306. Trust the Process: How to Design Teams That Actually Work
"The assumption of swift trust is really useful."
Teams don't always need years to build trust—they need the right conditions to build it quickly. As a Stanford professor and expert in organizational design, Melissa Valentine studies how communication, team structure, and emerging technologies help people collaborate more effectively. In this episode of Think Fast, Talk Smart, Valentine joins Matt Abrahams to explore how leaders can foster swift trust, adapt communication as teams move from brainstorming to execution, and use storytelling to drive meaningful change. Together, they share practical strategies for building stronger teams and navigating collaboration in an AI-enabled workplace.
Key Takeaways:
- Build trust from the start. High-performing teams assume competence, communicate openly, and address miscommunication quickly.
- Adapt your communication to the task. Encourage diverse thinking during brainstorming, then align your language as the team moves toward execution.
Activity:
- Practice swift trust. In your next project with a new colleague or team, begin by assuming competence and shared intent. Delegate one meaningful responsibility early, communicate clear expectations, and reflect afterward on how starting from trust influenced the team's collaboration and results.
Episode Reference Links:
- Melissa Valentine
- Melissa’s Book: Flash Teams
- Ep.241 Team Spirit: How to Make Group Work Work
- Ep.268 Going Viral: How To Balance Authenticity and Spectacle
Connect:
- Premium Signup >>>> Think Fast Talk Smart Premium
- Email Questions & Feedback >>> hello@fastersmarter.io
- Episode Transcripts >>> Think Fast Talk Smart Website
- Newsletter Signup + English Language Learning >>> FasterSmarter.io
- Think Fast Talk Smart >>> LinkedIn, Instagram, YouTube
- Matt Abrahams >>> LinkedIn
Chapters:
- (00:00) - Introduction
- (00:57) - What Makes a Flash Team?
- (03:01) - Building Swift Trust
- (04:54) - When Teams Need to Converge
- (07:17) - Repairing Miscommunication
- (09:18) - Stories That Drive Change
- (12:01) - Lessons for Every Team
- (13:47) - The Final Three Questions
- (16:41) - Conclusion
********
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Matt Abrahams: Swift trust can
help your communication and
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your teams be more effective.
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My name's Matt Abrahams, and I
teach Strategic Communication at
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Stanford Graduate School of Business.
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Welcome to Think Fast,
Talk Smart, the podcast.
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Today, I look forward to
speaking with Melissa Valentine.
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Melissa is an associate professor in
the Management Science and Engineering
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Department at Stanford and a senior
fellow at the Stanford Institute for
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Human-Centered Artificial Intelligence.
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Her research focuses on how emerging
technologies, including artificial
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intelligence and algorithms, are
fundamentally transforming work,
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organizational design, and team dynamics.
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Melissa, along with her co-author
Michael Bernstein, wrote the fascinating
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book Flash Teams: Leading the Future
of AI-Enhanced, On-Demand Work.
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Well, welcome, Melissa.
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I'm really excited to have you join us.
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Thank you.
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Melissa Valentine: This show is
so fun, and I love the guests you
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have, so I'm delighted to be here.
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Matt Abrahams: Well, thank you,
and thanks for being one of them.
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Shall we get started?
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Melissa Valentine: Let's do it.
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Matt Abrahams: Excellent.
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I have to say, I really enjoyed
your book, Flash Teams, very much.
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Really, really interesting.
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Can you define for all of us what a
flash team is and explain what people,
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processes, and infrastructure enable flash
teams to get aligned and execute quickly?
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Melissa Valentine: Yeah.
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So my PhD is in organization
science, basically.
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So I got my PhD at a business school,
and then my collaborator is a computer
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science professor, and he was doing
a lot of work on crowdsourcing.
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So what's cool about crowdsourcing is
the crowd is, like, millions of people
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online, and you can get things done
quickly 'cause you just put a task out,
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and then there's millions of people who
are available to come work on the task.
