WEBVTT - Bloomberg Businessweek Weekend-March 13, 2021

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<v Speaker 1>This is Bloomberg Business Week inside from the reporters and

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<v Speaker 1>editors who bring you America's most trusted business magazine, plus

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<v Speaker 1>global business, finance and tech news as it happened. Its

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<v Speaker 1>Bloomberg Business Week with Carol Messier and Bloomberg Quick Takes.

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<v Speaker 1>Tim Stinovic on Bloomberg Radio. Hi, everyone, Welcome to the

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<v Speaker 1>weekend edition of Bloomberg Business Week. Tim. This week I

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<v Speaker 1>thought about this a lot. It's been a milestone as

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<v Speaker 1>I've been keeping track. In fact, my calendar book, every

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<v Speaker 1>week I write, Okay, what week it is that we

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<v Speaker 1>have been or many have been working from home? It is,

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<v Speaker 1>and you know it's it's a week that I've seen

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<v Speaker 1>a lot of memories play out on social media, on

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<v Speaker 1>text message chains with family. One year ago this week,

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<v Speaker 1>you know, the last time stepping foot in a restaurant,

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<v Speaker 1>the last time visiting family. Um, it was a year

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<v Speaker 1>ago this week that the world completely changed. Yeah, exactly,

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<v Speaker 1>Friday March the last time we had a guest actually

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<v Speaker 1>in our Bloomberg Radio studio. And I just remember, you know,

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<v Speaker 1>our managers and like we want to be safe, we

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<v Speaker 1>want a home. We're sending you with equipment, like we

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<v Speaker 1>just want to make sure everybody safe. Hard to believe it.

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<v Speaker 1>It has been a year, no shortage of virus headlines.

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<v Speaker 1>This week it's still, of course top and center for us.

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<v Speaker 1>Here the CDC issuing its first set of guidelines Carol

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<v Speaker 1>on how fully vaccinated people can safely visit with others.

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<v Speaker 1>And I gotta say people are feeling good about reopenings,

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<v Speaker 1>but at the same time, we keep talking to various

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<v Speaker 1>members of the medical community, like listen, we still have

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<v Speaker 1>to be really, really cautious. And I gotta say on

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<v Speaker 1>that we've got the person that last spring was done

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<v Speaker 1>by the New York Times, the CEO at the center

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<v Speaker 1>of New York's coronavirus crisis. And we've got a new

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<v Speaker 1>crisis brewing cyber security. Lucky for us though, we just

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<v Speaker 1>happen to have on Tom Siebel, founder of Cebel Systems,

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<v Speaker 1>also c three AI, just as we learned that hackers

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<v Speaker 1>broke into thousands of security cameras, exposing testless suppliers, jails,

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<v Speaker 1>even hospitals doest you feel like cybersecurity. It's one of

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<v Speaker 1>those stories people keep saying, you know, you guys aren't

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<v Speaker 1>talking about it enough. It's a big, big story. It's

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<v Speaker 1>getting lost in the other headline, it's terrifying. Yeah, absolutely,

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<v Speaker 1>all right, So all of this to come. Let's begin

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<v Speaker 1>though with this week's issue of the magazine. It features

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<v Speaker 1>a deep dive into equality, and that includes him. The

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<v Speaker 1>cover's story, which was among our most read on the

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<v Speaker 1>Bloomberg It is about Dorothy Brown. So Dorothy Brown, she

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<v Speaker 1>she spent her career as a law professor documenting racism

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<v Speaker 1>in a tax system that's supposedly color blind. In fact,

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<v Speaker 1>she thought it was color blind until she really started

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<v Speaker 1>doing research onto this years into her career. Bloomberg News

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<v Speaker 1>Personal Finance editor Ben Steve Berman wrote all about it right,

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<v Speaker 1>and Ben joined us along with Bloomberg Business Week editor

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<v Speaker 1>Joel Weber. Joel kicking it off though by talking about

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<v Speaker 1>the overall equality issue we have. We launched a vertical

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<v Speaker 1>that UH at Bloomberg called Quality that will be sort

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<v Speaker 1>of the home for our ongoing coverage, and we wanted

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<v Speaker 1>to help make a splash at Business Weeks as we

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<v Speaker 1>launched that that initiative and that and that project, and

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<v Speaker 1>so we really kind of like pulled together across the

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<v Speaker 1>global news room to try and bring as many of

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<v Speaker 1>of these stories to life as we could. And there

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<v Speaker 1>were a couple in particular that stood out to me

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<v Speaker 1>that we're a little bit more US centric that funny enough,

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<v Speaker 1>both had to do with taxes, and we heard about

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<v Speaker 1>Jason Grotto's story on on property tax um and how

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<v Speaker 1>it's effectively like a regressive tax. And there was another

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<v Speaker 1>thing that caught our attention, which was Ben steveerman Um saying, Hey,

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<v Speaker 1>by the way, do you guys know about Dorothy Brown,

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<v Speaker 1>who's got a book coming out? And I said, I

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<v Speaker 1>have never heard of Dorothy Brown. Tell me more. And

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<v Speaker 1>with that I'll segue is over to Ben Um. This

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<v Speaker 1>is a professor, a legal illegal tax expert, Um, a

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<v Speaker 1>law professor at Emory UM. And she spent decades basically

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<v Speaker 1>examining the U. S. Tax code. And and Ben, that's

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<v Speaker 1>where it gets provocative. Where does she found Yeah, So

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<v Speaker 1>she's um an interesting person even before she became an

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<v Speaker 1>eminent professor of tax law. She's grew up in the

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<v Speaker 1>bron She worked at Drexel Burnham Lambert back in the eighties.

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<v Speaker 1>She's had a long career, but Um, since the nineties

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<v Speaker 1>she's been looking at different parts of the tax code

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<v Speaker 1>and saying and really analyzing what is the impact this

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<v Speaker 1>has on wealth, um, especially on the wealth of black

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<v Speaker 1>people and the wealth of white people, and what the

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<v Speaker 1>part of the question is, you know, and we've had

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<v Speaker 1>a racial wealth gap between black and white in this

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<v Speaker 1>country that really hasn't narrowed at all. So you see

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<v Speaker 1>many more black people going to college, incomes uh going up,

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<v Speaker 1>but they're the wealth of black folks is not keeping

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<v Speaker 1>pace with well, it is keeping pace, but it's it's

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<v Speaker 1>waste away behind um the wealth of white families. And

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<v Speaker 1>so what she's concluded is that the tax code has

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<v Speaker 1>a big part in that, especially the US income tax,

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<v Speaker 1>and a lot of these carve outs in the income

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<v Speaker 1>tax for retirement and homeownership and all sorts of other

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<v Speaker 1>things that have been built into this supposed the progressive

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<v Speaker 1>system did really end up in a situation where a

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<v Speaker 1>black person and a white person with similar incomes, uh,

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<v Speaker 1>the black person can end up paying significantly more. How

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<v Speaker 1>did she get there to this point because initially I

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<v Speaker 1>think her thinking, according to your story, is that you know, thought,

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<v Speaker 1>you know, tax code, it's going to be color blind. Yeah,

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<v Speaker 1>I mean, that's that was her assumption when she decided

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<v Speaker 1>to get into tax you wanted to escape the whole

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<v Speaker 1>issue of racism. Her original plan was to be Um

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<v Speaker 1>following the footsteps of Theurbid Marshall. And then she, you know,

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<v Speaker 1>civil rights lawyer, and she said, I don't want to

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<v Speaker 1>deal with that in my professional life. I just want

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<v Speaker 1>to focus on this this what seemed like this color

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<v Speaker 1>blind system of all these intricate rules and tax code

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<v Speaker 1>doesn't even mention race really. But she she Um was

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<v Speaker 1>part of a movement of people who back in the

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<v Speaker 1>nineties who really started to say, hey, there's these other

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<v Speaker 1>areas of the law. They were written, All these laws

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<v Speaker 1>were written by white people, generations of white people, Um,

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<v Speaker 1>And and you know, is there some hidden racism there?

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<v Speaker 1>And what she's really showing in her book is that

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<v Speaker 1>the generations of lawmakers have built the system that's really

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<v Speaker 1>optimized for white wealth, for people, for white people that

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<v Speaker 1>are already wealthy. The stories in this week special Equality

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<v Speaker 1>issue reminding us that so much work still has to

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<v Speaker 1>be done. That was Bloomberg News Personal Finance editor Ben Steveherman,

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<v Speaker 1>also Bloomberg Business Week editor Joel Webber. Be sure to

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<v Speaker 1>listen to the full audio version of the story on

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<v Speaker 1>our podcast feed at Bloomberg dot Com. Hey and Tim.

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<v Speaker 1>By the way, Dorothy Brown's book, it's entitled The Whiteness

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<v Speaker 1>of Wealth, How the tax system impoverishes Black Americans and

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<v Speaker 1>how we can fix it. That book coming out later

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<v Speaker 1>this month, and she's gonna be joining us in a

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<v Speaker 1>few weeks on air to talk about it. I'm really

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<v Speaker 1>excited for that interview. The book not even out yet,

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<v Speaker 1>already making a splash exactly. Coming up more on the

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<v Speaker 1>equality issue and once again involving taxes and racism. You're

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<v Speaker 1>listening to Bloomberg Business Week. This is Bloomberg. This is

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<v Speaker 1>Bloomberg Business Week with Carol Masser and Bloomberg Quick Takes

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<v Speaker 1>Tim Stenovik from Bloomberg Radio. So we continue with coverage

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<v Speaker 1>of this week's equality issue of Bloomberg Business Week magazine.

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<v Speaker 1>Another story Tim, having to do with taxes and racism,

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<v Speaker 1>more specifically about how in cities across the US, unfair

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<v Speaker 1>property taxes are keeping black families from gaining wealth. To

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<v Speaker 1>set it all up, here's Bloomberg's Reneed a young She's

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<v Speaker 1>got the story of one woman from Detroit. I feel

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<v Speaker 1>like there is no safe place for me to have

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<v Speaker 1>this conversation because I'm gonna get judge one way or another.

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<v Speaker 1>That's delicious. Scott from Detroit. She was over taxed on

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<v Speaker 1>what was once her home. She became a proud homeowner

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<v Speaker 1>in two thousand five, a dream because she always wanted

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<v Speaker 1>stable housing for her kids, something she's never known. But

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<v Speaker 1>when Scott lost her job during the Great Recession, she

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<v Speaker 1>fell three years behind on her property tax payments, and

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<v Speaker 1>those payments shield were much higher than she should have been.

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<v Speaker 1>Then Wayne County took her home away and auctioned it

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<v Speaker 1>off for less than ten percent of what she paid

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<v Speaker 1>for it. I feel betrayed to last year to learn

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<v Speaker 1>that I was over taxed by five thousand. It makes

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<v Speaker 1>me stand, It makes me depress, It makes me feel

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<v Speaker 1>like a failure. For years, the city of Detroit used

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<v Speaker 1>inflated valuations of Scott's house to calculate her property tax bills.

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<v Speaker 1>She now rents that same home for twenty seven percent

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<v Speaker 1>more than she once paid for the mortgage. You know,

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<v Speaker 1>it's not just a rental property. This is my home right.

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<v Speaker 1>I raised my children in the space. Scott is not

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<v Speaker 1>alone and her story is not unique. Her home was

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<v Speaker 1>among tens of thousands in Detroit's lower income black neighborhoods

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<v Speaker 1>that the city's assessors routinely overvalued, and this happens all

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<v Speaker 1>across the country, where nationwide data show local officials have

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<v Speaker 1>also systematically undervalued home and affluent areas, reducing the taxes

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<v Speaker 1>those homeowners paid. Ban Behaves Brown leads the nonprofit organization

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<v Speaker 1>Georgia Advancing Communities Together, which focuses on affordable housing and

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<v Speaker 1>community development. She says, the entire real estate system has

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<v Speaker 1>a role to play in equitable housing, and it all

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<v Speaker 1>starts with training, not just your training to get your

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<v Speaker 1>license and you're training for renewal, but to also go

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<v Speaker 1>deeper into ethics, trainings that look at in turn racial

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<v Speaker 1>biases and how to overcome them. In many cases, real

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<v Speaker 1>estate investors profit off of unfair tax burdens, but for

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<v Speaker 1>the people who they weigh on, like Delicia Scott, it

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<v Speaker 1>leads to a vicious cycle of unpaid bills and property

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<v Speaker 1>seizures and ultimately destroys the best chance for families to

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<v Speaker 1>build generational wealth. For more on this story, subscribed to

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<v Speaker 1>the Paycheck podcast from Bloomberg, with a new season focusing

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<v Speaker 1>on the racial wealth gap. You can find Paycheck on

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<v Speaker 1>Apple Spotify or wherever you get your podcasts. That was

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<v Speaker 1>Bloomberg's Rnita Young. Now let's get more on this story,

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<v Speaker 1>which was among the most red on the Bloomberg this week,

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<v Speaker 1>with the reporter who wrote it. It's Bloomberg News Projects

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<v Speaker 1>and Investigations reporter Jason Grotto. He joined us, as did

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<v Speaker 1>Bloomberg Business Week editor Joel Webber, who began by talking

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<v Speaker 1>about disparities. I think the unfairness is the thing that

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<v Speaker 1>um really stings about this one. And you know, everybody

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<v Speaker 1>hates property taxes to begin with, but then to have

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<v Speaker 1>unfair qualities kind of layered on top of it, I

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<v Speaker 1>think is the thing that can definitely provoke some outrage.

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<v Speaker 1>And it is one of these things that sort of

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<v Speaker 1>hidden in plain sight. Um, but it does affect people

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<v Speaker 1>of color, especially black communities, disproportionately. So, so Jason, help us.

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<v Speaker 1>You've been through so much data on this one. Help

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<v Speaker 1>us break down what you found. Well, first of all,

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<v Speaker 1>thanks so much for having me. Everybody, Um, well, so

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<v Speaker 1>you know, the thrust of the story is actually based

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<v Speaker 1>on a mass of study out of the universe. See

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<v Speaker 1>of Chicago Hair School of Public Policy. A professor there,

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<v Speaker 1>Chris Berry, analyzed twenty six million property tax records over

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<v Speaker 1>a ten year period and all over the country UM.

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<v Speaker 1>The analysis found the same pattern, and that is lower

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<v Speaker 1>priced homes being overassessed and higher priced ones being under

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<v Speaker 1>assessed relative to the market value of those homes. And

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<v Speaker 1>of course all property taxes are based off of these valuations.

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<v Speaker 1>So it's sort of bad data in, bad data out.

