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I think that's the issue. Somehow, big companies

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especially in the bureaucratic part of the organization.

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It's not focused on outcomes. It's focused on

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jobs and roles. What do I need? Oh

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I need an Sv of Ai kinda putting

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it off instead of saying, this is the

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outcome, what tasks do I need, what skills

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do I need? How do I match that?

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Welcome to activation your host, Peter Hi. My

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guest today is John Windsor. John is the

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executive in residence at Harvard Business schools laboratory

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for innovation science, which studies, artificial intelligence and

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workforce transformation strategies. He's also founder and chief

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executive officer of open assembly, a company that

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provides content, community, and strategic advising to organizations,

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people and platforms

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to c create the future of work. John

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is also an advisor to the digital initiative

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at Harvard Business School. John Author of several

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books, including beyond the brand, Spark, flipped, and

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the best selling baked in. His most recent

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book is Open talent, leveraging the global crowd

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to solve your biggest challenges. And previously, John

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was the chief innovation officer of the French

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global media

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agency, H, which fired his open advertising agency

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Victories and spoils in 20 15. John welcome

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to techno. It's great to speak with you

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today. Thanks. Thanks for having me. That's a

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great pleasure. Well, let's begin with the... I've

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got a copy of your book here, open

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talent.

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Congratulations on on Thanks. Your latest work. Why

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don't we begin? What what you mean by

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open talent to find that for us if

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you would. Yeah. I mean, I think, you

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know, it it essentially, we tried to come

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up with a a term that really

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really took its seeds from open source software

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that seemed to be, you know, a really

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great place start and and, you know, hands

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open talent. I mean, these strategies have been

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going around for a long time, whether it

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was freelancing

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or it was crowds or the gig economy

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1 of the things we've seen emerge is

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we think, you know, language is really important

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and trying to create a common language and

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common process,

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especially for enterprises to adopt. Right? And and

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1 of the things when we looked around,

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and we've studied this at Harbor for a

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while. 1 of the things that's happened is

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the gig economy really gotten coop opted by,

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you know, B2c services where algorithms are really

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controlling people when they work and how they

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work. And so, you know, I'm a driver

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for Uber. I'm told by an algorithm where

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to go to do my work, and I'm

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told who to work with, so who to

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pick up. And so,

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whereas you know, we look at open talent.

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As really 3 prong. 1 is building an

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external talent cloud, which includes freelancers,

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and and that really, you know, freelancers are

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really higher end, folks that are kind of

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subject matter experts that can really launch in

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and help companies.

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And then building internal talent clouds which are

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how do you kind of capture the cognitive

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surplus of your of your employees and then

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open innovation contests, which is something we've have

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a lot of experience at the labs we

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build all the stuff at Nasa.

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Oh, well, I wanna get into each of

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those and have you kind of provide an

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overview of each. But before we I do,

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I wanna just from a context setting perspective,

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the whole notion of an open talent company

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is something you have a lot of experience

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with. You founded your first version of that,

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I think dating back in the nineties. But

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I should add, you know, wasn't, like, your

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first company, you had worked in traditional settings

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prior to that. So

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at at at a point where the term

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probably was not even coined. It was something

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that occurred to you as a model to

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employ, and I wanna understand what the inspiration

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was for starting your your first open talent

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company.

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I come to the whole study of this

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practice not as somebody trying to figure out

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how to help companies use labor, but how

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do I build an organization with a new

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business model?

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And and think about what does that mean?

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So, you know, it was back when I

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I... My wife was a professional triathlete in

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bolder, and,

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this magazine that Billie Jean King started in

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in the seventies called women's sports and fitness

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was on the market timing kit bought it,

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and they were in the middle of bankrupt

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and they had 40 editors and writers. They

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just couldn't make it good economically. And so

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I had the opportunity to buy that. And

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all these... All my friends, the women athletes

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in Boulder were pushing me to do I

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flew to Nike and Mark Parker at the

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time was a mid level guy and and

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Tinker Hat field. And, you know, I... My

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question was, like, hey. If I'm gonna do

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this, I gotta put all my assets on

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the line. Right? I got mortgage in my

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house. I gotta do all this crazy stuff.

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You think Wim do sports. This is back

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in, like, 86, 87 and Parker was, like,

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yeah. Women are definitely gonna do sports we'll

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support you with a couple ads.

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And so, you know, it's was a huge

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risk for us. And so, you know, it's

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as anybody, And and I always suggest innovation

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always comes from when your back the. Right?

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You have no other course. You've gotta figure

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it out. And so it was obvious before

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I met and, you know, purchase the magazine

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that the paradigm in the publishing industry. There

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were 2 big shifts. 1 was, you know,

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how do I just reduce the number of

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readers to just a core readers leadership. And

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then the other thing was is, how do

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I

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flip the panel. I couldn't afford 40 people

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editorial stuff. So I flipped the paradigm by

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saying, you know, instead of the paradigm of

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a writer from New York who may be

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real in into Yoga, but it never rock

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climb coming to boulder and interviewing Lynn Hill,

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who is 1 of the most prominent, you

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know, rock climber, female rock climber in the

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world. And trying to go back to New

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York and get the story straight. There's just

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this

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propensity to get the story wrong because they

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don't know the Nuances is of what Lin

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talking about. And sometimes Lynn you know, how

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it is if you're subject matter x expert

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you talk in a very ob 2 language

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because you're used to your audience understanding a

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lot of the new nuances. And so we

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flipped the paradigm. I got rid of the

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40 editors and writers, and I hired 2

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former New York editors put them in boulder,

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but I had Lynn write her own story

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and that had editors edit it for the

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audience. Well, that kinda shift from 40 to

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02:38

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people out of the out of the system

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that that cost saved up money that we

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were profitable right away. And so that was

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kind of the first an inkling of that.

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And then 1 of the things that I

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found really interesting after the woman sports and

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Fitness, I sold that to Condo. And so

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I... But 1 of the things that was

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frustrating when I was in the magazine publishing

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businesses is that we worked with these early

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adoptive consumers and is you know in your

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work and innovation and and technology. They're are

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always these kind of early adopters. You know,

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there's

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traditional... Diffusion curve Right? You've got these early

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adoptive consumers that are doing really great stuff,

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and they could really influence the rest of

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the market. And so we put a group

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the women in our readers leadership, not at

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the bottom of the marketing funnel at top

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and charge companies for strategy and product design.

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Using these panels, we would call them, you

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know, crowds or collect ti at the time.

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It was kind of early days of market

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research kind of doing crowds sourced market research.

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And that worked really, really well. We worked

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with Nike and h hp and Intel and,

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you know, a slew of other companies. And

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then I I merged that company with, agency

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called Crisp Porter Bogus, which at the time

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was about you know, there about 75 of

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them, and there were about 14 of us,

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and we merged companies, and we put... I've

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written a few books by then, on c

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creation. So

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we put the idea of c creation. This

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philosophy of, you know, how do we use

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the power of people instead of us being

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the Arrogant experts on creativity, you know, it's

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the mom, you know, who knows how to

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remove spots

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from, you know, her kids outfits, you know,

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that that is probably has a better voice

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on it, What's really going on for hide,

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you know, the laundry church, than we would

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as a bunch of young creative.

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And so we put that, you know, in

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the center of what we did it worked

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really well. We won 3000000000 dollars with the

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business became creative global agency of the decade,

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went from a hundred of us to 1200

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of us in 2 years. And just a

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crazy ride, you know, 1 all these big

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clients Microsoft and Domino's and and Volkswagen. And

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1 of the things It was stressful was

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we couldn't find enough labor to do the

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work. I couldn't find enough creative labor.

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There's just too much, you know, too to

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turn. But what 1 the things we were

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trying to focus on as being innovative, So

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we took on a new client an electric

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motorcycle company called Bra

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and literally frustrated because we can get any

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creative to do the work inside

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So we were... We did the audacious move

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as the newly appointed, you know, newly awarded,

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credit agency of the decade. We decided to

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actually

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crowds source to creative, which pissed off the

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advertising world in a huge way. But 1

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of the things that we noticed

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is that holy crap. Like, the guy we

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interviewed or the woman we entered... You know,

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the guy we interviewed from when you Sydney

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that couldn't come to boulder because of family

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issues or the woman we interviewed, you know,

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in London really wanted to work with us,

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but she couldn't move either. And all of

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a sudden, all these amazing people were doing

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work for us. And it was like, they

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were doing work during the hours that they

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were supposed to be working for somebody else?

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And I was like, this is cool. Like,

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how can we capture the cognitive surplus of

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this industry? Why do we need to move

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people to boulder all the while we know

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that they're gonna leave pretty soon as older

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wasn't a creative hub.

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And it Dawned on us that this whole

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industry is gonna just imp because, you don't

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need, you don't need to have,

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kind of physical

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migration to a place like boulder, you can

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digitally migrate, you know, from my anywhere in

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the world. And so I took that and

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and launched my own company called Victor and

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spoils.

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And

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Became... It was an agency based on crowds

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sourcing principles. It became pretty

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iconic for a couple things. 1 is that

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it was a big challenge to the current

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paradigm.

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But there were really 2 things that shifted

263
00:09:15,303 --> 00:09:17,774
the industry, and that was, you know, Stuart

264
00:09:17,854 --> 00:09:19,644
Elliott who wrote for the new york times

265
00:09:19,944 --> 00:09:21,782
offered as this great opportunity to write an

266
00:09:21,782 --> 00:09:23,859
article about us. And so he wrote an

267
00:09:23,859 --> 00:09:26,177
article, but he said that stipulation was we

268
00:09:26,177 --> 00:09:27,855
couldn't launch the company until the article is

269
00:09:27,855 --> 00:09:30,829
written. And so in in October of 20...

270
00:09:31,069 --> 00:09:32,429
The I guess it was 2009,

271
00:09:32,990 --> 00:09:34,829
we were in my, you know, my garage,

272
00:09:35,069 --> 00:09:36,429
3 of us who started the company.

273
00:09:37,164 --> 00:09:38,682
And a little freaked out running out of

274
00:09:38,682 --> 00:09:40,839
money saying, wow, It thinks is gonna work

275
00:09:40,839 --> 00:09:41,798
and in that morning,

276
00:09:42,597 --> 00:09:44,367
the article appeared in the New York times.

277
00:09:45,082 --> 00:09:47,305
And by that night, 3000 people globally signed

278
00:09:47,305 --> 00:09:49,449
up to work for us. And Dish Network

279
00:09:49,449 --> 00:09:51,752
gave us their hundred and 10000000 dollar advertising

280
00:09:51,752 --> 00:09:54,472
account. So we'd went from 0 to 15000000

281
00:09:54,472 --> 00:09:56,860
dollars in in net revenue in, in about,

282
00:09:57,337 --> 00:09:59,327
12 hours. And so that kind of put

283
00:09:59,327 --> 00:10:01,412
things on app. Right? And and and from

284
00:10:01,412 --> 00:10:03,322
our perspective, you know, it was really exciting.

285
00:10:03,561 --> 00:10:06,028
Got to work. A couple years later, with

286
00:10:06,028 --> 00:10:07,881
a lot of momentum and a lot of

287
00:10:07,938 --> 00:10:10,421
notoriety, We noticed that Harley Day and was

288
00:10:10,421 --> 00:10:12,809
up for review. And we you know, like

289
00:10:12,809 --> 00:10:14,003
anybody else. We wanted to work for Harley,

290
00:10:14,242 --> 00:10:16,232
but we knew by asking for permission to

291
00:10:16,232 --> 00:10:17,029
be in the pitch.

292
00:10:18,078 --> 00:10:19,826
That it wasn't gonna be able to... We

293
00:10:19,826 --> 00:10:21,017
we would never get in there because it,

294
00:10:21,097 --> 00:10:22,685
you know, those pitches are half million dollar

295
00:10:22,685 --> 00:10:24,671
fares and they're it's all about dinners and,

296
00:10:24,751 --> 00:10:26,816
you know, golf games and all these lavish

297
00:10:26,816 --> 00:10:27,213
lunches.

298
00:10:28,023 --> 00:10:30,014
And so my credit director evan fry, you

299
00:10:30,014 --> 00:10:31,367
know, we were at the coffee when we'd

300
00:10:31,367 --> 00:10:32,641
heard the news, and he was like, you

301
00:10:32,641 --> 00:10:34,791
know, instead of asking for permission, Let's ask

302
00:10:34,791 --> 00:10:36,087
for forgiveness. And

303
00:10:36,478 --> 00:10:38,147
ran back to the office and literally in

304
00:10:38,147 --> 00:10:40,452
20 minutes, we, you know, made a video

305
00:10:40,452 --> 00:10:41,963
to our crowd and launched it. And just

306
00:10:41,963 --> 00:10:44,283
said, hey, we're working for harley Davidson and

307
00:10:44,362 --> 00:10:46,107
I'm putting 10000 dollars of my own money

308
00:10:46,107 --> 00:10:47,932
up. Let's do some kick ass work and

309
00:10:47,932 --> 00:10:49,122
see if we can get a meeting to

310
00:10:49,122 --> 00:10:50,812
show up, you know, that this new model

311
00:10:50,867 --> 00:10:53,267
works. And I wrote a blog post to

312
00:10:53,267 --> 00:10:55,176
to Marco Rick a letter to Mark on

313
00:10:55,176 --> 00:10:57,244
my blog. I never met before and just

314
00:10:57,244 --> 00:10:58,755
saying, hey Mark, You know, I enjoy the

315
00:10:58,755 --> 00:11:01,485
dinners and lunches. Super nice people, really creative,

316
00:11:01,725 --> 00:11:04,205
really fun. As you're doing that, I got

317
00:11:04,205 --> 00:11:05,804
10000 people working on your business. Give a

318
00:11:05,804 --> 00:11:06,845
shot if you wanna see something.

