Beyond Your Research Degree

Episode 4 - Dr Caitlin McDonald, LEF’s resident Digital Anthropologist

April 27, 2020

Welcome to the Beyond Your Research Degree podcast from the University of Exeter Doctoral College! The podcast about non-academic careers and all the opportunities available to you... beyond your research degree! In this episode PhD student Debbie Kinsey talks to Dr Caitlin McDonald, a University of Exeter alumni who now works at the Leading Edge Forum. Today Caitlin is recognised for her domain knowledge in qualitative methods like ethnography and participant-observation. 


Music from ’Cheery Monday’ by Kevin MacLeod ( License: CC BY (


Podcast transcript


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Hello and welcome to the Beyond Your Research Degree podcast by the University of Exeter, Doctoral College

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My name's Dr Caitlin McDonald.

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I graduated in 2011 with a degree in Arab and Islamic studies from here at the University of Exeter at the Institute of Arab and Islamic Studies.

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And hard as it is to believe that it's now nine years later.

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It's it's really interesting to look back on what's happened since that time and

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consider the skills that I took away from the university and how I'm applying them now.

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So maybe to give you a bit of an update on where I am. I currently work as a digital anthropologist at an organisation called The Leading Edge Forum,

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which does technology and strategy research for large businesses and just in the

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Last month I was at the UN delivering a talk at the International Labour Organisation.

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I then hosted a dinner at the House of Lords about ethics. And I've done a range of interesting and exciting things since then.

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But it's really interesting to think about this particular month in particular

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and how that the kind of culmination of where I started and how I got here.

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So I started working at the Leading Edge forum about two years ago, and before that I was based at what was the Times educational supplement.

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But it's no longer known as that it's just the tes

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It's no longer owned by the Times, where I was working as a digital analyst, data analyst and working with data systems quite a bit.

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So all of that sounds really different than where I started, which was very much middle easy studies based, but really the kind of the through line.

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The thread for me was that a lot of the research that I was doing when I was doing my PhD was very digital ethnography based.

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So I was looking at patterns of knowledge and how they shift around the world, in particular for dancers who often for Middle Eastern dance,

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want to base their practise or to base the centre at the hub of their knowledge in Cairo or sometimes in Turkey or in other kinds of regions.

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But in my particular case, I was looking at dancers who had a dance tradition that is based out of Cairo.

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And what ended up happening was I did a lot of ethnography around in particular how people were using Facebook groups,

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but also other social media channels to spread the knowledge and in the creation of knowledge

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about how the dance kind of mythology and epistemology of what the dance meant to people.

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And while this doesn't sound really revolutionary now, way back in 2006, 2007, 2008, when I was first doing that, that was fairly new.

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You know, there weren't a huge amount of digital humanities tools at the time.

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And certainly we weren't using anything like this wonderful lab that we have now. I think this was the old print print shop at the time.

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So it was really interesting. But then what ended up happening is I went to do a very quantitative role,

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which when you become an anthropologist, you don't necessarily think of yourself as a quantitative person.

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Some might. I did not. But it was having that kind of digital skills component that really was able to help me make

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the transition from a very academic role into a much more kind of commercially minded role.

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And I didn't really intend to leave academia, but around the time that I was leaving, there were huge budget cuts.

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So there simply weren't the kind of resources available for people to have postdocs and subsequent academic careers in particular.

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As an immigrant to this country, I was I needed to have a role if I wanted to stay working here.

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That was not short term. So it had to be a Full-Time full contract.

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And luckily, I was able to find something that worked out, which was with the Tes

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and they really wanted someone who could help them to an extent of their research skills.

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But a lot of the role was really about the kind of Day-To-Day operational knowledge to help the business run.

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So that was very, very different from what I previously been doing.

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But having this kind of interrogative skills, those kind of basics of a humanities research skills,

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those basic social sciences research skills was really helpful or for doing things

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like helping question why a particular thing was being done in a particular way.

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In particular, I was doing a lot of kind of daily reporting of what was happening on the website and what kinds of numbers

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were coming back in terms of circulation and all those kinds of things that digital businesses do.

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And really, the thing that was extremely useful was being able to turn around and say, hey, is anyone actually reading this report?

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You know, something as simple as this ritual that we go through on a daily basis of producing these numbers.

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How are they feeding into our decision making?

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And in some senses, that questioning was perhaps not always very welcome, but it also was that helpful to create the conditions for change.

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And I think that the social sciences are not always really great about talking about

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the transferable skills outside of academia that absolutely do exist.

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And I think now we're starting to see in particular with another research area that I do, which is all around ethics.

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You're starting to see some of those kinds of questions emerging around.

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Who is in charge of this knowledge or what are the kinds of different weights that we put on how we assess particular aspects of

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artificial intelligence and its relevance and its usefulness and how is it relevant to and who's benefiting and who's not benefiting?

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And I think that having a general social sciences research background, regardless of whether your specialism is in ethics or in,

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you know, particular aspects of digital technologies, you know, having that kind of questioning mind is is a really useful thing.

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And I think that people who work in digital context are starting to appreciate those qualitative skills,

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again, in a way that perhaps has been a little bit subsumed recently. So those kinds of questions around how is this going to benefit not only direct

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users of our services or our products or whatever it is that we're building,

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but also that kind of contextual knowledge about how is this affecting other people who are going to be impacted by the decisions that we're making?

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There is renewed curiosity and interest in those kinds of decisions. And so increasingly, organisations,

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businesses and non-commercial organisations are looking to the humanities as well as

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engineering to to make up the body of knowledge of creating those products effectively.

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So I would say now is a really good time, actually, to be in the digital humanities.

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And to some extent, no matter what you're doing, your work is always going to have a digital component.

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So recognising that, you know, when you think about the degree that I did,

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which was very much based in transmission of knowledge and very much about dance,

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you wouldn't necessarily think that that would lead to where it did lead. But in other ways, it makes total sense.

