248. Better Together: How to Supercharge Your Team’s Productivity

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Matt Abrahams: Collaboration is critical
to teaming, but how do we do it so

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that we feel effective and unburdened?

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My name is 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
chatting with Molly Sands.

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Molly is a behavioral scientist and the
head of the Teamwork Lab at Atlassian.

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She and her team conduct research into
best practices for high performing teams.

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Her work focuses on understanding how
teams can collaborate more effectively in

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a distributed and hybrid work environment,
especially in the world of AI.

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Welcome Molly.

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I have long admired the work of your
team and I'm really excited to have

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a conversation about the work you do.

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Molly Sands: Thank you so much.

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I'm excited to be here.

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Matt Abrahams: Okay, shall we get started?

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Molly Sands: Let's do it.

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Matt Abrahams: Awesome.

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So the Teamwork Lab studies many
aspects of teaming and productivity.

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How do you determine what to
study and do you have some guiding

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principles for the work that you do?

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Molly Sands: I am really focused
on a few things in our work.

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We have a couple key beliefs about
teamwork, and one is that people

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can accomplish a lot more together
when they work well together.

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And the other is that in most
companies today, it is way

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too hard to work together.

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And the more that we can get on the
same page about what we're trying to

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achieve together and how we're going to
get there, the more effective we are.

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Those are sort of my guiding
philosophies around how do teams work

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effectively together, and we anchor
our research in a couple areas.

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So one, my team, the Teamwork
Lab at Atlassian, we study

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teams across the world.

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So we will survey thousands of teams.

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We'll talk to leaders.

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We'll do lots of different types
of research, and then we also

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study teams within the company.

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And within Atlassian, we're really
able to get in the mix with teams

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and change how they work and measure
lots of different types of outcomes.

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And so from those two approaches,
we get a really good sense of what

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are the challenges that most people
are facing today and that all of our

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customers really care about and need us
to come up with better solutions for.

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And then we also have this amazing
experimental pool, and so we can start

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to really change ways of working and
then see how that impacts outcomes.

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Matt Abrahams: In that research that
you do, at least trying to identify

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what the big challenges, are there
two or three that stand out in terms

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of what really teams struggle with?

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Molly Sands: Yeah, so, goals.

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What actually matters is huge
for teams and how people invest

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their time in companies today.

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And so we'd spend a lot of time studying
and thinking about how do we get clear

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on what we're trying to do and how do
we invest our times in ways that are

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actually meaningful and help us do
real work and not just talk about work.

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Matt Abrahams: Do you have suggestions for
how people can help identify their goals?

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And then I know something you spend a
lot of time on is alignment, getting

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people aligned to those goals.

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'Cause I've been in several organizations
where I thought we were working in

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one direction and it turns out others
thought we were working in another.

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So how do we determine what
those goals are and how do we

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get alignment towards them?

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Molly Sands: So I think a lot
of the best work happens when

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you start by asking why, right?

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And you are really focused on
what are we, what do we want

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the true outcome to look like?

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And in a lot of companies and a lot
of teams today, people get activities

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confused with outcomes, right?

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It's less about what is the business
problem we're solving, what is the

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customer problem we're solving,
and more about what activities

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are we doing to get there?

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And so getting really clear about
the problems is really the first step

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to having a great strategy and then
being more explicit about how are

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we going to get there, and getting
that input, getting people to really

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understand why is this a problem?

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Why do we wanna solve it?

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And how are we uniquely
positioned to do that?

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All of that product thinking, is
really how I think about it, tends to

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help teams get much better aligned.

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And then being explicit, right?

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There's so many moments, you just
referenced times of thinking, well,

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I thought we were all on the same
page, but I never said it out loud.

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And your colleagues and your
teammates are not mind readers.

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So the more that we can really
map this out together, the more

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effective our teams tend to be.

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Matt Abrahams: I think taking the time
to really reflect on what is important

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here, what's the problem we're solving,
why are we doing this, and then making

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it explicit by documenting it and
communicating it, are really important.

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And I have found in the practice
that I do, and when I go into

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organizations, having people just
share what is the goal and have

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everybody give their version of it.

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People are often very surprised
that they weren't aligned.

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So explicitly not just providing it,
but making sure people share their

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take on it can be really helpful too.

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Molly Sands: Yeah.

