Design Better
Design Better
Sheena Iyengar: Choose to think bigger

Sheena Iyengar: Choose to think bigger

Episode 74 of the Design Better Podcast

We may not think about it all that often, but the choices that we make often end up defining who we become. Dr. Sheena Iyengar, the S.T. Lee Professor of Business at the Columbia Business School, makes the psychology of choice and decision-making the focus of much of her research. She wrote a best-selling book called The Art of Choosing, and just published a new book called Think Bigger.

We talk about Sheena’s new book, and dive into why decision-making has become a focus of her career. We also have a lively discussion about design thinking and its shortcomings, and talk about some of the myths associated with innovation.

Thanks for listening to the Design Better Podcast! Subscribe for free to receive episodes a week early, bonus content like post-show discussions, and more.


Sheena S. Iyengar is the S.T. Lee Professor of Business at the Columbia Business School. She graduated with a B.S. in Economics from the Wharton School of the University of Pennsylvania and received her Ph.D. in Social Psychology from Stanford University.

Dr. Iyengar’s research focuses on the psychology of choice and decision-making, addressing how humans face challenges in a world where they are inundated with options. She has also tackled issues in the business world through the lenses of network analysis and diversity-inspired ideation. She studies the processes used by both groups and individuals in making choices to see how we can improve on innovation, problem-solving, and leveraging business relationships.

Dr. Iyengar currently sits on the board of the Asian University for Women and is looking to expand her work on further board opportunities. She is also a member of the Ashinaga Kenjin-Tatsujin International Advisory Council. She is a blind, first-generation Indian-American who lives in New York City.

Bonus content: Post-show debrief

We’re trying out a new segment for subscribers where we discuss some of the highlights of the episode…let us know what you think.


This episode is brought to you by:

Fable: Build inclusive products:

Freehand by InVision: The intelligent whiteboard that's half the price of Miro and Mural:

Methodical Coffee: Roasted, blended, brewed, served and perfected by verified coffee nerds:

(use code "designbetter" for 10% off of your order).

Help us make the show even better by taking a short survey:

If you're interested in sponsoring the show, please contact us at:

If you'd like to submit a guest idea, please contact us at:

Summary (via ChatGPT)

Dr. Sheena Iyengar, a professor of Business at Columbia Business School, discusses her new book "Think Bigger" and the psychology of choice and decision-making. She emphasizes that choice is the tool that allows us to become who we want to be, and innovation is a useful and novel combination of existing ideas that solve complex problems. Dr. Iyengar also points out that learning from others is essential for innovation, whether through collaboration or exposure to different ideas.


  • 📚 Dr. Sheena Iyengar is a professor of Business at Columbia Business School who focuses on the psychology of choice and decision-making.

  • 🤝 Learning from others is essential for innovation, whether through collaboration or exposure to different ideas.

  • 💡 Innovation is a useful and novel combination of existing ideas that solve complex problems.

  • 🧠 The lone genius is a myth. Great innovators have access to knowledge and learn from others.

  • 🌟 Edison, for example, had a huge lab of people who worked with him and learned from people outside his lab, such as an African American inventor who helped him with the light bulb.

  • 🤔 Defining the problem clearly is crucial for successful innovation.

  • 🌍 Innovation requires defining the problem, learning from others, and being open to novel combinations of existing ideas.


Aarron Walter: Sheena Iyengar, thank you so much for joining us on the design. Better podcast.


00:01:54.640 --> 00:01:55.940

Sheena: Thank you for having me.


00:01:56.990 --> 00:02:16.430

Aarron Walter: You know you've got a new book that is fascinating about innovation. We want to jump into that. You've been investigating the decision-making process for a long time now. Your previous book was all about decision-making. Your new book, though it's about innovation, also investigates decision-making as well.

00:02:42.330 --> 00:02:54.610

Sheena: So I think that as human beings choice is the only tool we have that enables us to go from who we are today to whom we want to be tomorrow. And so that's really the tool we can use for finding the best of what exists. as well as for creating something that helps move us forward.


00:03:08.660 --> 00:03:20.790

Aarron Walter: It's an interesting way to think about it. Let's talk a little bit about innovation. How do you define the idea of innovation?


00:03:22.430 --> 00:03:23.270

Sheena: So the great economist said that innovation was a new combination of old ideas.


00:03:30.480 --> 00:03:36.050

Sheena: and the way I defined innovation is to say that it is a useful


00:03:36.840 --> 00:03:51.770

Sheena: and I put useful first novel combination of existing ideas that come to solve a complex problem. So that's my definition of innovation. So it requires that


00:03:52.030 --> 00:03:56.010

Sheena: you know you have a problem that you're. you know, fussing around with.


00:03:56.390 --> 00:04:02.630

Sheena: And then you are going to create a solution which, first and foremost has to work may be useful.


00:04:03.060 --> 00:04:12.120

Sheena: and the way it differentiates itself from what already exists is that it's a novel combination of existing elements.


00:04:17.690 --> 00:04:42.040

Elijah Woolery: So you know one thing that's tied to this ideas of innovation is also the this concept of genius. And there's there's been this sort of push back lately about the the idea of the low in genius, the the Einstein, the Sir Isaac Newton that that really drove things forward at the same time. There are these individuals who have, you know, expanded the scope of human knowledge, and who have great creativity.


00:04:42.070 --> 00:04:47.510

Elijah Woolery: But you know, according to your book, there's maybe some methodology behind that. Maybe we could talk a little bit about the methods for being creative.


00:04:49.790 --> 00:04:55.140

Sheena: Yeah, I think we. We love the idea of the lone genius. But you know


00:04:55.590 --> 00:05:00.220

Sheena: well Einstein did some amazing things that were.


00:05:00.440 --> 00:05:07.160

Sheena: It felt magical. We shouldn't forget that he had a wonderful education


00:05:07.410 --> 00:05:09.820

Sheena: when he was a patent officer


00:05:09.840 --> 00:05:20.700

Sheena: for 5 years, and in that process he learned from lots of people because he was the one who was looking through so many patents. In fact, he himself dabbled in patents, and


00:05:20.720 --> 00:05:28.220

Sheena: an earlier version of the typewriter. The refrigerator even dabbled and made an interesting blouse that never went to market.


00:05:29.390 --> 00:05:38.250

Sheena: And you know you can say that about almost every great so-called genius that there was they they got exposure.


00:05:38.690 --> 00:05:45.640

Sheena: And so that's really important. It wasn't just that a magic happened in their brain. They actually had access to knowledge.


