00:00:00.017 --> 00:00:04.537
How can we find game-changing insights from our research?

00:00:04.817 --> 00:00:09.537
We're talking about the kind of insights that lead to viral apps or services

00:00:09.537 --> 00:00:12.857
that seem so obvious after they become the new normal.

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If we set out to create something groundbreaking, how can we capture the right

00:00:19.437 --> 00:00:23.577
knowledge at the right time, which would be sometime early on in the project?

00:00:23.817 --> 00:00:30.717
In other words, what method can we follow to find the revolutionary answer we're looking for?

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What if I told you that most teams are skipping certain particular steps that

00:00:37.417 --> 00:00:39.777
could have changed both what and how they designed?

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Today, I'm excited to share a conversation I had with Larry Marine,

00:00:44.757 --> 00:00:46.617
who I'll introduce momentarily.

00:00:47.157 --> 00:00:51.577
Together, we explore questions like, what is disruptive research?

00:00:51.577 --> 00:00:56.737
And how does it reveal insights that get missed by more commonplace methods?

00:00:56.937 --> 00:01:02.197
What happens when we view users and processes in terms of knowledge?

00:01:02.237 --> 00:01:04.857
And where do personas fit into all this?

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And how can cognitive science help us build products and services that support

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how people think and behave?

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By the end of this episode, you'll have a clearer lens for evaluating your own

00:01:17.737 --> 00:01:22.857
research practices, and you'll have a set of tools that you can use to uncover

00:01:22.857 --> 00:01:27.337
insights that are deeper and for my entrepreneurial folks,

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more disruptive to your marketplace.

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So let's have a listen as I introduce and speak with today's guest.

00:01:36.157 --> 00:01:41.637
Welcome to the Design Psychologist podcast. I am your host, Thomas Watkins,

00:01:41.817 --> 00:01:44.377
and I have a really special guest today.

00:01:44.497 --> 00:01:49.557
I'm really excited to have Larry Marine, who is a veteran UX researcher.

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He started back in the day as a cognitive scientist and a human factors professional,

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and he's accumulated over three decades of success stories spanning across a very wide scope

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of applications, military, all types of B2B, all types of B2C.

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He is a methodologist who is really good at distilling down these steps and

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the reason why you're doing those steps when doing a methodology.

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We're going to talk about some of those today.

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And he works with his distinguished colleague, Debbie Levitt.

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Larry Marine is the author of some very

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influential blog articles including task analysis

00:02:32.104 --> 00:02:35.624
the key ux design step

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everyone skips that's when i first discovered him he wrote that back in 2014

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it's all over the internet and i discovered uh larry through that work and he

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is also the author of disruptive research do you also have your copy there okay

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you do you have to hold it in front of you because you're for people on video

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are holding up copies of the book.

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Yes, this is my current favorite book.

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I highly, very much would recommend all UX researchers or people interested

00:03:03.684 --> 00:03:08.924
in UX research, or even strategy should be reading this book.

00:03:09.064 --> 00:03:10.184
And we'll talk about that today.

00:03:10.724 --> 00:03:12.484
Larry Marine, thank you for being on the show today.

00:03:13.204 --> 00:03:17.404
Oh, thanks for having me. Glad to be here. Awesome. Awesome. Glad to have you.

00:03:18.744 --> 00:03:21.684
So I laid out some of your background there.

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Is there anything you'd like to add to that to help give people context of,

00:03:26.284 --> 00:03:29.164
you know, what kind of perspective you're going to be coming from today?

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So I think one of the things that a lot of people don't know is I was in the

00:03:34.544 --> 00:03:38.004
first graduating class of cognitive scientists in the world.

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And Don Norman was my professor. I had him for like five or six classes.

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So I'm what you call

00:03:47.744 --> 00:03:50.564
original gangster that's right he is

00:03:50.564 --> 00:03:53.224
an og yeah and

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that was in 88 correct uh that's when

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i started that program i graduated in 90 nice nice

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and so yeah that's during the time that really you know if you wanted to give

00:04:05.804 --> 00:04:10.484
a sort of a birth date to what we call modern usability i think it would be

00:04:10.484 --> 00:04:13.964
somewhere around there that's one of the some of the major books were starting

00:04:13.964 --> 00:04:19.264
to hit the market That's when Don Norman published his book,

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Design of Everyday Things Actually,

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back then it was called Psychology of Everyday Things And it got put in the

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wrong bookshelf at the stores So he changed the name It reflected it's more

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about design than it is psychology Although it really gets into understanding

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the human from the psychology perspective Rather than just,

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oh, they're a user But what does that really mean?

00:04:44.852 --> 00:04:48.572
Exactly. So, and I'm glad you pointed that out. That's a good piece of history.

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I think that's interesting.

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And so let's start off by getting into the use case.

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You've got lots of use cases out there, but one of the ones that people will

00:05:01.392 --> 00:05:06.472
mainly come across from you is the ProFlowers example. That's my best story.

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That's the best story. And I think it's a nice beachhead. It is easy to understand,

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like anybody can understand the use case.

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And I think it highlights this phenomenon that it's easy to think that something

00:05:19.512 --> 00:05:23.832
is obvious now, after it's been created, after something's been around for a

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while, after things are a certain way, it's easy to hear, oh,

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of course you would do it that way.

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But there is no of course, it has to be, it has to, people have to arrive at

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this. So tell us a little bit about the ProFlowers example, anything you want

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to say about it for folks who haven't heard about it.

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Yeah, so it was interesting.

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I like that perspective of, oh, it seems natural now.

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But when we did that, that was back in 97, nobody had done a website,

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a flower website, like the way we did for ProFlowers.

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And the big difference was people

00:06:01.832 --> 00:06:04.992
were designing it based on what they knew so florists were

00:06:04.992 --> 00:06:07.992
designing florist websites and what do florists

00:06:07.992 --> 00:06:10.872
do they build bouquets well when we

00:06:10.872 --> 00:06:13.952
went out and did observational research in the brick

00:06:13.952 --> 00:06:16.612
and mortars instead of watching people build you know

00:06:16.612 --> 00:06:20.832
try to use a flower shop online we went out and watched people to use a flower

00:06:20.832 --> 00:06:29.232
shop in a brick and mortar and what we learned was you know just observing the

00:06:29.232 --> 00:06:33.272
guys would walk in and most of the people buying flowers at the time were guys

00:06:33.272 --> 00:06:36.032
buying flowers for women guys would walk in.

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And they'd look at the display case clerk would come up says can I help you

00:06:41.392 --> 00:06:45.492
says yeah I need some flowers oh sure that's why you're in a flower shop I get

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that now what do you think the next question was that the clerk asked it wasn't

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what flowers do you need it was why do you need them.

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Right it was not about the flowers it was about

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the occasion or the reason and so we designed

00:07:02.051 --> 00:07:05.271
the pro flowers around that so instead of organizing

00:07:05.271 --> 00:07:11.411
the flowers by the flower types chrysanthemums wrote you know florida roses

00:07:11.411 --> 00:07:17.631
we organized the bouquets around the occasion that they were appropriate for

00:07:17.631 --> 00:07:24.711
not every occasion works for every or uh not every bouquet works for every occasion You know,

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you don't want to give flowers that are a sympathy bouquet to somebody when

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they're on their 30th birthday. That's sending the wrong message.

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But the thing is, like I said, no other websites were organized that way at all.

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And it wasn't until ProFlowers came out that all of the other websites changed.

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So here's a little side story that you probably never heard before.

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And it's in the book but um when

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we designed pro flowers we gave the design

00:07:56.891 --> 00:07:59.811
spec basically it was like this screen

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has to have this this screen has to have that but you can change the graphics

00:08:03.611 --> 00:08:10.971
if you want they gave this to a contract house out of chicago and valentine's

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came and a couple weeks later we get a call back from this the management of

00:08:16.631 --> 00:08:18.631
pro flowers saying we want our money back.

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What this is yeah the website failed miserably

00:08:23.091 --> 00:08:26.091
so i looked at it pulled it

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up on the website looked at my spec and go whoa so i

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had them come in and i walked through this is

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what they does they delivered to you but

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this is what i designed for you and so

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they called the developers and said what up and

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they said well you know didn't look like any of the other websites

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so we made some changes and those

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changes failed terribly and so they

00:08:51.231 --> 00:08:53.951
they told them rebuild it the

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way we told you to build it and it's not going to

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cost us any money otherwise we'll sue you for

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everything that we paid you well they rebuilt it and launched it on mother's

00:09:05.911 --> 00:09:10.571
day now at that time the average website was converting it around one to two

00:09:10.571 --> 00:09:17.391
percent pro flowers on the day that they launched It started converting,

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meaning convert a visitor to a buyer at 26%.

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And it stayed that way every month for 20 years.

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So that was a good A-B test of like, this is the way the developers wanted to do it.

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This is the way we wanted to do it. And which way do you think won?

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Obviously, you know, ProFlowers sold for almost a half a billion dollars here

00:09:40.851 --> 00:09:43.871
a few years ago. For a flower shop.

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That's incredible. And so not only was it a game changer for the company,

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it was an industry changer.

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And in fact, you talk about that

00:09:54.491 --> 00:09:59.091
a lot in the book about these kinds of industry changes and standards.

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Yeah, because a lot of people don't do the user research.

