Metadata
- Author: Benn Stancil
- Full Title:: The End of Our Purple Era
- Category:: 🗞️Articles
- Document Tags:: Data culture, Data Team Vision and Mission, Metrics layer,
- URL:: https://benn.substack.com/p/the-end-of-our-purple-era
- Finished date:: 2023-09-16
Highlights
A couple months ago, I attended an online conference on corporate accounting. During one of the sessions, the moderator asked a panel how they felt about the current state of accounting. The panelists all agreed that accounting was both important and, unfortunately, doomed to fail inside of most businesses. Most accounting initiatives stall before they deliver anything useful, they said, and today’s cost-conscious executives don’t have the patience for that. Ah, hahaha, no, of course not, this is a lie. Nobody’s ever said that about accounting (View Highlight)
naturally, we’ve come up with new obstacles that are getting in our way. Today, it’s talent. According to a Gartner survey, “less than half of data and analytics leaders (44%) reported that their team is effective in providing value to their organization,” and “the lack of available talent has quickly become a top impediment” to success. Other surveys agree: “60% of data leaders were finding it hard to recruit individuals with the necessary skills.” (View Highlight)
Ok, look. It’s 2023. If our issue is a skill shortage, it’s not an issue. It’s an excuse. (View Highlight)
First, there may not actually be gold in a lot of those thar hills. Most of us may just have “moderately valuable datasets that can inspire moderate business improvements.” Second, finding meaning in data is very hard, as suggested by our continued insistence that most job candidates who are trained to do it actually can’t. Third, even if we do find something interesting, it’s hard and expensive to make it useful: (View Highlight)
by chasing bespoke insights, we build bespoke systems. We design clever metrics that perfectly map to our businesses, measure our performance in ways that are meant to handle the nuances of how we do things differently from everyone else, and tell ourselves that this—that “it depends”—is the right way to do things. (View Highlight)
We do things our way; someone else does it their way; people come to meetings with different numbers; chaos ensues; people lose trust in the entire disciple. (View Highlight)
To create true institutional trust around the work that data teams do, we might need to do what accountants do: Give our work some rules. (View Highlight)
Levers Labs, led by Abhi Sivasailam, is working on exactly this problem. They’ve developed a set of Standard Operating Metrics and Analytics, called SOMA, that is meant to provide universal metrics to measure companies’ operational performance, much in the same way that GAAP standardizes how we measure companies’ financial performance (View Highlight)
A set of understood rules—not best practices, but expected standards—about how to do this job. (View Highlight)
If we never have that, I think we’ll be lost for a long time. People will have to learn every job on the job; trust in data will have to be built project by project, individual by individual. But with something like SOMA, we can lean on our collective wisdom. (View Highlight)
The tendency to bullshit oneself is basically … undefeated. It gets everyone eventually, even the most self-disciplined of thinkers (View Highlight)
If we humans overcome this at all, it is not through individuals Reasoning Harder or learning lists of common logical fallacies or whatever. If we achieve reason at all (which is rarely), we do so socially, together (View Highlight)
We make progress as a discipline not by reasoning our way through our problems individually—as tempting as that may be, given our rationalist proclivities for thinking from “first principles,” or whatever—but through social inquiry, in which we can all stumble forward together. (View Highlight)
It’s this refusal to fit ourselves to an imperfect standard that keeps us from moving forward, and sows seeds of distrust in what we do (View Highlight)
Unrelated but really cool
What I want is a service for finding companies that are teetering over the edge. Get hired easily at an inflated title because they are desperate; work stress free because, who cares, deck chairs and Titanics and all that; get laid off; collect severance; use my inflated title to get a bigger job at another time bomb. I may not make as much as I would if I picked winners, but I also would barely have to work, and nobody would question why I left Theranos after a six-month layover.10 Plus, if you pick a disaster that’s big enough, you can become a whistleblower and they will still make a movie about you. (View Highlight)