Rich Braden (3:16)

Sounds good. Well, so I started my career as a software engineer, and in my degree, I had one or two classes from a professor who came from Stanford that were about designing software that were my favorite of everything. They looked at things in a really different way than everything else I was doing. And after my second job, I was in Silicon Valley and started down the entrepreneurship path, starting a company and then trying several different product ideas and really got steeped in an approach to trying to find my way to how do we design things that really are useful to other people? A few years later, I kind of picked up improv, acting as a side hobby that became an obsession. And I had a side career for about 12 years teaching and performing improv, which was wonderfully creative. And you could. I mean, you can literally make anything up on the spot.

Nathan Isaacs (4:17)

But.

Rich Braden (4:17)

But to do that, you've got to seriously hone your collaboration, your listening skills, your lose judgment of everything that's in your head that you don't let out normally, which sometimes gets you in trouble. But all of those mixed together in a really lovely way. And so that's how I came to this set of principles. And then I was teaching an improv for Educators class and met a couple folks from Stanford's D School, and they invited me in and taught me what design thinking and this whole movement was about and started teaching there, where I ran into Tessa. And at that point we met and we started talking a little about how we saw design thinking and how we saw it a little differently than how we'd been introduced to it. And it just. I don't know, to use modern lingo, it started to vibe, I guess, but we really shared a worldview of it was different than the procedural, structured way that we normally had seen it done. And we thought it had a lot more freedom and needed a lot more of what I think of as the thinking part of design thinking and really charting your own path through it.

Jason Giles (5:32)

That's amazing.

Rich Braden (5:33)

That's where we started teaching together.

Jason Giles (5:35)

That is. That is great. And was it just through these kind of conversations that you decided, you know what, we're onto something here, like, maybe there's a book in the making.

Tessa Forshall (5:46)

I think, honestly, as an academic, Jason, the last thing in the world that I want to do is write a book, because I have seen the misery it puts so many of my colleagues through. But actually, the thing that really made us write the book was year after year, and we've been teaching this, I think, about seven years now, year after year, students were sort of saying to us, like, hey, where's the book? And we would try to find existing articles and things like that to kind of curate the list in the absence of a book. And they just kept Asking and kept asking. And eventually after one of our intensive classes that we ran at the Harvard Innovation Lab, Rich and I were like, okay, we just need to write this now.

Jason Giles (6:30)

I love it. Well, the approach to this whole problem space really resonates with me. I think Rich and I were talking previously around this idea of whether it's improv or jab or jazz, but reducing that barrier and maybe making something that we think is really intense, a little bit more approachable. And so maybe, Tessa, would you be able to talk a little bit more? You talk in the book about this idea of our innovation hesitation. It's this idea like, you know, there's just something that's holding people back. And as you through your research and through your work, I guess I'm wondering what surprised you most around the causes of that hesitation.

Tessa Forshall (7:21)

Yeah, absolutely. So I think that there are some pretty obvious causes and I'll just touch on those before we get there. The first being like, there's a real mythology around what innovation looks like. You know, Rich and I ran a survey that was several hundred people, gen gen pop, representative sample of U.S. adults. And what was fascinating is about 90% of them, when asked the question, you know, who is an innovator, actually named the same five people, which I really didn't expect to see. But they were naming Edison, they were naming Einstein, they were naming Gates, they were naming Musk and they were naming, oh my gosh, Facebook. I've just completely blanked on Mark Zuckerberg.

Rich Braden (8:06)

Zuckerberg.

Tessa Forshall (8:07)

