Welcome to Making Data Matter, where we've got conversations about leadership and data
at mission-driven organizations with practical insights into that helpful intersection of
nonprofit mission strategy and data.
I'm your host today, Sawyer Nyquist.
I'm your co-host, Troy Dueck.
And today we've got a friend of ours on the show.
His name is Matt Brody.
Matt, welcome.
Hey, thanks.
Really glad to be here.
And Matt, for people meeting you for the first time, tell us a little bit about who you are,
what you do, and maybe why you're here on the show.
What do you have to do with data?
Yeah, sure.
So I get to call home this particular spot in Canada, which is a bit west of Toronto.
It's called Guelph.
I get to live and work here.
And I also get to call myself a data storyteller and department co-manager.
I'm at one specific spot in a small corner of an organization, a nonprofit, and it's
kind of a weird space between formal leadership and just playing around, trying to make use
of useful things for our organization is the main thing.
Yeah.
And I'm about data.
I'm passionate about using tools to design and build stuff.
Actually using tools to design and build tools that are data-based that will help our organization
in some way, shape, or form.
I'm very much at the beginning of figuring out how to do that, but that's probably going
to be part of what we talk about.
Tell me about where the title or why you call yourself a data storyteller.
That's not a common job title.
There's data analysts, there's maybe data architects.
Tell me what a data storyteller is or how you adopted that as a title or were given
that.
Yeah.
It was me adopting it and asking for permission and they kindly gave it.
I kind of worked myself into this job.
I saw the opportunity of like, oh, I think that this could be a really valuable thing
and it seems like a thing I could do, provide value in.
So I put my hand up and said, I think I'd like to move my job in this direction.
And they said, yes.
And the storyteller part, I was casting around for something and I defined my criteria first,
kind of.
I said, I want something that communicates at least to some people.
I can't control what everybody thinks about me.
So I just let go of that to start.
But I want something that communicates a combination of technical chops to some extent, whatever
technical chops are needed and artistic pen.
Like goes back to my university degree, we put together like all the disciplines and
we're like, the idea was you use whatever you need to design and build things for actual
people.
That was a bread and butter.
So I've taken that with me and I want to use whatever scientific and or artistic methods,
creative and or technical that's going to do what I need to help people.
That's great.
I think I've seen so many times out there, whether on LinkedIn or just presentations,
even where there's this illustration of Legos, where you've got the mess of them and that's
just data in the raw.
And then you've got another layer where it's color coordinated and they start to cleanse
it.
And by the end of that illustration, it's the Lego house is put together.
All the colors are in the right place.
And I think it's an illustration that says that's data storytelling.
Well, as neat as that illustration is, give us an example of like successful data storytelling
from your perspective, Matt.
Sure.
Can do.
I'll talk about some recent projects I've done slash am doing.
Some of them are kind of iterative.
We do them a couple of times a year.
So one example is snapshot survey is what we call it.
It's just a survey of everybody involves like it's a national organization with a lot of
local chapters, you could say.
And so everybody who's leading in those local chapters wants to know, Hey, what's going
on on the grounds right now around me that I maybe can't see.
So we survey all the students we can gather stuff together and people want to know, Hey,
what did the survey say?
And so that's been my job.
I was the first person to do this as we were just trying out the survey thing.
And it's nothing impressive on the tech stack.
It's Google Sheets.
That's we live in Google and I know my way around some Google formulas.
Again, as I've needed to learn them, I've learned them.
And I designed and built super simple Google Sheet that can be exported to PDF because
that's what people wanted.
And it's got the stuff that hopefully they need and I won again, maybe sticking point
as I go through this process every single time is I want to hear what people actually
need and not just build the stuff that I think is cool or I think the data is saying I tend
to lean toward.
I know you can start from the data and what does it say and explore that that's a valid
way to do it.
I'm learning, but I tend to lean in the other direction and start with, Hey, what are the
people actually need?
What are they expecting?
Out of that, what can we do with the data?
So that's a bit more about posture, but with one concrete example.