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I always tell managers or anyone
that's leading a project, one of

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the first things you should do is
ask everyone to tell you what they

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think you're trying to accomplish.

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Matt Abrahams: And a powerful
question I found, I'd be curious

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to get your input on it, is asking
people, what does success look like?

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What does success of this team look like?

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Molly Sands: We actually start every
project we do in our platform, we

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have a way that people can document
this, but what are we doing?

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Why are we doing it?

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And what does success look like?

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And just by asking those three
questions, and writing something up

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that everyone working on that project
reads and thinks about and gives

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feedback on, that is such a fast way
to actually accelerate everything

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that happens from that point on.

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Matt Abrahams: Yeah, what are we doing?

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Why is it important?

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And what does success look like?

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Really important questions.

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I think another important question, and
I'm sure this won't surprise you, is

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I'd love to talk about AI and AI's role.

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It's certainly affecting work,
period, but also in teams.

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Your research shows a shift
towards using AI as a collaborator.

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Can you help us understand
what that looks like?

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What recommendations do you
have to leverage AI to help

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teams be more successful?

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Molly Sands: One of the things we saw
earliest as AI was really taking hold

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of how we do work was that people's
mindset around it mattered in a huge way.

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And so if you really think of AI as a
collaborator, rather than just a doer,

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but you're actually thinking about AI
more like a teammate and someone that

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can push your thinking forward and
that you can go back and forth with.

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Those are the people that are
seeing much better outcomes, and

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that's across a lot of things.

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So they're seeing more efficiency
in the work they're doing.

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They're able to do tasks faster, but
those folks are also seeing better

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quality work and their teams are
viewing them as more innovative.

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And some of the promise of AI that
we're all excited about is really coming

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true for the people that start to think
about AI in that collaborative mindset,

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rather than simply as, oh, well, I can
delegate and automate a few things.

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Matt Abrahams: Can you give
us a few examples of what true

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collaboration with AI might look like?

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Does it have a seat at the table?

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Is it in the Zoom meeting with me?

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Am I asking it questions like a colleague?

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What does that look like?

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Molly Sands: So I think it is great to
think of AI as a quick way to get some

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information that you need, but it's also
about that back and forth interaction.

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So actually creating things, and not
just taking the first output that you

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get, but actually going back and forth,
debating, asking questions, having AI

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push your thinking and pushing back too,
saying, I don't think this is right.

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I know about this other thing.

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How do we incorporate this?

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And much in the way you would go
about collaborating with other

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people where it is a back and forth.

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Matt Abrahams: We had a really insightful
episode we did with Jeremy Utley, where

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we talked about how treating AI as a
conversation partner, not just as a search

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engine, really can change the dynamic.

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And it sounds like that's what you're
advocating for is really engage in

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dialogue, talk to it, and challenge
it, and it will help you benefit.

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Can you give us an example of
using AI as a tool to help you?

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I read about, or listened to an episode
of something where Atlassian has built

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an onboarding tool out of AI to help
people get started and be more productive.

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Molly Sands: Yeah, we've had great
success with onboarding with an AI buddy.

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So we built what we call, her name is
NORA Atlassian onboarding Rovo agent.

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And NORA has access to all of the data
that we have about policies and people

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programs and how we run our company,
how people get set up in our systems.

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And when our new hires join, they have
a variety of touchpoints with other

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humans, but we also give them access
to NORA and say, Hey, if you have any

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of those basic HR questions, ask her.

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If you have any questions about how
things operate in this company, if

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you're wondering who to ask about this,
if you don't know how to file a ticket.

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Just all of those logistical things
that come up as you're joining.

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And you don't really wanna go
to your brand new manager and be

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like, oh, I have this like really
annoying list of twenty-five

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questions about logistical things.

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You wanna be showing up as strategic
in those conversations, and NORA

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is your buddy for everything that
you need, and people feel a lot

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more comfortable asking questions.

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They don't worry about how AI is
going to perceive those questions, so

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they really ask everything they want.

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And we've also found that this has
vastly increased how much people

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use AI as a collaborator, as
they onboard into their new role.

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Matt Abrahams: So it's an on-ramp to
helping them feel comfortable using AI

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as a tool to help them with their work.

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I like that.

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Molly Sands: Yeah.

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And so we've seen a really strong
relationship there that just this

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initial touch point sets that
expectation that this is a way that

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we work in this company and this is
how you're going to get information.

