and the new knowledge being pent up for a later time in the future, just having it on a weekly cadence or like, you know, certain hours every couple days is very important.

10:20
So, I’m really glad that you shared that and I think that’s a big secret to how you’ve been able to sort of last this long in this industry also.

10:29
So, you know, gives huge credit to what you’re doing and surely it works.

10:34
I wanna dive deeper into, I’m sure you’ve been a part of a lot of large scale big data projects and like, you know, projects of different sorts.

10:44
So what do you think are like some of the bigger challenges that come up with when dealing with data?

10:53
So see a couple of challenges, right?

10:55
When we deal with data, one of the key things is the knowledge.

11:01
So you need to have good amount of knowledge on the subject that you are working on from technology standpoint.

11:09
The other aspect is where I think the data initiatives at times you start great, but then they die out is when you don’t combine them with the business domain knowledge, data is based if you are not able to start making sense for business out of it, so that I think is a very, very important juncture.

11:29
So the challenge is your team structure, either it is with clients or within your team, it has to be such that you have good technology knowledge, within the team, you have good business understanding as well.

11:42
So that what you are doing, you can actually relate to how it is related to business and how is it going to impact them?

11:47
So that is the second one and the third one which I have seen has worked really well is the diversity in the team.

11:55
Now, why I’m saying diversity in the team, when you are thinking of data led solutions at that time, what you are doing is in most of the cases, we are looking at data of the end users for that business.

12:11
If you don’t have diversity in the team, whatever you are doing, you are doing with technology mindset or with one mindset that you can perceive how users might be thinking about it at that time.

12:24
Like for example, if you are dealing with say data for a brand in beauty, if you have all male people solving the technology problem and imagine they can, they can create good solutions for technology.

12:39
But then when you have to apply the lens to analyze this data and see what is making sense for business.

12:45
At that time, a diverse team would have helped better because they can bring in a real user viewpoint there.

12:50
So if you have to analyze data, you can really bring in and find out those triggers in the data from an end user perspective.

12:57
Right?

12:57
Similarly, the other example, it’s not just gender diversity that we talk about, it can be even from the perspective of you’re building an application, you want to create an experience on the basis of data.

13:08
If you have certain people in the organization who can help you to check your application from the people who are differently abled, that will give you an edge because now you are making an application for everyone and not just a bigger section of our community and leaving out some section.

13:27
So that is where technology business is definitely the key but diversity also helps you to cover from the end user landscape as well.

13:36
I think these are the key pillars and sharing of data.

13:40
Honestly speaking is one of the biggest challenge.

13:42
when you deal with data, mostly you will come across like the pi I data now, can organizations share it?

13:51
Do you have enough skills on how to handle this data?

13:54
What are the constraints that you need to have?

13:57
How do you restrict access?

13:59
How do you encrypt this data?

14:01
So all of that becomes a very, very complex challenge in the whole setup of the things.

14:06
So one is the team part second is the security and the understanding of the data from that perspective.

14:13
Definitely.

14:14
And I think that’s why a lot of like, you know, even in the USA a lot of the compliance and audits are being done just to ensure that this aspect is secure.

14:21
Because like any data that’s private and confidential cannot be just used without knowing, having the knowledge and knowing how to even dispose of it correctly.

14:31
If needed.

14:32
Exactly.

14:33
Yeah.

14:33
And as a consultant, you should be bringing up those points when you are working on an engagement. The client may just say there is compliance that we need to follow.

14:42
Yeah, but that’s just one statement.

14:44
But within data, what does it really mean?

14:47
So that is what as a consultant, you need to be very up to date with and bring in those questions yourself.

14:52
Is this the right data to be shared?

14:54
Can I do this with this data or not?

14:56
So you need to bring it up as a consultant, clients may, may not bring it that granular level of information and see a lot of these data projects.

15:05
What I’ve noticed is that it also takes longer periods to execute.

15:09
So it could, some could be like, you know, 12 months long, some could be nine months long.

15:14
And in this time, how do you sort of when you’re working with either your clients or within your teams?

15:20
How do you ensure that business value is added in such cases to see one in the current world if you talk to client and tell them that it’s going to be like a 12 months or a multi year program and you will see something by end of 20 months, they’ll shut the doors, I’m telling you right?

15:45
Because a is the way.

