When I started my PhD in 1999 (last century, as I have to remind myself, rather soberingly) one of the first hard questions I faced was how I'd collect my data.

As I completed my Master’s I was given just two choices. I could either do so qualitatively, through interviews, or quantitatively, through numbers and statistics.

It should have been an easy choice.

I loved reading and writing as a teenager.

Indeed, even in the 20 years since my PhD, I've spent the subsequent twenty years writing books, interviewing stakeholders, listening to clients and helping them make meaning of what they are sharing with me and indeed the truths they are hearing themselves say!

So qualitative work is where my heart lives. A choice of qualitative would have been a sheer joy.

But I'd grown up inside a particular sentence. My mother said it often, lightly, without malice: "We Doyles, we're no good at maths."

She’d meant it kindly, as if by explanation for my struggle when faced with learning division and then later, algebra and so on and so forth.

However, she’d also say the ‘self-evident truth’  while I watched her balance a chequebook to the penny. While keeping a family of four fed on the £11.40 left until my father's next payday.

The evidence of her own competence was right there in her hands. Yet, the story she told about our collective skills said the opposite.

And I'd swallowed the story whole. I avoided maths at school, never noticing I was actually rather good with money as a child: budgeting, saving, knowing exactly what change I was owed by the cashier.

Getting excited by compound interest in my small savings account even! The sentence had done its work long before I thought to question it.

So when that data-collection question was posed to me, the one I knew would shape the next three years of my life, I realised what believing the sentence had been quietly costing me.

I could keep living inside the inherited story.

Or I could challenge that self-limiting belief and create a new one for myself. 

So I pulled my big-girl pants on and chose the quantitative route.

The hard choice. The one that both frightened me and filled me with awe.

In my thesis I justified it on its merits; that numbers let you spot patterns across whole populations, see what holds true at scale, understand groups rather than individuals. All true.

But underneath the academic justification was something far more personal: I was refusing to be someone who ‘couldn't do maths’.

When the data I ran finally came in two years after that fateful choice; the t-tests, the ANOVAs, the survey results from over a thousand quantitative surveys from MEng students across ten UK universities,

I remember the feeling exactly. Like Christmas morning!

I pored over those spreadsheets like a ‘data buffet’ laid on just for me.

I was ready to ‘eat all I could eat!’ to see what any patterns could tell me!