His famous dorm room is just here. I shouldn't have known that. But that was really fascinating to me that there was this very clear vision of what an innovator looks like. Where it happens in places like Silicon Valley or New Yorkshire, but also if not in those places, at least in special buildings with fancy rooms and post it notes and you know, Birch and cold brew and like all those kinds of archetypes. And so that was quite. Is quite interesting, but not so surprising. I think the thing that surprised me the most is actually the sort of cognitive side of why we have a hesitation to innovation. So if you think about it in evolution in history, there are really good reasons why you or Rich or I or anyone else might want to make sure that we stay as part of a group and don't embarrass ourselves and get isolated from it. A great example of that reason is like, I have a two and a half year old. She doesn't want to be isolated from the group because that's a survival limitation. Right? But that Was that also historically has been true for adults. Right. If you, we went off on your own, you became much less likely to survive. Similarly, in, in our ancestral times, if you think about ambiguity, ambiguity could be really bad because if there might be a, you know, bear in the woods where you're camping in Yosemite, like that's not good, like that could again impact your survival. And so as humans, we always had a focus on, you know, clarifying risks and mitigating them. Again, very helpful. Let's keep us all alive and not get eaten by a bear. And B, you know, we through that making the ambiguity concrete. It is or it isn't. Either I'm moving or I'm going somewhere where the plane has open sight. There's no ambiguity about what's around me. And I've got this. These are really natural innate human processes and they're not bad. We don't want to get rid of them, they help us survive, but we actually often misapply them to innovation. We think because of this beautiful almond shaped part of our brain that's called the amygdala, we often get into an innovative situation or a situation that requires innovation, and we either hear innovation and then we assume that means like risk and ambiguity and putting ourselves out there. And the amygdala starts ramping up its role and engaging a lot of these cognitive processes that evolutionarily have been really helpful. But the truth is, I want to, I'm going to go with 99.9% of the time, innovation won't result in a bear eating you in Yosemite National Park. And the reason I'm not going with 100 is because I know a lot of innovators go to Burning man and there's a definite possibility there. So 99.9% of the time, and also overwhelmingly when we're talking about the types of risks in innovation, which is small failure, small risk, tasting, testing, iteration, those things are actually not going to result in exclusion from a social group. In fact, doing the really big thing without testing it and then it being an absolute disaster is much more likely to result in the exclusion from a social group. So all of that is to say, I think we have these evolutionary cognitive processes that are just misplaced when it comes to innovation. And they seem to be holding us back from stepping in and starting to engage.

Jason Giles (11:43)

Well. And certainly if you have this mental model of who is an innovator and it's with that elite crew, like, there's no question of why some might think, well, that's not for me. Yeah, I'm, I'm not, not like that. One of the things I found really interesting, Rich, you, you introduce us to this kind of approach of reducing that, that barrier and you introduce us to this thing called shots. You got your roof shots, your cloud shots, your orbit shots, and of course the moon shots that maybe a lot of us are more familiar with. Can you kind of talk us through that and how that might help leaders scale their innovation efforts with either not defaulting to just absolute incrementalism, but this, I think what a lot of us sometimes fall into is this all or nothing mindset.

Rich Braden (12:38)

Absolutely. Yeah. I think many people default by thinking, if it's innovation, it is gigantic. Like moon, we're going to the moon in 10 years. Moonshot, and there's plenty crispr and cryptocurrency and Waymo self driving cars. There's lots of big moonshot ideas and they're awesome. We love those, of course. But that's not the whole total of innovation. If it was that, I would be intimidated after all of my experience teaching it, thinking, oh, I can definitely come up with a moonshot idea. And you know, maybe I can, but it doesn't feel so tangible. I think the idea with the shots is it's a spectrum. And whether you use exactly our names or not, we kind of go look underneath a moon shot. There's some orbit shots and then there's some cloud shots and some roof shots and jump shots. So a jump shot is sort of like an essential new feature in a system you already have. An example might be, I don't know, maybe you can highlight incomplete sentences as you type.

Jason Giles (13:44)

That's.

Rich Braden (13:44)