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It was a logical chain of transmission. I was looking at the social components of how that knowledge was happening.

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And now we are even more immersed in digital technologies. Our careers are even more immersed in this, no matter who you are.

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So having that background of having done that, kind of that kind of study was really useful to get me where I am now.

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Yeah, it sounds really interesting. So it sounds like so

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all PhDs are very specific so yours was around dance and transmission of knowledge between dances and creation of knowledge in that way.

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But then it sounds you talk about thinking about things, those things more broadly in terms of the general skills we develop.

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And how did you find translating those things from kind of academic speak to then going into a non-academic, non-academic role?

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Yeah. I would say that initially it was a real challenge for me, partly because when I first was looking for a job,

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I still was applying for a very academic roles, as well as starting to look beyond that.

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So I was looking at a lot of roles in market research. I was looking at the National Centre for Social Research.

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I was looking at ESRA U.K. you know, you go places like that and they have a more kind of traditional, I would say, research bent.

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Whereas if you if you move into, you know, user research and a company, for example,

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and most organisations do have a user research arm if they have a digital component, even if that's not their kind of core business,

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but that the language of that is very different from what perhaps you might be talking about

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if you're coming out of the social sciences or have a real kind of pure research background.

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So but the advantage of being an anthropologist or a sociologist or someone who

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studies the way that people think about knowledge is that you can then apply

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all the research skills that you have to your own situation so you can notice

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the kinds of patterns of knowledge that are happening in your organisation.

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You can notice the particular language that people are using around things and say, OK, you know, this group is talking about doing AB testing.

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You know, I might describe that differently in my own historical research background or whatever it was.

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But actually, the actual things that you need to do, the mechanics of the research are the same.

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So simply learning the kind of patterns of the patterns of life and work in

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the organisation that you find yourself in is a really useful skill to apply.

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So I spent probably two or three years mostly working in a digital engineering team.

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People that were doing actual software creation. And my role there was to assist with data migration that was happening.

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So we essentially had a place that we'd been storing all of this hard quantitative data

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that we were collecting over the years about how that Web site that we had was being used.

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And then we were changing everything about the underlying infrastructure and technology that we had into a completely different data storage system.

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And my role is to make sure that as we were doing that, nothing got lost.

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The data was collected in the same way. Nothing was missing.

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Nothing suddenly looked out of place. And so part of that was doing things like mapping the infrastructure from how the old data system work,

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doing what's called an entity relationship diagram, and looking at what the new entity relationships would be.

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So the places where the data was collected from the stored.

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And as I was doing those, I was like, this is a lot like doing essentially is family tree diagrams.

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You know, it's very much the same thing where you're looking at where are things transmitting from A to Z.

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So you can use all those kinds of same skills. And also just the kind of.

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That sense that I would get when I would go in and if I didn't know what people were

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talking about or if I felt like there was something unspoken or something happening,

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I didn't quite understand, I would behave exactly as though I were doing ethnography with a community,

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which is to try and treat the knowledge that I was a part of as being something that was that I was studying, you know.

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And so kind of having that observational hat on.

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First of all, it really helped defuse some situations that could have otherwise been quite personally demanding.

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Because if you just view it as I'm learning about what's going on within this group,

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then you're kind of personal sense of responsibility about that while still high because you were working there.

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It doesn't feel quite so rooted in your own sense of identity, I suppose,

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because you can also treat it as I'm viewing this as objectively separate from myself.

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And also then, you know,

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eventually you will pick up the lingo and you will learn the skills and you will realise the patterns that are happening within your organisation.

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And that's really helpful for putting the right pieces in place at the right time to achieve the things that you want to achieve in your career.

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Yeah, yeah. It's kind of like learning the language when you're there using those skills.

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You already have to kind of pick up on that. Precisely.

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Yeah. And how did you find it kind of before that stage, kind of making applications,

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trying to write and tailor things in such a way that you're using a language you're not quite sure of yet?

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And kind of that probably is the hardest piece.

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I would say, because you're not yet immersed enough in the transition that you want to make.

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To really know what you need to say so that your legitimacy of knowledge in that spaces is understood.

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And you also simply don't have the connections, perhaps, that you would do once you've moved into the space.

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So I'd say if I were going to do anything differently, probably what I would do is, you know,

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and especially for students who are listening to this now that are maybe in their first or second year,

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I would have spent a little bit more time thinking about how am I going to make the

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kinds of connections I want to make to understand the spaces that are available to me,

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like what are the options that are out there? And, B,

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make the Connections to really form the right network so that at the right time I have the right information about what roles are available and

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potentially who can introduce me to the right kind of person to to know about a job that's that's out there and the right kinds of skills.

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So because skills do change in terms of need, employer need, and what they're looking for will change over time.

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So having an idea of how that space is shifting will allow you to see not only what's on the on the market right now or what's needed in the market,

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but you can get an understanding of what's going to be needed by the time I leave,

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because you can kind of observe the trends that are happening and say, OK.

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So if I put some resources into, for example, learning how to do network mapping or doing a bit more on the kind of digital skill side,

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then I'll be more valuable than if I'm spending time doing something else. Which isn't to say, of course, that you shouldn't focus on your degree.

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I mean, you know, it's such a kind of you have to get over that hurdle more than anything else.

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Right? That is the thing to get through. But I'd say a really crucial skill is networking.

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And I know that everyone always says that. And people find it can find it very overwhelming.

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But I think the thing to remember is networking is a skill that allows you to understand

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some knowledge that's out there in the world that you don't yet have in an informal way.

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So if you view it in that sense, then it can be less overwhelming.

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And I found as well, once I started learning to have an objective when I went to a networking event.

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So I go to a lot of digital skills, meet ups in London, or I try and attend a lot of webinars or whatever it is I'm trying to learn about.

