So many aspects to this. Are we trying to fit the data to what we’ve already decided? Are we measuring the right things or what’s easiest to measure? Is the data biased or trustworthy?
I think the fundamental problem all corporate data efforts are contained in and therefore constrained by is the root_truth that our economy is based on convincing people who don't want your thing to become customers who bought your thing, and customers who don't want to buy another of your things to become customers who bought another of your things.
The data world could open up, stream continuously, if it were based on actual, live, real-time needs and desires. We are still a species afraid to ask for what we want to want.
What do we want to want?
We can have ANYTHING. We just need to ask for it, and not turn off the asking until it is produced.
Nothing can exist/sustain at those extremes. Humans will learn that concepts like utopia or dystopia are more like platonic ideals. They're pristine hypotheticals only intended to stimulate and attract debate.
We will instead come to know we exist in a notopia, as in 'no, neither utopia nor dystopia can ever exist', where people know (through a firmware update bigger than the Magna Carta) that their idea of utopia is someone else’s idea of dystopia, and understand all the gaps in between classifications. Said differently, it will soon be quantifiable that we are all in fact One, sharing a single information field we call Consciousness ('imagination' is an incredibly useful stand-in if you find 'Consciousness' too cumbersome.)
We will all soon use the Internet, the global neural network, to awaken The Collective to The Single, the signal of global collective consciousness that *DOES* very much want to sustain, support, and Love (life) itself. Maxims/rules will be put in place to serve as global guide posts. Think: backpacking guide for mental thriving regardless of the terrain you encounter inside the culture you enter, whether consciously or not, should they happen to suppress the feminine/anima/Spirit.
Does this make sense to you or does it taste like word salad to your brain?
So many good points — plus the mention of one of my favorite books, Blue Ocean Strategy. Tuesday morning couldn’t have started better.
Let me be clear: my comment is not data‑bashing. Data analysis, when done objectively, is our best tool to make an objective assessment to support objective decisions. The real question is: how objective is the field where we’re trying to develop a strategy?—did I overuse the word objective? Nah... there's no such thing 😉
As Rory Sutherland put it, all data comes from one place — the past. And with it come biases, unknown or unaccounted‑for variables, and “black swans” that are still unexpected but no longer rare.
Add in conflicts of interest and personal agendas — from ideology to ego — and the picture gets even messier. Data collection is rarely clean, analysis rests on assumptions, and while physics can get closer to controlled precision, business rarely does. But it’s in the interpretation where things truly go off the rails, which is why challenging every step matters.
Establishing controls, running sanity checks, embracing fallibility, and setting rejection criteria before looking at the data can help keep us honest.
You’re speaking my language here. Numbers make us look smart, precise, in control — armed with complex theories and algorithms. The mental (and computational) effort involved can trick us into thinking, “this is as good as it gets.” Often, it’s the assumption that hard, complex work = good results. In many cases, data is used for one thing: precision signaling.
So well written Moe, this is a post in itself :). I love your point on how numbers can make us look smart while we might be analysing them in the dumbest manner. Important to know your bias and caveat it but also let data be the clue and not the crutch as I wrote. You can always interpret it differently, always.
Well, I'm trying to post more about this after reading plenty of "grow your Substack" advice with numbers- you've probably seen them too: posting on Monday between 6:16 and 8:32 leads to 23.12 likes and 12.23 comments... no segmentation, no context, no normalization to anything. Just pool 600M notes from the last 2 years across all topics and account sizes and get an average.
In other words, your post found me ready to fire 😀
So many aspects to this. Are we trying to fit the data to what we’ve already decided? Are we measuring the right things or what’s easiest to measure? Is the data biased or trustworthy?
Thanks for highlighting this.
Indeed. I think data bias and manipulation are so prevalent. Less attention is paid to it then needed to this.