00:10:03.431 --> 00:10:08.471
They don't understand the users well enough to really look into what the problem

00:10:08.471 --> 00:10:14.291
is that they're trying to solve. What happens, I see a lot, is one competitor

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starts off with something and says, we have this green widget.

00:10:18.411 --> 00:10:20.611
Everybody else makes green widgets after that.

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Well, nobody ever thought to investigate, is that really the problem?

00:10:25.851 --> 00:10:28.631
So they end up solving the wrong problem very well.

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And if you go out and do the research and you look at beyond just the use of that one product,

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If you start looking at the whole spectrum of the user's experience or the customer's

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experience or the employee's experience from beginning to end,

00:10:47.811 --> 00:10:49.531
you find that there's a whole lot missing.

00:10:49.851 --> 00:10:54.811
So there's this one product I worked on that the company, my client,

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was focused on the fifth step of a five-step process.

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And what they had was a report that came out and people were complaining about the report and all that.

00:11:07.071 --> 00:11:12.151
Well, I went out and watched the entire five-step process. It was an all-night affair.

00:11:12.531 --> 00:11:19.011
It was for blood screening labs. It turns out that they weren't complaining about the report.

00:11:19.311 --> 00:11:23.371
They were complaining about they didn't trust the whole process.

00:11:23.631 --> 00:11:28.591
And so what I designed was as a management process or a management tool.

00:11:29.765 --> 00:11:34.105
Checked up on the five steps of the process to make sure no data was lost,

00:11:34.245 --> 00:11:36.625
no data was confused or anything like that.

00:11:36.965 --> 00:11:42.825
And so the end result was the lab directors, when they got that final report

00:11:42.825 --> 00:11:47.785
at the end of the night that, oh yeah, everything was fine, all of this blood

00:11:47.785 --> 00:11:49.625
is okay to release to the hospitals,

00:11:50.285 --> 00:11:53.005
they felt confident, they trusted the results.

00:11:53.165 --> 00:11:56.925
And that was what the real problem was. It wasn't the format of the report.

00:11:56.925 --> 00:12:00.725
It was the trust that everything went smoothly all night.

00:12:01.425 --> 00:12:05.785
And you wouldn't know that if you just looked at a list of feature requests

00:12:05.785 --> 00:12:10.325
or, you know, requirements and just went by that.

00:12:10.625 --> 00:12:16.905
Right. And so when you think about user psychology and a lot of people ask customers,

00:12:17.045 --> 00:12:18.665
well, what's your problem? What do you need?

00:12:19.645 --> 00:12:23.125
You know, psychologically, that's difficult for people to answer.

00:12:23.405 --> 00:12:27.925
And what they do instead of describing the problem is they describe a solution

00:12:27.925 --> 00:12:29.745
that they think captures the problem.

00:12:29.905 --> 00:12:32.385
And you're left to reverse engineer that.

00:12:32.605 --> 00:12:37.485
But if you don't understand psychology and understand that people don't describe

00:12:37.485 --> 00:12:42.325
their problems as well as they describe a potential solution, you would miss that.

00:12:42.465 --> 00:12:46.545
And you would try to basically build what they told you. But they weren't telling

00:12:46.545 --> 00:12:47.925
you everything that they know.

00:12:48.665 --> 00:12:56.285
Yeah. So now your book gets a lot into the psychology, specifically knowledge.

00:12:56.685 --> 00:13:00.985
Knowledge is a very central concept in your book.

00:13:01.065 --> 00:13:05.925
And I love that. Um, yeah, that's the big differentiator.

00:13:06.065 --> 00:13:12.145
You know, uh, I focus a lot on task analysis, but you know, task analysis has been around a while.

00:13:12.825 --> 00:13:17.605
Uh, Joanne Hackers and Jenny Reddish wrote a book about task analysis and I've

00:13:17.605 --> 00:13:18.605
referred that quite a bit.

00:13:18.705 --> 00:13:23.745
It's a good book, but now what I've done is taken task analysis and added in

00:13:23.745 --> 00:13:25.405
that, that knowledge component.

00:13:25.685 --> 00:13:28.545
Because when you think about it, what you're trying to solve with,

00:13:28.585 --> 00:13:35.345
with respect to your design is how do you impart your knowledge into the product

00:13:35.345 --> 00:13:40.445
or design such that the user doesn't have to think about things that they may not know.

00:13:40.805 --> 00:13:45.625
Good example, the pro flowers example. Guys don't know anything about flowers.

00:13:45.965 --> 00:13:50.705
They don't know what the right flowers or bouquets are for forgetting their

00:13:50.705 --> 00:13:52.825
wife's birthday, right?

00:13:53.345 --> 00:13:57.645
And so when instead of organizing it by flowers,

00:13:57.645 --> 00:14:00.905
we organized that by the occasion all the

00:14:00.905 --> 00:14:05.385
person had to do was recognize the occasion oh yeah there's birthday i'll look

00:14:05.385 --> 00:14:09.485
at the birthday bouquet oh my wife likes purple i'll take that purple bouquet

00:14:09.485 --> 00:14:14.425
they knew that they were getting the right bouquet for the right occasion because

00:14:14.425 --> 00:14:20.005
pro flowers imparted their knowledge of what was right into the design.

00:14:21.069 --> 00:14:25.209
And I think a lot of the reason why a lot of companies get it wrong is because

00:14:25.209 --> 00:14:27.829
they're just living in their own situation.

00:14:28.309 --> 00:14:32.629
So like, you know, you might be if you're a flower shop doing it wrong on the

00:14:32.629 --> 00:14:37.389
web, you'll say like, OK, well, here are the roses that we sell here, the tulips.

00:14:37.549 --> 00:14:40.729
Here are the things. And they're thinking almost in terms of their inventory.

00:14:41.029 --> 00:14:43.549
Well, the user shouldn't have to think on those terms.

00:14:44.349 --> 00:14:48.029
Right, right. You should be thinking of that for them.

00:14:48.029 --> 00:14:55.309
Your job is to identify what knowledge they already have going into a task and

00:14:55.309 --> 00:14:59.429
what knowledge they're going to need in order to solve that problem, that task.

00:14:59.689 --> 00:15:01.669
And then you have to bridge that

00:15:01.669 --> 00:15:06.169
gap by imparting your knowledge into the design in some form or another.

00:15:06.389 --> 00:15:08.849
And there's really four basic ways to do it.

00:15:09.089 --> 00:15:14.789
There's examples, templates, intelligent defaults, and best practices.

00:15:15.469 --> 00:15:19.229
And so so like apple great

00:15:19.229 --> 00:15:24.709
example of a best practice approach when the mp3s first came out they were all

00:15:24.709 --> 00:15:30.369
the rage and but they were pretty clunky to use first you had to go to mp3.com

00:15:30.369 --> 00:15:35.989
to be able to use to find your music download it create a directory on your computer.

00:15:36.869 --> 00:15:41.829
Go to music match to create a playlist of the songs that you had take that playlist

00:15:41.829 --> 00:15:46.089
and then upload it into the device with its proprietary software,

00:15:46.109 --> 00:15:47.809
and then you finally played it.

00:15:48.069 --> 00:15:51.669
Think about that. That was pretty technical, especially when,

00:15:51.789 --> 00:15:54.609
what, 25 years ago when they came out.

00:15:54.929 --> 00:16:01.709
That was a pretty technical task, and the average mainstream user couldn't do it.

00:16:02.709 --> 00:16:06.789
And actually, MP3 sales were starting to flat, and they weren't selling that

00:16:06.789 --> 00:16:10.269
many more MP3s because you had to be a techie to do that.

00:16:10.989 --> 00:16:17.249
So Apple looked at it, and they came out with the iPod, but it wasn't the iPod

00:16:17.249 --> 00:16:18.169
that made the difference.

00:16:18.449 --> 00:16:24.609
It was marrying the iPod with iTunes in the Apple Store that made all the difference.

00:16:24.749 --> 00:16:29.549
Because you would go to iTunes, find your music, and it would automatically

00:16:29.549 --> 00:16:35.749
download into the device when you went to charge it out.

00:16:35.909 --> 00:16:40.329
It would automatically upload the music in there for you. and it created four

00:16:40.329 --> 00:16:43.529
generic playlists, album, artist, genre, and decade.

00:16:43.969 --> 00:16:46.589
And then you could make your own if you wanted, but you didn't have to.

00:16:47.109 --> 00:16:52.829
So they basically used their knowledge of what a best practice approach was.

00:16:52.929 --> 00:16:57.249
So all you had to do is find your music, the system took care of the rest,

00:16:57.409 --> 00:16:59.829
and then play the music. It was that simple.

00:17:00.269 --> 00:17:07.889
And that's when the iPod went from, I think they sold 650,000 units of MP3s

00:17:07.889 --> 00:17:12.709
worldwide and the iPod in their third year sold like 20 million units.

00:17:13.787 --> 00:17:19.767
It was disruptive. And the, you know, it's the person who's using it wants a

00:17:19.767 --> 00:17:21.287
song. They want to listen to music.

00:17:21.547 --> 00:17:25.907
They don't want to figure out what kind of file and then they're downloading

00:17:25.907 --> 00:17:27.287
it and they're storing it.

00:17:27.667 --> 00:17:31.387
That's not. And so the Apple did a good job of meeting people where they are

00:17:31.387 --> 00:17:35.587
and achieved disruption like that. Well said, yes.

00:17:36.327 --> 00:17:41.787
Yeah. And so in your book, you talk about, I mean, disruptive is in the title disruptive research.

