Watch the recorded live event:

Resources mentioned in the episode

• Practical Empathy (2015) and Mental Models (2008) by Indi Young
• Mixed Methods (2019) by Sam Ladner
• Weapons of Math Destruction (2016) by Cathy O’Neil
• Joy Buoalmwini’s work toward algorithmic justice
• Online courses and resources available through Indi’s website
• Articles on thinking styles and more at medium.com/inclusive-software
• You can follow Indi on Twitter @indiyoung
• 54 Templates for User Personas, Jobs to Be Done & Other Mental Models

About our guest

Indi is a renowned researcher with over 25 years of experience who coaches, writes, and teaches about inclusive product strategy. Her work is rooted in the problem space where the focus is on people, not users. Indi pioneered opportunity maps, mental model diagrams, and thinking styles. Indi has written two books, Practical Empathy and Mental Models. Her next book, Assumptions Aside, will cover thinking styles.She was also one of the founders of Adaptive Path, the pioneering UX agency. 

Transcript

Indi: [00:00:00] So what I do is I try to be very open about my bias, my team's bias. I don't want that affecting the data. We want the data to be able to say what it has to say. We want to actually hear other people's perspectives, understand other people's perspectives.  

Erin: [00:38:10] Hello everybody and welcome back to Awkward Silences. Today we're here with Indi Young, a researcher, a very well known researcher with several cool books and another one coming out soon. I believe. And today we're here to talk about how average users don't exist.

Erin: [00:00:56] So very excited for this topic. We've got JH here too.

JH: [00:01:01] Yeah I feel like I'm a pretty average person in a lot of ways. So I guess I'm going to have a lot of, I'm gonna have a lot to work through on this call. 

Yeah. 

Erin: [00:01:07] Indi thanks for joining us. We're thrilled to have you. 

Indi: [00:01:11] Yay. Yeah, And the whole average thing, I guess that's a word that gets used in a lot of different ways. Right? Lots of different baggage. The way that I hear people using it is like oh yeah, we're designing for the average user. And that's the usage that hopefully we will 

JH: [00:01:28] It does seem like a bit of a flag when you hear it. Yeah. 

Erin: [00:01:30] Well, that's one. Yeah. And it is one of those. You hear it and you don't even, it's invisible. You hear it so much, but then if you just ask the simple question, well, what does that mean? Who is that? It very quickly falls apart. So, Indi the average user doesn't exist, what do you mean when you say that

Indi: [00:01:47] Oh, quite simply that if you are looking at your market using market data, which is usually demographic, not qualitative.  You are really only looking at. probably, I don't know, less than a 10th of the people that you think are in your market actually fit exactly that average.

People that you're serving don't fall into that curve. And I believe what happened is that a, it came from the way that we used to treat people before digital came along, we used to treat it by populations and quant data is about populations. Now we've got digital and we can actually create different experiences for different people.

And yet we're still kind of working with this idea of a population. And I think the other of it is that digital itself comes from a background of making software to help people get there. An existing process is done faster. And in the beginning as software engineers, we would go and try to figure out what that process is.

So a lot of things like functional requirements, processes, jobs to be done even have its roots in like, well, what are the steps in that process? And in a process, the thing that needed to get encoded in the software was all the ways that. The process is a little bit different. It's an edge case if this context happens and then you have to do this extra step and that's where the word edge cases came from.

And we just somehow wholesale took that into design. And so now we start referring or we can hear our product managers start referring to people as edge cases. And there is no such thing as a human who is an edge case. I don't care if you are in a wheelchair, you are not an edge case. I don't care if you have dark skin or you've been incarcerated, you are not an edge case.

You are a human! 

Erin: [00:03:54] And by definition, we're all individuals. 

Indi: [00:03:57] Yeah. exactly. And so there, the idea then stepped back. To the average, right. We're still blinkered by the old way of thinking about trying to design one solution for a population where we can do much better. 

JH: [00:04:13] How do you, so you mentioned a lot of the context of like the physical products and how we kind of got here. It seems like some underlying factor here is that. People need some way of simplifying the world, right? And like abstracted a little bit.

So if you're designing for, you know, your product is just for a contrived example, has a thousand users. There's only a thousand people that can use it. It's hard to think of all 1000 at once to make decisions or do things right. And obviously aggregating it up to a single number is flawed in ways. but is it okay to cohort it? If these groups are similar and think about it that way, or is your position that you really should be trying to think it is like, you know, at the thousand level as much as possible, does that kinda make sense?