And I think you're hitting on like we can always start from different ends of the spectrum
and arrive at conclusions and inevitably there's going to be bias that enters into that process,
especially if you start with asking the question, well, what do we need?
How do you protect against confirmation bias where, okay, this is what I needed to know.
So I went out and I found exactly what I needed to know and it just told us what we already
thought we wanted it to say.
So how do you guard against that?
It's important.
I think you're bringing up a really valid thing where you want to be human centric,
that you want to understand what is the business need and back your way into the right kind
of data solutions that will answer those.
But how do you guard against that bias that can easily creep in if you're focused on data
points that you know will confirm what you already know to be true or want to have be
true versus looking at all the data?
Yeah.
Oh, great question.
And I'm smiling a bit though.
You can't see it as you're listening to this because just recently a senior leader in our
organization has a lot of wisdom and experience.
He philosophized a bit and said, you know, confirmation bias is kind of off the rails
in our kind of organization.
And I can see how that's the case.
So yeah, we've got to watch out for that.
A couple of things that come to mind.
Number one is having people around me who think differently than me and you have more
technical chops in like the science or statistics area because I've in that survey project had
somebody alongside me who took some basic research courses in university and I said,
hey, we should maybe go about things this way.
And he's like, no, that's the wrong way.
So have somebody who can tell you, no, that's the wrong way is one thing.
But another is going about trying to I tried to design the presentation of the data in
a like relatively neutral way.
I know things are always going to be subjective, but they don't have to be arbitrary.
That's another opinion point that I picked up as I go along.
Since I try to make it intentionally, so not arbitrarily say, hey, this is just what's
going on.
Like this is it's always going to be imperfect because it's always a model of reality.
It's not reality itself.
But here are some like graphs with scales that represent things with the whole perspective.
I don't crop the graphs to make them show only part.
Like there's a lot of this probably sounds like people are not along, nodding along going
like yeah, duh.
But it's being intentional in all the choices along the way and keeping in mind like, oh,
how is somebody going to interpret this?
What might they think?
And also finally thought final thought is actually talking to people after they've used
the thing.
And as much as I know it can be painful to get or to give feedback after you just use
the thing, I try to coax that out of people and always ask like, hey, what was good?
What was not so good?
And how can we get better?
So I picked up a couple frameworks for doing that.
And I make sure to do it as much as I can and just hope that people don't find me super
annoying as man, he's the feedback guy because then you take what they said and you make
something useful out of it.
And that's good.
Anyways, I drifted a lot in that answer.
I'm curious about something in there you mentioned because storytelling and then also presenting
data in a neutral way and even how those go together because sometimes I'll hear data
storytelling where you're crafting a specific narrative that has key points and then a conclusion
that someone should get to along the way, or at least that's one way to craft storytelling,
what you're describing though, you also mentioned presenting it in a neutral way or as subjective
as possible without it being to avoid a sense of bias.
So tell me how those kind of blend together having a neutral opinion and presentation
and trying to craft a storytelling element to it.
Yeah, I'm definitely just starting to figure this out too, along with everything else.
But I've heard enough to know that, oh, this is a thing that people talk about a lot.
So probably a good props to you for asking the question.
And my best responses, as usual, come from stuff other people have said.
One is to harken back to my speech communication course in university.
Actually, and they like traditional rhetoric.
There's a few different things you can do with communication.
You can inform, you can entertain, you can persuade.
And it's good to just be conscious of which one you're trying to do and try to do that
as ethically as you can, in short.
And there's going to be a mix, obviously.
But if you come out of the gate and say like, hey, this is the conclusion, then for one
thing you better have a lot of evidence to back that up.
And then you can have somewhere else for people to dig into the data.
That's something I'm playing with now is conclusion, then evidence, then data.
I can give you the citation for where I got that if that's helpful.
And then another thing is knowing what you're trying to do and being upfront about that.
Like don't be too sneaky.
It's okay.
Actually, one way of serving people, according to a LinkedIn post I saw recently, is to give
them what they need in as little time as possible.