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But what he was seeing at the time
that he and I started working together
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was crowdsourcing was stuck because
they were doing, like, really,
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they called them micro tasks, but
just really, like, small tasks.
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And then I had this toolkit, organization
science, and my dissertation had been
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about how you can use team scaffolds or
lightweight team structures, and then you
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populate the team structure with experts.
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And the team structure and
the role structure helps them
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know how to work together.
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So we sort of were able to combine
the logic of both of these.
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So you have these, like, lightweight
structures that allow people who are,
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like, relative strangers to come together
and work together on really complex stuff.
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So this system that we built with a
great team of a PhD student, Daniela
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Ratelny, she organized this great lab at
the time we first did our flash teams.
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So we built a platform that basically
took all the logic of organization
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science and team science, and then
the speed and scale of crowdsourcing,
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and then put them together.
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So the way the system works, you have
this platform where I'm somebody who
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wants to get something done, so I go
to the platform, I design the team,
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and then the platform integrates
with something like, we used Upwork.
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So there's like 10 million
freelancers who are on Upwork.
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And then, so I'll say, "Here's the task
that I need done. Here's the role I
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need filled." And then the platform can
integrate with Upwork, and then it's
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open call to the 10 million freelancers.
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Who's got the right expertise?
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They join the team.
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So you can just convene teams really fast.
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And what we showed with this
research is that you can get
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things done really quickly.
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You can pull teams together.
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They build really complex stuff.
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And it was really inspiring.
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I mean, it's even faster now with GenAI.
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Matt Abrahams: So you set a framework
and expectations and then leverage a
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tool that pulls people in, and then
the flash team is really the focused,
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concerted effort that it's all about.
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One of the essential elements
of any teaming or groups
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coming together is trust.
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What are some of the communication
skills or other skills that people
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can deploy to establish trust quickly?
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I'm assuming part of what flash teams
do, besides accomplish their work,
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is they're able to coordinate action,
perhaps through building trust.
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Melissa Valentine: Yeah, trust in flash
teams is essential and complex, right?
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'Cause it is relative strangers.
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You get together and you work
together really intensely,
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and then you disassemble.
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So I think that there's this idea in the
literature called swift trust, and there's
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an assumption that you just assume trust.
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You just meet somebody for the first
time, you assume they're competent, you
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assume that they know how to do their
role, you assume you're both there for the
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same reason, to work hard, get it done.
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So that, yeah, the assumption
of swift trust is really useful.
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It doesn't always work out,
but the sort of like offering
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of swift trust is part of it.
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And then paying attention to when it's
not going right and being willing and
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able to repair quickly is also important.
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Matt Abrahams: I love
this idea of swift trust.
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So you approach from a place of trust,
assuming that you are trustworthy,
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and I will trust you, and you will
do the same, can expedite things.
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Because there's a lot of this testing that
goes into trust and time, and if you start
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from that place, and obviously it might
fail or people could take advantage of it.
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But the second part, what you said,
I think really is the helpful part,
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is to have that meta-awareness and
watching for it, and then being willing
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to speak up and try to repair it.
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So I think it's not only swift
trust, being open to trust, but being
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open to repair when it's not there.
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I really like that idea of swift trust.
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So much in my life I think would
be better if we just approached
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everything with this notion of like,
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Melissa Valentine: Oh, swift trust.
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Yeah.
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Yeah.
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I mean, there is a real difference
'cause I think of the person I wrote
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the book with, Michael, he and I
have worked together for 15 years
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now, and that is a different kind
of trust than like swift trust.
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But swift trust is a tool that's useful.
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Matt Abrahams: Right.
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It's, and it's a way to at least
initiate and then you can build
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deeper, the trust and relationship.
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That can only happen, I think,
after repeated exposure and time.
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You talk about discursive diversity,
and I had to practice saying
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that multiple times, by the way.