319
00:11:07,565 --> 00:11:10,053
And that hit Twitter, And literally, 20 minutes

320
00:11:10,053 --> 00:11:12,758
later, Mark hans wrote me back, saying I'd

321
00:11:12,758 --> 00:11:14,531
love to see the work tired of traditional

322
00:11:14,588 --> 00:11:14,826
agencies.

323
00:11:15,463 --> 00:11:17,293
And 2 weeks later, we went to Milwaukee

324
00:11:17,293 --> 00:11:19,640
and won the glow billion dollar Harley Davidson

325
00:11:19,778 --> 00:11:22,190
work, which blew up the industry. And so

326
00:11:22,408 --> 00:11:23,842
because of that, in the notoriety,

327
00:11:24,400 --> 00:11:26,649
David Jones from Boss, I saw him a

328
00:11:26,649 --> 00:11:28,809
tad, and he said, he came... He approached

329
00:11:28,809 --> 00:11:30,329
me and said, you know, you're you're great

330
00:11:30,329 --> 00:11:32,569
at being controversial and throwing rocks at the

331
00:11:32,569 --> 00:11:34,501
glass houses of the companies why don't you

332
00:11:34,501 --> 00:11:35,937
come in here and help me fix 1.

333
00:11:36,256 --> 00:11:38,329
And so III

334
00:11:38,329 --> 00:11:40,425
decided to sell Victor Spoils to H boss

335
00:11:40,802 --> 00:11:42,876
and become chief Innovation officer out of Paris.

336
00:11:43,529 --> 00:11:44,887
And it was a shit show. You know,

337
00:11:45,047 --> 00:11:47,124
was, like, these guys, you know, they did

338
00:11:47,124 --> 00:11:49,122
not want that French did not wanna let

339
00:11:49,122 --> 00:11:51,134
go of the, you know, the importance of

340
00:11:51,134 --> 00:11:54,254
these amazing creative in Paris. They could not

341
00:11:54,254 --> 00:11:55,294
see some, you know,

342
00:11:55,934 --> 00:11:59,134
home in in in cl Cleveland doing creative

343
00:11:59,134 --> 00:12:00,985
work. It was there you know, is there

344
00:12:00,985 --> 00:12:02,360
identity. Right? And so

345
00:12:03,134 --> 00:12:05,043
although the project didn't go well and David

346
00:12:05,043 --> 00:12:07,192
lost a job that did the the Ceo

347
00:12:07,192 --> 00:12:09,199
and I excited to leave. It was super

348
00:12:09,199 --> 00:12:10,315
interesting and the thing I made it so

349
00:12:10,315 --> 00:12:11,750
interesting was that the 3 guys,

350
00:12:12,548 --> 00:12:13,186
Mike Tu,

351
00:12:13,664 --> 00:12:15,498
Cream Lac connie and and and brought and

352
00:12:15,498 --> 00:12:15,737
on.

353
00:12:16,629 --> 00:12:18,064
Started doing a much case studies on us.

354
00:12:18,223 --> 00:12:20,057
Wrote 1 on pictures and spoils and what

355
00:12:20,057 --> 00:12:21,891
wrote a really big 1, which is still

356
00:12:21,891 --> 00:12:23,485
1 of the best selling case studies at

357
00:12:23,645 --> 00:12:25,894
Harvard 10 years later on on a boss

358
00:12:25,894 --> 00:12:28,929
change faster on. The ability for organizations to

359
00:12:28,929 --> 00:12:30,367
adopt to new business models.

360
00:12:31,006 --> 00:12:32,538
We just, in fact, went back a few

361
00:12:32,538 --> 00:12:34,685
months ago, and they're gonna create a Hp

362
00:12:34,685 --> 00:12:36,833
o, Harvard business school online class on the

363
00:12:37,072 --> 00:12:39,537
Os case study. We did this tenth anniversary

364
00:12:39,537 --> 00:12:41,302
kinda, you know, update of it. But it's

365
00:12:41,302 --> 00:12:44,186
been really interesting to see, you know, how

366
00:12:44,401 --> 00:12:46,626
it's great as an entrepreneur because you're like,

367
00:12:46,864 --> 00:12:48,613
this is awesome. I can, you know, reduce

368
00:12:48,613 --> 00:12:51,097
my cost phenomenally. Can do great work. I

369
00:12:51,097 --> 00:12:52,294
can use these business models.

370
00:12:53,252 --> 00:12:55,647
Yet. It's just so hard for large organizations

371
00:12:55,647 --> 00:12:57,563
to adopt. So that's the stuff we've been

372
00:12:57,563 --> 00:12:59,252
trying to study, and and I went went

373
00:12:59,252 --> 00:13:02,135
to Harvard after the case studies and

374
00:13:02,826 --> 00:13:04,812
started working with the Cream Lac county at

375
00:13:04,812 --> 00:13:06,401
the laboratory for innovation Sciences.

376
00:13:07,369 --> 00:13:08,645
And 1 of the things that they had

377
00:13:08,645 --> 00:13:10,478
done is back in 2007,

378
00:13:11,514 --> 00:13:14,066
Nasa, Jeff Davis, who was the the head

379
00:13:14,066 --> 00:13:16,707
of Health human services the chief medical officer

380
00:13:16,707 --> 00:13:18,613
for Nasa. Had a real problem. He had

381
00:13:18,613 --> 00:13:20,383
a budget cut of 80 percent

382
00:13:20,836 --> 00:13:22,979
for that... The Health and human Services division,

383
00:13:23,058 --> 00:13:24,665
which meant. He only had 20 percent of

384
00:13:24,665 --> 00:13:26,419
the budget to keep astronauts alive in space.

385
00:13:26,737 --> 00:13:28,034
And so he went to cream

386
00:13:28,889 --> 00:13:31,693
that, you know, cream had studied under von

387
00:13:31,773 --> 00:13:34,001
Hip, and then that was the democrat of

388
00:13:34,001 --> 00:13:36,070
innovation, which was really 1 of the foundations

389
00:13:36,070 --> 00:13:37,344
of this whole body of work.

390
00:13:38,219 --> 00:13:39,666
And all of a sudden, we started doing

391
00:13:39,666 --> 00:13:43,000
projects together with Jeff and things accelerated. We

392
00:13:43,000 --> 00:13:43,579
were getting

393
00:13:44,111 --> 00:13:46,493
phenomenal results from people around the world that

394
00:13:46,493 --> 00:13:47,684
wanted to do work for Nasa.

395
00:13:48,493 --> 00:13:51,267
So next year, the center of excellence for

396
00:13:51,267 --> 00:13:53,329
collaborative innovation, which be we bill at Nasa,

397
00:13:53,884 --> 00:13:55,469
we'll have a budget of a billion dollars.

398
00:13:56,039 --> 00:13:58,039
And I think there's something really instructive here

399
00:13:58,039 --> 00:13:59,159
is, like, 1 of the things I point

400
00:13:59,159 --> 00:14:00,519
out in the book is you can have

401
00:14:00,519 --> 00:14:02,039
a mindset. Like, we can look at Nasa.

402
00:14:02,200 --> 00:14:04,360
Right? And we could say, wow, innovative organization

403
00:14:04,360 --> 00:14:06,852
seventeenth thousand full time employees, some of the

404
00:14:06,852 --> 00:14:08,450
most innovative people in the world. Right? That

405
00:14:08,450 --> 00:14:09,968
would be a traditional way of looking at

406
00:14:09,968 --> 00:14:12,126
it. The way Nasa looks at the organization

407
00:14:12,126 --> 00:14:14,700
is they think of themselves a network organization

408
00:14:14,700 --> 00:14:17,659
working with a workforce ecosystem. So because of

409
00:14:17,820 --> 00:14:19,120
C, they have

410
00:14:19,580 --> 00:14:22,711
17000 full time employees, we created some software

411
00:14:22,711 --> 00:14:25,663
called Nasa work that allows them to connect

412
00:14:25,663 --> 00:14:27,360
to their 30000

413
00:14:28,137 --> 00:14:28,536
contractors.

414
00:14:29,189 --> 00:14:29,986
And then C,

415
00:14:30,464 --> 00:14:33,571
the center actually uses 40 other platforms that

416
00:14:33,571 --> 00:14:36,062
tap into a hundred and 10000000 people globally

417
00:14:36,374 --> 00:14:37,810
that are willing to do work for Nasa.

418
00:14:37,970 --> 00:14:39,188
So a network

419
00:14:39,646 --> 00:14:42,518
organization an abundant mindset would be, Nasa has

420
00:14:42,518 --> 00:14:45,725
the ability to work with a hundred 10047000

421
00:14:45,725 --> 00:14:48,117
people to do hard work for them. And

422
00:14:48,117 --> 00:14:50,851
that mindset shift in Inside Nasa's been really

423
00:14:50,989 --> 00:14:52,743
explosive and and and game changing.

424
00:14:53,461 --> 00:14:55,232
But I find it so ironic. Right? I

425
00:14:55,232 --> 00:14:57,068
mean, I think I was on the on

426
00:14:57,068 --> 00:14:59,462
a thread this morning and somebody kind of

427
00:14:59,462 --> 00:15:01,856
included me something on Linkedin, and mister Guy

428
00:15:01,936 --> 00:15:03,728
Ireland trying to protect,

429
00:15:04,345 --> 00:15:06,259
you know, trying to say, freelancing is bad.

430
00:15:06,418 --> 00:15:08,253
You know, why should individuals have the rights

431
00:15:08,253 --> 00:15:10,087
to do work that our great agencies do?

432
00:15:10,247 --> 00:15:11,762
And he's a guy that runs an agency.

433
00:15:12,894 --> 00:15:15,206
The way I responded was, you know, I'm

434
00:15:15,206 --> 00:15:17,359
sure in 2006

435
00:15:17,359 --> 00:15:19,352
and 7, maybe 2008,

436
00:15:19,512 --> 00:15:21,505
there were a bunch of, you know, executives

437
00:15:21,505 --> 00:15:23,831
that published these things called phone books. And

438
00:15:23,831 --> 00:15:26,381
they probably rail against this thing called Google

439
00:15:26,381 --> 00:15:29,329
saying, oh, Google's wrong. It's not right. We

440
00:15:29,329 --> 00:15:31,502
spent years and hundreds of millions of dollars

441
00:15:31,734 --> 00:15:34,292
reading these phone books, and that's the most

442
00:15:34,292 --> 00:15:36,529
authentic way to get the information to define,

443
00:15:36,689 --> 00:15:37,648
say, a,

444
00:15:38,287 --> 00:15:39,965
I don't know, like, a dry cleaners. Right?

445
00:15:40,939 --> 00:15:42,773
Publish once a year. I I found it

446
00:15:42,773 --> 00:15:44,448
interesting when I did some research. Do you

447
00:15:44,448 --> 00:15:47,159
know how much it cost to produce the

448
00:15:47,159 --> 00:15:48,217
2007

449
00:15:48,515 --> 00:15:49,711
yellow pages in Boston?

450
00:15:50,283 --> 00:15:52,114
Hundred million dollars. Mike goodness this. Well, a

451
00:15:52,114 --> 00:15:53,546
hundred million dollars for you and I to

452
00:15:53,546 --> 00:15:55,456
find a dry cleaner. And now now that's

453
00:15:55,456 --> 00:15:57,047
free. Right? That's free on Google.

454
00:15:57,699 --> 00:15:59,455
And and somebody's putting up, you know,

455
00:16:00,173 --> 00:16:02,509
recommendations. You get the latest information. And so

456
00:16:02,887 --> 00:16:04,882
my sense is is every part of every

457
00:16:04,882 --> 00:16:05,781
industry has been

458
00:16:06,411 --> 00:16:08,553
digitally transformed and talent is a place that's

459
00:16:08,553 --> 00:16:10,854
gonna... It's that it's inevitable. Same thing's gonna

460
00:16:10,854 --> 00:16:12,838
happen. You mentioned earlier in your response you

461
00:16:12,838 --> 00:16:15,470
talked about challenges that large organizations have with

462
00:16:15,470 --> 00:16:17,531
with this sort of a model for obvious

463
00:16:17,531 --> 00:16:19,513
reasons. There's already kind of a mode of

464
00:16:19,513 --> 00:16:20,885
work. There's kind of a

465
00:16:21,352 --> 00:16:24,136
a means of continuing to justify the organization

466
00:16:24,136 --> 00:16:25,966
that's already there as opposed to a startup

467
00:16:25,966 --> 00:16:27,636
for instance, that's a couple of people in

468
00:16:27,636 --> 00:16:30,676
a and looking for easy ways to find

469
00:16:30,676 --> 00:16:32,746
creative people on the cheap, for example, if

470
00:16:32,825 --> 00:16:34,599
I may. Overly of.

