How a well-defined problem is crucial for unlocking innovation

Speaker A: Welcome to the Decoding Innovation Podcast series brought to you by the EY Naughtyum SPIRC Innovation Hub where we explore the innovative technologies, business models and ideas that are shaping the future of industries. During each episode, we meet with stakeholders at the cutting edge to discuss innovations in their space, challenges they need to overcome, and their outlook on the future. Welcome to the EY Nottingham SPURC Innovation Hub Decoding Innovation podcast. I'm your host, Brent Dersh. I'm coming to you live from the, uh, EY9 Hamsburg Innovation Hub in sunny Cleveland. I am really excited today to be, uh, joined by my, uh, guest, Sheena Iyengar. Sheena is both a professor at Columbia Business School as well as an author of, uh, a couple best selling books that we're going to unpack as we go through today's session. Sheena, welcome to the show.

Speaker B: Thank you for having me.

Speaker A: Let's start out with, uh, just a little bit of background question for our listeners, for our viewers. Um, you're both a professor and an author. Can you tell us a little bit about your life journey that sort of brought you, uh, to this point where you are today?

Speaker B: I am the daughter of Indian immigrants and I am blind. And I grew up in New York City. In my view, one of the best cities, if not the best city, one of the best cities in the world. And I grew up thinking about choice. Um, what I really wanted in life was to have good quality choices, uh, so that I could, you know, live out the American dream. That was essentially what I really wanted growing up. And I think that's what drew me to the study of choice. I would say the best choice I ever made was the choice to study choice.

Speaker A: Could you tell us a little bit about some of the research that you've, you've done historically, like some of your focus areas and if there's some, in particular, if there's some, some areas that are part of your current research focus.

Speaker B: So I study two big questions, right? One is, um, how what is choice? And what does choice mean to people? And that was essentially what my first book was about, the art of choosing. And what that laid out in lots of different ways is the idea that we all want choice because we, since the beginning of human civilization understood that choice is the only tool we have as humans, that A, separates us from non humans and, and B, enables us to create a better life for ourselves and a better world, right? And so for the longest time that's really why we were drawn to choice. Of course, in the last 50 years, we almost live in a kind of choice tsunami, where we have so many choices that people are sort of perplexed at times. You know, what to choose, how to choose, where to look for choice, what's a real choice, what's a fake choice, etc. So the art of choosing was really about what are the current dilemmas we have as modern individuals for how to make choice. More recently, in response to the choice tsunami, I created a methodology called Think Bigger. And what Think Bigger is, is a method that anybody can use. Think of it as a framework that anybody can use to help them create choices. You know, even though you live in a world with so many choices, half the choices are either fake or not, not really that different from what already exists. How do I actually create choices that are going to make my life better, that are going to solve my problem? And so Think Bigger is a methodology that I created. And it's based on neuro and cognitive science, uh, that I started to teach in 2013. I've been teaching it now for over 10 years. And in 2023, I wrote the second book, which was Think Bigger, which is how to create meaningful choices. Uh, and now in just the last, uh, 3M4 months, I now have a generative AI version of think Bigger that makes it accessible to people that go beyond my classroom so that anybody can essentially create meaningful solutions to problems that they're tackling.

Speaker A: This is exciting because we're going to do a little bit of, uh, uh, a live demo of this that you've created in a little bit. Uh, a couple more questions just to help frame things up a little bit. Uh, what life experiences have you had that have really fueled your passion for both understanding the science around choice as well as understanding some of, um, the cognitive needs around the need to think bigger.