And they don't have time to wade through everything.
So sometimes you're going to choose to give the conclusion upfront.
It's going to be short.
But make sure you've got the evidence to back it up if and when people want to dig in deeper.
That sounds like a little bit of the artistic side to this and a technical side to this.
You said you're approaching problems with some sort of mixing of those two and how you
order the equation of whether the conclusion is coming first or whether the data is coming
first.
Sounds like you maybe would start from more of an artistic and a design perspective rather
than the technical.
How do you make those decisions about I'm approaching this from a technical lens first
or I'm approaching this from a design and artistic lens first?
Yeah.
Good question.
And so far, my response has been to lean on processes that other people have already
figured out.
Generally, what I try to do is figure out how people make these decisions and how they've
already done it.
And then if I can learn that how, I can go apply it in different appropriate settings.
You got to know when to use the tool and when not to use the tool.
So one tool I found helpful in this area comes from a book called Good Charts by Scott Baranato.
And it's talk, sketch, prototype, three-step process where first you talk about the need
and what you're trying to do with data, the thing that you're trying to make, like some
kind of chart presumably.
And then you sketch out, hey, it could look like this or it could look like this or it
could look like this.
And you talk ideally with the people who are going to be using it, but at least with people
who kind of know the basics of the situation, say which one looks good.
And then you can build a very basic prototype and go test it and validate or invalidate
certain parts of what you were thinking.
And you kind of repeat it, talk, sketch, prototype.
And I don't know if it even fits in either technical or artistic.
It's just been useful.
And it has a lot of similarities to another approach I default to a lot, which is design
thinking as things like inspiration, ideation, implementation from firms like IDEO, IDEO.
You can go look that up.
And yeah, it seems to have a good marriage of both.
Because at some point, you got to know some technical stuff and you got to know what's
possible and what's not possible.
But I try to center it again on humans.
So technical comes up, I guess, if I had to pick one, maybe it's artistic, but it's just
a process.
So design thinking, that's something I hear about in the world outside of data.
And I don't have the background in design thinking.
So how would you, and probably some of our listeners don't have a design thinking background
or they're technical nerds like me.
How would you orient me to that topic of design thinking?
Or maybe like some of the core principles I would want to have if I were trying to practice
that into my daily life?
Yeah.
Thanks for asking.
This is fun.
I like talking about it.
And like I said, using it.
I'll point, I'll pause and note that you mentioned like people may not have a background in this,
but I'll point out people do have a background in other stuff too.
And I'll just advocate, don't be afraid to, in fact, maybe lean into using other areas
of your life to inform the quote technical stuff.
Don't keep it all walled off.
The best creative stuff.
And even if you think of yourself as technical, I think you are creative.
Best creative stuff comes from making connections across different disciplines or across different
areas of your life.
Have some fun and play with that, which is actually, I think also a tenant of design
thinking is creative play.
So one way to talk about it is again, the process of inspiration, defining a problem
is usually one part of the process.
And this is one area where maybe you can just skip ahead a bit and do a Google search and
it might be a bit, make a bit more sense to you, but this is how I've experienced it.
You define the problem, you figure out like who you're trying to serve exactly what they
need and then you use some divergent thinking.
So like think up a whole bunch of possibilities of how you could solve that problem.
And then you converge to like, okay, actually it seems like this one's going to be good.
We're going to actually test it out and you prototype it.
And from that you can decide, persevere or pivot.
So this is also getting into lean startup methodology, which is a really similar process.
If that makes more sense to you, as you look it up, go use that, like just go use something
and try it.
But it's that idea of define the problem, then try something, think of ideas, narrow
them down to one, try something out, repeat until you have made something valuable for
some other person.
And there is that company, I think you mentioned it already, Matt Ideo.
And they've got some videos that you can kind of watch how they've done their design thinking
and they've come up with how they designed grippers for toothbrushes or, you know, grocery
carts for the grocery store.
And they follow this design thinking.
It's a neat pattern and it's cool to hear, Matt, how you're bringing that into the data
world.