471
00:16:34,975 --> 00:16:36,901
Push sure describing. You so you but you

472
00:16:36,901 --> 00:16:38,495
talked about it work for Nasa because they

473
00:16:38,495 --> 00:16:40,807
were a network organization. Is that is that

474
00:16:40,807 --> 00:16:41,307
a

475
00:16:41,764 --> 00:16:43,995
necessary ingredient for large organizations to be able

476
00:16:43,995 --> 00:16:45,547
to make work or are there other

477
00:16:45,923 --> 00:16:49,110
versions of large companies or other characteristics that

478
00:16:49,110 --> 00:16:50,624
are put of large companies that would allow

479
00:16:50,624 --> 00:16:51,182
them to do this?

480
00:16:51,994 --> 00:16:53,269
I mean, I think there's a couple things.

481
00:16:53,508 --> 00:16:54,168
1 is

482
00:16:54,863 --> 00:16:56,718
that I think we have to always

483
00:16:57,892 --> 00:16:58,392
ensure

484
00:16:58,849 --> 00:17:01,255
that we have a any organization, has a

485
00:17:01,255 --> 00:17:02,154
customer centric

486
00:17:02,850 --> 00:17:03,350
strategic

487
00:17:03,807 --> 00:17:05,561
mindset. And what I mean by that, and

488
00:17:05,641 --> 00:17:07,155
I look back to my own to my

489
00:17:07,155 --> 00:17:08,112
own history. Right?

490
00:17:09,484 --> 00:17:10,283
Back in the day,

491
00:17:10,922 --> 00:17:12,680
I was just so curious,

492
00:17:13,239 --> 00:17:14,857
like, publishing companies

493
00:17:15,476 --> 00:17:18,040
weren't in the business of providing information to

494
00:17:18,040 --> 00:17:20,264
the audience. It wasn't, like, let's say, fast

495
00:17:20,264 --> 00:17:23,067
company wasn't in the business of providing

496
00:17:23,441 --> 00:17:24,179
the latest

497
00:17:24,632 --> 00:17:25,664
business information.

498
00:17:26,474 --> 00:17:29,428
To their audience. Essentially what transpired was the

499
00:17:29,428 --> 00:17:29,827
editor,

500
00:17:30,466 --> 00:17:32,462
his vision was that. But, you know, soon,

501
00:17:32,861 --> 00:17:34,219
what happens and I think this happens in

502
00:17:34,219 --> 00:17:36,076
every company. The biggest expenses

503
00:17:36,629 --> 00:17:39,269
in this case, putting ink on paper and

504
00:17:39,269 --> 00:17:39,769
distributing

505
00:17:40,149 --> 00:17:40,649
magazines,

506
00:17:41,349 --> 00:17:42,950
those are the things that either make you

507
00:17:42,950 --> 00:17:45,429
or break you profitability from a magazine company.

508
00:17:45,844 --> 00:17:47,838
And so the executives that start running the

509
00:17:47,838 --> 00:17:50,630
company are focused on putting ink on paper

510
00:17:50,630 --> 00:17:52,145
and distributing the magazine.

511
00:17:52,703 --> 00:17:54,937
Nothing to do with satisfying the needs of

512
00:17:54,937 --> 00:17:56,867
the reader that of the editors and the

513
00:17:56,867 --> 00:17:58,384
founders get kinda pushed off to the side.

514
00:17:58,863 --> 00:17:59,842
And I think every

515
00:18:00,300 --> 00:18:02,216
organization gets stuck in that. Right? As time

516
00:18:02,216 --> 00:18:03,732
goes on, there are new ways to do

517
00:18:03,732 --> 00:18:04,531
the same thing.

518
00:18:05,263 --> 00:18:07,959
It's unfortunate. Right? I think when the internet

519
00:18:07,959 --> 00:18:10,021
started, I guess because I was a magazine

520
00:18:10,021 --> 00:18:12,003
publisher and a little bit Tech savvy,

521
00:18:13,210 --> 00:18:16,410
I somehow just assumed that V Magazine was

522
00:18:16,410 --> 00:18:19,289
gonna be innovative and own fashion online.

523
00:18:20,009 --> 00:18:20,250
Yet,

524
00:18:21,064 --> 00:18:23,451
Ko, all they cared about was making an

525
00:18:23,451 --> 00:18:25,998
efficient way of putting ink on paper and

526
00:18:25,998 --> 00:18:28,067
and distributing a fashion magazine.

527
00:18:28,958 --> 00:18:30,413
Instead of being in the information

528
00:18:30,947 --> 00:18:31,447
industry

529
00:18:32,141 --> 00:18:32,641
supplying,

530
00:18:33,017 --> 00:18:34,710
you know, the greatest fashion

531
00:18:35,245 --> 00:18:36,222
information to their customers

532
00:18:36,533 --> 00:18:39,153
However, they decide to buy it or have

533
00:18:39,153 --> 00:18:40,899
the consume it, they were only in the

534
00:18:40,979 --> 00:18:42,884
Magazine business, and they got wiped out by

535
00:18:42,884 --> 00:18:44,130
social media, by,

536
00:18:44,566 --> 00:18:46,154
online things. And I think that's the threat

537
00:18:46,154 --> 00:18:48,560
for every company that you get siloed

538
00:18:49,172 --> 00:18:49,672
into

539
00:18:50,045 --> 00:18:53,063
not trying to deliver, like agencies. Right?

540
00:18:54,031 --> 00:18:54,349
Agencies,

541
00:18:55,222 --> 00:18:56,811
at least what I see now and in

542
00:18:56,811 --> 00:18:58,741
this article this morning with this this this

543
00:18:58,876 --> 00:19:01,339
opinion piece this morning was spot on in

544
00:19:01,339 --> 00:19:03,380
this thinking is that... He's not thinking about

545
00:19:03,419 --> 00:19:04,778
like, how do I best...

546
00:19:05,337 --> 00:19:07,175
Let's forget about the business model. How do

547
00:19:07,335 --> 00:19:08,634
I best deliver

548
00:19:09,093 --> 00:19:09,593
advertising

549
00:19:10,132 --> 00:19:12,564
for the the consumer for my clients

550
00:19:13,022 --> 00:19:13,522
versus

551
00:19:13,900 --> 00:19:16,135
I'm gonna protect my my business model. I've

552
00:19:16,135 --> 00:19:18,290
got this moat and protect this antiquated business

553
00:19:18,290 --> 00:19:20,445
model. It's really hard for organizations to change

554
00:19:20,445 --> 00:19:23,519
that. Very interesting, John. Had classic innovators dilemma

555
00:19:23,579 --> 00:19:25,980
scenario that you're describing there. For sure. And

556
00:19:26,140 --> 00:19:28,115
I wonder how do you think about the

557
00:19:28,234 --> 00:19:29,268
balance between,

558
00:19:29,984 --> 00:19:32,689
internal resources, employees, when to bring on people

559
00:19:32,689 --> 00:19:34,997
full time versus external talents such as the

560
00:19:34,997 --> 00:19:37,638
high end freelancers you were describing, earlier,

561
00:19:38,276 --> 00:19:39,712
how do you think about the balance between

562
00:19:39,712 --> 00:19:41,865
those? What sorts of rules are, you know,

563
00:19:42,025 --> 00:19:44,657
best equipped to have as as permanent employees

564
00:19:44,657 --> 00:19:45,853
versus those that are not?

565
00:19:46,651 --> 00:19:46,890
Yeah.

566
00:19:47,463 --> 00:19:50,167
That's a great question. So III would suggest

567
00:19:50,167 --> 00:19:52,792
that, you know, every... Not just every a

568
00:19:52,792 --> 00:19:54,008
company as was described

569
00:19:54,319 --> 00:19:56,780
you know, becomes protective of their bureaucracy and

570
00:19:56,780 --> 00:19:58,289
their way of doing things, but so did

571
00:19:58,289 --> 00:20:00,909
divisions inside companies. Right? So let's lay out

572
00:20:00,909 --> 00:20:01,806
a scenario

573
00:20:02,434 --> 00:20:04,824
Let's just say, Peter, you were disappointed, you

574
00:20:04,824 --> 00:20:06,974
know, Ceo of a Fortune 500 company. And

575
00:20:06,974 --> 00:20:08,966
it's a technology company, and the board told

576
00:20:08,966 --> 00:20:10,400
you first thing you need to do as

577
00:20:10,400 --> 00:20:11,276
an Ai strategy.

578
00:20:11,849 --> 00:20:13,846
So, you know, there 2 ways to get

579
00:20:13,846 --> 00:20:15,684
that done. Right? The first way, which is

580
00:20:15,684 --> 00:20:17,921
the traditional ways is to say, go to

581
00:20:17,921 --> 00:20:18,661
your C,

582
00:20:19,294 --> 00:20:22,152
and say, I need Of of Ai. Well,

583
00:20:22,391 --> 00:20:23,582
how long do you think it's gonna take

584
00:20:23,582 --> 00:20:25,567
to hire an Sv of Ai today? It's

585
00:20:25,567 --> 00:20:27,488
gonna take 6 to 8 months. Right? A

586
00:20:27,488 --> 00:20:27,807
good 1.

587
00:20:28,523 --> 00:20:30,513
And then you hire her, and she's gonna

588
00:20:30,513 --> 00:20:32,344
take 3 to 4 months to hire her

589
00:20:32,344 --> 00:20:34,334
team, and then it's gonna take 2 to

590
00:20:34,334 --> 00:20:36,583
3 months to set up the processes to

591
00:20:36,583 --> 00:20:38,501
get the strategy done. Then you're talking about

592
00:20:38,501 --> 00:20:40,898
18 months. Now the alternative, if you have

593
00:20:40,898 --> 00:20:43,296
an open talent mindset, you would say,

594
00:20:44,588 --> 00:20:47,696
this... My my my outcome, I need to

595
00:20:47,696 --> 00:20:49,688
have a strategy. Right? And I don't have

596
00:20:49,688 --> 00:20:50,485
the talent house.

597
00:20:51,043 --> 00:20:51,543
So

598
00:20:52,412 --> 00:20:53,230
1 strategy

599
00:20:54,003 --> 00:20:55,832
could be to go to platforms and say,

600
00:20:55,992 --> 00:20:58,060
who are the 10 best people in my

601
00:20:58,060 --> 00:21:00,626
field that our freelance that are around the

602
00:21:00,626 --> 00:21:02,063
world, that I could invite in for the

603
00:21:02,063 --> 00:21:03,361
weekend experts

604
00:21:03,819 --> 00:21:05,176
and sit with my team when we can

605
00:21:05,176 --> 00:21:06,852
do a 2 day strategy and define what

606
00:21:06,852 --> 00:21:08,862
are the a hundred tasks in order to

607
00:21:08,862 --> 00:21:12,051
accomplish that strategy, like that outcome. And in

608
00:21:12,051 --> 00:21:13,806
a weekend, we could say, you know, hey,

609
00:21:14,364 --> 00:21:16,756
Joe manufacturing doesn't know anything about Ai, but

610
00:21:16,756 --> 00:21:18,366
he knows a lot about manufacturing. So I'm

611
00:21:18,366 --> 00:21:19,722
gonna pair him with somebody. And we're gonna

612
00:21:19,722 --> 00:21:21,716
put together and those hundred tasks are to

613
00:21:21,716 --> 00:21:22,354
be assigned.

614
00:21:23,072 --> 00:21:24,906
And within a month, you can create a

615
00:21:24,906 --> 00:21:27,632
pretty good strategy. Right? With that that team.

616
00:21:28,188 --> 00:21:30,518
You know, it's not a great strategy, but

617
00:21:30,575 --> 00:21:32,029
18 months and a great strategy

618
00:21:32,563 --> 00:21:33,541
is gonna be

619
00:21:34,328 --> 00:21:36,152
nonexistent today. Right? And so I I think

620
00:21:36,152 --> 00:21:38,239
that's the issue is that somehow,

621
00:21:39,484 --> 00:21:40,221
big companies

622
00:21:40,673 --> 00:21:42,046
especially have forgotten

623
00:21:42,434 --> 00:21:44,343
But you see the C suite understands it,

624
00:21:44,502 --> 00:21:46,729
but below that, in the bureaucratic part of

625
00:21:46,729 --> 00:21:48,002
their parts of the organization,

626
00:21:48,877 --> 00:21:51,675
it's not focused on outcomes. It's not focused

627
00:21:51,675 --> 00:21:52,550
on outcomes.