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Matt Abrahams: I know when I would
onboard on companies, I would always

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feel so embarrassed 'cause I couldn't
remember something I was taught

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and I'd have to go back and ask.

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And I feel like I'm trying to set
a good impression and now everybody

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thinks I can't remember anything.

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To have a tool like that would be helpful.

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So finding niche needs and building
AI tools to help, not only help

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with whatever that need was, but
it also helps people feel more

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comfortable using AI as a collaborator.

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Molly Sands: Yeah, and I think it's
important for companies to think about

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where they have really robust knowledge.

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So AI works the best when it has
access to the right information,

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and so in HR policies tend to
be really carefully documented.

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You actually do need to have good
resources for any new employee about

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what your benefits look like, about
how people manage different systems,

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about how they integrate into teams.

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We're able to pretty easily
create customized onboarding

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plans using AI as well.

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And so when all that
information is available, you

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can easily build on top of it.

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And so I usually encourage leaders
to think about where are pockets

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within your company that you have
that great data already there, and

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to think about those as use cases
where you can get some clear ones.

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Matt Abrahams: Yeah, clear, easy pilot
wins and really get that momentum going.

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I appreciate that a lot.

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As you and I talked about before we
came on the air, meetings can be really

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useful for teaming, but many of us
struggle with the meetings we have.

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We feel like they're too many.

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We feel like we're
victimized by poor meetings.

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They zap our time.

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I know you have done research
into meetings and actually at

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Atlassian, you guys have some
really interesting approaches.

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I know you use Loom videos
for asynchronous updates.

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You have what are called
page led meetings.

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Can you define these two approaches
because I think they're really

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unique and could be helpful for many.

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And then what other advice do you have
generally in terms of how we meet better,

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when we meet better, who we meet with.

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So I'd love to get specific on what
you all have done, because I think it

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transfers to many people, and I just love
generally what your research has found.

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Molly Sands: Meetings are
one of the biggest challenges

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in people's jobs, right?

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Anytime that we run research about
what's holding people back from

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achieving what they want to at work,
meetings are the number one thing.

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It's the biggest barrier to
productivity, but it's essential

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that we talk to each other.

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That's how we come up with great ideas.

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That's how we create together.

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There are so many things that
are so important about that.

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And in the last few years, as companies
have embraced much more distributed

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global work, people have brought a lot
of the meeting habits, that we did not

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love in the office, online with them.

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And so now we're all stuck in these
back to back meetings all day long.

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And what we really think about
is taking control of our time and

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solving the problems that meetings are
supposed to solve in different, more

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efficient and more effective ways.

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And so I think people should
think about having kind of three

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types of time in their day.

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One is time for deep work.

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You really do need time to think, to
write, to create, depending on what your

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job is, that time will look different, but
the time where you're using your brain in

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the most powerful ways, and now you've got
AI as a partner during that time as well.

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And then we should have meetings.

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And at Atlassian we do page led meetings,
and we've done a lot of research

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on this idea, and the basic idea is
that you put together a really clear

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synopsis of what everyone needs to
know as context to have a conversation.

00:13:21.705 --> 00:13:24.615
This works really well when you're
trying to make a decision, when you're

00:13:24.615 --> 00:13:30.885
trying to align people, when you want
feedback on a perspective or path forward.

00:13:31.245 --> 00:13:35.025
So any of those kinds of meetings where
you really are bringing a group together

00:13:35.025 --> 00:13:39.870
to say, let's chart the path forward or
make sure everyone's at least aware of it.

00:13:40.080 --> 00:13:43.890
Those moments work really great
for this page led meeting concept.

00:13:44.280 --> 00:13:46.050
And the pages should be short.

00:13:46.200 --> 00:13:48.780
Pages should be no more
than a five minute read.

00:13:49.020 --> 00:13:51.600
You don't want people
reading for hours together.

00:13:51.720 --> 00:13:54.565
Matt Abrahams: And do people read those
when they all convene together, is the

00:13:54.565 --> 00:13:56.215
expectation that you read them in advance?

00:13:56.215 --> 00:13:58.705
Because I know Amazon does
in the room, we all read.

00:13:58.975 --> 00:14:00.535
Molly Sands: Yes, we
do in the room as well.