And usually I've thought of design thinking as something when I'm going to design something
very concrete, very like just a daily tool that I might use in toothbrush, like a toothbrush.
Exactly.
And yet here you are, like you said, taking those ideas and concepts and building a bridge
into these less concrete tools in that we're talking about systems of data and relationships
of data and how to then wireframe that into a report and get feedback on a wireframe so
that I've got the right chart to display to my end users.
Really awesome stuff.
I'd like to piggyback on that to talk about some strategic objectives.
You know, that is a core of what we talk about as these mission driven, non-profit, private
sector type of data leaders.
What are some of the strategic objectives that you have had to aim towards and think
through?
Okay, I heard that strategic objective.
Now what's that problem I'm trying to solve?
So just give us a few more examples, maybe even related to that survey project you talked
about earlier.
What was the strategic objective in that and any others if you've got some that come to
mind?
A note on what you said is getting in the way of my thinking of that.
So I'll just say that you're also not just designing like data and stuff, you are designing
an experience for a person.
And that's the reality that I think we should keep in front of mind.
The data is there to serve the people, not the other way around.
Let's design an experience well.
Okay, onto your question, strategic objectives.
I might actually need to clarify.
Are you talking about strategic objectives for like how we're going to chart a course
for our data use or strategic objectives of the organization that we use data to accomplish?
Right, I'm thinking of the latter.
It's the mission of the org.
And so how does your data help meet one of those objectives for the org?
Yeah, thanks for clarifying.
Yeah, sure.
Okay.
Yeah, if we start with the survey example, the objective of the survey is basically get
a pulse on our population, the people who are benefiting from our services.
And specifically, it comes from some really strong strategic leadership that our national
leadership team did within our org.
And they set out a like playbook of here are our strategic anchors, here are our values,
and here's like where we're going in some really concrete terms.
So then survey project was kind of birthed from saying like, hey, how about we check
whether we're doing this with the people we're working with?
So the survey was basically transferring a good bulk of it.
Like it's used for a few different purposes.
You imagine lots of people want to know lots of different things.
But one core part of it that we have kept the same over a few years now is basically
just asking, are we doing what we're doing according to our strategic anchors and our
values?
We're asking people who are actually on the ground and asking them in an anonymous way
like, hey, what else can you tell us?
What else are like, are we on track or not?
And we've gotten some good info from that that has led to some concrete decisions of
like, hey, we should try this, or maybe we need to pay attention to that.
And we pay attention to that at a national and local scale.
That's one thing.
And there are a few others.
A lot of the rest is kind of a bit more scattershot in that, A, we're trying to figure it out.
And B, it covers a lot of different sections of the organization, which I'm still just
starting to figure out.
But we can talk about those too, if you want.
Matt, as I'm sure you described the surveys and working within leadership, I expect there's
a probably an orientation around data that's newer for leadership.
I think about like data literacy or being able to understand and interact with data
effectively.
And even you don't come from as technical of a data background, more of a design background.
I'm curious how you've helped yourself grow in maybe your ability to understand and interpret
data or how you've had to help leadership and people you've been presenting data to
help them to understand.
When you present data to them in like an objective way or a neutral way, there's going to be
some interpretation that they're doing on that.
How have you helped people navigate that, either yourself or other people?
Yeah, great question.
So I'm hearing about how do I get there and how to help other people get there.
Start with the first in short, I get there by reading a whole lot.
I'm a nerd in lots of areas of life.
So I've got a bunch of books and we can like throw them all in the show notes or something
because I don't know that everybody wants to hear me list all of them.
But yeah, and I find that reading has helped me, especially the stuff that I don't really
understand.
Like I've got a copy here of the Data Warehouse Toolkit by Kimball on recommendation by somebody
very wise.
And I don't understand a whole lot of what's in there.
And that I've learned since the beginning of my undergrad.
That's really valuable, being able to know, like, I don't yet know this, I don't yet know
that, but this is kind of the lay of the land of what is possible.
