Probably? But it's mostly just a return to sanity at this point, though it probably will overshoot as these things usually do. Meta going from 47K employees in 2019 to 81K employees in about 3 years was just crazy, for example. How do you even assimilate that many new employees in such a short time?
> But it's mostly just a return to sanity at this point,
That's what the word "correction" implies: That it's going down, not because the business itself is bad or anything in the market has fundamentally changed, but because it was valued "incorrectly" (where "insane" would be an extreme form of "incorrectness"), and that its value is being "corrected".
I see UncleOxidant as saying it's a 2020-2021 correction, distinct from the larger talk of a correction that's been going around for years now even pre-Covid.
I haven't seen signs of that latter, larger one yet. Fingers crossed...
Exactly. Look at graphs of employee growth at the large tech companies between 2019 and 2022 - we're lopping off some of that growth... probably will end up lopping off a lot of that growth before this is over.
All the layoffs announced (sans the Musking that just happened) are in line with normal annual attrition plus a bump given the huge hiring spree during the pandemic to meet pandemic demand. I’ll bet $20 if you took HC growth prepandemic and straight lined it through to today inclusive of layoffs you would see normal YoY growth between those two points, which an aberration in 20/21 of high hiring. I think you’ll see a bit of party hangover and if the whole economy sinks it’ll get worse. But overall I’ve not observed any material structural shift in the world or in tech, unlike say the dot com bust or the global financial crisis. There’s some cold spots though like real estate tech that’ll probably go through a tough time.
I think a lot of folks here have never been through a down cycle before though and anything that’s not frantic growth and double digit comp growth YoY will feel like a nuclear winter.
the correction is happening now. the pandemic pushed all these tech companies up artificially. they hired in record numbers to meet demand and thought it would be permanent/the new floor. The economy has since rebounded and companies are returning to previous levels. The war isn't helping however
>"the pandemic pushed all these tech companies up artificially. they hired in record numbers to meet demand and thought it would be permanent/the new floor."
This is the really surprising thing to me - many(most?) of these companies are data driven companies. Companies with teams of analytics folks, data scientists, modeling-experts and teams of engineers working on tools to do ML and large scale data analytics. Do none of them actually use their tools and internal expertise to model their own hiring practices and historical market trends? Or maybe they did and always knew they would need to do mass layoffs when inevitably the cheap money pump got shut off?
I hope that if we've learned anything from the past few years, it's that you can interpret and manipulate data to make it say whatever you want to say. That's true even when analyzing data about the present, doubly so trying to predict the future.
Being data-driven is a method for justifying decisions. But it's still a human making a decision in the end.
>But it's still a human making a decision in the end
I've got a story here from a previous job that illustrates this.
I used to be part of an Analytics and Forecasting team at a well known non-tech company. It's a global company that sells a lot of things to consumers. This means they strive to have a very good understanding of sales and manufacturing volume because that drives everything from raw material orders and supplier contracts to how much of product to put where so people can go and buy it.
We had short term forecasting teams generating forecasts (at a brand level) and analysts (mostly aggregations, not really statistical inference) that rolled into a medium term analytics/forecasting team(s), that rolled into a long term analytics/forecasting team(s). Not to mention Research teams that did pure statistical and economic modeling to try and understand market factors in a more comprehensive way so they could better inform all these forecasts. All of this went right to the top of the food chain.
The glue between all these teams were managers. And one of the fundamental problem for managers with all of this comes from this simple question - if one of these teams provides a forecast that is very different from the rest, what does that mean? Is that team right or wrong? And how does that information now flow into the other teams so they can incorporate it into the info that goes upstairs.
From this question emerges an astonishing amount of group think. Not just from the company I worked at, but at all competitors as well.
When companies ask "Do we forecast sales to go up" they are really asking "Do we think this market segment is going to go up in the future and we have the right strategy to move up with it?" Cars, Snacks, phones, whatever the market segment, you're really asking how you are doing compared to your competitors in the space.
To understand where you are going, you need to understand how your competitors are doing. This data comes from agencies and consulting houses. But since everybody uses the same data from the same agencies, everybody is feeding each other. What can emerge from this is a massive amount of group think.
I'm greatly simplifying everything of course. When these teams get it right they do amazing stuff like making sure the thing you want to buy is available when you want to buy it. But when they get it wrong, it seems like most everybody else gets it wrong as well. This can slowdown an entire industry as everybody realizes they got it wrong.
The risks of under-hiring if things had continued and not being able to keep up with competitors was probably just too great. It's much easier to simply lay people off if the bubble pops than to play catch up if it doesn't.
What do you do when the model says your favorite project (say the one that got you promoted or is getting you promoted) is a bad idea? Heck, forget fancy modeling, what does an excel sheet say?
As old as the bible, the saying, "Physician, heal thyself!"
I work as a data scientist in the grocery industry, specifically (at least for the past six months) on sales forecasts. Even for relatively short-term forecasts accuracy is surprisingly low, even with lots of data and the most up-to-date forecasting methods, applied by smart people (those who aren't me). I'm not at all surprised that companies can't see precisely when downturns will happen.
> Do none of them actually use their tools and internal expertise to model their own hiring practices and historical market trends?
This! It’s exactly what have occupied my mind since layoffs started. May they did use tools. But, remember the output is a forecast, not a shining light out of a crystal ball. Estimates/Forecasts can go wrong and clearly turned out that way.
Its a difference now that there are waves of people coming to software from other industries. Its one of the few industries that does not require certification, pays great and you can pick up relatively quickly.
There was the dot com bubble burst in 2000, so there has actually been one. A few years after the 2008 crash sounds about right to when people started talking about tech bubbles again to me.
I lived and worked through it and I’ve not seen tech slow down measurably, even then. There was a correction, and a shake out, but then it picked up basically where it left off and shot up. There have been other busts over the last 70 years but they’re more like a system that overheats, slows, then resumes.
All the signs were there for everyone to see in the 2000 Dotcom Dotbomb. The root problem was a bunch of investors wildly investing in crappy tech companies, like tinder for cats. There were toxic assets, huge and publicly visible waste, low product output.
This time, there is a lot more growth from many companies but we also see the results of that work, products and services exist as a result. There is waste but not like in 2000.
Agreed, these recent moves are not a great sign, but the dot com crash was so much worse from a people and company perspective.
The moment that sticks with me is (former) employees wheeling all the Herman Miller chairs through the parking lot with the facilities guy holding the door open saying "Take it. Take it all..."