15:47
So in case of data engagements, what is ideal is two lenses you can apply.

15:53
One is any low hanging fruits because those are the ones with which your clients can start seeing value earlier.

16:02
So something is already there.

16:03
It’s just that you need to position it in the right way, do the right things with that data.

16:08
So that’s a low hanging fruit for you for the other aspects.

16:11
What I generally prefer to do is break up the whole big project into smaller pieces and see how you can measure value out of it.

16:21
If you don’t do that at the end of 12 months, when you start seeing the value, maybe the value parameters have changed in that long time.

16:30
Yeah.

16:30
Right.

16:31
So having those smaller chunks and having measurable metrics to measure the value is something which is really, really important.

16:39
So start creating a backlog, but the backlog has to also be managed in a way that with this backlog here is one chunk and this is how it is adding value to business.

16:51
This is what will cause investment.

16:53
So you can have a certain scoring mechanism there and that will help you to even prioritize.

16:58
So where you are getting more value, maybe effort is less or here, the effort is more value is less.

17:03
Let’s start prioritizing.

17:05
So if you do that in small pieces and chunks that will help you and it will also help you to know the dependencies also upfront.

17:13
So there will be no surprises, you know, in two months time, what I’m doing is I need to deliver this value.

17:20
You will aim for it and you will be able to measure it.

17:22
If you are not meeting that value, you are slightly behind your next iteration.

17:27
You need to do that and make sure that you are then doing the right things to make sure the value is getting generated there.

17:34
So it’s like a smaller pieces.

17:36
Check the value.

17:37
Yes, it is attained.

17:37
Move forward.

17:38
No, it not.

17:39
No, it is not attained again.

17:40
Go back, look at your backlog, refine it and then start working again.

17:43
So this whole cycle of repeated value check is what can help you to continue to deliver the continue to deliver value in smaller pieces rather than big bank.

17:54
Yeah, I think having those many milestones is very important for like the business side, but also the team that you work with.

18:00
So it keeps up the momentum of going forward.

18:03
And I think you mentioned some great points about like good project management essentially of like, you know, what should be done in the beginning, how it should be managed to sort of make sure that the entire flow of the project goes well.

18:16
again, like you said, there’s a lot of times when like, you know, even by the end of the period, like the impact that you’re trying to make changes, the metrics can change completely.

18:25
So keeping track of them throughout the engagement is truly essential.

18:30
I think I wanna dive deeper more into a little more of a personal side here.

18:37
as you know, how do you think your journey has been as a woman in tech starting out from like, you know, a java developer that also being tagged to now working severely in data and also like, you know, managing so many people.

18:53
So definitely, you know, reaching a lot of success in your field.

18:58
How has your journey been?

18:59
Has there been any like, you know, challenges that you faced when you started out or like, you know, as you were going through your journey?

19:08
So yeah, I think no journey is without challenges.

19:11
The flavor of challenges can vary from person to person, right?

19:16
So a few weeks back there was an article in Times of India where I shared this story with them as well.

19:24
It was again for women in tech that I shared this story.

19:27
So see the hurdle started when I was in college.

19:34
So I was in, in a way I was lucky that my parents were all supportive with what I wanted to do.

19:40
But then it is the environment and the community where you will always find forces which are towards you and which are against you.

19:49
Right.

19:49
Right.

19:49
So I have when I was in college, I I was doing electrical engineering and I started doing my computer, course, three year diploma side by side.

20:00
But during four years of engineering I did three years of diploma as well in the same time period.

20:06
And my day used to start at like, seven in the morning and end up at like 9, 10 in the night.

20:11
I used to be, like, on the road after my college from 4 35.

20:16
I used to go to my,, computer center, be there, do my programming, coding, study, create my project and then come back by 8 39 10, whatever time it is, right?

20:27
So now imagine those years back, right?

20:29
So like 15 years I’m in industry and then it was college.

20:32
So almost around 18, 20 years back.

20:36
I was like out of my home for like full day time, night time at home.

20:42
So yeah, there were courses against it like, oh why girl has to do so much, right?

20:47
But I was very clear that I want to do something in the technical field.

20:51
with my background, my parents, my father was into technical field.

20:56
My brother was similarly an engineer.

20:58
I was pretty clear, I want to do that though.

21:01
Everybody was telling me, what will you do with so much of studying and whole day roaming around?