That's kind of a fun new thing. Helps a little bit. But then a roof shot is more like a collection of features that kind of enhance and reshape that system. So if you update several things like that into a text editor, you have a smart editor now. It on a daily basis improves your productivity, helps you out. But a cloud shot version of that might be embedding it in like smartphones, autocomplete across every app, wherever you are. It's any app automatically gets it. That's a little bit bigger innovation because your sphere of influence, your impact radius is bigger. And then an orbit shot is something a little more revolutionary, but it might be siloed into one industry, so. Or one type of thing. Like I would say generative AI is as a category more like an orbit shot because it does predict. It's like super fancy autocomplete. Right. There's much more to AI than just large language models. And so if you think about AI or generalized AI, we have a paradigm shift that is going to change on a Gutenberg level, on an Internet level, or maybe even bigger. If we can achieve that, it's going to change the whole paradigm. So that I think that's the range that we're talking about. We saw a concrete example of this. Tess and I got to go to Saudi Arabia last year and visit the NEOM region. And for those that don't know, NEOM is about a Belgian sized area the size of Belgium, where they have many different really big moonshot, maybe even I think Tessa calls a Mars shot ideas, they're gigantic. One of those is called the line. It is a new take on a very old idea of a city that is a straight line. It's vertical, 500 meters tall and it's supposed to be over 100 kilometers long. You're also supposed to be able to be anywhere in the city within 15 minutes and everything you need is within a 15 minute walk inside your house. If that is not a really big innovation idea, I don't know what is. But when we got there, of course that's impressive. But what we saw were people that look like many other places in New York, in Silicon Valley, in Sydney, Australia that we see that are smart, capable people solving problems. But to build that city, they have to build sections of the building and lift them up up to 500 meters in the air in the windiest place on or one of the windiest places on Earth. So cranes don't work very well because things can swing around. So they had to create an orbit shot of lifting, getting those things up in place in a safe way. And then to even build Those, they're using 40 millimeter rebar, which if you don't know the normal stuff is like maybe 8 to 10 millimeters. It's gigantic steel rods and they don't know how to bend them. So they had to create a more of a cloud shot of a robot to bend the rebar into cages, to be able to pour the cement and to get the volume of cement that they needed to be able to pour those in the volume they needed. They had roof shot and jump shot logistics, road paving to get the cement trucked in in the timing they need. So those aren't revolutionary, but they're critical. So if you have even a moonshot idea and many companies have one, that's their main product, you need to support it with a whole portfolio of innovation underneath just to Serve that one idea.

Jason Giles (17:29)

Well. What I love about just the kind of framework is as a design leader, I think about it gives me taxonomy or language to use as we talk about those different levels. Right. And you know, to achieve something amazing, we sometimes don't take into account that this innovative mindset, even on the small things, are part of what, what, what gets us there. So I think I, I, I love the metaphor. And again, it's just a one of those other tools that other design leaders can kind of start throwing into the mix, because I think it's around everybody having that innovation mindset, and the more that can participate, participate in that really, that's where you're starting to make the, the big impact.

Rich Braden (18:12)

I think it's that inclusion of everybody can be involved. It reminds me of the, I don't know if this story is true, but I love it of the janitor at NASA and somebody says, what are you doing? And they're like cleaning up, saying, we're putting a person on the moon. Right. Like they're invested in and their contribution is critical for everything else to work. And that's what I love about the shots.

Jason Giles (18:34)

I love it. Tessa, you know, the book, it really emphasizes that innovation, it's just not about brainstorming and design sprints and these type of exercises that maybe we've kind of canonized a little bit. It actually begins with a deep understanding of people. And so can you talk to us a little bit about what, how some of some teams can kind of go to go past the obvious, uncover some of those deeper, deeper insights into what make people tick and why it matters?

Tessa Forshall (19:14)

Absolutely. One of my most favorite mindsets that we talk about as being essential to innovation is this idea of interacting with others. And it's essentially the mindset of, I'm going to go out into the world and learn from people. And it's fascinating, I think, to me when we have class, how, how much resistance there is from a lot of people to actually just going out in the world and talking to customers or users or stakeholders and just like hearing from them, having a chat in a coffee line, like, whatever it is, it's quite fascinating. But we really, really push the point much to our students, sometimes dismay, that this is an essential aspect. And one of the core reasons for that is that a lot of people don't realize that your brain quite literally processes information differently when you engage in empathy, when you empathize with other humans in an interaction. So empathy activates neural pathways that allow us to suspend assumptions and to deeply understand Others experiences and perspectives. And so by doing that, we're essentially able to reshape and reconsider and reconstruct our understanding of certain circumstances and circuit certain mental models or perceptions or beliefs that we have. And that's really powerful because actually, without empathy, that's really, really hard to do. Like, having somebody understand that, you know, the way that they perceive something is not actually truth, and to re, like, have them reconstruct that neural pathway and belief is, Is incredibly challenging. But with empathy, we seem to be able to do that much more quickly and much more efficiently. So not only are you actually like doing a good thing by centering a human voice, but you're also actually, if I'm honest, like, helping and supercharging your team's ability to innovate because you're using your empathy and your interactions with other people to start seeing things differently and in unexpected ways and to make connections and to illuminate surprises that you would not have otherwise seen had you not had that interaction, not only because of what they said, but also because of the malleability that you're introducing into your mental model. So it's, it's actually really important.

