谷歌人事部資深副總裁談領導統御 - 面試

谷歌人事部資深副總裁談領導統御、遴選人才、以及GPA的無用
[又：如何用巨量數據處理來導正領導統御觀念]

This interview with Laszlo Bock, senior vice president of people operations
at Google, was conducted and condensed by Adam Bryant.

本篇係從紐時專欄作家 Adam Bryant 訪問谷歌人事部資深副總裁 Laszlo Block 之訪談
全文擇要刊出
[刊出後，由譯者再擇其精髓節錄翻譯之]

Adam Bryant 專欄原文：

http://www.nytimes.com/2013/06/20/business/in-head-hunting-big-data-may-not
-be-such-a-big-deal.html
短網址：http://goo.gl/wLZd1

--------------------

Q. How is Big Data being used more in the leadership and management field?

問：你們谷歌在領導統御方面如何使用巨量數據處理？

A. I think there's been a fairly recent confluence of the ability to crunch
lots of data at fairly low cost, venture capital investments that support new
businesses in this field, and changes in what people expect. Leadership is a
perennially difficult, immeasurable problem, so suddenly people are saying, “
Maybe I can measure some piece of it.”

(譯註：我個人認為這段沒意思，故略。)

Part of the challenge with leadership is that it's very driven by gut
instinct in most cases — and even worse, everyone thinks they're really good
at it. The reality is that very few people are.

答：領導統御的挑戰之一就是大多數人都「憑感覺」，而且更糟糕的是，大家都自以為自
己很會。實際上，只有極少數人有這方面的才華。

Years ago, we did a study to determine whether anyone at Google is
particularly good at hiring. We looked at tens of thousands of interviews,
and everyone who had done the interviews and what they scored the candidate,
and how that person ultimately performed in their job. We found zero
relationship. It's a complete random mess, except for one guy who was highly
predictive because he only interviewed people for a very specialized area,
where he happened to be the world's leading expert.

多年前我們做了項研究，探討谷歌公司裡有沒有人特別懂得遴選好員工。我們審視數以萬
計的面試資料，包括面試官給面試人的評分，以及面試人最後在谷歌公司裡的表現。我們
找不到任何一點相關性。面試官評分跟面試員表現之間的相關性完全是隨機的一團亂，我
們全公司只有一個人能夠很有效的預估職員未來表現。這是因為這個人只面試某個高度專
業領域的人，而他本人正好是該領域的世界級專家。

Q. Other insights from the studies you've already done?

問：你們的[人事數據化]研究還顯示了哪些重點？

A. On the hiring side, we found that brainteasers are a complete waste of
time. How many golf balls can you fit into an airplane? How many gas stations
in Manhattan? A complete waste of time. They don't predict anything. They
serve primarily to make the interviewer feel smart.

答：在遴選及面試方面，我們發現「腦力激盪」題目完全是浪費時間。就是那些「一架飛
機裡能塞幾顆高爾夫球」、「曼哈頓有幾間加油站」之類的問題，完完全全的是在浪費時
間。這些問題[對人員未來表現]毫無預估效果，主要功能只是讓面試官可以展現自己有多
聰明而已。

Instead, what works well are structured behavioral interviews, where you have
a consistent rubric for how you assess people, rather than having each
interviewer just make stuff up.

有用的反而是具架構的行為式面試，也就是要有一套不變的架構來評估面試人，而不是要
面試官臨場自己編。

Behavioral interviewing also works — where you're not giving someone a
hypothetical, but you're starting with a question like, “Give me an example
of a time when you solved an analytically difficult problem.” The
interesting thing about the behavioral interview is that when you ask
somebody to speak to their own experience, and you drill into that, you get
two kinds of information. One is you get to see how they actually interacted
in a real-world situation, and the valuable “meta” information you get
about the candidate is a sense of what they consider to be difficult.

行為式面試好用還不只這一點：你不要丟假設的問題，要丟實際的問題，例如「談談你如
何克服一個很難以分析的問題」。行為式面試有意思的部分就是，當你要求對方根據他們
的經驗來回答，然後你再挖的深一點，你就可以得到兩項資料。第一就是這人在真實情況
下如何反應，第二就是更基本的，也就是甚麼東西對這人來說算是「困難」。

On the leadership side, we've found that leadership is a more ambiguous and
amorphous set of characteristics than the work we did on the attributes of
good management, which are more of a checklist and actionable.

至於領導統御方面，我們發現「領導」的特質比我們所研究出來的「統御」(或管理)特質
更難以捉摸。我們研究出的統御特質有點像清單一樣，是可以依項實行的。

We found that, for leaders, it's important that people know you are
consistent and fair in how you think about making decisions and that there's
an element of predictability. If a leader is consistent, people on their
teams experience tremendous freedom, because then they know that within
certain parameters, they can do whatever they want. If your manager is all
over the place, you're never going to know what you can do, and you're going
to experience it as very restrictive.

我們發現，對領導而言，一個關鍵就是要讓人知道你的作風以及做決策的思考是一貫且公
平的，讓人可以預測。如果領導人作風一貫，下面的人就可以很自由的做事，因為他們知
道他們可以自由行事的尺度。如果領導人朝令夕改，下面的人永遠都不會知道什麼能做甚
麼不能做，就會有一種綁手綁腳的感覺。

Q. Other examples?

問：還有其他例子可以分享嗎？

A. Twice a year, anybody who has a manager is surveyed on the manager's
qualities. We call it an upward feedback survey. We collect data for everyone
in the company who's a manager on how well they're doing on anywhere between
12 and 18 different factors. We then share that with the manager, and we
track improvement across the whole company. Over the last three years, we've
significantly improved the quality of people management at Google, measured
by how happy people are with their managers.