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I look for places where I can find that information and in particular I potentially can

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share some information as well because people are always willing to engage with you.

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First of all, if you're interested in them and ask them questions, everyone loves talking about themselves.

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This is like the crucial skill of good networking is if you can get someone, if you can express interest in them.

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People are usually very willing to tell you more about what they're doing,

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but also people are usually have some kind of a need that if you can fulfil that need in some way,

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like having a slightly adjacent skill or a different skill that they're looking for, then they'll want to talk to you as well.

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So so building that skill of saying, OK, there is a big data meetup on Wednesday, I'm going to go and

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My goal is to find out either a little bit more about this particular topic or to meet someone that works in this

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business or to find someone that has this job title and just speak to them a little bit about whatever my objective is.

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Having that focus can really, really make it much easier because you feel less overwhelmed by the idea of networking in general.

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That can. Huge kind of topic and kind of focussing it on something smaller to achieve can make can make life just a little bit less overwhelming.

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Yeah, yeah, definitely. I think a lot people do get it. Oh, you've got to network.

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But then what does that really mean? What does it look like in practise. They kind of.

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Yeah. So to get tip of going to something with an objective and kind of having a little bit of reciprocity in that,

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like maybe there's two things you can offer as well as getting people to talk about themselves.

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Yeah. And honestly, the other thing that I would say, which is a really good tip, is even if you're fairly early in your career,

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especially if you're looking at a non-academic role, getting up there and being a speaker.

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So, you know, it gives it gives you a chance to showcase what you're doing or the kinds of knowledge and skills that you have.

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But it also gives people an excuse to talk to you at a networking event.

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And even if you're an introvert, actually, as scary as it could be to go on stage,

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giving a talk is a really excellent way of putting the burden on others to come and talk to you so you don't have

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to feel like you're trying to muscle your way into someone else or to identify a friendly face in the crowd,

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because everyone knows that you're so and so talked about the thing and then they might want to come ask you questions.

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So it's a really great way of, you know, it's essentially you saying I'm here, I can talk about this.

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And I'd say the real value is that in the personal connections, the one on one connections that you make after you've given the talk.

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So even a short you know, in particular, when I think about the technology team,

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which is mostly what I work in, there are tons of events, in particular London, where I live.

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You could probably go to multiple. You'd have your choice of events to go to every evening.

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And typically they're very short form talks, two to three minutes about a subject of interest.

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So there's usually lots of opportunities to get in and kind of on the ground floor of the ladder of speaking, as it were.

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If you're in a place that has less accessible resources in that way, there are definitely a lot of online resources.

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And in particular, I think now that there is so much fear about physically being lots of people together,

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lots of the kinds of events that I would typically have gone to are going to be thinking about moving online more and more.

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And the way that we develop essentially digital etiquette.

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So, you know, how people develop those kinds of informal connections is going to become increasingly important.

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You know, it's relatively easy to put together a podcast or a webinar that is one way broadcast content,

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but creating those connections that those networking events are really valuable for.

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There are very few ways that people are good at that right now. But I think increasingly that's a thing that people will get good at.

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So I'd say look for opportunities in that space where you can not only watch a piece of content,

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but also in some way contribute to an ongoing dialogue and meet people through that kind of a mechanism.

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I'm trying to think of other examples of good kind of asynchronous or at a distance ways that people can learn and connect with one another.

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I subscribe to a lot of newsletters about such just some interest to me professionally as well.

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Usually reaching out to someone and saying, I read this thing or I have a question about whatever it is,

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you won't always have a hundred percent success so that people will get a lot of demands on their time,

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particularly as they get more skilled or experienced in their space.

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But often people are again willing to talk about something or willing to connect with you,

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you know, to answer a question or to be involved or engaged in something.

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People are typically very generous with their time, you know, especially if you're only asking for 10 minutes or, you know,

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whatever it is, a small or small chunk of time is usually a good way to go in, particularly if you can be specific about your ask.

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That really helps people to engage with you quickly is instead of being like, hey, I read your thing, will you be my mentor?

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That's that's often too open ended. But if you say I read your thing, it was interesting.

00:18:53,000 --> 00:18:57,000
Specifically, I have a question about blah. You can often then open a dialogue in that way.

00:18:57,000 --> 00:19:05,000
Yeah. So it kind of being specific and kind of very much time limited when you're asking of people.

00:19:05,000 --> 00:19:11,000
And yeah. And it's really interesting to think about kind of non sort of Face-To-Face in person ways you can do networking.

00:19:11,000 --> 00:19:15,000
I think a lot of people think of networking as you got to go to this event and a lot

00:19:15,000 --> 00:19:18,000
of PGRs are part time or they have caring responsibilities and they just think,

00:19:18,000 --> 00:19:23,000
oh, I just can't do that. Actually, there are all these other ways that you can get involved.

00:19:23,000 --> 00:19:28,000
Yeah. And like I say, I think that those kind of online and asynchronous abilities are where the necessity for those

00:19:28,000 --> 00:19:34,000
is going to become increasing over the next few months and probably years after that as well.

00:19:34,000 --> 00:19:39,000
You know, because businesses have long been looking for ways to encourage less business travel, for example.

00:19:39,000 --> 00:19:43,000
And it's always, oh, it's too hard. There's no way to do this. It's impossible.

00:19:43,000 --> 00:19:49,000
And one of my current research areas is how digital technologies are actually changing the physical spaces that people work.

00:19:49,000 --> 00:19:57,000
And so right now is a real kind of fascinating live experiment for me to watch the way the businesses are responding to the current pandemic crisis.

00:19:57,000 --> 00:20:00,000
And I think that that really will change a lot of the things that we're thinking about.

00:20:00,000 --> 00:20:05,000
In particular, you look at things like slack channels for technology.

00:20:05,000 --> 00:20:09,000
Conferences have always been very popular, but.