21:06
Why did you get into education and start teaching?

21:09
And I was like, no, I don’t want to do that.

21:11
My aspiration is to get into technology.

21:13
And work in a good firm.

21:15
Right.

21:15
So, yes, there were those challenges that I faced.

21:18
Then I got into the organization.

21:21
Luckily I got into a good organization.

21:23
And that is where I started to live my dreams.

21:28
Right.

21:29
And I started getting opportunities that I wanted to work on.

21:33
then came a life stage change.

21:35
You get married and then you have a baby.

21:38
Now what to do?

21:40
And that is the time when you really start thinking yourself because the way we all are grown up, especially in India, you feel like it is your total responsibility and your only responsibility to take care of the family and career is secondary, you can make compromises there.

21:59
So before anyone else can tell you, I think most of the girls, they get into this feeling that am I doing the right thing by continuing for my career?

22:08
And I, I was no exception.

22:09
I had those challenges in my journey as well.

22:13
But then the thought that got me going was why I should stop doing anything that I love doing.

22:22
Can’t I do both the things in parallel?

22:24
But maybe I go slow on my professional career for a few years when the kid needs more time.

22:30
And then I go full fledge again because the scariest thought I’m honestly telling you to me was after 78 years, when the kid will grow up and the kid will be on her own.

22:40
What will I do?

22:41
Where will I go back?

22:43
That was the scary.

22:44
Just thought that always got to be a lot of gap from your career also if you decided to completely stop.

22:50
Yeah.

22:50
Exactly.

22:51
Right.

22:52
So now there are like so many such programs that organizations have where returning mothers get support.

22:57
But at that time, it wasn’t so much of the talk of the town.

23:00
Right.

23:01
If there is a gap, there is a gap.

23:03
And that used to scare me.

23:04
Like if for say 56 years, I stopped working, then for me to get back into the industry will be very, very difficult.

23:11
So that was another challenge which every day was coming to me.

23:16
And then I was like, no, I have to do it.

23:18
Let me continue to see how I go forward.

23:21
And one of the lessons that I learned was if you are going slow, you are still making a progress.

23:28
It is just that at your own pace, think of your priorities, what you want to prioritize go slow on one end if you feel so and that’s absolutely OK.

23:38
And stick to your decision.

23:40
I, I took those decisions.

23:42
I went a little slow and on my professional journey.

23:45
Then once the kids grew up, the advantage I got was they saw me like working so hard.

23:50
So they themselves imbibed those things knowingly unknowingly, they invite those things and now they are the ones who tell me, why don’t you go and work full out.

23:59
Yeah.

23:59
Go for the trips, go for your meetings.

24:02
You don’t have to wait for us.

24:04
We will manage on our own, right?

24:06
So that is how you start getting the results later.

24:09
But at that time, the journey is difficult.

24:11
So challenges are there and especially then comes the challenge of, oh, am I lagging behind from others?

24:18
It is ok.

24:19
You are not in a race for everything.

24:21
Yeah.

24:21
And I think you made a good point.

24:23
You’re not like, you know, competing against anyone but just yourself.

24:27
So if you’re getting better every single day, even if it’s making baby steps or some steps every single day, that’s better than not doing anything at all.

24:34
So, yeah, I think that’s wonderful and that’s really inspiring to see that, you know, you continue the ro despite so many challenges, would you happen to have any advice, like, you know, just a closing advice for other women or other people sort of getting into these industries, regardless of the gender?

24:52
Yeah, I guess anyone in this industry, right?

24:54
So the industry is always changing so be prepared that it is a changing world.

25:01
And if, if you want to be having a stagnant life, this is not the industry for you.

25:08
And in this industry come with a full rigor.

25:11
That change is the only constant for you.

25:14
Give time to yourself.

25:17
Make sure that you’re taking out time for yourself, either for relaxing, for study, whatever it is taking out time for yourself is the key to continuously grow in this industry.

25:28
I think that was really, really beneficial like this entire session has so many nuggets of like, you know, information that you shared with us today.

25:39
So thank you for taking the time to do that.

25:42
I think I personally really enjoyed this conversation and I’m sure that our audience today did as well.

25:49
So, thank you so much again.

25:52
Thank you.

25:53
So, this is a wonderful session with Farm and I hope that you guys catch us on our next session.

25:58
Thank you.

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