Why corporate diversity programs fail and how small tweaks can have big impact Joan C. Williams

Transcriber:

In 2018, two Black men
went to a Starbucks

to wait for a business associate.

But when they asked to use the bathroom,

the manager ordered them to leave.

They refused.

He called the police,

and the video went viral.

Amidst an avalanche of bad publicity,

Starbucks closed all stores
across the country

for four hours of diversity training.

And so, baristas were handed workbooks

with prompts like,
“What makes me me and you you?”

and, “Understanding our bias:
from color-blind to color brave.”

This made newspapers across the country,

and arguably, that was the goal.

“Look, everyone! We’re solving
our diversity problem!”

The assumption, though, was that you could
address structural racism

with an earnest conversation
about our feelings.

My take:

give me a break.

To address structural racism,
you need to change structures.

So in the aftermath
of George Floyd’s death,

my sense is that many companies
are feeling pressure

to actually deliver
on their diversity goals,

but they haven’t a clue what to do.

And that’s because we spent probably
close to a billion dollars on diversity.

But the basic tools of the diversity
industrial complex,

they just don’t work.

A one-shot bias training –

it doesn’t work
for a really simple reason:

doing anything once won’t change
a company’s culture.

And the other basic tools –

things like an employee resource group
or a women’s initiative –

they’re fine,

if the problem is with the women
and the people of color.

But it’s not.

If a company faces challenges
surrounding diversity,

typically, it’s because subtle
and not-so-subtle forms of bias

are constantly being transmitted
through their basic business systems –

through hiring,
through performance evaluations,

through access to opportunities.

So we need to stop trying to fix
the women and the people of color.

We need to fix the business systems.

And if you think about it,
this makes sense,

because if a company was facing
challenges with sales,

it wouldn’t respond by holding
a series of sincere conversations

about how much we all value sales

and put on programming
for “National Celebrate Sales Month”

and expect sales to improve.

But that’s a lot of what we’re doing
in the diversity context.

If we really want to tackle
diversity effectively,

we need to use the same tools businesses
use to tackle any business problem –

evidence and metrics.

And, you know, I suspect
this will come as a relief

to a lot of CEOs who feel far more
comfortable using those tools

than they do with trying to lead
a deep conversation

about the inner workings
of social inequality.

The first step

is for us to understand
what bias looks like on the ground.

And I and my team at WorkLife Law,

we have been studying how bias plays out
in everyday workplace interactions

for well over a decade.

And what we find
is that the same patterns of bias,

the same five patterns,

they emerge over and over again.

So here’s what the evidence looks like.

The first pattern we call
“prove it again.”

Some groups have to prove themselves
more than others.

This is triggered
by lots of different things.

It’s triggered by race and gender,

age, disability, LGBTQ status,

even social class.

So one study, for example,

looked at callbacks offered to white men
with identical qualifications

but different hobbies.

One résumé listed things
like sailing and polo,

and the other résumé listed things like

counseling first-generation
college students

and country music.

And, if you can believe it, Mr. Polo –

he got 12 times the number of callbacks
as Mr. Country Music.

Too often when we talk about privilege,
we forget about class.

The second pattern is called
“the tightrope,”

and it reflects the fact
that a certain in-group of white men

just need to be authoritative
and ambitious in order to succeed.

But women walk a tightrope,

where they may be seen as abrasive
if they’re authoritative

but unqualified if they’re not.

And people of color who behave assertively
often are written off

as angry if they’re Black,

even hotheaded if they’re Latinx

and sometimes as untrustworthy
if they’re Asian American.

The next pattern we call the “tug-of-war,”

and it reflects the fact
that sometimes bias against a group

fuels conflict within the group.

So, for example, if there’s room
for only one woman or person of color,

it’s entirely predictable:

women are going to be
supercompetitive with other women,

and people of color,
competitive with other people of color.

The fourth pattern of bias is actually
the strongest form of gender bias,

called “the maternal wall.”

And it reflects assumptions
that mothers aren’t committed,

probably shouldn’t be

and aren’t competent –

think “pregnancy brain.”

So mothers often find
they have to prove themselves yet again

when they return from maternity leave.

And if they do, they may be seen as
bad mothers and so as bad people

and disliked.

The final pattern consists
of racial stereotypes.

So, Asian Americans again and again report

that they’re seen as a great match
for technical skills,

but lacking in leadership potential.

And our studies show that Black
professionals, again and again,

report really high levels of isolation

and often startling forms of disrespect.