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<v Speaker 1>And the result is it just excused the entire property

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<v Speaker 1>tax um uh and places a much greater burden on

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<v Speaker 1>those who can support it, makes it regressive. So tell

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<v Speaker 1>us the story of Delicia here. So you know, uh,

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<v Speaker 1>Delicia is someone who you know, I've been talking with

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<v Speaker 1>for many, many months. Uh. You know, obviously it took

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<v Speaker 1>a lot of bravery for her to come out, um

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<v Speaker 1>and actually talk and put her story out there. You know,

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<v Speaker 1>there's a lot of game that goes on here. But essentially,

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<v Speaker 1>you know, she bought a home back in two thousand

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<v Speaker 1>and five after working at a corporate cafeteria. She doubled

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<v Speaker 1>her income when she got a job at a domestic

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<v Speaker 1>violence shelter and was able to qualify for a mortgage,

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<v Speaker 1>and and things were going along fine until the Great Recession,

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<v Speaker 1>when she lost her job, and it took her a

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<v Speaker 1>couple of years to get a job back, and she

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<v Speaker 1>missed a tax payment and once you followed behind property taxes,

0:12:27.679 --> 0:12:31.520
<v Speaker 1>it's really difficult you know to get back, uh, you know,

0:12:32.480 --> 0:12:34.520
<v Speaker 1>caught up with those because there's so many fees and

0:12:34.600 --> 0:12:37.160
<v Speaker 1>fines that get ladled on and so she just couldn't

0:12:37.200 --> 0:12:40.680
<v Speaker 1>catch up. Um, the Wayne County, the county you know

0:12:41.040 --> 0:12:44.480
<v Speaker 1>for Detroit, foreclosed on the home and an auction it off,

0:12:44.920 --> 0:12:47.800
<v Speaker 1>as your story mentioned, And since then it's been sold

0:12:47.840 --> 0:12:51.040
<v Speaker 1>two more times while she's been renting the home. So

0:12:51.080 --> 0:12:55.160
<v Speaker 1>the last sale was for eighty four thousand dollars um,

0:12:55.200 --> 0:12:58.720
<v Speaker 1>you know, far more than she paid originally. And you know,

0:12:58.800 --> 0:13:00.440
<v Speaker 1>part of the reason why the value has gone up

0:13:00.480 --> 0:13:02.880
<v Speaker 1>because her rents have gone up because now you know,

0:13:02.920 --> 0:13:06.000
<v Speaker 1>it's an income producing property and the cash that it

0:13:06.200 --> 0:13:09.880
<v Speaker 1>that it throws off every month is keeping the value high. Well,

0:13:09.880 --> 0:13:12.280
<v Speaker 1>the investment, right, there's a whole investment angle into that,

0:13:12.400 --> 0:13:14.200
<v Speaker 1>and and I wish we had more time. But one

0:13:14.240 --> 0:13:15.600
<v Speaker 1>thing I do want to get to is this whole

0:13:15.600 --> 0:13:20.000
<v Speaker 1>idea between you know, tax assessment being overvalued and private

0:13:20.120 --> 0:13:23.960
<v Speaker 1>appraisal sales being undervalued. And as you say, you know,

0:13:24.000 --> 0:13:27.839
<v Speaker 1>Christopher Barry's research. It's not just Detroit you talk about

0:13:27.840 --> 0:13:31.440
<v Speaker 1>it an example in Brooklyn. Oh yeah, it's all over

0:13:31.480 --> 0:13:34.199
<v Speaker 1>the place. We we spoke with a woman Carmen Daniels

0:13:34.240 --> 0:13:36.719
<v Speaker 1>in East New York, you know who. You know. The

0:13:36.920 --> 0:13:41.040
<v Speaker 1>really hard thing here is m Daniels her property, uh,

0:13:41.080 --> 0:13:44.480
<v Speaker 1>you know, a single family home. Um. She felt like

0:13:44.559 --> 0:13:47.320
<v Speaker 1>the valuation that the New York City Department of Finance

0:13:47.360 --> 0:13:49.400
<v Speaker 1>put on it was pretty good, you know, she thought

0:13:49.400 --> 0:13:52.000
<v Speaker 1>it was pretty fair. But then she learned that, you know,

0:13:52.160 --> 0:13:55.040
<v Speaker 1>three miles away in Clinton Hill, there's a condo that

0:13:55.160 --> 0:13:58.400
<v Speaker 1>someone bought for three million dollars and the tax you know,

0:13:58.520 --> 0:14:00.880
<v Speaker 1>it's taxed as if it were, is only one point

0:14:00.920 --> 0:14:04.600
<v Speaker 1>two millions. So even though that home the market value

0:14:05.160 --> 0:14:09.240
<v Speaker 1>is eight times greater than hers, the actual tax bill

0:14:10.000 --> 0:14:13.160
<v Speaker 1>is only a thousand dollars more for that prop higher

0:14:13.200 --> 0:14:16.800
<v Speaker 1>price property. So once again, the burden of it is,

0:14:16.880 --> 0:14:20.320
<v Speaker 1>you know, tilted unfairly. There's something called the effective tax rate,

0:14:20.320 --> 0:14:22.920
<v Speaker 1>which I'm sure everyone knows about. That's what gets skewed

0:14:22.920 --> 0:14:26.760
<v Speaker 1>because of these valuations. That was Bloomberg News Projects and

0:14:26.840 --> 0:14:30.640
<v Speaker 1>Investigations reporter Jason Grotto and Bloomberg Business Week editor Joel Weber.

0:14:30.880 --> 0:14:33.520
<v Speaker 1>Check out more of Business week special equality issue. It's

0:14:33.520 --> 0:14:37.680
<v Speaker 1>on newsstands, online, and on the Bloomberg still ahead. Unfortunately

0:14:37.920 --> 0:14:41.520
<v Speaker 1>for New York City, it seems to be anomalous compared

0:14:41.600 --> 0:14:43.560
<v Speaker 1>to a lot of the declines we're seeing in the

0:14:43.600 --> 0:14:45.440
<v Speaker 1>rest of the country. We check in with the CEO

0:14:45.480 --> 0:14:49.480
<v Speaker 1>of New York Presbyterian Hospital. One year since the COVID outbreak. Yes,

0:14:49.520 --> 0:14:51.360
<v Speaker 1>we've made some progress, but there's still a lot of

0:14:51.400 --> 0:14:53.840
<v Speaker 1>costs for concern. There really is. You're listening to Bloomberg

0:14:53.840 --> 0:15:01.040
<v Speaker 1>Business Week. This is Bloomberg broadcasting from the financial capital

0:15:01.080 --> 0:15:04.920
<v Speaker 1>of the world Bloomberg eleven Frio in New York to Washington,

0:15:04.960 --> 0:15:09.080
<v Speaker 1>d C. Bloomberg to Boston, Bloomberg one oh six one,

0:15:09.160 --> 0:15:12.640
<v Speaker 1>to San Francisco, Bloomberg nine sixty to the country Sirius

0:15:12.800 --> 0:15:15.960
<v Speaker 1>XM Chado one nineteen and around the globe the Bloomberg

0:15:16.000 --> 0:15:20.400
<v Speaker 1>Business app and Bloomberg Radio dot Com. This is Bloomberg

0:15:20.440 --> 0:15:23.640
<v Speaker 1>Business Week. So, as we mentioned at the top, this

0:15:23.680 --> 0:15:26.000
<v Speaker 1>week marked the one year anniversary when the World Health

0:15:26.120 --> 0:15:30.240
<v Speaker 1>Organization declared the coronavirus outbreak a global pandemic, which meant

0:15:30.520 --> 0:15:32.720
<v Speaker 1>tim we know this for so many of us, the

0:15:32.760 --> 0:15:36.120
<v Speaker 1>beginning of working from home and a real complete disruption

0:15:36.320 --> 0:15:40.200
<v Speaker 1>of our lives. Friday thirteenth, we're talking about Friday, March thirteen,

0:15:41.120 --> 0:15:43.800
<v Speaker 1>tim that was the day we last had a live

0:15:43.880 --> 0:15:46.000
<v Speaker 1>guest in studio. I think for a lot of people,

0:15:46.200 --> 0:15:48.520
<v Speaker 1>including our next guests, there were signs that this was

0:15:48.560 --> 0:15:51.360
<v Speaker 1>going to be worse than we thought, even earlier then

0:15:51.600 --> 0:15:54.480
<v Speaker 1>March thirteenth of last year. Dr Stephen cor Went, President

0:15:54.480 --> 0:15:57.400
<v Speaker 1>and CEO of New York Presbyterian Hospital, who, as you

0:15:57.480 --> 0:16:00.400
<v Speaker 1>might recall the New York Times calling in the Ring,

0:16:00.560 --> 0:16:04.119
<v Speaker 1>the CEO at the center of New York's coronavirus crisis.

0:16:04.240 --> 0:16:08.440
<v Speaker 1>Unfortunately for New York City, it seems to be anomalous

0:16:08.480 --> 0:16:10.880
<v Speaker 1>compared to a lot of the declines we're seeing in

0:16:10.920 --> 0:16:13.960
<v Speaker 1>the rest of the country. What we've seen was a

0:16:14.040 --> 0:16:19.000
<v Speaker 1>secondary surge that started in that December time frame, and

0:16:19.080 --> 0:16:22.280
<v Speaker 1>we still have a lot of COVID patients in the

0:16:22.320 --> 0:16:25.000
<v Speaker 1>hospital and a lot of sick COVID patients in the hospital.

0:16:25.520 --> 0:16:29.480
<v Speaker 1>So although we're about thirty to thirty five percent of

0:16:29.560 --> 0:16:32.520
<v Speaker 1>where we were at that horrendous peak in the April

0:16:32.520 --> 0:16:35.360
<v Speaker 1>time frame, we still have a lot of patients in

0:16:35.400 --> 0:16:38.480
<v Speaker 1>the i c U. We're still living with the virus,

0:16:38.480 --> 0:16:40.800
<v Speaker 1>and the positivity rate in New York City still is

0:16:40.840 --> 0:16:44.040
<v Speaker 1>hovering in that five percent range. So it still doesn't

0:16:44.040 --> 0:16:47.240
<v Speaker 1>really feel good in terms of what our emergency rooms

0:16:47.240 --> 0:16:51.600
<v Speaker 1>and I S users seeing. So hopefully with the with

0:16:51.680 --> 0:16:55.200
<v Speaker 1>the vaccine, as we get more people vaccinated UH, the

0:16:55.280 --> 0:16:58.160
<v Speaker 1>quicker we get people vaccinated, the less likely one of

0:16:58.240 --> 0:17:03.160
<v Speaker 1>these variants UH will escape the vaccine and we can

0:17:03.200 --> 0:17:05.280
<v Speaker 1>get back to normal. But right now we're seeing a

0:17:05.280 --> 0:17:08.159
<v Speaker 1>plateau at a level that we're not really happy with.

0:17:08.320 --> 0:17:10.920
<v Speaker 1>To be honest with you, that's some really disconcerting news.

0:17:10.920 --> 0:17:13.520
<v Speaker 1>And my question is is why. I mean, we did

0:17:13.600 --> 0:17:16.840
<v Speaker 1>learn today that new virus variances account for fifty of

0:17:16.880 --> 0:17:19.640
<v Speaker 1>New York City's COVID cases. That's what health officials said

0:17:19.840 --> 0:17:22.640
<v Speaker 1>at a briefing on Wednesday. We know that these are

0:17:23.040 --> 0:17:26.040
<v Speaker 1>more infectious than older strains of the virus. Is this

0:17:26.080 --> 0:17:29.040
<v Speaker 1>why this is happening in New York? I think so.

0:17:29.240 --> 0:17:32.560
<v Speaker 1>I mean, you know, all of this becomes speculative because

0:17:32.560 --> 0:17:35.200
<v Speaker 1>we're not testing every single sample, but it looks like

0:17:36.440 --> 0:17:39.280
<v Speaker 1>the British variant is the dominant variant. We've seen some

0:17:39.400 --> 0:17:43.320
<v Speaker 1>South African variant with our own genetic testing when we

0:17:43.359 --> 0:17:46.879
<v Speaker 1>do sampling. Um So, I think that that's probably it.

0:17:47.440 --> 0:17:51.040
<v Speaker 1>The more disturbing thing is that the percentage in the

0:17:51.040 --> 0:17:54.040
<v Speaker 1>i c US has gone up, and that means that

0:17:54.119 --> 0:17:56.440
<v Speaker 1>you know that the number of people who are quite

0:17:56.520 --> 0:17:59.439
<v Speaker 1>critically ill has gone up. Um So, even with the

0:17:59.480 --> 0:18:03.160
<v Speaker 1>south to get variant with Johnson and Johnson vaccine, people

0:18:03.200 --> 0:18:05.720
<v Speaker 1>did not end up in the hospital and did not

0:18:05.920 --> 0:18:08.040
<v Speaker 1>end up in the i c U. So I think

0:18:08.080 --> 0:18:10.800
<v Speaker 1>that's going to be the critical thing, making sure that

0:18:10.800 --> 0:18:13.040
<v Speaker 1>people don't end up in the hospital, even if the

0:18:13.080 --> 0:18:17.240
<v Speaker 1>positivity rate is high. Dr. Coroner the demographics the same

0:18:17.280 --> 0:18:19.960
<v Speaker 1>as it older people, is it minorities in terms of

0:18:20.320 --> 0:18:23.280
<v Speaker 1>the more severe cases or the majority. It's a somewhat

0:18:23.320 --> 0:18:28.280
<v Speaker 1>younger skew in part because I think that, thank god,

0:18:28.320 --> 0:18:31.040
<v Speaker 1>the nursing home patients and a lot of elderly patients

0:18:31.040 --> 0:18:34.879
<v Speaker 1>have already gotten the vaccine. So that's good. Um And

0:18:34.960 --> 0:18:38.280
<v Speaker 1>we're you know, uh, I know that younger people are

0:18:38.320 --> 0:18:40.520
<v Speaker 1>at lower risk, but we see a lot of young

0:18:40.600 --> 0:18:42.840
<v Speaker 1>people in the i c U. So everyone's got to

0:18:42.880 --> 0:18:47.560
<v Speaker 1>be particularly people young people who are have high body

0:18:47.600 --> 0:18:52.359
<v Speaker 1>mass indexes or are obese or prediabetic and diabetic. So

0:18:53.680 --> 0:18:57.720
<v Speaker 1>so that's that's a concern. You know, I heard you

0:18:57.840 --> 0:19:03.240
<v Speaker 1>two anecdotes about what you recall. My recollection of that

0:19:03.440 --> 0:19:05.720
<v Speaker 1>day was, you know, in March eight, believe it or not,

0:19:06.320 --> 0:19:09.800
<v Speaker 1>March eighth of last year, we had four COVID cases

0:19:09.800 --> 0:19:12.679
<v Speaker 1>in our entire health system, which has thirty six undred beds.

0:19:13.680 --> 0:19:17.320
<v Speaker 1>By March fifteenth, we had sixty six patients. By March

0:19:17.400 --> 0:19:21.919
<v Speaker 1>two we had five nine patients, and by Marche we

0:19:22.000 --> 0:19:26.720
<v Speaker 1>had patients. So you call that dramatic slope and for

0:19:26.800 --> 0:19:30.159
<v Speaker 1>those of us in New York, how absolutely horrific it is.