Jason Giles (21:50)

I've, obviously, I've been in design and research for decades now, and I, I literally did not know that there was a scientific chemical neuron pathway where empathy has a, has, has a role. You mentioned that folks are, are a little bit hesitant. You have to kind of force them sometimes to go out there. And yet when they do, we call it the aha moment. Like when you all of a sudden see something through somebody else's eyes and it really motivates. I'm curious, you know, do you think, going back to kind of earlier discussion around evolutionary, like, why, why do you think that is that the people hesitate to just put themselves out and, and, and engage with, with, with the world in, in that space.

Tessa Forshall (22:45)

I think there is a lot of social anxiety. But I, I also think, I mean, at least for I can speak from my experience teaching this, that I've noticed it become in an even bigger ask of students in the last few years than it was before. And so I do think there's something to like, you know, if you went to Covid school online and you're a young person, we know, you know, from a lot of the work about devices, the, the biggest issue is, or one of the biggest issues with young people and devices is not so much the device itself, but actually the behavior that that's replacing. And often the behavior that that's replacing is a social interaction. So I think people are a little bit scared. I also think empathy takes effort and a lot of we like, we tend to make very fast value judgments and decisions unconsciously using our value system to minimize human effort versus game. And so often what will happen is if you don't have a learner who has, or a tester or a designer who has experienced that aha moment again and again and knows that empathy reliably helps them do that when they're making a decision about, well, I could go out into the world and speak to people and that's foreign to me and I don't know how to do that versus I could send a survey out from my computer. The value reward system that, like that sort of deep neurobiological system that we have it, I think is going to make that calculation and you're going to do the survey. Even maybe if you intended at the beginning of the project to go out into the world and engage with us. It's kind of like, you know, when you eat the cookie, even though you told yourself, you know, wouldn't like it's the, the value reward system in that moment is like, actually I'll, I'll eat the cookie. It's yummy. And I'm standing here in front of me. And so yeah, that would be my kind of reason. I think there's a social, social play and, and just our intrinsic values model.

Jason Giles (24:50)

I, I think that resonates really strongly and you know, kind of similar to innovation in general and kind of the, the discussion you have in, in the book, it's around reducing those barriers. And I know many times I've got designers who, you know, they've been taught how to go out and you know, get feedback earlier in their process and it can be quite intimidating. But make reducing that barrier by starting small just so that they can have even the little, the little tasters. Rich, I'm sure that you've done a lot of this yourself, both in the teaching that you've done and in your practice, as you've gone out and engaged with, with people and you're looking for those insights. You know, what, what are, what's the difference between maybe an insight that would lead to some real breakthrough innovation versus maybe feedback that just has an impact on a surface level.

Rich Braden (25:50)