00:17:42.227 --> 00:17:48.627
And I find that you're getting at a concept that is a often romanticized concept.

00:17:49.407 --> 00:17:53.907
And, you know, innovators, they say, well, we're disrupting and we want to,

00:17:53.947 --> 00:17:55.447
you know, innovate and disrupt.

00:17:56.027 --> 00:18:00.047
And but they don't talk about how to achieve it. And you kind of get the idea

00:18:00.047 --> 00:18:05.307
that it just comes from, you know, an innovator business person and a turtleneck

00:18:05.307 --> 00:18:08.467
comes out on stage and they say, I've come up with a great idea.

00:18:10.287 --> 00:18:13.287
And then people try to repeat this.

00:18:13.487 --> 00:18:18.027
And a lot of founders, I'm sure you know a lot of founders, I do as well,

00:18:18.247 --> 00:18:21.887
where they're trying to come up with the next idea and you can tell they want

00:18:21.887 --> 00:18:24.967
this kind of a groundbreaking thing and it's hard to achieve.

00:18:25.507 --> 00:18:33.807
You and your book get into actually methodically how to arrive at the key insights

00:18:33.807 --> 00:18:37.487
that could lead to a disruptive invention.

00:18:37.927 --> 00:18:41.407
So do you want to unpack that a little bit for us? This, this idea of getting

00:18:41.407 --> 00:18:44.107
to those, those unmet needs?

00:18:44.427 --> 00:18:48.367
Yeah, I was actually thinking about that when I was telling the last story.

00:18:48.747 --> 00:18:52.807
So yeah, there is a method and that's what I learned from Donna Norman,

00:18:53.067 --> 00:18:57.767
by continually breaking things down into smaller chunks as you go along.

00:18:58.087 --> 00:19:02.267
You start out with the big picture. You do some, some research on the users

00:19:02.267 --> 00:19:05.827
or the problem domain. Then you go out and you watch the users.

00:19:06.367 --> 00:19:11.227
And by watching, I mean standing off to the side, don't interrupt them, just watch them.

00:19:12.207 --> 00:19:15.587
And then you start to take that information and figure out, okay,

00:19:15.667 --> 00:19:19.847
what was the process they went through? What was the problem they were trying to solve?

00:19:20.227 --> 00:19:23.447
And so that's where the task analysis comes in.

00:19:23.767 --> 00:19:29.387
And when you capture this notion about the users, you know, it's not the persona

00:19:29.387 --> 00:19:34.787
type information. It's more about what can you observe about their knowledge set?

00:19:35.465 --> 00:19:39.465
You know, because people are going to act based on what they think they know.

00:19:40.105 --> 00:19:44.645
And so you can observe behaviors and start to attribute some cognitive phenomenon

00:19:44.645 --> 00:19:46.605
to the observed behaviors.

00:19:46.745 --> 00:19:51.045
So you kind of capture that like that person didn't seem to know what they were doing.

00:19:51.065 --> 00:19:54.525
They looked at that thing three times before they made a choice.

00:19:54.685 --> 00:19:56.645
So obviously that's not very clear.

00:19:57.085 --> 00:20:00.645
So these are the kind of things you look for in the user. And then the task

00:20:00.645 --> 00:20:06.685
analysis breaks down what steps were they going through. And so you don't do it all at once.

00:20:06.865 --> 00:20:10.165
You break it down into, these are the five main steps they went through.

00:20:10.625 --> 00:20:13.905
And then you take each of those and break that down and break that down until

00:20:13.905 --> 00:20:16.305
you get to the atomic level, if you will.

00:20:16.965 --> 00:20:21.285
But you don't stop there. What you've done is just identified what the world

00:20:21.285 --> 00:20:23.145
is right now, what exists.

00:20:24.565 --> 00:20:29.005
Well, obviously something's missing, but you don't know what that is.

00:20:29.185 --> 00:20:33.465
And so you start to optimize the task flow. What if we could do this for the

00:20:33.465 --> 00:20:37.865
user? What if the system automatically generated that artifact for the user?

00:20:38.085 --> 00:20:44.465
What if we streamlined the task flow? What if we optimized their task?

00:20:45.325 --> 00:20:49.925
And you're always looking at, you're trying to achieve the desired outcome.

00:20:50.185 --> 00:20:55.565
The desired outcome, like you said, isn't to do all of these things,

00:20:55.665 --> 00:20:56.985
create directories and all that.

00:20:57.025 --> 00:21:01.925
It's to listen to music. Like as Ted Levitt from the Harvard Business School

00:21:01.925 --> 00:21:05.285
said, people don't want a quarter-inch drill. They want a quarter-inch hole.

00:21:07.485 --> 00:21:14.165
So the process in the book follows that pattern. Understand the users.

00:21:14.865 --> 00:21:18.845
Understand the task. Optimize the task. And once you've optimized the task,

00:21:19.065 --> 00:21:22.725
then you can start to see a strategy for that product.

00:21:22.905 --> 00:21:27.945
Like the strategy for ProFlowers was ProFlowers doesn't sell flowers. They sell occasions.

00:21:29.045 --> 00:21:32.345
And then you can start to design from

00:21:32.345 --> 00:21:35.265
that strategy because everything has to has to

00:21:35.265 --> 00:21:38.525
fit that strategy has to fit what the desired outcome

00:21:38.525 --> 00:21:44.605
is and then it fits into that that optimized task flow and the cool thing about

00:21:44.605 --> 00:21:49.505
the optimized task flow is you identify the different artifacts that the users

00:21:49.505 --> 00:21:54.425
are going to use like they have to use uh this screwdriver and this socket set

00:21:54.425 --> 00:21:55.645
things like that, right?

00:21:56.185 --> 00:22:00.305
You also start to identify what things the system can do for the user.

00:22:00.485 --> 00:22:03.405
Because when you optimize it, what you're trying to do is to get the system

00:22:03.405 --> 00:22:05.745
to do more of the steps for the user.

00:22:05.885 --> 00:22:11.025
And the user only has to acknowledge some or make a final decision somewhere.

00:22:11.705 --> 00:22:16.985
So what you end up with is, I use different color stickies. The yellow is for

00:22:16.985 --> 00:22:18.705
the system. The green is for the user.

00:22:19.105 --> 00:22:24.025
You end up with a few greens. And then all you All you have to do is design screens for the greens.

00:22:25.292 --> 00:22:29.392
Yeah. So in for in for the audience, you know, picture a bunch of sticky notes.

00:22:29.592 --> 00:22:33.872
And I think one of the takeaways that I take from this whole process before

00:22:33.872 --> 00:22:41.252
I dive into the sticky note process is that you have the human being in the environment.

00:22:41.252 --> 00:22:46.312
One of the examples I give is, you know, an app like Uber Eats or something

00:22:46.312 --> 00:22:50.272
like that, right, where it's a human looking for food.

00:22:50.432 --> 00:22:54.092
And humans have been looking for food for thousands of years.

00:22:54.772 --> 00:22:58.172
And we have whatever ways we used to do it.

00:22:58.172 --> 00:23:05.752
But the information architecture of the screen has to deliver the right information

00:23:05.752 --> 00:23:10.192
in the right ways to just so you're only thinking about the food that you want.

00:23:10.292 --> 00:23:12.312
You're not thinking about the screen and navigation.

00:23:12.872 --> 00:23:16.412
You're seeing, OK, those are that's a restaurant. I like the food from there.

00:23:16.612 --> 00:23:19.452
And then you open as OK, here's the menu. what type of

00:23:19.452 --> 00:23:22.952
thing and it pulls your thinking

00:23:22.952 --> 00:23:26.072
out of the interface and it

00:23:26.072 --> 00:23:29.432
puts your thinking onto the content that

00:23:29.432 --> 00:23:32.612
you actually are trying to to work with and

00:23:32.612 --> 00:23:35.372
as you mentioned in your book and i've heard others say it as well is

00:23:35.372 --> 00:23:37.992
that good ux is invisible so if you

00:23:37.992 --> 00:23:41.032
do it right you're really stripping away

00:23:41.032 --> 00:23:44.552
everything and you're you're trying to get the most direct path of

00:23:44.552 --> 00:23:47.612
the human being doing their work right it's

00:23:47.612 --> 00:23:50.772
almost intuitive like that's the way it should flow

00:23:50.772 --> 00:23:54.092
and that's what their expectations are that's what

00:23:54.092 --> 00:23:56.892
that's how you make it invisible they don't have to think about

00:23:56.892 --> 00:24:01.072
that navigation it just happens exactly and

00:24:01.072 --> 00:24:06.212
so so one methodological nuance i want to get your opinion about is um you mentioned

00:24:06.212 --> 00:24:13.752
um user uh the researchers doing research show up at the environment where people

00:24:13.752 --> 00:24:19.012
are doing their task and starting with naturalistic observation,

00:24:19.012 --> 00:24:21.072
you're not interfering.

00:24:21.072 --> 00:24:24.232
You're just watching, observing, recording.

00:24:24.632 --> 00:24:32.452
And then in your view, when is it time to do contextual inquiry or when is it

00:24:32.452 --> 00:24:35.332
time to bring in the subject matter expert to say, okay,

00:24:35.632 --> 00:24:40.732
from your expertise, what are the tasks, what order and how should those kinds of things interplay.