628
00:21:53,107 --> 00:21:55,413
It's it's focused on jobs and roles. Like,

629
00:21:55,572 --> 00:21:57,424
what do I need? Oh, I need a

630
00:21:57,893 --> 00:22:00,273
you know, an Sv of of Ai,

631
00:22:00,987 --> 00:22:03,129
let them decide what the role what the

632
00:22:03,129 --> 00:22:05,033
what the what the tasks are, let them

633
00:22:05,033 --> 00:22:06,796
decide what the skills are. Kinda putting it

634
00:22:06,796 --> 00:22:07,751
off instead of saying,

635
00:22:08,547 --> 00:22:10,378
this is the outcome, what tasks do I

636
00:22:10,378 --> 00:22:10,696
need,

637
00:22:11,333 --> 00:22:13,085
what skills do I need? How do I

638
00:22:13,085 --> 00:22:13,562
match that?

639
00:22:14,214 --> 00:22:14,612
The reality,

640
00:22:15,248 --> 00:22:17,397
according to Corn Ferry is that 8... There

641
00:22:17,397 --> 00:22:18,352
85000000

642
00:22:18,352 --> 00:22:20,182
tech jobs that will go filled by 20

643
00:22:20,182 --> 00:22:22,887
30. It's gonna cost companies 8500000000000.0

644
00:22:22,887 --> 00:22:23,126
dollars.

645
00:22:23,698 --> 00:22:25,287
That's gonna get it reduced a lot with

646
00:22:25,446 --> 00:22:27,751
Ai, You know, the speed of which Ai

647
00:22:27,751 --> 00:22:29,818
is growing, but it's still gonna have, you

648
00:22:29,818 --> 00:22:31,328
know, no matter who you are. You can't

649
00:22:31,328 --> 00:22:32,123
hire the best talent.

650
00:22:32,933 --> 00:22:33,967
Just don't wanna work for you, you know,

651
00:22:34,126 --> 00:22:35,637
they have this ability to go do things

652
00:22:35,637 --> 00:22:37,069
that they where they wanna do. So in

653
00:22:37,069 --> 00:22:38,683
that case, if there's this

654
00:22:39,058 --> 00:22:39,558
power

655
00:22:39,948 --> 00:22:42,974
between demand setting the terms to supply the

656
00:22:42,974 --> 00:22:44,248
best supply setting the terms.

657
00:22:46,319 --> 00:22:48,365
In my mind, if you're focused on task

658
00:22:48,802 --> 00:22:51,268
and outcomes, it doesn't matter. If somebody works

659
00:22:51,268 --> 00:22:53,576
for full time or part time, you want

660
00:22:53,576 --> 00:22:55,406
the best talent to get the best outcomes,

661
00:22:55,724 --> 00:22:57,649
and like that's gotta be the focus. Yeah.

662
00:22:57,889 --> 00:22:59,809
Really interesting. I I was

663
00:23:00,289 --> 00:23:02,849
I'm particularly intrigued with your chapter on how

664
00:23:02,849 --> 00:23:05,344
culture matters in an open talent world. I

665
00:23:05,344 --> 00:23:07,502
could say like, a fascinating topic because I

666
00:23:07,502 --> 00:23:09,580
think to the uni unemployed, 1 of the

667
00:23:09,580 --> 00:23:11,418
first things they might think about is what

668
00:23:11,418 --> 00:23:13,336
what John's talking about here is a disaster

669
00:23:13,336 --> 00:23:15,665
from a culture perspective because you know, how

670
00:23:15,665 --> 00:23:17,098
do you even form a culture when you

671
00:23:17,098 --> 00:23:18,213
don't have people that are,

672
00:23:18,770 --> 00:23:20,522
kind of bought in enough to be a

673
00:23:20,522 --> 00:23:23,482
permanent employees of of of a institution? Talk

674
00:23:23,482 --> 00:23:25,626
a bit about your thoughts about culture and

675
00:23:25,626 --> 00:23:27,294
and why it does indeed matter in a

676
00:23:27,294 --> 00:23:28,882
in a in a scenario like what you're

677
00:23:28,882 --> 00:23:29,200
describing?

678
00:23:29,914 --> 00:23:32,138
Yeah. So I I would say anybody that

679
00:23:32,138 --> 00:23:34,710
thinks that there is a... If if you

680
00:23:34,710 --> 00:23:35,669
have more than 1 office,

681
00:23:36,230 --> 00:23:38,309
the thinks that you have a specific culture,

682
00:23:38,950 --> 00:23:41,278
you're being naive. Like, the idea that, you

683
00:23:41,278 --> 00:23:43,825
know, you have 10 offs around the world,

684
00:23:44,302 --> 00:23:46,292
you have 10 different cultures. You know, where

685
00:23:46,292 --> 00:23:47,964
the people are, you know, there there's lots

686
00:23:47,964 --> 00:23:50,128
of different reasons for that. Right? There's in

687
00:23:50,128 --> 00:23:52,198
office culture, there's cultures that people have, you

688
00:23:52,198 --> 00:23:53,551
know, and where they live and what they

689
00:23:53,551 --> 00:23:54,825
do and how they interpret things.

690
00:23:56,099 --> 00:23:57,793
I I believe that the best

691
00:23:58,184 --> 00:24:00,421
work is always an ecosystem. I mean, you

692
00:24:00,421 --> 00:24:02,099
you you represent that. Right? You work on...

693
00:24:02,419 --> 00:24:04,815
You help companies solve their big, you know,

694
00:24:05,468 --> 00:24:07,776
strategy problems with technology and their culture problems.

695
00:24:08,333 --> 00:24:10,799
You're not unemployed full time. They hire you

696
00:24:10,799 --> 00:24:13,424
because you have a unique perspective because you've

697
00:24:13,424 --> 00:24:15,992
had experiences out side of that. But you

698
00:24:15,992 --> 00:24:17,989
are a part of this network. Credit? You're

699
00:24:17,989 --> 00:24:20,146
part of what makes organizations really great.

700
00:24:21,598 --> 00:24:21,996
For me,

701
00:24:22,633 --> 00:24:24,621
I'm a, you know, climber and and surfer,

702
00:24:24,780 --> 00:24:26,530
and I've spent a lifetime doing that. And

703
00:24:26,530 --> 00:24:27,962
so I've worked a lot over the years

704
00:24:27,962 --> 00:24:29,394
with Pat. And I was on the Board

705
00:24:29,394 --> 00:24:31,739
of Directors of black diamond equipment, and

706
00:24:32,114 --> 00:24:35,137
all of those organizations are network organizations and

707
00:24:35,137 --> 00:24:36,727
network cultures. And 1 of the things we

708
00:24:36,727 --> 00:24:37,939
used to do Black Diamond,

709
00:24:39,057 --> 00:24:40,655
Peter Met, the Ceo,

710
00:24:41,054 --> 00:24:42,971
you know, implemented the system that we would

711
00:24:42,971 --> 00:24:45,223
build equipment all week Monday to Friday, and

712
00:24:45,223 --> 00:24:46,502
on Friday and I would have a pizza

713
00:24:46,502 --> 00:24:46,741
party,

714
00:24:47,381 --> 00:24:49,778
and we'd take that all the equipment the

715
00:24:49,778 --> 00:24:51,695
prototypes and we handed it out not just

716
00:24:51,695 --> 00:24:53,548
employees but talk Anybody would show up in

717
00:24:53,548 --> 00:24:54,927
the in Salt lake

718
00:24:55,306 --> 00:24:57,383
to go test equipment, and that weekend can

719
00:24:57,383 --> 00:24:58,901
everybody go out and they would break the

720
00:24:58,901 --> 00:25:01,154
equipment, they would try it. And then Sunday

721
00:25:01,154 --> 00:25:02,835
we'd have a beer party and everybody come

722
00:25:02,835 --> 00:25:05,234
back together and mention like things. So it

723
00:25:05,234 --> 00:25:07,815
was building a community that was much bigger

724
00:25:07,954 --> 00:25:10,207
than call culture. I I think this idea

725
00:25:10,207 --> 00:25:12,844
of there's an internal culture is just wrong.

726
00:25:13,084 --> 00:25:15,181
Like, the the great cultures in the world

727
00:25:15,401 --> 00:25:17,645
are ones that their customers are involved in

728
00:25:17,645 --> 00:25:19,950
the culture, and their are suppliers and there's

729
00:25:19,950 --> 00:25:20,450
this

730
00:25:20,903 --> 00:25:23,526
ecosystem of culture. So for me, and we

731
00:25:23,526 --> 00:25:25,218
call it the book, the network... A network

732
00:25:25,218 --> 00:25:27,535
culture, But I think that's super important to

733
00:25:27,535 --> 00:25:28,035
rethink

734
00:25:28,414 --> 00:25:30,651
what your culture is and bring in outsiders

735
00:25:30,651 --> 00:25:31,391
not just

736
00:25:31,770 --> 00:25:33,884
great freelance talent or

737
00:25:34,985 --> 00:25:38,105
using open innovation tools like contests, but also,

738
00:25:38,345 --> 00:25:39,625
you know, how do we dis fill it

739
00:25:39,625 --> 00:25:41,319
down so that other people can buy in

740
00:25:41,479 --> 00:25:42,996
I mean, Nasa is a great example. Right?

741
00:25:43,155 --> 00:25:43,794
Like, every...

742
00:25:44,273 --> 00:25:45,790
I'm sure you see it too. Every 5

743
00:25:45,790 --> 00:25:47,248
years you're walking through

744
00:25:47,786 --> 00:25:51,790
some fashion, you know, district and some brand

745
00:25:51,790 --> 00:25:54,341
has started to produce Nasa t shirts. And

746
00:25:54,341 --> 00:25:56,732
you're like, wow, the stickiness of the Nasa

747
00:25:56,732 --> 00:25:59,615
logo, the stickiness of the culture like, everybody

748
00:25:59,615 --> 00:26:00,968
wants to be part of that? And and

749
00:26:01,048 --> 00:26:01,866
I would encourage

750
00:26:02,321 --> 00:26:04,948
brands and companies, no matter if they're ABB

751
00:26:04,948 --> 00:26:06,938
or B company. Like, how do you do

752
00:26:06,938 --> 00:26:08,234
that? How do you get customers

753
00:26:08,784 --> 00:26:11,498
to tattoo themselves with your brand, not just

754
00:26:11,498 --> 00:26:14,532
the giveaway away polo shirt. Right? But but

755
00:26:14,532 --> 00:26:17,485
actually say, I love this brand. This represents

756
00:26:17,485 --> 00:26:19,338
me to me, that's a strong culture.

757
00:26:20,856 --> 00:26:22,214
And you've noted the

758
00:26:22,773 --> 00:26:25,170
necessity to focus on outcomes, which I think

759
00:26:25,170 --> 00:26:27,173
again is not the turkey For sure. It

760
00:26:27,173 --> 00:26:29,317
it makes so much sense, of course. But

761
00:26:29,317 --> 00:26:30,984
it it isn't the way the traditional work

762
00:26:30,984 --> 00:26:32,096
is done. I mean, we, we you know,

763
00:26:32,334 --> 00:26:33,604
most people think about you arrive at the

764
00:26:33,604 --> 00:26:35,448
office at a certain time. I would granted

765
00:26:35,448 --> 00:26:37,044
the pandemic has changed a lot of this.

766
00:26:37,283 --> 00:26:38,959
For sure. So the world is actually many

767
00:26:38,959 --> 00:26:41,911
ways moving towards the insights you've you've been

768
00:26:41,911 --> 00:26:44,565
familiar with decades now. But talk a bit

769
00:26:44,565 --> 00:26:47,205
about, you know, the necessary ingredients to be

770
00:26:47,205 --> 00:26:49,765
able to be outcome oriented and and some

771
00:26:49,765 --> 00:26:52,252
of the frankly, cultural shifts that are necessary

772
00:26:52,252 --> 00:26:53,527
in order to to foster that.

773
00:26:54,562 --> 00:26:56,155
Yeah. I I think it starts... You know,

774
00:26:56,315 --> 00:26:58,386
there's a balance. Right? There's a balance between...

775
00:26:58,864 --> 00:26:59,422
First of all,

776
00:27:00,154 --> 00:27:02,152
it... It's a it's a bottom up and

777
00:27:02,152 --> 00:27:04,149
a top down solution. Right? So the first

778
00:27:04,149 --> 00:27:05,667
thing is, and and you you've probably seen

779
00:27:05,667 --> 00:27:08,395
this and I... I'm sure that we're aligned

780
00:27:08,395 --> 00:27:10,464
on this. It's like the current, you know,

781
00:27:10,623 --> 00:27:13,090
argument about Ai. Like, you know, like, yeah.