00:14:00.805 --> 00:14:02.005
The pre-reads are tough.

00:14:02.005 --> 00:14:02.995
People don't do them.

00:14:03.085 --> 00:14:04.645
You're not sure if people did them.

00:14:04.855 --> 00:14:09.655
You maybe did it, but it was four days ago
and now that's not top of mind for you.

00:14:09.835 --> 00:14:13.885
So it's a great way at the beginning
to just set the context for everyone

00:14:14.095 --> 00:14:15.685
and we ask people to comment.

00:14:16.295 --> 00:14:18.064
Matt Abrahams: So you said there
were three ways of using time.

00:14:18.064 --> 00:14:19.234
I'd love to revisit those.

00:14:19.234 --> 00:14:22.895
And then, I hate update meetings and
I know you all have an interesting

00:14:22.895 --> 00:14:25.895
way of getting that information that
I think everybody should consider.

00:14:26.074 --> 00:14:26.555
Molly Sands: Yes.

00:14:26.584 --> 00:14:26.765
Okay.

00:14:26.765 --> 00:14:27.994
So three ways of using time.

00:14:28.234 --> 00:14:33.704
One is traditional meetings,
another is deep work, and the third

00:14:33.854 --> 00:14:39.959
is, and this sounds so silly, but
collaboration, more fluid collaboration.

00:14:40.410 --> 00:14:45.600
And what we've seen in people trying
to fix meetings is that some teams

00:14:45.600 --> 00:14:48.660
have shifted to way too much structure.

00:14:48.689 --> 00:14:52.709
And so every time that you're bringing
people together to talk, it is like

00:14:52.709 --> 00:14:57.780
very agenda led and someone is giving a
presentation and that's not the moment

00:14:57.780 --> 00:14:59.610
where you can really create together.

00:14:59.995 --> 00:15:03.385
And so, especially if you're working
on distributed teams where people are

00:15:03.385 --> 00:15:08.995
in lots of different locations, having
these more fluid moments where you can

00:15:08.995 --> 00:15:11.694
come together and really just work.

00:15:11.964 --> 00:15:16.105
That could be pair programming, that
could be writing a page together, that

00:15:16.105 --> 00:15:20.995
could be doing a creative brief or
coming up with concepts, brainstorming.

00:15:21.275 --> 00:15:25.715
All these different ways that we really
do work together, and I think people

00:15:25.715 --> 00:15:29.975
need to start to think about that as a
category that is different from a formal

00:15:29.975 --> 00:15:34.745
structured meeting, but make a lot more
time for that kind of collaborative work.

00:15:35.015 --> 00:15:38.345
Matt Abrahams: So it's this notion of deep
time where you're by yourself, maybe with

00:15:38.345 --> 00:15:40.655
an AI collaborator, working on something.

00:15:40.655 --> 00:15:46.200
It's the typical, traditional, structured
meeting led with pages where you all

00:15:46.200 --> 00:15:50.310
sync up on what it is we're talking
about, and then the more collaborative

00:15:50.310 --> 00:15:55.290
ideative time where people come together
and can really have the freedom to

00:15:55.290 --> 00:15:56.490
do the work that needs to be done.

00:15:56.550 --> 00:15:57.240
Molly Sands: Exactly.

00:15:57.240 --> 00:16:00.810
And in order to have time to do all
of those things, you cannot be in

00:16:00.810 --> 00:16:03.990
back to back standing meetings where
you were giving status updates.

00:16:04.200 --> 00:16:07.170
And people don't have meetings
for no reason, even if they're

00:16:07.170 --> 00:16:10.725
not effective, which most of the
time they tell us they are not.

00:16:11.085 --> 00:16:14.205
They're trying to solve a problem
and usually that problem is

00:16:14.205 --> 00:16:16.005
getting or sharing information.

00:16:16.215 --> 00:16:19.845
And so we do a lot of asynchronous video.

00:16:19.875 --> 00:16:25.365
We have a tool called Loom that we use,
which lets you record yourself talking.

00:16:25.485 --> 00:16:30.405
You can screen record, you can just record
a video of you, and that captures a lot

00:16:30.405 --> 00:16:34.040
more signal than simply a written update.

00:16:34.340 --> 00:16:38.060
We find that people feel more connected
to other people when they communicate

00:16:38.060 --> 00:16:42.860
through video, and that there's a
lot of benefits to giving more of

00:16:42.860 --> 00:16:45.770
that personal touch to information.