00:24:41.677 --> 00:24:45.637
Yeah, that's good that you mentioned that. So the subject matter expert is somebody

00:24:45.637 --> 00:24:50.157
that you might want to talk with early on so you can get a kind of a sense of the domain.

00:24:50.637 --> 00:24:54.437
Now, the problem with subject matter experts is they've been doing this a long

00:24:54.437 --> 00:24:57.137
time, and they're stuck in their ways.

00:24:57.617 --> 00:25:00.877
I mean, that's an oversimplification.

00:25:01.357 --> 00:25:04.557
But generally speaking, their way is the way.

00:25:04.797 --> 00:25:09.357
Well, in reality, it never is. There's always an improvement you could make somewhere.

00:25:09.557 --> 00:25:14.077
But at least start with them. And you bring them in after you've got some data,

00:25:14.077 --> 00:25:19.917
you know, to do a validity check, a reality check. Am I going down the right direction?

00:25:20.257 --> 00:25:25.597
You know, it's amazing. A lot of times you'll find something that they have

00:25:25.597 --> 00:25:29.577
internalized for so long that they don't even realize it is there anymore.

00:25:29.997 --> 00:25:33.197
And so it's kind of a surprise when you say, well, what about this?

00:25:33.337 --> 00:25:34.957
Oh, yeah, I forgot about that.

00:25:35.137 --> 00:25:39.677
Because it's so endemic to the way they do things that they no longer give it any thought.

00:25:40.197 --> 00:25:44.137
So you start with the subject matter expert and any, you know,

00:25:44.217 --> 00:25:46.317
buddy in the company that has any insights.

00:25:46.477 --> 00:25:50.257
And I like to go to the customer support people and talk to them.

00:25:50.377 --> 00:25:51.677
And I don't ask, you know, what's

00:25:51.677 --> 00:25:55.037
the most difficult part of the interface that people complain about?

00:25:55.117 --> 00:25:59.957
I ask them, what problems are people trying to solve? What are they trying to

00:25:59.957 --> 00:26:01.937
do that they're struggling with?

00:26:02.637 --> 00:26:08.097
So you get, you try to stay solution agnostic, you know, early on.

00:26:08.097 --> 00:26:13.337
So then you do some observational research, and you might even call it contextual

00:26:13.337 --> 00:26:18.377
inquiry because I like to do a post-observation interview with people if possible.

00:26:18.617 --> 00:26:24.377
Sometimes you can't because, you know, they're not available or you can't talk

00:26:24.377 --> 00:26:25.697
to them for whatever reason.

00:26:25.997 --> 00:26:31.917
But when possible, yes, do a post-observation interview. That's contextual inquiry right there.

00:26:32.217 --> 00:26:38.077
But you can't just ask people what they're, oh, no, not again.

00:26:38.097 --> 00:26:45.457
Again oh it looks like we're yeah i can still hear you for the technical technical

00:26:45.457 --> 00:26:51.177
difficulties just uh for the audience right there um yeah give you a second

00:26:51.177 --> 00:26:55.677
on there yeah can you can you still hear my light keeps uh turning,

00:26:56.567 --> 00:27:01.207
Yes. All right. Can you hear me? Excellent. Yes, I can. I think we're back.

00:27:03.427 --> 00:27:08.107
So one of the things you talk about in your book is when you're doing the research,

00:27:08.347 --> 00:27:10.887
things to do and things not to do.

00:27:11.307 --> 00:27:19.227
Right. So one of the things is you're you're working on a project and the workers,

00:27:19.467 --> 00:27:23.027
the users, if you're using B2B software, are using a current solution.

00:27:23.027 --> 00:27:25.727
And they have a tool that they've been

00:27:25.727 --> 00:27:28.967
using for God knows how long and everybody knows

00:27:28.967 --> 00:27:32.627
this tool and they've learned the the workarounds

00:27:32.627 --> 00:27:35.467
and they've got a cheat sheet at their desk of how to deal with

00:27:35.467 --> 00:27:38.207
all the quirky things and um and we've

00:27:38.207 --> 00:27:42.927
all seen that and so but one of the things that you point out is that if you

00:27:42.927 --> 00:27:49.527
research the tool or people using that tool you're missing an opportunity to

00:27:49.527 --> 00:27:53.847
learn just about the task itself because the person is kind of winding their

00:27:53.847 --> 00:27:55.487
way through the, you know,

00:27:55.587 --> 00:27:59.467
the peculiarities of the tool, but you want to learn about the task.

00:27:59.807 --> 00:28:03.447
What are some things you would recommend for situations where,

00:28:03.707 --> 00:28:05.867
well, that concept overall,

00:28:06.207 --> 00:28:11.467
but then following up, what, you know, what if it's kind of a quirky,

00:28:11.727 --> 00:28:17.687
weird, specific business task that it's hard to get a use case of them?

00:28:17.787 --> 00:28:21.367
What are some strategies that people can do when they're thinking about,

00:28:21.707 --> 00:28:26.147
you know, I want to research the task itself and not get so wrapped up in the tool?

00:28:26.647 --> 00:28:33.767
Yeah, that's the science part of it and where the art comes into the science.

00:28:34.067 --> 00:28:40.247
Because yes, you know you have to be somewhat agnostic, but you have to take

00:28:40.247 --> 00:28:44.907
that step back and say, what they're doing with that tool is dictated by the

00:28:44.907 --> 00:28:46.507
design of that tool right now.

00:28:46.847 --> 00:28:51.567
Is that really the task or is the task something more generic?

00:28:51.967 --> 00:28:56.767
So take the step back, try to be solution agnostic.

00:28:57.207 --> 00:29:00.547
Otherwise, all you end up doing is automating current frustrations.

00:29:01.617 --> 00:29:04.837
You know, if people are doing the wrong thing and you fine tune that,

00:29:04.997 --> 00:29:06.177
they're still doing the wrong thing.

00:29:07.137 --> 00:29:12.077
And so I've always looked at it like every, and to be honest,

00:29:12.117 --> 00:29:17.377
I've had over 250 projects in my 35 years of doing this.

00:29:18.157 --> 00:29:23.537
And every time the original solution was solving the wrong problem.

00:29:24.057 --> 00:29:27.697
So you have to take that step back and say, what is the real problem?

00:29:27.697 --> 00:29:32.237
And you start with, what is the problem that they're trying to solve?

00:29:32.797 --> 00:29:34.677
What is the desired outcome?

00:29:35.677 --> 00:29:39.757
So, for instance, dashboards. You know, dashboards are all the rage,

00:29:39.817 --> 00:29:43.297
you know, because they're pretty, you know, graphics and everything up there.

00:29:43.597 --> 00:29:47.137
But when it comes down to it, what are people trying to get out of a dashboard?

00:29:47.697 --> 00:29:50.897
They're trying to figure out what to do next. next and so

00:29:50.897 --> 00:29:53.697
a really good dashboard and i've got an example in

00:29:53.697 --> 00:29:56.617
the book a really good dashboard tells the user

00:29:56.617 --> 00:29:59.657
what they need to do not what's you know

00:29:59.657 --> 00:30:02.597
what their sales were last month or you know

00:30:02.597 --> 00:30:06.097
who's got the most sales or you know which advertising

00:30:06.097 --> 00:30:09.217
is working no they want to know what to

00:30:09.217 --> 00:30:12.137
do next and so they're taking

00:30:12.137 --> 00:30:14.777
that step back you say people are doing this so they

00:30:14.777 --> 00:30:17.797
can figure out what to do next a dashboard

00:30:17.797 --> 00:30:21.137
only gets you halfway yeah larry

00:30:21.137 --> 00:30:24.097
i really appreciated it in chapter 11 when uh

00:30:24.097 --> 00:30:29.037
you said uh why dashboards suck and there's a section on it and you talk about

00:30:29.037 --> 00:30:33.177
some of the things and i run across it all the time i'm a data viz guy myself

00:30:33.177 --> 00:30:37.917
and i work on a lot of dashboards and i follow the steven few approach to um

00:30:37.917 --> 00:30:42.277
data visualization um but there's all kinds of things that drive me nuts.

00:30:42.397 --> 00:30:47.117
There's the thing I like to call it the donut stamp, where you just take a number,

00:30:47.117 --> 00:30:49.717
and then you just have a donut graph around it.

00:30:49.837 --> 00:30:53.097
And then you just stamp a bunch of those at the top of the screen.

00:30:53.577 --> 00:30:57.117
And you call it a dashboard and then wonder why people aren't using it.

00:30:57.237 --> 00:30:59.797
People don't engage with it. It doesn't solve problems.

00:31:00.257 --> 00:31:05.337
There is research to be done there too, not just, oh, we've got data, let's visualize it.

00:31:06.029 --> 00:31:09.969
You know, think about it. When you say we have data, let's visualize it.

00:31:10.069 --> 00:31:11.589
You're starting from the data perspective.

00:31:11.949 --> 00:31:17.229
If you start from what the desired outcome is, you're starting from the user's

00:31:17.229 --> 00:31:22.429
endpoint perspective and working backwards instead of from the data moving forward.

00:31:23.129 --> 00:31:30.609
So, and what you'll find is that if you work backwards, what the people want

00:31:30.609 --> 00:31:36.189
is different than what the data wants. and sometimes you won't even have the right data.

00:31:37.289 --> 00:31:40.629
So data visualization is about, we have this data, let's make it pretty.