Speaker B: So I would say there were two things that affected my interest in choice. First was the fact that I really was bicultural. So as an Asian American, particularly an Indian American, at home, you would learn about the limits of choice, right? You had duties, you had responsibilities. My parents met on their wedding night, their marriage was arranged. And at school I would learn that what you're supposed to be able to choose everything from your hair to, of course, whom you married, et cetera. These were two entirely different narratives of how you made choice. And so my very first study, for which I actually received the dissertation award back in the 1990s, was where I demonstrated sort of the precursor to the Tiger mom study. Um, I demonstrated that Asians and Anglo Americans had very different reactions to the Presence of choice. You know, that whereas Americans, like, it doesn't even have to be a real choice. As long as they believe it's a choice, they're drawn to it. It's seductive. Whereas for Asians, they would actually look at choice a little suspiciously, like, what? What's going on? And so I think the first observation was that choice really is a social construct. So that even though we as humans are all born with a desire to not be controlled, none of us wants to be. Be in a cage. Everything else about choice is taught to us. We're not born knowing how to choose. We often think we might be, but we're not born knowing how to choose. And so everything about how many choices, how we choose, what's a good, bad choice, these are all taught. And I'd say that's really important, particularly in today's world, to recognize that choosing is not something that. That we're innately born knowing how to do. It is something that requires learning and training. The second observation that I had, and this really came from me being blind, um, is the idea that, you know, on the one hand, we're told that you can do whatever you want, the sky is the limit. You can make the impossible possible. On the other hand, we tell ourselves and each other that a big part of growing up is accepting reality and picking amongst whatever choices are put in front of you. And you try to pick the best one of those. And that might mean then that you have to settle for something you really don't want. You might have to compromise. You have to settle for the meager options put before you. Now, as someone who was going blind, I wanted to dream. I wanted to do big things. And yet I found that, you know, again and again, people would question what I could and couldn't do. Like, can she really read? Can she really learn how to do math? Can she walk around? Can she live on her own? Can she have friends? I mean, the questions were endless. And the three words I hated most and still do actually are the words, it's not possible. I hate that feeling of powerlessness and paralysis. And so I would say that that desire to get rid of the words it's not possible fueled my interest to study choice, primarily with an eye towards helping to empower people with choice. That, yes, choice has its limitations. Yes, we have to train ourselves to get more out of choice, but that we have to use choice as the ultimate tool that we as humans have been given to create a better life for ourselves as well as the world we want to live. In and is honestly what led to, uh, the development of Think Bigger. Because I got so tired of all the research that shows the many ways in which we fail at choice, I wanted to create something which would enable people to see how to succeed at choice.

Speaker A: So, Gina, I know one of the areas you've researched that's been a big focus of, uh, some of the publications you've worked on is the too much choice phenomenon. Could you help us unpack that? Ah, a little bit in terms of what the practical implications are for us both is consumers that are living in a world with overwhelming amounts of choice, but as well as business professionals who are dealing with just a myriad of options before us every single day.

Speaker B: So we live in a world of a lot of choice. When you look at how many choices you have on dating apps, I mean, imagine how complicated that's become. We have over 6,000 different dating apps now. The world over, uh, Starbucks has over 100,000 different drink combinations. So that, that really has been a big sea change in the last 25 years. How many choices we have. Um, back in the 1990s, when I was a PhD student at Stanford, I did a, at that time, it was a really a small sort of exploratory study. And I did a study at a upscale grocery store. And the study now has been dubbed the Jam study. Um, and what we did was we put out a little tasting booth right near the entrance of the store where we either put out six different flavors of jam or 24 different flavors of jam. And we essentially looked at two things. First, in which case, were people more likely to stop and sample some jam? And second, in which case were people more likely to buy a jar of jam? And it turned out that more people stopped when there were 24 on display, 60% as compared to 40% when there were six on display. But when it came down to buying behavior, of the people who stopped when they were 24 on display, only 3% of them bought a jar of jam. Whereas of the people who stopped when there were six on display, 30% bought a jar of jam. Now, this was the first illustration of the idea that even though people are initially more attracted to a larger display of options, when it comes down to buying behavior, they're more likely to buy when they have less than when they have more. Now, since then, that study came out in the year 2000, and we've now hit the 25 year mark. There's been now over a thousand studies that have essentially looked at the consequences of offering people more and more Choice. And they've looked at it across lots of different contexts, lots of different consumer choices. You know, from soda pop to cakes and chocolates to, to medical, uh, prescription drugs to dating choices, um, to retirement savings choices. Uh, they've also looked at it for voters and how it affects their decisions. They've looked at it for how it affects patients when they, um, have different choices of medications they can take for different diseases. They've even looked at animals and their mating behavior as a function of when they have more choices. And essentially what they have observed is that the more choices that are present, the more likely people are, uh, to be initially attracted. So they show signs of being, you know, seduced by the presence of more choice. Uh, but then when they are put in a position of actually having to make a choice, they experience greater frustration, they experience more anxiety, more uncertainty. Um, they tend to delay making a choice for obvious reasons. Uh, if they do make a choice, and they often don't, they'll opt out of the choosing process. But if they do make a choice, they tend to choose less. Well, they tend to be less satisfied with that which they have chosen. Um, patients who choose, uh, from 10 different potential drugs for their medical condition actually report experiencing more side effects than people that are choosing from two. And that's even though they have actually all been given a placebo. Um, animals tend to mate less as the number of mating options go up. So it's really quite remarkable how pervasive the phenomenon is. And I would say in a nutshell, you know, as the number of choices rise, we don't know what we want and we don't know how to differentiate between the options. And so we get a little overwhelmed.