00:05:45.700 --> 00:05:55.070

Sheena: And then, second, they learned not just through themselves asking the right pro the right questions, but they also learned through access to other people.


00:05:58.600 --> 00:06:05.540

Elijah Woolery: Talk a little bit more about that. What it what kind of relationships helped some of these people move their big ideas forward.


00:06:07.700 --> 00:06:12.800

Sheena: Well, for example, Edison, you know we often give him


00:06:13.040 --> 00:06:22.720

Sheena: credit for making lots of different innovations from the light bulb to you know the record player. But, in fact, if you look at the the.


00:06:22.830 --> 00:06:24.970

Sheena: for example, the light bulb.


00:06:25.350 --> 00:06:29.220

Sheena: First of all, I had a huge lab of people that worked with him.


00:06:29.580 --> 00:06:36.920

Sheena: Second of all he learned from a lot of people who aren't in his lab. In fact, One of the critical pieces of making the light bulb work was an African American


00:06:36.990 --> 00:06:45.370

Sheena: inventor at the time. Who is the freed freed black who helped solve him some critical pieces to make the light bulb so.


00:06:45.570 --> 00:06:58.250

Sheena: And that's an example of a very famous person that we had his fame as an inventor. There's really no such thing as an in a famous ideator that didn't get help.


00:07:02.320 --> 00:07:05.380

Aarron Walter: So is is collaboration sort of


00:07:05.580 --> 00:07:09.000

Aarron Walter: core tenant of innovation.


00:07:11.660 --> 00:07:12.550

Sheena: So


00:07:14.140 --> 00:07:27.710

Sheena: in order to innovate. You do need to be able to learn from what others have done and what others know. Sometimes you can do that on your own


00:07:28.120 --> 00:07:41.620

Sheena: by reading by. you know. talking to people not necessarily collaborating with them. and sometimes you actually do have to collaborate with them because they just have


00:07:41.860 --> 00:07:50.150

Sheena: a different way of looking at the problem that helps you solve important pieces more often than that


00:07:50.400 --> 00:07:59.300

Sheena: people to are more likely to innovate because of their ability to collaborate with others, but it doesn't always have to be the case


00:08:00.010 --> 00:08:06.320

Sheena: in in every case. You're learning from others. But you may not be necessarily physically collaborating.


00:08:07.400 --> 00:08:11.790

Aarron Walter: So we're we're building on what?


00:08:12.430 --> 00:08:16.000

Aarron Walter: Right? Not Not a not operating with a blank slate.


00:08:16.390 --> 00:08:21.850

Sheena: Yeah. So for example. the great French polymath on


00:08:23.150 --> 00:08:33.880

Sheena: who it's invented in so many different areas. Well, he ends up, becoming the inspiration for both Einstein and Picasso


00:08:34.039 --> 00:08:39.409

Sheena: now did either one of them officially collaborate with them. No, but they they learn from him


00:08:39.470 --> 00:08:44.179

Sheena: and take his ideas in a different direction, and get inspired by him absolutely.


00:08:46.800 --> 00:08:58.250

Aarron Walter: So what are the the core elements that create opportunity or just kind of a ripe, fertile soil for for innovation is.


00:08:58.420 --> 00:09:05.480

Aarron Walter: is it, you know, exposure to different people, different ideas? What are those specific pieces?


00:09:06.170 --> 00:09:09.600

Sheena: Well, I think, in order for you to successfully innovate.


00:09:09.690 --> 00:09:13.950

Sheena: whether it's your solving a personal problem like.


00:09:14.080 --> 00:09:26.630

Sheena: And how do I figure out my career path, or whether it's solving a professional problem like, how do I get this start off off the ground, or how do I grow My company's market share by another 5%.


00:09:27.370 --> 00:09:39.080

Sheena: In every case you have to be able to do 3 things. The first is, you have to really be able to define your problem that you're trying to solve, for in a way that's concrete and solvable.


00:09:39.490 --> 00:09:46.840

Sheena: Most of the time we fail because we just don't define the problem well enough. It's too big to abstract, too big, too small.


00:09:47.990 --> 00:09:59.790

Sheena: The second thing you want to do is you have to be able to. After defining the problem for yourself. You have to be able to say, okay? Well, I know how people that I know have solved it or think about it.


00:10:00.340 --> 00:10:03.000

Sheena: I know how people in my industry. Think about it?


00:10:03.400 --> 00:10:13.980

Sheena: Who else has had a similar problem? And how did they solve it? That ability to search far and wide is critical to your ability to think out of the box


00:10:14.770 --> 00:10:19.060

Sheena: out of the box. Ideas, don't just magically appear in your head.


00:10:19.250 --> 00:10:20.960

Sheena: They come from your


00:10:21.360 --> 00:10:27.920

Sheena: the ability to expose yourself to relevant knowledge bits that come from far and wide.


00:10:28.970 --> 00:10:48.120

Sheena: And then the third thing you need to have in order to innovate is, you need to be able to take all the bits that you've gathered. Organize them in a way that enables you to combine and recombine in so many different combinations, so that you can see what are the different alternatives and pick the best.


00:10:51.230 --> 00:10:56.720

Aarron Walter: What about the scenarios where there's unexpected innovation? So


00:10:57.850 --> 00:11:05.630

Aarron Walter: refrigeration and air conditioning is one example where you, you, you set out defining a problem I want to solve.


00:11:06.950 --> 00:11:10.180

Aarron Walter: You know how to keep


00:11:10.300 --> 00:11:23.230

Aarron Walter: food cool and accidentally discover this technology could be used for other purposes like air conditioning a space. There are lots of examples out there where the


00:11:24.220 --> 00:11:32.510

Aarron Walter: person who's innovating was headed in in a different direction, and stumbles upon a an another idea. How does that fit into your model?


00:11:32.720 --> 00:11:39.300

Sheena: Absolutely you as the ideator? You need to start with a problem just because it gives you focus.


00:11:39.460 --> 00:11:44.110

Sheena: Will you end up solving a different problem along the way? Sure.


00:11:45.920 --> 00:11:47.090

Sheena: It's just that


00:11:48.100 --> 00:11:54.260

Sheena: If you don't have a problem you're trying to solve for, and you just create an idea for the sake of an idea. Nobody knows what to do with it.


00:11:55.500 --> 00:12:04.130

Sheena: and there's lots of solutions out. There are wild ideas out there in the marketplace that never go anywhere, not because they aren't necessarily cool. We just don't know what to do with it.