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Can you share what you mean by
discursive diversity, and how can
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teams recognize when they need to shift
their communication style from a more
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open-ended brainstorming, ideating to
a very highly coordinated approach?
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Melissa Valentine: Yeah.
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So that is from the dissertation of one
of my really brilliant PhD students.
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So her name is Katharina Lix,
and she invented that measure.
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So what she was able to do, she
had all of the Slack transcripts of
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different flash teams, and she was
able to, she did this NLP processing.
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Matt Abrahams: And NLP is natural
language processing, I assume.
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Melissa Valentine: Yeah, yeah.
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Before it was cool, she learned
how to do it, and she was able to
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create this measure where she was
looking at the similarity of the
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language that people were using.
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So you have all of the Slack
interactions, and you can basically
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compare people talking on the team and
how similar are the words that they're
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using, the sentence structure, right?
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Are they using the same
adverbs, like adjectives?
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Sense of urgency gets
encoded in all of that.
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And what she was able to show is that the
similarity of the language that people
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are using or the difference, so this is
where, let's see, discursive diversity.
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Matt Abrahams: Discursive diversity.
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Yeah.
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Melissa Valentine: Yes.
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Matt Abrahams: Different
types of words and language.
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Melissa Valentine: Exactly.
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Yeah.
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So that sort of would predict the team
meeting a milestone in different ways.
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So there were times when you really
want the language to diverge.
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So this is a moment of
brainstorming, ideation, right?
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You want a lot of creativity,
you want a lot of divergence.
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But then as you get closer to
the deadline, you really, for the
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team to meet the deadline, then
the language needs to converge.
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Like, people need to start sounding more
like each other to hit the deadline.
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Matt Abrahams: So one,
it's a measure really.
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So you can look at, you know, if I'm a
manager or somebody looking back at doing
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a postmortem or after the project is done,
and I can look at the communication, be
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it Slack, Jira, whatever the tool is,
and I can actually see the, the language
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might be a hint as to where we are.
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And as you're trying to get closer to the
decision, more similar language is a sign.
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What I'd be curious, and I don't know if
there's any research on this, is can you
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actually use language to influence that?
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So can I, as a manager, encourage
more diverse language through
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ideation, but want us to start moving
towards a decision, encourage people
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to start using similar language?
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I wonder if you, if
it's causal in that way.
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Melissa Valentine: I think
that's a great research question.
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Matt Abrahams: Yeah.
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I think that's really interesting.
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So I encourage everybody listening to
think about the language you're using
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for the different tasks you have and
start to notice what that looks like.
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And maybe you can run your own
experiment and play with that.
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I want to keep on flash teams, and then I
want to make a, have a broader question.
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But when flash teams hit a snag, for
example, like a miscommunication, what
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is the most effective way to fix that
so they don't fraction and deal with
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too much friction in those situations?
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Melissa Valentine: So I'm so
glad you asked this question.
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I have an unpublished paper.
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So we ran three really complex flash teams
one summer, and we had all of the DMs.
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So we had all the Slack front stage and
then all of the Slack DMs, the backstage.
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And the thing that was really interesting
in analyzing all of that data is a
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lot of repairs happened backstage.
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So something would happen in the
public Slack channel, and then a dyad
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would go to the back channel, and
they'd be like, "What is this bug?"
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And they would sort it out and then
come front stage with the solution.
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So it created a lot of smooth operations.
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Like the flash teams, they
all accomplished their goal.
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There didn't seem to be a ton of conflict.
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So this pattern of backstage repair
was really interesting to discover.
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I think any human behavior,
it's got different sides to it.
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So I think it did
support smooth operation.
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But what I saw in the analysis that I
have not yet published is that the people
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who are more involved in backstage repair
ended up with more influence over time.
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So these are the workers and the
managers who were, like, really
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helping make the decisions.
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So it's something about access to where
the real problems get solved was, like,
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creating a lot of influence for people.
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Now, I don't totally know
what to do with that.
