building the metrics platform of the future at Trace (https://teapawt.net/t.co/7Oo0We0pfZ); data snorter, product creator; ex-@renttherunway, @oracle
New York
Joined May 2010
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3/3 Here’s a list of 20 such opposing/complementary forces in company building - obviously not an exhaustive list but the ones I’ve encountered most (and remembered!) that need to be managed in harmony.
Analytics needs more science. Data science needs more engineering. Engineering needs more analytics.
Fascinating study. $ issues aside, free transit does not drive the incremental usage shift from the non-transit segment - and actually makes it less likely for this to happen. Higher frequency, better connectivity and experience - the factors that matter are simple and timeless.
I had the opportunity to study free public transit in depth for an economics project at HEC. Although my colleagues and I were initially favourably biased towards free transit, our study led us to conclude against it. Here's why (thread)
@TaylorNoakes #STM cultmtl.com/2022/05/30-dolla…
Using subtle modifiers like “up to” helps arm-twist the data to feed your narrative. Happens frequently in orgs in slide decks.
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For this group, it was never about legal vs illegal immigration or assimilation or what-not - it’s always been about the “browning” of the country in the last 2 decades coded through other variables.
As a general rule, I should avoid reading Benn’s weekly takes on a sun night at 11pm. I’m now going to spend the next hour thinking about hype cycles, brand vs product marketing, CIO vs bottom up adoption, category creation vs better mousetraps, warehouses vs lakes/lakehouses.
it's friday, let's fight about whether or not $38 billion is a lot of money
benn.substack.com/p/the-end-…
When you click submit and realize you did NOT uncheck the send promotional emails box - and it’s your work email!
I’m taking today, April 1st off - to reflect on my career as a data practitioner and an operator. And I’ve come to the shocking realization that data, numbers, tables, metrics, models, what-have-you are completely made up concepts. Just figments of our imagination.
(I kid! I kid! - really really looking forward to meeting some folks I’ve only known via Zoom and hanging with fellow Brooklyners - @bennstancil and more?)
Vijay Subramanian retweeted
A metric is a deceptively simple object - there is much to be discovered as you explore. It matters how it's composed, and how it's further transformed. It matters how it's connected to other metrics. And it deeply matters what moves it and why. This is the essence of analytics.
I’m old enough to have seen a generation of data influencers pat themselves for anointing “data science” as a profession and a newer generation take a slow protracted shit on this term.
Unfortunately Canada’s $1M check per person per year didn’t have the same impact.
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This is a case study in data interpretation - this pattern repeats in orgs. Often b/w the business and analysts.
1) it’s crazy that folks vaxxed/boosted are this worried about covid vs the unvaxxed!
2) it’s the ones actually worried about Covid who got vaxxed and boosted.
Corollary: if you find a business leader who immediately reasons through this, you are in good hands. That’s the truly numerate decision-maker who will make things happen. Not even the other exec who pores over dashboards every day but can’t reason through it.
Vijay Subramanian retweeted
These two graphs side by side are a red alert for American growth and innovation
The recent swing to infuse the data world with engineering principles has a cultural side effect where running data pipelines well seems like mission accomplished. it’s necessary but nowhere near sufficient. So much more room to make orgs numerate and better decision-makers.
Some key themes for 2022: create tools, systems, and processes for data to inform executive decision-making and strategy (AND visa versa); stop treating data like exhaust. Such a great time chatting with @juansequeda and @TimGasper!
