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- When the dishwasher was introduced, research showed that "80% of people" would be impacted.

- When email was introduced, research showed that "80% of workers" would be impacted.

- When Gmail introduced predictive sentence completion, "80% of people" were impacted.

So please don't get concerned this will result in job loss.



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> It showed that productivity dropped by 18% among a group of workers randomly assigned to WFH.

Sounds like a random insignificant outcome to me.


Not that it lessens the blow any, but it's worth mentioning that these figures are across the entire employment spectrum. Some of the commenters mention large hits in management, but it can also represent the freefall in construction and other especially vulnerable blue collar/service industries.

Probably because I am in the midst of starting my own job search and targeting SF/SV, I got a little unnecessarily worried. This is not a tech job specific figure.


How about not guessing and reading the statistics:

http://www.technologyreview.com/featuredstory/515926/how-tec...


> Its survey last year found that almost 90 percent of workers were either “not engaged” with or “actively disengaged” from their jobs.

Is this true? That seems like an very high number.


I think this just reveals bad hiring practices, more than anything else.

There are 1,000 different things that can affect your productivity. Maybe her migraines cause 15% "lost productivity", but her enthusiasm causes 35% better quality work, her daydreaming cuts 10%, and her intelligence adds 20%, the fact she's stimulated by spicy food adds 5%, etc.

Companies that might attempt to do this kind of micro-analysis miss the forest for a few trees, will be less competitive in the long run, and over time will die out.


Why not break this into:

N% have lost jobs

N% have lost hours

We don't have N% have dead or infected with cv, do we?


Clickbait; the author jumps from “41% of employees are considering leaving their employer this year” (original source) to “Microsoft predicts 41% attrition.”

Scanning for 20 seconds showed some of those numbers are 5% of the workforce, that's not insignificant.

> 0.15 % of the entire us population just for cyber security?

Even better: 0.15% of the entire US population for unfilled jobs.

I'm going to assume most of these aren't permanent positions but gigs.


Concerns are just sentiment: 0.25% is still very low. Need to see sample size.

Won't be surprised on how today's exaggerated and manipulated media will impact employee outlook and fears.


> 60-70% drop in hires compared to our original (pre-COVID) projections for the month

what was your original projection


Key paragraph:

> Because previous years have been reliably consistent and because our competitors' numbers are off by similar measures, we feel confident assuming fewer jobs are available across the industry. Whether it's 40% fewer or another amount is anyone's guess.


I've personally been asked to look at H1s instead of local staff to save wages (they cost 1/3). I'm in management now, but when I wasn't, you really would have expected a study to negate my own self-interest as an employee threatened with unemployment, and ultimately negate myself so that tech companies can rake in more profit and ultimately bring the aggregate numbers up (which is the net effect you highlight)?

> Until i see the data

What do you think the “percentage change in the largest 100 metro areas’ share of digital services jobs, from 2020 to 2022” may is?


That's an interesting and informative read, however one line did catch my eye, and increase my background level of despair at the general maths/stats level of the wider population:

> An overwhelming majority of employers, 48 percent or so


But that's not the implication of the study itself, or at least it's not at all obvious. That would be the implication strictly from the headline and a lot of people are making comments that suggest that they only read the headline or perhaps the first two sentences.

The study itself shows that if the company hires someone else from within the organization, the effect disappears. So at very least from the data one can't immediately conclude what you assumed.


> 4%–5% attrition YoY would be low, IMO. My experience is closer to 30–50% YoY

50% is fast food level attrition. 12% is bottom tier in tech.


Joel Spolsky's article, "Everyone thinks they're hiring the top 1%" seems relevant here.

http://www.joelonsoftware.com/items/2005/01/27.html


https://www.bls.gov/ooh/computer-and-information-technology/...

The number of "jobs" added doesn't quite double, but if we think of it as "for every 4 that retire, five take their place" it would definitely feel like what you're saying.

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