> It's very naive to think these huge orgs don't have dead weight which is much bigger than 6%.

Pretty much my experience that when a company keeps growing, at some point most corporate employees will not actually be contributing anything.

Paradoxically, constraining teams with resources (but allowing them to make their own decisions) makes teams more efficient than if they had resources. Necessity is the mother of invention -- when people are forced to deal with the problem they will find a solution.

Corporations are worst possible places to be efficient -- not only you have the resources (and most people get lazy when they don't have to be inventive) but you are also typically not even allowed to be inventive as companies typically work towards centralising decisionmaking rather than allowing teams to steer themselves.

Same goes for hiring. I worked with teams which hired anybody because the manager was forced to hire quickly or loose budget. Or managers hired people just to enlarge their estates because headcount was how they decided who is more important.

So I completely understand why companies are laying off people. The only question is whether they are too optimistic about being able to identify who to lay off, exactly.

In my experience it is pretty difficult even for managers to understand who are best contributors in their teams. Get removed 2-3 levels from a line manager (2-3 levels is where the decisions would typically be made) and you can pretty much dream about understanding who to lay off, individually.

Presumably they already have performance processes that eliminate "dead weight". Be assured that layoffs never really mean that usual performance bases firings are paused. It's pretty much always happening on top of existing performance processes.

Layoffs like this mean you can blame external forces like the economy rather than saying, "our projects failed".

Some of these layoffs may have been coming anyway, but not the corporate statement about them is different.

I've seen this play out the consulting world which puts a much finer point on the process. There, work is all project-based. We build something for a customer and then maybe build another thing or otherwise move on to something else. There's basically no long-term value for our own business beyond unquantifiable things like reputation. When the pipeline dries up and there's not enough work to keep everyone staffed, layoffs happen. And as much as we tried to be meritocratic, being good at your job was less visible than being ok at your job while working on a valuable project. It was incumbent on managers to do emergency shuffling if they wanted to stash top performers on good projects or vice-versa, but it wasn't easy.

It is also naive to think layoffs effectively target dead weight. As more extensive layoffs are often decided by senior management rather than team leaders, such releases have a high signal-to-noise ratio.

Natural attrition will also not be close to 0 in the next year or 2. Even if the markets stay stagnant, there will be the usual musical chairs turnover (a Facebook employee joining Google replacing a Google employee who joined Facebook).

Layoffs are usually family within company graphs, with this family then naming the "guys" necessary for the departments to do there job. Means, you have dead weight forced to identify the vital organs, allowing to fire the "medium" weight. Yes, connections or talent are everything. No, its not fair.

> If you're used to 5% of people leaving on their own per year, assume its closer to 0% for 2023 and 2024

Strongly doubt this claim. Especially for employees of a sought-after firm like Spotify, there will always be people jumping ship either to other big co's or to join startups/start their own thing

>It's very naive to think these huge orgs don't have dead weight which is much bigger than 6%. If you start figuring some of your moonshot ideas aren't hitting their OKR's, you have a few options:

there's been so many versions of this low quality comment on every tech-company-mass-firing article. why is so little thought put into it? if the company feels it can save on salaries then:

1. close down projects that aren't effective/profitable/whatever

1. fire people who aren't effective/profitable/whatever

mass broad spectrum layoffs like these are not that, they're "oh, let's just randomly put holes in the org chart to save X% of salary and see how it goes". would you suggest saving data storage costs by deleting 6% of files? would you suggest reducing compute by turning off 6% of jobs?

Why do you think that mass broad spectrum layoffs are random holes? From what I've seen they follow exactly the structure you're describing - there's a company-wide search for projects that aren't pulling their weight, those projects are shut down, and the employees whose roles no longer make sense without the projects that will be shut down get laid off.

> would you suggest saving data storage costs by deleting 6% of files? would you suggest reducing compute by turning off 6% of jobs?

