狗家砍人的標準

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I think I've figured it out. Poll below. Please read ad nauseum.

Each PA was hit differently. VPs were given targets. Layoffs are *always* a mathematical formula. It needs to optimize for "something", which I argue in this case is sustainable labor focused on high performers only at least possible price, ideally with "trajectory" to grow and have more impact at Google.

The formula looks at the variables below, and then spits out a "number" for every Googler. Each PA VP gets a % to cut, and as such there is a threshold. Anyone below that threshold gets RIF'd.

Variables are:

1) Location of labor. US Premium Plus was largely impacted versus cheaper areas.
2) Tenure and performance in level.
3) "Runway" of comp. (e.g. base salary vs MRP.  eg. .8 of MRP Googlers have a long runway, vs 1.x of MRP Googlers are basically top of band, and 'tenured' with no runway except promo
4) Promo velocity
.
Examples:
1) US-SVL L6 CME consistently at a very high pay versus the market reference point = top of list.
2) US-CAM L6 consistent >EE + bottom of MRP = much lower on the list

I've run enough polls to say that I think I got most of this right. I'm sure there was weighting involved to come out with an actual formula.

Say whatever weighted formula spits out Googler #1 at "8", and whatever weighted formula spits out Googler #2 at 5.

-If VP1 needs to cut 20%, and as such their threshold is "7", then Googler 1 gets booted.
-If VP2 needs to cut 5%, as as such their threshold is "9", then both survive
-If VP3 needs to cut 50%, and the threshold is 4, then both are RIF'd.

Other variables:
1) Managers (<=4 directs) with not enough direct reports
2) Lower levels were also disproportionately impacted as well,
3) Tenure <1 year

Think about it as a company

If you can get high performing L6s that are being paid much cheaper (say in Canada, EMEA, JAPAC) who consistently have high performance reviews and have a long runway (from a comp perspective) in their level, why wouldn't you prioritize these?

**
Note: GRAD/SCI was not a factor. That I have figured out. Past performance ratings WERE a factor as per the manager FAQ.

==

Data sources:
1) Seemingly no correlation between last perf rating and RIF
2) No correlation with GRAD/SCI and RIF
3) People who were just promoted in the last perf cycle were largely not impacted.
4) A very high # of L8s and higher who have been at Google for 10 + years were impacted. These individuals were very likely CME forever given their level and pay.

==

Discussion points
1) For those impacted, take a look at your performance in level. Has it been flat (eg. a bunch of CMEs in a row?)
2) For those impacted, have you consistently had EE and higher and have you been promoted quickly?

***Think about it. After the RIF is done, who do you want left at Google? You want the rockstars that have room to grow.
. 1point 3acres
Who do you want out of Google? Expensive coasters.

补充内容 (2023-01-23 01:13 +8:00):
个人感想：
我觉得还有一个factor就是vp/svp对每个team/project的“重要度”评分， 不重要的权重应该会给的大一些。 这样我们应该就有一个比较完整的formula了。

但是我跟作者观点不一样的是： 个人觉得这个formula不是deterministic的，它应该会给出一个0到1之间的数字，也就是裁员概率，然后为每个人生成一个随机数，随机数<这个概率就被被裁了。不然没法解释为什么也有一小部分high performer被裁掉。

匿名用户 发表于 2023-1-22 09:05
给看不到图的兄弟姐妹上文字版：

也看org了。
如果是边缘部门，可有可无的组，high perf也无所谓了

匿名用户 发表于 2023-1-22 03:18
MRP是指什么

market rate pay

匿名用户 发表于 2023-1-22 00:18
MRP是指什么

market reference point

突然发现有点像三体里面的枪手和农场主故事。火鸡科学家也不是没有意义的，至少前面300多天是正确的，可以参考

匿名用户 发表于 2023-1-22 03:12
我个人认为研究哈佛招生标准没有意义，而且是一点意义都没有，理由如下：
1. 会去研究这个的所有人都没 ...

. ----别笑死人了，我都懒得反驳你

我只是试图防止你们浪费自己的时间，要去研究是你的个人自由

TLDR：裁的是到了terminal level常年CME的，以及包大的。

总结的不错。

公司不同，估计标准也不同。但是大方向不错的。
第一，肯定是不能违法；第二，肯定是要cut cost。如果你性价比不够高，自己琢磨吧。这一点资本家和打工人刚好相反。

匿名用户 发表于 2023-1-22 03:12
我个人认为研究哈佛招生标准没有意义，而且是一点意义都没有，理由如下：
1. 会去研究这个的所有人都没 ...

对的，而且拿自己一个例子，或者一部分例子，存在幸存者偏差。搞不好结论都是反的。

匿名用户 发表于 2023-01-22 09:05:14
给看不到图的兄弟姐妹上文字版：

谢谢文字版