00:31:40.969 --> 00:31:44.209
But if you start from the desired outcome, you realize, wow,

00:31:44.309 --> 00:31:48.689
we don't have the data to do this. We need to find that somehow.

00:31:49.309 --> 00:31:55.949
So there's one product I've worked on had to do with how do you incentivize

00:31:55.949 --> 00:31:59.089
salespeople to do a better job at their job?

00:31:59.289 --> 00:32:04.629
Well, turns out that sales managers all have different formulas for their product,

00:32:04.809 --> 00:32:06.969
their domain, you know, things like that.

00:32:07.089 --> 00:32:11.409
And if you start from saying, the user needs to know what to do,

00:32:11.489 --> 00:32:14.949
because what's the salesperson most important consideration?

00:32:15.509 --> 00:32:20.389
How am I going to make my bonus? Because they're compensated on how well they perform.

00:32:20.889 --> 00:32:27.329
So the formula, if you follow a sales formula, right, and you deviate from the

00:32:27.329 --> 00:32:31.509
formula, it can tell you, you're not visiting, you know, this customer often

00:32:31.509 --> 00:32:35.189
enough. You need to visit them some more. That's an actionable state.

00:32:35.789 --> 00:32:41.349
And so that means you're going to design to that actionable state to inform

00:32:41.349 --> 00:32:46.449
the user they need to go visit these three customers that they haven't visited

00:32:46.449 --> 00:32:50.209
for a while because those sales are starting to come down. Go visit them.

00:32:51.169 --> 00:32:55.329
Well, if you start from that and you work backwards, you realize we don't have

00:32:55.329 --> 00:32:57.069
all the data that the formula needs.

00:32:57.249 --> 00:33:00.849
So we need to put in another hook to find that data and plug it in.

00:33:01.829 --> 00:33:05.389
And that's better than a dashboard. Yeah, absolutely.

00:33:05.829 --> 00:33:09.509
And, you know, returning to, you know, sort of the knowledge being the central

00:33:09.509 --> 00:33:18.969
piece, one of the things that I love is this contrast between personas and knowledge profiles.

00:33:19.089 --> 00:33:22.529
And I think the knowledge profile is still kind of a persona,

00:33:22.689 --> 00:33:26.969
but a better persona focused on the right things and not like this person is

00:33:26.969 --> 00:33:31.549
married and has drives a minivan and has three kids and stuff that's irrelevant.

00:33:32.309 --> 00:33:38.469
To the building of the product, but a knowledge profile. Can you talk about that?

00:33:39.130 --> 00:33:42.430
Sure. Thanks for asking about that. That's one of my favorites, too.

00:33:42.870 --> 00:33:48.730
So I found this persona that somebody had put together and posted it up on the web.

00:33:48.970 --> 00:33:51.730
And her name is Diane. She's an HR specialist.

00:33:52.190 --> 00:33:56.290
And one of the things they have on there is she likes designer gin.

00:33:57.310 --> 00:34:01.690
How is that going to help you sell an HR software to this woman?

00:34:02.630 --> 00:34:08.670
You know, it likes designer what? Gin, you know, the drink gin.

00:34:11.570 --> 00:34:14.350
You know that's that's worse than the ones that say oh

00:34:14.350 --> 00:34:17.590
yeah has a dog a minivan and three kids

00:34:17.590 --> 00:34:20.590
yeah but how is that going to help you sell refrigerators you

00:34:20.590 --> 00:34:23.910
know so the problem

00:34:23.910 --> 00:34:27.570
with personas is that they're far too vague now what's interesting a little

00:34:27.570 --> 00:34:34.370
backstory there when alan cooper was first writing um his book about face uh

00:34:34.370 --> 00:34:40.750
he called a number of us people that had graduated from Don Norman's program, I being one of them,

00:34:40.990 --> 00:34:46.130
to talk about this notion of the user. And he crafted the term persona.

00:34:46.390 --> 00:34:52.350
I actually think Don Norman did. But anyway, he crafted this image of a persona

00:34:52.350 --> 00:34:54.510
in his book, but he got it wrong.

00:34:55.070 --> 00:35:00.350
Because we were all talking about the persona is based on what it is they're

00:35:00.350 --> 00:35:02.450
doing, not just this general person.

00:35:03.110 --> 00:35:08.330
A persona is not a person. is it was supposed to represent now what I call hats.

00:35:08.930 --> 00:35:13.490
So for instance, when you do a different task, you're an expert at that task.

00:35:13.570 --> 00:35:16.950
But when you do another task, you're a novice, you change hats.

00:35:17.250 --> 00:35:18.710
Your knowledge base is different.

00:35:19.290 --> 00:35:27.150
So you may be an expert chart maker in Excel, but when you turn around and do

00:35:27.150 --> 00:35:30.510
a pivot table, which you've never done, are you still an expert?

00:35:30.750 --> 00:35:33.050
No, you're a novice. You've changed hats.

00:35:34.170 --> 00:35:37.430
So the knowledge profile user

00:35:37.430 --> 00:35:40.530
knowledge profile is all about understanding what task

00:35:40.530 --> 00:35:44.570
is it that somebody is performing what problem are they trying to solve what's

00:35:44.570 --> 00:35:49.210
their desired outcome and what do they know going into that task and then what

00:35:49.210 --> 00:35:53.930
will they need to know in order to succeed but they won't know because that's

00:35:53.930 --> 00:35:58.450
the knowledge gap that you have to design a bridge across.

00:35:58.950 --> 00:36:03.790
Your goal is to bridge that knowledge gap for the user with your design.

00:36:04.940 --> 00:36:08.660
And it's going to change for each task that the user is going through.

00:36:08.920 --> 00:36:12.900
So, like I said, they may be an expert in one sense, but a novice in another.

00:36:13.100 --> 00:36:15.960
How do you, you know, design for that?

00:36:16.820 --> 00:36:20.600
Yeah. And so with the, I think you mentioned it in the book,

00:36:20.800 --> 00:36:26.160
with Alan Cooper's work, because he introduced the idea to, I think,

00:36:26.220 --> 00:36:28.980
many people in the business world, their first time hearing about personas was

00:36:28.980 --> 00:36:30.280
inmates are running the asylum.

00:36:30.280 --> 00:36:35.980
And then he clarified it a little bit more in About Face in that chapter that he's got.

00:36:36.000 --> 00:36:38.920
About Face was his first book.

00:36:39.800 --> 00:36:44.780
Inmates Are Running the Asylum was his second book. Was it a different edition?

00:36:45.460 --> 00:36:48.700
I'm thinking of the About Face published in 2005 or something.

00:36:49.760 --> 00:36:53.140
Maybe there was multiple editions or something like that. I thought,

00:36:53.200 --> 00:36:56.140
you know, I had a copy of it here and I don't think so.

00:36:56.420 --> 00:37:02.020
Sure, sure. I thought about face came first, and inmates came second. I could be wrong.

00:37:02.740 --> 00:37:07.620
Okay. But during that time period, you seemed to allude to it,

00:37:07.680 --> 00:37:13.440
that practitioners were sort of talking to each other and challenging each other

00:37:13.440 --> 00:37:18.600
during that time to try to get it right. Because was that the case?

00:37:19.380 --> 00:37:24.660
Well, a lot of us were out of Don Norman's class or one of his graduate students.

00:37:24.660 --> 00:37:28.820
And we all kind of understood personas from the way Don told it.

00:37:28.900 --> 00:37:31.300
And it was task oriented. It was task related.

00:37:31.820 --> 00:37:37.900
So I learned task oriented analysis and design from, you know, that program.

00:37:38.520 --> 00:37:40.820
And everything was about the task.

00:37:42.080 --> 00:37:46.420
Excellent. And so I think that one of the things that really proves the value

00:37:46.420 --> 00:37:51.280
of the things that you talk about in your book is that the ability.

00:37:52.899 --> 00:37:56.399
Deliverables are more tied to each other. And you talk about this,

00:37:56.479 --> 00:38:00.539
there's a section where, you know, when we think about user research,

00:38:00.699 --> 00:38:02.939
right, there's all these deliverables we have.

00:38:03.099 --> 00:38:07.099
And as we go further and further into UX future, we're expected to make them

00:38:07.099 --> 00:38:10.159
more beautiful and not necessarily more valid.

00:38:10.499 --> 00:38:13.919
Because I talk to people who are, you know, young practitioners,

00:38:13.919 --> 00:38:17.859
and they say, oh, I'm working on my portfolio. Oh, what do you do? I'm a researcher.

00:38:18.299 --> 00:38:21.479
It's like, okay, well, can I see your portfolio? And they have these beautiful

00:38:21.479 --> 00:38:25.719
setups and you get the idea there's much more focus, especially coming out of

00:38:25.719 --> 00:38:32.339
these bootcamps on how to make wonderful journey maps and these beautiful, yeah, exactly.

00:38:33.299 --> 00:38:38.319
But you point out that a lot of this stuff doesn't get used, which is sad.

00:38:40.239 --> 00:38:43.219
And it goes a little bit by the wayside.

00:38:43.219 --> 00:38:47.379
But when you're talking about your you

00:38:47.379 --> 00:38:50.839
know sort of reconstruction um of these

00:38:50.839 --> 00:38:53.859
deliverables and um kind of

00:38:53.859 --> 00:38:56.999
advocating a way to do it it becomes really clear

00:38:56.999 --> 00:39:02.059
and you show it multiple times that each deliverable is directly tied to the

00:39:02.059 --> 00:39:07.039
next they all stay relevant one of them doesn't fall out of relevance they stay

00:39:07.039 --> 00:39:12.199
linked and they stay useful right because we've all heard that personas once

00:39:12.199 --> 00:39:15.459
they're done they They look great, have nice graphics on them and everything.