I would, and I've seen mandates like this achieve good results multiple times in my career. It's very rare to have a team that can't make do with 94% of their data storage footprint, but it's very common to have a team who would find it temporarily inconvenient or would rather prioritize other work over reducing it.

> Why do you think that mass broad spectrum layoffs are random holes? From what I've seen they follow exactly the structure you're describing - there's a company-wide search for projects that aren't pulling their weight, those projects are shut down, and the employees whose roles no longer make sense without the projects that will be shut down get laid off.

I’ve been through 2 companies with layoffs in the past year. What you describe is not how either worked. There were some targeted shutdowns, but many teams also just lost a member or two. In both cases my teams lost important people which have a really bad impact on the rest of the team.

> Why do you think that mass broad spectrum layoffs are random holes? From what I've seen they follow exactly the structure you're describing - there's a company-wide search for projects that aren't pulling their weight, those projects are shut down, and the employees whose roles no longer make sense without the projects that will be shut down get laid off.

? what are you talking about? The Google layoffs weren't like that, nor the Meta ones nor the Amazon, and I'm pretty sure the Spotify ones this article is about aren't either, though the post is very short.

I know quite a few people who were laid off at this point. I'm not seeing what you are. It's quite random.

As I mature in this industry I find it hard to agree, even though I draw my experience from organisations outside the FAANG if it’s still a thing. Dead weight, is in my experience no more than 2%, where I qualify dead weight as someone who cannot add value or is actively detrimental. Most people can add more value than they currently do. Many more people do not match their capacity, but that is mostly out of bad allocation of work etc. That bad allocation could be improved with restructuring but crowded and rigid management hierarchies are often the reason organisations don’t grow at the risk of diluting the self perceived value of upper-middle management. I think this round of layoffs will see a rebalance across sectors with banking etc. looking at huge resourcing demands that are inelastic (e.g. regulation) pulling in some of the talent. Similar to Covid layoffs outside tech, my prediction is the inversion will start soon.

I agree. But IME the number of "dead weight" varies heavily depending on some factors. I've definitely seen teams with >10% dead weight, because of a combo of bad hiring process, coupled with management not caring to check on them. Of course that might be a biased view: in the cases I know, the managers couldn't manage to get them back to speed, but those were managers that had failed on the hiring/day-to-day already.

After 1-3 years of tenure things start to look different imo. Sure you get bad hires, and you also get people who become lazy. But on any given project you tend to have some split of people who work on the wrong things, don’t work on anything, or fail to deliver. People who consistently hit one of these categories usually move on on their own - either because of culture fit or comp growth. It’s much easier and healthier to focus on retaining your best people. As long as someone is doing something, and isn’t a net drag on the team - firing seems to be more pain then the alternative in software.

Assuming that the industry returns to its standard 30-50% attrition year on year.

And those people become lazy because they put A LOT into the company those first 1-3 years. And after they coast a bit, they usual come back strong because 1. They are intimately familiar with the corporate culture and the internal software paradigm and 2. They have emotional investment. It's like getting divorced in your early 40s because things are not the same as a few years before, and not getting to the good part of a relationship.

Absolutely! I also didn’t quite see it when I moved around earlier in my career - but many of the more tenured folks simply know how to work efficiently in the organization.

They tend not to pick up meaningless fights, or invest time in work that the org doesn’t care about, when their are debates - they can usually settle them.

In hindsight I spent too much time early in my career on work no one cared about. I spend less time on that stuff now and have better wlb and feedback to boot.

You also transform a good percentage of your high performers into low performers (until they leave and high perform somewhere else). I've seen it happen every time.

> Create new moonshots for them just because

This seems disingenuous? They're "moonshots" as they've low chance of succeeding. You could pick the most proficient engineers and out-of-the-box thinkers and put them working on a "moonshot" and they'd still fail. Giving that team a new lofty goal seems like a great idea since they have experience working on large problems and can likely prune good/bad approaches much sooner than a fresh team.