Sample Of One Vs. Example Of One

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At a conference I recently attended, a Gen Y-aged speaker was talking ’bout his g-g-g-g-generation, basing his conclusions on a sample of one — himself. When I confronted him later, telling him that I had research data to refute his claims, he was unfazed. “Well, even 60% to 70% of the sample doesn’t represent us all.”

Maybe not, but a sample of one does?

Fast Company recently ran an article titled Why I Love My Gen Y Assistant. In it, the author writes:

“I recently hired a part-time assistant to help me get a bit more organized. Though we’ve only worked together for a couple weeks, I couldn’t be happier with the arrangement.”

The author then goes on to use her experience with her new assistant to make characterizations about Gen Y’s tech-savviness and skills regarding personal branding.

It’s one thing to characterize your own generation based on your own behavior, but to characterize a different generation based not just on a sample of one, but on someone you know for just a couple of weeks? I’m not sure you could even characterize that person very well after just a few weeks.

On the other hand…I’m quite aware that us analysts often err on the exact opposite end of the spectrum by basing conclusions solely on the data.

Here’s what I think works best: Moving from a sample of one to an example of one.

A sample of one — even yourself — works if you’re using your own behavior or experience to bring the data to life. For example, in presentations I give, I like to support the trend that, increasingly, women are controlling (um, managing) the family finances, by pointing out that nobody knows that better than I do, as “I stand before you with the $7 dollars in my pocket that my wife let me out of the house with.”

The example would fall flat without the data — the data comes to life with the example.

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