Name: 【TED】Tamekia MizLadi Smith: How to train employees to have difficult conversations (How to train employees to have difficult conversations | Tamekia MizLadi Smith)
Uploaded: 2018-08-20T16:51:15.000Z
Duration: 8 min 11 s
Description: Thousands of YouTube videos with English-Chinese subtitles! Now you can learn to understand native speakers, expand your vocabulary, and improve your pronunciation...

We live in a world where the collection of data

is happening 24 hours a day, seven days a week,

This data is usually collected by what we call a front-desk specialist now.

These are the retail clerks at your favorite department stores,

the registration specialists at the hospital

and even the person that sold you your last movie ticket.

They ask discreet questions, like: "May I please have your zip code?"

Or, "Would you like to use your savings card today?"

However, the conversation becomes a little bit more complex

when the more difficult questions need to be asked.

Once upon a time, there was a woman named Miss Margaret.

Miss Margaret had been a front-desk specialist

And in all that time, she has never, and I do mean never,

had to ask a patient their gender, race or ethnicity.

Because, see, now Miss Margaret has the ability to just look at you.

And she can tell if you are a boy or a girl,

black or white, American or non-American.

And in her mind, those were the only categories.

when her sassy supervisor invited her to this "change everything" meeting

and told her that would have to ask each and every last one of her patients

She gave her six genders, eight races and over 100 ethnicities.

So much so that she marched down to that human-resource department

to see if she was eligible for an early retirement.

that her sassy supervisor invited her to this "change everything" meeting

You know you've got to bring food to these meetings.

Now, that was an example of a healthcare setting,

but of course, all businesses collect some form of data.

True story: I was going to wire some money.

And the customer service representative asked me

and before she even realized why I hesitated,

she began to throw the company she worked for under the bus.

She said, "Girl, I know it's stupid, but they makin' us ask this question."

Because of the way she presented it to me,

But then I had to turn on the other side of me,

the more professional speaker-poet side of me.

The one that understood that there were little Miss Margarets all over the place.

People who were good people, maybe even good employees,

but lacked the ability to ask their questions properly

and unfortunately, that made her look bad,

but the worst, that made the business look even worse

I mean, I literally could have been a woman who was scheduled to do a TED Talk

what happens is people would decline to answer the questions,

because they feel like you would use the information

all because of how you presented the information.

Bad data costs you time, it costs you money

and we have social determinants of health,

all of which depends on the data that we collect,

and if we have bad data, than we have those issues still.

that remain unfortunate and underprivileged,

because the data that we're using is either outdated,

or is not good at all or we don't have anything at all.

Now, wouldn't it be amazing if people like Miss Margaret

and the customer-service representative at the wiring place

were graced to collect data with compassionate care?

Can I explain to you what I mean by "graced?"

G: Getting the front desk specialist involved and letting them know

R: the Relevance of their role as they become

A: Accountable for the accuracy of data while implementing

C: Compassionate care within all encounters by becoming

【TED】Tamekia MizLadi Smith: How to train employees to have difficult conversations (How to train employees to have difficult conversations | Tamekia MizLadi Smith)

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【TED】Tamekia MizLadi Smith: How to train employees to have difficult conversations (How to train employees to have difficult conversations | Tamekia MizLadi Smith)

present

eliminate

realize

applause