0:19:30.200 --> 0:19:35.280
<v Speaker 1>But my recollection of that week was actually this very day, Uh,

0:19:35.440 --> 0:19:39.960
<v Speaker 1>my chief Operating Officer, Dr. Laura Freese called her contacts

0:19:40.800 --> 0:19:43.680
<v Speaker 1>in the archdiocese and said, you don't really plan to

0:19:43.720 --> 0:19:45.719
<v Speaker 1>go ahead with the St. Patrick's Day parade, do you?

0:19:46.600 --> 0:19:49.440
<v Speaker 1>And if you recall that Friday before the St. Patrick's Day,

0:19:50.119 --> 0:19:54.760
<v Speaker 1>they canceled it. Uh And um, you know we all

0:19:54.800 --> 0:19:57.960
<v Speaker 1>sort of rolled into it thinking let's hope for the best,

0:19:58.160 --> 0:20:01.240
<v Speaker 1>and it was really horrific. Listen to him, that's something

0:20:01.280 --> 0:20:04.040
<v Speaker 1>we've heard over and over throughout the pandemic. That was

0:20:04.119 --> 0:20:07.560
<v Speaker 1>Dr Stephen Corwin, President n C of New York Presbyterian Hospital.

0:20:07.920 --> 0:20:10.040
<v Speaker 1>And we know that even though vaccines are are rolling

0:20:10.040 --> 0:20:12.720
<v Speaker 1>out him, We've heard from everybody, still got to wear masks.

0:20:12.760 --> 0:20:14.880
<v Speaker 1>You's still got to do some social distancing. We still

0:20:14.880 --> 0:20:16.639
<v Speaker 1>have a long way to go. Yeah, we certainly do.

0:20:16.920 --> 0:20:32.080
<v Speaker 1>You're listening to Bloomberg Business Week up next, Always be well,

0:20:32.160 --> 0:20:36.920
<v Speaker 1>increasingly that is the case. Somebody is watching a Bloomberg

0:20:37.000 --> 0:20:42.400
<v Speaker 1>exclusive involving the breach of thousands of surveillance cameras inside hospitals, companies,

0:20:42.480 --> 0:20:45.560
<v Speaker 1>police departments, prisons and more. Totally creeped out. All right,

0:20:45.600 --> 0:20:48.480
<v Speaker 1>what our team uncovered that's coming up next. This is Bloomberg.

0:20:59.160 --> 0:21:02.679
<v Speaker 1>You're listening to Bloomberg Business Week with Carol Messer and

0:21:02.760 --> 0:21:08.200
<v Speaker 1>Bloomberg Quick Takes. Tim Stinovik from Bloomberg Radio. Big Bloomberg

0:21:08.240 --> 0:21:09.960
<v Speaker 1>exclusive this week. We were all over it when it

0:21:10.000 --> 0:21:12.639
<v Speaker 1>crossed the Bloomberg terminal. It was about a group of

0:21:12.640 --> 0:21:16.000
<v Speaker 1>hackers that say they breached a massive trope of security

0:21:16.000 --> 0:21:18.720
<v Speaker 1>camera data collected by a Silicon Valley startup and tim.

0:21:18.720 --> 0:21:21.600
<v Speaker 1>In doing so, they gained access to live feeds of

0:21:21.600 --> 0:21:24.359
<v Speaker 1>what about a hundred and fifty thousand surveillance cameras. They

0:21:24.400 --> 0:21:29.520
<v Speaker 1>were inside everywhere, hospitals, companies, police departments, prison schools, even

0:21:29.560 --> 0:21:34.400
<v Speaker 1>a testless supplier. But talk about serendipity. When this news broke,

0:21:34.440 --> 0:21:37.359
<v Speaker 1>we actually had Tom Siebel, founder and chairman and CEO

0:21:37.520 --> 0:21:40.600
<v Speaker 1>at C three AI on the air. You were talking

0:21:40.640 --> 0:21:43.640
<v Speaker 1>to him. Tom is also, of course founder of Sibel Systems.

0:21:44.040 --> 0:21:50.080
<v Speaker 1>I think the threat associated with US cyber threat okay

0:21:50.280 --> 0:21:54.600
<v Speaker 1>from bad actors at nation states including Russia, China, North Korea,

0:21:54.680 --> 0:21:59.560
<v Speaker 1>Iran is existential. I mean, these people have the ability

0:22:00.160 --> 0:22:03.439
<v Speaker 1>to shut down the United States, a great power, great infrastructure,

0:22:03.560 --> 0:22:07.800
<v Speaker 1>the financial system, the healthcare system, you know, with a

0:22:07.880 --> 0:22:09.840
<v Speaker 1>cell from from the other side of the planet, and

0:22:09.880 --> 0:22:13.120
<v Speaker 1>they can do it tomorrow. This has been very very

0:22:13.160 --> 0:22:16.880
<v Speaker 1>well documented in books that have been recently published, such

0:22:16.920 --> 0:22:20.320
<v Speaker 1>as The Perfect Weapon and this is how they tell

0:22:20.359 --> 0:22:24.119
<v Speaker 1>me the world ends. Uh. And this is very various

0:22:24.160 --> 0:22:28.840
<v Speaker 1>here stuff. The National Security Commission for Artificial Intelligence published

0:22:28.880 --> 0:22:32.800
<v Speaker 1>its report for years in the making, then concludes that

0:22:32.920 --> 0:22:38.200
<v Speaker 1>today the United States government is not organized or investing

0:22:38.280 --> 0:22:43.640
<v Speaker 1>to win the technology competition against the committed competitor, nor

0:22:43.840 --> 0:22:48.159
<v Speaker 1>is it prepared to defend against AI enabled threats and

0:22:48.400 --> 0:22:52.919
<v Speaker 1>rapidly adopt AI applications for national security purposes, that we

0:22:53.000 --> 0:22:56.600
<v Speaker 1>are exposed there are bad actors out there, and this

0:22:56.720 --> 0:22:58.960
<v Speaker 1>is very scary. Well, you know, it just reminds me

0:22:59.000 --> 0:23:01.080
<v Speaker 1>of It's like I've seen this movie before. We saw

0:23:01.080 --> 0:23:03.040
<v Speaker 1>it in the form of the health pandemic. Lots of

0:23:03.040 --> 0:23:06.320
<v Speaker 1>warnings for years, and yet we weren't prepared. And I

0:23:06.400 --> 0:23:09.000
<v Speaker 1>feel like we're setting setting up for something like that again.

0:23:09.040 --> 0:23:10.960
<v Speaker 1>And I have to say, I'm reading this story and

0:23:10.960 --> 0:23:14.440
<v Speaker 1>they say, um, they breached massive trove of security camera

0:23:14.520 --> 0:23:18.600
<v Speaker 1>data collected by a Silicon Valley startup, Ricata. They gained

0:23:18.600 --> 0:23:20.840
<v Speaker 1>access to live feeds of a hundred and fifty tho

0:23:21.040 --> 0:23:25.240
<v Speaker 1>security cameras inside hospitals, companies, police departments, prisons, and schools,

0:23:25.720 --> 0:23:29.800
<v Speaker 1>able to view video from inside women's health clinics, psychiatric hospitals,

0:23:29.800 --> 0:23:34.159
<v Speaker 1>and the offices of this company of Ricata itself. Um.

0:23:34.280 --> 0:23:37.560
<v Speaker 1>And they were using in some cases, some of these cameras,

0:23:37.680 --> 0:23:41.760
<v Speaker 1>including in hospitals, were using facial recognition technology to identify

0:23:41.800 --> 0:23:45.480
<v Speaker 1>and categorize people captured on the footage. UM. I think

0:23:45.480 --> 0:23:49.000
<v Speaker 1>about this. You are so in on the AI world.

0:23:49.480 --> 0:23:52.400
<v Speaker 1>You talk about us not being prepared for Listen, there's

0:23:52.480 --> 0:23:55.240
<v Speaker 1>great things to be had by it, but there's also

0:23:55.280 --> 0:23:57.840
<v Speaker 1>a downside. We're not ready for it or not prepared

0:23:57.880 --> 0:24:01.320
<v Speaker 1>for it. When you get into cyber security and info

0:24:01.520 --> 0:24:05.280
<v Speaker 1>sect this is just very scary stuff. I mean, the

0:24:05.400 --> 0:24:10.080
<v Speaker 1>Chinese went into the Office of Personal Management in Washington,

0:24:10.160 --> 0:24:12.959
<v Speaker 1>d C. And it walked off of like twenty million

0:24:13.040 --> 0:24:17.520
<v Speaker 1>records of everybody it's ever been considered for a security clearance.

0:24:18.000 --> 0:24:21.280
<v Speaker 1>I mean, the you know, the Russians were in there

0:24:21.320 --> 0:24:24.480
<v Speaker 1>within the last month and no telling. Nobody's him in

0:24:24.640 --> 0:24:28.280
<v Speaker 1>telling the story of how thoroughly they penetrated the United

0:24:28.320 --> 0:24:32.359
<v Speaker 1>States government. I mean, the Emperor has no clothes either.

0:24:32.440 --> 0:24:36.640
<v Speaker 1>This is not on the national agenda. And this is existential.

0:24:37.040 --> 0:24:39.520
<v Speaker 1>If these people to turn off the US power created,

0:24:39.600 --> 0:24:42.000
<v Speaker 1>which they could do in a second, nine out of

0:24:42.080 --> 0:24:44.840
<v Speaker 1>ten people in the United States die. So this makes

0:24:44.840 --> 0:24:48.720
<v Speaker 1>the whole COVID pandemic look like a common cold, you know,

0:24:48.840 --> 0:24:52.119
<v Speaker 1>compared to I mean, this is very very serious stuff.

0:24:52.160 --> 0:24:56.160
<v Speaker 1>This is existential stuff, and it's not on the national agenda. Yeah,

0:24:56.240 --> 0:24:58.679
<v Speaker 1>it says. Another video shot inside the Tesla warehouse and

0:24:58.720 --> 0:25:01.880
<v Speaker 1>Sayghai says workers an assembly line hacker, said they obtain

0:25:01.960 --> 0:25:05.840
<v Speaker 1>access to two cameras and Tesla factories and warehouses. Well,

0:25:05.880 --> 0:25:09.360
<v Speaker 1>this is your world. You're having conversations with people who

0:25:09.359 --> 0:25:12.040
<v Speaker 1>are tapping into and working with you. Guys, you provide

0:25:12.200 --> 0:25:16.439
<v Speaker 1>you know, enterprise AI software, UM is anybody kind of

0:25:16.480 --> 0:25:19.679
<v Speaker 1>aware of how to do this in a responsible way.

0:25:19.720 --> 0:25:21.960
<v Speaker 1>I mean, this is your world. Yeah. I would say

0:25:22.080 --> 0:25:25.960
<v Speaker 1>the organizations that are most equipped okay and have the

0:25:26.640 --> 0:25:30.040
<v Speaker 1>greatest levels of security as it relates to AI and

0:25:30.160 --> 0:25:34.560
<v Speaker 1>cybersecurity are the banks. I mean, these guys have have

0:25:34.800 --> 0:25:39.440
<v Speaker 1>security regiments for their information systems are completely aero gapped,

0:25:39.840 --> 0:25:44.960
<v Speaker 1>they're tested, they have security protocols that are incredibly vigorous.

0:25:45.119 --> 0:25:48.080
<v Speaker 1>While they're dealing with the US banks or the European banks.

0:25:48.160 --> 0:25:51.119
<v Speaker 1>These people have done us a perlative job, and the

0:25:51.160 --> 0:25:53.800
<v Speaker 1>people in the United States government could go to school

0:25:53.800 --> 0:25:56.560
<v Speaker 1>on that. They look like, you know, candidly, they look

0:25:56.600 --> 0:25:59.560
<v Speaker 1>like cub scouts compared to the way the banks handling

0:25:59.560 --> 0:26:02.800
<v Speaker 1>information security. You've been kind enough to indulge us as

0:26:02.840 --> 0:26:06.000
<v Speaker 1>we were breaking down these headlines on this major hack.

0:26:06.040 --> 0:26:08.480
<v Speaker 1>You know, listen, Tom, You've been in the technology world

0:26:08.520 --> 0:26:10.320
<v Speaker 1>for a long time. You've seen it evolved. It's gotten

0:26:10.400 --> 0:26:13.440
<v Speaker 1>much more sophisticated, it's got a lot more invasive, it's

0:26:13.480 --> 0:26:16.400
<v Speaker 1>gotten a lot more useful, and it's such a part

0:26:16.440 --> 0:26:20.560
<v Speaker 1>of everything that we do. AI specifically talk to us

0:26:20.600 --> 0:26:22.719
<v Speaker 1>about kind of what's front and center right now in

0:26:22.800 --> 0:26:25.800
<v Speaker 1>terms of where it's going, who's using it, where it's

0:26:25.840 --> 0:26:29.919
<v Speaker 1>going to be the most productive. Well, leading corporations around

0:26:29.960 --> 0:26:41.160
<v Speaker 1>the world are using AI and smarting analytics, precision medicine, aerospace, manufacturing, telecommunications, banking,

0:26:41.600 --> 0:26:45.440
<v Speaker 1>and they're using AI to deliver better products and services,

0:26:45.800 --> 0:26:51.639
<v Speaker 1>to deliver safer, cleaner, more reliable energy. They're using AI

0:26:51.720 --> 0:26:58.280
<v Speaker 1>to secure data, data assets from cybersecurity attacks. They're using

0:26:58.320 --> 0:27:02.400
<v Speaker 1>AI and defense and intel agents. This is the largest

0:27:02.520 --> 0:27:05.840
<v Speaker 1>this is you know, we look at enterprise AI software.

0:27:06.160 --> 0:27:09.879
<v Speaker 1>This is a third of a trillion dollars market in

0:27:10.080 --> 0:27:15.080
<v Speaker 1>say so, this is the largest growing enterprise application software

0:27:15.119 --> 0:27:18.920
<v Speaker 1>market in history. Okay, and we serve all segments of

0:27:19.000 --> 0:27:22.440
<v Speaker 1>that industry, from banking to tel go to healthcare to government. Listen.