00:12:07.580 --> 00:12:12.820

Elijah Woolery: She had. There was a post you it on Linkedin somewhat recently, asking


00:12:12.930 --> 00:12:15.780

Elijah Woolery: Chat Gbt what the differences between


00:12:15.910 --> 00:12:22.790

Elijah Woolery: design thinking in in your most recent book, and we want to get to the AI thing, too, because we think that's an interesting thing to chat about with you. But


00:12:23.120 --> 00:12:33.550

Elijah Woolery: there there are some overlaps between what you just outline in your framework and the approach of design thinking. And I think there's also some differences too. Maybe you could talk a little bit about those similarities and differences.


00:12:34.840 --> 00:12:40.430

Sheena: So i'm going to be a little bit simplistic, just because in the interest of time.


00:12:40.540 --> 00:12:46.590

Sheena: obviously design thinking is a big topic and think bigger is a big topic. So here's how i'm going to boil them down.


00:12:47.160 --> 00:13:01.090

Sheena: Think of design thinking as having 3 big phases, and each of these phases are unto themselves processes. The first is going out and doing research on your customer sort of become an anthropologist.


00:13:02.480 --> 00:13:14.820

Sheena: The second phase is, you brought back all this knowledge. Now let's do a brainstorming session where we collect up. You know our knowledge. And now let's come up with a whole bunch of different ideas.


00:13:16.360 --> 00:13:18.650

Sheena: And then the third is okay.


00:13:19.080 --> 00:13:29.720

Sheena: We've got all these ideas. We're now going to take the idea that, or ideas that there seems to be some consensus around. And now let's prototype


00:13:29.800 --> 00:13:35.080

Sheena: to some form of visualization or a mock up, so that we can see what it is.


00:13:35.310 --> 00:13:40.500

Sheena: So those are the 3 main phases, I would say, of design thinking.


00:13:42.060 --> 00:13:43.770

Sheena: One thing bigger is


00:13:44.170 --> 00:13:48.100

Sheena: is, you start by defining the problem.


00:13:48.560 --> 00:13:51.510

Sheena: and the defining of the problem comes from


00:13:51.760 --> 00:13:55.470

Sheena: is is driven by the Id or by the Creator.


00:13:56.850 --> 00:14:08.990

Sheena: And in defining the problem. Yes, you learn from customers. You also learn from experts. You learn from as many different voices as you can to try to understand the problem.


00:14:10.040 --> 00:14:13.010

Sheena: We're not assuming that there's one main source of that.


00:14:13.470 --> 00:14:21.600

Sheena: We're not trying to be the we're not actually trying to be the anthropologist. We're trying to be the broad scientist.


00:14:22.630 --> 00:14:24.780

Sheena: The second phase is


00:14:26.240 --> 00:14:27.480

Sheena: search


00:14:29.150 --> 00:14:34.980

Sheena: and combine. I'm going to search to find all kinds of elements.


00:14:35.510 --> 00:14:41.190

Sheena: I'm not relying on my customers to tell me what I need to edit, or what how I need to fix it.


00:14:41.430 --> 00:14:45.520

Sheena: I customers were only telling me about the problem, they not telling me my solution.


00:14:46.270 --> 00:14:55.130

Sheena: My solution phase is, i'm searching all over the place for different pieces that I can bring together to combine in a new way.


00:14:56.300 --> 00:15:00.970

Sheena: And that's essentially choice. Mapping is what I call that the alternative to brainstorming.


00:15:02.290 --> 00:15:09.150

Sheena: And the third big phase is what I call the third. I test. So rather than doing a


00:15:09.480 --> 00:15:11.580

a prototype, a quick mockup


00:15:12.340 --> 00:15:18.930

Sheena: is in my method, i'm saying, even before you can get to the stage of a prototype and


00:15:19.580 --> 00:15:33.710

Sheena: perfectly fine if you want to go, do a prototype. But I think first and foremost, you have to understand how to collect meaningful feedback on what your idea is, not for the sake of finding out if other people like it or not.


00:15:33.710 --> 00:15:47.000

Sheena: but for the sake of learning how to further edit the idea before it's even worthy of prototyping. And so the third eye is, do you see what I see? Is there alignment between what I have in my head


00:15:47.180 --> 00:15:51.880

Sheena: and what you, an external person who isn't in my head are envisioning.


00:15:55.620 --> 00:15:56.990

Elijah Woolery: That's interesting, I think.


00:15:57.260 --> 00:16:00.360

Elijah Woolery: Oh, I I was just gonna say that I think


00:16:00.380 --> 00:16:07.230

Elijah Woolery: there there, there may be more overlap then, then initially appears, because I do think you know


00:16:07.270 --> 00:16:12.730

Elijah Woolery: one problem I feel like with design. Thinking is just the way that it's been implemented over the years. I think


00:16:12.890 --> 00:16:31.000

Elijah Woolery: there's there's a lot of fault to be put at the feet of my own institution at the Stanford the school for sort of popularizing it, but not maybe handing it off in such a way that it's always used to the best of its best of its capabilities. But but I do think with


00:16:31.000 --> 00:16:45.330

Elijah Woolery: you know, a a a key phase that's often overlooked. Is that defined phase Where? Yes, you go out. You talk to customers, try to understand their needs. But then you do need to define the problem in a way that's really concrete, and something that you can.


00:16:45.460 --> 00:16:56.090

Elijah Woolery: Yes, Id around and then built prototypes around. But I I do think there's you know there's kind of a synergy between the methodology you're talking to and design thinking if it's approached in a way that's a bit more


00:16:56.220 --> 00:17:01.000

Elijah Woolery: more rigorous, which I think is kind of left out a lot of time in the more popularized versions of it.


00:17:02.000 --> 00:17:13.609

Sheena: Hey? I'm sure there's variability also in terms of how it's practice. But the way I think of it is. If Henry Ford had asked people what they wanted, they would have all said they wanted a faster horse and buggy


00:17:15.460 --> 00:17:28.720

Sheena: customers will tell you what's wrong with what is what's existing right now. Experts would tell you what has already been tried, and what Hasn't worked so far. If they knew how to solve the problem, they would have solved it.


00:17:31.730 --> 00:17:39.830

Aarron Walter: There's a there's an interesting tension, though, between the idea of let's go to customers and understand their needs.


00:17:39.880 --> 00:17:47.810

Aarron Walter: You You can innovate with that methodology starting out where you can come up with some new


00:17:48.250 --> 00:17:51.530

Sheena: Let's say something is already working pretty well.