Yeah, I mean we know that we have a lot of internal biases that work against us here. So like jumping to conclusions and, and confirmation B and bandwagon jumping on to like latching onto a, a data point that we really like or we hear first that can, like, send us down the wrong path. So I think it's about making sure you collect enough data and enough is relative. Like, it's. There's no clear. You must capture 47 different interviews in every design project that you do. It's an evolution. You have to sort of feel your way through it. But collecting enough so that you can get past those biases and then make yourself aware that there are biases to look for it. So you got to stop and check in and look. I know I keep coming back to this point. Why do I, do I really see this? Or did I fall in love early? So I think that's, that's a piece of it. And then it's going through the analysis of all this data, looking for surprises and contradictions, intentions, things that are there, and then putting it out in front of you and processing it as a group. So in the synthesis that you're going to do, you're trying to make a big abductive leap, right? You're taking not enough data and make a prediction about how the world works based on not, not complete data. And that is a difficult thing to do. But what can help is to make sure that all those nucleation sites, all the data points you're going to use to make that leap at least have some validity. And so an example of that is we were working with a big quick service restaurant that had a supply chain they were redesigning. And we took interviews, massive number of interviews. We did them some together and trained them, and then we sent them off in the field for six weeks to collect and do interviews and come back together. And then we plastered a huge conference room wall full of all these insights and we distilled them down to point of view statements. And once we had those, we started. We had everyone go around and share and look and pull and cluster them together. So anything we used moving forward had at least three or four different sources where we had found the same thing. And it's in those that we start to get this insight might be a little more durable, it might be a little more important. And it's not based on we really, really, really think, think it. It's based on we have hard evidence that's external to us that we can point to and that's a much better place to get insights from. And some were very surprising and stood out. Like one in particular really stood out to me. We went into a place where they were, this is a restaurant, so they were, it was a bakery making buns and they come through some very expensive machines that like they count the seeds that go on top of the bunch of with vision to make sure there's an appropriate distribution of them. Right. So this is highly technical. They come out the other end and the manager who is was there to put them forward, counted by hand all the buns and wrote it on the printout of the count. And we asked why and he said, because I don't trust any of the data. And what we found is that one story, what showed up on many places on that wall, that trust in the data that they had was an overall issue. I don't know if accuracy or precision were actual problems, but the how the data was used and interpreted in the system had problems. And there were plenty of examples of why that had come up. So that was a thing that we knew we needed to solve is people needed to trust the data they had. Whether it's changing perception or fixing the data or integrating it better or all three. That was something that needed to be fixed. Unless they trusted the data, they were going to be blocked and not able to move forward fast.

Jason Giles (30:04)

Got it. And that rigor to have all those data points, amazing. Particularly when you need high confidence for maybe some of these bigger orbit moonshots. On the other end of the spectrum, I know you encourage testing ideas early and are there like low risk ways where you can kind of also get some value but maybe where it's not in such a high risk situation?

Rich Braden (30:40)

Yeah, absolutely. I think the guiding principle here is that evidence over opinion. You want data when you are testing and then you want to make a lot of small prototypes and test lots of different things very quickly and expect that many or most are going to fail. I think that's the recipe. We're really engaging with this. So if you wanted to sell a product like I have an eraser flashlight, it's a special laser light and you can put it over paper so students, they don't mess up their paper, pen, pencil, it takes everything off. Seems like what a magical idea, right? And we could go and ask parents and teachers, hey, would you like something like that? And many of them would say yes, because erasing is kind of tough. I have a third grader, so this is like day to day for me. It comes up, but instead of going out and asking people, would you like this? We could bake a website and have photos and have a buy button and if somebody clicks on that buy button, they're trying to purchase it. That's much better data than an opinion because if we Go back to those people who said yes and say, hey, here's this, you know, $20 eraser flashlight. Do you want to give that to your third grader? A lot of people are going to go, oh, batteries, and they're going to lose it. And no, I'm not going to pass. But if they click on the buy button, we know they're interested. So that's one level. But then we could collect the shipping information. They're willing to put personal information in. Now that's even better and stronger data. And if we get to credit card information, I think we stop. I think now you've crossed a line. Don't actually take credit card information, but you can put up a message that says, hey, this is on backorder. Tell you what, we've got your email and when we have more, we'll send you a 25% coupon. Sorry, it's on backorder. So you can construct that as a very fast prototype and you can pay off the information that you got, which is a little, but not a lot with that. And it sounds like a bait and switch. But if you are thinking about it and you try that idea and you get thousands of people trying to order it now, it changes the game and you're like, actually, let's look up some manufacturers. I think we could make this real. You would pay it off if there was enough interest. So I think it's using methods like that where you go and do tests that look very real in the world but take very little time. I did that in one of our classes. From week to week, this topic came up. I had a friend during the pandemic who said, I've got this great idea for remote wine tasting. We'll connect sommeliers and wine with people that want to do this and we'll get them all together. And I'm like, okay, bud, let's actually look at this before you start buying cases of wine. And we put a website together in a week and I presented that back to the students and they were shocked how much we could learn. It turns out that idea did not pass the test, which is a good thing. We learned it very cheaply. And that took a week with traditional. But in an hour with AI, you can generate that website and have it up and running so quickly. Now AI is changing the prototyping landscape tremendously. So you can do this actually very quickly. Don't make a full on version of a product before you make sure somebody actually wants it, I think is the idea.