Indi: [00:04:49] Think at the pattern level. Right. So we are mostly researchers. We know that when you do qualitative research, the measure of validity is that patterns are coming out. And this is all based on how you frame the study and how you recruit for the study. And if you're allowing somebody else to frame your study and somebody else to say who to recruit and it doesn't jive. You're not going to get patterns out of it. You're going to get like anecdotal one-off insights, right? This little word. I don't like to use insights. Sam Ladner wrote a book that's called Mixed Methods and she's all like, okay, enough everybody. Let's be professionals, be our professional selves and stop working with the anecdotes because the anecdotes are not patterns.

And I think that we don't have power. We're being told by some manager or some product owner or some product strategist what to search for. And what we really want to do is get in there and help people.  The product, the solution, the service that we're making for people strategize different paths into the future, but we're disempowered from that. 

Erin: [00:06:05] Yeah. And so the anecdote isn't a pattern, but it could illustrate a pattern. 

Indi: [00:06:10]Right. And it could illustrate a pattern if you. If you pull that story from a bunch of different people. But you have to be really specific about what you're talking about. So the way that I get really specific, isn't it's kind of a two-part orthogonal way. One is to understand what is going through their mind.

What part, if they're approaching or addressing. A purpose that they have, whether that purpose is a lifetime purpose or a purpose, like for the next couple of days of the next hour, right. A decision I have to make or something. They've got a purpose. We have to frame it by the purpose and out of that.

Doesn't come steps because it's not a process. It might be a process in which case, the things coming out of it would be looking like the steps that you would get. But instead, what we do is we let them tell us what's going through their minds and therein lies the differences therein lie the patterns that we can start to see how people are addressing this in different ways. 

The second orthogonal part is to look at different thinking styles. So I think a lot of us already know you can't segment by demographic that is harmful. You can't segment by psychographic.

That is harmful. Why is it harmful? Because you're making assumptions about the inner thinking and emotional reactions and the guiding principles of these people. And as soon as we let assumptions come into our discussions about product design And strategy, we're leading our organization down a path of high risks. 

Erin: [00:07:47] Yeah. And just to make a point on demographics and correct me if I'm wrong, but this is the, this is where I've sort of ended up in my thinking on demographics, which is that they're important for representation, right? If you're doing a study, we need to make sure we have an inclusive representative sample.

But they are not the right way to cohort people and find patterns in people that starts to look like stereotyping, which is not what we want to be. 

Indi: [00:08:12] Exactly. Definitely. When I am carefully framing a study around a purpose and carefully choosing who I'm going to recruit. That's where the demographics come in. And that's where I ask these questions of the clients I'm working with. Like, how are we harming people? Do you know how you're harming people?

Are you interested in finding out this is sort of that whole discussion that comes like, what knowledge are you after truly. And who can we find or hear stories from that will help us fill in that gap in knowledge? So yes, definitely demographics come in and recruit, but then from then on out, they do not play a part except when you hear enough stories about a demographic causing inner thinking, causing emotional reactions, like you've been affected by this so long that you've got guiding principles around it.

When that happens. I put a demographic lens in front of my thinking styles. So in use, I'm designing for each thinking style for each part of what we're doing toward a purpose. And I'm also designing for each thinking style with a demographic lens in front of it. So let me give you an example.

There was a client I had last year and just as we transitioned into the pandemic and They were interested in how they were harming people. And so we specifically recruited for it. We heard all those stories and we ended up not with one demographic lens, but three. And they were all based on discrimination.

You can have demographic lenses based on physiology, culture, environment and And this one was all very much discrimination based. We had three because of these people we were listening to, they had different approaches to it, different methods of dealing with it. Some people were like, this has got to change and it's got to change for society.

So I'm going to do my part to push back. Other people were like, this can't be right for me. I'm not putting up with it. And others were like, I'm lucky to be here. I'm going to put up with it. 

Erin: [00:10:32] So the groups were the pattern. Wasn't the demographics themselves. In other words—

Indi: [00:10:36] No. 

Erin: [00:10:37] the wheelchair, it was there's a discrimination happening that is related to your demographics. And you're dealing with it in this way, which is more of a thinking style. How do you interact with this? 

Indi: [00:10:48] It's a lens on top of the thinking style because they are also that thinking style with respect to the purpose, they're a human trying to get that purpose done, but they also have to deal with this other lens and it can be demographic. It can be, Hey, I am black and this is what I have to deal with.

Or there was one from a help desk kind of agency, and it was, I am, I have a female voice. And when I get on a call with somebody a quarter of the time, they don't believe what I say. Yeah. So, yeah, it can be demographic.