0:27:22.560 --> 0:27:25.040
<v Speaker 1>So give me AI for dummies, because I feel like

0:27:25.119 --> 0:27:29.080
<v Speaker 1>we throw around, certainly not you, but we throw around

0:27:29.119 --> 0:27:31.760
<v Speaker 1>the term artificial intelligence a lot, and I think people

0:27:31.840 --> 0:27:34.080
<v Speaker 1>have a grasp of it, but I don't think they understand,

0:27:34.160 --> 0:27:37.800
<v Speaker 1>especially as you go through that list of basically our world,

0:27:37.920 --> 0:27:41.680
<v Speaker 1>to be quite fair, whether it's military, whether it's you know, medical,

0:27:41.800 --> 0:27:45.560
<v Speaker 1>whether it's energy, um where the use of AI is

0:27:45.720 --> 0:27:48.159
<v Speaker 1>making things so much better. What is the AI for

0:27:48.240 --> 0:27:51.240
<v Speaker 1>dummies if you had to explain it to somebody, great question. Okay,

0:27:51.280 --> 0:27:53.800
<v Speaker 1>so AI and so many to strip away all the

0:27:54.400 --> 0:27:57.439
<v Speaker 1>all the mystique and all the noise, AI is an

0:27:57.480 --> 0:28:01.920
<v Speaker 1>area that would call predictive and where we're able due

0:28:02.000 --> 0:28:06.800
<v Speaker 1>to kind of advances in information technology to solve problems

0:28:06.880 --> 0:28:09.719
<v Speaker 1>that never been able to solve before. Where we can

0:28:09.920 --> 0:28:15.879
<v Speaker 1>predict things before they happen very accurately. Heart failure okay,

0:28:16.280 --> 0:28:22.679
<v Speaker 1>diabetes Okay, it's a failure of a transformer in New

0:28:22.760 --> 0:28:26.560
<v Speaker 1>York City. Okay, the failure of a jet engine, so

0:28:26.760 --> 0:28:30.040
<v Speaker 1>we can predict these events, or the failure of a

0:28:30.920 --> 0:28:33.720
<v Speaker 1>critical piece of equipment on an offshore or rig, say

0:28:33.800 --> 0:28:37.040
<v Speaker 1>for world Dutch Shell, where we can predict these events,

0:28:37.280 --> 0:28:41.600
<v Speaker 1>you know, say days or months in advance, and replace

0:28:41.720 --> 0:28:46.480
<v Speaker 1>the transformer in New York City and prevent the electricity outage. Okay,

0:28:47.400 --> 0:28:52.400
<v Speaker 1>intervene uh clinically and prevent the heart failure. Okay, you

0:28:52.800 --> 0:28:57.240
<v Speaker 1>do some intervention on the machine and present the aircraft

0:28:57.320 --> 0:29:00.640
<v Speaker 1>failure before it fails. That in a nutshell, that's what

0:29:00.880 --> 0:29:05.040
<v Speaker 1>enterprise AI is all about, is predictive ant relication. That is,

0:29:05.560 --> 0:29:08.920
<v Speaker 1>accurately predicting events before they happen. And we're able to

0:29:09.000 --> 0:29:12.440
<v Speaker 1>do that today with very high levels of precision. Well,

0:29:12.480 --> 0:29:14.400
<v Speaker 1>and when it comes to something like healthcare, Listen, we

0:29:14.520 --> 0:29:17.120
<v Speaker 1>have all been obsessed with our health care because our

0:29:17.160 --> 0:29:20.360
<v Speaker 1>lives depended on it in the last year. And understanding

0:29:20.440 --> 0:29:24.080
<v Speaker 1>we all got I think safe to say, somewhat smarter

0:29:24.320 --> 0:29:28.160
<v Speaker 1>in understanding how vaccines are developed and the complications of

0:29:28.440 --> 0:29:31.200
<v Speaker 1>you know, a virus and and all these things. When

0:29:31.240 --> 0:29:34.160
<v Speaker 1>it comes to healthcare specifically, you talk about AI like

0:29:34.280 --> 0:29:36.440
<v Speaker 1>we can predict heart failure. I mean, is this an

0:29:36.480 --> 0:29:39.000
<v Speaker 1>area that we have yet to explore in a big

0:29:39.040 --> 0:29:41.240
<v Speaker 1>way when it comes to a I yes, I think

0:29:41.280 --> 0:29:42.960
<v Speaker 1>this is well. This is a field where we apply

0:29:43.120 --> 0:29:46.160
<v Speaker 1>AI to healthcare. This is what we call precision medicine.

0:29:46.520 --> 0:29:50.160
<v Speaker 1>This will be the largest commercial application of AI. And

0:29:50.280 --> 0:29:53.280
<v Speaker 1>for example, we can take the genome sequences and the

0:29:53.400 --> 0:29:56.040
<v Speaker 1>health care records of say the population of the United

0:29:56.080 --> 0:30:01.360
<v Speaker 1>States or any population, okay, and apply seene learning algorithms

0:30:01.440 --> 0:30:05.480
<v Speaker 1>to these data and predict with very high levels of precision,

0:30:06.360 --> 0:30:09.200
<v Speaker 1>who is going to be diagnosed with what disease? Okay

0:30:09.240 --> 0:30:12.200
<v Speaker 1>in the next five years, heart disease, lung cancer or

0:30:12.240 --> 0:30:16.680
<v Speaker 1>whatever it might be, and then intervene clinically and avoid

0:30:16.800 --> 0:30:21.480
<v Speaker 1>the diagnosis. Well, you combine that with telemedicine to reach

0:30:22.320 --> 0:30:27.680
<v Speaker 1>previously unserved UM members of the community, and the economic

0:30:27.800 --> 0:30:31.080
<v Speaker 1>and social benefit of this is staggering. Then you have genomes,

0:30:31.120 --> 0:30:35.320
<v Speaker 1>specifical medical protocols where where we you know, have tailored

0:30:35.400 --> 0:30:39.520
<v Speaker 1>medical protocols to the individual genome which are highly much

0:30:39.600 --> 0:30:42.400
<v Speaker 1>going to be much more highly efficacious at a much

0:30:42.480 --> 0:30:45.560
<v Speaker 1>lower cost. So these are examples of a I applied

0:30:45.640 --> 0:30:49.240
<v Speaker 1>to medicine. This will be again the largest application of

0:30:49.320 --> 0:30:53.160
<v Speaker 1>ai UH in any field. That was Tom Siebel, founder,

0:30:53.240 --> 0:30:56.360
<v Speaker 1>chairman and CEO at C three AI. He's also author

0:30:56.360 --> 0:30:59.360
<v Speaker 1>of the book Digital Transformation, Survive and Thrive in an

0:30:59.440 --> 0:31:02.600
<v Speaker 1>Era Mass Extinction. That wraps up the first hour of

0:31:02.640 --> 0:31:05.080
<v Speaker 1>the weekend edition of Bloomberg Business Week from Bloomberg Radio.

0:31:05.160 --> 0:31:07.600
<v Speaker 1>I'm Carol Masser and I'm Tim Stanivik. More ahead in

0:31:07.640 --> 0:31:11.480
<v Speaker 1>our next hour, including our Women's History Months special Hour,

0:31:11.800 --> 0:31:15.280
<v Speaker 1>a look at prominent individuals and finance, tech, venture capital

0:31:15.360 --> 0:31:18.239
<v Speaker 1>and innovation who just also happened to be women as well.

0:31:18.440 --> 0:31:20.960
<v Speaker 1>That's right, are all female lineup includes the CEO of

0:31:21.000 --> 0:31:23.520
<v Speaker 1>work Board and why diversity is so important, especially when

0:31:23.520 --> 0:31:26.680
<v Speaker 1>it comes to venture capital. Also the CFO Estate Lauder

0:31:26.760 --> 0:31:30.000
<v Speaker 1>on global growth and consumers what they're buying lipstick not

0:31:30.200 --> 0:31:33.360
<v Speaker 1>so much skincare. Yeah, I definitely bought a lot of

0:31:33.400 --> 0:31:37.320
<v Speaker 1>skincare during the pandemic. And also coming up Verizon Business

0:31:37.360 --> 0:31:41.120
<v Speaker 1>CEO on supporting women owned small businesses and female entrepreneurs.

0:31:41.440 --> 0:31:44.840
<v Speaker 1>And grab your favorite snack, but ditch that plastic cutlery.

0:31:44.840 --> 0:31:47.040
<v Speaker 1>We're gonna have the president founder of Habits of Waste

0:31:47.160 --> 0:31:49.640
<v Speaker 1>on how you can help combat climate change by making

0:31:49.840 --> 0:31:52.200
<v Speaker 1>these simple changes in your life. Doesn't have to be

0:31:52.240 --> 0:31:56.040
<v Speaker 1>an organic snack. I don't know, but it's gonna be easy. Okay, deal.

0:31:56.680 --> 0:32:05.120
<v Speaker 1>This is Bloomberg for those fortunate enough to help the

0:32:05.200 --> 0:32:07.560
<v Speaker 1>person who has always been their hero find the care

0:32:07.640 --> 0:32:10.000
<v Speaker 1>guides you need to help at a a ARP dot

0:32:10.160 --> 0:32:12.760
<v Speaker 1>org slash Caregiving brought to you by a ARP and

0:32:12.840 --> 0:32:17.959
<v Speaker 1>the ad Console. This is Bloomberg Business Week inside from

0:32:18.000 --> 0:32:21.160
<v Speaker 1>the reporters and editors who bring you America's most trusted

0:32:21.240 --> 0:32:25.320
<v Speaker 1>business magazine, plus global business, finance and tech news as

0:32:25.400 --> 0:32:29.280
<v Speaker 1>it happened, Sloomberg Business Week with Carol Messer and Bloomberg

0:32:29.400 --> 0:32:34.400
<v Speaker 1>Quick Takes Tim Stinovic on Bloomberg Radio. Hi, I'm Carol Masser.

0:32:34.520 --> 0:32:36.920
<v Speaker 1>And in the second hour of the weekend edition of

0:32:36.960 --> 0:32:40.160
<v Speaker 1>Bloomberg Business Weeks, some of our great guests on International

0:32:40.240 --> 0:32:43.480
<v Speaker 1>Women's Day, leaders in tech, innovation, branding, and the environment,

0:32:43.520 --> 0:32:45.840
<v Speaker 1>who just happened to be women as well. We're going

0:32:45.920 --> 0:32:47.920
<v Speaker 1>to hear from the CFO at Estate Lauder on how

0:32:47.960 --> 0:32:50.840
<v Speaker 1>the global cosmetics giant and its consumers around the globe

0:32:50.880 --> 0:32:53.480
<v Speaker 1>have been shopping during the pandemic. Yeah, the trends have

0:32:53.640 --> 0:32:55.640
<v Speaker 1>changed a little bit. Also, a friend of the show,

0:32:55.800 --> 0:32:58.560
<v Speaker 1>Verizon Business CEO Tammy Urin, on where we stand in

0:32:58.640 --> 0:33:01.120
<v Speaker 1>the fight for equality. Little hint, We've got a long

0:33:01.120 --> 0:33:03.320
<v Speaker 1>way to go. Yeah, we certainly do. Carol, you also

0:33:03.360 --> 0:33:05.640
<v Speaker 1>had a great conversation with the president and founder of

0:33:05.720 --> 0:33:09.360
<v Speaker 1>Habits of Waste. She's spreading the message about small, everyday

0:33:09.480 --> 0:33:13.160
<v Speaker 1>changes that we can make that would make a big difference.

0:33:13.360 --> 0:33:15.600
<v Speaker 1>This was a favorite interview of mine. First up, though,

0:33:15.680 --> 0:33:18.200
<v Speaker 1>let's get to the entrepreneur who has founded and led

0:33:18.280 --> 0:33:21.320
<v Speaker 1>three tech startups, sold one to IBM ran a high

0:33:21.360 --> 0:33:24.840
<v Speaker 1>growth business at IBM. We're talking about dadre Park not

0:33:25.120 --> 0:33:28.360
<v Speaker 1>she's CEO and co founder of the Enterprise sas company Workboard.

0:33:28.880 --> 0:33:31.920
<v Speaker 1>They work with Comcast, Cisco, g E, S, tra Zenica,

0:33:32.080 --> 0:33:35.720
<v Speaker 1>so many companies, And she is definitely no stranger to

0:33:35.800 --> 0:33:39.080
<v Speaker 1>the VC world. This is my third company where I

0:33:39.120 --> 0:33:42.840
<v Speaker 1>thought funding and got funding a CC world and I'll say,

0:33:43.160 --> 0:33:45.520
<v Speaker 1>you know, with some embarrassment that it hasn't improved much

0:33:46.560 --> 0:33:48.720
<v Speaker 1>a few decades that I've been working on it. I

0:33:48.800 --> 0:33:51.840
<v Speaker 1>think part of it is, um, we don't look like

0:33:52.600 --> 0:33:56.920
<v Speaker 1>what the prototypical founder should look like, right, the architect

0:33:57.000 --> 0:34:00.200
<v Speaker 1>that people have in their heads. Now, that's changing, I

0:34:00.320 --> 0:34:02.680
<v Speaker 1>think now in very meaningful ways. And there's a lot

0:34:02.760 --> 0:34:06.880
<v Speaker 1>of organizations driving chains, including for example, all Rays, and

0:34:07.000 --> 0:34:09.279
<v Speaker 1>what you see today which you just wouldn't have seen

0:34:09.520 --> 0:34:12.320
<v Speaker 1>five years ago, much less ten years ago, is women

0:34:12.520 --> 0:34:17.680
<v Speaker 1>partners at really every quality firm has real women partners

0:34:17.760 --> 0:34:22.680
<v Speaker 1>making real investment decisions, uh and driving those investment decisions

0:34:22.719 --> 0:34:25.839
<v Speaker 1>in in the VC firm. So I think we well,

0:34:25.880 --> 0:34:27.640
<v Speaker 1>it takes a bit of time. I think we actually

0:34:27.680 --> 0:34:32.560
<v Speaker 1>finally turned a corner on getting women partners in the

0:34:32.680 --> 0:34:36.000
<v Speaker 1>venture firms that actually fuel those startups. Well, that that

0:34:36.440 --> 0:34:39.719
<v Speaker 1>gives me hope. Um. What about corporate boards though, and

0:34:39.920 --> 0:34:41.719
<v Speaker 1>I know this is something that you've certainly been keeping

0:34:41.760 --> 0:34:46.799
<v Speaker 1>an eye. Corporate boards still mostly white? Uh white? Are

0:34:46.920 --> 0:34:52.680
<v Speaker 1>eight in ten directors at Spies at least are still male.

0:34:53.800 --> 0:34:55.799
<v Speaker 1>What's going on with corporate boards? Why is it so slow?

0:34:55.880 --> 0:34:59.279
<v Speaker 1>Especially when we you know, we know the research when

0:34:59.280 --> 0:35:01.839
<v Speaker 1>it comes to diver City Mackenzie's done at so many

0:35:01.920 --> 0:35:04.200
<v Speaker 1>others have done at that. When you've got a diverse board,

0:35:04.239 --> 0:35:09.920
<v Speaker 1>when you've got a diverse senior leadership, you do better financially. Yea.