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As someone who is interested in flash
teams going well, I would maybe say you
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need like a postmortem on a flash team.
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What were the problems?
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Who helped solve them?
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What do we learn about this together?
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Matt Abrahams: It's really intriguing
that the people involved in that
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repair or that dealing with those
problems end up being more influential.
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Melissa Valentine: Yeah.
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'Cause it's like they had the
realer story of what was going on.
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And sometimes it was in the backstage
repair that decisions were made
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and then presented as if they were
quite done, if that makes sense.
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Matt Abrahams: That's really intriguing.
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I'm putting on my manager hat and thinking
if I were in the midst of any team, be
00:09:23.808 --> 00:09:28.147
it a flash team or a regular team, how
I could be aware that the folks who are
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involved in helping fix, repair, dive
deep into problems, what that means
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for them in terms of their currency and
how we interact on the public stage.
00:09:36.968 --> 00:09:39.657
And I just think it's interesting that
we now have these two channels and ways
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of communicating that can be measured.
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I know you think about
storytelling and change.
00:09:45.837 --> 00:09:50.027
How can everyday employees in an
organization use storytelling to drive
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broader systemic change and build
coalitions to help achieve whatever
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it is they're trying to achieve?
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Melissa Valentine: Yeah.
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So one of the studies that I did
when I first got to Stanford was
00:10:00.008 --> 00:10:01.998
actually of an academic cancer center.
00:10:02.258 --> 00:10:06.418
I saw stories be really
influential in this study.
00:10:06.668 --> 00:10:09.748
So it feels a little different than what
we've been talking about with AI and
00:10:09.758 --> 00:10:13.478
algorithms and so forth, but it still to
me is a study of organizational design,
00:10:13.478 --> 00:10:14.808
which is what I'm really interested in.
00:10:15.127 --> 00:10:18.368
What happened in this study, so I
was studying as this cancer center
00:10:18.368 --> 00:10:20.038
was trying to do a transformation.
00:10:20.098 --> 00:10:22.678
They were trying to decrease
the coordination burden on
00:10:22.678 --> 00:10:24.628
patients and their families.
00:10:25.008 --> 00:10:29.828
And during the study, there was a group of
patient advocates or activists who really
00:10:29.828 --> 00:10:33.458
wanted the cancer center to understand how
much coordination they were having to do.
00:10:33.798 --> 00:10:37.848
So the way that they made their case, this
is why I'm thinking of it, is they had an
00:10:37.848 --> 00:10:39.698
initiative they called Patient Stories.
00:10:39.907 --> 00:10:42.567
And so they went to great effort to
collect a lot of patient stories where
00:10:42.567 --> 00:10:46.207
patients just talked about, like a family
member had to quit their job to become
00:10:46.208 --> 00:10:48.457
the full-time coordinator for the patient.
00:10:48.627 --> 00:10:51.208
So they came up with
dozens of patient stories.
00:10:51.247 --> 00:10:54.987
And then in this paper that I have,
I analyze how they basically use
00:10:54.988 --> 00:10:58.548
the stories to make the case and
to spread the movement, spread the
00:10:58.548 --> 00:11:00.037
message across the cancer center.
00:11:00.357 --> 00:11:03.927
And at the end of the study, they had
convinced the cancer center to take
00:11:03.927 --> 00:11:05.497
on some of the coordination work.
00:11:05.758 --> 00:11:08.997
So it ends up being this end-to-end
story of patient stories, patient
00:11:09.008 --> 00:11:12.497
narratives actually changing
the organizational design, which
00:11:12.508 --> 00:11:14.107
is why I'm thinking about it.
00:11:14.107 --> 00:11:16.947
It was like a very powerful thing
that these patient activists did.
00:11:17.247 --> 00:11:19.757
Matt Abrahams: Stories can really
resonate and motivate people.
00:11:19.997 --> 00:11:23.907
Was there anything specific to the stories
that you think were really important?
