Episode Fifteen: Answering the Questions That Matter

Making Data Simple and Actionable

Virginia Falcon and Nadia Sotiropoulou from Google’s Measurement & Analytics Team joined us for this episode recorded at the Women in Data conference. They shared their passion for making data actionable and focusing on answering the questions that matter.

Listen or click on 'subscribe' below for links to subscribe directly via your favourite podcast platform, including Apple, Google and Spotify.

Read full transcript

The Power of Data Podcast

Episode 15: Answering the Questions That Matter

Guests: Virginia Falcon, Head of Measurement & Analytics, Google
Nadia , Sotiropoulou, Measurement Lead, Google
Interviewer: Louise Cavanagh, Communications Director, Dun & Bradstreet

Louise Cavanagh 00:00
Welcome to the Power of Data podcast. Today, we're excited to be at the Women in Data conference in London. And I'm delighted to be joined by Virginia and Nadia from the measurement and analytics team at Google. Welcome to you both.

Guest 00:11
Thank you

Louise Cavanagh 00:12
Great to have you here. I know you're both big ambassadors of Women in Data. And when Roisin and Rachel spoke to me about you guys coming on the podcast, they were super excited and said that you have their biggest fans and you will work together really well, and champions of diversity. Virginia I know you were hot off stage. And you talked about the importance of I think finding your purpose and voice. I just wondered if you'd give our audience and our listeners what you shared with the wider audience out there. I know you've just been speaking to a four-digit audience, as we’ve just discussed. Just a little bit of highlights and the snippets.

Virginia 00:43
Yeah, well, to be fair, I have to be honest, I didn't take the brunt of the work. So I shared the stage with Gill Whitehead, who is a great mentor for both Nadia and myself. She used to run the client solutions and analytic organization. Now we're both part of Google. And then well this woman who has had this has had this amazing career. So she was sharing stories very personal stories, actually, which was really interesting to hear about her career and how she's got to where she's got, and tips that she's got along the way. And it was a very refreshing human story, because you could expect that somebody with her journey will come in and just show everything as perfection. But actually, she was quite conscious about the things that didn't work and was actually quite transparent at it. And then she wanted us part of her story to include somebody on the team that will come and give a view of how you've taken your journey because she definitely takes it very personally as a responsibility to help other people on their way, what she calls the glass escalator. So how we can throw the glass ceiling is not about just one woman, making it to the top but actually helping others move upwards as well. So she was extremely generous to share this stage with me and then in turn, and because it was such a personal career talk from her side, then it became a very personal story for me, which is actually quite surprising because typically I've been not done four digits, but let's say three digit talks about before, and it's typically about what I do and data and the work that I do, which is fine. I guess I'm comfortable in that. But this was definitely taking me out of my comfort zone where I have actually to go back to my origin story almost in five minutes, and then give it sense of what is it that we do in the team as well. So yeah, that was quite fun.

Louise Cavanagh 02:16
Great, so Nadia you obviously work with Virginia as well. So can you maybe start off and tell me about how your current role and how you've ended up in it in a data related career?

Nadia 02:25
Yeah, I'll answer the last question first. And so as I was growing up, I was really interested in maths generally a lot of the technical subjects, but I also really enjoyed psychology and understanding the human side of how we make decisions, how we interact with others, and the ups and downs of our psychology. Although I really liked that, and I kind of wanted to go down that career, I didn't feel like it would suit me so much to become a therapist, maybe I didn’t have the right patience. So I thought, actually, maybe I should pursue the mathematical side. And so I started economics. And from there, I was really lucky to fall into British Government economics. And so I started my data career through there, they're really trying to understand how we can use data to drive policy decisions and to inform ministers. And then just, you know, trying to diversify my experience, I wanted to enter the private sector. So I worked in a couple of companies both publishing company and retail company, before I was then lucky enough to join Google and work with Virginia. So to answer your first question about what we do, please jump in Virginia to give you a flavor to but the best way I can describe it, essentially, we work with some of Google's biggest UK advertisers. And the way in which we help them is to enable them to better understand the impact that their advertising dollars are having on their business. So what is the impact? What's the return on their investment? And how can they improve that? And the reason why it's an important job for from Google's perspective, is because it's a very complex landscape. There are lots of tools, lots of data, lots of ways in which you can evaluate the impact it has. So it's hard to navigate that and we like to support our clients with it

