September 27, 2018

Masters of Scale: Keep Humans in the Equation

MASTERS OF SCALE Host: Reid Hoffman – founder of LinkedIn

Guest: Stacy Brown-Philpot – CEO 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
- 1^st 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.”