00:17:52.720 --> 00:18:00.430

Sheena: and it. Customer insight is, is absolutely helpful to give you some an important information that you otherwise would not have gotten.


00:18:00.790 --> 00:18:09.250

Sheena: and it can give you edits and and and let's be clear. A lot of times just defining the problem and learning what's going wrong might be enough


00:18:10.080 --> 00:18:12.430

Sheena: to solve it right. We're talking


00:18:12.610 --> 00:18:21.010

Sheena: a complex problem like. How do I figure out what's my next career move? How do I increase growth of my firm?


00:18:22.120 --> 00:18:26.180

Sheena: I want to think about this new startup. I want to create around.


00:18:26.260 --> 00:18:36.280

Sheena: you know, lots of things like reducing violence, or how to create some kind of a new product that helps reduce stress amongst teenagers. So for that


00:18:36.620 --> 00:18:42.680

Sheena: you do need to go beyond the the The anthropologist approach


00:18:42.840 --> 00:19:01.060

Sheena: is helpful in defining the problem. But you, the idiator, have to really take up the various information bits from watching your customers, learning from experts, learning from outsiders as well as and then from you the idea to know what it is you really want to solve for.


00:19:02.200 --> 00:19:04.640

Sheena: and that's what leads to the defining of the problem.


00:19:06.020 --> 00:19:08.260

Aarron Walter: I totally follow you on that.


00:19:08.930 --> 00:19:14.900

Sheena: There there is a that. But to go back to this idea


00:19:15.280 --> 00:19:18.570

Sheena: It's already a developed product. I just want to make it better.


00:19:18.860 --> 00:19:22.100

Sheena: It's it's it rating.


00:19:22.510 --> 00:19:32.620

Sheena: Yeah, for iterating absolutely go to the customers the fastest way. See what's not doesn't seem to be functioning. and that's the fastest way to get that information, fix it.


00:19:34.050 --> 00:19:52.760

Aarron Walter: Let's talk about where innovation can go sideways, though there's a great example of, like Dean Kamen and the Segue, and this idea that there is a fundamental problem with mobility, and we could create a new way for people to get around.


00:19:52.760 --> 00:19:54.690

Aarron Walter: That's sustainable.


00:19:54.710 --> 00:20:11.920

Aarron Walter: That's practical, that's, you know, inclusive, etc. And it was going to revolutionize and change cities and change so many things. And the Segue is really like we see, you know, police officers right around on it at the airport like it's and and kids every once in a while. It's.


00:20:11.970 --> 00:20:30.630

Aarron Walter: It's an innovative idea. There's a wild idea, but they didn't really have a problem in mind they were trying to solve for, but they they had lots of they had lots of problems, but they didn't think about the details of the problem of like. What if I have a child? And I have to, you know. Take my child to school.


00:20:30.630 --> 00:20:40.380

Aarron Walter: What if I have to bring my groceries home? They just didn't think about all the details that were associated with that. So it it fails pretty quickly in a lot of use cases.


00:20:40.800 --> 00:20:47.240

Sheena: Yeah, I mean, I I agree with you. I I regularly use the Segue as one of the examples of lots and lots of


00:20:47.450 --> 00:20:52.520

Sheena: you know ideas out there that for cool ideas. They just didn't


00:20:53.110 --> 00:20:56.290

Sheena: go anywhere, I think, because they didn't solve a problem for people.


00:20:56.870 --> 00:21:01.150

Aarron Walter: Yeah. So I wonder like this


00:21:01.910 --> 00:21:10.090

Sheena: is taking off because it does, and at least in urban environments where you're not going very far, it solves a problem for people


00:21:10.660 --> 00:21:11.820

Aarron Walter: absolutely.


00:21:11.890 --> 00:21:29.500

Aarron Walter: So with design, thinking like talking to customers. First the the think big approach, which is, instead of going directly to that is, you know, starting with a bigger problem, bigger idea. Each kit has the potential to go sideways. And i'm curious like.


00:21:29.500 --> 00:21:32.420

Aarron Walter: with the innovative approach of


00:21:32.460 --> 00:21:42.290

Aarron Walter: starting with it with a big problem. How do you keep it from going sideways like Dean came in Segue, where you're missing some of the core.


00:21:42.290 --> 00:21:52.580

Aarron Walter: You you don't you You've got an idea of the problem. But you don't understand the details of the problem well enough for execution to actually bring a product to market that


00:21:52.760 --> 00:21:56.550

Aarron Walter: that that is is going to be practical for for the world.


00:21:57.800 --> 00:22:07.390

Sheena: So in the case of Segue, and this to be fair, there's lots and lots of ideas that fail. So I don't want to just pick on Segue.


00:22:07.760 --> 00:22:08.700

You know.


00:22:09.580 --> 00:22:17.500

Sheena: this is also one of the reasons why I say it's really important to do the third eye. Because i'm envisioning in my head, and i'm obviously


00:22:18.280 --> 00:22:32.330

Sheena: putting my imagining what the Creators had in their head. You know. I'm. I'm envisioning. Oh, everybody's going to be doing this thing, and you know it's no longer going to be cars on the road. It's going to be people scooting around.


00:22:33.410 --> 00:22:35.510

Sheena: I'm envisioning that in my head.


00:22:36.980 --> 00:22:38.710

Sheena: and I think


00:22:39.050 --> 00:22:41.040

Sheena: what you want to be able to do


00:22:41.490 --> 00:22:43.480

is do what I call the third eye.


00:22:43.780 --> 00:22:46.760

Sheena: which is, I describe my idea to you.


00:22:47.660 --> 00:23:04.200

Sheena: No, it's easy enough for you to say, oh, that sounds cool. People do that all the time, particularly if I tell you this is a great idea. Wouldn't it be amazing, and particularly if i'm like some famous guy like Steve Jobs, who's telling you this is this is really great idea. This is gonna revolutionize transportation.


00:23:04.490 --> 00:23:07.410

Sheena: You're going to n your head and say, Yes, yes, yes.


00:23:08.030 --> 00:23:09.770

If I really want to know


00:23:10.100 --> 00:23:23.820

Sheena: how you're gonna perceive and understand my idea. I just describe my idea to you. I don't tell you whether it's good, better, and different. I don't ask you whether you think it's good, better, and different bad idea to ask you what you think


00:23:24.120 --> 00:23:31.060

Sheena: you don't know any way what you think and how you feel about it yet. So I just described my idea.


00:23:31.260 --> 00:23:36.860

Sheena: and then come back to you a few days later. I think. How would you describe my idea


00:23:38.160 --> 00:23:39.680

Sheena: like? How would you do it?