00:16:45.950 --> 00:16:51.410
And so we ask people to usually do their
updates or status updates, either through

00:16:51.415 --> 00:16:56.005
writing or through Loom videos, depending
on how much context they need to share.

00:16:56.214 --> 00:16:59.334
And we align all of our work to goals.

00:16:59.485 --> 00:17:02.395
So there's a whole system and
infrastructure around goals.

00:17:02.694 --> 00:17:04.075
What are teams working on?

00:17:04.165 --> 00:17:05.815
Where do you have shared goals?

00:17:06.085 --> 00:17:08.935
And this creates a lot of that
clarity that we were talking about

00:17:08.935 --> 00:17:12.275
in the beginning, right, of what
are we trying to achieve together.

00:17:12.605 --> 00:17:18.395
And just repeatedly having people look at
and remind themselves of that information

00:17:18.395 --> 00:17:23.645
through our ways of sharing updates is
huge for staying on the same page about

00:17:23.645 --> 00:17:25.205
what we're really trying to achieve.

00:17:25.595 --> 00:17:29.435
Matt Abrahams: I really like that
idea of recording the update.

00:17:29.825 --> 00:17:33.635
Not only do you get more information, as
you said, more signal, but people can take

00:17:33.635 --> 00:17:34.985
in that information when they need it.

00:17:35.635 --> 00:17:38.575
So I will often coach people in
the organizations I go into where

00:17:38.575 --> 00:17:41.425
people are just so frustrated with
these long update meetings where

00:17:41.425 --> 00:17:43.255
maybe ten percent is useful to you.

00:17:43.405 --> 00:17:47.515
Have everybody record their sessions in
a structured way, so you know, you're

00:17:47.515 --> 00:17:51.355
getting the same type of information
and the requirement is that you just

00:17:51.355 --> 00:17:52.765
watch it in advance of the meeting.

00:17:52.765 --> 00:17:55.225
So when you come together, you can
actually have a discussion about what

00:17:55.225 --> 00:17:58.345
you learned rather than wasting the
time of hearing everybody's update.

00:17:58.375 --> 00:17:59.665
And I really like that.

00:17:59.725 --> 00:18:03.625
And I also like what you said about tying
these into the broader goal and always

00:18:03.955 --> 00:18:06.145
reminding people how these things connect.

00:18:06.475 --> 00:18:10.375
So I think those are very useful
tools to help people be more efficient

00:18:10.375 --> 00:18:11.935
and effective in their meetings.

00:18:11.935 --> 00:18:14.274
So the idea is not get
rid of all the meetings.

00:18:14.274 --> 00:18:18.925
The idea is maximize the utility of the
meetings for what they're meant for.

00:18:18.925 --> 00:18:19.735
So thank you for that.

00:18:20.879 --> 00:18:23.610
So Molly, before we end, I like
to ask everybody three questions.

00:18:23.610 --> 00:18:26.670
One I make up just for you and two,
I've been asking everybody for as

00:18:26.670 --> 00:18:28.290
long as this podcast has gone on.

00:18:28.320 --> 00:18:28.980
Are you up for that?

00:18:29.430 --> 00:18:30.270
Molly Sands: I'm up for that.

00:18:30.570 --> 00:18:32.670
Matt Abrahams: I am curious, what
is something that your team is

00:18:32.670 --> 00:18:35.355
currently studying or working
on that has you really excited?

00:18:36.510 --> 00:18:40.230
Molly Sands: We are working on
a lot of research about how you

00:18:40.230 --> 00:18:42.540
really make AI part of the team.

00:18:42.930 --> 00:18:47.850
So we see people are using AI more
and more at work and in their personal

00:18:47.850 --> 00:18:53.895
lives, but how do we solve team level
challenges and problems, the things that

00:18:53.895 --> 00:18:55.965
are really hard about working together.

00:18:56.265 --> 00:18:59.805
And so we are doing some really
interesting interventions right now with

00:18:59.805 --> 00:19:05.685
teams where we embed AI not just as an
individual collaborator for everyone on

00:19:05.685 --> 00:19:09.675
the team, but also into some of these
team processes and ways of working.

00:19:09.680 --> 00:19:13.035
And I'm very excited to see more
of what we learned from that.