Louise Cavanagh 03:55
Obviously at Dun and Bradstreet we've got the sales and marketing side of our business as well. So it's something that's really interesting to us around the advertising piece and promote with programmatic. It's just, it's such a different landscape now than it was 10 years ago. And the way we use data is just going to go more in that direction. And we're just going to have so much more and that's something Virginia, that would be great to get your insight on in, in terms of the amount of data that's now out there. How do you and the team go about focusing in on the ones that can provide you as a business with the most insight and the most value? It feels like there's so much data now? How do we even tackle the amount that's out there?

Virginia 04:28
Yeah, I think sometimes in the data field, to be fair, and I've been around for a while. I don't want to disclose my age from really well more years in the data field, or at least up. So sometimes people get obsessed with complexity and like all of the different sources of data that you have an old data points, it's amazing. We can understand so many different things. But I guess the best analytical advice that I given to people is make it simple. Sometimes you don't need absolutely everything. But actually the things that matter. So obviously the more you can canvass and try to cast the net wider in terms of what could be telling you something, but then establish the things that actually have a direct impact in the question that you're asking. And then make sure that the modeling of the methods that you're using, I wouldn't call them simple but transparent enough so that you can explain it to people, because we're asking businesses to make huge decision while an individual is based on data. So we need to make sure at least my experience with clients is that we need to make sure that we're able to explain this to human beings in a simple, digestible way so that they're comfortable making those decisions on top of it. So I guess my personal take on data is, yes, we have loads and we've continued to develop all the infrastructure, the methods, and the talent, hopefully, and this is what this conference is doing that is able to mine that data. But at the end of the day, we really need to go back to what's the question that we're trying to answer, and what’s the things that really have the most direct impact to it. And then how can we make this, well how can we bring it back to that original problem, I suppose, to make it overly complicated without a need?

Louise Cavanagh 05.58
That's really interesting. It resonates with me, obviously I'm not a data analyst, I'm a communications person. But that's almost like a skill that you guys have got to have in your arsenal as data professionals is that it's about how you communicate those insights from the data that meets the objectives. And I'm always kind of thinking about how to make something simple and easy to understand. And there's a real range of skills in a data career that you need to have. It's not just about knowing the numbers and, and the programming and things like that. It's communication skills, it's much wider.

Virginia 06:32
Well, have you seen most of the program here at the Women in Data conference, which has been absolutely amazing. It's been more about a career reflections and communication tips for professionals in data. So again, we could have spent the whole day talking about machine learning, and there's been some bits of it, but ultimately, a skill that is vital in the data community is the ability to communicate that back and then to make sure that the data and the insights that we're bringing have impact and change the way that we run businesses today and for that we have a big responsibility on our shoulders, which is not just about being the best coder that you possibly can be but also how do you make it simple and actionable for other people,

Louise Cavanagh 07:01
Yeah. And talking about that, Nadia from your side in terms of the increasing automation, the technology, machine learning, AI, is that really changing how you as a team have been working in your previous experience within the government? Have you seen a real change in in how data is managed and processed? And what's that been like being sort of on the front line with that?

Nadia 07:17
Yeah, you can certainly see that there's more and more tools out there that utilize some of the automation and technological and even vastness of data much more effectively than it used to. I mean, our ability to process huge amounts of data has changed our ability to store huge amounts of data has changed. Cloud has really also improved our future and how we can utilize all that. And I'd say the hard bit about that is keeping up with it and actually making sure that your skills are up to scratch that you understand it well enough to know when you want to lean on it when you need to include something newer that's out there, but it's certainly a very exciting space, and so it never gets boring.