00:23:41.440 --> 00:23:54.150

Sheena: And if you do it that way. we actually learn what stock would they take away? Did they even remember, by the way? And in the process of the retelling of your idea? Back to you.


00:23:54.680 --> 00:24:04.150

Sheena: You're gonna make some edits, and they're in the process of making those edits. They're teaching you ways in which you would imagine using it.


00:24:04.720 --> 00:24:08.570

Sheena: The truth of the matter is, you're only going to use something that you can imagine yourself using.


00:24:13.140 --> 00:24:29.570

Elijah Woolery: I'm: curious about another problem. A lot of larger companies run into sheet and one that comes to mind is kodak. We had this guy. Paul Sappo is a futurist into class yesterday, so the story is kind of fresh in mind, but you know, kodak's up and thought of as this sort of


00:24:29.600 --> 00:24:46.550

Elijah Woolery: company that was doing great in the film era. Didn't really pay that much attention to digital. And and then digital cameras just kind of ate their lunch, but in reality they actually invested a lot. They They invented the first digital camera and over the years they tried many different attempts at creating digital camera products that just failed.


00:24:46.580 --> 00:24:48.670

Elijah Woolery: and to some degree it was.


00:24:48.760 --> 00:24:56.600

Elijah Woolery: you know, push back from maybe middle management who didn't believe in these ideas, or had it, or a stake in the ground around their existing products. But


00:24:56.650 --> 00:25:00.250

Elijah Woolery: maybe you could talk about companies and what prevents them


00:25:00.330 --> 00:25:10.340

Elijah Woolery: from entering a new era with their products, or being disrupted by other younger companies?


00:25:10.470 --> 00:25:11.500

Sheena: I think


00:25:11.690 --> 00:25:17.930

Sheena: so. I think design thinking the benefits of design. Thinking was that it really did


00:25:18.300 --> 00:25:25.770

Sheena: highlight the value of being the anthropologist, and it brought together the marriage between the anthropologist and engineering.


00:25:26.370 --> 00:25:38.210

Sheena: and I think clay Christian shen, which is what you're referring to. Now, really the value of his contributions to innovation. He really showed us the sort of curse


00:25:38.220 --> 00:25:44.780

Sheena: that it that exists in large organizations that the more successful you become at doing X.


00:25:44.910 --> 00:25:52.740

Sheena: You know the more invested you are in the knowledge you've already developed, so that even when you see something that could be better.


00:25:53.120 --> 00:26:06.770

Sheena: it's such a startup cost for you in your mind that you're not willing to pivot right, and that's the curse of the large organization. You saw that at Kodak you saw that saw that at Xerox Park. I mean. Just think of all the various


00:26:06.770 --> 00:26:20.580

Sheena: amazing. You know ideas that they passed up on, you know, including what ends up becoming apple, just because the middle management just didn't weren't willing to see


00:26:20.720 --> 00:26:23.350

Sheena: what their innovators saw.


00:26:24.210 --> 00:26:29.870

Sheena: and I and I do think that so. I think that's the reason why that's happening.


00:26:30.060 --> 00:26:32.940

Sheena: and I think that the way you


00:26:33.020 --> 00:26:48.250

Sheena: you get around. That is it you companies have. I mean, this is going to be very controversial, but companies have to be willing to do 2 things: One, the corporate boards have to be dedicated to having.


00:26:48.350 --> 00:27:05.660

Sheena: if not a subcommittee on the Board, then to have an advisory committee that actually has power for scientists and technology like a science and technology committee that's really about innovation, because otherwise companies will get.


00:27:05.660 --> 00:27:25.130

Sheena: you know, stuck in their ways. We all do. And there's nothing unnatural about that. But you need an entity that's responsible for literally getting people incentivized to come up with new solutions. So you need science and technology to essentially do


00:27:25.360 --> 00:27:37.970

Sheena: 2 jobs. One is identify all the various technologies or innovations that are happening both in your industry as well as in other industries


00:27:38.220 --> 00:27:42.190

Sheena: and sort of organize them Into what sorts of


00:27:42.280 --> 00:27:59.990

Sheena: you know categories could we put them in? On? What kinds of problems would they solve for? And then you also need that committee to identify what sort of problems exist currently in my organization that would benefit


00:28:00.090 --> 00:28:02.110

Sheena: from new ideas.


00:28:02.140 --> 00:28:04.330

Sheena: Do you need that at the high level.


00:28:04.370 --> 00:28:16.060

Sheena: and then at the lower levels of the company, you actually do need to be shifting people from different tasks around. You need people to be essentially exposed


00:28:16.220 --> 00:28:20.990

Sheena: to different knowledge bases in order for them to be more open to innovating.


00:28:23.630 --> 00:28:27.610

Aarron Walter: What does that look like? Shifting from one knowledge base to another?


00:28:29.290 --> 00:28:45.320

Sheena: Well, depending on the organization like, let's say i'm a professor, right? And I said in management, I actually think that business schools and other academic institutions, one of the biggest hurdles to innovation is the fact that we are siloed in our various disciplines.


00:28:45.400 --> 00:28:47.150

Sheena: which, you know


00:28:47.240 --> 00:28:55.840

Sheena: it hurts our ability to innovate. The more you have faculty, have to work with people from other disciplines.


00:28:56.160 --> 00:29:05.030

Sheena: Put them in on committees, move them around in terms of teaching teams, research collaboration centers


00:29:05.190 --> 00:29:14.320

Sheena: that you need to get people exposed to different knowledge bases in order for them to be able to expand their way of thinking and identifying new solutions


00:29:16.740 --> 00:29:31.400

Sheena: are. Is is there a a company or an organization that we could look to from his? Well, Samsung did this very well. They were ones that would create. They went out of their way to continuously


00:29:31.400 --> 00:29:46.490

Sheena: move people into different committees, so that they would be working with different parts of the organization. 3 M. Is another company that created the sort of innovation to subgroups


00:29:46.760 --> 00:29:59.340

Sheena: into. It, did it for a while. Right. These 8 person or we had to be fed in 2 pizzas or less groups that would spend time just innovating. But you gotta be careful that they're not just doing it with their friends.


00:30:03.230 --> 00:30:08.580

Elijah Woolery: She had a recent interview with the globe and mail that that you discussed your book, and some of these sort of


00:30:08.740 --> 00:30:11.650

Elijah Woolery: popular myths that surround creativity and innovation.