00:19:13.285 --> 00:19:15.685
Matt Abrahams: I would love for you when
you start getting results to have you

00:19:15.685 --> 00:19:18.595
share some of that, and we will try to
get that information out because I see

00:19:18.595 --> 00:19:21.985
that as a big unlock, but I also see it as
something that could be a real challenge.

00:19:21.985 --> 00:19:24.205
So it'd be really interesting
to find what you've learned.

00:19:24.565 --> 00:19:25.375
Question number two.

00:19:25.375 --> 00:19:28.465
Who is a communicator
that you admire and why?

00:19:29.085 --> 00:19:32.475
Molly Sands: I really admire Molly Graham.

00:19:32.745 --> 00:19:38.205
She, I think, is a fantastic communicator
in really synthesizing some of the

00:19:38.205 --> 00:19:43.215
core things that are hard about
work and putting analogies behind

00:19:43.215 --> 00:19:45.165
them that make them very memorable.

00:19:45.285 --> 00:19:47.985
And I've been really
impressed with her work.

00:19:48.015 --> 00:19:53.055
She's most well known for the giveaway
your Legos piece that she's written about

00:19:53.055 --> 00:19:55.665
how to scale in companies and how to grow.

00:19:55.995 --> 00:20:01.185
But I think all of her content
is so actionable and memorable.

00:20:01.875 --> 00:20:03.105
Matt Abrahams: So I like
that it's actionable.

00:20:03.105 --> 00:20:06.195
That's what we're all about is
practical and tactical actions.

00:20:06.615 --> 00:20:10.125
But it sounds like the ability to
synthesize and to make things accessible

00:20:10.125 --> 00:20:13.575
through things like analogies, which
are wonderful skills for anybody

00:20:13.575 --> 00:20:15.015
hoping to be a good communicator.

00:20:15.555 --> 00:20:19.095
Final question, what are the first
three ingredients that go into a

00:20:19.095 --> 00:20:21.255
successful communication recipe?

00:20:21.899 --> 00:20:23.340
Molly Sands: Making it resonant.

00:20:23.550 --> 00:20:27.780
You want people to immediately
feel what you're talking about.

00:20:28.110 --> 00:20:28.680
Clarity.

00:20:29.250 --> 00:20:35.610
And I think passion, when you care
about the topic, when you care about

00:20:35.610 --> 00:20:39.450
what your message is, that really comes
through in the way you communicate.

00:20:40.139 --> 00:20:43.500
Matt Abrahams: Making it resonant,
relevant, salient, really important.

00:20:43.500 --> 00:20:44.370
Being clear.

00:20:44.460 --> 00:20:46.020
You've talked about clarity a lot today.

00:20:46.020 --> 00:20:48.720
Clarity of goal, alignment
to goal, clarity of messages.

00:20:48.840 --> 00:20:49.830
And then passion.

00:20:49.980 --> 00:20:53.350
And you clearly are passionate
about helping people collaborate

00:20:53.350 --> 00:20:54.790
and work better in teams.

00:20:54.790 --> 00:20:56.290
Thank you for the best practices.

00:20:56.590 --> 00:21:00.520
Thank you for helping us understand
the details of what goes into

00:21:00.520 --> 00:21:04.360
collaboration and effective work, and
thank you for your time and helping

00:21:04.360 --> 00:21:06.220
all of us be better in our teaming.

00:21:06.730 --> 00:21:07.030
Molly Sands: Yeah.

00:21:07.030 --> 00:21:09.700
Thank you so much for having me
and for this wonderful discussion.

00:21:12.010 --> 00:21:13.810
Matt Abrahams: Thank you for
joining us for another episode of

00:21:13.810 --> 00:21:15.760
Think Fast Talk Smart, the podcast.

00:21:15.820 --> 00:21:18.040
To learn more about teams
and teaming, please listen to

00:21:18.040 --> 00:21:20.290
episode 242 with Colin Fisher.

00:21:20.835 --> 00:21:25.755
This episode was produced by Katherine
Reed, Ryan Campos, and me, Matt Abrahams.

00:21:26.055 --> 00:21:27.495
Our music is from Floyd Wonder.

00:21:27.555 --> 00:21:29.985
With special thanks to the
Podium Podcast Company.

00:21:30.435 --> 00:21:33.435
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