782
00:27:13,329 --> 00:27:15,318
Ceos can say, no Ai can be used

783
00:27:15,318 --> 00:27:18,042
in the company. But that just isn't reality.

784
00:27:18,202 --> 00:27:20,117
Right? Like, in in a open talent, 1

785
00:27:20,117 --> 00:27:21,395
of the things that we studied at Harvard,

786
00:27:21,554 --> 00:27:23,310
which I thought was super interesting is that

787
00:27:23,310 --> 00:27:25,386
the free freelancer dot com, which is a

788
00:27:25,386 --> 00:27:25,705
platform.

789
00:27:26,278 --> 00:27:28,823
Has only a couple dozen Fortune 500 clients,

790
00:27:29,380 --> 00:27:32,664
yet 70 percent of Fortune 500 companies

791
00:27:33,213 --> 00:27:36,175
have an active corporate email that works weekly

792
00:27:36,231 --> 00:27:38,932
on freelancer dot com. And so, you know,

793
00:27:39,329 --> 00:27:40,679
you can put your head and sand as

794
00:27:40,679 --> 00:27:42,369
a leader and say, you know, these are

795
00:27:42,369 --> 00:27:44,470
my day mandates. This is not gonna happen

796
00:27:44,850 --> 00:27:47,090
all the while. The reality is is your

797
00:27:47,090 --> 00:27:49,009
workers are gonna try to find really good

798
00:27:49,009 --> 00:27:51,343
and efficient ways to make their their jobs

799
00:27:51,343 --> 00:27:51,742
easier.

800
00:27:52,301 --> 00:27:54,456
And so, first of all, it's admitting that.

801
00:27:54,696 --> 00:27:56,691
Right? It's admitting that this is gonna happen.

802
00:27:56,851 --> 00:27:58,926
Like, these innovations happen whether we like it

803
00:27:58,926 --> 00:28:00,778
or not. And we have to be a

804
00:28:00,778 --> 00:28:02,217
part of it. So how are we gonna

805
00:28:02,217 --> 00:28:04,134
adapt to that? And and I I think

806
00:28:04,134 --> 00:28:06,532
that's the the first recognition. The second recognition

807
00:28:06,532 --> 00:28:08,230
is just to start experimenting

808
00:28:08,623 --> 00:28:12,194
I never would recommend whether it's ai or

809
00:28:12,194 --> 00:28:14,813
or it's, you know, open talent to bet

810
00:28:14,813 --> 00:28:17,527
the farm on, you know, let's you know,

811
00:28:17,686 --> 00:28:19,517
let's get rid of everybody and use Ai

812
00:28:19,517 --> 00:28:21,109
tools or let's, you know, get rid of

813
00:28:21,109 --> 00:28:22,065
everybody and use freelancers.

814
00:28:22,940 --> 00:28:24,793
But trying to find small

815
00:28:25,263 --> 00:28:26,876
experiments that are non

816
00:28:27,728 --> 00:28:30,374
risky that are that are kinda not threatening

817
00:28:30,828 --> 00:28:32,577
to get work done. 1 of 1 of

818
00:28:32,577 --> 00:28:33,054
our clients,

819
00:28:33,690 --> 00:28:34,190
Us

820
00:28:34,659 --> 00:28:36,015
who worked with for a long time, You

821
00:28:36,015 --> 00:28:38,089
know, But not Cars got really interested in

822
00:28:38,089 --> 00:28:40,402
the space and was really stoked. And he

823
00:28:40,402 --> 00:28:42,635
found this really interesting place where, you know,

824
00:28:42,795 --> 00:28:44,092
his Hr team

825
00:28:44,644 --> 00:28:47,509
was supposed to put all us data into

826
00:28:47,509 --> 00:28:48,384
the Oracle system.

827
00:28:48,942 --> 00:28:50,533
But over a a couple of years, they've

828
00:28:50,533 --> 00:28:52,259
been just using an excel

829
00:28:52,619 --> 00:28:54,138
spreadsheet. And so there all this data that

830
00:28:54,138 --> 00:28:55,257
was outside their system.

831
00:28:55,896 --> 00:28:57,095
Well, they're trying to figure out what to

832
00:28:57,095 --> 00:28:58,773
do. First of all, you know, V not

833
00:28:58,773 --> 00:29:00,771
kinda mandated that the Hr department do it,

834
00:29:00,931 --> 00:29:02,383
but they're so busy doing their day to

835
00:29:02,383 --> 00:29:03,737
day job that they couldn't get to it.

836
00:29:04,056 --> 00:29:06,525
So Hr department recommended that they use a

837
00:29:06,525 --> 00:29:08,915
consulting firm, and v not got a bid

838
00:29:08,915 --> 00:29:11,146
from the consulting firm for 3 months and

839
00:29:11,146 --> 00:29:12,196
250000

840
00:29:12,196 --> 00:29:13,865
dollars. You know, the reality I I've ever

841
00:29:13,865 --> 00:29:15,852
written a couple states case studies on deloitte

842
00:29:15,852 --> 00:29:17,840
and deloitte, you know, is super upfront. They

843
00:29:17,840 --> 00:29:20,397
charge 5 times their employees salary, and that

844
00:29:20,397 --> 00:29:22,539
pays for the Deloitte brand and the deloitte

845
00:29:22,539 --> 00:29:24,919
offices, and all those things, it's not about

846
00:29:24,919 --> 00:29:27,617
the work. It's about the deloitte brand. Right?

847
00:29:28,108 --> 00:29:30,656
So now there are new matching ways. So

848
00:29:30,736 --> 00:29:33,045
But not went out to great platforms like

849
00:29:33,045 --> 00:29:33,545
graphite,

850
00:29:34,239 --> 00:29:36,642
found 4 people to do the work bid

851
00:29:36,642 --> 00:29:38,869
that out to those 4 people, and they

852
00:29:38,869 --> 00:29:41,335
they put together a bid for 25000 dollars

853
00:29:41,335 --> 00:29:43,140
and 5 days to do the work. So

854
00:29:43,338 --> 00:29:45,329
So you're seeing this, like, can't get it

855
00:29:45,329 --> 00:29:46,125
done with the team,

856
00:29:47,001 --> 00:29:49,150
the the external use of external tools is

857
00:29:49,150 --> 00:29:50,822
it's really expensive and slow.

858
00:29:51,554 --> 00:29:53,304
And you can do it much faster using

859
00:29:53,304 --> 00:29:56,090
freelancers. Now there's a responsibility for fin not.

860
00:29:56,249 --> 00:29:57,681
Right? You can't just hand it over to...

861
00:29:58,000 --> 00:29:59,671
You hand it over to deloitte. You know

862
00:29:59,671 --> 00:30:01,516
that it's gonna get done that they have

863
00:30:01,516 --> 00:30:03,982
your systems, but the not now has a

864
00:30:03,982 --> 00:30:06,130
responsibility to understand what needs to be done,

865
00:30:06,528 --> 00:30:08,855
to understand and, you know, the outcomes to

866
00:30:08,855 --> 00:30:11,735
to own those outcomes. You can't blame, you

867
00:30:11,735 --> 00:30:12,795
know, deloitte

868
00:30:13,095 --> 00:30:14,295
the nets and that's 1 of the things

869
00:30:14,375 --> 00:30:16,709
I think stopped this innovation. Right? A lot

870
00:30:16,709 --> 00:30:18,465
of people wanna a neck to choke to

871
00:30:18,465 --> 00:30:21,121
say, oh, Mckinsey, Those numbers might have been

872
00:30:21,259 --> 00:30:23,654
right, But, you know, I wasn't successful because

873
00:30:23,654 --> 00:30:25,491
they gave us a bad strategy.

874
00:30:26,304 --> 00:30:29,813
Right. Yeah. Very interesting. Very interesting. I wanna

875
00:30:29,813 --> 00:30:31,589
get into you You've mentioned a few different

876
00:30:32,286 --> 00:30:33,961
recommendations you have in your book open talents.

877
00:30:34,280 --> 00:30:36,089
First among them was was building an ink

878
00:30:36,289 --> 00:30:39,006
external talent cloud. Can you just describe what

879
00:30:39,006 --> 00:30:40,124
do you mean by that and the steps

880
00:30:40,124 --> 00:30:42,601
to do so? Yeah. So we start with

881
00:30:42,601 --> 00:30:43,720
the idea of building

882
00:30:44,212 --> 00:30:46,281
building a a center of excellence. And that

883
00:30:46,281 --> 00:30:47,712
could be 1 person that's passionate about it.

884
00:30:47,872 --> 00:30:50,417
That understands the platforms. And I think sorting

885
00:30:50,417 --> 00:30:50,869
out

886
00:30:51,390 --> 00:30:52,210
what platforms

887
00:30:52,750 --> 00:30:55,309
can help you do a great job, you

888
00:30:55,309 --> 00:30:57,309
know, of of solving a problem. A couple

889
00:30:57,309 --> 00:31:00,198
of really interesting places that I'm intrigued with

890
00:31:00,198 --> 00:31:02,112
right now is in a couple platforms.

891
00:31:02,750 --> 00:31:04,823
You know, 1 1 platform that's really interesting

892
00:31:04,823 --> 00:31:06,577
to me is, you know, everybody's looking for

893
00:31:06,657 --> 00:31:08,210
New talent. So that that

894
00:31:08,589 --> 00:31:09,570
everybody's building

895
00:31:10,190 --> 00:31:12,589
their own offices and call center, not call

896
00:31:12,589 --> 00:31:13,630
centers, but but, you know,

897
00:31:14,269 --> 00:31:14,750
workflow centers.

898
00:31:15,323 --> 00:31:17,309
Latin America because there's a lot of good

899
00:31:17,309 --> 00:31:19,295
tech talent down there. Right? And so a

900
00:31:19,295 --> 00:31:22,289
lot of platforms are building, you know, big

901
00:31:22,409 --> 00:31:24,483
big crowds from Latin America, and it's been

902
00:31:24,483 --> 00:31:26,955
really, really successful. But 1 of the companies

903
00:31:26,955 --> 00:31:29,109
that we work with called Mandela, you know,

904
00:31:29,269 --> 00:31:31,342
started. Actually, it's such an interesting story. They

905
00:31:31,342 --> 00:31:31,661
started,

906
00:31:32,394 --> 00:31:35,125
They noticed that there was a a propensity

907
00:31:35,262 --> 00:31:38,130
for African talent to be over indexing on

908
00:31:38,130 --> 00:31:39,347
the ability to learn

909
00:31:39,657 --> 00:31:42,275
computer science skills, software engineering skills. So pre

910
00:31:42,275 --> 00:31:44,416
pandemic, they worked with Soft bank and a

911
00:31:44,416 --> 00:31:47,534
few other large investors and built place based

912
00:31:48,003 --> 00:31:49,996
education center, and they've trained a third of

913
00:31:49,996 --> 00:31:51,191
the African tech talent.

914
00:31:51,749 --> 00:31:53,583
Now coming out of the out of the

915
00:31:53,583 --> 00:31:53,902
pandemic,

916
00:31:54,460 --> 00:31:55,496
they have, you know,

917
00:31:56,147 --> 00:31:59,162
really unique things to to really unique people

918
00:31:59,162 --> 00:32:01,383
to be involved with your business. And have

919
00:32:01,383 --> 00:32:04,333
really become a an open talent platform with

920
00:32:04,333 --> 00:32:05,309
a hundred and 30

921
00:32:05,682 --> 00:32:08,062
countries, but really created a great process. So

922
00:32:08,062 --> 00:32:10,259
when you're looking for talent and not everybody

923
00:32:10,299 --> 00:32:11,890
else is used or, you know, in, you

924
00:32:11,890 --> 00:32:14,276
know, interesting points of view. They're really interesting.

925
00:32:15,151 --> 00:32:16,367
Another probably

926
00:32:16,742 --> 00:32:19,223
more interesting case study right now is there's

927
00:32:19,223 --> 00:32:22,593
a platform called invisible. And invisible launched

928
00:32:22,970 --> 00:32:24,564
a bit ago, maybe 7 years ago, but

929
00:32:24,564 --> 00:32:26,158
in 20 20. They had an interesting insight.

930
00:32:26,317 --> 00:32:28,084
They said, you know, What what would happen

931
00:32:28,084 --> 00:32:29,141
if we aggregated

932
00:32:29,516 --> 00:32:33,653
all the freelance talent for Ai software engineers.

933
00:32:34,464 --> 00:32:37,096
Put together a crowd of 2500 software engineers

934
00:32:37,096 --> 00:32:40,148
that had Ai specific, you know, experience

935
00:32:40,605 --> 00:32:42,998
and sure enough in 20 21, Open, I

936
00:32:42,998 --> 00:32:45,001
called them and then Meta and then and

937
00:32:45,001 --> 00:32:47,403
then Google and then, you know, and then

938
00:32:47,616 --> 00:32:49,042
ant all of the guys,

939
00:32:49,914 --> 00:32:51,394
and it's scaled radically.