I think the fundamental problem all corporate data efforts are contained in and therefore constrained by is the root_truth that our economy is based on convincing people who don't want your thing to become customers who bought your thing, and customers who don't want to buy another of your things to become customers who bought another of your things.
The data world could open up, stream continuously, if it were based on actual, live, real-time needs and desires. We are still a species afraid to ask for what we want to want.
What do we want to want?
We can have ANYTHING. We just need to ask for it, and not turn off the asking until it is produced.
Then you'll see what data can do.
Everything til now was banging rocks together 🪨💥🪨
That is true rob but such a state would be utopia or dystopia depending on how you want to view it.
Furthermore what is to say there would be another leading indicator even before customer demand that someone will start chasing then? Thoughts?
Utopia - Dystopia
Nothing can exist/sustain at those extremes. Humans will learn that concepts like utopia or dystopia are more like platonic ideals. They're pristine hypotheticals only intended to stimulate and attract debate.
We will instead come to know we exist in a notopia, as in 'no, neither utopia nor dystopia can ever exist', where people know (through a firmware update bigger than the Magna Carta) that their idea of utopia is someone else’s idea of dystopia, and understand all the gaps in between classifications. Said differently, it will soon be quantifiable that we are all in fact One, sharing a single information field we call Consciousness ('imagination' is an incredibly useful stand-in if you find 'Consciousness' too cumbersome.)
We will all soon use the Internet, the global neural network, to awaken The Collective to The Single, the signal of global collective consciousness that *DOES* very much want to sustain, support, and Love (life) itself. Maxims/rules will be put in place to serve as global guide posts. Think: backpacking guide for mental thriving regardless of the terrain you encounter inside the culture you enter, whether consciously or not, should they happen to suppress the feminine/anima/Spirit.
Does this make sense to you or does it taste like word salad to your brain?
🙏
The data is telling me I'm right - Wey! A year later - I'm still right but it's NOT working out how I thought it would... 😳
Hahaha indeed.
Very well written and very good point!
Idea: write one on the beginning!
“Should not data-driven be a role too?”
It sounds like a joke, but I think there might be more than meets the eye there.
Thank you Luca. Looking forward to reading that.
So many good points — plus the mention of one of my favorite books, Blue Ocean Strategy. Tuesday morning couldn’t have started better.
Let me be clear: my comment is not data‑bashing. Data analysis, when done objectively, is our best tool to make an objective assessment to support objective decisions. The real question is: how objective is the field where we’re trying to develop a strategy?—did I overuse the word objective? Nah... there's no such thing 😉
As Rory Sutherland put it, all data comes from one place — the past. And with it come biases, unknown or unaccounted‑for variables, and “black swans” that are still unexpected but no longer rare.
Add in conflicts of interest and personal agendas — from ideology to ego — and the picture gets even messier. Data collection is rarely clean, analysis rests on assumptions, and while physics can get closer to controlled precision, business rarely does. But it’s in the interpretation where things truly go off the rails, which is why challenging every step matters.
Establishing controls, running sanity checks, embracing fallibility, and setting rejection criteria before looking at the data can help keep us honest.
You’re speaking my language here. Numbers make us look smart, precise, in control — armed with complex theories and algorithms. The mental (and computational) effort involved can trick us into thinking, “this is as good as it gets.” Often, it’s the assumption that hard, complex work = good results. In many cases, data is used for one thing: precision signaling.
So well written Moe, this is a post in itself :). I love your point on how numbers can make us look smart while we might be analysing them in the dumbest manner. Important to know your bias and caveat it but also let data be the clue and not the crutch as I wrote. You can always interpret it differently, always.
Well, I'm trying to post more about this after reading plenty of "grow your Substack" advice with numbers- you've probably seen them too: posting on Monday between 6:16 and 8:32 leads to 23.12 likes and 12.23 comments... no segmentation, no context, no normalization to anything. Just pool 600M notes from the last 2 years across all topics and account sizes and get an average.
In other words, your post found me ready to fire 😀
Hahahah good to know.