Louise Cavanagh 07:53
Yeah. And Virginia, sort of linked to that, there's been you know, headlines about the robots are going to take our jobs and all this kind of stuff. And I think the data industry is probably one that people would look to for that. But from what I've read and my experience of working with the colleagues at Dun and Bradstreet, because of the pace of change and the new technology and the new methods, there's more demand than ever for people with the right skills to understand that and to stay ahead of the game, as you were saying,

Virginia 08:16
Yeah, I guess I've actually I cannot claim this to be mine. But I was at a talk recently, I don't know who was talking about it. But I think it was a guy who had a big head in cloud, he was saying, oh, the first time that computer won at chess with the best chess player in the world, we thought, Oh, this is it we’ve cracked AI, we actually know everything there is to know about AI. And now the computers have taken over. And the reality is chess is a pretty simple setup. You can teach a machine all of the rules of chess, and then all of the strategies and then it's fairly simple for a computer to sort out that problem. I think where the humans come in is actually framing those problems, and then directing the robots to actually go and fix that a or to solve the puzzles that we cannot solve on ourselves, but we still have a huge role. I can tell, we've obviously seen a lot of progress. And we continue to see progress of what we can do with AI. It's amazing and what the things that we will be able to achieve in the future are definitely encouraging. But the way that it works is that we need to point it to the right problems too, we actually need to explain the rules of whatever game is it that we're trying to solve whatever puzzle, and then he will come in and be really valuable. But we're not at a stage yet where the robots are ready to take over on everything. But just the problems that we point them to,

Louise Cavanagh 09:26
There's always going to be that that human element and we need that level of subjectivity or objectivity. My brain is dying today, but whatever the right word is, I think that's always going to be there. We can work in partnership rather than be scared of the takeover of the robots

Virginia 09:41
Yeah.

Louise Cavanagh 09:41
Cool.

Nadia 09:42
There’s a movie in that.

Louise Cavanagh 09:44
So I wanted to just get back to sort of the theme of today. So I know, you guys are really involved with Women in Data. And I think you recently hosted a meetup session over at Google. So both of you being females in the industry, have you experienced barriers yourselves or do you think there's been a change in the sort of approach and the balance and diversity in the industry?

Nadia 10:05
If I may, I want to introduce because we started just going on to the topic of women in this organization, I just wanna say a couple of things about how amazing it is. So, you know, Virginia and I are really fortunate to be working in a place like Google, we do have a lot of opportunities, but not every business does have access to all that resource. And the reason why Women in Data has a really big place in my heart is because it's free, it's covered by sponsors. And so anyone can apply and come and you don't have to have access to loads of resources to get all this information and hear all these incredible speakers and the amazing stories and messages and the network that is involved in it. And so that's kind of the passion behind why moving to Google both Virginia and I saw the opportunity to support that that initiative and I think it'd be amazing if every industry had similar free events because not every industry has these free events, usually even if they're free there’s some commercial message in it. And I don't feel like that was the case today

Virginia 10:58
It’s a huge labor of love. So for us has been a real interesting journey working with Roisin or Rachel and see their devotion to this cause that they do as a side job, I think and then all of the volunteers that come together and the fantastic network of people that are really supportive is that's really inspiring.

Louise Cavanagh 11:14
I was gonna say about the volunteers and the red t shirts, but actually, there's quite a lot of people in red because red was the color today to celebrate their fifth anniversary but there's, there's a huge amount of people, they really don't struggle to get volunteers.