00:20:09,000 --> 00:20:14,000
It's going from that being a kind of adjacent thing to the event, to being that is the event.

00:20:14,000 --> 00:20:17,000
You know, video conferencing again. It's not like that's a new technology,

00:20:17,000 --> 00:20:24,000
but the way that people get comfortable with using those things in particular in large groups is going to be really interesting.

00:20:24,000 --> 00:20:31,000
I think how people understand the visual and audio cues that they're getting on multiple person calls is going

00:20:31,000 --> 00:20:37,000
to be interesting because you often have these kind of slightly weird signals where if you were in person.

00:20:37,000 --> 00:20:42,000
So, of course, you know, we're probably sitting about four or five feet apart as we're recording this podcast.

00:20:42,000 --> 00:20:47,000
And that has a particular kind of etiquette about the way that we do distancing

00:20:47,000 --> 00:20:52,000
But if you're in a video conferencing situation, people often have the camera at a slightly weird distance.

00:20:52,000 --> 00:20:55,000
So you either feel like you're too close or you're too far away.

00:20:55,000 --> 00:21:01,000
And that gives different cues to how you perceive that interaction, where they have the microphone to close it.

00:21:01,000 --> 00:21:05,000
It's like they're breathing on you. I don't know if you've had that experience. I'm sure everyone has.

00:21:05,000 --> 00:21:09,000
And it's that really sets up a very different kind of interaction.

00:21:09,000 --> 00:21:13,000
And I think that as these technologies become ever more ubiquitous,

00:21:13,000 --> 00:21:17,000
people are going to have to be getting better at understanding what those implications

00:21:17,000 --> 00:21:21,000
are of sound and eyesight and what that means for people's comfort level of distancing.

00:21:21,000 --> 00:21:25,000
So that for me, is very fascinating subject right now. Yeah, yeah. There's so much to explore.

00:21:25,000 --> 00:21:29,000
And it's going to be interesting how it develops like over the next couple of months especially.

00:21:29,000 --> 00:21:35,000
Definitely. And you mentioned that he thought networking would be particularly with people in the early

00:21:35,000 --> 00:21:41,000
stage of their PhD just in terms of finding out about what different entities are doing,

00:21:41,000 --> 00:21:42,000
how things are moving and trends,

00:21:42,000 --> 00:21:48,000
and then they can use that to think about what skills do I need to pick up and develop and see if someone was interested

00:21:48,000 --> 00:21:55,000
in doing the kind of work that you do like as a digital anthropologist and all the various things that that's include

00:21:55,000 --> 00:22:01,000
What kinds of experiences would be useful for people to try and pick up alongside or as part of the PhD

00:22:01,000 --> 00:22:05,000
I think one of the it's important to focus on one of the reasons that I think it's important

00:22:05,000 --> 00:22:09,000
to do this early in your academic career is because when you are working in academia,

00:22:09,000 --> 00:22:14,000
unless you are doing something part time or you have prior experience outside of academia,

00:22:14,000 --> 00:22:19,000
the people who are teaching you so often don't have the experience of working outside of academia.

00:22:19,000 --> 00:22:25,000
So they are simply not in a very good position to advise you about if you want to explore non-academic options.

00:22:25,000 --> 00:22:28,000
What that transition looks like, what kinds of skills are being looked for.

00:22:28,000 --> 00:22:33,000
They can't really advise you on the kind of non-academic lingo unless they themselves are also doing some of this stuff.

00:22:33,000 --> 00:22:35,000
This is all, of course, very context dependent.

00:22:35,000 --> 00:22:39,000
You have some departments who are very different or you have university support services which can help you.

00:22:39,000 --> 00:22:46,000
But in general, my experience when I was a PhD student was that of many others that I spoke to was that they simply weren't

00:22:46,000 --> 00:22:55,000
able to bridge that gap into the commercial realm because they didn't have the right advice at the time.

00:22:55,000 --> 00:22:59,000
And being an anthropologist and someone who does a lot of ethnography

00:22:59,000 --> 00:23:05,000
I always think that the best way of learning about something is going to immerse yourself in that thing and then experiencing it for yourself.

00:23:05,000 --> 00:23:12,000
So finding an internship or some kind of work experience, I know it's less common for older people to be doing those.

00:23:12,000 --> 00:23:20,000
But you can usually find something. And there are often places that will offer short work placements even to postgraduate students,

00:23:20,000 --> 00:23:26,000
although it is you know, sometimes they're not quite very well set up for that. But, you know, there are definitely places that are doing it,

00:23:26,000 --> 00:23:29,000
especially if they're interested either in your area of research or the kinds of creative skills that

00:23:29,000 --> 00:23:35,000
you can bring to the situation that you're looking at and doing those fairly early on in your career.

00:23:35,000 --> 00:23:42,000
Gives you an opportunity to understand more about yourself, what you like and what you don't like instead of waiting until the end and thinking, hey,

00:23:42,000 --> 00:23:48,000
I'm just going to sit out in the wide world and having this wonderful badge of my degree is going to

00:23:48,000 --> 00:23:55,000
tell people something about who I am and the kind of skills I have often in a commercial setting.

00:23:55,000 --> 00:24:03,000
You know, you might recognise the value of a PhD, but you won't understand how that applies to your business.

00:24:03,000 --> 00:24:09,000
So particular for early people who are just out of the PhD

00:24:09,000 --> 00:24:16,000
It's a hard sell because in essence, from an employer perspective, they're seeing it was just a regular graduate who is a little bit more expensive.

00:24:16,000 --> 00:24:18,000
And that can be challenging to overcome that.

00:24:18,000 --> 00:24:27,000
You know, I'd say after your first job or first couple of jobs, when you move it to either a more managerial role or more strategic looking role,

00:24:27,000 --> 00:24:33,000
then people begin to value your active experience more than they did when you were first out of the gate.