00:11:23.917 --> 00:11:27.957
Was it the fact that the stories accounted
for all the specific coordination events,
00:11:27.978 --> 00:11:32.187
or was it the emotionality, or was it the
fact that these people just collected a
00:11:32.188 --> 00:11:35.007
bunch of stories and the cancer center's
like, "Wow, there are all these stories.
00:11:35.008 --> 00:11:36.068
We should probably do something"?
00:11:36.527 --> 00:11:39.097
Melissa Valentine: I think a lot of us
interface with the healthcare system,
00:11:39.137 --> 00:11:40.367
and we could just see ourselves.
00:11:40.377 --> 00:11:43.157
So the patient stories were just
like, "This is us. This is you
00:11:43.157 --> 00:11:46.187
and me." And then it illustrated
the problem really specifically.
00:11:46.237 --> 00:11:49.568
So somebody's sitting in a wheelchair
in a hallway 'cause they had been
00:11:49.618 --> 00:11:50.807
dropped or something like that.
00:11:50.817 --> 00:11:54.047
And so it's like, wait, like, I think
the cancer center is so full of people
00:11:54.048 --> 00:11:58.317
who care, and then hearing like the
specific instance in a really relatable
00:11:58.328 --> 00:12:01.248
story, they were just like, "Oh,
that's a problem that I can help with."
00:12:01.438 --> 00:12:02.247
Matt Abrahams: I think you hit on it.
00:12:02.287 --> 00:12:04.317
It's relatable and real,
and we can connect.
00:12:04.317 --> 00:12:04.788
Thank you.
00:12:05.536 --> 00:12:10.806
Can you take what you've learned about
flash teams and give us any insight
00:12:10.826 --> 00:12:12.545
that we can just apply to a normal team?
00:12:12.545 --> 00:12:15.526
So I've got a team that's been around
for a while, and we meet regularly.
00:12:15.866 --> 00:12:18.665
Is there any insight from your work
on flash teams that could perhaps
00:12:18.665 --> 00:12:22.146
help my team be more efficient,
feel more connected, ideate better?
00:12:22.576 --> 00:12:24.945
Melissa Valentine: One thing that Michael
and I used to say when we were writing the
00:12:24.945 --> 00:12:28.726
book, we were trying to think of what's
the mindset here that any manager would
00:12:28.726 --> 00:12:33.516
find empowering, and the phrase we came up
with is experts everywhere all the time.
00:12:33.845 --> 00:12:35.185
So you've got your trusted team.
00:12:35.445 --> 00:12:35.785
Great.
00:12:36.146 --> 00:12:38.415
Keep working together, taking good
care of each other, working hard,
00:12:38.616 --> 00:12:43.946
but really recognize that your
organization, the world, the internet,
00:12:44.256 --> 00:12:47.985
the world is just full of experts who
can help, and people like helping and
00:12:48.035 --> 00:12:49.705
bringing their expertise to something.
00:12:50.115 --> 00:12:53.525
So it's just having a mindset of
recognizing how much collaboration
00:12:53.545 --> 00:12:56.645
is available, how much expertise
is available, and maybe it,
00:12:56.655 --> 00:12:59.185
like, invites you to think of the
boundaries of the team a little more.
00:12:59.615 --> 00:13:01.436
Matt Abrahams: That's funny you said
that 'cause that was exactly the word I
00:13:01.436 --> 00:13:05.866
was thinking is porous, is that it can
be very easy to insulate a team and say,
00:13:05.875 --> 00:13:09.315
"This is the team," but being a little
more open and pulling in expertise.
00:13:09.566 --> 00:13:12.666
When I was managing a team, I
ran a learning and development
00:13:12.666 --> 00:13:16.036
group, and we had this very tricky
thing we had to train people on.
00:13:16.486 --> 00:13:20.916
And it turned out that somebody in the
company who was an admin was using our
00:13:20.916 --> 00:13:24.595
tool, and they actually knew how to do
things that we were trying to figure
00:13:24.596 --> 00:13:25.925
out how to train people on better.