JH: [00:11:23] You've mentioned the harm piece a couple of times in there like, are we harming people? And so I wanted to just make sure I'm understanding this correctly. So again, I'm going to come up with a simple example because I'm around everything. I'm deciding to start a clothing business, right?

And it turns out everyone in my target market is either five feet or six feet or whatever. And I do the average. And so I make my clothes for a five and a half foot person. My clothes don't fit anybody. Right. your definition, is that like we're harming them because we made a product that doesn't work for them or it's just like, we're just going to fail because we designed for the average and we didn't really understand what I, this, I don't know if this is actually the right, hitting the right point, but I'm curious how harm—

Indi: [00:11:58] Yeah. Let me define what I mean by harm. Harm can be mild harm, it can be as mild as, it's frustrating to use this thing. Like when I was trying to get on Zoom for this call, I had to press, like 14 different buttons, right? So there's that harm. Right. But there's also harm in that.

I've got it in like bring my guiding principles to help me through this discrimination or to help me through this physiological thing. Like a person getting on a plane who has a large body and doesn't fit in the tiny, only seats that they have there has to shield themselves emotionally, psychologically from all the looks that are going to get the comments that shoves in the re you know, whatever. right. So, that is serious harm. That's a good example of serious harm, but serious harm can also go up to like, you're driving a car and it's got a screen and you have to like, try to figure it out. You know, you want to see far down the road and squint to see the tiny print on the screen and you get in a crash.

That's also serious harm, right? serious harm can Also, or it depends on the severity of it can be, being made to feel unwelcome. So for your clothing company, anyone who is not five and a half feet, Is being made to feel unwelcome, unsupported. There was an ad I saw for some wine delivery company, where they're like just tell us you know your favorite chocolate and I'm all like, okay, I do have a favorite chocolate.

And then tell us your favorite cocktail cocktails, and then tell us your favorite coffee. And I'm like, I don't drink coffee or whatever. I'm not gonna, you know, it's that kinda, that's kinda mild, right? But it can have higher severity. There's also a third kind of harm and that's systemic harm. And that's the kind of harm that we find that people have written such as Cathy O'Neil’s Weapons of Math Destruction, such as Sarah Wachter Boucher's Technically Wrong there, such as Joy Buolamwini’s [work]. We've got a lot of people out there, like ringing the alarm bells going there is systemic harm being done in our algorithms. Right. Facial recognition, insurance charging to judging people in the courts giving teachers ratings or whatever, et cetera, et cetera.

I mean, it's all sort of based in a way that we're writing software. Based on this idea of where it came from, which just like, oh yeah, We did all this work in advertising and like recommendation engines, which never have recommended anything to me. So let's take it the next Step and let's now start rating other people, like why are we going that direction? That it's just the next thing that people who are blindly feeling their way around the room. 

Erin: [00:14:58] Right. We think we can. And therefore we should. Well, first of all, JH, thanks for making a t-shirt store just for me very much. Appreciate that. 

...But Indi, we kind of jumped right into thinking styles and we've been talking about them and I imagine there's some people who listen, who maybe don't know what we're talking about.

So can we introduce the concept? What is the thinking style and why are they so potentially powerful for folks? 

Indi: [00:15:20] So a thinking style, it's just an archetype, it's the archetype we've been wanting to use. It is a demographics free representation of a person's philosophical approach to their purpose. So for example let's take, people who are buying a new mobile phone the company mobile phones.

So like, oh, they're the, like the techno geeks who always want to have the latest and greatest, you know, that's how they define it. In the research we didn't find that person, but we found the person who's like, I am interested in how I look. And my accessories are a part of that. Versus we found a person who is, who's the darn thing has to work.

It is a key part of my life, and it's got to do this and this, and I'm going to use it even though the screen is cracked, that kind of thing, et cetera. So, I can give you another example. We did a study about how people take care of clothing. It was for a company that makes a particular product.

But whenever I do my studies, I go a little bit broader because I want to allow for associative innovation. So for broader purposes, I'm going to take care of my clothing and it begins in the store when you're buying clothes. And you're looking at the labels, like, can I take care of this? right, and there was a thinking style that was called. Neat and pressed.

There was also the person who's all like, it'll be fine. Like, I'm just going to throw it all in together.

Erin: [00:16:52] right. 

Indi: [00:16:53] And these are all based on patterns. They're not individuals or patterns that I saw. And this one the group who called them the segregationists. No, the separationists, that's it: separationists. They were really worried about bacteria and germs. 

