Kirsty Neal

Senior Data Analyst, Bliss

What does your job entail?

My charity, Bliss, supports premature and sick babies and their families. To do that we are given a lot of support by people who fundraise for us, who campaign for better services, who volunteer in neonatal units and on our support helpline. That all generates lots and lots of data. My job is to make sense of the data so that we can better understand our supporters, to encourage them to continue to support us and also to find other people like them so we can continue to grow support. That all goes back towards helping those babies who are born premature or sick.

What do you like best about working in data?

I love working in data because a lot of the time it’s like solving a puzzle. I have all these parts and I have to put them together and work out what it’s trying to tell me. Then I have to be able to share that with people and explain it to them in a way that they can understand. I also love working across the whole organisation and with all the different teams – there isn’t a single team across my charity that I don’t work with.

What is the biggest challenge you face in your role?

I think being able to say no to people, especially where it concerns data – people always think that I’m going to be able to pull out all of the answers and sometimes there isn’t enough data or it’s not going to tell people what they actually want to know.

What’s the best advice you’ve been given?

The best advice I’ve heard is: ‘done is better than perfect’, which I think is one of the mottos they use at Facebook. I’m such a tweaker – I never want to finish a project and always think there’s a bit more I can do here or there – but meanwhile people are waiting for an answer. It’s learning to let go.

You still need to be able to look at people as individuals and not let statistics inform your prejudices.
What significant object have you chosen?

My significant object is the book Generation X by Douglas Copeland. This is a book that came out in the early 1990s and it’s supposedly about me, because I am slap-bang in the middle of Generation X – I was born in the early 1970s. Generation X is the very small generation squeezed in between the Baby Boomers and the Millennials, and we were called ‘the slacker generation’. What I find interesting about it is that none of the people in this book are actually very like me at all. I’d say it’s a warning to people working in data to not put too much store by generalisations. You still need to be able to look at people as individuals and not let statistics inform your prejudices. This book said that everyone in this generation was a slacker and wasn’t going to amount to anything but I think we’ve proved them wrong.