My husband and I have a one completely non-negotiable morning ritual: we compare our sleep scores.
Before coffee, before talking about the day, it’s,
“How’d you sleep?”
“92. You?”
“99!”
The entire purpose of this week’s newsletter is just to brag about my recent sleep score.
If you have ever gotten 100, please do not tell me.
For me, sleep is the number one most important thing that’s going to affect your day, and a good/bad sleep will change what you can accomplish.
But recently, my husband woke up with a terrible score. The data said it took him 104 minutes to fall asleep. Two hours! We both burst out laughing - there’s no way.
Turns out, his watch strap was too loose. The sensor wasn’t reading properly, so the data was way off. His “bad sleep” was actually just bad input.
It was a good reminder: you can’t believe data that happens once, especially without context.
Data vs. Reality
Everyone’s talking about data right now - especially in the world of AI. “Data is the new oil,” “You need clean data,” “Data drives decisions.” And all that’s true. But data isn’t perfect.
In AI, the phrase data quality comes up constantly. Models are only as good as the data they’re trained on, and the same goes for us. One strange input (a loose watch, a misread signal, a missing data point) can throw off the whole story.
Good data quality takes time, repetition, and consistency. It’s not about one big measurement; it’s about patterns that hold up over time.
That’s why in my husband’s case, we didn’t just trust the number, we looked at the other data:
How did he feel when he woke up?
Was he groggy?
Did he remember lying awake that long?
The data said one thing, but the human side said another.
The Gut Check Matters
In a world obsessed with dashboards and metrics, it’s easy to forget that data only tells part of the story. Sometimes your gut sense, intuition, or lived experience knows better.
Here are a few everyday examples where your instincts might outshine the data:
Fitness trackers: The app says your workout was “low intensity,” but you know you pushed hard because your muscles are shaking.
The Email Analytics Trap: Your newsletter has lower open rates one week, and you assume it flopped, but three of your favourite people email you saying they loved this week’s edition. Not that I’m speaking from personal experience.
Budget apps: The chart says you overspent on “food,” but really, you hosted Friendsgiving - that’s community, not just consumption.
Time tracking: Your calendar looks empty, yet you feel completely spent - maybe you had five emotional conversations, or had to make a lot of huge decisions this week.
Productivity data: You didn’t check many boxes, but you solved a tricky problem that cleared the way for tomorrow - quality over quantity.
The Story Behind the Numbers
Good data tells you what happened.
Human awareness tells you why.
AI, dashboards, metrics: they’re all tools, but context is what makes them meaningful. Whether it’s a misread sleep tracker or a strange trend in your business analytics, take a moment to step back, ask questions, and trust your own observations, too.
Because sometimes, the best data point isn’t on the screen - it’s in how you feel when you wake up.
