Data Points at Dawn-ish
Photo by Patrick on Unsplash
What four newsletters taught me before I got vertical
I hadn’t gotten out of bed yet.
Four newsletters. One conversation with my sister the night before. An audiobook about linear regression I’d fallen asleep to and then couldn’t stop reading. And somewhere between the sleep timer running out and the coffee I hadn’t made yet, I started seeing data points.
That’s the thing about algorithms. They don’t know but they know. They find you whether and when you’re well rested or tired, you’re Black, a Person of Color, white, a woman or femme, non-binary, queer, watching the World Cup, raising pets, children, mailing in your ballot, or trying to build something values-aligned in an economy that keeps trying to extract from you. They know you clicked. So they send you more.
It actually started weeks earlier while talking on the phone with my sister during our regular walks. Our walk-and-talks are part of our sister ritual. It’s not quite daily, the walks, that is, the talks are multiple times a day. I found a statistics book at my neighborhood Tiny Library. A neighbor unwittingly left me a breadcrumb. I used the statistics book initially as a laptop stand. Ergonomical. Economical. A DIY standing desk in the living room to mix up my own indoor regime. Then I started reading it. Voluntarily.
Welcome to the Summer of Statistics, Swimming, and (Regression) Modeling.
Which is how I ended up at 1am with Scott E. Page’s The Model Thinker open on the tablet beside me, reading about linear regression, variables, significance, and magnitude. I’m not trying to become a statistician. I’m trying to understand the chaos and mitigate some of the uncertainty. Find paths forward. That’s a different thing.
Here’s what the algorithm sent me that morning:
One writer — scrappy, self-made (aren’t they always), presumably well-intentioned — telling me that if I’m not making money online, it’s entirely my fault. The cure, he said, was ruthless posting, brute force, and working like a horse instead of a lion. Tim Denning’s words.
I’m not mad at him. I’m not even sure he’s wrong. But I noticed something: his framework was built from a very specific set of variables. Left high school. Worked a banking job that didn’t fit. Found his way out through sheer volume. Good for him. Truly. But his regression model is not my regression model. His variables are not my variables. His intersections don’t run as deep as he might believe.
Adam Grant — organizational psychologist, author, and one of my returning sources for good reason — was writing about the mental health crisis and pointing at perfectionism. He named something true: that perfectionism isn’t a character flaw. It’s a learned response to environments that punished imperfection. Similar to folks who always show up early because the consequences for being late were too painful to risk. The parent who penalized an A-minus. The coach who berated a missed shot. The system that told you good enough was never going to be good enough. I held that one for a minute.
Photo by Marco J Haenssgen on Unsplash
From Adam Grant's Granted newsletter — worth slowing down for:
Ten reframes for the perfectionists, the over-preparers, and anyone who learned early that the margin for error was smaller for them.
Mistakes don't make you a failure. They make you a learner.
Achievements are not a symbol of your worth. They're a snapshot of your performance.
Beating yourself up doesn’t make you stronger; it leaves you bruised. Don’t say anything to yourself that you wouldn’t say to a good friend.
It’s impossible to please everyone. Decide whose opinion matters to you—and whose doesn’t.
Character is not revealed by how many setbacks you face. It’s forged by how you face them.
People gauge your competence mostly by your hits, not your misses.
The objective is not to be the best; it’s to get better. The person you’re competing with is your past self, and the bar you’re setting is for your future self.
Our biggest regrets aren’t actions—they’re inactions. Don’t set yourself up to wish you’d taken more chances.
Healthy goals include two targets: an aspirational result and an acceptable outcome. If you fall anywhere between them, you haven’t failed.
Success is not a straight line. It’s a squiggly line
Because here’s what neither Denning nor Grant named directly: some of us aren’t perfectionists. We’re closing loops our brains won’t let us leave open. We’re navigating literalisms, seeking out more shades of gray, trying to make sense of systems that don’t make sense to our brains. We’re justifiably concerned — but working hard to stay curious instead of catastrophic.
We’re looking for simplicity. Groups. Tribes. Comfort. Containment. A clean dining room table. Our car keys.
That’s not a character flaw. That’s not a mindset problem. That’s an accurate read of a world that was not designed with our nervous systems in mind.