00:30:11.720 --> 00:30:16.160

Elijah Woolery: First one was that creativity is innate. Either have it or you, Don't.


00:30:16.170 --> 00:30:17.640

Elijah Woolery: Why, why isn't that true?


00:30:19.380 --> 00:30:30.390

Sheena: I mean it became popular because of the work of Sperry, who got the Nobel. But then his work got sort of overly interpreted, and


00:30:32.240 --> 00:30:43.240

Sheena: I guess misunderstood. And so I mean his work just looked at the effects of what happened if the 2 sides of your brain tended to get severed, and


00:30:43.450 --> 00:30:46.180

Sheena: and then people began to assume that


00:30:46.200 --> 00:30:53.080

Sheena: the right brain was for creativity, and the left brain was for analytical thinking, and


00:30:53.150 --> 00:31:12.100

Sheena: we made the assumption that you know different portions of the brain took care of different things, and that some people just happen to be stronger in one side versus the other side, or in order to get people to be creative, maybe I needed to do stuff to light up your right portion of the brain all that got the bonked


00:31:13.390 --> 00:31:25.110

Sheena: in the last 20 years. So essentially there's you know, that there's no such thing as creative tasks versus in a little tasks. Essentially everything happens, and learning in memory


00:31:25.120 --> 00:31:34.190

Sheena: both portions of the brain light up whether you're doing a so-called you know, analytical task like a math problem, or so called creative tasks, like


00:31:34.250 --> 00:31:37.400

Sheena: writing a poem or making a painting.


00:31:38.860 --> 00:31:39.960

Sheena: And so


00:31:40.370 --> 00:31:44.810

Sheena: yes, we, the the Internet is still filled with


00:31:44.840 --> 00:31:50.110

Sheena: the right left. Brain tests that we love to take, but actually not true.


00:31:51.740 --> 00:31:53.880

Sheena: You might have a preference


00:31:54.010 --> 00:32:08.560

Sheena: for certain kinds of activities. You might prefer to do math over making a painting. You might over time develop a better skill for it, because you're really spending the time to do more and more of it, and you like it.


00:32:09.740 --> 00:32:10.820

Sheena: That's fair.


00:32:12.770 --> 00:32:13.910

Elijah Woolery: Do you think that


00:32:14.360 --> 00:32:20.130

Elijah Woolery: our educational institutions have a part to plan that, too? I, Dave Kelly, has this idea of creative confidence, and that


00:32:20.470 --> 00:32:36.230

Elijah Woolery: in large part in in early years in school, when you look at almost any toddler and their finger painting and singing and being creative, but it eventually just sort of gets drilled out of us as we're taught to like in our seats. And do you know, memorization, that kind of thing. You think that's another component of this.


00:32:38.330 --> 00:32:40.340

Sheena: So I think that


00:32:41.760 --> 00:32:54.250

Sheena: is it important. So I I I agree and disagree right. I think essentially it's not as black and white right. Do you need memory in order to be creative? Yes, you're only going to be able to create with the stuff you have in your head


00:32:55.340 --> 00:33:09.990

Sheena: right? So if I ask you, you're creating right now every time you ask me a question every time you say a statement. You're You're engaging in an exercise and creativity. It's it unless you're saying the same sentence over and over again. You're you're engaging in improper improvisation


00:33:10.000 --> 00:33:21.120

Sheena: in order for you to be able to create new sentences. You clearly needed to learn how to read and write. That took a lot of wrote memory, a lot of doing things over and over and over again, so clearly that skill is important.


00:33:21.690 --> 00:33:34.180

Sheena: At the same time, do you need the ability for me to create for you opportunities for you to have time to sort of, hey? Can you, you know, Write me a paragraph.


00:33:34.780 --> 00:33:47.030

Sheena: and you can write a paragraph about any number of things or anything you want. This is a chance for you to now explore. What could you do with all these words? You learned how to read.


00:33:47.790 --> 00:33:55.750

Sheena: So I think what is a fair thing to say is that we have privileged. or


00:33:55.830 --> 00:34:05.990

Sheena: learning that comes in the form of very unduly structured, unduly rigid unduly about, just, you know, stuffing stuff in the memory.


00:34:05.990 --> 00:34:16.679

Sheena: and we're not giving you enough training and how to take this stuff that's in your Memory Bank. And now taking those pieces and combining and recombining in multiple combinations.


00:34:17.110 --> 00:34:17.699



00:34:18.290 --> 00:34:22.350

Sheena: That's what we need to have more of in our education teaching people how to do that


00:34:24.389 --> 00:34:33.989

Sheena: Another one of the myths that you debunked in that article was one more thing, and they also need to be able to exercise their curiosity.


00:34:34.330 --> 00:34:37.110

Sheena: You don't usually leave room for that in curriculum.


00:34:39.909 --> 00:34:46.940

Aarron Walter: Another one of the myths that you debunked in that article was that creatively designed offices yields creative ideas.


00:34:48.400 --> 00:34:55.960

Aarron Walter: Tell us a little bit about that, like what's flawed with that that that that if we design creative spaces will be created.


00:34:56.190 --> 00:34:57.870

Sheena: You know I don't know if we know


00:34:58.490 --> 00:35:03.660

Sheena: definitively that space has like what role it plays.


00:35:03.840 --> 00:35:06.840

Sheena: It is interesting that


00:35:07.270 --> 00:35:16.400

Sheena: you know Google, which has, which was the leader of creating the most fun. Space was actually invented in a garage.


00:35:16.770 --> 00:35:27.390

Sheena: And you see that for a lot of stories of the great innovators, right? They kind of came out they were, which the idea of the great company was started in some


00:35:27.510 --> 00:35:28.510

Sheena: hello.


00:35:28.900 --> 00:35:31.440

Sheena: fairly humble


00:35:31.450 --> 00:35:33.190

Sheena: circumstances.


00:35:33.370 --> 00:35:34.560

Sheena: We.


00:35:34.720 --> 00:35:46.590

Sheena: the studies on the role Space plays are very undefinitive. It's clear that space might make you feel happier.


00:35:47.530 --> 00:35:54.840

Sheena: and as results might make you more likely to stay at that company, and to the extent that pretension is important.


00:35:55.120 --> 00:35:56.750

Sheena: Make a nice space


00:35:58.390 --> 00:36:03.330

Sheena: the the best study. if we could call it that


00:36:03.470 --> 00:36:06.720

Sheena: the best controlled example of


00:36:06.800 --> 00:36:15.450

Sheena: does space make a difference? Your ability to innovate really comes from Bell Lab, I think. where they had an really ugly building


00:36:15.750 --> 00:36:21.570

Sheena: that was very quickly erected around World War 2, and then a really beautiful building


00:36:22.250 --> 00:36:24.300

Sheena: built in the sixties.


