「G」态度:团队管理的成功,关键取决于规范而不仅是智慧

摘要: 恰当的团队规范,可以提升团队的群体智慧;反之,不恰当的团队规范也会束缚整个团队。

11-13 04:51 首页 戈壁创投

本文作者Hunter Walk,是Homebrew VC合伙人,为初创公司提供种子时期的风险投资。

 

Which Google employees has made the biggest impact to the company over the past decade? Besides the familiar choices of Larry and Sundar, I’d nominate Google’s outgoing CPO Laszlo Bock. Under Laszlo’s direction Google’s hiring and management assumptions have been challenged by real data, resulting in transformative shifts such as *not* assuming college test scores are a predictor of success as a Googler.


过去十年内哪些谷歌员工对该公司的影响最大?除了大家所熟悉的拉里(Larry)和桑达尔(Sundar),我还想提一下谷歌即将离职的首席人才官拉斯洛·博克(Laszlo Bock)。在拉斯洛的领导下,谷歌的招聘和管理理念受到真实数据的挑战,因此引发了一轮巨大的公司转型,例如, 「不」要将大学考试分数作为衡量谷歌员工是否成功的指标。


Another important question was “What makes a team successful (or not)?” and Google’s research into this topic was beautifully recounted in a NYTimes Magazine article earlier this year.


另一个重要的问题是,“团队成功(或不成功)的关键是什么?”谷歌对这一问题的研究报告曾在今年早些时候刊登在《纽约时报》中。



It would make sense to start with some assumption that a team’s success is tied to its composition in some fixed way. For example, a ratio of engineers to non-engineers. Or senior leaders with junior followers. But when Google started to examine the variables it couldn’t find a connection.


初看这个问题,你的直觉可能是:团队的成功与否与其人员构成具有某些固定的联系。例如,工程师人员与非工程师人员的比例,或者资深领导与年轻队员的比例。但在谷歌开始调查这些变量时,却未在其中找到任何关联。


‘‘We looked at 180 teams from all over the company,’’ Dubey said. ‘‘We had lots of data, but there was nothing showing that a mix of specific personality types or skills or backgrounds made any difference. The ‘who’ part of the equation didn’t seem to matter.’’


“我们调查了全公司中180个团队,”杜贝(Dubey)表示,“我们收集了大量的数据,但没有任何证据表明,特定性格类型或技能或背景的组合会产生任何差异。团队中的人员构成似乎并不太重要。”


What did the research?—?called Project Aristotle?—?eventually discern? That team norms?—?how teams agree to behave and function?—?were more important determinants than purely team composition. So they dove into understanding what type of norms mattered most.


这个名为亚里士多德项目(Project Aristotle)的研究,最终研究结果是什么呢?该研究发现,团队规范,即团队对于如何表现和如何运转所达成的共识,比单纯的团队组成更为重要。因此他们深入挖掘了哪些规范类型最为重要。


What interested the researchers most, however, was that teams that did well on one assignment usually did well on all the others. Conversely, teams that failed at one thing seemed to fail at everything. The researchers eventually concluded that what distinguished the ‘‘good’’ teams from the dysfunctional groups was how teammates treated one another. The right norms, in other words, could raise a group’s collective intelligence, whereas the wrong norms could hobble a team, even if, individually, all the members were exceptionally bright.


但是,最受研究人员关注的是,在一项任务中表现突出的团队通常在所有其他任务中都会有出色的表现。相反地,将一件事情搞砸的团队通常会将每件事情都搞砸。研究人员最终总结道,“良好”团队与不良团队的区别在于团队成员如何对待彼此。也就是说,恰当的团队规范,可以提升团队的群体智慧;反之,即使里面的所有成员都极其优秀,不恰当的团队规范也会束缚整个团队。 


I can only imagine how shocking this would be to Googlers who often prided themselves on raw intelligence and generally believe throwing data and brains at a problem is the surest solution.


我能想象出来谷歌员工在听到这一结论时的震惊程度,因为他们经常以天资聪颖为荣,通常认为抛出数据和头脑风暴是最可靠的解决问题的办法。


So what were the norms of successful teams?

那么成功团队的规范是什么呢?


First, on the good teams, members spoke in roughly the same proportion, a phenomenon the researchers referred to as ‘‘equality in distribution of conversational turn-taking.’’


首先,在优秀团队中,成员的话语权相差不大,研究人员将这种现象称之为“话语轮换机会是均等的”。


Second, the good teams all had high ‘‘average social sensitivity’’?—?a fancy way of saying they were skilled at intuiting how others felt based on their tone of voice, their expressions and other nonverbal cues.


其次,优秀的团队都有比较高的“平均社会敏感度”,说得通俗易懂些,就是他们善于从其他人的语气语调、措辞表达以及非言语线索感知对方的感受。


On one level these are intuitive conclusions but they’re certainly not the characteristics that I’ve ever seen an organization build teaming or training around. The entire article is wonderful and I’d recommend it for anyone who works on a team or helps teams succeed. So basically, everyone.


在某种程度上来说,这些都是比较直观的结论,但我的确从未看到任何企业在构建团队或培训方面关注这些特点。整篇文章非常精彩,推荐任何在团队中工作或为团队成功助力的人员阅读一下——也就是说,基本上所有人都应该读一读这篇文章。


本文由戈壁创投编译,原文刊载于

http://bit.ly/2cbUGUy?cc=0511ef53b2034dd538b3108c214244ad



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