And an Asian American professional
may be seen as too emotional

in a discussion where, you know what,

a white man behaving exactly the same way

would be seen as having a career-enhancing
passion for the business.

And so what we find is that white women
report four patterns of bias.

Men of color also report four.

Women of color report all five
in very substantial proportions.

And among women of color,

Black women report
the most bias as a group.

But the bottom line, really, is that
the experience of white men as a group

differs from that of every other group.

If a white man is a first-generation
professional or LGBTQ,

he may encounter bias.

But but most aren’t.

These biases can have
really serious negative effects.

There’s a ton of research.

But here’s a story
that really says it all.

We were working with one company,
and we spoke to a woman engineer

who had found a mistake
in one of the calculations

of a male colleague,

and she pointed it out.

When she pointed it out,

she was violating an unwritten rule.

The good woman is seen as modest,
self-effacing and nice,

not a mission-driven expert.

That’s why male experts in meetings
exert more influence.

But you know what?

Female experts, they actually exert
less influence than female nonexperts do.

And so when this engineer pointed out
the mistake in calculation, she told us,

the response of her department
was so massively negative that, she said,

“Now I’m just smiling a lot
and bringing in cupcakes.”

This company, by allowing
gender bias to go unchecked,

was literally jeopardizing their mission.

So what’s the solution?

The solution is to use bias interrupters,

new tools my team has developed

that are evidence-based
and metrics-driven.

And I’ve just told you about
a lot of the evidence.

Metrics are also superimportant

because they help you pinpoint
where things are going wrong.

So if a company
has challenges with hiring,

they should be keeping track of who
is in the original pool of candidates

and who survives résumé review

and who gets called to interview

and who survives the interview.

And the reason that’s important
is because the fix,

if you have a nondiverse original pool,

is totally different than the fix
if no woman ever survives the interview

because every woman is either too witchy

or too meek.

Metrics are also superimportant
for another reason:

to establish baselines

and measure progress.

If you use evidence and metrics,

what we have found is that small tweaks
can have really big effects.

So we’ve worked with
one company, for example,

who asked us to look at
their performance evaluations.

And when we did,

we found that only 9.5 percent
of the people of color

had leadership mentioned
in their performance evaluations.

That was 70 points lower
than white women.

And that was superimportant
because, as you can imagine,

mentions of leadership
predicted advancement.

And so we worked with them
to do two simple things.

First, we redesigned
the performance evaluations form.

And second, we help them develop
a simple one-hour workshop that,

among other things,

projected actual comments from the prior
year’s performance evaluations,

and asked people a simple question:

Which of the five patterns of bias
does this represent,

or is it no bias?

Just doing that, we found in year two,

100 percent of the people of color
had leadership mentioned

in their performance evaluations.

At this company, white women,
they had a different problem.

Almost 20 percent had comments
in their performance evaluations

that they didn’t really want
to make partner –

this was a partnership.

And we suspected the women hadn’t
actually said that.

It was just assumptions.

And so in that one-hour
workshop, we told people,

“Hey, don’t say this unless
you’ve actually had a conversation,

and someone has told you
they don’t want to make partner.”

In year two, only one woman
got that comment –

one woman in the entire company.

And so what we find is that we have
helped over 100 companies

actually make progress
towards their diversity goals.

And there’s growing evidence
that these bias interrupters work.

And the best thing about them
is that they help every single group.

So in this company
I’ve been talking about,

in year two, people of color
got wildly more constructive feedback –

it was like a 30-percent jump.

But white women, they got more
constructive feedback, too,

and so did white men.

If you design your systems
based on evidence,

it’s going to help every single group.

So the bottom line, if you think about it,
your systems and your culture,

they reflect the people
you’ve already hired.

So if you want to replicate
that workforce into the future,

definitely keep on doing
exactly what you’re doing.

But if you don’t,

if you actually want to make progress

on diversity, equity
and inclusion – what we call DEI –

my message to CEOs is reassuring:

you already know what to do.

Use standard business tools,

start from the evidence,

gather metrics to establish baselines
and measure progress

and keep at it
until you achieve your goals.

That’s the new DEI playbook.

And it works.

Thank you.

抄写员

:2018 年,两名黑人男子

星巴克等待商业伙伴。

但当他们要求使用洗手间时

,经理命令他们离开。

他们拒绝了。

他报了警

,视频在网上疯传。

在雪崩般的负面宣传中,

星巴克关闭
了全国所有门店,

进行了四个小时的多元化培训。

因此,咖啡师收到了

带有提示的工作簿,例如
“是什么让我成为我和你?”