0:35:10.080 --> 0:35:12.440
<v Speaker 1>I think there's a couple of things that are shifting

0:35:12.520 --> 0:35:15.239
<v Speaker 1>there and that will accelerate some sense of sort of

0:35:15.360 --> 0:35:20.000
<v Speaker 1>accelerate post But a couple of those. One is you know,

0:35:20.200 --> 0:35:23.680
<v Speaker 1>I just added to women independent directors to my board,

0:35:24.200 --> 0:35:28.279
<v Speaker 1>Margot Geo Judgis, who was a former CEO of Ancestry

0:35:28.280 --> 0:35:32.120
<v Speaker 1>and Kathy Bengko, who is a former vice chair of Deloitte,

0:35:32.200 --> 0:35:35.759
<v Speaker 1>both really senior talented women, And as I was doing

0:35:35.840 --> 0:35:38.719
<v Speaker 1>the search to add them to the board, I used

0:35:38.800 --> 0:35:42.759
<v Speaker 1>a search firm that was focused on women executives. And

0:35:42.880 --> 0:35:45.280
<v Speaker 1>so what they've done, which is something I think hadn't

0:35:45.320 --> 0:35:48.360
<v Speaker 1>been done in the past, is actually build the database

0:35:49.000 --> 0:35:52.600
<v Speaker 1>of candidates, build the pool so that when you want

0:35:52.640 --> 0:35:55.120
<v Speaker 1>to find talent, you're looking at a pool that is

0:35:55.280 --> 0:35:59.439
<v Speaker 1>enriched by women leaders and women executives versus the same

0:35:59.440 --> 0:36:01.600
<v Speaker 1>old data is of the same old pool that looks

0:36:01.640 --> 0:36:03.640
<v Speaker 1>the same old way it's always looked. And that's what

0:36:03.719 --> 0:36:05.359
<v Speaker 1>people and that's what's going on still on a lot

0:36:05.400 --> 0:36:07.800
<v Speaker 1>of companies right everybody's going back to the existing pools,

0:36:07.920 --> 0:36:11.600
<v Speaker 1>the old ones exactly. But I do think that executive

0:36:11.600 --> 0:36:16.400
<v Speaker 1>search firms are now quite mindful of opening the aperture.

0:36:16.600 --> 0:36:19.480
<v Speaker 1>The other thing, and probably more interesting, is in my

0:36:19.640 --> 0:36:24.040
<v Speaker 1>work with senior leaders, most of them are looking beyond

0:36:24.160 --> 0:36:29.239
<v Speaker 1>their own sector for expertise, for insights for how other

0:36:29.360 --> 0:36:31.480
<v Speaker 1>people are changing the game, and most of them are

0:36:31.600 --> 0:36:37.120
<v Speaker 1>acutely aware of the extreme disruptive opportunities and frankly risks

0:36:37.520 --> 0:36:39.879
<v Speaker 1>and face their business. And I think that what we'll

0:36:39.920 --> 0:36:44.960
<v Speaker 1>see is this enormous generation of direct to consumer leaders,

0:36:45.520 --> 0:36:49.080
<v Speaker 1>many of whom are women, who have created fantastic companies,

0:36:49.280 --> 0:36:52.600
<v Speaker 1>grown them have real go to market leadership skills and

0:36:52.640 --> 0:36:56.239
<v Speaker 1>are very disruptive thinkers. If I were the CEO of

0:36:56.400 --> 0:37:02.360
<v Speaker 1>a mainstream company looking for diversity of thought provocative ideas

0:37:02.400 --> 0:37:04.560
<v Speaker 1>in a way to enrich the conversations I was having

0:37:04.640 --> 0:37:07.959
<v Speaker 1>at the board, I would look to those disruptive leaders

0:37:08.040 --> 0:37:13.080
<v Speaker 1>coming out of d C, DTC, what for, what forgive me?

0:37:13.160 --> 0:37:15.200
<v Speaker 1>And what is it about d to see that you

0:37:15.320 --> 0:37:18.440
<v Speaker 1>think really puts them out there ahead of ahead of others.

0:37:19.840 --> 0:37:23.520
<v Speaker 1>Their business models, the way they think about reaching their customers,

0:37:23.600 --> 0:37:26.840
<v Speaker 1>the way to think about serving those customers. It's a

0:37:28.800 --> 0:37:31.840
<v Speaker 1>a lot of it is just blank slate, right, not

0:37:32.040 --> 0:37:33.920
<v Speaker 1>bogged down by the way we've always done it, and

0:37:34.120 --> 0:37:37.279
<v Speaker 1>started instead with what would be awesome? Like what would

0:37:37.360 --> 0:37:40.239
<v Speaker 1>what could we imagine? And then that's a pool of

0:37:41.400 --> 0:37:45.239
<v Speaker 1>many many women in those organizations as co founders, as

0:37:45.280 --> 0:37:48.640
<v Speaker 1>CEOs and clos and CFOs right, women in different roles there.

0:37:48.680 --> 0:37:52.680
<v Speaker 1>So I think it creates a pipeline of diverse talent

0:37:52.960 --> 0:37:57.480
<v Speaker 1>that has the kind of disruptive thinking and phenomenal success

0:37:58.440 --> 0:38:01.479
<v Speaker 1>that you'd want around you in the board room. Because

0:38:01.520 --> 0:38:04.200
<v Speaker 1>I do wonder too, and you probably have a lot

0:38:04.239 --> 0:38:06.120
<v Speaker 1>of experience that this are are a great person to

0:38:06.200 --> 0:38:09.800
<v Speaker 1>talk to about this is that you know, money always talks,

0:38:10.200 --> 0:38:12.560
<v Speaker 1>and I do wonder if there's at some point somebody's

0:38:12.560 --> 0:38:15.480
<v Speaker 1>going to be like, Wow, look at this company, uh,

0:38:15.960 --> 0:38:18.200
<v Speaker 1>the diversity that they've got, and look at how well

0:38:18.239 --> 0:38:21.320
<v Speaker 1>they're doing, and so what's the common denominator? What is

0:38:21.360 --> 0:38:24.560
<v Speaker 1>it that's getting them to that point? And I know

0:38:24.640 --> 0:38:26.400
<v Speaker 1>there's a lot of factors at play that make a

0:38:26.560 --> 0:38:30.759
<v Speaker 1>successful venture or institution or company, but we but we

0:38:30.840 --> 0:38:32.600
<v Speaker 1>know the research, and I do wonder at some point

0:38:32.760 --> 0:38:34.960
<v Speaker 1>is it just people are like, this is the smart

0:38:35.080 --> 0:38:40.160
<v Speaker 1>thing to do financially, especially if you're publicly held or anything. Yeah,

0:38:40.560 --> 0:38:44.279
<v Speaker 1>I think until its leaders perceive CEO is perceive it

0:38:44.360 --> 0:38:47.640
<v Speaker 1>as the smart thing to do financially, until they perceive

0:38:47.719 --> 0:38:50.759
<v Speaker 1>it as when I bring those different voices on that

0:38:50.880 --> 0:38:54.600
<v Speaker 1>different experience to my table, I'm a smarter leader. That

0:38:54.719 --> 0:38:56.960
<v Speaker 1>was dadre Park, no CEO and co founder of the

0:38:57.040 --> 0:39:01.080
<v Speaker 1>Enterprise Sas Company Workboard. The full conversation on our podcast feed.

0:39:01.160 --> 0:39:03.640
<v Speaker 1>You're listening to Bloomberg Business Week coming up, the CFO

0:39:03.719 --> 0:39:06.600
<v Speaker 1>at St. Lauder and what global consumers are buying that's

0:39:06.680 --> 0:39:19.919
<v Speaker 1>up next. This is Bloomberg. This is Bloomberg Business Week

0:39:20.080 --> 0:39:23.839
<v Speaker 1>with Carol Messer and Bloomberg Quick Takes. Tim Spinovik from

0:39:23.960 --> 0:39:28.200
<v Speaker 1>Bloomberg Radio. St. Lauder is a behemoth when it comes

0:39:28.239 --> 0:39:30.960
<v Speaker 1>to the cosmetic, skincare and fragrance world. They are, tim

0:39:31.040 --> 0:39:32.920
<v Speaker 1>one of the largest in the world, selling in some

0:39:33.040 --> 0:39:36.000
<v Speaker 1>a hundred and fifty countries. They own a portfolio brand,

0:39:36.160 --> 0:39:39.959
<v Speaker 1>some created internally, many others like Lamaire, Bobby Brown, glam Glow,

0:39:40.080 --> 0:39:42.840
<v Speaker 1>Mac and others. They bought them. A great person to

0:39:43.000 --> 0:39:45.040
<v Speaker 1>find out what's going on around the world and answer

0:39:45.120 --> 0:39:48.000
<v Speaker 1>the question of what consumers are buying is Tracy Travis,

0:39:48.239 --> 0:39:52.280
<v Speaker 1>Executive Vice president of Finance also CFO of s day Lauder.

0:39:52.680 --> 0:39:57.200
<v Speaker 1>The consumer, UM, you know, based on what we've seen globally,

0:39:57.480 --> 0:40:01.279
<v Speaker 1>you know, is still UM supporting obviously prestige beauty. I

0:40:01.360 --> 0:40:04.600
<v Speaker 1>mean our our sales, you know, are are recovering UM,

0:40:04.800 --> 0:40:08.800
<v Speaker 1>you know, every every month, every every quarter. Certainly we

0:40:08.920 --> 0:40:12.279
<v Speaker 1>just reported our our second quarter results UM, and we

0:40:12.440 --> 0:40:16.359
<v Speaker 1>returned to growth UM for uh, you know, a quarter

0:40:16.480 --> 0:40:20.000
<v Speaker 1>earlier than what we had expected. UM. But the consumer

0:40:20.280 --> 0:40:23.840
<v Speaker 1>is uh, you know, is gradually UM you know, coming

0:40:23.920 --> 0:40:27.319
<v Speaker 1>back to I think spending UM in in the categories

0:40:27.440 --> 0:40:30.600
<v Speaker 1>that that are important to to her like like beauty.

0:40:31.000 --> 0:40:35.640
<v Speaker 1>How did consumer spending shift during the pandemic? Consumer UM

0:40:35.760 --> 0:40:39.879
<v Speaker 1>spending shifted very much UM to online. First of all,

0:40:40.080 --> 0:40:42.279
<v Speaker 1>so you know, we were one of the companies that

0:40:43.080 --> 0:40:47.360
<v Speaker 1>um our our distribution was deemed to be non essential globally.

0:40:47.480 --> 0:40:50.120
<v Speaker 1>You know, we sell only prestige beauty, so we sell

0:40:50.200 --> 0:40:53.480
<v Speaker 1>in a lot of department stores and specialty stores UM

0:40:53.600 --> 0:40:57.560
<v Speaker 1>which closed UM initially during during the pandemic UM and

0:40:57.640 --> 0:41:01.440
<v Speaker 1>then reopened. But you know, TRACK has been been a

0:41:01.520 --> 0:41:04.880
<v Speaker 1>bit light UM and has gradually been building. So we

0:41:04.960 --> 0:41:07.800
<v Speaker 1>saw a tremendous shift to online and we were prepared

0:41:07.880 --> 0:41:10.839
<v Speaker 1>for that, you know, with our own brand dot com

0:41:10.960 --> 0:41:14.080
<v Speaker 1>sites UM, with our retail partners and UH and their

0:41:14.160 --> 0:41:16.439
<v Speaker 1>sites as well as some of the platforms in pure

0:41:16.480 --> 0:41:20.200
<v Speaker 1>play UM sites that that we sell on UM. We

0:41:20.360 --> 0:41:25.839
<v Speaker 1>saw a tremendous UM you know, UH shift to UM

0:41:26.080 --> 0:41:30.120
<v Speaker 1>to looking for her favorite skin care products, whether it's

0:41:30.200 --> 0:41:33.680
<v Speaker 1>Lamaire or Clinique or or Essay Lauder UM or some

0:41:33.880 --> 0:41:37.160
<v Speaker 1>of the other skincare brands that we UH that we have.

0:41:37.520 --> 0:41:41.080
<v Speaker 1>We also saw UM a pick up in fragrance UM

0:41:41.239 --> 0:41:44.920
<v Speaker 1>and again no surprise, more people working from home people

0:41:45.200 --> 0:41:49.000
<v Speaker 1>UM were UM. We saw our our bath and body

0:41:49.560 --> 0:41:53.520
<v Speaker 1>category grow as well as our home fragrance category grow. UM.

0:41:53.920 --> 0:41:55.960
<v Speaker 1>So you know, those are are some of the trends

0:41:56.040 --> 0:41:59.120
<v Speaker 1>that we have observed during the pandemic. Makeup has been

0:41:59.160 --> 0:42:02.520
<v Speaker 1>the most impact of no surprise, given given the fact

0:42:02.600 --> 0:42:04.640
<v Speaker 1>that you know, many people are working from home and

0:42:04.680 --> 0:42:08.279
<v Speaker 1>those that are going out many are wearing masks as uh,

0:42:08.680 --> 0:42:11.319
<v Speaker 1>you know, as instructed, and so that does have an

0:42:11.400 --> 0:42:17.359
<v Speaker 1>impact on particularly the largest categories of makeup, foundation and lips. Um.

0:42:17.560 --> 0:42:21.279
<v Speaker 1>And those are categories that we expect, certainly as the

0:42:21.400 --> 0:42:25.560
<v Speaker 1>vaccine rollout um, you know continues to progress uh and

0:42:25.880 --> 0:42:28.759
<v Speaker 1>uh and we start to see people migrating back to

0:42:28.840 --> 0:42:31.080
<v Speaker 1>work and back to school and resuming some of their

0:42:31.120 --> 0:42:33.840
<v Speaker 1>social activities. UM, we expect to you know, to have

0:42:33.920 --> 0:42:36.920
<v Speaker 1>a strong, strong makeup recovery at that point in time. Tracy,

0:42:36.960 --> 0:42:38.799
<v Speaker 1>I feel like you've described me. I spend so much

0:42:38.840 --> 0:42:43.880
<v Speaker 1>more on skincare uh in the last year or so.

0:42:44.520 --> 0:42:48.840
<v Speaker 1>UM then then you know, certainly on you know, traditional makeup.

0:42:48.880 --> 0:42:52.279
<v Speaker 1>And it's just very interesting you talked about though, you know,

0:42:52.360 --> 0:42:55.239
<v Speaker 1>shifting to online and I do wonder we've seen just

0:42:55.400 --> 0:42:59.240
<v Speaker 1>an increased digitization of our world when it comes to retail.

0:42:59.320 --> 0:43:01.759
<v Speaker 1>Not just you guy is but everybody and you know,

0:43:02.480 --> 0:43:04.600
<v Speaker 1>folks that had strategies that maybe they were going to

0:43:04.680 --> 0:43:06.640
<v Speaker 1>roll out over the you know, next three to five years,

0:43:06.640 --> 0:43:09.560
<v Speaker 1>all of a sudden did them overnight? What has changed

0:43:09.560 --> 0:43:13.040
<v Speaker 1>in terms of your digital strategy specifically because of the

0:43:13.120 --> 0:43:15.640
<v Speaker 1>pandemic and just you know, seeing how this is how

0:43:15.719 --> 0:43:19.400
<v Speaker 1>an increasing number of consumers want to shop. Well, we

0:43:19.560 --> 0:43:22.800
<v Speaker 1>had a very strong UM focus on on online for

0:43:23.080 --> 0:43:26.799
<v Speaker 1>for many years. Actually we started our online sites more

0:43:26.880 --> 0:43:29.560
<v Speaker 1>than more than twenty years ago UM, and we were

0:43:29.640 --> 0:43:32.680
<v Speaker 1>focused at was our fastest growing channel heading into the pandemic.