00:36:24.330 --> 00:36:31.260

Sheena: and when you come and you know a lot of times the the people were cross-pollinating across those 2 buildings.


00:36:31.800 --> 00:36:33.960

Sheena: you know you actually had.


00:36:34.450 --> 00:36:45.800

Sheena: It's slightly more Nobel prize winners from the ugly building than from the other building. I don't know if that means anything. But essentially you actually have just as much amazing innovations for Bell labs


00:36:46.720 --> 00:36:48.390

Sheena: coming from both buildings.


00:36:49.390 --> 00:37:05.050

Sheena: That's about as we control the setting as I can think of. I mean you have other one off examples like there was that ugly building at Mit which ultimately had to be torn down because of asbestos problems, but it actually had more Nobel prize winners at 1 point than any other place on the planet.


00:37:06.920 --> 00:37:25.390

Aarron Walter: It would make sense that these on precious spaces would create more creativity. You know opportunity for more creativity just going back to your core tenant of innovation that we're broadening our aperture of possibilities, what is possible. And if you're in a very precious space, it says


00:37:25.390 --> 00:37:41.900

Aarron Walter: you can't spill a can of paint. You can't tape things to the wall. You can't sort of explore in any behave in in lots of different ways that that may or may not lead to some innovative idea. I'm curious if if that


00:37:42.110 --> 00:37:45.840

Aarron Walter: I don't know how that sits with with your perspective of space and creativity.


00:37:47.270 --> 00:38:02.460

Sheena: So I would say that the most important things for you. when thinking about your space and your ability to be creative is, it has to be a space in which you feel comfortable thinking.


00:38:03.840 --> 00:38:07.650

Sheena: You know, I I, that could be different places for different people.


00:38:08.330 --> 00:38:22.930

Sheena: But you need to have a space in which you can sit and think and say, okay, what do I know? What do I still need to know. What pieces do I have? What could I create?


00:38:23.260 --> 00:38:27.940

Sheena: That's one thing. You need to have some space where your mind can actually do its work.


00:38:28.620 --> 00:38:36.630

Sheena: And the same thing that's got to be important for you is access to information that you don't have.


00:38:37.640 --> 00:38:46.080

Sheena: and whether that's having colleagues that are helpful, which I believe it was probably critical in the case of Bell Labs and Mit


00:38:46.210 --> 00:38:50.610

Sheena: colleagues that are willing to chat chat with you and tell you what they know.


00:38:50.740 --> 00:38:52.910

Sheena: or whether that be.


00:38:52.930 --> 00:39:02.480

Sheena: you know, access to databases or Google, or it be picking up the phone, whatever it is. I think those are the 2 things you both need.


00:39:05.560 --> 00:39:24.930

Elijah Woolery: How do you think this plays with? You know this? There was this pendulum swing towards remote work during the pandemic, and it seemed to have swung back towards requiring people in the office, or in some cases, maybe a hybrid scenario. How does that play with this idea of being in a comfortable space, but also needing access. Maybe the colleagues and and information.


00:39:27.010 --> 00:39:40.770

Sheena: So I think you've described it very well, right? I do think that when we need that that thinking space. provided your home is a place where you're not gonna get distracted can be a very good place.


00:39:41.420 --> 00:39:51.440

Sheena: At the same time you could be stuck in the vacuum where you really are going in circles and circles and circles, because you don't have access as easily.


00:39:51.560 --> 00:39:53.620

Sheena: 2 other people that can help you.


00:39:53.910 --> 00:40:00.870

Sheena: And then coming into the office sometimes and being able to talk to people, can be really helpful.


00:40:02.820 --> 00:40:04.660

Sheena: And how do you create that


00:40:05.330 --> 00:40:15.000

Sheena: really beautiful balance is, I mean, the tricky part about that is that varies from individual to individual, and also probably tasks to task right


00:40:15.540 --> 00:40:20.620

Sheena: certain tasks. You need more people to help, and other tasks you may need less.


00:40:23.190 --> 00:40:37.110

Elijah Woolery: Let's go back to the AI, which we sort of hit it out earlier, and there's been these immense developments. Obviously, over the last 6 months, many kind of unexpected emergent behaviors from some of these large language models.


00:40:37.180 --> 00:40:46.800

Elijah Woolery: You had an interesting post about AI and creativity. I think many people are afraid that AI has a potential to take away creative jobs that we thought were sort of safe


00:40:46.850 --> 00:40:50.450

Elijah Woolery: for machines. But maybe there's another way to think about that.


00:40:51.890 --> 00:41:01.680

Sheena: Yeah, I think AI is only going to make us more creative. I honestly don't. I mean, I will there be some unintended negative consequences? Of course there there always are


00:41:01.780 --> 00:41:09.200

Sheena: from every innovation that's innovation is never purely positive, nor is it purely negative. Right.


00:41:09.260 --> 00:41:12.400

Sheena: So I I think that


00:41:13.820 --> 00:41:22.240

Sheena: you know, when the camera was invented we were worried that painting and artistry, as we know it was going to be done.


00:41:22.360 --> 00:41:28.810

Sheena: But you know impressionism came along with the what did the camera do? It gave us a new way to see the world.


00:41:29.510 --> 00:41:33.900

Sheena: It taught us something, and that led to impressionism and cubism. And then


00:41:34.240 --> 00:41:37.580

even photography itself has become an art form.


00:41:39.010 --> 00:41:52.700

Sheena: When the computers stimulation of chess came along, and Deep Blue beat Gary Kasparov. This was a really big deal. My God, this is the end of human intelligence. As we know it.


00:41:52.760 --> 00:41:55.090

Sheena: we're nothing but cogs.


00:41:56.260 --> 00:41:57.720

Sheena: Well, I mean


00:41:58.840 --> 00:42:07.560

Sheena: The reality is that the presence of computer simulations of chess is actually made. Humans become better chess players.


00:42:08.500 --> 00:42:11.800

Sheena: I think the same thing is going to happen with Chat Gbt.


00:42:11.940 --> 00:42:25.300

Sheena: It's we're gonna see as the more we're able to use it, and those who do take the time to use it will probably become. They'll see more ways to combine the same materials. They'll


00:42:25.380 --> 00:42:33.760

Sheena: get bits of pieces as I was talking about before, that they might not have thought of, and that'll enable them to come up with solutions.