Speaker A: So it gets harder and harder or more challenging to make individual decisions. Is there also a cumulative kind of decision fatigue effect where the more decisions you have to make back to back, the quality or speed or, you know, confidence in those decisions. Does it change over time if there's lots of decisions involved? Serially?

Speaker B: Yeah. There's some wonderful studies done by Roy Baumeister that show that if you even if I just take two individuals and one individual just sees like let's say two pairs of pans, two cups of coffee, etc. Sees a bunch of options but doesn't have to make decisions versus another person who sees the options and has to make a decision for each pair, and we're not even talking a lot of options per decision, just pairs, it turns out just the act of having to make decision, decision, decision, decision, decision, ends up overwhelming. People to the extent that they observe that their immun immune system drops. Mhm. So and they call that a decision fatigue or ego depletion.

Speaker A: So thinking about the impacts of, you know, kind of this too much choice phenomenon and kind of turning our attention uh, towards Think Bigger, you know, really how did you start to approach Think bigger with this too much choice phenomenon in mind?

Speaker B: So first off, what we observe when you look at humans under the MRI machines is that, you know, the sweet spot does seem to be somewhere between three to five, which is actually pretty similar to what George Miller in 1956 identified in his famous paper, the magical number seven plus or minus two. So, so that theme keeps popping up now I can't say, uh, with confidence that that would be true for every single choice domain. It's impossible to do that study. I'm just saying that that pops up a lot now. So what we want to do I think is even though people say they want more and more choice, I think what they really want is to feel competent during the choosing process and to feel confident with what they've chosen. And if there isn't an option available for them, they want to have the wherewithal to create a meaningful choice. And um, I would say that's really where Think Bigger comes in. Um, Think Bigger is a framework which structures the decision making process. And at every step we make the number of decisions that you have to make and choices that are present for you manageable rather than overwhelming. And in so doing I think we actually empower people to identify and create a lot more options than they otherwise would. You see, if you walk into a candy store and are just looking around at all this candy, you're overwhelmed. But if I have you pivotal and um, uh, central to the process of creating the candies that you're going to choose amongst, then you're not overwhelmed. That's the beauty of us as humans. We're very good when we're engaged in creating it. And that's really a big insight that also led to Think Bigger, that we make the process manageable, but in so doing we give you the power to actually create in a sense, infinite choice.

Speaker A: So let's talk a little bit about the framework that guides Think Bigger. You've got a six step framework. Do you want to take us through kind of the framework at the high level and then we can show what it would look like in real use using the AI tool.

Speaker B: Sure. And so there's essentially six steps. Um, but I would think of those as um, really more like the first three steps are one big part of it. So the first three steps which are choose a problem, break it down, compare wants, those are three steps that are really designed to get help you as the chooser, think about what is it you're trying to do here? Like, I understand you're upset that you're not happy with what's going on at your job, you're not happy with, you know what's going on and with your kid and whatever your kids do it, you're not happy with your country, etc. Whatever the problem might be. Can you define that problem? Because, you know, 72% of us fail at, uh, solving problems because we just didn't define the problem. Right. And so the first three steps are about you defining your problem in a way that's solvable and concrete rather than vague and abstract. Breaking it down into the most important challenges that now have to be accounted for or addressed. If you were to make a meaningful solution and compare wants is about what would be your metrics of success? You know, like, if you were to solve this problem, what would success look like? These might sound self evident to you, but think about how many times we don't do this. Like even something simple like, you know, I want my kid to eat vegetables. Well, what is your metric for success? Is it if you could trap your kid in a chair and force food down its throat, is that a metric of success or is it that your metric of success is I actually want my kid to happily eat the spinach and broccoli and choose that over a cupcake. Right. And so it, it, so it. The first three steps are about thinking about your problem.