And I try to get to know the stuff that I need to know for the task at hand while also
paying attention to what else is out there, what else is possible.
Another book I have is a bunch of interviews of data viz professionals.
And I took copious notes through that and I'm like, okay, so this is how you do this.
Oh, this is a way to think about it.
And so I try to take from all sources I can of like different mental models, different
ways of thinking about the world.
And then I can use those again as tools in the appropriate situation.
So listening to lots of people have already figured it out and trying to take the 20%
as far as I can tell of what they do that can give me 80% or more of the results.
As for other people, it's been first trying to understand where they are and what's typical
for them.
So I have a list of questions I tend to ask at the beginning of a data project, which
is taken from yet another book.
And that list of questions includes things like what kind of charts are people used to
seeing?
What's going to be typical for them?
What's going to be atypical?
Because especially if it's people I haven't interacted with, I have no idea.
So I try to ask people if I've done some kind of internal consulting work, like working
with people who I don't work with usually and producing some one-off reports.
And I ask them, hey, what's typical?
What's not?
And then I can gauge whether I want something typical or not.
But if I don't even know that, I guess that gets back to helping me.
I'll say one more thing about the people, like helping people understand.
And it's kind of defaulting to the simplest and or the, yeah, again, most typical if you
understand that.
But simplest can have a lot of value.
Like I read a line in one of these books that said, like, why design a chart if you don't
have to?
If you can just convey stuff in words, then maybe that's best.
So right now I'm playing with a Google Sheet that reports on one of our KPIs.
And the display is not a scorecard or a chart or graph or anything.
It's like some if statements that spit out a sentence.
And so far people have said that's really helpful.
That's all they need to know.
So keep that in mind.
Maybe you can just keep it incredibly simple and you don't even need all the fancy data
wizardry.
I know it's tempting.
Use all the tools and stuff, but you might not need to.
That's interesting.
The textual data or textual visualization of data is what it is.
Like hey, we're going to just scribe in paragraph or sentence format.
In Power BI, they've always had charts, bars, graphs, pies, et cetera.
And that was the way I always defaulted to doing visualization.
And then they introduced with kind of the advent of generative AI, it's even more so,
but some sort of like narrative summaries of like you can put a chart on the visualization
on the canvas and then it will summarize in a couple of paragraphs what data is being
visible there.
So people have a paragraph way to consume the information in text.
And that's just a different way of experiencing data.
And it comes back to, I think what you're talking about where you started like with
the human experience in mind of how is this human going to experience it?
Some humans might interpret charts really well.
Some humans might interpret paragraphs a lot better or more effectively.
Yeah.
So I'd like to ask a question around aspirations.
So Matt, you've talked a bit about like where you and where the company is at in terms of
some of this is new, some of this you're still figuring out or it's a bit scattershot.
And that's okay, because I think we're all there.
And so I think for our audience, love to hear some of your aspirations, whether they're
personal for you as a data storyteller, but maybe even organizationally, where do you
see the organization going?
Where would you like to see the organization go around things like data literacy, maybe
tech stack in terms of maturity and the tools you're using.
Maybe it's even just the collaboration that you desire to see around data when let's be
honest, I think we've all lived in siloed data realities where, well, this department
has data for their department and they're not allowed to see data from another department.
And that's hard.
It's hard to break down those walls.
So I'd love to hear just what are your aspirations to keep growing in data and maybe even some
tips and tricks, maybe things you've used to actually see some of those aspirations
become realities.
Yeah, that's a good question.
I think one thing I'm holding onto for now for myself is I want to design and build useful
things.
And honestly, even being in data, being again, relatively new to it, it's a tool and it seems
like a really cool place to play.
So I hope I'll be here for a while playing with data.
But if I can help people help understand the reality as it actually is, ponder some possibilities
of how we might make it better and then act on those to make reality better for some people,
I'm pretty happy, especially if and when I get to learn stuff along the way, can the
nerd piece comes in.
So that's as long as I can keep doing that, I'm going to be relatively happy, I think.