Jason Giles (34:14)

Well, and to. To Be able to incrementally increase your confidence. And whether this is even. It's. It's kind of like trying to find your way through the dark. Sometimes when it comes to innovate, we've got these big ideas. We think that there's something out there, maybe there's just a little bit of a gut. But the quicker that we can start realizing, hey, you might be onto something. I really like that example actually of the website with the different signals along the way because you're like, okay, well this is one signal. But actually if they did this, you know, and really thinking, thinking through it in that strength of confidence and as well as the, you know, in your case study there of like, yeah, I don't think this is a direction that we need to go. But think of the savings and the risk that you've avoided. Yeah, yeah.

Rich Braden (35:05)

Lots of ideas with a small number of people and then incrementally fewer ideas as you hone in more people and more cost of developing the prototype. It's a safe way to mitigate the risk of launching. And that works for products, but it works internally at a company with a new people team program for, I don't know, collecting feedback or for doing performance reviews, you can ease your way into it and make sure it works.

Jason Giles (35:35)

I love it. So, Tessa, in the book there was another concept that is introduced, metacognition. This is the first time I've heard, I don't know if you coined the phrase, but it's this act of stepping back and thinking about how you are thinking. And so when you think of the context of innovation or creative problem solving, what is the impact of that? And practically, how can teams start practicing it today?

Tessa Forshall (36:08)

Yeah. So metacognition just a sort of baseline. Meta meaning sort of above or self referential and cognition meaning how we think, feel and act. So metacognition is the being self referential and thinking about how we think, feel and act. I didn't coin coin the term. It's been used in education and learning for a long time. But my research has evolved it and I think about and study a concept of metacognition in action. And so that is metacognition that is not just about reflecting and thinking about my thinking at the end of something or when it's done, which is quite common and certainly what Rich and I used to do in our design classrooms too, like have a lovely session at the end where we all did thinking routines. Or if you think about in companies, often you have like your splashdowns and Your retros, or if it is during the course, you still have designated meetings or spaces, maybe a pause or a separate stage gate. But metacognition in action is really this idea that you are thinking about your thinking and therefore adjusting and navigating and changing what you're doing in the course of doing it. So metacognition and creative problem solving is really important and we already knew that. There's some great work out of the University of Kentucky where they gave half of the students metacognitive tasks in their creative problem solving class and taught them metacognitive skills. And half of the students didn't get them. And the students who were metacognitive throughout the creative problem solving course created more ideas. So I believe it was twice the number of ideas than the students that were not metacognitive. Their ideas were three times more novel, so unique and creative. And when the final products of the students were judged by a committee of independent design experts, the students who were metacognitive's work was much better. So as you can.

Jason Giles (38:21)

That sounds amazing, but what does that mean? Yeah, in practice.

Tessa Forshall (38:26)

Yeah.

Jason Giles (38:26)

So what were they doing?

Tessa Forshall (38:28)

So what they were doing is really, really simple things. So when we studied them, when I've studied them, what I've noticed is in the middle of a project, they'll pause and they'll notice that maybe the strategy of interrogating the acronyms that their interviewee is using means that they're missing insights. And they might stop and think about that strategy and decide for the next interview that instead they're going to write the acronyms down and circle them as they hear them, but they're not going to talk about the acronyms and they just going to engage in the conversation with the person to elevate the insights. Or it could look like a. Another example is somebody who notices that their tendency is to continuously get a task and then like squirrel away and go do it until it's perfect and then show somebody and they might recognize that, like, hey, I did that the last couple of times and that didn't really work so well for me. Maybe this time I'm going to try a different strategy. So. And instead, in one case of me observing somebody, they then went and continuously showing unfinished work every day for five minutes and they got to a final product much more quickly than they would typically and it was exceeding, you know, considered very good and accepted by stakeholders. So they're examples of these little metacognitive strategies that can, can happen if you stop and you start to Think about your thinking and your actions and your choices.