Speaker A: So I, I love the emphasis on problem definition. I always used to coach a lot of my innovation teams that, you know, a problem well defined as a problem half solved. I don't even know who said that quote originally. I heard it and I, I latched onto it because it's, it's, there's this natural tendency to gloss over problem definition and go into some sort of brainstorming exercise right away. Right. And it always seems like slowing down and really falling in love with the problem is such a critical step.

Speaker B: Yeah, fall in love with the problem is a great line. My other favorite quote is from Einstein who said, if I had an hour to save the planet, I would spend the first 55 minutes thinking about the problem and, and the last five minutes thinking about the solution. So really understand what is that problem you're trying to solve? What does success look like?

Speaker A: Love it. All right, so Take us through the back half of the process now.

Speaker B: Okay, so then you have, uh, step four, which is search in and out of the box. And step five is choice map. So what is that? When we, uh, solve problems, we typically think of our experiences, think of our knowledge base, and we take all that stuff and we whirl it around our mind and we take those pieces and we combine them and we have a flash of insight. That's what a flash of insight is is pieces coming together in your head. When you're doing a brainstorm, what are you trying to do? You're saying, well, a bunch of minds came together, they collectively put a bunch of pieces together. Voila. Uh, you had a flash of insight. Now what that's doing though is it's only taking the experiences and memories that you have right now top of mind. And it's often taking very, um, domain or industry specific knowledge and combining that, it leads to sort of in what I call in the box thinking. Because you're primarily looking at what's going on in my industry and what can I learn from what other people are doing and improve upon what I'm doing. There's nothing wrong with that. That can often be a good thing. I mean, Zoom absolutely took advantage of that when the world shut down. Uh, but for out of the box thinking to happen, you have to go beyond what's happening in your own industry. And so we, in step four, we talk about search in and out of the box, where we ask ourselves, okay, I've got this problem. Who else had a similar sort of a problem in a different industry, maybe a different point of history, and how did they solve that other problem that's sort of like mine? Mhm. Right. So think back to the days of the 1990s when we used to go to Blockbuster to get a movie. We would go to the store, pick out a video cassette, bring it home, then we had to return it in two days, and if we didn't, we'd have to pay a late fee. Reed Hasting was upset about that business model. And he said, what other leisure activity do I do? And I never quite know how often I'm gonna do it. And you know, so there's no mandate as to how often I'm going to do it. And how else do they structure it so that there's no such thing as a late fee? Because this late fee is irritating me. And he said, well, what do gym memberships do? You can use it as little or as much as you want. It's a leisure activity. It's a flat fee every month. Today we take that for granted. That was a flash of insight he got from searching in a different box. Um, and so what we do in Think Bigger is we have people look in other boxes to identify strategies that could be edited and imported into your world to solve your problem. And choice mapping is simply combining, uh, people pieces from your industry as well as from other boxes to create an unexpected solution. So that's the next big part of Think Bigger. Um, and then the last part is you now use that system of getting pieces outside and inside. And now you almost like a kaleidoscope, create lots and lots of different options, lots and lots of different ideas. You compare and contrast them against your metrics of success because you never want to pick something that goes against your original goals. And now you find an idea. And we have a tendency when we have an idea to, you know, walk up to somebody we care about, you know, let's say our kid, our spouse, our dog, and say, what do you think of my idea? And then they're like, oh, that's great. And then we're very pleased with ourselves. But. And if they hate it, then obviously they don't know what they're talking about. Um, and so what we do in step six is something we refer to as the third eye. And the third eye says, I don't. It's not really relevant to me. If you like my idea, if you hate my idea, that's not teaching me anything. What I need to really understand is when I describe my idea to you, what do you see and how would you in turn describe my idea back to me or to a third party? Because if I want to know if my idea is sticky, if my idea has legs, it needs to go beyond my head, others have to be able to communicate it in their own words in ways that builds on what I came up with. And that's the real litmus test. And so the sixth step is the third eye. It's going to others, describing your idea and seeing how that idea sounds from others mouthpieces.