Virginia 11:26
Well actually in the morning. So it's a fantastic network. Really, when I came in in the tube this morning, I was like trying to like I didn't have signal on my phone and I don't live in this part of town at all. So I was trying to find out which way I had to go. And then I was relieved to see how they had people with like banners telling people where to walk. This is so organized and then the guy who was holding it actually he come to the meetup that we did a Google three weeks ago and I spoken with him he really nice guy. And he was just there with it. Like it's not even a woman. He's a man and he's yet like, yeah know, after talking ourselves, it's amazing that you volunteer here. He said, Yeah, I came to the meetup. I was really inspired just came to the organizers and said do you need any help, I think this is amazing, how can I help and then he ended up guiding people to the venue, which is amazing. So yeah, I think was kind of become a movement. So everybody wants to do their bit because we all think is a really nice thing. So

Nadia 12:11
You make a really important point. So like our joint manager, Harry, who's a huge supporter of every sort of diversity, and he has hugely supported this initiative, his mantra is because he recognizes he's a white male, middle aged, you know, fairly privileged. And he says, the thing he finds is helpful to do in terms of encouraging and helping minorities is to just ask, How can I help literally, it's just the one thing he does is just tell me what I can do to help even if it is just, you know, a menial task, but he uses the example of inflating the balloons for our LGBT groups events or something like that, you know, it doesn't have to be something huge, doesn't have to change the world, but actually showing support by just asking the question, how can I help you?

Louise Cavanagh 12:48
And just being there? That's really good. So later on today, we're talking to some young girls. And when this goes out, it will have been announced the girls in data initiative, which I think is really important. Then a few of the people that we've talked to today have shared personal stories about, they've got daughters, or they've got children, they want them to feel that there's no restrictions on what they can go into. And they shouldn't see certain careers as not for them or having, you know, loads of restrictions and barriers to it. I just wondered whether there's something from each of you that you would like to say to those girls considering a career in data? Is there a piece of advice that you've had, perhaps, in your career or something, to inspire them to, to work in data, why it's so brilliant to work in have data?

Virginia 13:33
I think it's definitely a very exciting field. I mean, the data skills are needed across almost every role. So it's not a big data roles. Everybody needs to like at least a Google everybody needs to have some fluency with data to do what we do. So I think A) there's demand for it. So it's a very exciting field, it's not going away. So definitely very highly ranked, I think at the top of like, interesting careers to go to and then second, well, I guess, just believe in yourself and what you're good at. So even when other people might not think but if you like doing something and just push on it, don't be convinced by others that there's things that are more appropriate and just trust on what you're good at. And I think with those over time, you'll find also people that believe in it, and then they'll push you up. But yeah, just find enjoyment in what you do. And if you like numbers and data, physics, or that sort of thing, if you're interested in computers, and then please come and do data jobs.

Nadia 14:25
I would add also, you know, if you're thinking about and you're unsure of whether to do it, you know, almost everybody I know who works in data would be happy to talk about their day to day and what it really looks like what are the fun stuff and what are the less fun stuff and so utilize that. I would say if a parent is worried about their daughter thinking about it and they want to know more than you know, I mean Virginia and I would certainly be happy to chat to anybody.

Louise Cavanagh 14:45
There you go listeners it’s an open offer.

Nadia 14:49
And the other thing I would say is data is a very diverse area and the number of professions that fall under the banner of data is huge. It could go from a really, really technical job. When we talk about data science or data engineering, but you can also go into the kind of job that requires a lot more of the human side and understanding how consumers behave or how, say in a charity, how people are using different services in that charity and how the services can be improved. That's the kind of research side of data, a data job. So there's a lot there. And so you can give it a go try different professions, talk to different people. And at the end of the day, if it doesn't suit you, then as Virginia said, there's some skills you've gained that are useful for pretty much any job. And it will certainly be an advantage to have those skills under your belt.

Louise Cavanagh 15:33
I'm sure there's lots of people listening, that would be really useful to. I think we could talk for ages. I’ve had real fun with you guys. But I know we've got limited time today and you need to get back to the conference. So just wanted to say thank you to you both. Congratulations on your speaker slots. Yes. And we'll see you again for another Power of Data podcast soon. Thank you.

Both 15:52
Thanks for having us.