Hi, I'm Helen and I'm Sarah and you're listening to the Squiggly Careers podcast, a weekly show where we dive into the ins-outs, ups and downs of work and share some insights, some ideas for action and some tools to help you take a bit more control of your career development.

And today we're talking about data points that will support your career development.

That's very formal, Sarah.

It does, doesn't it?

But also, we can't come up with a shorter title.

So that's what we're going with everybody.

It's Ferry does what it says on the tin, I would suggest.

It is worth just thinking about when we say data, what do we mean?

And I think data is something that you can track over time to increase your self-awareness

and that prompts actions for you.

So if you're almost like, if you can't track it, it might still be useful, but it's probably not data.

So I was really trying to think about this.

When we were coming up with ideas, I was like, okay, could you see, well, where am I today? And then could you come back to it in a month's time and be like, right, well, how has that changed? So sometimes that will be numbers, like the obvious data that probably we all think about. But it could also be somebody writing something to you, like giving you feedback. It could also be your own feelings or reflections.

You know, some of this will be about your own data. Some of this will be about gathering data

from other people too. And I think we want a number of different data points because I suspect

when you put all this together as well, it paints a bit of a picture for kind of where you are

in your squiggly career at the moment. And I think actually in like the world that we work in now, I think we've got more data points than

ever that are available to people. You're like how many emails that you get versus how many

emails you send. How many minutes a day you spend in meetings? How many hours you sleep? Like there's

actually there's quite a lot of data capturing

tools. And I think we're trying to go a bit beyond the tech and the tools and think a bit more

about, well, what can you observe? Like, what is the data that sometimes we miss? And what tools have

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