00:24:33,000 --> 00:24:37,000
So that's really tough because that's kind of the biggest hurdle is is getting into your first job.

00:24:37,000 --> 00:24:46,000
It's a very much kind of a catch 22 situation. But coming in from your your postgraduate experience, having had some commercial experience as well,

00:24:46,000 --> 00:24:52,000
puts you in a much stronger position than to be looking at a commercial role because people can

00:24:52,000 --> 00:24:57,000
people make assumptions about your commercial experience when they're reviewing your CV or your,

00:24:57,000 --> 00:25:03,000
you know, as you're being in your hiring process than they will about someone who's just coming with no experience.

00:25:03,000 --> 00:25:08,000
That's obvious to them. Yeah. So it sounds like it's really important.

00:25:08,000 --> 00:25:16,000
First, few roles to really think to really keep in mind that someone else won't know, understand what a PhD is.

00:25:16,000 --> 00:25:21,000
Also all the skills involved. So you really have to work at both getting other experiences,

00:25:21,000 --> 00:25:27,000
maybe then also how you kind of market those things, I guess what those skills mean from your PhD.

00:25:27,000 --> 00:25:31,000
It's not just I did this degree and there's nothing about it that makes sense.

00:25:31,000 --> 00:25:39,000
Yeah. Yeah. Yeah. And also, it's worth remembering that in a commercial setting, the word research can mean very different things.

00:25:39,000 --> 00:25:47,000
So I'm doing some doing a little bit of research on what is the commercial we're looking for and what do those kinds of roles do.

00:25:47,000 --> 00:25:55,000
And if I'm if I'm right. Gosh, the PGR resource that I'm forgetting the name of.

00:25:55,000 --> 00:25:59,000
But it's like academia to ac-doc or something like that. Yeah.

00:25:59,000 --> 00:26:02,000
I can find it to be linked. That would be awesome. Thank you. So.

00:26:02,000 --> 00:26:06,000
So there's some good kind of role descriptions of, you know, what does a U x designer do.

00:26:06,000 --> 00:26:10,000
And what does a commercial analyst do.

00:26:10,000 --> 00:26:14,000
And things of that nature that are just kind of general descriptions of jobs that are out there in

00:26:14,000 --> 00:26:20,000
the market and getting an understanding of what the language is that's used around those roles is

00:26:20,000 --> 00:26:25,000
really helpful because you can then tailor your CV to reflect those skills specifically and in

00:26:25,000 --> 00:26:31,000
particular to take some projects that you've done and demonstrate how those skills relate to that role.

00:26:31,000 --> 00:26:35,000
So essentially, it means you as the person coming into the job,

00:26:35,000 --> 00:26:41,000
you have to be a bit more forward stepping and thinking to to to the commercial

00:26:41,000 --> 00:26:46,000
person to give them an understanding of what you want them to see about that.

00:26:46,000 --> 00:26:49,000
That relates to their job that they have on the market.

00:26:49,000 --> 00:26:55,000
And that can be challenging because, again, sometimes the language is, you know, very jargonistic in particular.

00:26:55,000 --> 00:27:00,000
And, you know, if you've worked in a commercial setting, you might understand the particularities of what they're looking for.

00:27:00,000 --> 00:27:04,000
Whereas if you haven't, you don't really know what they're looking for.

00:27:04,000 --> 00:27:08,000
But trying to get informal interviews with people just to understand what they're specifically

00:27:08,000 --> 00:27:12,000
asking or getting in examples of prior work that other people who are in that field have done.

00:27:12,000 --> 00:27:19,000
So that's why networking isn't just about learning from people who are already hiring managers.

00:27:19,000 --> 00:27:24,000
It's not just about trying to find people who are looking for, you know, who have jobs on offer,

00:27:24,000 --> 00:27:29,000
but also about meeting people in those roles and finding out what their backgrounds are and how they got into that role.

00:27:29,000 --> 00:27:35,000
So it's really important, even just pure networking, can be super important to to understand how they bridge that gap and how they got into that space.

00:27:35,000 --> 00:27:41,000
Yes, I say there's a lot to do in terms of not having assumptions yourself.

00:27:41,000 --> 00:27:45,000
Someone else will understand what you're talking about then not assuming that

00:27:45,000 --> 00:27:48,000
you also know what they're talking about when they say research and you say, I've done this research,

00:27:48,000 --> 00:27:52,000
you might be talking about two completely different things and you might not either

00:27:52,000 --> 00:27:57,000
have a good match or they might not realise that you might be a good match. And talking to other people,

00:27:57,000 --> 00:28:03,000
who are in the field and their experiences can really help to sort of reach those gaps and find that language like you say,

00:28:03,000 --> 00:28:08,000
before you're fully immersed in whatever field. Is that kind of thing.

00:28:08,000 --> 00:28:17,000
Yeah. Yeah. Precisely. Yeah. So you say if someone was applying to work with you with that particular things that you are looking for in

00:28:17,000 --> 00:28:23,000
terms of how people put those things across or things you'll particularly like not looking for things like,

00:28:23,000 --> 00:28:27,000
nope, don't do that. Yeah. Let me answer that question in two ways.

00:28:27,000 --> 00:28:31,000
So where I work now, we are essentially a small consortium of researchers who have very different skills.

00:28:31,000 --> 00:28:37,000
So you can think about in an academic setting as being like an area skills department where you might have an economist and an anthropologist

00:28:37,000 --> 00:28:44,000
and a musicologist and whoever else that are all working on either a particular geographic region or some kind of conceptual region.

00:28:44,000 --> 00:28:47,000
But they all have very, very different skills that they're bringing to the table.

00:28:47,000 --> 00:28:53,000
And they might not even work very closely together, although they might on some projects. So that's really where I work now, is like that.

00:28:53,000 --> 00:28:57,000
We all have very specialised skills. I'm the only digital anthropologist on the team.