0:43:33.040 --> 0:43:36.480
<v Speaker 1>What we've seen is an acceleration of the penetration of

0:43:36.719 --> 0:43:40.640
<v Speaker 1>of online. Certainly more consumers, a lot of new consumers

0:43:40.760 --> 0:43:44.880
<v Speaker 1>that we had not seen purchase online previously started to

0:43:44.960 --> 0:43:49.480
<v Speaker 1>purchase online. Obviously when when UM brick and mortar UM

0:43:49.680 --> 0:43:54.160
<v Speaker 1>you know, became less less attractive to shop in UM

0:43:54.320 --> 0:43:56.880
<v Speaker 1>during this pandemic. And so we expect that we're going

0:43:56.960 --> 0:43:59.880
<v Speaker 1>to continue to see those those trends coming coming out

0:44:00.000 --> 0:44:03.200
<v Speaker 1>of the pandemic. Clearly, we expect that consumers will return

0:44:03.280 --> 0:44:05.520
<v Speaker 1>to brick and mortar. But those that you know have

0:44:06.360 --> 0:44:10.320
<v Speaker 1>developed the habit of shopping online we expect will continue

0:44:10.800 --> 0:44:13.200
<v Speaker 1>and we have added quite a bit of functionality to

0:44:13.440 --> 0:44:16.720
<v Speaker 1>our online site that have many of our retail partners.

0:44:16.880 --> 0:44:19.759
<v Speaker 1>We've added virtual try on in terms of makeup UM,

0:44:19.880 --> 0:44:24.120
<v Speaker 1>we have a virtual diagnostic for our clinique brand UM.

0:44:24.239 --> 0:44:26.640
<v Speaker 1>We have live streaming events. We've added a lot more

0:44:26.800 --> 0:44:30.160
<v Speaker 1>video content and how too, and we've actually seen which

0:44:30.239 --> 0:44:32.520
<v Speaker 1>is one of our encouraging signs for makeup, We've seen

0:44:33.239 --> 0:44:38.320
<v Speaker 1>more consumers actually access those videos and uh UM you know,

0:44:38.440 --> 0:44:41.759
<v Speaker 1>with an interest in learning more about skincare treatments as

0:44:41.800 --> 0:44:45.480
<v Speaker 1>well as UH as well as makeup treatments as well.

0:44:46.040 --> 0:44:48.560
<v Speaker 1>This is this is a business where people like to

0:44:48.960 --> 0:44:52.279
<v Speaker 1>try before they buy UM, and you know, they do

0:44:52.440 --> 0:44:56.680
<v Speaker 1>that in person in stores. I'm wondering how the in

0:44:56.800 --> 0:44:58.839
<v Speaker 1>person experience is going to change on the other side

0:44:58.840 --> 0:45:02.920
<v Speaker 1>of this pandemic. We think that you know, again, uh

0:45:03.400 --> 0:45:06.720
<v Speaker 1>you know, we have tried to add as much consultation

0:45:07.440 --> 0:45:10.560
<v Speaker 1>to our online sites as as possible, but we also

0:45:10.680 --> 0:45:13.960
<v Speaker 1>know that people miss that human interaction UM and that

0:45:14.200 --> 0:45:18.680
<v Speaker 1>ability to actually buy now, get now, and so that's

0:45:18.760 --> 0:45:22.440
<v Speaker 1>something that you know, certainly an in store experience provides

0:45:22.480 --> 0:45:25.800
<v Speaker 1>an addition to as as you mentioned being able to

0:45:26.360 --> 0:45:29.920
<v Speaker 1>physically physically try on product. You know, we have sanitary

0:45:30.000 --> 0:45:32.560
<v Speaker 1>practices at you know, all of our counters and in

0:45:32.640 --> 0:45:36.800
<v Speaker 1>our freestanding stores. UM. So you know, as consumers return,

0:45:36.960 --> 0:45:40.160
<v Speaker 1>you know, we are are making sure that um that

0:45:40.320 --> 0:45:44.320
<v Speaker 1>they can try comfortably. And and you know, in terms

0:45:44.400 --> 0:45:47.400
<v Speaker 1>of the behavior's post post pandemic, you know, we do

0:45:47.560 --> 0:45:50.319
<v Speaker 1>expect that. You know, we ended last year with our

0:45:50.400 --> 0:45:54.160
<v Speaker 1>online business, UM, you know at a twenty penetration. You know,

0:45:54.239 --> 0:45:57.560
<v Speaker 1>we certainly expect grow from from there going forward, as

0:45:57.680 --> 0:46:01.040
<v Speaker 1>vaccines continue to roll out, they're expecting more business. Of course.

0:46:01.120 --> 0:46:04.160
<v Speaker 1>That was Tracy Travis, Executive vice president of Finance also

0:46:04.280 --> 0:46:06.800
<v Speaker 1>CFO of St. Lawder. I gotta say I find it

0:46:06.880 --> 0:46:09.279
<v Speaker 1>interesting too, you know, and I'm not surprised. We've seen

0:46:09.400 --> 0:46:12.279
<v Speaker 1>shopping trends changed dramatically over the past year, what people

0:46:12.320 --> 0:46:15.000
<v Speaker 1>are buying, how they're buying, uh, and what she talked

0:46:15.000 --> 0:46:17.320
<v Speaker 1>about kind of a focus on skincare. I've seen that

0:46:17.360 --> 0:46:19.760
<v Speaker 1>in my own world. You know, you're not buying lipstick,

0:46:19.800 --> 0:46:21.680
<v Speaker 1>You're not doing the things you were doing when the

0:46:21.719 --> 0:46:24.160
<v Speaker 1>world was opening, you know, was opened up. Yeah, it

0:46:24.239 --> 0:46:26.520
<v Speaker 1>makes sense if you're wearing a mask you're not necessarily

0:46:26.600 --> 0:46:28.640
<v Speaker 1>buying what you'd be putting on your face. You seem

0:46:28.640 --> 0:46:32.640
<v Speaker 1>like a mask kind of guy. Wait, I was I

0:46:32.800 --> 0:46:36.360
<v Speaker 1>was thinking of Like, I wasn't thinking of that. I

0:46:36.560 --> 0:46:39.279
<v Speaker 1>was thinking of like overnight masks. I mean, I wasn't

0:46:39.280 --> 0:46:41.600
<v Speaker 1>thinking of overnight masks, That's what I mean. I was thinking,

0:46:41.880 --> 0:46:44.920
<v Speaker 1>as you're also like, you know, my my nine that

0:46:44.960 --> 0:46:46.960
<v Speaker 1>I'm wearing around the office. That's what I'm thinking. Well,

0:46:47.120 --> 0:46:48.880
<v Speaker 1>you're that too, But I could see you like, I

0:46:48.920 --> 0:46:53.160
<v Speaker 1>didn't think, yeah, sure, sign me up, give it to me,

0:46:54.600 --> 0:46:56.719
<v Speaker 1>all right, still to come up Bloomberg Business Week. I

0:46:56.800 --> 0:46:58.880
<v Speaker 1>think what we're now seeing as a sense of hope

0:46:59.080 --> 0:47:02.680
<v Speaker 1>and optimism. Verizon Business CEO Tammy Irwin on helping women

0:47:02.719 --> 0:47:16.320
<v Speaker 1>and female entrepreneurs succeed. This is Bloomberg Broadcasting from the

0:47:16.440 --> 0:47:20.279
<v Speaker 1>financial capital of the World Bloomberg eleven Frio in New

0:47:20.360 --> 0:47:24.799
<v Speaker 1>York to Washington, d C. Bloomberg to Boston, Bloomberg one

0:47:24.880 --> 0:47:28.000
<v Speaker 1>O six one to San Francisco, Bloomberg nine sixty to

0:47:28.080 --> 0:47:31.279
<v Speaker 1>the country Sirius XM Chado one nineteen and around the

0:47:31.320 --> 0:47:34.759
<v Speaker 1>globe the Bloomberg Business app and Bloomberg Radio dot Com.

0:47:35.400 --> 0:47:40.840
<v Speaker 1>This is Bloomberg Business Week. Carol recently Verizing Business announcing

0:47:40.840 --> 0:47:43.439
<v Speaker 1>an effort led by our next guest. It's all about

0:47:43.560 --> 0:47:47.319
<v Speaker 1>championing women and confronting the ongoing crisis of women leaving

0:47:47.360 --> 0:47:50.640
<v Speaker 1>the workforce at unprecedented rates due to the impact of

0:47:50.680 --> 0:47:53.480
<v Speaker 1>the pandemic. We see it everywhere. Tim, She's a favorite

0:47:53.520 --> 0:47:55.479
<v Speaker 1>voice of mine to check in with. We're talking about

0:47:55.560 --> 0:47:59.120
<v Speaker 1>Verizon Business CEO Tammy Irwin, who I've talked with several

0:47:59.239 --> 0:48:02.680
<v Speaker 1>times throughout a pandemic, and this time around again that's

0:48:02.680 --> 0:48:05.399
<v Speaker 1>where we started. We've talked so much about how people

0:48:05.440 --> 0:48:07.960
<v Speaker 1>have reacted and responded, and now we're really in that

0:48:08.080 --> 0:48:11.880
<v Speaker 1>phase where people are beginning to reimagine what the workforce

0:48:12.000 --> 0:48:14.600
<v Speaker 1>of the future looks like. We're calling that work forward

0:48:14.680 --> 0:48:16.840
<v Speaker 1>at Verizon, which is how will we work and what

0:48:16.960 --> 0:48:19.480
<v Speaker 1>does the new norm look like? You know, Carole and

0:48:19.560 --> 0:48:21.880
<v Speaker 1>I have talked about some of the challenges that women

0:48:21.920 --> 0:48:25.239
<v Speaker 1>have faced throughout the cod and I think what we're

0:48:25.280 --> 0:48:28.080
<v Speaker 1>now seeing is a sense of hope and optimism, a

0:48:28.160 --> 0:48:30.919
<v Speaker 1>sense that kids might be back in school in the fall.

0:48:31.480 --> 0:48:33.359
<v Speaker 1>So I would just tell you, I think we're seeing

0:48:33.440 --> 0:48:36.239
<v Speaker 1>resiliency and we're seeing the hope as people begin to

0:48:36.400 --> 0:48:38.480
<v Speaker 1>look to what the workforce of the future might be

0:48:39.120 --> 0:48:41.360
<v Speaker 1>and how that will give women a little more time

0:48:41.520 --> 0:48:44.080
<v Speaker 1>to lean into their career and people a chance to

0:48:44.120 --> 0:48:46.320
<v Speaker 1>get out and live life well. Having said that, you

0:48:46.480 --> 0:48:49.320
<v Speaker 1>guys at Verizon are very specific and deliberate when it

0:48:49.400 --> 0:48:52.719
<v Speaker 1>comes to initiatives and programs. Talk to us about the

0:48:52.800 --> 0:48:54.480
<v Speaker 1>most recent effort and some of the work that you

0:48:54.560 --> 0:48:56.880
<v Speaker 1>guys have done, whether it's mentoring, whether it's working with

0:48:56.960 --> 0:48:59.040
<v Speaker 1>small businesses. Tell me a little bit about what you

0:48:59.120 --> 0:49:03.200
<v Speaker 1>guys are doing right now. Yeah, thank you for the opportunity.

0:49:03.280 --> 0:49:05.160
<v Speaker 1>We are really proud of the work that we've done

0:49:05.239 --> 0:49:07.560
<v Speaker 1>to really put a spotlight on so many thanks. Carroll

0:49:07.640 --> 0:49:09.719
<v Speaker 1>and I have talked about the fact that when COVID hit,

0:49:09.840 --> 0:49:12.320
<v Speaker 1>we said our number one priority was taking care of

0:49:12.360 --> 0:49:16.120
<v Speaker 1>our employees, followed by our second stakeholders, which is making

0:49:16.200 --> 0:49:18.960
<v Speaker 1>sure customers have all the connectivity in the services that

0:49:19.040 --> 0:49:21.919
<v Speaker 1>they get and relied on from Verizon, and then third

0:49:22.000 --> 0:49:25.160
<v Speaker 1>caring for shareholders, and forth caring for society. And as

0:49:25.239 --> 0:49:27.640
<v Speaker 1>we've looked at how we really lean in and care

0:49:27.800 --> 0:49:30.880
<v Speaker 1>for all four of those stakeholders, we've really put a

0:49:30.960 --> 0:49:33.279
<v Speaker 1>lot of time into how do we make sure that

0:49:33.440 --> 0:49:36.160
<v Speaker 1>women have a chance to be successful. We know in

0:49:36.280 --> 0:49:39.720
<v Speaker 1>January alone, two hundred and seventy five thousand women dropped

0:49:39.760 --> 0:49:42.360
<v Speaker 1>out of the labor force. We know that women are

0:49:42.440 --> 0:49:45.759
<v Speaker 1>coming into the workforce more educated than ever before, but

0:49:45.880 --> 0:49:47.960
<v Speaker 1>following out. So what we've done is a number of

0:49:48.000 --> 0:49:52.160
<v Speaker 1>things building off of things we did in We successfully

0:49:52.239 --> 0:49:55.160
<v Speaker 1>launched a program last year called Women in Business and

0:49:55.239 --> 0:49:57.680
<v Speaker 1>it was a series of seminars, and it was a

0:49:57.760 --> 0:50:00.520
<v Speaker 1>seminar that really focused on a number of different its vertical,

0:50:00.640 --> 0:50:03.560
<v Speaker 1>so whether you were in the healthcare, whether you were entertainment,

0:50:03.640 --> 0:50:06.960
<v Speaker 1>whether you were in a public sector of finance, you

0:50:07.040 --> 0:50:09.320
<v Speaker 1>had an opportunity to do say what are other women

0:50:09.440 --> 0:50:11.200
<v Speaker 1>doing them? What are the things I need to do

0:50:11.400 --> 0:50:15.000
<v Speaker 1>to be successful? Those summers are reviewed two hundred thousand

0:50:15.120 --> 0:50:18.759
<v Speaker 1>times because what we know is that working women view

0:50:18.960 --> 0:50:23.120
<v Speaker 1>employee sponsored resources. It's an important aspect of how they

0:50:23.360 --> 0:50:26.560
<v Speaker 1>do it all, how they've battle this work personal that

0:50:26.600 --> 0:50:28.960
<v Speaker 1>they're trying to do. We're really building out that phone

0:50:28.960 --> 0:50:31.400
<v Speaker 1>and we said that's great for yesterday, but what can

0:50:31.440 --> 0:50:34.920
<v Speaker 1>we do in one And we've launched a new program

0:50:35.000 --> 0:50:38.480
<v Speaker 1>we announced on Friday called the Rizon Collab and It

0:50:38.880 --> 0:50:42.719
<v Speaker 1>was really intended to be a collaborative career engine platform

0:50:43.200 --> 0:50:45.600
<v Speaker 1>that we're going to invite others to participate on. As

0:50:45.680 --> 0:50:48.440
<v Speaker 1>we talked with women about the things that they need

0:50:48.520 --> 0:50:52.319
<v Speaker 1>to do to be most successful, as they reimagine UM

0:50:52.480 --> 0:50:55.759
<v Speaker 1>and an environment posts COD and we think that's really important. Terry.