Some of them—it was pre-COVID—so some of them worked in a hospital and did their laundry in a laundromat because they had babies at home. Some of them were new people, parents, and they actually bought a little tiny laundry washing machine That hooked up in their bathtub to separate their baby's clothes.

Some of them were just like, eh, we're not putting the kitchen clothes in with my clothes in with the kids' soccer clothes. So that's what I mean is like it is your philosophical approach to the purpose of taking care of clothing. Now, there's two, there's a couple of caveats. One is that it has to be data driven by qualitative deep data.

Otherwise you can't understand what's going through people's minds. And the other Is that a person can shift thinking styles. It is not a horoscope and there are so many personas out there. Not only are they not based on data, they also contain information about the rest of the person's life, which is not germane to the purpose.

And they carry with them by doing that. They carry with them this flavor that is there. Personality like a Zodiac, like a horoscope, like, you know, you're this type of person, oh, you were born in the year of the rat. That means you're uh, blah, blah, blah. right.

And that's not what a persona should be used for.

That is not what thinking styles are. So the example I like to give here, the thinking style, examples around airline travel. And we have someone who is like, time is really important to me. When I'm traveling, I'm going to fill up my time. Wisely, I'm going to be really prepared. I'm maybe getting work done or getting, finishing, knitting that thing that I needed to do, I'm shortening my connections.

I'm making sure that everything when it goes wrong and pear shaped, I'm like, am I able to get on the other plane? Can I just take a bus? You know, that kind of thing. Versus the type of person who is Zen about it, you know, I'm gonna. Yeah, things are going to happen. Bad. Things are going to happen.

I'm going to carry on. I've got everything. I'm prepared for that kind of thing. I might even help other people be prepared for it. Like if it happens, I'll help calm down total strangers around me. And you Might. Be in that first group, if you were going on a business trip, say you're going to a conference, but you have a deliverable, right, You've been there. And When you take your toddler on a trip, you might be in the second group, right? So you can switch to a horoscope. And the problem. So here's the follow on, is that the problem nobody's using them? There are no seats for getting work done on the plane. For example, there's nothing like that at the gate.

I mean, actually there are things like that at a lot of gates now where you can sit down, you can plug in, you can get work done. They don't have that on the plane yet. 

JH: [00:20:23] Yeah. So you were saying that, I think you've stressed her out this, right. Is that like, these patterns need to be based on data. There's a sort of foundational piece to this. And I guess the question I'm coming up with is as you think about thinking styles and you're putting them together, like what's the heuristic for knowing we have enough data here around this pattern that we should label it as such versus these ones are pretty similar.

Maybe we should come up with a more umbrella term or like, is there a hierarchy? Like how do you figure out that piece? Is that more art or do you still like, lean on the data and do it in a more scientific way?

Indi: [00:20:50] I just taught a course on this.

JH: [00:20:53] Yeah.

Indi: [00:20:53] So, it's a huge topic. It takes between four to 10 hours to figure it out as a group. I always do group working sessions to work on this. And what we do is we try to understand what is foremost in a person's mind as they are going. Out there like a day of travel, let's say, as I'm putting myself out there in the airport and out there in the plane, what's kind of the philosophy that I pull, carry around with me to address things.

And there might be two or three different things in thinking. I always go with this tryout of inner thinking, emotional reactions and guiding principles. And I can define those if you want, but they are the definition of cognitive empathy. This is you being able to understand a person well enough to act them.

Okay. That's the definition that we're after. So what are the 2, 3, 4, 5 things that are foremost for this person, all the participants that we had. And then we're looking at those foremost things that they are taking out there into the airport and into the plane and seeing what affinities there are. And there will be some pretty obvious ones. There will be some, I'm not sure about that one kind of thing. And then you have to ask the question well, is that foremost and if it's foremost and it just doesn't fit, then this person is kind of by themselves, 

 Erin: [00:23:00] and I, I know you talk, you talk about how people can switch things, styles, contextually as well. So do you try to dig into that, like how that a given person might react in a different context? Or is it about just ascertaining, which styles exist and then recognizing a person may switch?

Indi: [00:23:21] Part of it is that we'll break up the transcript. If they have switched. If it does feel like they've taken a different kind of approach, we'll break up the transcript so that it's like they become participant 1 0 1 a and participant 1 0 1 B in a way, right? And we'll present them that way when we're doing those working sessions together. 