00:39:15.619 --> 00:39:18.879
And they go on a shelf and never to see the light of day again.

00:39:19.279 --> 00:39:23.579
So yes, a really good process should be a connected process.

00:39:23.979 --> 00:39:28.259
One step should inform the next, should inform the next, should inform the next.

00:39:28.459 --> 00:39:34.039
And that's what the book talks about and describes and displays and demonstrates

00:39:34.039 --> 00:39:36.879
is this is all a continuous flow.

00:39:37.379 --> 00:39:41.359
And the reason you do that is so that everybody can follow along.

00:39:41.359 --> 00:39:44.499
Why were these design decisions made this way?

00:39:44.879 --> 00:39:49.499
It's because the strategy was this, and the strategy came from the optimized

00:39:49.499 --> 00:39:55.759
task flow, which came from the task analysis, which came from the user observations.

00:39:56.819 --> 00:40:04.599
And so you get away from this opinion war that typically happens in research

00:40:04.599 --> 00:40:08.099
and design. Well, I think this, I saw this, you know, this, that, and another.

00:40:08.759 --> 00:40:12.659
And a lot of research reports are just that, they're reports,

00:40:12.859 --> 00:40:17.079
but they don't describe how to apply that to the next step.

00:40:18.199 --> 00:40:24.479
And it's because people learn these disconnected steps and they don't realize

00:40:24.479 --> 00:40:27.039
that there should be a connection between everything.

00:40:27.459 --> 00:40:30.959
One thing should inform the next, it should flow all the way down to the,

00:40:31.139 --> 00:40:33.219
actually to the usability testing.

00:40:33.219 --> 00:40:38.079
Because the task analysis that you do up front, the task optimization,

00:40:38.739 --> 00:40:46.179
should inform what the tasks are in the usability tests at the very end of the design process.

00:40:47.647 --> 00:40:51.867
Yeah, absolutely. And on this topic of artifact continuity, I love that phrase

00:40:51.867 --> 00:40:55.347
that you got in the book. You also address the jobs to be done.

00:40:55.527 --> 00:40:56.907
And I think that's really important

00:40:56.907 --> 00:41:01.727
because it's become popular in the business world, jobs to be done.

00:41:01.867 --> 00:41:06.187
And jobs to be done is probably better than the older business ways of doing things.

00:41:06.327 --> 00:41:13.847
But could you contrast for us where jobs to be done is maybe good or where it

00:41:13.847 --> 00:41:15.227
maybe misses some things?

00:41:16.027 --> 00:41:20.967
Well, you know, jobs to be done is kind of like a task analysis light.

00:41:21.687 --> 00:41:25.787
It's not as specific as a task analysis. Now, with task analysis,

00:41:25.807 --> 00:41:28.447
you're breaking down all the tasks and jobs to be done.

00:41:29.027 --> 00:41:34.327
You're starting to do that, but you don't get into identifying what some of

00:41:34.327 --> 00:41:36.267
the issues are, what the artifacts are.

00:41:36.487 --> 00:41:42.027
And there's no real step that they build into that about task optimization.

00:41:42.587 --> 00:41:46.587
How do you reinvent the task? You know, if you're going to have some new,

00:41:46.807 --> 00:41:50.547
say, for an AI, right, you're going to introduce an AI.

00:41:50.747 --> 00:41:54.487
What can you get the AI to do? How does that change the user's task?

00:41:55.067 --> 00:41:58.867
That's not covered in Jobs to be Done. Jobs to be Done is the initial step,

00:41:58.907 --> 00:42:01.807
but they don't follow through with it. And it's much more vague.

00:42:01.947 --> 00:42:04.127
It's not as specific and clear-cut.

00:42:04.607 --> 00:42:06.927
But it's still a worthwhile, you know, practice.

00:42:08.087 --> 00:42:12.367
Yeah. And with these, you know, kind of business methods, another one that I

00:42:12.367 --> 00:42:16.687
liked, and it had a big overlap with UX or perhaps it's UX.

00:42:17.747 --> 00:42:23.847
Well, it's the three different parties, technology, UX, business that play a role into it.

00:42:24.327 --> 00:42:34.307
Priority matrix as a way of being a little bit more objective about how we prioritize.

00:42:34.987 --> 00:42:39.167
I'd like to say that I created that, but I'll be frank and said I stole it from

00:42:39.167 --> 00:42:40.807
Six Sigma's House of Quality.

00:42:41.607 --> 00:42:46.527
But I streamlined it down because House of Quality was far too cumbersome.

00:42:47.707 --> 00:42:53.227
So I actually was a certified product manager for a while, and I learned all

00:42:53.227 --> 00:42:57.247
about Six Sigma and the House of Quality. And it had an application.

00:42:57.987 --> 00:43:04.007
But I streamlined it down to you list the tasks that the user is trying to perform,

00:43:04.127 --> 00:43:06.047
not the features. That was a big difference.

00:43:06.447 --> 00:43:10.987
So you list the tasks that the users are trying to perform and you identify

00:43:10.987 --> 00:43:13.407
what is the priority of that task.

00:43:14.168 --> 00:43:18.568
You know, if they didn't get to print something out, that's a lower priority,

00:43:18.568 --> 00:43:21.828
but they needed this calculation. That's the highest priority.

00:43:23.068 --> 00:43:28.288
So then you look at what's the value of that task to the business,

00:43:28.568 --> 00:43:32.168
you know, to the marketing, to the to the business side of it.

00:43:32.268 --> 00:43:36.808
And so you get a different set of scores along that list of tasks.

00:43:37.328 --> 00:43:42.988
So you may have one task that's a highest priority, a priority one for the user,

00:43:42.988 --> 00:43:46.188
but the business can't figure out how to make money out of it.

00:43:46.228 --> 00:43:48.668
And it's just not cost effective for them.

00:43:48.788 --> 00:43:52.068
So that would give it a three on a three point scale.

00:43:52.528 --> 00:43:57.788
And then the technology column is how feasible is it for us to make this?

00:43:58.008 --> 00:44:03.748
Is this a task that's going to require all new sets of features that we've never done before?

00:44:03.988 --> 00:44:09.088
That's a difficult level of three. or as we already have all of these features,

00:44:09.228 --> 00:44:11.788
we just have to reorganize them. That would be a one.

00:44:12.668 --> 00:44:18.008
So you do that with all of the different tasks and what you find is that a third

00:44:18.008 --> 00:44:20.168
of them are things you should do right now.

00:44:20.628 --> 00:44:25.528
And it's not just based on the user and it's not based on the technical feasibility

00:44:25.528 --> 00:44:28.268
and it's not solely based on the business.

00:44:28.628 --> 00:44:33.628
But that priority matrix is only a guideline because you still need to make

00:44:33.628 --> 00:44:37.248
some accommodations to different perspectives here and there.

00:44:37.508 --> 00:44:42.788
Like we have to do this now because this other thing that we want to launch

00:44:42.788 --> 00:44:44.208
is going to be dependent on it.

00:44:44.308 --> 00:44:49.308
So you have those technical dependencies, business dependencies and user dependencies.

00:44:49.648 --> 00:44:53.188
But at least it gives you a pretty good starting point.

00:44:54.102 --> 00:44:57.002
And I like the constraint that you can only use the number, you have to use

00:44:57.002 --> 00:44:59.782
each number, one, two, and three, an equal number of times.

00:45:00.242 --> 00:45:02.862
So you can't just claim one, one, one, one, one, one. Otherwise,

00:45:03.022 --> 00:45:07.362
everything's the one in marketing, everything's the three in technology. That's right. Exactly.

00:45:08.482 --> 00:45:13.462
So now in your discussion about knowledge-oriented design, there's a concept

00:45:13.462 --> 00:45:21.222
that's truly powerful and it's fairly simple, but it's required knowledge and the knowledge gap.

00:45:21.222 --> 00:45:25.822
And you have this way of kind of, you could almost put it in an equation.

00:45:25.822 --> 00:45:32.622
I don't think it's quite that, you know, maybe explicit, but it's really deliberate

00:45:32.622 --> 00:45:36.822
about getting to what is the knowledge gap and what is the current knowledge.

00:45:36.942 --> 00:45:38.982
Could you talk about that a little bit?

00:45:39.802 --> 00:45:46.402
Yeah. So the example I like to use, and it's in the book, is nurses can be expected

00:45:46.402 --> 00:45:48.482
to have a certain base knowledge.

00:45:48.722 --> 00:45:53.002
They know how to give medications, such as ointments, pills,

00:45:53.222 --> 00:45:56.142
shots, rubs, things like that.

00:45:56.322 --> 00:45:59.602
So you could expect every nurse to know that.

00:45:59.822 --> 00:46:06.222
But a key responsibility for nurses is to avoid any drug interactions that might occur.

00:46:06.502 --> 00:46:11.902
So there's a whole host. There's tens of thousands of potential drug interactions

00:46:11.902 --> 00:46:15.522
where people would react negatively. It could even kill somebody, right?

00:46:16.122 --> 00:46:20.142
Well, you can't expect the nurses to remember all of those.