0:50:55.800 --> 0:50:57.560
<v Speaker 1>One thing I want to ask you, especially because you

0:50:57.840 --> 0:51:00.480
<v Speaker 1>at Verizon in your team, there's a lot of different

0:51:00.520 --> 0:51:02.680
<v Speaker 1>programs that you put out there, what really makes a

0:51:02.760 --> 0:51:07.200
<v Speaker 1>difference in terms of giving UM a woman, a woman's

0:51:07.280 --> 0:51:10.320
<v Speaker 1>the support they need, the leg up, the ability to

0:51:10.560 --> 0:51:13.640
<v Speaker 1>kind of aspire for more, you know, where they maybe have,

0:51:14.200 --> 0:51:17.520
<v Speaker 1>you know, financial responsibilities at a firm, you know, to

0:51:17.640 --> 0:51:20.560
<v Speaker 1>take on more. What what are the programs? Is it mentoring?

0:51:21.239 --> 0:51:23.480
<v Speaker 1>Is it? You know, we had a great story on

0:51:23.560 --> 0:51:27.560
<v Speaker 1>the Bloomberg specifically at a European bank who said, you know,

0:51:27.760 --> 0:51:31.360
<v Speaker 1>what really makes a difference is child care enable you know,

0:51:31.520 --> 0:51:34.200
<v Speaker 1>enabling women to then take on more. So what is

0:51:34.239 --> 0:51:38.040
<v Speaker 1>it specifically that you find packs the biggest punch when

0:51:38.120 --> 0:51:42.080
<v Speaker 1>it comes to helping women advance professionally and really get

0:51:42.160 --> 0:51:45.920
<v Speaker 1>to those higher echelons. Yeah, listen, I think there's several

0:51:46.040 --> 0:51:49.440
<v Speaker 1>critical things. One you touched on, which is caregiver programs,

0:51:49.520 --> 0:51:52.680
<v Speaker 1>whether it's caring for children or caring for aging parents,

0:51:52.840 --> 0:51:57.040
<v Speaker 1>making sure that companies offer programs to give families choice

0:51:57.480 --> 0:51:59.680
<v Speaker 1>as to how they take care of those responsibilities. So

0:51:59.760 --> 0:52:02.360
<v Speaker 1>that's one we've really taken a leadership position, and the

0:52:02.440 --> 0:52:05.000
<v Speaker 1>other one is really making sure that women have the

0:52:05.200 --> 0:52:09.200
<v Speaker 1>right kind of competent skills and capabilities to compete in

0:52:09.400 --> 0:52:12.320
<v Speaker 1>the in the work environment. I started a program in

0:52:12.360 --> 0:52:16.239
<v Speaker 1>two thousand seventeen that I'm super excited about. It's called WOW,

0:52:16.440 --> 0:52:19.960
<v Speaker 1>which was Women of Wireless we translated into Women of

0:52:20.040 --> 0:52:22.920
<v Speaker 1>the World. It is a program deployed across Verizon. At

0:52:22.960 --> 0:52:26.080
<v Speaker 1>this point, we've got six thousand women who have graduated

0:52:26.120 --> 0:52:29.439
<v Speaker 1>from that program, and it's really designed to say, help

0:52:29.560 --> 0:52:33.600
<v Speaker 1>women learn great confidence, how do I define my personal

0:52:33.719 --> 0:52:38.640
<v Speaker 1>brand as a woman, compete for jobs, have good communication skills,

0:52:38.800 --> 0:52:41.680
<v Speaker 1>and learn to network, all things women are great at,

0:52:41.920 --> 0:52:44.640
<v Speaker 1>but sometimes they need a little encouragement. Sometimes they need

0:52:44.719 --> 0:52:46.800
<v Speaker 1>to be taught how to affectively do that. That was

0:52:46.960 --> 0:52:50.120
<v Speaker 1>Rising Business CEO Tammy Irwin cutting up. Most people don't

0:52:50.160 --> 0:52:52.440
<v Speaker 1>even want it, so it's a win win. And by

0:52:52.480 --> 0:52:55.000
<v Speaker 1>the way, restaurants are saving a ton of money. Our

0:52:55.120 --> 0:52:58.520
<v Speaker 1>next guest successfully convinced Uber to change settings in their

0:52:58.520 --> 0:53:01.840
<v Speaker 1>applications so that no one no one receives forks and

0:53:01.920 --> 0:53:04.439
<v Speaker 1>knives plastic forks and knives unless they ask for it. Wow,

0:53:04.520 --> 0:53:06.680
<v Speaker 1>talk about a change maker. This is the president and

0:53:06.719 --> 0:53:09.440
<v Speaker 1>founder of Habits of Waste. Coming up next. You're listening

0:53:09.440 --> 0:53:19.680
<v Speaker 1>to Bloomberg Business Week. This is Bloomberg. You're listening to

0:53:19.840 --> 0:53:23.720
<v Speaker 1>Bloomberg Business Week with Carol Messer and Bloomberg Quick Takes.

0:53:23.840 --> 0:53:28.800
<v Speaker 1>Tim Stinovik from Bloomberg Radio. Tim, we have talked a

0:53:28.880 --> 0:53:31.240
<v Speaker 1>lot about the climate, certainly on air and about climate

0:53:31.320 --> 0:53:34.360
<v Speaker 1>change in the past year. Some good blue skuys animals

0:53:34.440 --> 0:53:36.920
<v Speaker 1>coming out seeing mountain ranges for the first time as

0:53:36.960 --> 0:53:39.520
<v Speaker 1>our society was shut down because of the pandemic. Not

0:53:39.600 --> 0:53:41.400
<v Speaker 1>good that it was shut down because of that, but

0:53:41.600 --> 0:53:43.960
<v Speaker 1>nonetheless the environment came back in a big way. Right

0:53:44.000 --> 0:53:46.319
<v Speaker 1>is Bloombergreen reported last year as many as two point

0:53:46.360 --> 0:53:50.000
<v Speaker 1>six billion metric tons of carbon dioxide emissions. It's about

0:53:50.080 --> 0:53:52.560
<v Speaker 1>eight percent of the estimated total for the year will

0:53:52.680 --> 0:53:55.920
<v Speaker 1>never be admitted into the atmosphere. That's according to estimates

0:53:55.960 --> 0:53:59.799
<v Speaker 1>by the International Energy Agency pick any world shaking event

0:54:00.200 --> 0:54:04.880
<v Speaker 1>twentieth century history, none has produced a bigger decrease in admissions,

0:54:05.040 --> 0:54:07.240
<v Speaker 1>and that's the good news. But Tim, you also smartly

0:54:07.320 --> 0:54:10.239
<v Speaker 1>remind us that we've also seen single use garbage to

0:54:10.239 --> 0:54:13.080
<v Speaker 1>move up, plastic utensils, masks, and a lot more because

0:54:13.120 --> 0:54:15.839
<v Speaker 1>of the pandemic. Masks on the ground, loves on the ground,

0:54:15.880 --> 0:54:18.440
<v Speaker 1>you still see it everywhere. Yeah, exactly, Well, looking at

0:54:18.480 --> 0:54:21.040
<v Speaker 1>how we can create all of us can create better

0:54:21.160 --> 0:54:23.799
<v Speaker 1>habits that help the environment and climate. Is Sheila more

0:54:23.840 --> 0:54:26.120
<v Speaker 1>of body. She's president and founder of Habits of Waste,

0:54:26.440 --> 0:54:28.440
<v Speaker 1>and we began talking about what the past year has

0:54:28.480 --> 0:54:31.160
<v Speaker 1>been like for her. It's been quiet. I have to

0:54:31.239 --> 0:54:34.800
<v Speaker 1>say I've been Um. I was living a very intense

0:54:34.920 --> 0:54:37.239
<v Speaker 1>life prior to the pandemic. I don't even know how

0:54:37.320 --> 0:54:39.080
<v Speaker 1>I did it. I mean I was a classic person

0:54:39.160 --> 0:54:41.560
<v Speaker 1>that was burning the candle at two ends, and the

0:54:41.680 --> 0:54:45.640
<v Speaker 1>pandemic just forced us into a very different lifestyle that, um,

0:54:46.400 --> 0:54:48.479
<v Speaker 1>you know, really made me think a lot of about

0:54:48.480 --> 0:54:51.640
<v Speaker 1>a lot of things. So, um, the environment is definitely

0:54:51.680 --> 0:54:53.240
<v Speaker 1>at the top of the list. Well, and it's interesting

0:54:53.320 --> 0:54:55.520
<v Speaker 1>because of the pandemic. As I mentioned, Uh, and the

0:54:55.600 --> 0:54:57.280
<v Speaker 1>inswer to this is that like all of a sudden

0:54:57.360 --> 0:54:59.520
<v Speaker 1>we talked about with people not driving to work and

0:55:00.080 --> 0:55:03.680
<v Speaker 1>planes not flying, uh, the environment got a lot cleaner.

0:55:04.160 --> 0:55:06.680
<v Speaker 1>At the same time, we have been using a lot

0:55:06.760 --> 0:55:11.080
<v Speaker 1>of single use items, whether it's uh, plastic cutlery and

0:55:11.200 --> 0:55:15.000
<v Speaker 1>plastic bags or you know, masks one time. So it's

0:55:15.440 --> 0:55:18.920
<v Speaker 1>it's kind of this dichotomy of of different things going on. UM,

0:55:19.480 --> 0:55:22.400
<v Speaker 1>tell us about what you are trying to do with

0:55:22.520 --> 0:55:24.880
<v Speaker 1>habits of waste, especially when I feel like we've all

0:55:24.960 --> 0:55:27.920
<v Speaker 1>had a past year to really think about our impact,

0:55:28.080 --> 0:55:33.160
<v Speaker 1>our footprint on society. Absolutely, UM, So I come into

0:55:33.239 --> 0:55:35.719
<v Speaker 1>environmentalism with a little bit of a different angle. I

0:55:35.880 --> 0:55:39.279
<v Speaker 1>studied sociology at U c l A and found it

0:55:39.320 --> 0:55:42.560
<v Speaker 1>fascinating to understand human behavior and how to shift the

0:55:42.600 --> 0:55:46.120
<v Speaker 1>behavior of the masses. So throughout the pandemic, UM, food

0:55:46.160 --> 0:55:50.120
<v Speaker 1>delivery applications went through the roof. So the increase in

0:55:50.160 --> 0:55:54.400
<v Speaker 1>food delivery orders was about So what I realized is

0:55:54.960 --> 0:55:58.040
<v Speaker 1>if we were able to convince people to only receive

0:55:58.120 --> 0:56:02.720
<v Speaker 1>plastic cutlery upon request, how could we decrease the forty

0:56:02.800 --> 0:56:05.640
<v Speaker 1>billion pieces of plastic cutlery that are entering our waste

0:56:05.680 --> 0:56:08.560
<v Speaker 1>stream every single year. So I was able to convince

0:56:08.719 --> 0:56:12.840
<v Speaker 1>uber Eats, Postmates, and grub Hub to swap that default setting,

0:56:12.960 --> 0:56:16.120
<v Speaker 1>so it's no plastic cutlery comes out anymore unless you

0:56:16.200 --> 0:56:18.920
<v Speaker 1>ask for it. We're still waiting on DoorDash to jump in,

0:56:19.080 --> 0:56:21.400
<v Speaker 1>and it's imperative that they join us because they had

0:56:21.400 --> 0:56:26.480
<v Speaker 1>about of all food delivery orders. In that being said, um,

0:56:26.600 --> 0:56:29.719
<v Speaker 1>we used technology to get to this point. We had

0:56:29.719 --> 0:56:32.320
<v Speaker 1>an email campaign on our website at Habits of Waste

0:56:32.360 --> 0:56:35.200
<v Speaker 1>dot org where users could come in send an email

0:56:35.239 --> 0:56:37.799
<v Speaker 1>and it would go directly to these food delivery applications.

0:56:37.880 --> 0:56:40.919
<v Speaker 1>And I felt that if the food delivery apps knew

0:56:41.040 --> 0:56:42.959
<v Speaker 1>that this is what we wanted. We have this junk

0:56:43.080 --> 0:56:45.480
<v Speaker 1>drawer everybody has in the kitchen that they feel horrible

0:56:45.520 --> 0:56:48.279
<v Speaker 1>about throwing away, yet it built to the rim with

0:56:48.400 --> 0:56:51.239
<v Speaker 1>plastic cutlery. I mean, ask anybody they've got one. So

0:56:51.640 --> 0:56:55.120
<v Speaker 1>luckily these emails worked and we sent about ten thousand

0:56:55.160 --> 0:56:57.960
<v Speaker 1>emails to date, and now we're just holding out for

0:56:58.080 --> 0:57:00.960
<v Speaker 1>DoorDash and then we'll have it all done. Amazing. How though,

0:57:01.040 --> 0:57:02.600
<v Speaker 1>like I've got to say, we've gotten used to it

0:57:02.640 --> 0:57:04.600
<v Speaker 1>and not getting cutlery and don't miss it. I'm actually

0:57:04.680 --> 0:57:07.200
<v Speaker 1>kind of grateful. That we're not getting it, and silly

0:57:07.280 --> 0:57:09.120
<v Speaker 1>for us for not kind of saying earlier on like

0:57:09.200 --> 0:57:10.719
<v Speaker 1>don't you know, don't put it in. But it became

0:57:10.719 --> 0:57:13.680
<v Speaker 1>such a habit right of all the takeout places, right,

0:57:13.800 --> 0:57:16.680
<v Speaker 1>and it's really about choice architecture, Like, how is it

0:57:16.800 --> 0:57:19.880
<v Speaker 1>that we're just being bombarded with these habitual behaviors of

0:57:19.960 --> 0:57:22.919
<v Speaker 1>waste without really getting a chance to even do better

0:57:23.120 --> 0:57:26.160
<v Speaker 1>or bypass it. You know, I spearheaded the first plastic

0:57:26.240 --> 0:57:28.360
<v Speaker 1>straw and cutlery ban in history, which was in the

0:57:28.440 --> 0:57:32.360
<v Speaker 1>city of Malibu, and unfortunately, banning plastic straws was a

0:57:32.440 --> 0:57:35.080
<v Speaker 1>lot easier than banning plastic cutlery. So here we are

0:57:35.520 --> 0:57:38.840
<v Speaker 1>trying to at least have it only upon request, and

0:57:38.920 --> 0:57:41.320
<v Speaker 1>most people don't even want it, so it's a win win.

0:57:41.680 --> 0:57:44.080
<v Speaker 1>And by the way, restaurants are saving a ton of money.