Speaker A: So, Gina, you did a great job of taking our viewers and listeners through the overall framework behind Think Bigger. And I know that you and your team have been working to create a tool using Gen AI that helps bring that framework, bring that process to life in a very, very practical way, uh, for teams that are working through innovation processes. So what I'd like to do now, and this will be the first, uh, time we've ever done this, uh, on the podcast, is turn it over to you and Ingrid to take us through a live demo of what this tool looks like and how it works.

Speaker B: Thank you so much. I'd like to introduce you to my co founder, Ingrid. Uh, she and I and a couple of others, a software engineer, have been putting together, uh, a Generative AI a, uh, Think Bigger app that helps you do the very steps that I just described to you. It helps you do that in a matter of minutes, and you can apply it to any sort of business problem that you might have. So let's pick, you know, a problem that maybe everybody can relate to. It's my local coffee shop, and I want my local coffee shop to succeed. Uh, so the coffee shop that's right here where I am is called Dear Mama. And so the problem I want to solve is, um, how do I. How do I increase the number of, uh, customers that go to Dear Mama so that Dear Mama becomes the number one coffee shop for Columbia faculty, staff, staff, students, our entire Morningside community. And so the way this app begins is you start by putting in a problem. Notice, I put in the problem as a question. And the reason why we put problems in as a question is because when we put in, we think of our problems as questions. We have much more of an open mind. So we start by putting in a problem. And now what it does is it breaks it down for you. Now it does its best guess. It thinks about the problem. It searches. It now searches all the different, um, challenges, and it'll try to prioritize based on frequency of occurrence. What are the five most likely challenges that you have to confront to solve this problem problem? So, Ingrid, what challenges does it give you?

Speaker C: We have? How can we identify and target the specific preferences and of the Columbia University community? How do we enhance the visibility and appeal of Dear Mama to the members of Columbia University? How might we optimize the customer experience at Dear Mama to encourage repeat visits? How can we leverage social media and digital marketing to attract more Columbia University students and staff? And how do we engage with the Columbia University community to build loyalty and a strong brand presence?

Speaker B: Okay, so it breaks it down and you can edit these. If, you know, if you were the owner of Dear Mama, you can say, well, I don't really care about M1 of these, and I'm going to edit it. So you. You can edit this as you go along. It's interactive. But let's move on now to step three. In step three, you have to think about who are your stakeholders. So, uh, let's imagine I'm taking on the role of the, um, the owner of Dear Mama and my target, meaning my customers, my target are going to be members of the Morningside community, Columbia, uh, University community, because this is a coffee shop in a university area. Um, it will also ask you if you have third parties in mind. Um, and, you know, for mom and Pop shop, you may not have too many third parties, but obviously if you're a bigger business, you often have government regulators and investors, etcetera, as your third parties. But for now, we'll just stick to, we'll keep this simple. These are our two parties. And now what it'll do is it will identify for you the, the needs of each of these stakeholders. Right. Because a lot of times we as problem solvers tend to only think about what we want, as, you know, the leaders or what our customers might want or what our boss might want. We may not think of the needs of across all the various stakeholders. So what this does is it gives you its best guess for what the needs might be. So, Ingrid, you want to tell us some of the needs that have popped up?

Speaker C: Sure. For the community, we have, um, to enjoy a welcoming atmosphere that fosters community engagement. Um, there's also to have convenient facilities for studying in meetings. For the owner, it might be to, um, increase customer retention with loyalty programs and promotions. And we also have to enhance menu offerings to cater to diverse customer preferences.

Speaker B: Um, and what it does is it also gives you a site, uh, a place where you can hit the button and it'll show you the sites like, uh, how did it come up with these needs? So that you don't have to wonder, well, how did it come up with this stuff? It actually tells you where it found these, uh, and you can edit these. Right. Again, as the owner of Dear Mama, you may have much better specificity about what your needs and wants are. So thus far, what's happening here is it's helping you think through the problem. Because a lot of times simply having something prompt you to think of what's the problem? How do you break it down? Just doing this much helps you get past that initial hurdle, that initial intimidation to even start a problem. This gets you started. You're starting to think you're now off to the races. But let's imagine that thus far everything is in line. Um, and I'm going to continue. So I'm now ready to think about what are some potential solutions. So now what it's going to do, it's going to give you what we call the choice maps. Remember steps 4 and 5. We search in and out of the box and choice map. So we're up to the choice map. So what it does is it gives you a five by five. So at the top you have the problem and along the left column you have your five sub problems. And obviously if we had edited these sub problems, it would have been the edited sub problems. And now what it does is in the first column, it gives you different strategies that are typically used in your industry. Now let's look at the second column. It's kind of giving me what's going on in industries that are not exactly mine, but they're near enough. Now, if you go all the way to the right, that's where it's really trying to say, well, you know, maybe you want to think of some, you know, some other boxes. Who else has solved sort of similar problems? And what do you have there?