Then there was Good Company, landing with a warm pragmatic reminder: your next opportunity is closer than you think. You already met your next client.
And then there was Rachel Rodgers and the Hello Seven Team, hitting my inbox via the SHMONEY newsletter with the most clarifying thing I’d read all morning: “We are not Amazon and we are not Apple and we are not Microsoft. Those companies get hammered by the economy because they need millions of customers to keep the lights on. Millions. When you're a small business, you only need 100 customers, a thousand customers. The number of customers you need to be successful and to grow your company is relatively small.”
That one I exhaled at.
Life feels like a regression model exercise. We’re all trying to make sense of how we got here and where we’re going. Rather — some of us are. Plenty are winging it. Avoiding it. A handful are modeling it, deconstructing it. And perhaps the happiest among us are shaping it — and delegating their regression model to someone else entirely.
Is that squad goals?
The Model Thinker has a concept worth borrowing: in any complex system, a small number of variables explain most of the variance. Not all of them. Most of them. Which means you don’t need to optimize everything. You need to find your significant variables and tend those.
My sister has been taking a course on the trauma of money. She’s been watching people — our people, people like us — exhaust themselves trying to thrive inside systems that weren’t designed for their Blackness, their queerness, their values, their voice, their ways of being in the world. The struggle isn’t a data anomaly. It’s historical. It’s an extended pattern — what Scott E. Page calls in The Model Thinker “a long tail running along the horizontal axis corresponding to large events” — which is statistician for: this didn’t happen once, and it didn’t happen by accident. And patterns have variables worth examining. Naming. Disrupting, even.
Her class said it plainly: it’s okay to want to get paid. For some of us, that sentence requires practice.
Here’s the reframe: equity isn’t asking for fairness. It isn’t asking to be rewarded for luck. It’s naming something true — that the lived experience and skills we developed navigating systems that were not designed for us make us the most qualified people in the room to redesign them. That expertise has a price. Naming that price is not audacity. It’s accuracy.
You can’t have connective tissue in these systems without scar tissue. The scar tissue is the credential.
So no. I’m not building a funnel. I’m weaving mesh.
A funnel implies one entry point, one direction, one exit — and most of the people who touch it fall out the bottom. A mesh catches. A mesh holds. A mesh is load-bearing in multiple directions simultaneously.
Things can enter from anywhere. Nothing falls through if the weave is tight enough.
“I am fascinated by what can be layered, draped, strengthened — not just stacked. I want to work with other builders and weavers.”
I am fascinated by what can be layered, draped, strengthened — not just stacked. I want to work with other builders and weavers. Resource amplifiers. Revenue generators, unapologetically. System designers. Provocateurs. If you’re inside a system that isn’t working — let’s re-envision it.
The algorithm doesn’t know your body. But you do. And you already know your people. The question isn’t how to find them. It’s how to show up for them — and yourself — in a way that’s actually sustainable.
I’m learning to start even when I don’t know where it’s going. That’s what the writing is teaching me. It’s always going to be the struggle.
I’m okay with that too.
Stay curious.
Sources & further reading:
1. Scott E. Page —The Model Thinker: What You Need to Know to Make Data Work for You
2. Tim Denning —If You’re So Smart, Why Can’t You Make Money on the Internet
3. Adam Grant —There’s More to the Mental Health Crisis Than Smartphones and Social Media — Granted newsletter
4. Good Company — You Already Met Your Next Customer
5. Rachel Rodgers & Hello Seven — Specializing in working with women, BIPOC, LGBTQIA, people living with disabilities, and other folks from historically excluded communities.
6. 🐇 Bonus rabbit hole — Dr. Fei-Fei Li, A Functional Taxonomy of World Models— the Substack headline I almost clicked before the algorithm had other plans. Recommended for the extra curious.
Data Points at Dawn-ish is a Buzz or Bloom Field Note from The Pollinator Group exploring algorithmic content delivery, equity-centered business strategy, neurodivergent nervous systems, the trauma of money, and weaving mesh instead of building a funnel — written for values-aligned consultants, purpose-driven leaders, and anyone building something real inside systems that weren't designed for them.