Erin: [00:23:44] Got it. And I know you also talk about like, not naming your thinking styles, these kinds of like, oh, like negative Nancy or like, right? Like things that are going to put bad idea in your head about, well, this is the kind of thinking style we don't like, or there's something like wrong with this person or that sort of thing. 

Indi: [00:24:01] I think a lot of people have already heard that message. I think the more subtle message is if you put a face and you're like, hey, we're going to be inclusive. Let's put a face that has brown skin and let's give her a name that, you know, Sounds foreign or something, then it becomes harmful because what's happening is that you're using those demographics to then assume things and you forget.

So a thinking style is described by three or four or five sentences and that's it. 

There's nothing else. Yeah.

And the other thing that I get asked a lot about this is like, well, my company is not ready for thinking styles. We have personas left and right. Can I merge them? 

I’m like, totally.

You have to land these things. How it works in your context. So one, person's all like, I'm going to take those three, four or five sentences and shove them into the block where the picture used to be, because the key is to get rid of the demographics, right? 

JH: [00:25:09] As you said in the very beginning around, you know, labeling someone as an edge case, very dehumanizing, right. And not a particularly helpful frame, but as you do start to like, see these patterns and develop thinking styles and stuff, I assume often you're going to realize that some of them are more prevalent than others.

Okay. So the people who are very mindful of their time in the business, whatever reason decides that is the thinking style that we want to prioritize. Is it okay to say that these other styles we've heard, we're just not going to solve for, or?

Indi: [00:25:38] Yeah. Yeah. In fact, I think that's a smart thing to do because we don't have enough resources to solve for everybody right out the gate. And there are organizations where you're just never going to solve for one of the thinking styles. You know that they're doing something that you are just not interested in, didn't doing as an organization.

That's just not something we're gonna be, you know, supporting. But the idea is that yes, prioritize. Usually if you  want to put it, honestly, the organization's already prioritizing the thinking style. That's just like them. The one that's prevalent, the one that's kind of average, right?

The one that people make a lot of assumptions about. And you'll find one of these thinking styles kind of matches that. And so the challenge is to say, okay, let's go beyond that. What is a thinking style that we can support?

That's different, what w but that will add to how we I don't know, make profit, how we make a better name for ourselves, how we retain people, how we reduce costs, how we, whatever other business type of goal the CEO has. 

Erin: [00:26:55] Right and a lot of applications of this one is, you know, we've got like, let's say an ideal customer profile. We know how to make good money from these. If we understand them better and kind of break them into groups, we could serve them each a little bit better by understanding their different ways of—

Indi: [00:27:09] Yeah. And that's apparently not going to fly. That's not going to get funded as a research project. 

Erin: [00:27:16] Right. 

Indi: [00:27:16] Yeah. It's I think the question about like, well, who are we harming and how are we doing the harm that'll fly, especially now. I think the question is because, you know, like with this airline, we did eight studies back to back and we kept asking to recruit people with physiological problems and disabilities (I shouldn't have said problems) and they wouldn't ever approve it. 

JH: [00:27:41] What was the rationale like at a high level?

Indi: [00:27:43] We didn't get to hear the rationale. We were, you know, the cogs in the wheel.  So, I think that there are different questions that we can ask to try to show where we're missing information that could be really valuable to the organization.  

Erin: [00:28:00] Someone asks, we've got a question here about the street verbatim because it's short and as simple as possible. What is your technical definition of pattern? So I'll just add on to that in my own language, which is: You could imagine, you could say any people that have two things in common, there's a pattern, you know, where there's five people and in a five with two things in common, that's a pattern you talked about like foremost or four fronts, right?

Like being a leading part of their philosophy, being an important aspect of a pattern. But when you're thinking about how many patterns there are, how many thinking styles is like the right number for us? 

Indi: [00:28:40] Oh, you don't ask that. 

Erin: [00:28:42] You don't ask that question. 

Indi: [00:28:43] Yeah. You don't want to bias or curate the data. You want the data, tell you what it has to say. So you never ask what's the right number of thinking styles for us. That's a moot question. That's like, you know, I don't know. I don't know what a good analogy is, but I can describe the pattern.

So there was something that I said that I base everything on, which is the definition of cognitive empathy. Okay. I want to do that because I want to be able to act like this person. I want to be able to act like this person so that I can design for this person so that I can, you know, make services that will actually help them and not harm them.

I can unarm the design. Right. What are those Things that define the definition of cognitive empathy? I'm going to give you like everybody, like two seconds. Can you, I remember in your mind, and then I will tell you, there were three of them: inner thinking, emotional reactions, guiding principles. three are set.