Speaker C: We have an example from Ben Franklin in the 18th century. Um, there's also the coffeehouse movement in the 19th century, um, 19th century marketplaces, more Ben Franklin. And also an example from the Medici family.

Speaker B: Okay, so notice how what you have here is you have strategies. And for each strategy, it gives you a reference so that you can click on that and it'll teach you something more about it. You can learn about this because I don't want you to just take me at my word. So really, in many ways, when you do a Google search or a library search or a ChatGPT search, you'll get a lot of hits. But you have to then read through it and figure out what's good, bad, true, false, uh, relevant, irrelevant. What this is doing is it's pulling for you relevant strategies drawn from both within your industry, out of your industry. Historical stuff giving you the reference, and it's organizing it for you to make you understand why you might be interested in it, why it might be relevant. Um, so now let's imagine you've looked at all this and you've said, oh, some of these things are kind of interesting. Now I'm ready to come up with some ideas. So the first thing I'm going to do is I'm going to take the strategies that are just in the first column. My most conservative strategy is to just take best practices from within my industry and say, okay, if I were to combine these, what would I get? And so it's now going to combine these for you. And what it's going to pop out for you are two scores. The first is going to give you what we call big picture score. And the big picture score uh, says what percentage of the needs that you said were associated with your stakeholders would be met if you employed this strategy, this collective strategy. And it'll also give you an innovation score, which is, you know, how out of the box did you get? So for this one, since we stay very conservative, the out of the box score should be zero. So what do you have there, Ingrid?

Speaker C: So we have a big picture score of 43% and innovation score of zero.

Speaker B: Yeah. So not very good. So sticking to best practices, maybe not so great. So now what we could do is we can say, well, but what if I want to do something a little different? So let's take, you know, I'm really curious about the coffee, the historical coffee house. Ingrid, let's take that one and make a new idea with that. Let's see what happens then. And so what she's going to do, she's going to take the coffee house and then she's going to randomly pick some other ones. Now, of course, we could have taken Coffee House plus a few others. If you had one in mind, you could pick the ones you most want. Um, the coffee house one stuck out for me, so I'm going with my biases.

Speaker C: So we have a big picture score of 80% and an innovation score of 4 out of 5.

Speaker B: That's not bad. Okay, what about if you took one of the Benjamin Franklin things? Sure, that's another one. I'm kind of cool. I like the Benjamin Franklin and Medici. And, you know, honestly, I would say if you look at history, the most successful innovations, no matter what point in history you take, the most successful innovations are usually a mix of the stuff within industry that are expected, a mix between that and just one or two things that are unexpected. All right, so what did you get here when you put, uh, Benjamin Franklin and some Medici in there?

Speaker C: So we have a 57%, but an innovation score of five out of five.

Speaker B: Yeah. So it's quite innovative, but it's probably meeting fewer needs. So why don't you do a random combination? Sure. So we can also ask it to do a random combination. So in our, um, Generative AI Think Bigger app, it will allow you to do up to nine different ideas. You can pick which strategies you like. You could have it randomly generate, um, and so you can get different strategies. And you notice how it also gives you scores so you can compare and contrast.

Speaker C: So for this, um, combination, we have a score of 60% and innovation score of 2 out of 5.

Speaker B: Okay, let's do one more, and then we'll pick one. And we'll take it, um, to the next step.

Speaker C: Okay.