00:42:33.980 --> 00:42:38.980

but they wouldn't have thought of before, so I I think on balance is going to make people more creative, not less.


00:42:40.900 --> 00:42:44.330

Sheena: What people are afraid of is that the bar will go up.


00:42:48.600 --> 00:42:49.920

Elijah Woolery: Aaron, You're on mute.


00:42:52.750 --> 00:42:54.110

Aarron Walter: Say more about that.


00:42:56.580 --> 00:42:57.330

Sheena: Well


00:42:58.550 --> 00:43:04.000

Sheena: did the camera kill the portrait. The one who makes portraits. Yeah.


00:43:05.640 --> 00:43:12.210

Sheena: Did artists have to innovate and figure out a new way to do something interesting? Yeah.


00:43:13.540 --> 00:43:19.100

Sheena: Did the average quality of the human chess. Master, go up. Yeah.


00:43:23.130 --> 00:43:26.460

Aarron Walter: how do we? How do we start to


00:43:27.190 --> 00:43:36.970

Aarron Walter: get better at thinking about the negative implications of our innovations? It seems like, you know, speaking of of a


00:43:37.000 --> 00:43:44.890

Aarron Walter: of of a raising bar, like the stakes, are only getting higher as what we're innovating on becomes imminently more powerful and influential.


00:43:46.680 --> 00:43:53.350

Sheena: I mean that. Gosh! If someone could ever answer that one I mean, can you just imagine?


00:43:53.940 --> 00:43:58.060

Sheena: I mean, first of all, we're as humans. We're terrible at forecasting.


00:43:59.400 --> 00:44:05.630

Sheena: And I mean, that's the genius of humans. You know, for better and for


00:44:05.850 --> 00:44:08.330

Sheena: and for evil, that we


00:44:08.340 --> 00:44:09.610

Sheena: never know


00:44:09.910 --> 00:44:12.910

Sheena: how something is gonna take off. So


00:44:13.980 --> 00:44:16.690

you know, like take, for example.


00:44:17.730 --> 00:44:18.750

Sheena: abortion


00:44:20.300 --> 00:44:22.680

Sheena: it is. It was an innovation.


00:44:23.980 --> 00:44:40.480

Sheena: it can. It has absolutely become a symbol. a female empowerment in this country and different parts of the world. It's also become the symbol of female suppression and and and abolishment. Right?


00:44:40.900 --> 00:44:42.400

Sheena: Same technology.


00:44:45.940 --> 00:44:49.560

Sheena: you know, if you think about the


00:44:50.190 --> 00:45:01.630

Sheena: any innovation, whether from the camera to social media. On the one hand, it gives you access to more information. On the other hand, it's there also tools that have been used to.


00:45:02.260 --> 00:45:10.260

Sheena: and i'll lead to alternative interpretations, misinformation, deception, I mean.


00:45:10.710 --> 00:45:13.850

Sheena: take your pick very tough.


00:45:15.210 --> 00:45:16.220

Aarron Walter: It is


00:45:18.570 --> 00:45:25.450

Aarron Walter: last question for you here, you know, thinking about innovation as like a compounding energy.


00:45:25.580 --> 00:45:32.290

Aarron Walter: You, you know we we innovate on a certain thing where that's AI medical advancements, etc.,


00:45:32.320 --> 00:45:37.290

Aarron Walter: and that creates new opportunities for additional innovation. That's


00:45:37.370 --> 00:45:40.600

Aarron Walter: exponentially better and better and better and better.


00:45:40.770 --> 00:45:47.350

Aarron Walter: And it feels like at this position we're we're into the 20 first century here a little bit


00:45:47.540 --> 00:45:49.400

Aarron Walter: long way still to go.


00:45:49.460 --> 00:45:54.630

Aarron Walter: What does compounding innovation look like as we go through this century?


00:46:00.360 --> 00:46:12.130

Sheena: I would say, so far in the 20 first century the big innovations have been well. My favorite is to James Webb Telescope.


00:46:12.270 --> 00:46:13.840

Aarron Walter: Hmm. Yes.


00:46:14.090 --> 00:46:19.620

Sheena: I mean, that's just incredible. The advances we've made in in space.


00:46:20.390 --> 00:46:29.680

Sheena: I would say the other one was the Mrna vaccine. you know, which I understand now feels boring, or


00:46:29.950 --> 00:46:35.250

Sheena: or maybe it became so political it is. It's not sexy, but, my God!


00:46:35.360 --> 00:46:37.330

Sheena: It was an amazing innovation.


00:46:38.360 --> 00:46:51.250

Sheena: and it's absolutely changing the face of medicine. And I think the third is going to be AI and machine learning just because I do think it's changing the human frontier


00:46:51.520 --> 00:46:54.540

Sheena: of both creativity and innovation more generally.


00:46:55.540 --> 00:47:03.150

Sheena: Now, what the world's gonna look like by the next century. I'm not going to be alive by then. So not even going to make a prediction.


00:47:05.130 --> 00:47:11.720

Aarron Walter: Totally fine. That's that's helpful. But from 1,900 to the year 2,000.


00:47:12.620 --> 00:47:17.200

Sheena: Wow! Think about those 2 worlds.


00:47:18.340 --> 00:47:20.310

Aarron Walter: Yeah, it's just unrecognizable.


00:47:22.080 --> 00:47:27.610

Aarron Walter: Yeah. Sheena. Where can people learn more about you and your new book.


00:47:28.600 --> 00:47:36.140

Sheena: You can follow me on Linkedin, and feel free to follow it. Go to my web page, or on the Amazon and


00:47:36.280 --> 00:47:39.790

Sheena: order a book email me. I'm always happy to chat


00:47:42.100 --> 00:47:54.880

Aarron Walter: fantastic. Your new book is, Think bigger how to innovate your previous book. Also a great book the art of choosing both good reads. Advise everybody to check those out. Sheena. Thank you so much for being on the show.


00:47:55.190 --> 00:47:56.080

Sheena: Thank you.

Design Better
Design Better
Design Better co-hosts Eli Woolery and Aarron Walter explore the intersection of design, technology, and the creative process through conversations with inspiring guests across many creative fields. Whether you’re design curious or a design pro, Design Better is guaranteed to inspire and inform. Episodes are released semi-weekly for free subscribers, weekly for premium subscribers. Vanity Fair calls Design Better, “sharp, to the point, and full of incredibly valuable information for anyone looking to better understand how to build a more innovative world.”