00:13:26.225 --> 00:13:30.325
That person was an expert, and by
just dumb luck, we figured that out
00:13:30.325 --> 00:13:31.865
and incorporated them into the team.
00:13:31.995 --> 00:13:32.975
And I like that idea.
00:13:33.325 --> 00:13:35.485
Melissa Valentine: I think that
there are a lot of tools that can
00:13:35.486 --> 00:13:39.346
be very helpful to managers in terms
of how the team works together,
00:13:39.386 --> 00:13:40.405
coordinates, and stuff like that.
00:13:40.625 --> 00:13:44.375
The other thing we said in the book is
AI-driven team design, so just making
00:13:44.375 --> 00:13:47.595
use of the tools to be very thoughtful
in how you're structuring your team.
00:13:47.915 --> 00:13:50.336
Matt Abrahams: So AI can help us
structure the team and maybe even
00:13:50.346 --> 00:13:53.005
identify who some of the experts
are that, that we might know.
00:13:53.026 --> 00:13:53.475
I love that.
00:13:54.638 --> 00:13:55.638
Melissa, this has been great.
00:13:55.698 --> 00:13:58.668
Before we end, you know I like to ask
three questions one I make up just for
00:13:58.668 --> 00:14:00.158
you and two I've been asking everybody.
00:14:00.158 --> 00:14:00.748
Are you up for that?
00:14:00.798 --> 00:14:01.428
Melissa Valentine: Yeah, let's do it.
00:14:01.648 --> 00:14:04.898
Matt Abrahams: Beyond the academic
research you do, you're also a creator,
00:14:05.008 --> 00:14:08.778
and you study the algorithms that
serve up information on social media.
00:14:09.258 --> 00:14:12.407
What advice do you have for
others who are creators?
00:14:12.607 --> 00:14:16.248
Melissa Valentine: Okay, so
I love Instagram and TikTok.
00:14:16.248 --> 00:14:19.007
I don't, like, I have, I think
it's people have complicated
00:14:19.007 --> 00:14:20.417
relationships with social media.
00:14:20.597 --> 00:14:21.877
So the attention stuff is real.
00:14:21.917 --> 00:14:27.088
My attention span is shot, but I have
learned so much from content creators.
00:14:27.147 --> 00:14:28.357
I am such a fan.
00:14:28.787 --> 00:14:30.227
My advice is keep going.
00:14:30.518 --> 00:14:33.257
If you're an expert, put it out in
the world, like, people will find it.
00:14:33.428 --> 00:14:35.837
Different life transitions I've gone
through, different, like, health
00:14:35.847 --> 00:14:37.997
stuff, different fitness stuff,
different hobbies, like, I have
00:14:37.998 --> 00:14:39.717
learned so much from the internet.
00:14:39.728 --> 00:14:41.267
So thank you, content creators.
00:14:41.568 --> 00:14:43.788
Matt Abrahams: You know, as a creator
myself, and it took me a while to
00:14:43.847 --> 00:14:47.997
identify as a creator, but I think
many of us are motivated to help
00:14:48.007 --> 00:14:52.147
people, and it's that motivation
that actually helps us get through.
00:14:52.377 --> 00:14:56.027
It's hard to put out the content,
and the algorithm can sometimes
00:14:56.027 --> 00:14:57.197
help you and sometimes not.
00:14:57.388 --> 00:15:01.377
So it's that passion, desire to learn and
to help, I think, that really motivate.
00:15:01.377 --> 00:15:03.277
And I can hear that in your
voice, and I see it in the
00:15:03.288 --> 00:15:04.687
things that you post and create.
00:15:04.998 --> 00:15:08.478
Question number two, who is a
communicator that you admire and why?