Speaker B: This is a beta product that we're showing you. And we've actually been pre testing this, pilot testing this, and we did it with a bunch of MBA students. Uh, they learned the method and used this tool, uh, in just two days. Uh, they came up with different entrepreneurial ideas. And we actually had two students that got funding, uh, for their entrepreneurial ventures. Uh, we also just recently pilot, uh, tested this tool with 12 CEOs of manufacturing companies that used this to come up, um, with two year, uh, strategies to your growth plans for their companies.

Speaker C: So for, uh, the latest, uh, combination, we received a score of 60%.

Speaker B: Okay. And so what this means is, oh, why don't you show them? So let's take the one that had 86%. Okay. Uh, what. For each of these, what you can do is you can actually look to see what needs are met, what needs are not being met. And essentially, if we had more time, we would keep playing with this, we would keep going back up because maybe we could define the problem better or differently. Uh, it would also help if I knew something about what Dear Mama's, uh, owner, uh, wanted. Um, and so we can keep playing with this until we actually get one that gets us closer to our real needs. Um, so let's take this 86% one and take it down to the bottom. And our final step is, you know, look, I, I may like this idea. Ah, the strategy sounds, you know, interesting enough to, in my head, but how would this actually read to an outsider, to somebody else? And so in the last step, you're asked, well, let's create an elevator pitch. Who do you want to present it to? So, so let's imagine that the owner of Dear Mama wants to present it to, um, you know, Columbia University, like community, like a potential customer.

Speaker C: Okay.

Speaker B: And, uh, and so now it'll give you an elevator pitch. It'll give you a memo, it'll give you a five step plan. Um, and so it actually, and the idea here would be to do this for more than one idea so that you can compare and contrast which one seems better, which one seems worse. Um, and some of the things that we're working on building out in the future, uh, is to make it so that it'll give you a full product roadmap. Uh, you would be able to click on it to give you a PowerPoint slide deck if you wanted, depending on what project you were working on. There you have it, our Think Bigger demo.

Speaker A: That is really impressive. This is one of the, uh, best applications I think, of Gen AI that I've seen manifest and brought to life. I have to give you all, uh, just a great deal of credit for taking advantage of the cutting edge technology, but also doing it in a way that is extremely intuitive and useful. Nicely done.

Speaker B: Thank you. Appreciate it.

Speaker A: Hina, as you and your team went through the process to create and test this tool, what did you really learn about where this tool can help potential users the most?

Speaker B: Well, I would say that what we learned was some of the very insights that I knew theoretically as somebody who studied choice for years and now got to be a live guinea pig for. Um, I actually have experienced the too much choice problem firsthand. Uh, there are no two people that will look at this app and not come up with a choice. Totally different used case. And so, like I tell all my, you know, when I do a too much choice talk, I always say the most important thing for managing choice is to be choosy about choosing. I have to remind myself of that every day. Um, and so I would say that was one lesson I learned is that really it's got so much potential, but in order for it to be really effective, you've got to remind yourself to focus, focus, focus on the most important priorities so that, uh, it will have obvious usability for people, um, for particular problems.

Speaker A: So for folks who would look at this and say, oh, wow, you're taking this highly creative process or process that, uh, involves a lot of creativity and you're replacing it with Gen AI. You know, you could imagine some people getting freaked out in the sense that, oh, you're, you're, you're taking the creative part away from people. How would you, how would you position that? How would you think about that?

Speaker B: I actually think we're augmenting people. I don't think we're taking anything away. Notice how in every step of the way it's interactive. So if anything, I'm making the black box of generative AI and the mind more transparent. Right. So this is essentially what your mind does. It's just often you're not aware of it. I've just made it more transparent by. And made it transparent in a way that prompts you and makes it more of an aid and assist. So it's helping you, you know, be more deliberative about the problem breakdown. You're probably intuitively thinking about half of those without even realizing it. But I've made it more transparent. You certainly are aware of certain metrics of success. I've just made all of them more transparent. You're certainly combining pieces in your head when you're trying to come up with a flash of insight. I'm just being deliberative about it. And I'm going beyond what's at your fingertips in terms of knowledge by making the library much more user friendly for you, by giving you stuff in an organized way that is potentially relevant. I really see this more of as an assist, uh, than as something that if, uh, anything, I would hope that this makes being creative easier and more fun.

Speaker A: Excellent. So what's next for the tool in terms of you've got the current iteration of it? It looked, it's looking pretty good. It seems pretty logical to use. But what's next, uh, on the roadmap for it?