But I also would love to keep learning what is possible and then creatively building a
creative practice actually, which might sound really foreign to nerdy people.
It's still a bit weird to me, but I'm learning from the creative people in my life.
I'm actually in a department that's full of them.
And I'm learning that there's something about making stuff that is inherently creative.
So you could even use that word for yourself.
And when you make stuff, you should be intentional about getting better at that.
So I want to be intentional at getting better at actually making stuff because I can live
in my head a lot of like, oh man, this would be cool.
But then at the end of the day, it's in my head, not in reality.
So I want to get better at actually making stuff through a creative practice.
So if that sounds like you, definitely get in touch because another thing, an aspiration
is getting connected to people who want to do similar work even.
I started off asking who is doing similar work and for all kinds of reasons we don't
need to go into, there wasn't a good connection.
And we tried real hard finding some people.
So I defaulted back to, I'll just read a bunch of books and connect with people that way.
But I would love to have somebody who's got a similar bent, either in the technical or
in the creative artistic side.
I think we could build a team that blends the two together and designs database stuff.
And even if it's not a department, even just like projects, I actually would kind of prefer
to take on stuff on a project basis rather than long-term, but that's getting into personal
career stuff.
One more thing about the bigger picture, I kind of touched on it already.
I've been talking a lot about what reality actually is.
And then you get maps that are representations of reality.
My minor in university was in geography.
So I think in maps, and I think it's actually really useful to A, recognize that reality
is out there and your map is not reality, but B, maps can be really useful, especially
when everybody's looking at the same map.
So this is kind of off the cuff, but I would love to see some version of people in the
organization, whatever chunk of the organization, because ours is a bit complex, multiple people
looking at this from different parts of the organization, looking at the same map and
saying, yeah, that's what we need.
We're starting to get there somewhat in our little corner, but I'm not sure that our map
is going to jive all that well with other people's maps.
And so we'll have to figure that out.
So actively figuring that out is definitely where I'd want to be as for tech stack and
stuff.
I'm starting to play with Tableau and we're leaning into it a bit.
So sure, if it's useful, great.
If not, if Google Sheets proves to be better for some stuff, I'm not above using that instead.
You've mentioned this a couple of times of making things that are valuable or making
things or getting better at making your art or creating or creativity.
This might be too, I don't know, philosophical, but how do you know if something's more valuable
or getting more valuable or if you're becoming more creative or getting better at being creative?
What are even marketed that?
Creativity is one of my words that I have held and embraced of like, I am trying to
express myself creatively more in different ways, in challenging ways for me.
And I'm trying to chew on what does that look like for me to be more creative or to be better
at being creative?
So I'll love that one and see where that takes you.
Yeah, sure.
So I think we share that Sawyer.
I have seven ideas or values that I hold.
I'm again, holding on to for now and holding on pretty solidly because I like my life values.
Creativity is one of them.
Curiosity is another, as you might have guessed.
But you didn't ask about that.
It's like, how do you get better about creativity?
Because we both value that.
I once again, I'm trying to pay attention to and pick up work from other people.
And there are people like Austin Kleon, who's an artist and he talks about creativity.
I can't think of the names of his books right now, but I've read one of them.
And yeah, his like him and a couple other people who are doing this well, including
a data person, Ali Torban, who wrote Charts Spark, her whole book.
So if you want to get better at data visualization type of creativity, go read Charts Spark and
do some of the stuff because there are actionable prompts in there, some of which I found really
useful and others of which you might find useful.
That's my short answer, but the theme I get from that book, from Austin Kleon stuff, from
other designers that I'm learning to respect is, and the thing you can hold me accountable
to if we talk again in a year or something, is you just got to actually make stuff.
And then you got to keep making stuff and ideally share it with other people and get
some idea of whether that stuff is useful to them with the idea in mind, with the keeping
in mind that sometimes the use or the purpose is attractiveness.
Sometimes it's utility.
Sometimes it's soundness or reliability.
Those are, I've learned three things that the ancient Romans used to assess their architecture
or to guide their architectural doings.