00:46:20.602 --> 00:46:27.262
So that's the knowledge gap. The knowledge is they know how to administer medications.

00:46:27.622 --> 00:46:31.202
And the required knowledge is to prevent drug interactions.

00:46:31.562 --> 00:46:35.602
The knowledge gap is they don't know all the potential drug interactions by

00:46:35.602 --> 00:46:41.062
heart. So how do you design something that makes sure that when they get those

00:46:41.062 --> 00:46:46.062
meds out for that patient, that they're not giving two meds that would interact negatively?

00:46:46.502 --> 00:46:49.602
And so we came up with a system that did that.

00:46:51.096 --> 00:46:55.556
Absolutely. And, you know, when you're coming up with this methodically,

00:46:55.556 --> 00:46:59.376
there's a process, of course, to it.

00:46:59.616 --> 00:47:04.056
I like the iterative nature of the process that you emphasize.

00:47:04.816 --> 00:47:09.376
So, for example, with task analysis, there are explicit phases.

00:47:09.376 --> 00:47:13.856
It's not just, oh, we're iterating, but you've got the first stage that has

00:47:13.856 --> 00:47:18.016
a certain purpose and it has a beginning and end and you have an idea of when it's done.

00:47:18.136 --> 00:47:22.116
And then you have two or three stages in the end, But they're different.

00:47:22.836 --> 00:47:26.496
They have a slight qualitative difference to them.

00:47:27.676 --> 00:47:32.616
It's about the specificity or the details of the task. You don't have to get

00:47:32.616 --> 00:47:35.576
mired in the details with your initial analysis.

00:47:35.876 --> 00:47:40.136
You do the five main steps, and then you can break each one of those down into

00:47:40.136 --> 00:47:43.836
five to 20 steps, and then break those down if you need to.

00:47:44.036 --> 00:47:46.416
Usually by the second one, you have enough information.

00:47:47.256 --> 00:47:49.016
But yes, it's methodical. And

00:47:49.016 --> 00:47:52.996
it's done so that you don't get mired in the details and forget details.

00:47:54.456 --> 00:47:59.716
And that's where you start to identify where the knowledge is that people have to have.

00:47:59.856 --> 00:48:04.936
In this step, you have to be able to make sure that you don't have potential drug interactions.

00:48:05.236 --> 00:48:12.556
So that means that the system has to inject that knowledge into the flow for

00:48:12.556 --> 00:48:14.356
the user because they can't do it themselves.

00:48:15.196 --> 00:48:19.696
Yeah, one of the ways I look at that too is in kind of the knowledge company.

00:48:20.056 --> 00:48:21.436
We could talk about that as well.

00:48:21.876 --> 00:48:27.336
And I see it as, you know, again, it's back to humans are trying to achieve a task.

00:48:27.656 --> 00:48:33.436
Then you've got this company with lots of data and a massive amount of knowledge.

00:48:33.436 --> 00:48:36.796
How can we design things

00:48:36.796 --> 00:48:39.736
so that we're not depending you point

00:48:39.736 --> 00:48:42.616
this out um repeatedly throughout the book is you know

00:48:42.616 --> 00:48:45.876
not depending on the individual skills and

00:48:45.876 --> 00:48:49.656
individual knowledge of a person but leverage

00:48:49.656 --> 00:48:52.476
all of the information that

00:48:52.476 --> 00:48:55.236
we have in the task right and you

00:48:55.236 --> 00:49:00.136
introduced that the concept of what kind of company are you a service company

00:49:00.136 --> 00:49:06.256
a product company um are you a non-profit you're none of the above you're a

00:49:06.256 --> 00:49:09.676
knowledge company people come to you not because of your product or service

00:49:09.676 --> 00:49:12.576
but because of the knowledge about that product or service,

00:49:13.216 --> 00:49:17.576
so the more knowledge you can share with your customers in the design of your

00:49:17.576 --> 00:49:23.256
product the more successful your product will be so people don't like i said

00:49:23.256 --> 00:49:28.076
people don't want a quarter inch drill they want a quarter inch hole and so.

00:49:29.077 --> 00:49:35.457
Think about, you know, I tell the story about the toolbox in there and task analysis.

00:49:36.537 --> 00:49:41.057
Say you buy a used car and it needs spark plugs and you figure you can change

00:49:41.057 --> 00:49:44.617
the spark plugs yourself so you don't have to spend hundreds of dollars, right?

00:49:45.037 --> 00:49:48.777
And your developer friend says he has a garage full of tools.

00:49:48.777 --> 00:49:51.437
He's not going to be home this weekend, but you're welcome to use it.

00:49:51.597 --> 00:49:55.357
Don't worry, all the drawers are labeled, right? And sure enough,

00:49:55.377 --> 00:49:58.417
you go over there, open the garage door, wall-to-wall tool chest,

00:49:58.537 --> 00:50:01.897
and you see the labels on every drawer and think, this is going to be easy.

00:50:02.417 --> 00:50:06.557
And then you start opening the drawers and realizing, I don't even know which

00:50:06.557 --> 00:50:10.217
tools to use. So you open the socket drawer, and there's 200 sockets in it.

00:50:10.417 --> 00:50:14.877
I don't know which one to use, but do you remember your ex-friend said she had

00:50:14.877 --> 00:50:18.497
a garage full of tools also, and you're welcome to use that.

00:50:18.497 --> 00:50:22.837
You go over there, open your garage door, wall-to-wall tool chest,

00:50:22.997 --> 00:50:25.577
and all the drawers are labeled, but they're labeled differently.

00:50:26.697 --> 00:50:30.857
It says, change oil, change tire, change spark plugs.

00:50:31.037 --> 00:50:35.437
And you open the spark plug drawer, and there's a socket, just one,

00:50:35.577 --> 00:50:39.937
an extender, and a ratchet handle, and a rubber hose.

00:50:40.457 --> 00:50:42.637
And you wonder what the rubber hose is for.

00:50:43.357 --> 00:50:48.257
Well, after you take the spark plugs out, you realize you can't fit your fingers

00:50:48.257 --> 00:50:52.497
down in the cylinder head to put the spark plug in.

00:50:52.657 --> 00:50:56.537
So you put the hose on the end of the spark plug, stick it down and start the

00:50:56.537 --> 00:50:58.097
spark plug with the rubber hose.

00:50:58.577 --> 00:51:02.437
Who knew that? She knew that. And so she put it in the drawer.

00:51:02.957 --> 00:51:06.217
So all the right tools were in that drawer just for you.

00:51:07.137 --> 00:51:10.477
Wow, I love that story. yeah so

00:51:10.477 --> 00:51:13.177
um one of the things

00:51:13.177 --> 00:51:16.937
i wanted to touch on is the um

00:51:16.937 --> 00:51:23.137
the story i'm looking forward here it was a um it was about a search and rescue

00:51:23.137 --> 00:51:28.197
kind of use case where there's big maps spread out on a table and there's this

00:51:28.197 --> 00:51:33.177
process war on the floor i wanted to talk about that a little

00:51:33.377 --> 00:51:37.917
because I thought it was a striking example of a complex kind of work scenario

00:51:37.917 --> 00:51:40.057
where something needs to be designed for it.

00:51:40.537 --> 00:51:44.057
So the Coast Guard, U.S.

00:51:44.197 --> 00:51:48.957
Coast Guard, brought us in to help them figure out how to sell more.

00:51:51.217 --> 00:51:56.737
I guess it was satellite receiving equipment. When a boat or an airplane goes

00:51:56.737 --> 00:52:01.697
in the water, a signal automatically generates, and it's an SOS signal.

00:52:02.610 --> 00:52:05.950
And they thought, we need to sell more of this equipment. Well,

00:52:06.110 --> 00:52:09.630
what we observed was the equipment was fine.

00:52:09.790 --> 00:52:12.670
People could use that in a manner of seconds.

00:52:13.030 --> 00:52:17.130
But it was the next six hours where they were trying to figure out,

00:52:17.290 --> 00:52:23.110
based on the wind direction, the tides, what the sea swell was,

00:52:23.510 --> 00:52:27.970
what different ships and planes were in the area to help us look.

00:52:27.970 --> 00:52:34.870
They were trying to put together a search plan because say there's a sailboat

00:52:34.870 --> 00:52:39.870
that starts sinking and there's another sailboat, you know, 30 miles away from it.

00:52:40.830 --> 00:52:43.750
Coast Guard will call over to them and say, can you see them?

00:52:43.970 --> 00:52:48.330
Well, if you're on a sailboat, you can only see maximum a couple of miles in

00:52:48.330 --> 00:52:51.630
the water to be able to see anybody floating in the water.

00:52:52.230 --> 00:52:57.170
But if you're on a freighter, you know, you're higher up on the bridge, you can see farther.

00:52:57.170 --> 00:52:59.890
And so there might be a freighter going by and

00:52:59.890 --> 00:53:02.650
they'll have them look but they don't want them looking in the same

00:53:02.650 --> 00:53:06.250
piece of ocean because then it's a wasted resource so

00:53:06.250 --> 00:53:10.170
they try to map out figure out where are we going to have all of these people

00:53:10.170 --> 00:53:14.390
look what's their they're going to go in circles or they're going to go in squares

00:53:14.390 --> 00:53:18.710
and you might have an airliner flying over and you get the airliner to drop

00:53:18.710 --> 00:53:22.710
down to see if they can see anything and you know and that airliner is going

00:53:22.710 --> 00:53:26.090
to go in one line and you want to figure out what line that should be.