00:28:57,000 --> 00:29:04,000
The other people who have more skills that are focussed on looking at things like digitisation and cloud

00:29:04,000 --> 00:29:14,000
technologies and organisational strategy and some in some cases software engineering concepts and things like that.

00:29:14,000 --> 00:29:17,000
So we all have very, very different goals.

00:29:17,000 --> 00:29:23,000
So when we look for someone, we're typically looking for someone who has different skills and what we already have.

00:29:23,000 --> 00:29:34,000
I would say in the roles that we're doing, if I was hiring someone to be an assistant to me, then I probably would be looking for.

00:29:34,000 --> 00:29:37,000
Usually I've done that in a kind of short term project way.

00:29:37,000 --> 00:29:44,000
So in that case, it will very much depend on other project is when we hire into the the LEF.

00:29:44,000 --> 00:29:49,000
More broadly, we probably will be looking for somebody with a fair amount of commercially experience already.

00:29:49,000 --> 00:29:53,000
So I probably wouldn't see that as a good was a good starting role for somebody who has a PhD.

00:29:53,000 --> 00:30:03,000
But, you know, I've managed to make it there eventually. So I think if you want to work in an organisation that's like the one that ours is,

00:30:03,000 --> 00:30:08,000
then it's a matter of figuring out what kinds of steppingstones you need to put him.

00:30:08,000 --> 00:30:10,000
Along the way to get there.

00:30:10,000 --> 00:30:20,000
So to answer the question more from the perspective of my old job, when I was doing a more kind of data science y data analysis, background.

00:30:20,000 --> 00:30:30,000
When we were first hiring people who were typically coming straight out of their degrees for junior analyst roles.

00:30:30,000 --> 00:30:32,000
That was a very quantitatively oriented department.

00:30:32,000 --> 00:30:42,000
So we were typically looking for some examples of statistical knowledge, some potentially familiarity with statistical package software.

00:30:42,000 --> 00:30:47,000
And interestingly, there's not a lot of crossover between academic usage of those things.

00:30:47,000 --> 00:30:53,000
So you typically might be doing SPSS or quite a lot of stuff with, ah, potentially some stuff with Python.

00:30:53,000 --> 00:30:57,000
And what commercial organisations use in those spaces.

00:30:57,000 --> 00:31:01,000
Obviously all the maths is the same, but they simply are using different kinds of software packages.

00:31:01,000 --> 00:31:06,000
So we wouldn't always be looking for some experience in those commercial packages,

00:31:06,000 --> 00:31:14,000
which are things like Tableau and Click View and software package called Looker.

00:31:14,000 --> 00:31:18,000
But if they had some, that was usually perceived as an advantage.

00:31:18,000 --> 00:31:26,000
But if they had Python, our other stuff, we knew that they'd worked with statistical package software before and that was OK.

00:31:26,000 --> 00:31:35,000
We also were looking for people who at the time, again, very quantitive were all but we wanted people who could look at a set of data

00:31:35,000 --> 00:31:39,000
and see where there were irregularities or unusual things happening so that

00:31:39,000 --> 00:31:48,000
they could then raise a challenge in terms of either how the data was being collected or an anomaly of some kind in what was happening with the data.

00:31:48,000 --> 00:32:01,000
So you needed to have a bit of an investigative hat. And I would say my role there as an anthropologist was much more about assisting

00:32:01,000 --> 00:32:06,000
people with the kind of more ephemeral qualities of questioning those things.

00:32:06,000 --> 00:32:15,000
So while I did have a very quantitative role when I was there, I wasn't necessarily doing a lot of the kind of data sciences side of things.

00:32:15,000 --> 00:32:20,000
A lot of it was more of the summary statistics. And then, OK, we've noticed that there's an unusual pattern.

00:32:20,000 --> 00:32:23,000
What are some creative ideas we can think about, about in terms of why that might be?

00:32:23,000 --> 00:32:29,000
So you needed that mixture of people who could do the the crunchier side of the maths,

00:32:29,000 --> 00:32:39,000
but also say things like all the schools are on holiday this week or there's been a strike in Chicago teaching in the Chicago teaching union

00:32:39,000 --> 00:32:46,000
And so therefore, we're having less people who are logging on to share their stories with us this week or whatever it might be.

00:32:46,000 --> 00:32:53,000
So there is kind of that social side in terms of understanding what you know, if you see something unusual, what might it be?

00:32:53,000 --> 00:32:59,000
So a lot of my role in the end was really about training the newer trainees so they would come in with a more kind of hard sciences background.

00:32:59,000 --> 00:33:05,000
And then my role would be to help them. Question. When you see something unusual, why might that be so they can answer a lot of questions about this.

00:33:05,000 --> 00:33:09,000
Looks weird, but they didn't necessarily know what to do with that information. And my role is to help them understand that.

00:33:09,000 --> 00:33:12,000
Know how could you then question this more broadly? Yeah.

00:33:12,000 --> 00:33:18,000
So it's kind of, um, combining those that kind of hard science, the social sciences types together.

00:33:18,000 --> 00:33:25,000
Precisely. And I would say if you depending on the size of the organisation you're with, you often find that you get blended teams.

00:33:25,000 --> 00:33:31,000
So and that can be a real strength when you're able to when you're able to have people who have strengths in different areas,

00:33:31,000 --> 00:33:37,000
it allows you to see information in a different way than if you are just one person is looking at it in one way.

00:33:37,000 --> 00:33:42,000
And of course, there's always the wonderful idea of having everyone have all of the skills.

00:33:42,000 --> 00:33:44,000
But people are simply going to have different strengths.

00:33:44,000 --> 00:33:48,000
And recognising where they can contribute the most is really important for any organisation to do.

00:33:48,000 --> 00:33:56,000
Yeah. Yeah, sure. I know I say sounds like you're saying your current role and maybe that's a person that's listenings dream.