So you can take any of those purposes and be like, is it better at that purpose?
And get an idea between yourself and others.
But you also kind of just need to trust the process because not everything can be graphed
perfectly, including creativity.
And you got to know that as you continue making stuff, ideally in community, you're going
to get better at it.
Practice makes progress, not perfect.
And part of creativity is also things that you're going to try things that don't work
and fail.
And so there's the, hey, did that serve one of those, that utility or beauty better?
No, that one failed.
I tried something different that didn't work.
That's a hard part of what makes creativity hard for me.
And it's like, oh, I'm going to try something and it's going to break and fail.
No one's going to listen to my podcast and whatever.
But those are the things that come up for me when I think about creating the max and
realize they might fail or they might be valuable.
And I won't know until I start trying and iterating on those things.
Matt, as you've thought about these gifts and mindset and thinking that you have around
design thinking and storytelling and creativity, as well as data, why have you decided to apply
them in the organization you're in?
Why does the organization matter to you?
Why is that where your career has landed you now?
So tell us a little bit more about where you're at and maybe why you choose to brought your
gifts to that place.
Yeah.
I'm working at Power to Change Students, which is a Christian nonprofit here in Canada.
And it's like, I was going to say loosely connected, but like medium strength connected
to crew in the States and all around the world.
So we get to better from and also hopefully serve people all over the world.
But we're focused on Canada and it's about student experience like university or post
secondary, I guess, college student experience across the country.
And the why it matters to me is I got involved right in university and thought, this is a
really meaningful place to apply the gifts that I have these mindset shifts I'm developing.
I think that could be really useful over here.
Another thing was my degree is kind of weird and isn't career focused by its very nature.
It's called knowledge integration.
And at the end of university on a practical note, I was like, what do I do with this?
And one real possibility was join up with this organization I know I care about and
pioneer into something new.
At the time it was social media and then advertising and now it's data.
But they were like, nobody's done social media.
Want to come try it?
I was like, this seems like it could be a good fit.
Again, not because it was social media, but because it was the organization working towards
something I really care about.
And I've gotten to continue exploring since, which I've learned is a value of working in
this particular nonprofit.
That's cool.
And talking about creativity, I have to ask you, when you put a data analyst together
with someone who can play music, what do you get?
Oh man, I don't know.
A disk jockey.
Okay.
Took me a moment, but I think I got it.
Sawyer, did you get that one this time?
I mean, it was like a disk of data, like a hard drive.
Yeah.
Okay, I think that's probably where he's going.
But like, I don't work with that anyway.
I was trying to be as punny as possible.
See, this is one of those things where like our data becomes so abstracted from physical
hardware that we don't think about disk of data anymore.
What is a CD?
Those kind of things.
I'm just old enough to- Yeah, yeah, yeah.
Floppy disk?
Troy, are we talking about floppy disk?
Okay.
Yep.
That's exactly where I was going here.
All right.
Good.
Got right to the disk.
Matt, this has been a really fascinating conversation in a different direction than we have gone
with other conversations in this space or that I've had in this space for a while.
And I'm curious if people are interested in connecting with you more about these topics
you've mentioned wanting to have dialogue partners for some of these things.
Where can people find you online or find out more about your organization if they're north
of the border here?
Yeah, or if you know people heading north of the border, the organization I'll start
with that is p2c.com slash students, like p numeral 2c.com slash students.
And you'll find out about us.
Maybe you'll even come after we launched the website, the new website that we're having
in a while.
And you can connect with me personally on LinkedIn is a good default.
I'm just Matt A Brody.
I hope to get in touch with some people.
This has been I've got a couple of things I need to talk with you about after this,
Matt, because you've sparked some things that I need to follow up with you on.
I hope some people in our audience, I'm sure people in our audience have also taken away
some core principles around design thinking and creativity and data.
And I hope it's I know it's been useful to them.
Thank you for listening, Matt.
Thanks for joining us, Troy.
Troy, always a pleasure.
And thanks everybody for listening today.
That's all for making data matter.
We'll see you again next time.