00:53:26.470 --> 00:53:31.270
So there's all of these different calculations that are constantly going on

00:53:31.270 --> 00:53:32.650
and they're all done by hand.

00:53:32.930 --> 00:53:36.310
And they're all done, you know, calculating in the head with calculators and

00:53:36.310 --> 00:53:39.870
keeping track of things. A lot of cognitive effort going on there.

00:53:40.609 --> 00:53:44.689
And so that's one of the things that I like to point out is when you're doing

00:53:44.689 --> 00:53:48.249
your user observations, you're looking for four key things.

00:53:49.029 --> 00:53:52.429
One is something manually intensive.

00:53:52.469 --> 00:53:57.769
And with all these maps and these rulers and all of that, it was this process

00:53:57.769 --> 00:54:01.749
of figuring out what the search pattern should be was very manual.

00:54:02.469 --> 00:54:05.429
And then you look for things that are cognitively demanding.

00:54:05.469 --> 00:54:08.509
And these people were trying to remember things in their heads,

00:54:08.629 --> 00:54:12.489
do mental calculations and all that. A lot of cognitive demand there.

00:54:12.909 --> 00:54:17.109
And then there was a potential for errors if they wrote something down wrong,

00:54:17.229 --> 00:54:18.689
measured something wrong, whatever.

00:54:19.329 --> 00:54:24.709
Or in the case of the Coast Guard thing, they had to use a radio to call out

00:54:24.709 --> 00:54:28.989
to all of these other ships and planes and everything and tell them what the

00:54:28.989 --> 00:54:30.369
coordinates were and everything.

00:54:30.909 --> 00:54:36.109
And for the sailboat, for instance, they might get 100 coordinates that they

00:54:36.109 --> 00:54:38.309
would have the map into their GPS system.

00:54:38.449 --> 00:54:41.509
They always got something wrong. always.

00:54:42.629 --> 00:54:46.369
So that's 100% failure, right? And the other is a knowledge dependency.

00:54:46.569 --> 00:54:51.569
Is there a specific knowledge, like the nurses had to remember all the drug interactions?

00:54:52.189 --> 00:54:55.769
So you look for all of those things, the manually intensive,

00:54:56.029 --> 00:54:58.909
cognitively demanding, error prone, and knowledge dependent.

00:54:59.269 --> 00:55:04.749
And that'll tell you where an opportunity is that you can design for and solve.

00:55:04.749 --> 00:55:07.749
And so this so this

00:55:07.749 --> 00:55:10.549
this coast guard thing turns out that what they

00:55:10.549 --> 00:55:13.729
needed wasn't so much new satellite receiving equipment

00:55:13.729 --> 00:55:16.609
but equipment to not only

00:55:16.609 --> 00:55:19.489
figure out what the search map was but to

00:55:19.489 --> 00:55:23.329
be able to send it out in a more efficient manner because it could take an hour

00:55:23.329 --> 00:55:29.309
to tell somebody what their map would be you know over a voice so a digital

00:55:29.309 --> 00:55:33.989
format that you can send the coordinates out to and then be able to track on

00:55:33.989 --> 00:55:37.989
their GPS how they're doing on that and respond back to you,

00:55:38.189 --> 00:55:44.749
the Coast Guard, so you could adjust any other assets and their search map as well.

00:55:45.902 --> 00:55:51.742
Yeah, that's excellent. And so, and one of the last concepts to get to here

00:55:51.742 --> 00:55:54.422
that I want to make sure I get to is the UX strategy stuff.

00:55:55.742 --> 00:56:02.502
And you talk about it as a, like it's an explicit deliverable to the business

00:56:02.502 --> 00:56:05.642
because a lot of UX researchers kind of think of like, okay,

00:56:05.762 --> 00:56:12.122
well, I'm producing this knowledge and hopefully we can influence the way the business does things.

00:56:12.122 --> 00:56:18.962
But this is producing a strategy. And so I want you to talk about that.

00:56:19.202 --> 00:56:23.782
So that's what the output of the priority matrix is.

00:56:24.002 --> 00:56:28.762
You have to agree that since these are all your priorities, you're going to

00:56:28.762 --> 00:56:34.482
settle on as a business, as a technology component, as the user advert.

00:56:34.682 --> 00:56:40.802
You're going to settle on what this one driving paradigm is.

00:56:40.802 --> 00:56:43.762
Like for pro flowers and it was pro flowers doesn't sell

00:56:43.762 --> 00:56:47.162
flowers it's about the occasion and so

00:56:47.162 --> 00:56:50.282
that drives every other step that drove marketing

00:56:50.282 --> 00:56:53.922
that drove design that drove development you

00:56:53.922 --> 00:56:57.142
know it was a codifying single

00:56:57.142 --> 00:57:00.502
purpose for that product and it

00:57:00.502 --> 00:57:03.622
provides focus for everyone and if it's

00:57:03.622 --> 00:57:07.022
well researched then it's the right thing to focus on right so

00:57:07.022 --> 00:57:09.922
like you know kennedy made his famous we're

00:57:09.922 --> 00:57:14.002
going to space speech back in uh 61 62

00:57:14.002 --> 00:57:17.222
can't remember what and so during

00:57:17.222 --> 00:57:20.522
the 60s you could go ask anybody an astronaut an

00:57:20.522 --> 00:57:24.022
engineer a flight surgeon a janitor

00:57:24.022 --> 00:57:26.762
pushing a broom down the hall at three o'clock in the morning what are

00:57:26.762 --> 00:57:30.082
you doing here we're going to the moon everybody said

00:57:30.082 --> 00:57:33.722
that we're going to the moon that single focus got

00:57:33.722 --> 00:57:37.142
them there excellent going to

00:57:37.142 --> 00:57:40.402
the moon achieving high goals and this book

00:57:40.402 --> 00:57:44.382
to help us out doing it disruptive research larry

00:57:44.382 --> 00:57:49.422
where's the best place for people to uh link up with you is it linkedin and

00:57:49.422 --> 00:57:54.582
find what you're working on and yeah i'm on linkedin uh almost exclusively i

00:57:54.582 --> 00:57:59.662
don't have any other social media channels i find linkedin to be the best as

00:57:59.662 --> 00:58:03.742
far as sharing knowledge and feel free to connect with me And, you know.

00:58:03.842 --> 00:58:06.702
I'll text with anybody.

00:58:07.522 --> 00:58:11.582
I work at LSA Digital. We're a digital transformation company.

00:58:11.782 --> 00:58:12.962
And so I'm reachable there.

00:58:13.742 --> 00:58:17.342
Larry.Marine at lsadigital.com.

00:58:18.862 --> 00:58:23.582
And I'd love to hear any of your questions or comments or anything like that.

00:58:23.902 --> 00:58:27.182
And the book is available on Amazon and Instagram.

00:58:28.322 --> 00:58:31.202
What's that called? I was going to say Instagram.

00:58:34.874 --> 00:58:39.214
Is it another bookstore? I'm not aware of any of that. Ingram Spark.

00:58:39.954 --> 00:58:46.774
Yeah, it's an international bookstore because some of my international people can't get it off Amazon.

00:58:47.894 --> 00:58:52.074
Gotcha, gotcha. So it's where everybody can get it. Disruptive Research.

00:58:52.534 --> 00:58:54.934
Larry Marine, thank you so much for being on the show today.

00:58:55.454 --> 00:58:59.514
Thanks. You did a great job preparing for this, by the way. I'm impressed. Well done.

00:59:00.554 --> 00:59:06.094
So to wrap things up, Today's conversation with Larry Marine challenged some

00:59:06.094 --> 00:59:10.114
of the thinking that has become commonplace in user research today.

00:59:10.574 --> 00:59:16.214
We explored the idea that most teams are skipping critical steps that could

00:59:16.214 --> 00:59:19.434
have changed the conclusions they drew from their research.

00:59:19.674 --> 00:59:24.834
Activities like task analysis, especially when combined with a deeper understanding

00:59:24.834 --> 00:59:27.994
of user knowledge, are incredibly powerful.

00:59:27.994 --> 00:59:32.894
We discussed a methodology that has been shaped by years of practice,

00:59:33.254 --> 00:59:38.294
adapted from classical forms of task analysis, and turned into something new.

00:59:38.494 --> 00:59:43.374
It's a method that's been shaped and refined across hundreds of real-world projects.

00:59:43.394 --> 00:59:48.594
It's been built to cut through the noise and illuminate what truly matters.

00:59:48.874 --> 00:59:54.494
And in doing so, it creates fertile ground where new disruptive ideas can take root.

00:59:54.674 --> 00:59:59.474
And why does this work? Well, it's because by reframing the problem methodically,

00:59:59.694 --> 01:00:05.714
we can move the picture frame of our imagination into a new solution space.

01:00:05.934 --> 01:00:10.534
This is a space that encompasses fresh ideas. And these are the kinds of ideas

01:00:10.534 --> 01:00:13.294
you would need to have a disruptive impact.

01:00:13.454 --> 01:00:18.154
If you want your product to stand out or your service to really get it right,

01:00:18.394 --> 01:00:22.674
you need to investigate this space that most teams are overlooking.

01:00:22.674 --> 01:00:28.314
And as Larry shows us, that space begins with rethinking how we research and

01:00:28.314 --> 01:00:33.414
doing so in a way that we see old problems with a fresh pair of eyes.