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Have we hit bottom yet?

Searching for green shoots using job offer metadata

Jun 13, 2023
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Have we hit bottom yet?

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NASDAQ is up 28% year-to-date, although still off 2021 highs.

What about the talent markets?

With tech companies continuing to layoff thousands each month, it’s hard to believe we’ve hit bottom yet, but we can find some early, although uneven, signs of recovery in job offers.

I analyzed offer trends in the top US tech markets — San Francisco, New York, and Seattle — to understand where the market is going next.

Tl;dr: we might have hit bottom last quarter:

  1. Offer acceptance rates peaked in Q1, but not everywhere

  2. Offer volumes are still trending way below last year

Summary of my analysis below.

What do you think — have we hit bottom yet?

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Methodology

To analyze offer data I used Compa Index, a source of real-time market data based on actual offers from our network of enterprise technology companies.

I wanted to look at high-volume technical roles, so I filtered to engineering offers only and excluded offers for management positions.

I focused on three major tech centers: San Francisco, New York, and Seattle. These markets generally have higher volumes (read: more reliable data), and also I’m curious whether there are differences in recovery, if any. Note these locations span the entire metro area, e.g., San Francisco = the City, Oakland, and San Jose.

The analysis spans nearly six quarters, January 1, 2022 — May 25, 2023.

As far as metrics go, I decided to set aside actual compensation amounts, a much bigger analysis, and instead focus in on two useful pieces of offer metadata:

  1. Offer acceptance rates as a measure of market softness, e.g., rising rates suggest candidates may be willing to accept lower pay

  2. Offer volumes as a measure of overall market activity

I love these metrics because they have a predictive quality. They remind me of similar housing market metrics like sale-to-list ratio and home sales.

Offer acceptance rates

Offer acceptance rates for eng IC roles. Source: Compa Index

Offer acceptance rates are at historic highs, currently 81% this quarter, up from 59% the same quarter last year.

With a supply shock of laid off talent (as I recently wrote about here), candidates will accept less to get employed again. Yikes.

But it looks like acceptance rates may have already peaked in San Francisco and New York:

Offer acceptance rates for eng IC roles by metro. Source: Compa Index

By comparison, Seattle acceptance rates are still rising, with a large upward spike this quarter. Perhaps this is driven by recent layoffs at Amazon that could impact the entire metro area.

I think it’s too early to draw firm conclusions, but the acceptance rate drops in SF and New York give me cautious optimism.

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Offer volumes

Offer volumes indexed to Q1 2022 = 100. Source: Compa Index

This is an ugly picture.

Offer volumes are off a staggering 88% from market highs in early 2022.

And this is for engineering ICs. Middle-management and corporate roles, the focus of recent layoffs, may be faring even worse.

Tech companies just aren’t hiring nearly as many people as they were before.

Looking at it by each of the major tech metros reveals a similar story.

Offer volumes by metro area indexed to Q1 2022 = 100. Source: Compa Index

Offer volumes are way down by every market, but SF is far and away the worst at 92% below early 2022 levels.

Interestingly, the drop in activity happened in SF much faster than New York and Seattle, which both saw elevated hiring late into 2022.

Note that Q2 is 60% complete in this analysis (May 25), so I extrapolated the partial quarter rate through June 30 to make the numbers comparable.

Note also — I indexed each metro to 100 for Q1 2022 to compare volume changes by area over time. San Francisco offer volumes dwarf other metros, 7x larger than New York and 3.6x larger than Seattle.

What happens next?

This analysis paints an overall grim picture, but I think the falling acceptance rates in San Francisco and New York could be green shoots.

There’s more we could analyze — actual compensation amounts tell an important story, as do the relative levels of hiring, i.e., volume of P3 versus P5 offers.

And then there’s the question we’re all asking: will AI save us?

(or just take our jobs…)

Next time I’ll drill into offer trends for AI / ML / data scientist roles to see what we can learn.


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