940
00:32:51,832 --> 00:32:54,138
They're just growing, you know, doubling every every

941
00:32:54,138 --> 00:32:56,127
couple months. But 1 of the things that's

942
00:32:56,127 --> 00:32:58,593
happened is that invisible has been in building

943
00:32:58,593 --> 00:32:59,649
those Ll m's

944
00:33:00,198 --> 00:33:02,497
and they know that stuff. So they've decided

945
00:33:02,497 --> 00:33:03,949
to create a, a new

946
00:33:04,321 --> 00:33:07,414
process called the process orchestration platform.

947
00:33:08,064 --> 00:33:09,742
And what they'll do, they they work with

948
00:33:09,742 --> 00:33:12,619
large enterprises to go in and to say,

949
00:33:12,858 --> 00:33:14,776
here the task need to be done, let's

950
00:33:14,776 --> 00:33:17,429
atom those tasks. And decide which tests are

951
00:33:17,429 --> 00:33:19,509
best for humans and which tasks are are

952
00:33:19,509 --> 00:33:20,569
best for Ai

953
00:33:21,109 --> 00:33:23,909
to really make you efficient. They've increased the

954
00:33:23,909 --> 00:33:26,002
the, you know, the launch of chat Gp

955
00:33:26,002 --> 00:33:27,837
by 6 months. So they're really into this.

956
00:33:28,076 --> 00:33:31,665
But that's not stuff that any company can

957
00:33:31,665 --> 00:33:33,898
get experience at. Just like, you know, no

958
00:33:33,898 --> 00:33:36,387
company, we just had this Ai conference at

959
00:33:36,546 --> 00:33:38,004
Harvard at d cubed

960
00:33:38,382 --> 00:33:39,898
our big... You know, at the business school,

961
00:33:40,057 --> 00:33:42,132
but our our big initiative called digital design

962
00:33:42,132 --> 00:33:42,611
and data.

963
00:33:43,264 --> 00:33:45,411
And the this president of Wealth Management for

964
00:33:45,888 --> 00:33:47,955
Jpmorgan, you know, she said, hey, we've got

965
00:33:47,955 --> 00:33:48,909
75000

966
00:33:48,909 --> 00:33:49,624
data scientists.

967
00:33:50,260 --> 00:33:52,089
We can't compete with Ll. We're not even

968
00:33:52,089 --> 00:33:53,772
gonna try to do like that. What we're

969
00:33:53,772 --> 00:33:55,993
gonna do is match each 1 of our

970
00:33:55,993 --> 00:33:58,531
data scientists with a with the senior executive

971
00:33:58,531 --> 00:33:59,325
or an executive,

972
00:34:00,134 --> 00:34:03,671
and every executive will sit with a Ai

973
00:34:03,730 --> 00:34:06,687
software engineer all day long, and Ai engineers

974
00:34:06,687 --> 00:34:08,685
is only there to help make them more

975
00:34:08,685 --> 00:34:10,773
efficient. And so, you know, Jamie Diamonds is

976
00:34:10,773 --> 00:34:12,286
not gonna be Jamie Dim anymore. Is gonna

977
00:34:12,286 --> 00:34:14,517
be super Jamie Dim with all these Ai

978
00:34:14,517 --> 00:34:15,712
tools that are gonna be connected.

979
00:34:16,349 --> 00:34:17,885
But I think those are areas

980
00:34:19,152 --> 00:34:20,903
that no matter who we are as a

981
00:34:20,903 --> 00:34:22,279
company, we can't

982
00:34:22,655 --> 00:34:24,804
be fast enough in this area. We can't

983
00:34:24,804 --> 00:34:26,316
get the knowledge. We can't get the people.

984
00:34:26,555 --> 00:34:28,226
We have to use outside resources.

985
00:34:28,799 --> 00:34:30,235
People that have done this a lot. And

986
00:34:30,235 --> 00:34:32,787
so, you know, freelance is certainly a really

987
00:34:32,787 --> 00:34:35,419
important thing. So building an external tale cloud

988
00:34:35,419 --> 00:34:38,051
would start with connecting with a few really

989
00:34:38,051 --> 00:34:40,625
good platform right? Either invisible or in other

990
00:34:40,625 --> 00:34:41,684
cases, Mandela

991
00:34:42,224 --> 00:34:43,744
and being able to tap into kind of

992
00:34:43,744 --> 00:34:46,385
this higher end, you know, subject matter expert

993
00:34:46,385 --> 00:34:47,664
to really accelerate things.

994
00:34:48,477 --> 00:34:48,953
Recently,

995
00:34:49,350 --> 00:34:51,334
a couple weeks ago Ron stat bought torque,

996
00:34:51,652 --> 00:34:53,477
and 1 of the things they've noticed, so

997
00:34:53,477 --> 00:34:54,771
to a a technical,

998
00:34:55,144 --> 00:34:56,194
you know, crowd,

999
00:34:57,313 --> 00:34:58,112
freelance platform.

1000
00:34:58,831 --> 00:35:00,909
And the president of of Ron was really

1001
00:35:00,909 --> 00:35:02,827
clear the Us president of Ron set. He

1002
00:35:02,827 --> 00:35:04,105
said, you know, the reason we're doing it

1003
00:35:04,105 --> 00:35:06,265
is that our margins and staffing industry really

1004
00:35:06,265 --> 00:35:08,409
shitty and we expect we're gonna put everybody.

1005
00:35:09,045 --> 00:35:11,347
We're gonna change radically change our organization and

1006
00:35:11,347 --> 00:35:13,356
put everybody in Ron digital

1007
00:35:13,904 --> 00:35:15,122
onto the torque platform.

1008
00:35:15,899 --> 00:35:17,197
And currently,

1009
00:35:17,654 --> 00:35:19,750
when we have a client call, it takes

1010
00:35:19,968 --> 00:35:20,867
60 days

1011
00:35:21,338 --> 00:35:22,554
to go through the process

1012
00:35:23,166 --> 00:35:25,311
and to be able to deploy talent to

1013
00:35:25,311 --> 00:35:27,456
somebody with all the analog process. You have,

1014
00:35:27,536 --> 00:35:27,774
you know,

1015
00:35:28,583 --> 00:35:30,492
Here's the brief. It goes out to a

1016
00:35:30,492 --> 00:35:33,036
hundred recruiters, A hundred recruiters compete against each

1017
00:35:33,036 --> 00:35:34,309
other to find the right talents.

1018
00:35:34,866 --> 00:35:36,059
It takes a while.

1019
00:35:36,949 --> 00:35:38,222
Torque can do that same work in 2

1020
00:35:38,222 --> 00:35:40,608
hours because they have this crowd of people

1021
00:35:40,608 --> 00:35:43,177
ready to go ready to work, digitally defined

1022
00:35:43,313 --> 00:35:44,984
ability to interview. And so those are the

1023
00:35:44,984 --> 00:35:46,594
kind of the radical shifts that you need

1024
00:35:46,594 --> 00:35:47,872
to do. But you can't get from here

1025
00:35:47,872 --> 00:35:48,532
to there

1026
00:35:48,911 --> 00:35:52,527
without employing either acquiring those companies or crime

1027
00:35:52,586 --> 00:35:55,636
acquiring those kind of relationships. Yeah. Super interesting.

1028
00:35:56,034 --> 00:35:56,353
And,

1029
00:35:56,912 --> 00:35:58,906
a complement to that, which you alluded to

1030
00:35:58,906 --> 00:36:01,240
is, building an internal talent marketplace.

1031
00:36:01,777 --> 00:36:03,213
To talk talk a bit about how those

1032
00:36:03,213 --> 00:36:03,692
work together.

1033
00:36:04,583 --> 00:36:06,495
I think that's really critical. Right? In our

1034
00:36:06,495 --> 00:36:07,849
in our work with Nasa, 1 of my

1035
00:36:07,849 --> 00:36:08,349
favorite

1036
00:36:08,805 --> 00:36:09,305
examples

1037
00:36:10,398 --> 00:36:13,999
in our Nasa work platform was that A

1038
00:36:13,999 --> 00:36:17,295
guy had just gotten commissioned or AAAA

1039
00:36:17,355 --> 00:36:20,471
budget for 5000000 dollars, 1 of the engineers

1040
00:36:20,471 --> 00:36:20,950
inside Nasa,

1041
00:36:21,604 --> 00:36:23,119
And the project that he got the budget

1042
00:36:23,119 --> 00:36:26,649
on was to figure out how do

1043
00:36:27,185 --> 00:36:27,685
detect

1044
00:36:28,222 --> 00:36:31,027
dehydration inside a space suit So it's gotta

1045
00:36:31,027 --> 00:36:33,101
be... You know, you got somebody out outside

1046
00:36:33,101 --> 00:36:35,732
of the space station, they, you know, whatever

1047
00:36:35,732 --> 00:36:37,806
they they they they pee in their system.

1048
00:36:38,204 --> 00:36:40,850
But is he dehydrated easy he not. Nobody

1049
00:36:40,850 --> 00:36:43,001
ever knew. Right? Nobody could could analyze that.

1050
00:36:43,559 --> 00:36:44,913
And so that was the project he was

1051
00:36:44,913 --> 00:36:46,427
working on. The idea of how do we

1052
00:36:46,427 --> 00:36:48,817
digitally separate these kinds of 2 different liquids.

1053
00:36:49,629 --> 00:36:51,302
He put that question up after he got

1054
00:36:51,302 --> 00:36:53,213
the budget, he put that question up on

1055
00:36:53,213 --> 00:36:54,647
the internal talent marketplace.

1056
00:36:55,046 --> 00:36:57,117
And loan behold, somebody else in Nasa had

1057
00:36:57,117 --> 00:36:58,630
been doing a project for a few years

1058
00:36:58,630 --> 00:37:01,125
of separating digitally separating 2 different kinds of

1059
00:37:01,125 --> 00:37:03,525
liquids and analyzing their content.

1060
00:37:04,085 --> 00:37:06,219
And using those principles, he was able to

1061
00:37:06,418 --> 00:37:08,564
accelerate 3 or 4 years worth of research

1062
00:37:08,564 --> 00:37:10,312
and 5000000 dollars of budget. He didn't need

1063
00:37:10,312 --> 00:37:12,536
to use a budget budget. He could solve

1064
00:37:12,536 --> 00:37:13,093
that problem.

1065
00:37:13,904 --> 00:37:15,502
I would suggest that this points to the

1066
00:37:15,502 --> 00:37:19,337
fact that most large organizations have probably somewhere

1067
00:37:19,337 --> 00:37:21,349
in your organization have probably figured out a

1068
00:37:21,349 --> 00:37:23,340
problem or a solution to the problem you're

1069
00:37:23,340 --> 00:37:26,048
working on. Yet because of bad communications of

1070
00:37:26,048 --> 00:37:27,800
relying on email or even Slack,

1071
00:37:28,358 --> 00:37:30,292
it's really hard to get that. And so

1072
00:37:30,524 --> 00:37:32,360
The question is, how do we capture the

1073
00:37:32,360 --> 00:37:33,498
cognitive surplus

1074
00:37:34,195 --> 00:37:36,590
of an organization? I would say, let's forget

1075
00:37:36,590 --> 00:37:38,998
about the external tale clouds for now. Right?

1076
00:37:39,157 --> 00:37:41,065
Like, where are the people in there that

1077
00:37:41,065 --> 00:37:43,292
maybe, you know, maybe he's a marketing guy

1078
00:37:43,292 --> 00:37:44,485
or she's a marketing person?

1079
00:37:45,041 --> 00:37:47,824
And and at night, she's gotten certified on

1080
00:37:47,904 --> 00:37:50,464
Google Ai training, and she's gotten, you know,

1081
00:37:50,782 --> 00:37:52,213
she's had 2 or 3 months of that.

1082
00:37:52,849 --> 00:37:56,110
Yet, there's no opportunity inside the organization for

1083
00:37:56,110 --> 00:37:58,416
most organizations to actually cross poll.

1084
00:37:59,229 --> 00:38:01,146
Gl a great example of a platform that

1085
00:38:01,146 --> 00:38:03,144
allows, you know, that not only ups skill

1086
00:38:03,144 --> 00:38:05,142
to be able to get new skills, but

1087
00:38:05,142 --> 00:38:06,740
also that idea that, you know,

1088
00:38:07,553 --> 00:38:09,619
you, Peter could say, I wanna, you know,

1089
00:38:09,778 --> 00:38:11,129
be in the Ai space. That's what I

1090
00:38:11,129 --> 00:38:12,878
wanna do with my career. Oh, look, there's

1091
00:38:12,878 --> 00:38:14,864
are some projects with my marketing experience that

1092
00:38:15,023 --> 00:38:15,898
I can kinda help out.

1093
00:38:16,469 --> 00:38:17,902
On my off hours to be able to

1094
00:38:17,902 --> 00:38:19,357
do that. I think that's a huge

1095
00:38:19,812 --> 00:38:19,971
acceleration.