00:15:08.837 --> 00:15:11.607
Melissa Valentine: So I'm at a
moment where I'm thinking a lot about
00:15:11.617 --> 00:15:16.128
communication, where we really take
each other in in a really deep way.
00:15:16.288 --> 00:15:19.847
So I have a friend who is
a therapist and a Buddhist.
00:15:20.017 --> 00:15:23.547
She has a quality of listening and
expression that it, that allows
00:15:23.557 --> 00:15:25.487
for, like, true communication.
00:15:25.498 --> 00:15:27.507
So I would say I'm gonna,
I'm gonna nominate her.
00:15:27.788 --> 00:15:30.748
It's, like, a fascinating thing about
being very aware of yourself that
00:15:30.767 --> 00:15:33.637
allows you to be very aware of others
and just, yeah, like, it is a lot of
00:15:33.638 --> 00:15:36.717
presence, as you're saying, like, a
lot of kind of presence and connection.
00:15:37.197 --> 00:15:39.257
Matt Abrahams: Yeah, I like that,
self-awareness and other awareness.
00:15:39.257 --> 00:15:39.707
Thank you.
00:15:40.267 --> 00:15:43.447
And final question, what are the
first three ingredients that go into
00:15:43.447 --> 00:15:45.448
a successful communication recipe?
00:15:46.087 --> 00:15:49.878
Melissa Valentine: Something that I've
come to appreciate is how useful, like, a
00:15:49.878 --> 00:15:53.687
deep awareness of your own experience is,
'cause then you're even more able to take
00:15:53.687 --> 00:15:56.037
in another's in all of its complexity.
00:15:56.357 --> 00:16:01.007
So yeah, self-awareness, other awareness,
and then working from there, I think
00:16:01.047 --> 00:16:03.157
what's possible between you is, like, new.
00:16:03.188 --> 00:16:04.717
It's like something that
neither of you would have done
00:16:04.897 --> 00:16:06.718
without that kind of connection.
00:16:07.328 --> 00:16:09.917
Matt Abrahams: I sort of bristle at
the word synergy, but in this case
00:16:09.917 --> 00:16:13.117
that's exactly what you're talking
about, is it's the power of the two
00:16:13.117 --> 00:16:14.897
is greater than either individually.
00:16:14.947 --> 00:16:18.708
But that comes, as you said, from a
self-awareness and then other awareness.
00:16:19.378 --> 00:16:22.097
Thank you for the three ingredients,
and thank you for the conversation.
00:16:22.298 --> 00:16:26.648
Your work to me is really intriguing
because it focuses both on technology,
00:16:26.907 --> 00:16:30.467
but the human aspect of people coming
together, and the fact that there are
00:16:30.468 --> 00:16:34.417
structures that we can rely on to help
expedite and make things more efficient.
00:16:34.627 --> 00:16:35.868
Melissa, this has been fantastic.
00:16:35.868 --> 00:16:37.467
Thank you, and thank
you for the work you do.
00:16:37.517 --> 00:16:37.847
Melissa Valentine: Totally.
00:16:37.858 --> 00:16:38.687
Really fun for me too.
00:16:38.697 --> 00:16:39.138
Thank you.
00:16:41.110 --> 00:16:43.180
Matt Abrahams: Thank you for joining
us for another episode of Think
00:16:43.180 --> 00:16:45.000
Fast, Talk Smart, the podcast.
00:16:45.430 --> 00:16:49.810
To learn more about groups, listen in
to our episode 241 with Colin Fisher.
00:16:49.980 --> 00:16:52.810
And to learn more about social
media algorithms, please check out
00:16:52.840 --> 00:16:55.260
episode 268 with Angèle Christin.
00:16:55.610 --> 00:17:00.190
This episode was produced by Katherine
Reed, Ryan Campos, and me, Matt Abrahams.
00:17:00.449 --> 00:17:04.549
Our music is from Floyd Wonder, with
special thanks to Podium Podcast Company.
00:17:04.959 --> 00:17:07.820
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