并且,“了解我们的偏见:
从色盲到勇敢。”

这使得全国各地的报纸都成为了报纸

的目标,可以说,这就是目标。

“大家看!我们正在解决
我们的多样性问题!”

不过,假设是,您可以

通过认真
讨论我们的感受来解决结构性种族主义问题。

我的看法:

让我休息一下。

要解决结构性种族主义,
您需要改变结构。

所以在
乔治·弗洛伊德(George Floyd)去世后,

我的感觉是,许多公司
都感受到

了真正
实现其多元化目标的压力,

但他们不知道该怎么做。

那是因为我们可能
在多样性上花费了近 10 亿美元。

但是多元化
工业综合体的基本工具,

它们根本不起作用。

一次性的偏见培训——

它不起作用的
原因很简单:

做任何事情一次都不会
改变公司的文化。

其他基本工具

——比如员工资源小组
或女性倡议——

它们很好,

如果问题出在女性
和有色人种身上。

但事实并非如此。

如果一家公司面临
围绕多样性的挑战

,通常是因为微妙
和不那么微妙的偏见

形式不断
通过其基本业务系统传播——

通过招聘、
绩效评估

、获得机会。

所以我们需要停止试图
修复女性和有色人种。

我们需要修复业务系统。

如果你仔细想想,
这是有道理的,

因为如果一家公司在
销售方面面临挑战,

它不会通过举行
一系列

关于我们对销售

的重视程度的真诚对话来回应,并
为“全国庆祝销售月”做节目 ”

并期望销售额有所改善。

但这就是我们
在多元化背景下所做的很多事情。

如果我们真的想
有效地解决多样性问题,

我们需要使用企业
用来解决任何业务问题的相同工具——

证据和指标。

而且,你知道,我怀疑
这会让

很多 CEO 松了一口气,他们觉得
使用这些工具

比试图就

社会不平等的内部运作进行深入对话更自在。

第一步

是让我们了解
实际的偏见是什么样的。

十多年来,我和我在 WorkLife Law 的团队

一直在研究偏见如何
在日常工作场所互动中发挥作用

我们
发现相同的偏见

模式,相同的五种模式,

它们一遍又一遍地出现。

所以这就是证据的样子。

我们
称之为“再次证明”的第一个模式。

有些团体必须比其他团体更多地证明自己

这是
由许多不同的事情触发的。

它是由种族和性别、

年龄、残疾、LGBTQ 身份,

甚至社会阶层引发的。

因此,例如,一项研究

着眼于为
具有相同资格

但爱好不同的白人男性提供的回调。

一份简历列出
了帆船和马球之类的内容

,另一份简历列出了为

第一代大学生提供咨询

和乡村音乐之类的内容。

而且,如果你能相信的话,波罗先生——

他收到的回电数量
是乡村音乐先生的 12 倍。

当我们谈论特权时,
我们常常忘记阶级。

第二种模式被称为
“走钢丝”

,它反映了一个事实
,即某些白人男性

只需要权威
和雄心勃勃才能成功。

但女性走的是钢丝,

如果她们是权威的,她们可能会被视为粗暴,但如果她们不是,她们可能会被视为

不合格。

如果他们是黑人,表现得自信的有色人种
经常被

认为很生气,

如果他们是拉丁裔,甚至会变得头脑发热,如果他们是亚裔美国人

,有时会被认为不值得信任

下一种模式我们称之为“拔河”

,它反映了一个事实
,即有时对一个群体的偏见会

助长群体内部的冲突。

因此,例如,如果
只有一个女性或有色人种的空间,

这是完全可以预测的:

女性将
与其他女性具有超级

竞争力,而有色人种将与其他有色人种竞争。

第四种偏见模式实际上
是最强烈的性别偏见形式,

称为“母性墙”。

它反映
了母亲没有承诺、

可能不

应该也没有能力的假设——

想想“怀孕的大脑”。

所以妈妈们常常发现

当她们休完产假回来时,她们必须再次证明自己。

如果他们这样做了,他们可能会被
视为坏母亲、坏人

和不受欢迎的人。

最终模式
由种族刻板印象组成。

因此,亚裔美国人一次又一次地报告

说,他们被视为
技术技能的绝配,

但缺乏领导潜力。

我们的研究表明,黑人
专业人士一次又一次地

报告说他们处于高度孤立的状态,

并且常常表现出令人吃惊的不尊重行为。

一个亚裔美国专业人士在讨论中
可能会被视为过于情绪化

,你知道吗,

一个行为完全相同的白人

会被视为对企业有促进职业发展的
热情。

所以我们发现白人女性
报告了四种偏见模式。

有色人种也报告了四个。

有色人种女性
以非常可观的比例报告所有五人。

在有色人种女性中,

黑人女性
作为一个群体报告的偏见最多。

但实际上,最重要的是,
白人男性作为一个群体的经历

与其他群体的经历不同。

如果白人是第一代
专业人士或 LGBTQ,

他可能会遇到偏见。

但大多数不是。

这些偏见会产生
非常严重的负面影响。

有大量的研究。

但这是一个真正说明一切的故事

我们正在与一家公司合作
,我们与一位女工程师交谈,

她发现

一位男同事的计算中有一个错误

,她指出了这一点。

当她指出这一点时,

她违反了一条不成文的规定。

好女人被视为谦虚、
谦逊和友善,

而不是任务驱动的专家。

这就是为什么会议中的男性专家
发挥更大影响力的原因。

但你知道吗?

女性专家,她们的
影响力实际上比女性非专家少。

因此,当这位工程师指出
计算中的错误时,她告诉我们,

她所在部门的反应
非常消极,以至于她说,

“现在我只是笑得很开心
,拿来纸杯蛋糕。”

这家公司允许
性别偏见不受控制

,实际上是在危及他们的使命。

那么解决方案是什么?

解决方案是使用偏见中断器,这是

我的团队开发

的基于证据
和指标驱动的新工具。

我刚刚告诉过
你很多证据。

指标也非常重要,

因为它们可以帮助您查明
哪里出了问题。

因此,如果一家公司
在招聘方面遇到挑战,

他们应该跟踪哪些
人在最初的候选人池中

,哪些人在简历审查中幸存下来

,哪些人被要求参加面试

,哪些人在面试中幸存下来。

这很重要
的原因是,

如果你有一个非多样化的原始池,

那么解决方法与
如果没有女性在面试中幸存下来的解决方法是完全不同的,

因为每个女人要么太巫术

要么太温顺。

由于另一个原因,指标也非常重要

:建立基线

和衡量进度。

如果您使用证据和指标,

我们发现小的调整
可以产生非常大的影响。 例如,

我们曾与
一家公司合作,该公司

要求我们查看
他们的绩效评估。

当我们这样做时,

我们发现只有 9.5%
的有色人种

在他们的绩效评估中提到了领导力。

这比白人女性低 70 分

这非常重要,
因为正如你可以想象的那样,

提及领导力
预示着进步。

所以我们和他们
一起做了两件简单的事情。

首先,我们重新设计
了绩效评估表。

其次,我们帮助他们开发
一个简单的一小时研讨会,

其中包括

预测上
一年绩效评估的实际评论,

并问人们一个简单的问题:

这代表了五种偏见模式中的哪一种

或者是 没有偏见?

只是这样做,我们在第二年发现,

100% 的有色人种

在他们的绩效评估中提到了领导力。

在这家公司,白人
女性有一个不同的问题。

近 20% 的人
在他们的绩效评估中

表示他们并不
想成为合作伙伴——

这是一种合作伙伴关系。

我们怀疑这些女性实际上并没有这么
说。

这只是假设。

所以在那一小时的
研讨会上,我们告诉人们,

“嘿,除非
你真的有过谈话,否则不要这么说,

并且有人告诉你
他们不想成为合作伙伴。”

在第二年,只有一位女性
得到了这样的评价——

整个公司只有一位女性。

因此,我们发现我们已经
帮助 100 多家公司


实现其多元化目标方面取得了实际进展。

越来越多的证据
表明这些偏见干扰器有效。

他们最好的一点
是,他们可以帮助每一个群体。

所以在
我一直在谈论的这家公司中,

在第二年,有色人种
得到了更具建设性的反馈——

这就像一个 30% 的跳跃。

但是白人女性也得到了更有
建设性的反馈,

白人男性也是如此。

如果你根据证据设计你的系统

它会帮助每一个群体。

所以最重要的是,如果你仔细想想,
你的系统和文化,

它们反映了
你已经雇佣的人。

因此,如果您想将
这些劳动力复制到未来,请

务必继续
做您正在做的事情。

但如果你不这样做,

如果你真的想

在多样性、公平
和包容性方面取得进展——我们称之为 DEI——

我给 CEO 们传达的信息是令人放心的:

你已经知道该怎么做。

使用标准业务工具,

从证据开始,

收集指标以建立基线
并衡量进度

并坚持下去,
直到实现目标。

这就是新的 DEI 剧本。

它有效。

谢谢你。