1096
00:38:20,926 --> 00:38:22,358
Really great overview of that as well. And

1097
00:38:22,358 --> 00:38:26,282
then you, finally noted open innovation contests as

1098
00:38:26,282 --> 00:38:28,519
an important ingredient as well. Again, talk about

1099
00:38:28,519 --> 00:38:30,277
those if you would. I mean, I think

1100
00:38:30,277 --> 00:38:31,715
for a lot of companies that's terrifying. Right?

1101
00:38:31,875 --> 00:38:34,539
The idea that we built our identity on

1102
00:38:34,755 --> 00:38:37,379
the quality of our work or expertise and

1103
00:38:37,379 --> 00:38:38,492
my career built on it.

1104
00:38:39,208 --> 00:38:41,037
I mean, 1 of the more fascinating things

1105
00:38:41,037 --> 00:38:42,284
that happened at at Lyft

1106
00:38:43,118 --> 00:38:44,706
was that the Harvard Medical school called us,

1107
00:38:44,865 --> 00:38:45,898
and they had been doing a thing with

1108
00:38:46,056 --> 00:38:46,771
Broad Institute,

1109
00:38:47,803 --> 00:38:50,130
to think about new ways to sequence

1110
00:38:50,599 --> 00:38:51,318
some Dna.

1111
00:38:51,957 --> 00:38:54,354
And a abroad had spent a couple decades,

1112
00:38:54,993 --> 00:38:56,910
over a hundred million dollars to get this

1113
00:38:56,910 --> 00:38:59,157
kind of you know, ability to sequence this

1114
00:38:59,237 --> 00:39:01,489
Dna in 5 and a half minutes. Huge

1115
00:39:01,547 --> 00:39:03,618
success. Right? The guys who did it are

1116
00:39:03,618 --> 00:39:04,436
world famous

1117
00:39:05,131 --> 00:39:06,428
amazing. And so

1118
00:39:06,979 --> 00:39:08,813
came to us and we just... We're curious

1119
00:39:08,893 --> 00:39:10,249
We were say, wow. What happens if we

1120
00:39:10,249 --> 00:39:11,387
just did an open contest

1121
00:39:12,083 --> 00:39:14,476
in 1 month. Right? Put the prize money

1122
00:39:14,476 --> 00:39:15,513
at 35000

1123
00:39:15,513 --> 00:39:17,682
dollars. Let's do it in a collaborative way

1124
00:39:17,682 --> 00:39:20,074
where we invite people in, they get into

1125
00:39:20,074 --> 00:39:21,931
the contest by actually

1126
00:39:22,547 --> 00:39:23,765
proposing an algorithm

1127
00:39:24,222 --> 00:39:26,158
that tested to a certain level

1128
00:39:26,869 --> 00:39:29,530
And then once they're in, a certain level

1129
00:39:29,909 --> 00:39:30,869
compared to the standard.

1130
00:39:31,429 --> 00:39:33,510
Once they're in, then then everybody gets to

1131
00:39:33,510 --> 00:39:35,690
see the algorithms and it's a collaborative

1132
00:39:36,004 --> 00:39:38,002
project with 80 people across the globe to

1133
00:39:38,002 --> 00:39:39,681
see how fast they can build on each

1134
00:39:39,681 --> 00:39:41,679
other. Right? Well, the guys have probe were,

1135
00:39:41,759 --> 00:39:43,037
like, theirs is no way, and we spent

1136
00:39:43,037 --> 00:39:44,715
a hundred million dollars and 3 decades doing

1137
00:39:44,715 --> 00:39:46,407
where the smartest guys in There's no way

1138
00:39:46,407 --> 00:39:48,238
this will lower happen. Well, you know, their

1139
00:39:48,238 --> 00:39:49,831
standard was... Not only does it have to

1140
00:39:49,831 --> 00:39:52,300
beat the benchmark of their algorithm it had

1141
00:39:52,300 --> 00:39:53,734
to be 10 percent better to get in

1142
00:39:53,734 --> 00:39:54,291
the contest.

1143
00:39:54,864 --> 00:39:56,218
How long do you think it took for

1144
00:39:56,218 --> 00:39:58,926
somebody outside to beat their algorithm? Very rapidly.

1145
00:39:59,165 --> 00:40:02,510
24 hours. 24 hours. Yeah. But the crazy

1146
00:40:02,510 --> 00:40:04,199
thing was is the 80 folks that that

1147
00:40:04,199 --> 00:40:05,258
they gone in the contest

1148
00:40:05,636 --> 00:40:08,191
by iterating and and and being, you know,

1149
00:40:08,430 --> 00:40:09,468
psyche to do it And what we find

1150
00:40:09,468 --> 00:40:11,145
in the Nasa work. Right? There's 3 reasons

1151
00:40:11,145 --> 00:40:13,675
that people play open innovation platforms. 1 is

1152
00:40:14,112 --> 00:40:16,182
for the for the money. Right? But also

1153
00:40:16,182 --> 00:40:18,514
for the glory, like, I solved an algorithm

1154
00:40:18,651 --> 00:40:19,208
for broad.

1155
00:40:20,005 --> 00:40:22,130
And also for the for the guts, like

1156
00:40:22,249 --> 00:40:23,389
can I compete

1157
00:40:23,927 --> 00:40:24,407
with this?

1158
00:40:25,365 --> 00:40:27,523
And so over the next 3 weeks, this

1159
00:40:27,523 --> 00:40:30,652
crowd did the did the work guess how

1160
00:40:30,652 --> 00:40:33,677
fast the the the sequencing happened by a

1161
00:40:33,677 --> 00:40:35,451
guy out of Poland. Minutes

1162
00:40:36,066 --> 00:40:38,349
14 seconds. From 5 and a half minutes

1163
00:40:38,549 --> 00:40:41,181
14 seconds and the top 25 algorithms were

1164
00:40:41,181 --> 00:40:43,891
all under 30 seconds. My goodness. And so

1165
00:40:43,891 --> 00:40:46,204
if you're looking to solve really hard problems,

1166
00:40:46,842 --> 00:40:47,342
Unfortunately,

1167
00:40:48,130 --> 00:40:50,431
what I've seen And III bet you've seen

1168
00:40:50,431 --> 00:40:52,415
the same thing, it is that when companies

1169
00:40:52,415 --> 00:40:54,081
run into really hard problems,

1170
00:40:55,049 --> 00:40:56,244
they tend to start putting them on the

1171
00:40:56,244 --> 00:40:58,632
back burner. Oh, spent tens of millions of

1172
00:40:58,632 --> 00:41:00,225
dollars on that. We can't figure it out.

1173
00:41:00,703 --> 00:41:02,614
We've got more pressing things. That's not a

1174
00:41:02,614 --> 00:41:03,012
big deal.

1175
00:41:03,744 --> 00:41:05,578
Our suggestion always is to let... Let's pull

1176
00:41:05,578 --> 00:41:07,493
those out of the warehouse or out of

1177
00:41:07,493 --> 00:41:09,486
the closet and start giving those over to

1178
00:41:09,486 --> 00:41:11,002
contest to see if people can't kinda push

1179
00:41:11,002 --> 00:41:12,836
them along. And what we find is it's

1180
00:41:12,836 --> 00:41:15,235
it's not the fact that there are smarter

1181
00:41:15,235 --> 00:41:17,140
people outside your company. It's the fact that

1182
00:41:17,140 --> 00:41:19,703
a lot of those folks have adjacent knowledge

1183
00:41:19,838 --> 00:41:22,476
that your experts didn't even know existed because

1184
00:41:22,476 --> 00:41:23,670
it's not what they do.

1185
00:41:24,306 --> 00:41:26,853
The guy that solved the Rodents institute problem.

1186
00:41:27,410 --> 00:41:28,228
He is

1187
00:41:28,619 --> 00:41:30,533
he is a mathematician. He solved a lot

1188
00:41:30,533 --> 00:41:31,410
of problems for us.

1189
00:41:32,287 --> 00:41:34,201
Made a lot of money. But he's never

1190
00:41:34,201 --> 00:41:37,173
done a Dna sequencing or any biological

1191
00:41:38,044 --> 00:41:39,710
problem at all. It's just they had such

1192
00:41:39,710 --> 00:41:41,456
a different perspective on how to look at

1193
00:41:41,456 --> 00:41:43,203
the problem. He's able to solve it, and

1194
00:41:43,361 --> 00:41:45,290
I would suggest that every company has

1195
00:41:45,838 --> 00:41:48,305
intra problems that they cannot solve and they

1196
00:41:48,305 --> 00:41:51,909
need that adjacent knowledge and open innovation capabilities

1197
00:41:52,046 --> 00:41:53,797
allow you to think about things in a

1198
00:41:53,797 --> 00:41:54,434
in a new way.

1199
00:41:55,404 --> 00:41:57,956
Or are there, like, platforms that you would

1200
00:41:57,956 --> 00:42:00,987
recommend using or what? Yeah. Yeah. So W

1201
00:42:00,987 --> 00:42:03,300
is a really amazing platform. They focus on

1202
00:42:03,300 --> 00:42:03,800
the

1203
00:42:04,257 --> 00:42:04,896
innovation space.

1204
00:42:05,389 --> 00:42:07,936
So do innovation consulting, but they bought a

1205
00:42:07,936 --> 00:42:10,426
platform called innocent, which is 1 of the

1206
00:42:10,563 --> 00:42:12,393
grand daddy's of the space, and they... It's...

1207
00:42:12,632 --> 00:42:14,383
And it's in incentives done more work than

1208
00:42:14,383 --> 00:42:16,543
new anybody. A few others, but those guys

1209
00:42:16,543 --> 00:42:18,606
are, you know, the best. The problem with

1210
00:42:18,606 --> 00:42:21,384
these open innovation platforms that we've seen are

1211
00:42:21,384 --> 00:42:23,230
great platforms come along like C,

1212
00:42:23,710 --> 00:42:26,190
and then C gets bought by Google and

1213
00:42:26,349 --> 00:42:28,349
Google takes up a hundred percent of their

1214
00:42:28,349 --> 00:42:30,349
capacity. So C still round,

1215
00:42:31,084 --> 00:42:33,068
they still do amazing work. They have an

1216
00:42:33,068 --> 00:42:35,371
amazing community that does that work. It's just

1217
00:42:35,371 --> 00:42:37,038
a hundred percent of their capacity taken up

1218
00:42:37,038 --> 00:42:39,840
by Google. That makes sense. So we've talked

1219
00:42:39,840 --> 00:42:42,239
about Ai in for variety of different ways.

1220
00:42:42,559 --> 00:42:44,800
I I wanna kind of more squarely talk

1221
00:42:44,800 --> 00:42:46,960
about artificial intelligence and the role, you see

1222
00:42:46,960 --> 00:42:49,153
it playing. It sounds as though you're you're

1223
00:42:49,212 --> 00:42:51,370
largely an opt optimistic relative to the to

1224
00:42:51,370 --> 00:42:54,087
the the topic. You certainly see the necessity

1225
00:42:54,087 --> 00:42:56,739
for companies to delve into it. Rather than

1226
00:42:56,739 --> 00:42:56,979
to,

1227
00:42:57,858 --> 00:42:59,056
stick their heads in the sand as you

1228
00:42:59,056 --> 00:43:02,092
noted. Talk about how your own experience with

1229
00:43:02,092 --> 00:43:04,545
it has informed what you think the future

1230
00:43:04,743 --> 00:43:08,635
of these these work models are with, enhanced

1231
00:43:08,635 --> 00:43:10,065
with artificial intelligence.

1232
00:43:10,938 --> 00:43:13,338
It's interesting. Right? I I so I played

1233
00:43:13,338 --> 00:43:14,855
just like you, you know, played a lot

1234
00:43:14,855 --> 00:43:16,132
with it. I'm, 1 the things that I

1235
00:43:16,291 --> 00:43:18,526
I found pretty profound was that I took

1236
00:43:18,526 --> 00:43:21,021
all my my manuscript, all my writing

1237
00:43:21,334 --> 00:43:23,191
and put into its own Gp.

1238
00:43:23,728 --> 00:43:25,164
And then when somebody asks me a question

1239
00:43:25,164 --> 00:43:26,760
of, like, what are the 3 ways to

1240
00:43:26,760 --> 00:43:28,889
build an external tale cloud, I just go

1241
00:43:29,010 --> 00:43:31,010
to my tool and it builds that for

1242
00:43:31,010 --> 00:43:33,250
me. And so, and, it's based on my

1243
00:43:33,250 --> 00:43:34,609
information. And I can do that. I I've

1244
00:43:34,609 --> 00:43:35,989
actually written a few articles

1245
00:43:36,624 --> 00:43:39,088
or B not telling Hp that I've used

1246
00:43:39,088 --> 00:43:41,076
the Ai to build it and it's slid

1247
00:43:41,076 --> 00:43:43,064
right through and they're like. This is amazing.