Jason Giles (40:05)

So if I wanted to try this next week with my team, what would be some little things that I might, might want to do with them?

Tessa Forshall (40:13)

Yeah. Great. So the first thing is you need to make space. You can't be metacognitive and cognitive at the same time. Like if you try to actually think and do the thing you're doing and think about the thinking of the doing the thing that you're doing at the same time, like it's not going to go so well. So that's the first thing is make sure that you have dedicated space to do it. And by space it can be three minutes, but it just can't be considered in the flow. And then some great questions that I think to start with are, last time I faced a problem like this, what did I do? How did that go? Did that work? Did that not work? What advice would I give myself for next time I face that problem and am I taking that right now?

Jason Giles (41:07)

Interesting. So simple.

Tessa Forshall (41:11)

Yeah. Another example can be some questionings about the bias, like cognitive biases. So for example, you might ask yourself when you've done a series of interviews, am I weighting one of these voices more strongly than other than others and why might I be doing that? Or you might ask, am I Rich mentioned bandwagon effect. Am I holding on to the idea that I heard first and carrying that forward? So things like that can be really, really helpful self questioning techniques.

Jason Giles (41:47)

What I really like about that because I find as I participate as a leader in a lot of these activities that I'm the one that's holding that torch of meta, is the conversation going right. Is this leading to a productive environment and things. But what I like about this and is the inclusion of the team and just like, okay, we're going to take a little three minute step back here and ask ourselves some of these key questions. And to your point, the teams, not the individual, but the teams that are doing this are seeing some really remarkable results. So that's really exciting. That might be the power move, but are there other favorite moves that you recommend that teams really consider? Maybe they're things that could be overlooked but are really powerful in sparking creative problem solving.

Tessa Forshall (42:44)

Yeah, absolutely. So I think two of my favorite ones, so one is in brainstorming, I really like to introduce and Rich actually taught me this, but then I sort of dug into the cognitive science of why is it that this works, is this idea of brainstorming levers. So throwing in different things into your brainstorm so it might be like a constraint. So if we had how might we do X if we were to spend $100 or to throw in a Persona, how might we do it if we were Apple, how might we do it? If we were Red Cross, how might we do it if we were my school's preschool teacher? Right. Like thinking different Personas. And the reason that that works very well is because what you're doing is bringing. So you've in the brainstorm, you've brought forward things that you already know from your archival memory into your working memory. When you throw constraints, you're bringing in new things and then you're able to find new connections between them. So actually, structurally, that's a really good hack or a really good move. The second move that I love, that I think is really helpful for creative problem solving is any kind of collaborative frameworking activity where you're trying to put data into some kind of framework. So it could be as simple as like a two by two that's like impact and effort. Or it might be like a two by two evaluating a person's interview data and based on two different constraints that you notice from that from as a theme from their data. But anything that requires you to collaboratively map like that is really helpful because again, that process of having another person or a set of people who have a different lived experience to you and therefore have a different structure to their archival memory than you do, means that when you interact with them, you're all cueing each other to bring forward different pieces of information that you didn't know before. And like, that is a really beautiful thing. And you can really supercharge just with.

Jason Giles (44:54)

Those two moves that that is, that really resonates. We talk so often around diverse teams coming up with better solutions because they're bringing it. But what you're talking about too is not only is it just what they're bringing together from their background, but then it triggering another side of ourselves.

Tessa Forshall (45:14)

Yes.

Jason Giles (45:14)

That is really. That's really amazing. Rich, I'm sure you've got a favorite move. I know you're coming from the improv days. Is there just one? I know we gotta wrap up soon, but I'm sure that you've got a favorite tool that you like to employ for sparking creativity.