00:33:56,000 --> 00:34:03,000
Well, they want to work in a team, but it's a case that you won't necessarily do that straight away to think about the kind of work.

00:34:03,000 --> 00:34:08,000
What are the steps and experiences I need to get to that point. If that's the kind of thing I want to be aiming for.

00:34:08,000 --> 00:34:12,000
Yeah. Precisely. So a good example would be like, there is no way that I would have the job I have now,

00:34:12,000 --> 00:34:15,000
even though my role is much more qualitative than it was previously.

00:34:15,000 --> 00:34:21,000
If I hadn't had my experience where I was doing essentially the kind of hard number crunching for the past six years before that,

00:34:21,000 --> 00:34:26,000
because it gave me experiences like managing a team, give me a lot of organisational operational experience.

00:34:26,000 --> 00:34:32,000
So I understood the different parts of what most businesses have in terms of the kinds of ways that they're set up.

00:34:32,000 --> 00:34:39,000
Give me a lot of experience around kind of standard ways of doing commercial modelling for different kinds of things.

00:34:39,000 --> 00:34:45,000
So then when I go into businesses now where where I'm advising them, I usually understand the organisational setup pretty well.

00:34:45,000 --> 00:34:53,000
Because, you know, though, of course, there are differences, there are definitely commonalities in terms of how large organisations are always set up.

00:34:53,000 --> 00:34:55,000
So if I hadn't had that experience,

00:34:55,000 --> 00:35:01,000
I wouldn't simply I've simply wouldn't be able to kind of stretch to putting myself in the shoes of the organisations I work with.

00:35:01,000 --> 00:35:08,000
So so, yeah, it's definitely that kind of sense of, OK, if I want to someday work in a think tank or work in a research.

00:35:08,000 --> 00:35:15,000
organisation or something of that nature or go into a kind of political policy organisation.

00:35:15,000 --> 00:35:17,000
What do I need to do so that when I get there,

00:35:17,000 --> 00:35:25,000
I have the right mixture of skills and background and essentially area knowledge so that I can really provide the most value in that kind of role.

00:35:25,000 --> 00:35:33,000
Yeah, yeah. And when you were moving to your first role at tes, like, how did you find because obviously that was quite different in terms of quantitative,

00:35:33,000 --> 00:35:39,000
in terms of applying for that role, how you sort of sold your skills in that setting mixture thing.

00:35:39,000 --> 00:35:43,000
So I had applied for several different things around that time.

00:35:43,000 --> 00:35:49,000
I specifically remembers applying for internship and publishing as well. And I was applying at that time as well as it has.

00:35:49,000 --> 00:35:55,000
And the tes connection was actually through a personal friend.

00:35:55,000 --> 00:36:02,000
So, again, networking, it comes down to, you know, it absolutely is about what you know, because, you know,

00:36:02,000 --> 00:36:07,000
when you show up in the room to be the one who is in the interview, you have to you have to pass the bar.

00:36:07,000 --> 00:36:13,000
But in terms of the knowledge about what roles are available and out there,

00:36:13,000 --> 00:36:19,000
it really is helpful to not just be depending on job boards and kind of publicly available information.

00:36:19,000 --> 00:36:27,000
Having some knowledge about, you know, roles that either are not being advertised explicitly or in particular this role.

00:36:27,000 --> 00:36:31,000
When I first was applying, it has had a very hard time filling the role.

00:36:31,000 --> 00:36:35,000
And that's partly because it was a slightly unusual setup for the role.

00:36:35,000 --> 00:36:42,000
So a lot of the people that they were interviewing either had one side of the job that they were looking for covered already,

00:36:42,000 --> 00:36:44,000
or they had the other side that they wanted.

00:36:44,000 --> 00:36:53,000
So in this case, they wanted somebody who could do a lot of the kind of analysis and Day-To-Day reporting.

00:36:53,000 --> 00:37:00,000
But they also wanted someone who they could eventually train to do some of the the actual programming of the reporting tools.

00:37:00,000 --> 00:37:04,000
And what they were finding at the time was that they could they could find someone who was one of the other very strongly,

00:37:04,000 --> 00:37:10,000
who had a commercial background. But they were really struggling to find somebody who either had both or wanted to do both because it was unusual,

00:37:10,000 --> 00:37:17,000
you know, expectation, especially for that level of role. And of course, I come in as a newly graduated PhD and like, I can do anything.

00:37:17,000 --> 00:37:23,000
I'm willing to do whatever it takes to succeed in this job. And sometimes that extra flexibility of simply saying, hey,

00:37:23,000 --> 00:37:31,000
I'm willing to learn it can it can sometimes put you in a better position simply because other people whose careers were

00:37:31,000 --> 00:37:40,000
fixed or have a very focussed career path in mind might not be interested in having that kind of broad range of skills.

00:37:40,000 --> 00:37:48,000
And so, you know, for you to come in then and say, I can learn things very quickly and I'm very experienced in part of this or I am

00:37:48,000 --> 00:37:51,000
very thorough in the way that I go about learning things can be a real advantage.

00:37:51,000 --> 00:37:56,000
And so that was eventually what happened was because they'd had such a hard time filling the role,

00:37:56,000 --> 00:38:01,000
they were then willing to look slightly differently at what kinds of mix of skills they needed. So essentially,

00:38:01,000 --> 00:38:10,000
I showed up at the right time when they were looking for someone who is a little bit different than what they had initially had in mind.

00:38:10,000 --> 00:38:14,000
And then when I was doing the interviewing, clearly they were impressed by the research skills that I had,

00:38:14,000 --> 00:38:21,000
but also some of the ways that I was thinking about or questioning some of the stuff that they were putting forward that made them feel like,

00:38:21,000 --> 00:38:26,000
OK, this could be someone who can approach this role differently, which is really helpful for them.