They're set against things that we get out of their data at the surface, which are explanations. How things were done, how they work, why they work that way, preferences, opinions, those are all at surface. What causes those preferences? Where did those opinions come from? That's over here in guiding principles and inner thinking.

That's what we want. Okay. Context setting scene setting. That's not inner thinking. There's always two layers. When we're doing an, a listening session or an interview or a non-directed interview. The two layers are the person talking with you. Like There we are in an interview and we're communicating. And the other layer of the person being back where they were in time and place and the thoughts running through their head and the emotions and their guiding principles are brought to bear.

So that's the second layer. And I want that second layer. And often what happens in our interviews is it stays all first layer and people will tell you their opinions and they will generalize about everything in terms of you know, you know, I like coffee. Why do you like coffee? Cause you know, blah, blah, blah, whatever, you know, it's just kinda like preferences and then it, and then little bits of opinion and maybe explanations. Like I get coffee at this one spot on the corner, because it's on my way to pick up my kid from school or whatever. Right. So, And that's, as far as it goes, you never get down to the level of inner thinking, emotional reactions and guiding principles. What's behind that. 

Erin: [00:31:29] We got to go deep or at least below the surface level to get to those patterns that—

Indi: [00:31:33] Yeah. So the patterns are, someone might have some inner thinking and you might think, oh, well then somebody else has the exact same inner thinking.

Well,  that rarely will happen if you get populations of bigger than 35 in your study. But And you've got a fairly narrowly defined, there's all these dials, right? A fairly narrowly defined purpose. But what I do is I look for patterns by focusing on mental attention. So for example, if you've been in a near miss accident when you're in the accident, your focus of mental attention is like, Hey, let's, you know, keep the harm from happening, right.

When you're right after it, you might have a focus of mental attention. You idiot. Why did you, do you do that or, oh my God. Why did I let that happen? right. Those are both similar focuses of mental attention. Now you're inner thinking might be why did I steer into or steer out of the slide on the ice?

Right, or it might be, why did I yell at that guy in the car? Who could have run me over? Because I'm a pedestrian. Right. So Why did I, and it could be all sorts of different scenarios, different contexts, different kinds of near miss accidents, right. And yet you have the same Focus of mental attention.

And that is what brings these patterns together. Okay. So with respect to those thinking styles around the airline, let's say that one of the focuses of mental attention is like, my time is really valuable. I want to use it to the best of my ability. A lot of the people we're talking about being able to get home to their family, Right, that is what's driving. That other people were talking about. Being able to get things done for work or for one person was knitting a sweater for a new baby, right. Being able to finish this project. Same focus of mental attention. 

Erin: [00:33:47] Right. 

Indi: [00:33:47] Okay. In general. Yeah. 

Erin: [00:33:50] Right. And it's okay. That the underlying reason behind it is different. The 

focus is different. 

Indi: [00:33:56] Right. 

Erin: [00:33:57] I've got a question here, like kind of a B2B use case as someone, you know, like let's say business insurance, but the customer is a business.

Indi: [00:34:05] Right. Oh, same way. I've done that study a couple of times. Exactly the same way. So let's say you want to do insurance for business customers. I go find what the purpose is. Right? What is a purpose that you could study and how broad of a purpose, or how narrow of a purpose do you want to study that you could study?

Once you find what that business purpose is for insurance? I don't know. I'm afraid to use the one that I did because it's proprietary. 

JH: [00:34:36] Sure. Yeah. 

Indi: [00:34:37] So I'm trying to make one up. Let's see... if you are In business, maybe one of the things you insure is all the equipment, right. And you've got You know, computers, breaking phones, breaking, and telephones breaking, and, you know, things like that.

Oh, let's say that you're insuring your digital equipment and your devices and stuff. And so you go and you talk to people and you say what went through your mind the last time? And then you have to find what purpose you want to study. Let's say the last time that you had Something broken, right. Something happened, let's say you get a story about a laptop breaking and somebody losing a potential client because that particular thing they were going to show wasn't available and they hadn't backed it up and blah, blah, blah or whatever. I don't know, I'm making this up on the Fly. 

Erin: [00:35:27] No, but... how do you think about the difference? Like different people at the business who might, you know, right. Like the purchasers of whatever you're selling versus right. The legal versus the end user, right. And all these different, this committee of people who are going to be part of this decision. 

Indi: [00:35:43] So it depends. It totally depends. It's just like in jobs to be done, they make the same discussion. Right. So, we were working with a team of folks, trying to figure out what the exact differences are between what I do and what jobs to be done. Yeah. And one of the things that one of the examples was this idea of somebody who's running a fleet of trucks.

