Masters of Scale: Keep Humans in the Equation

MASTERS OF SCALE         Host: Reid Hoffman – founder of LinkedIn

 

Guest:   Stacy Brown-PhilpotCEO of TaskRabbit

Topic:    Keep Humans in the Equation

INTRO

  • Like any catchy tune, a good jingle can get in your head and make a lesson stick
  • Others repeat it and, in turn, learn from them
  • Humans are learning machines
  • The human cloud is waiting to be tapped, a workforce that can teach itself, learn for itself, discover its hidden talents
      • The Cloud – tapping distributive power of computers across the world to store things/get things done
      • Human cloud has extraordinary potential, but more complex than computers because humans are not a fixed variable, they change over time
      • X factor in any equation for scale is the human variable
        • Especially the human capacity for learning and teaching each other
      • TaskRabbit – Where anyone can be hired to complete jobs
      • You can harness the power of the human cloud to solve any problem as long as keep “human” in the equation

Stacy Brown-Philpot – CEO for TaskRabbit, former manager at Google

    • Stacy is from west Detroit
    • 1st job was paper route – 10 year old had to get people to pay their bills
    • Inspired me later on – “Do good work for people, it’ll pay off.”
    • Tougher lesson – “Detroit taught me grit, not just cold weather, but there’s a community that needs to thrive, and you need to figure out a way.”
    • Attended Wharton and Stanford
      • Hired by Google
      • High school was 98% African American but there were few black people in tech industry
      • Went to her then-boss, Sheryl Sandberg
        • Told her to hire and recruit more blacks
        • Sheryl said: “No, you’re the person we’ve been waiting for.”
          • Lean in
        • Started with a simple email exchange of all black people she knew – told them to add to it, then forward, over and over again
      • The Human Cloud kicked in. At first it was a club then became, The Black Googler Network
      • Pioneered schemes to reach out to talented black students
    • One of Stacy’s first exercises in tapping the Human Cloud
    • Stacy was sent to India to make Google’s ad platform smarter
      • Lesson 1: Started teaching a machine to do yes – no decision making. “But at some point, there’s just some judgment about what’s on this page that the machine can’t learn.”
        • Needed human judgment
        • Started exploring the essential role human intelligence plays in artificial intelligence
      • Lesson 2: Things don’t always work the way you expect them
        • Frustrated when weekly one-on-one meetings with direct reports didn’t translate to checking off items on her to-do list
        • “What I needed to learn, was that this meeting is not about you, Stacy. This meeting is about the person you’re leading.”
    • What every manager needs to know: how to get the best out of humans- need to do more than just direct your employees or drive their to-do list, “Your job is turn the light on inside of them.”
    • Sometimes treat our teams like assembly lines- units of work to accomplish tasks.

Unlike machines, people often teach each other and themselves if you give them a chance

  • Whitney Johnson – author of Build An A Team
    • You and every member on team is a learning machine
    • On-the-job development gets lost in the day-to-day chaos, people stagnate, so does organization
    • Easy to keep people where they are and keep doing what they’re doing because you know the work will get done
    • Most want the challenge of something new, learning how to do it, then mastering and then learning something new
    • Learn, leap, repeat – good for satisfied employees and innovative companies
  • TaskRabbit
    • Stacy back from India – “Needed to do something else that would grab at my heart.”
    • Joined TaskRabbit as CEO in 2013- “I’m a mission person.”
    • “Took me back to Detroit, people who were good, hard-working but lost their jobs because of the failure of an entire industry.”
    • TaskRabbit was EBAY for services- great little app- anybody could do anything and get what they want
    • Taskers” – freelance, all-purpose workers
    • But free-wheeling system had limitations
      • Taskers had to go through bidding process, bidding against each other
      • Time consuming for clients to go through bids
    • 50% people had a bad experience
    • How to fix – rethink how it worked
      • Types of tasks now had to fit in four categories: housecleaning, moving help, personal assistant, handyman work
      • Taskers could set hours and specify rates; new minimum rate
      • Clients could book a tasker with one visit to site, no scrolling through bids
      • Tested in a new area: London
        • Because they never had it before
        • Brits loved it
        • “Knew we were on to something”
        • Brought it back to US but made a Big mistake
          • Told the taskers about new changes the same day everyone else learned about it
      • Though management had implemented a program that would make their lives better, it did not give workers a head’s up
        • Undermined their sense of investment
        • It’s a community where people have a sense of ownership
      • CEO blindsided – forgot the human element
      • Lost revenues and users, taskers and clients
      • Eventually turnaround worked – then something strange started happening
        • Because Taskers were no longer bidding against each other, they started helping each other/posting videos and increasing their earning power:
          • Example of what happens when you allow the human cloud to be human
      • The community of taskers takes pride in what they do, developed new skills to address customer’s needs
      • Once hyper-competitive bidding structure was removed, a supportive community of Taskers emerged
        • Teach each other skills
        • Increase one another’s earning power
        • Expansion of human cloud
        • Harnessed the power of the community to train and develop
      • What happens when you keep humans in the equation, they find ways to positive sum gains
      • Created this self-enabling way for people to learn and earn in the marketplace
      • “When people are more secure in their economics, they tend to be more open hearted.”
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