答：我們一年有兩次問卷，讓任何有上司的人評估他上司的能力，我們把這叫做「向上回
饋問卷」。我們收集所有居領導職人員的資料，並根據12至18項指標來分析他的領導統御
能力，然後把分析結果跟那位領導人員分享，並在公司內全面追蹤其改善能力。在過去三
年內，以「職員對主管的滿意程度」計算，我們谷歌在人員管理方面有明顯的進步。

We've actually made it harder to be a bad manager. If you go back to somebody
and say, “Look, you're an eighth-percentile people manager at Google. This
is what people say.” They might say, “Well, you know, I'm actually better
than that.” And then I'll say, “That's how you feel. But these are the
facts that people are reporting about how they experience you.”

我們其實讓一個人更難成為一位壞主管。如果你跟某人反應「你在谷歌的領導統御方面排
名僅為8% (譯註：也就是92%的主管都幹的比你好)，人們都這樣說。」他可能回答「我其
實沒那麼糟吧。」那我就可以說「那只是你自我感覺良好，事實就是你的下屬對你的感覺
就是如此這般。」

You don't actually have to do that much more. Because for most people, just
knowing that information causes them to change their conduct. One of the
applications of Big Data is giving people the facts, and getting them to
understand that their own decision-making is not perfect. And that in itself
causes them to change their behavior.

其實做到這裡就很夠了，因為大多數人只要知道狀況就會改善。數據是用來引以為鑑，讓
人了解自己的決策並不完美，也是有缺陷的，人們就會自動改善。

Q. What are some things that the managers are ranked on?

問：你們的主管評估指標包括哪些項目？

A. Some of them are very straightforward — the manager treats me with
respect, the manager gives me clear goals, the manager shares information,
the manager treats the entire team fairly. These are fundamental things that
turn out to be really important in making people feel excited and happy and
wanting to go the extra mile for you.

答：有些很直接，例如「主管會尊重我」、「主管會給我明確的目標」、「主管會跟大家
分享資訊」、「主管會公平對待小組所有人」等等。這些東西很基本，但也很關鍵，讓下
屬在工作時感到興奮、感到開心、會想更進一步的辦事都取決於這些關鍵。

Q. Other insights from the data you've gathered about Google employees?

問：你們從谷歌員工所蒐集的資料當中有沒有發掘出其他心得？

A. One of the things we've seen from all our data crunching is that G.P.A.'s
are worthless as a criteria for hiring, and test scores are worthless — no
correlation at all except for brand-new college grads, where there's a slight
correlation. Google famously used to ask everyone for a transcript and
G.P.A.'s and test scores, but we don't anymore, unless you're just a few
years out of school. We found that they don't predict anything.

答：我們從資料分析中得出的心得之一就是 GPA 在遴選人才方面完全沒用，考試分數也
一樣沒用。這些東西與員工進公司後的表現相關程度是零，除非你是新科畢業生，但也只
有微小的相關性而已。以前大家都知道要面試谷歌我們會跟你要成績單、GPA、考試成
績等等，但我們現在不要這些東西了，除非你兩三年內剛畢業。我們發現這些東西根本毫
無預估能力。

What's interesting is the proportion of people without any college education
at Google has increased over time as well. So we have teams where you have 14
percent of the team made up of people who've never gone to college.

還有一點很有意思，就是谷歌公司裡面沒上過大學的員工比例有隨著時間而增加。我們現
在有些小組的成員中高達14%是從沒上過大學的。

Q. Can you elaborate a bit more on the lack of correlation?

問:能不能更深入的談談這個「零相關」的心得？

A. After two or three years, your ability to perform at Google is completely
unrelated to how you performed when you were in school, because the skills
you required in college are very different. You're also fundamentally a
different person. You learn and grow, you think about things differently.

答：工作了兩三年後，你在谷歌的表現與你在學校的表現毫無相關性，因為大學所需要的
能力跟工作需要的截然不同。而且，工作幾年後你基本上已經是個不一樣的人了，你會學
習、成長，你的思緒也會改變。

Another reason is that I think academic environments are artificial
environments. People who succeed there are sort of finely trained, they're
conditioned to succeed in that environment. One of my own frustrations when I
was in college and grad school is that you knew the professor was looking for
a specific answer. You could figure that out, but it's much more interesting
to solve problems where there isn't an obvious answer. You want people who
like figuring out stuff where there is no obvious answer.

我認為造成這個零相關性的另一個原因就是，學術界是一個刻意營造的人工環境，在學術
界成功的人是那些被訓練適應了那種環境的人。我念大學跟研究所的時候感到很挫折的就
是你知道教授要的是某個標準答案，這答案你不是找不到，但是沒標準答案的問題相較就
有意思多了。你要請的人就是喜歡鑽研那些沒標準答案的問題的人。











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'Cause it's a bittersweet symphony, this life
Trying to make ends meet, You're a slave to money then you die
-Bittersweet Symphony, The Verve


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