Speaker B: Uh, the next thing on the roadmap is to make this uh, really intuitive so that anybody can use it. You don't need me to demo it. You just upload it on your phone or on your computer. You can use it whenever you've got a problem you want to get some insights on. So we have to mainly design it on the front end to make it uh, really user friendly.

Speaker A: Are there plans to uh, launch it in a commercialized way? Like how are you thinking about it from a business, like a kind of an adoption and business standpoint?

Speaker B: Oh yeah. So we will, you should follow me on my webpage. We will announce its launch and then you can download it. The first people that will download it will get it for free. And then after the early adopters we will start uh, charging people. And we're expecting to charge people around the same as you would chart. You would get paid for this kind of an app for, for other apps as well. So less than $20 a month.

Speaker A: Fantastic. So we've talked a little bit about what's next for the app, what's next for you, what's on your mind in terms of topics you would, you would want to delve into for the next round of research? If you were going to write a third book, what would it be about? What's on your mind for what's next?

Speaker B: So as an entrepreneur, I want to be able to take, think bigger, uh, at the individual level. And I'd also like to make it evolve to being an enterprise level product as well so that uh, employees at a company, uh, can think bigger collaboratively about different problems that they're confronting. So I see that as first we start with individuals, then we move to the enterprise level. Uh, so that's what I see in terms of me as an entrepreneur, uh, for me, as an academic that continues to try to help people make better choices, I essentially see my next step is continuing to study choice. What's amazing about choice is you never run out of, uh, things to better understand about choice. Uh, so I think, uh, I think the next thing I would want to do, if you think about the big struggle that people have and have had, um, for a long time, is they're always looking to figure out how to answer the question, who am I? Who do I want to be? And I think think bigger can be applied in a much more concrete way to help people answer that question for themselves, whether they're right out of college or graduate school or whether they're starting their second or third career in their life. How do I reposition myself and come up with my new career path? So I think of that as the power of choice.

Speaker A: So, Hina, I know we spent a lot of time talking about choice today. Too much choice phenomenon and so on. Um, I know that, you know, just in the aftermath of the election, there are a lot of people now that are kind of thinking through the choices that were made and what's the outcome? What's the results of the choices? What's next for me? What's your advice? What's your thinking for folks who are kind of caught in this, this post election world right now?

Speaker B: Well, as I mentioned earlier, the words I hate most are, uh, it's not possible. And I would say that the thing that concerns me is how many women I've been hearing from feel a sense of powerlessness or paralysis. And they're asking as individuals, as a collective, uh, can I achieve the American dream? Is it even possible? Or is this not the land in which that dream can ever be applicable to a woman? And I'd like to say that it is. And I think the way we get there is by every single one of us making a pledge. And here's my ask of you that can we make a pledge as individuals that in the next week we will pick one woman that we will help, even if it's in a small way help her m. In some way get closer to achieving her dreams?

Speaker A: I love the challenge. And yeah, I would, uh, strongly encourage all of our listeners and viewers to think personally about what they can do, um, in that regard. So one last question then, is just kind of a closing thought. As an entrepreneur, do you have any parting advice for the entrepreneurs in our crowd that are listening and viewing today who are, uh, have these ideas that they want to bring to market what would you. What advice would you give them?

Speaker B: I would say the biggest question that you want to ask yourself every single day as an entrepreneur is what's that problem that your product is solving for? If you can answer that question, that helps you motivate your team, that helps you know what to say to your investors, to your potential customers? What's that problem you're trying to solve? And what's that vision of what that solution that your product is offering look like? Everything else will fall in place.

Speaker A: Fantastic. Well, I would like to thank you, Sheena, for your time today. This has been a very enlightening, wonderful discussion. It was great to see the tool that you and your team have created in person. Uh, but thank you for being part of the podcast and wish you all the best in your endeavors.

Speaker B: Thank you so much. And remember to think bigger.

Speaker A: The Decoding Innovation Podcast series is a limited production of the EY Nottingham Spark Innovation HUH Hub, based in Cleveland, Ohio. For more information, visit our website@ey.com decodinginnovation if you enjoyed this podcast, please subscribe. Leave a review wherever you get your podcasts and be sure to spread the word.