And in the study that I did, we went abroad. We allowed the fleet of trucks to be semi-trucks with tractor trailer kind of rigs. We allowed them to be fleets of bulldozers. They were also fleets of plumbing, trucks, right. Being sent out to various people's houses to fix things. So, we went abroad and what we did was we looked at them because we wanted to understand the company was a company making hardware for tracking, and the dispatchers were closest to the tracking. But as we were doing that, we learned that we needed to hear the drivers' stories. And so we went and found, we didn't do as much work in that area, but we went and got a bunch of those stories from certain  drivers who were facing a certain issue with regard to the tracking. So, So, yeah, that was how we did it. The folks who were doing the jobs to be done, what they did was the Division manager. I think it was some manager, a little bit higher up than the dispatchers. So, it's a discussion, right? We could have gone a little bit higher and tried to figure that out.

And in fact, in another semi-related story, we did go a little higher to the owners of the small business that we reduced it to small businesses. So in that particular study, there were no semi truck trailers. There were no bulldozers. And what we found was that people were having a hard time.

Trying to decide when to add to their fleet when to grow their business. And not having A hard time with dispatch or tracking people. 

Yeah. 

Erin: [00:37:49] I'm imagining you're like on the thinking style squad and then there's like another jobs to be done squat or this is these, are you all working. 

Indi: [00:37:57] If we're working together to try to figure it out. yeah. Yeah. We're because there's so many differences and so many similarities. Jobs to be done are kind of, the business person who doesn't want to waste money on doing research. Right, just tell me what to do. And so they've liked packaged research in this, well, gift box so that the buyer doesn't have to know there's actually research in there. 

JH: [00:38:21] Oh, interesting. 

Indi: [00:38:22] Yeah. 

JH: [00:38:22] Because the output is so testable for somebody coming at it—

Indi: [00:38:26] Yeah, and there are different churches or whatever jobs to be done apparently. And certain people do research more, in better ways than others. My approach though, because what I'm really after is trying to understand different people's perspectives and to stop harming them because we are harming them.

So what I do is I try to be very open about my bias, my team's bias. I don't want that affecting the data, the focus of mental attention. We don't know what it is. Right. We don't know. What are the thinking styles going to come out of this? How many we want the data to be able to say what it has to say.

We want to actually hear other people's perspectives, understand other people's perspectives. So that's One of the key things is that I think what comes out of what I do is more of the associative innovation, the idea that we're using focus of mental attention for our affinities, we're finding innovations and much different places  than sort of the step wise kind of innovation that you get.

Out of that. Yeah.

But you know, some Of those searches do some resources fairly well. 

Erin: [00:39:45] Yeah. Right. And it's not that one is better than, you know, they both have different values to bring to your effort to understand your— 

Indi: [00:39:52] And I think what's happened too, is the jobs to be done is like all of a sudden A thing that agencies do for other companies. And so they have a very cut and dried way of doing it so that they can do it scalably over a bunch of dirt, you know?

So, Yeah, And I think that's one other difference with what I do is that we all know you can't do things exactly the way they're prescribed. We have to do them because we've got that boss there and this like constraint over here and you know, this team and we're going to do things that are gonna work for us that we can do.

We're not going to try to bite off something that we can't do. 

Erin: [00:40:35] Yep. We've got about eight minutes left and about five questions. So we'll do what we can to bang through these, if that works for you, Andy question number one, I think you're going to have some recommendations here, recommendations for better understanding thinking styles in our write-up we can link some, you know, resources and articles and things 

Indi: [00:40:52] Yeah. On my website. There's a great description. Under the courses, and then on my publication, there is a whole set of things that describe thinking styles. I'm also writing the first book on thinking styles right after this next book that I'm putting out. So, yeah, there's a lot out there. 

JH: [00:41:13] Cool. 

Erin: [00:41:14] Someone here has a, there's a, the subject matter is sensitive subject matter, and it's preventing them from doing ethnographic observational research. Can they do interviews instead to uncover thinking styles?

Indi: [00:41:27] So I don't know what context you're in, but I bet it'll work. What I do is all of my listening sessions are remote audio only. I do that for a reason to better form the connection for trust to build. I use my tone of voice. The other person feels a little bit shielded by not being present, not having you in their presence or being in your presence.

And what we really have to do is form that trust before we can get to depth. People are not going to just open up and be vulnerable to you. Right? So that's the format that I use, to be able to form that connection.