00:38:26,000 --> 00:38:31,000
And interestingly enough, when I went to then move to the leading edge forum where I work now,

00:38:31,000 --> 00:38:35,000
I knew that I was ready to move on from a role that was very quantitative.

00:38:35,000 --> 00:38:38,000
And I wanted to get back into some of those more kind of core research skills that I developed.

00:38:38,000 --> 00:38:45,000
And when I was here at Exeter and I was having a hard time because my role at that point was so quantitive that all anyone could see in me was,

00:38:45,000 --> 00:38:51,000
oh, she's an analyst. She's an analyst. And so it was very hard for them to see that the qualitative skills that I'd amassed

00:38:51,000 --> 00:38:55,000
in the previous simply weren't things that in their mind were showing up for them.

00:38:55,000 --> 00:38:57,000
When I was trying to put myself forward.

00:38:57,000 --> 00:39:05,000
So but the leading edge forum was specifically looking for someone who wanted to do a digital anthropology programme for them, programme of research.

00:39:05,000 --> 00:39:09,000
So again, it was just the right thing at the right time. It just matched up. That was what I wanted to do and that was what they needed.

00:39:09,000 --> 00:39:14,000
And again, they'd been having a hard time filling the role because they had a lot of people who either had a

00:39:14,000 --> 00:39:19,000
lot of commercial experience but didn't really have the kind of core research skills that I had.

00:39:19,000 --> 00:39:25,000
Or they had a lot of people who had been doing very academic research for a long time,

00:39:25,000 --> 00:39:31,000
but didn't have the commercial experience and the context to operate in that world.

00:39:31,000 --> 00:39:36,000
So, you know, it's just about finding the right the right match at the right moment, I think.

00:39:36,000 --> 00:39:41,000
Yeah. Yeah. And this only about. Throughout kind of the importance of networking,

00:39:41,000 --> 00:39:47,000
finding out about jobs that are available in any kind of different people's experience and backgrounds in these industries.

00:39:47,000 --> 00:39:52,000
And it sounds like that makes it experience between the academic and the kind

00:39:52,000 --> 00:39:57,000
of commercial industry industry type stuff and get having both those things.

00:39:57,000 --> 00:40:02,000
And I said maybe trying to get some of these experiences durinf your PhD really helpful.

00:40:02,000 --> 00:40:06,000
Yeah, yeah, absolutely. It can be really powerful if you want to move into a commercial role.

00:40:06,000 --> 00:40:17,000
And I I'd say also what I've observed. Is there an increasing number of public private partnerships or academic quasi

00:40:17,000 --> 00:40:24,000
academic research skills or or things of that nature where there's some kind of,

00:40:24,000 --> 00:40:32,000
oh, hey, we, the university have a lot of research skills or a lot of scope for doing like innovation lab style stuff.

00:40:32,000 --> 00:40:34,000
But what we don't have is a lot of the commercial side of things.

00:40:34,000 --> 00:40:42,000
So they develop these like digital hubs or innovation hubs in different parts of the world, in different country.

00:40:42,000 --> 00:40:51,000
And so there are often roles that are available that are kind of quasi academic, but also really depend on the commercial experience as well.

00:40:51,000 --> 00:40:54,000
So, you know, I haven't really had an experience of fighting for those,

00:40:54,000 --> 00:40:58,000
but it's something I've observed as I've been thinking about my my future career path.

00:40:58,000 --> 00:41:02,000
It's something that I've observed is out there in the market. So there might be something like that. You know,

00:41:02,000 --> 00:41:05,000
if you're thinking about perhaps wanting to stick a bit closer on the academic

00:41:05,000 --> 00:41:10,000
side and maintaining those academic credentials and publishing and all that.

00:41:10,000 --> 00:41:16,000
But also having a bit of commercial experience that would let you be that kind of linchpin between those two those two things.

00:41:16,000 --> 00:41:23,000
So I'd say that's an interesting potential career path as well. It's adjacent to but not exactly the same as the way that I've gone.

00:41:23,000 --> 00:41:27,000
And would there be any other kind of final tips you'd give someone kind of in the middle of

00:41:27,000 --> 00:41:33,000
your PhD or something you wish you'd done a bit differently when you were doing your PhD?

00:41:33,000 --> 00:41:36,000
I think the only other tip.

00:41:36,000 --> 00:41:45,000
And again, it's probably something that is spoken about perhaps a bit more than when I was a student, is prioritising your own self care.

00:41:45,000 --> 00:41:51,000
And I mean that not in a fluffy bubble bath kind of way, although if that is something that works for you, then great.

00:41:51,000 --> 00:41:57,000
But really look after your own mental health and your own physical health.

00:41:57,000 --> 00:42:05,000
Because if you don't have a working as a working instrument, then it's going to be very difficult for you to play the sonata, basically.

00:42:05,000 --> 00:42:15,000
And I'm hoping that there are a lot of resources out there available now to enable students to to really

00:42:15,000 --> 00:42:22,000
care about those things and to look after themselves and also to develop those habits early in life,

00:42:22,000 --> 00:42:24,000
especially when you're in the kind of pressured environment that a Masters or

00:42:24,000 --> 00:42:30,000
PhD is that will put you in extremely good stead for later in life when you

00:42:30,000 --> 00:42:34,000
have pressured roles or are dealing with different kinds of pressures like

00:42:34,000 --> 00:42:38,000
balancing work and family or what or financial concerns or whatever it might be.

00:42:38,000 --> 00:42:46,000
So developing those habits early on, when you're at what might be the most pressured moment of your career, ultimately will then help you.

00:42:46,000 --> 00:42:52,000
Everything else beyond that will seem like a piece of cake then. And that's it for this episode.

00:42:52,000 --> 00:43:07,349
Join us next time when we'll be talking to another researcher about their career beyond their research degree.


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