Rich Braden (45:35)

I do. We talked a little about the prototyping, so that is one of my favorites. But the one I'll go to is from an inspiration Inspirations mindset Tess was just talking about. We need, you said diverse collaborative teams. We need that for so Many reasons. And if you're going to have a diverse collaborative team, you've got to get them to sign on and get involved in the project. You also need customers and partners and executive sponsors and investors and board members. Like, there's a whole group of stakeholders that need to contribute in their way to how this project moves forward. And so to do that, one of the best ways we know to influence other people is through story and storytelling. And so from my improv days, that's so much about what the improv I did was. Is about how do we collaboratively. Collaboratively tell a story. And then I did speaker coaching. It was about how do you influence people with it. So one of my favorites is by a guy named Ken Adams, called the Story Spine, and it has gone on to be made famous. People call it the Pixar pitch because they have integrated it into a lot of what they do. And it's a simple form of how do you tell a story that goes from point A to point B in a consistent way? And if you are not a person that knows if that is happening or not, you probably are not telling great stories. Because if you have to land the plane at some point, Right. So the Story Spine is a simple set of sentence scaffolds that they start and you finish them once upon a time, every day, but one day, because of that, because of that, because of that. And you can continue those, if you need, until finally and then ever since that day. So if you just complete those eight sentences, you can tell a story that has a really good structure. Or if you have a story and you can't map it back to that, you are probably wandering around a little bit and not being direct. So it's a simple tool. Anybody can use it. In fact, I use it. I started using it to make up bedtime stories all the time, and then I started reversing it and just giving the prompt. And my kids make up their own stories, which is infinitely fun. So, quick parenting tip. But it's simple because if you can't tell a simple, straightforward story, like an elevator pitch, you don't really understand the idea yet. So it's a good litmus test on do I know what we're doing? And those two pivot points. But one day, until finally can show you. Here's how the problem presents itself today. But if we change this, these other things happen until finally that problem is not a problem anymore. Is a great way to encapsulate the essence of your idea and your innovation into a tight package that you can make somebody understand right away.

Jason Giles (48:36)

That's it. I'm stealing that. I'm going to use it a fun one to start my next brainstorm, but then a final one to see if we've really been able to, or we were able to tell a story about the idea or the, what we're trying to accomplish in the, in the workshop.

Rich Braden (48:51)

Well, we often say innovation is not hard. It's hard work. Like any of the individual things we've talked about is not like multivariate calculus. Right. It's can you tell a story and can you approach that and change the designer? Everyone can do that. But like most practices like meditation, can you stop the thoughts in your head or guide those away? That's a difficult thing to do and it takes work and effort. But as Tessa has taught me, anything you are learning needs to necessarily be effortful. And so you have to put in the work if you're going to learn enough about a problem to solve it.

Tessa Forshall (49:31)

It.

Jason Giles (49:33)

Those are great words to, to wrap up on Brit. Tessa, it's been really, really awesome to, to speak with you. Clearly, I'm sure lots of folks are really interested about the, the book. Where might somebody get their hands on it?

Tessa Forshall (49:52)

Yeah, absolutely. It's available anywhere books are sold. So be that, you know, Amazon, Barnes and Nobles, Target, local bookstores, things like that. You can also go to www.innovationish.com both with the hyphen and without it. It works. And there's a lot of information about the book and us there. Yeah.

Jason Giles (50:15)

Oh, I was going to say, is that also the best way to find out more about some of the thought leadership that you're each doing?

Rich Braden (50:21)

Yeah. Well, there's LinkedIn. You can reach out to us and connect. And then there's also on innovation, ish leads to substack.innovation ish.com and so we've got some research there, but there's, there's research and practical application and we're starting to do a few short videos with tips like that story spine or different things that you can start to put it in practice in small ways.

Tessa Forshall (50:45)

And if you want to check out the academics, you can look up my lab at Harvard, which is the next level lab.

Jason Giles (50:53)

Next level lab. I love it. I personally have walked away with some great practical ideas that I'm going to be taking away and working with my team next week. But both of you, thank you so much. It was really nice to meet you. I'm very excited to dig in deeper into your, into the book. And thank you for being on the show.

Rich Braden (51:16)

Thank you for a thoughtful conversation.

Tessa Forshall (51:18)

Yeah, thank you so much for having us. It was lovely to meet you.

Podcast Host/Announcer (51:22)

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