Erin: [00:42:11] Let's see. How would you tackle very varied thinking styles in terms of delivering a conclusive finding, for instance, you have an in the literate very low income perspective versus a persona non grata. Not sure what that means, but —

Indi: [00:42:25] Okay. So Illiterate doesn't mean a thinking style. Low-income is not a thinking style. I have spoken to a lot of people in the low income bracket who have different thinking styles that are all human. They all have a mind, and they do very good thinking with that mind. And they have emotions and they have guiding principles that they have learned from their parents and their teachers just like everybody else.

So, the thinking styles that would be coming out of that, like I had thinking styles coming out of this was a group of people who were wanting to go to college to level up and I couldn't afford it. Right? So the thinking styles were a better life for my family. That was one thinking style.

I just want a better life for my family. We cannot go on this way. And then another one was, I want to do good. I want to help people. And by helping people, I think that I can, you know, change rolled in, you know, very small ways. 

Erin: [00:43:29] Right. And they might've come from very different contexts, but this was the forefront of their mind.

Indi: [00:43:34] Yeah. And notice none of those have to do with how much money you make.

I mean, yes, the better life did. I mean, they both are trying to get out of poverty. Right. But it's a thinking style. It's a human thing.

JH: [00:43:50] I had a question just on averages in general, while we're wrapping up here, since that was the header topic it feels like there are some applications if you narrow it in right where an average is like a useful statistical tool. Right? So my son was running a fever the other day. If I took a couple of measurements within like a 10 minute span, and then I average those out, I probably get a better read of what his real temperature is in that 15 minute range. Right. Then one single measurement for some purposes. Right? If it's 1—

Indi: [00:44:14] First of all I think your son would object to having his temperature taken that often in one 15 minute period. 

JH: [00:44:21] Done it. Yeah... 

JH: [00:44:24] You're taking some of the variants out right. Of like he had just run a lap around the house before the first measurement was a little high and then he went outside for the second one was a little low. And you do it and you start to like it, so there is some use for it. Right. But is it just that, as a statistical tool, we misuse it on the design side often?

Indi: [00:44:41] I think even mathematically, there's also this idea of the mode, which is the number that comes up the most frequently. And the average is often not a number that ever came up. 

JH: [00:44:53] Right? 

Indi: [00:44:54] Right. So, yeah. So I think that your question though is like, man, we are looking at it wrong for the whole purpose of doing a design, we can't design for something that doesn't exist. Like that number never came up in the temperature range. But you could design for the number that came up the most, but maybe the number that came up the most, isn't the important thing. Maybe the fact that your son kicked you in the shins because he got his temperature measured is more important, right?

So yeah, what are, what, where are we starting? What is the question? And we can't even figure out the question until we figure out, well, what are we missing? What do we think we're missing? We won't know what we're missing because you don't know what you don't know, but we sense from what other companies are doing or from what we're seeing in the news or from what we read in this book that maybe we were missing a piece here.

That's a very researchy way of putting it. If you are a product owner, You would not put money into that. And so I think in closing one of the, one of the most important things that we need, I need to do to get a word in edgewise with regard to strategy is to start developing trust relationships with the people who do.

So if you're just a beginner, just start building a relationship with your manager. If you're higher up, start building with your manager and their manager and by building trust, I mean, having listening sessions repeatedly with them over time, this takes years. If you don't think you're going to be at that job for years then, oh yeah, you don't have to do this.

Or if you don't want to get into strategy You don't have to do that. right. But by building relationships, by seeing who it is, that's making these decisions and understanding how they came up with those decisions. And understanding their thinking and where that came from. Not surface level depth, like where did those opinions come from?

Oh, it was like some big project that you did 20 years ago. And it's sort of influenced everything you've done since then. It's like, wow. You know, I need to know this stuff to be able to work with people respectfully and for them to start to trust me as well. 

Erin: [00:47:23] Yeah, the more we do this, the more I realize the internal stakeholder conversations and methods mirror, the user research methods that you're doing with your dependents. And they're almost as important if you want to make 

Indi: [00:47:37] Yeah. I think they're more important. yeah, And it also seems to be the thing that we're like, oh, we're really good at interviewing people, but oh my God, I don't want to make a relationship. I don't want to get into it.

Erin: [00:47:47] Right. Guess what? They're human too, right? 

Indi: [00:47:50] Right. 

Erin: [00:47:51] Anyway thanks so much for joining us, everyone who joined. Thanks so much. And we'll be sending out a recording and a video and transcripts and all of that. So thanks so much. 

JH: [00:48:02] Take care. Bye.