1248
00:43:43,302 --> 00:43:44,257
What a great article.

1249
00:43:44,749 --> 00:43:46,427
And so I think that that's just the

1250
00:43:46,427 --> 00:43:48,664
reality. Like, it it to me,

1251
00:43:49,862 --> 00:43:51,300
you know, I I love this image that

1252
00:43:51,300 --> 00:43:52,751
you probably saw on the book. There's in

1253
00:43:52,751 --> 00:43:53,626
in 1900,

1254
00:43:53,785 --> 00:43:56,092
there was a picture of, you know, fifth

1255
00:43:56,172 --> 00:43:56,672
Avenue

1256
00:43:57,444 --> 00:44:00,402
across way, on Fifth Avenue. An intersection, and

1257
00:44:00,402 --> 00:44:03,107
there were all horses, you know, just jammed

1258
00:44:03,107 --> 00:44:04,460
packed with horses in 1 car.

1259
00:44:05,096 --> 00:44:07,800
And literally, 13 years later, that same intersection

1260
00:44:07,800 --> 00:44:09,810
was packed with cars and 1 horse.

1261
00:44:10,449 --> 00:44:11,805
And I think that's what we're talking about

1262
00:44:11,805 --> 00:44:13,481
here. Right? If you were a buggy with

1263
00:44:13,481 --> 00:44:13,880
manufacturer,

1264
00:44:14,359 --> 00:44:16,846
you could rail all day long off on

1265
00:44:16,846 --> 00:44:18,833
the fact that, you know, cars are unsafe.

1266
00:44:18,992 --> 00:44:21,537
They're dangerous. They're horrible. In fact, if you

1267
00:44:21,537 --> 00:44:22,730
look back in history, 1 the things that

1268
00:44:22,809 --> 00:44:23,922
I find super interesting.

1269
00:44:25,036 --> 00:44:25,775
Is theirs

1270
00:44:26,244 --> 00:44:29,195
there were some laws in Massachusetts that I

1271
00:44:29,195 --> 00:44:32,066
found, you know, crazy. 1 was if you

1272
00:44:32,066 --> 00:44:33,581
owned an automobile, and you came to an

1273
00:44:33,581 --> 00:44:34,697
intersection. You had to get out of the

1274
00:44:34,697 --> 00:44:36,546
car as a driver with flags,

1275
00:44:37,104 --> 00:44:38,938
get all of the animals to stop, and

1276
00:44:38,938 --> 00:44:40,691
then you could proceed through. That was the

1277
00:44:40,691 --> 00:44:43,242
first 1. The crazier 1 was if you

1278
00:44:43,242 --> 00:44:44,771
see an animal, and you're driving on the

1279
00:44:44,771 --> 00:44:47,160
road, you have to stop and dis assemble

1280
00:44:47,160 --> 00:44:49,868
your automobile hide it behind a tree. And

1281
00:44:49,868 --> 00:44:51,142
then when the coat is clear, you could

1282
00:44:51,142 --> 00:44:52,655
come back on the road and re assemble

1283
00:44:52,655 --> 00:44:54,264
it. I think that's a little bit what's

1284
00:44:54,264 --> 00:44:55,937
happening. Right? Is I think that there's a

1285
00:44:55,937 --> 00:44:58,725
lot of Ais in reality. It's gonna happen.

1286
00:44:59,203 --> 00:45:01,195
Either we engage with it and decide what's

1287
00:45:01,195 --> 00:45:03,204
good and bad. How do we put some

1288
00:45:03,204 --> 00:45:05,605
guard rails on it, or we can stand

1289
00:45:05,605 --> 00:45:08,005
on the sidelines and complain about it, but

1290
00:45:08,005 --> 00:45:09,844
that's not gonna get us anywhere. And I

1291
00:45:09,844 --> 00:45:11,844
think it's gonna be an incredibly powerful tool.

1292
00:45:12,179 --> 00:45:13,775
Who knows what the outcome gonna be. I

1293
00:45:13,775 --> 00:45:15,311
think we have to figure out

1294
00:45:16,486 --> 00:45:18,241
who should we follow and 1 of the

1295
00:45:18,241 --> 00:45:19,836
people I follow a lot is Ethan Male,

1296
00:45:19,916 --> 00:45:21,431
who's, you know, wrote a book on c

1297
00:45:21,431 --> 00:45:23,202
intelligence and, you know is right at the

1298
00:45:23,202 --> 00:45:25,116
top of the game. And it's it's super

1299
00:45:25,116 --> 00:45:26,951
fascinating name space. I think it's gonna be

1300
00:45:26,951 --> 00:45:28,627
profound Right? And I think that it's gonna

1301
00:45:28,627 --> 00:45:30,636
cause a lot of big cultural shifts.

1302
00:45:31,354 --> 00:45:33,906
My sense is is that even the sense

1303
00:45:33,906 --> 00:45:36,719
of what work is and our identities as

1304
00:45:37,176 --> 00:45:39,011
do... You know, our our work identities are

1305
00:45:39,011 --> 00:45:42,213
gonna be radically shifted and probably ding to

1306
00:45:42,213 --> 00:45:43,886
buy a lot of this stuff. Right? How

1307
00:45:43,886 --> 00:45:45,798
how soon, you know, it's gonna be my

1308
00:45:45,798 --> 00:45:48,210
age... My Ai agent talking to your Ai

1309
00:45:48,268 --> 00:45:50,507
agent coming up with some copy for an

1310
00:45:50,507 --> 00:45:51,007
article

1311
00:45:51,458 --> 00:45:53,756
that we can approve. Right? That's the way

1312
00:45:53,756 --> 00:45:54,311
it's gonna work.

1313
00:45:55,579 --> 00:45:57,583
So who knows know if that's good answer

1314
00:45:57,583 --> 00:45:58,323
or not, but

1315
00:45:59,262 --> 00:46:01,259
it's it's up in the air. Yeah. Sure...

1316
00:46:02,058 --> 00:46:04,136
I... John, Here at the close of the

1317
00:46:04,136 --> 00:46:06,247
conversation. I I'd love to have you diagnose

1318
00:46:06,304 --> 00:46:07,655
what the secrets to your success have been?

1319
00:46:07,815 --> 00:46:09,961
You've had such an interesting and varied career?

1320
00:46:10,359 --> 00:46:12,609
You've been able to draw

1321
00:46:13,301 --> 00:46:16,598
insights and inspiration from across very different experiences.

1322
00:46:17,051 --> 00:46:19,219
You seem to maintain great curiosity,

1323
00:46:19,911 --> 00:46:22,055
as your as your career in life has

1324
00:46:22,055 --> 00:46:22,452
unfolded.

1325
00:46:22,929 --> 00:46:24,889
What what do you attribute some of the

1326
00:46:25,009 --> 00:46:26,520
routes to your success. What are some of

1327
00:46:26,520 --> 00:46:27,554
the ingredients to that?

1328
00:46:28,668 --> 00:46:30,338
I mean, yeah, that's a great question. I

1329
00:46:30,418 --> 00:46:31,236
I would say

1330
00:46:32,504 --> 00:46:33,403
my success

1331
00:46:33,942 --> 00:46:34,442
has

1332
00:46:35,061 --> 00:46:35,561
been

1333
00:46:36,020 --> 00:46:38,338
built on my failures. You know, I'm not

1334
00:46:38,338 --> 00:46:40,515
a detailed guy. I can't

1335
00:46:41,385 --> 00:46:43,925
you know, Like, I can't plan out things

1336
00:46:43,925 --> 00:46:45,750
a long time in advance. I've tried to,

1337
00:46:45,829 --> 00:46:47,258
you know, I've I have been a ceo

1338
00:46:47,258 --> 00:46:49,266
6 times and and successfully, but

1339
00:46:49,972 --> 00:46:52,381
I'm just super curious. Right? I'm not

1340
00:46:52,915 --> 00:46:55,461
I'm not a guy. I'm I've did a

1341
00:46:55,461 --> 00:46:56,256
great example.

1342
00:46:56,734 --> 00:46:58,659
You know, my my buddy, Jim call so

1343
00:46:58,739 --> 00:46:59,859
I climbed with a bunch. He's a here

1344
00:46:59,859 --> 00:47:00,259
and boulder.

1345
00:47:00,900 --> 00:47:02,500
When he was riding before he wrote, you

1346
00:47:02,500 --> 00:47:04,420
know, built the last. He he had this

1347
00:47:04,420 --> 00:47:06,420
rock climb project and Aldo that's right down

1348
00:47:06,420 --> 00:47:07,059
the road from us.

1349
00:47:07,874 --> 00:47:08,534
He spent

1350
00:47:08,913 --> 00:47:12,188
3 years working on a rock climb that

1351
00:47:12,188 --> 00:47:14,346
was about a hundred feet long. Like, he

1352
00:47:14,346 --> 00:47:15,579
documented every

1353
00:47:15,953 --> 00:47:16,930
move. He

1354
00:47:17,384 --> 00:47:19,292
analyzed that he figured it out. And he

1355
00:47:19,292 --> 00:47:21,756
was super successful at it. I I can't

1356
00:47:21,756 --> 00:47:23,744
do that. I... I'm more interested in, like,

1357
00:47:23,982 --> 00:47:26,379
you know, asking why not kind of, you

1358
00:47:26,379 --> 00:47:29,156
know, exploring around the corner, you know, over

1359
00:47:29,156 --> 00:47:29,871
the horizon.

1360
00:47:30,505 --> 00:47:32,172
I think that's some of it. I think

1361
00:47:32,172 --> 00:47:34,579
that, you know, It's not... It it it's

1362
00:47:34,579 --> 00:47:36,420
some of its curiosity, but some of its

1363
00:47:36,420 --> 00:47:38,660
resilience. I've had a, a few tragedies have

1364
00:47:38,660 --> 00:47:41,079
happened in my my life, and it's,

1365
00:47:41,619 --> 00:47:43,394
you know, You just have to keep moving

1366
00:47:43,394 --> 00:47:45,315
forward. Right? Yeah. 1 step at a time

1367
00:47:45,315 --> 00:47:48,114
and and figure out what's next. I I

1368
00:47:48,114 --> 00:47:49,735
think we're in for a real

1369
00:47:50,208 --> 00:47:52,986
difficult time, especially for large companies, and especially

1370
00:47:52,986 --> 00:47:54,121
for Ge rh age

1371
00:47:54,574 --> 00:47:56,478
that have been running those companies. Their identities

1372
00:47:56,478 --> 00:47:58,090
tied up in, you know, having

1373
00:47:59,034 --> 00:48:00,406
big company and having

1374
00:48:01,809 --> 00:48:03,554
a bunch of employees. And I think those

1375
00:48:03,554 --> 00:48:05,774
days are gonna be gone. Right? I... Unfortunately,

1376
00:48:06,012 --> 00:48:06,860
the unit of

1377
00:48:07,378 --> 00:48:09,372
organization is gonna be much smaller. And with

1378
00:48:09,372 --> 00:48:11,845
the Sam Alt question of, like, you know,

1379
00:48:11,924 --> 00:48:13,201
it's gonna be in within the year, there's

1380
00:48:13,201 --> 00:48:15,195
gonna be a billion dollar public company with

1381
00:48:15,195 --> 00:48:16,231
the 1 employee.

1382
00:48:17,043 --> 00:48:18,794
I think that's gonna be true. Right? These

1383
00:48:18,794 --> 00:48:21,363
tools are super powerful, but it's not just

1384
00:48:21,659 --> 00:48:24,046
the radical shifts of organization. It's the radical

1385
00:48:24,046 --> 00:48:25,980
shifts for the identity of who people are.

1386
00:48:26,539 --> 00:48:28,059
Like, what does that mean? Right? If I

1387
00:48:28,059 --> 00:48:30,300
don't have my office to go to and

1388
00:48:30,300 --> 00:48:32,480
don't have my employees to report to and

1389
00:48:32,794 --> 00:48:35,182
So we've gotta rethink that. I think that's

1390
00:48:35,182 --> 00:48:36,854
the coming crisis. How do we deal with

1391
00:48:36,854 --> 00:48:37,014
that?

1392
00:48:37,969 --> 00:48:39,322
Well John, thank you so much for an

1393
00:48:39,322 --> 00:48:40,889
interesting conversation, and and

1394
00:48:41,409 --> 00:48:43,407
Congratulations again on your book. Is open talent,

1395
00:48:43,646 --> 00:48:45,964
leveraging the global crowd to solve your biggest

1396
00:48:45,964 --> 00:48:47,962
challenges. Thank you for sharing your insights through

1397
00:48:47,962 --> 00:48:49,560
this conversation. I really enjoyed it.

1398
00:48:50,534 --> 00:48:52,289
Thanks so much. I really appreciate it. It's

1399
00:48:52,289 --> 00:48:53,886
really great to get to know you and

1400
00:48:53,886 --> 00:48:55,243
like to learn more about your work.