0:57:44.720 --> 0:57:47.840
<v Speaker 1>I'll give you this one really interesting fact. Postmates announced

0:57:47.880 --> 0:57:49.920
<v Speaker 1>that within a year they saved a hundred and twenty

0:57:49.960 --> 0:57:53.000
<v Speaker 1>two million packs of cutlery from entering the environment, and

0:57:53.160 --> 0:57:56.040
<v Speaker 1>that was an equivalent of three point two million dollars

0:57:56.080 --> 0:57:59.960
<v Speaker 1>in savings for restaurants. So, you know, plastic is really important,

0:58:00.160 --> 0:58:03.240
<v Speaker 1>But the next most important thing that I've ever done,

0:58:03.320 --> 0:58:06.680
<v Speaker 1>probably in my whole entire life, has been um, trying

0:58:06.760 --> 0:58:08.800
<v Speaker 1>to get more people to eat plants. Well, well, the

0:58:09.440 --> 0:58:11.600
<v Speaker 1>almost important thing we need to do right now, Sheila,

0:58:11.720 --> 0:58:13.720
<v Speaker 1>let's talk about I'm up on your website and I

0:58:13.840 --> 0:58:16.840
<v Speaker 1>was looking at it earlier today as well. There's a

0:58:16.960 --> 0:58:19.880
<v Speaker 1>form you can fill out to join a challenge that

0:58:20.000 --> 0:58:24.120
<v Speaker 1>you have. It's called hashtag eight meals. What's that about? Yeah,

0:58:24.200 --> 0:58:27.240
<v Speaker 1>so um. Actually, it's a brand new app that we

0:58:27.320 --> 0:58:29.680
<v Speaker 1>have and it's available in the app Store under Habits

0:58:29.720 --> 0:58:32.680
<v Speaker 1>of Waste and eight Meals was basically born because you know,

0:58:32.840 --> 0:58:36.120
<v Speaker 1>I'm very much involved in environmental work, yet one thing

0:58:36.200 --> 0:58:38.360
<v Speaker 1>I've yet to, you know, be able to commit to

0:58:38.800 --> 0:58:42.760
<v Speaker 1>fully is going fully vegan and eating every single meal

0:58:42.880 --> 0:58:46.160
<v Speaker 1>plant based. Is just something that I felt was impossible.

0:58:46.720 --> 0:58:49.480
<v Speaker 1>If I feel this way, I can guarantee that many

0:58:49.560 --> 0:58:52.040
<v Speaker 1>of your listeners probably feel the same way. And I

0:58:52.160 --> 0:58:55.800
<v Speaker 1>felt very dissuaded by the whole thing, and always like I, Okay,

0:58:55.840 --> 0:58:57.440
<v Speaker 1>I'm going to try this week, but then I'd fall

0:58:57.480 --> 0:59:00.120
<v Speaker 1>off the bandwagon. I came across the study by this

0:59:00.600 --> 0:59:04.400
<v Speaker 1>University of Michigan and two lane talking about how Western

0:59:04.520 --> 0:59:07.560
<v Speaker 1>cultures must decrease their animal protein and take by fort

0:59:08.480 --> 0:59:10.440
<v Speaker 1>at the very minimum in order for us to even

0:59:10.480 --> 0:59:12.840
<v Speaker 1>have a chance that climate change. It is the number

0:59:12.960 --> 0:59:16.520
<v Speaker 1>one thing individuals must do to make an impact. So

0:59:16.640 --> 0:59:18.520
<v Speaker 1>I thought about that and I said, okay, well, how

0:59:18.560 --> 0:59:21.240
<v Speaker 1>do we translate that for the everyday person to be

0:59:21.320 --> 0:59:24.400
<v Speaker 1>able to adopt this idea into their daily lives. So

0:59:24.720 --> 0:59:27.400
<v Speaker 1>three meals a daytime, seven days a week, twenty one meals.

0:59:27.680 --> 0:59:31.480
<v Speaker 1>What's that that gives us eight meals? So that's the goal,

0:59:31.760 --> 0:59:34.000
<v Speaker 1>is that we all want to try and increase our

0:59:34.040 --> 0:59:37.200
<v Speaker 1>plant based meals by eight meals a week, and we've

0:59:37.240 --> 0:59:40.040
<v Speaker 1>created this new application to help everyone do that by

0:59:40.360 --> 0:59:43.680
<v Speaker 1>providing recipes, linking your meals. You want to plug in

0:59:43.800 --> 0:59:45.920
<v Speaker 1>into your calendar, you can check out how much of

0:59:46.000 --> 0:59:49.240
<v Speaker 1>a carbon reduction you're making, because by eating eight meals

0:59:49.280 --> 0:59:53.680
<v Speaker 1>a week, it's actually carbon that you're reducing, which is

0:59:53.720 --> 0:59:56.400
<v Speaker 1>the equivalent of driving a hybrid car a week, I'm sorry,

0:59:56.440 --> 0:59:58.440
<v Speaker 1>a hybrid car for a year. So eight meals a

0:59:58.520 --> 1:00:03.080
<v Speaker 1>week for a year is equivalent. Um, don't you don't

1:00:03.080 --> 1:00:05.240
<v Speaker 1>you almost feel like like I think about this year

1:00:05.360 --> 1:00:09.680
<v Speaker 1>where we as individuals global citizens learned a lot about

1:00:10.160 --> 1:00:13.040
<v Speaker 1>obviously a health pandemic, but also what it takes to

1:00:13.200 --> 1:00:15.480
<v Speaker 1>create a vaccine, Like we peeled back the layers. And

1:00:15.520 --> 1:00:18.760
<v Speaker 1>I almost feel like food production is a thing where

1:00:19.000 --> 1:00:21.560
<v Speaker 1>I don't think we all really understand where a lot

1:00:21.640 --> 1:00:24.600
<v Speaker 1>of stuff comes from or the impact it has. We've

1:00:24.760 --> 1:00:27.160
<v Speaker 1>we've done a lot of stories here at Bloomberg about meat,

1:00:27.320 --> 1:00:29.920
<v Speaker 1>meat production and what it does for the climate and

1:00:30.000 --> 1:00:33.920
<v Speaker 1>the environment. Um, you know, what what do you think

1:00:33.960 --> 1:00:36.200
<v Speaker 1>about in terms of what we need to do though

1:00:36.240 --> 1:00:39.880
<v Speaker 1>to also educate people about food. I mean, we understand

1:00:40.000 --> 1:00:43.320
<v Speaker 1>organic versus not and things like that, but the mass

1:00:43.400 --> 1:00:46.520
<v Speaker 1>production of food, you know, not so much, although we've

1:00:46.520 --> 1:00:47.800
<v Speaker 1>got a glimpse of it, right when all of a

1:00:47.840 --> 1:00:51.840
<v Speaker 1>sudden the supply chain started coming undone during the pandemic. Right.

1:00:52.400 --> 1:00:56.200
<v Speaker 1>You know, one fact that always sticks, um, is when

1:00:56.240 --> 1:01:00.200
<v Speaker 1>you keep it really simple. So for example, creating one

1:01:00.320 --> 1:01:03.080
<v Speaker 1>pound of beef is the equivalent of eight thousand gallons

1:01:03.160 --> 1:01:06.720
<v Speaker 1>of water. So just thinking about these small things that

1:01:07.000 --> 1:01:10.360
<v Speaker 1>you know, just like tidbits of information. And by the way,

1:01:10.560 --> 1:01:13.400
<v Speaker 1>eating a plant based meal eight times a week is

1:01:13.480 --> 1:01:16.160
<v Speaker 1>not so you know, impossible for many people, and in

1:01:16.280 --> 1:01:20.240
<v Speaker 1>fact you feel better and it's less expensive. So there's

1:01:20.240 --> 1:01:22.360
<v Speaker 1>a lot of winds in there for your health, for

1:01:22.440 --> 1:01:25.120
<v Speaker 1>your wallet, for the environment. So if we can just

1:01:25.640 --> 1:01:29.400
<v Speaker 1>look at it like, Okay, I'm not going to commit, Fine,

1:01:29.880 --> 1:01:31.960
<v Speaker 1>maybe you will. You never know. After eight meals, a

1:01:32.000 --> 1:01:33.560
<v Speaker 1>lot of people are like, I'm kind of grossed up

1:01:33.560 --> 1:01:35.840
<v Speaker 1>by me. I don't even need it. Great, But my

1:01:36.120 --> 1:01:39.120
<v Speaker 1>my whole mission is to educate with as much small

1:01:39.280 --> 1:01:43.360
<v Speaker 1>bits of information that would interest the everyday person that's

1:01:43.440 --> 1:01:46.640
<v Speaker 1>not in the environmental world. Because people are living their lives.

1:01:46.680 --> 1:01:48.800
<v Speaker 1>They're busy, they just got to get dinner on the table,

1:01:48.920 --> 1:01:51.280
<v Speaker 1>and they've got work in school and a million other things,

1:01:51.400 --> 1:01:54.960
<v Speaker 1>especially this past year. So um, yeah, this is my

1:01:55.080 --> 1:01:57.080
<v Speaker 1>philosophy that you know, if you can just give small

1:01:57.120 --> 1:01:59.160
<v Speaker 1>bits of info, it's great. What do you think it's

1:01:59.160 --> 1:02:02.760
<v Speaker 1>holding people back the most from doing things? Little things

1:02:02.840 --> 1:02:05.920
<v Speaker 1>like you say, these habits, uh, you change them. If

1:02:06.000 --> 1:02:09.320
<v Speaker 1>everybody starts to change a little habit that's a significant one,

1:02:09.360 --> 1:02:11.760
<v Speaker 1>you can you can kind of alter the outcome of

1:02:11.800 --> 1:02:15.000
<v Speaker 1>our climate. What's holding keep up back? I think people

1:02:15.200 --> 1:02:18.920
<v Speaker 1>just aren't aware that their impact matters. So it's just

1:02:19.160 --> 1:02:21.760
<v Speaker 1>that everyone says I'm just one person. I'm only one person,

1:02:21.880 --> 1:02:23.840
<v Speaker 1>But if we all said that, then nothing would get

1:02:23.880 --> 1:02:26.480
<v Speaker 1>done in the world. So this is an opportunity. Our

1:02:26.520 --> 1:02:29.760
<v Speaker 1>whole website, our whole mission on Habits of Waste dot

1:02:29.840 --> 1:02:32.440
<v Speaker 1>org is really about inspiring people to know you do

1:02:32.720 --> 1:02:35.400
<v Speaker 1>matter and your actions do add up and so and

1:02:35.480 --> 1:02:38.320
<v Speaker 1>then taking away obstacles. So for example, the eight Meals

1:02:38.360 --> 1:02:40.400
<v Speaker 1>app is an opportunity for us to make it really

1:02:40.480 --> 1:02:44.320
<v Speaker 1>easy and fun um and interactive to try you know,

1:02:44.440 --> 1:02:47.760
<v Speaker 1>increasing your plant these meals or cut out cutlery. Ultimately,

1:02:47.840 --> 1:02:51.000
<v Speaker 1>companies want to do the right thing for their consumers

1:02:51.200 --> 1:02:53.960
<v Speaker 1>um and if the consumers speak up and are heard,

1:02:54.360 --> 1:02:57.280
<v Speaker 1>then it's a beautiful synergy. So with again back to

1:02:57.400 --> 1:02:59.880
<v Speaker 1>the you know, cut out Cutlery campaign that we did,

1:03:00.360 --> 1:03:03.480
<v Speaker 1>the applications, you know, they're like these emails, can you

1:03:03.520 --> 1:03:06.480
<v Speaker 1>stop sending them to us? So they're listening. It's not

1:03:06.680 --> 1:03:09.560
<v Speaker 1>it's working. It's just a matter of again not shaming,

1:03:09.760 --> 1:03:12.400
<v Speaker 1>and it's just positive and just understanding that we all,

1:03:12.680 --> 1:03:14.920
<v Speaker 1>we all can make an impact. It's so true, we

1:03:15.040 --> 1:03:18.120
<v Speaker 1>can all make an impact, each and every single one

1:03:18.160 --> 1:03:21.400
<v Speaker 1>of us. That was Sheila Moravati, President and founder of

1:03:21.440 --> 1:03:24.880
<v Speaker 1>Habits of Waste. The nonprofit is focused on reducing environmental footprints.

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<v Speaker 1>Really love her points about doing small things that can

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<v Speaker 1>make a big difference. It's a great way that we

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<v Speaker 1>can think about accomplishing goals too. Right, you can start

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<v Speaker 1>moving the needle, all of us, just a little step

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<v Speaker 1>at a time. Alright. Be sure to check out that

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<v Speaker 1>full conversation. It's in our podcast feed. And that wraps

1:03:39.240 --> 1:03:41.960
<v Speaker 1>up the weekend edition of Bloomberg Business Week from Bloomberg Radio.

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<v Speaker 1>Thanks so much for joining us. I'm Carol Masser and

1:03:44.160 --> 1:03:46.520
<v Speaker 1>I'm Tim Stanivik. Be sure to tune into our Bloomberg

1:03:46.560 --> 1:03:49.080
<v Speaker 1>Business Week daily show Monday through Friday. It starts at

1:03:49.120 --> 1:03:51.400
<v Speaker 1>two pm Wall Street Time on Bloomberg Radio. You can

1:03:51.400 --> 1:03:54.640
<v Speaker 1>also watch our daily broadcast on YouTube just search Bloomberg

1:03:54.680 --> 1:03:57.720
<v Speaker 1>Global News. Also check out our Bloomberg Business Week podcast.

1:03:57.800 --> 1:03:59.720
<v Speaker 1>You can find that at Bloomberg dot com, Apple or

1:03:59.760 --> 1:04:02.200
<v Speaker 1>where ever you get your podcasts. And that's we will

1:04:02.240 --> 1:04:05.320
<v Speaker 1>also find our extra podcast this week. It's Theresa Peyton,

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<v Speaker 1>former White House Chief Information Officer, in fact, the first

1:04:08.040 --> 1:04:10.680
<v Speaker 1>woman to have that position, and CEO at the Cybersecurity

1:04:10.720 --> 1:04:13.439
<v Speaker 1>Advisory and Strategy Firm for a list. It's of course

1:04:13.480 --> 1:04:16.440
<v Speaker 1>timely considering that Bloomberg exclusive on the group of hackers

1:04:16.480 --> 1:04:19.520
<v Speaker 1>who breached a massive trove of security camera data, and

1:04:19.600 --> 1:04:21.720
<v Speaker 1>you can also see me on Bloomberg Quicktake, available at

1:04:21.720 --> 1:04:24.760
<v Speaker 1>Bloomberg dot com, slash Qt and streaming platforms like Roku,

1:04:24.840 --> 1:04:27.880
<v Speaker 1>Apple TV, Samsung TV and more. Bloomberg Business Week, it's

1:04:27.880 --> 1:04:31.360
<v Speaker 1>available on newstands now are special Equality issue also finding

1:04:31.400 --> 1:04:33.920
<v Speaker 1>at Bloomberg dot com and on the Bloomberg Terminal. Have

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<v Speaker 1>a great weekend everyone. This is Bloomberg