Chicago Booth Review Podcast Can Technology Make Us Smarter?

Pradeep Chintagunta: So, I think there's a lot of information that's coming out of the app because it's capturing their own information, but it's translating it into a way that is then useful for them for their decision-making. And I think that's really the power behind the app.

Hal Weitzman: Doom scrolling, social media cat videos and YouTube rabbit holes. You might well think that technology is more mind-numbing than mind-boosting. But could tech actually make us smarter? Welcome to the Chicago Booth Review Podcast, where we bring you groundbreaking academic research in a clear and straightforward way. I am Hal Weitzman.

Today, Chicago Booth's Pradeep Chintagunta tells us about his research on the effect of technology on small business owners. Could using apps help us to think in new ways and make better decisions?

Pradeep Chintagunta, welcome to the Chicago Booth Review Podcast.

Pradeep Chintagunta: Thanks, Hal. Nice to be here.

Hal Weitzman: It's great to have you here. And we are here to talk about how technology can make us smarter. Right?

Pradeep Chintagunta: That's right.

Hal Weitzman: So, you've written this paper that's called (Smart) Technology Doesn't Make Us Dumber. You've done it in a negative, I guess. What is the prevailing view that you think you're challenging with this research that says that technology does make us dumber?

Pradeep Chintagunta: Well, I think there's a lot of concern these days, especially with people's access to gadgets. They're constantly on their mobile phones. The question is, is this distracting them from things that they could be spending their time on? And so, one of the things that we wanted to do is to see whether this prevailing view was true in the context of small businesses, specifically in Rwanda.

Hal Weitzman: Okay. So, your sort of headline finding here is that tech can really improve how we think. Tell us... I mean, is that right? Is that the headline?

Pradeep Chintagunta: That is the headline. I would like to caution listeners that this is focused on a very specific aspect that we are looking at. These are small businesses that typically do not have access to the kinds of technology that we are making available to them. And as a consequence, within that narrow realm, I think that is the finding.

Hal Weitzman: Okay. So, at least according to those parameters or the way you set up the experiment, which we talk about, tech can actually make us think better or improve how we think. As you said, it's from Rwanda and a study of micro-enterprises, small companies. Why did you choose Rwanda or did Rwanda choose you?

Pradeep Chintagunta: Well, I think you could say it's both ways. Rwanda, I think, for the short answer to that question is that that's where we had the money to do the study. These studies tend to be expensive, and that was the reason why. But also, I think Rwanda is a country that has focused a lot on tech. They've been trying to improve the access to technology for a lot of their citizens and businesses. And I think there's a general interest in trying to see whether technology can improve the lives of people there.

Hal Weitzman: So, we might have a prejudice thinking that Rwanda, there's not a lot of tech around, but you're saying actually that's not the case?

Pradeep Chintagunta: Well, to the extent that payments, for example, are done a lot on your mobile device, which is quite unlike other countries like the U.S. So, I think in some dimensions, yes. But in other dimensions... For example, in our experiment, we used smartphones. And at the time we ran the experiment, not everyone had access to these smartphones. Most of what they did was on feature phones or the old, if you recall, either the flip devices or... I forget what the other device is called. But yeah, so these older technologies that were prevalent at that time. And so, there are some things that clearly they are or were ahead of where we are in the U.S., but on other dimensions, I think they are not.

Hal Weitzman: Okay. So, walk us briefly, your headline finding is that in these particular businesses, in the context of Rwanda, that they actually were able to improve the way they... thinking about business using technology. Tell us about your methodology. How did you find that out?

Pradeep Chintagunta: Yeah. So, the gold standard for a lot of these types of questions is to use what's called a randomized controlled trial. And so, that's what we ended up doing-

Hal Weitzman: Just remind us what that is.

Pradeep Chintagunta: Okay. So, a randomized controlled trial essentially means that you randomly assign, in this case, businesses to either a treatment group, which is the group that actually gets the input that you want to study, and the other group, which we'll call the comparison group, sometimes also called the control group, which does not get the same access.

Now, our study was slightly different in the sense we had a third group, which we called the placebo group. And the placebo group essentially got access to the smartphone, but did not get access to the technology we put on the smartphone, which is the app that actually collected data about the business and provided the business information about how they were doing.

Hal Weitzman: Okay. So, tell us about the methodology. So, it sounds like you gave those in the placebo group and those in the test group smartphones, and the ones in the test group had the app, and the ones in the placebo group didn't have the app, and then the control group had no phones. Or you didn't give them phones anyway?

Pradeep Chintagunta: That's correct. We did not give them phones. So, we had 250 firms in the treatment group, another 250 in the control group, and we had 50 in the placebo group. So, the treatment group essentially got the smartphone and the app installed on it. The placebo group only got the smartphone. And the control group got neither. But all of them did get visits from our enumerators who were gathering the data.

Hal Weitzman: Okay. But you were trying to find out what difference it made to actually have the phone and to have the app. So, tell us about the app.

Pradeep Chintagunta: So, this is an app that we ended up designing. There's an interesting side story to it. The company that designed the app was very keen on essentially pursuing the academic market for their future offerings. But after working with us, they decided that they were not interested in that segment anymore. So, maybe this tells you something about how difficult it is to do these things. But in any event.

So, this is an app that we designed. The idea was very simple. How can we get businesses to record their own information and then provide outputs from that information back to these businesses that could potentially help them improve their decision-making? That was the idea. And so, think about a typical marketing class that you would teach in a business school. There are certain kinds of metrics that you are interested in knowing. For example, you would want to know what your sales are. So we capture that information. You want to know what your top-selling products are. We capture that information. Who are your top customers? What are the different types of customer segments you have? What are the marketing activities you engage in? So, these are all the pieces of information that we capture through the app. And we essentially make the app friendly enough for people to provide this information on a regular basis.

Hal Weitzman: Right. But when you say you capture it, they're the ones who are inputting it?

Pradeep Chintagunta: That's right. The burden is on them to input the information. And what we can do is to nudge them to make sure that they actually input that information. And one of the things that I think we observe, and maybe I'm getting ahead of myself here, is that in the initial part of the intervention, there was some reluctance to actually input that information. But as we kept nudging them, getting them to put that information in, what we noticed was that these businesses got increasingly engaged with the app. And so the rate at which they input their information actually went up over time.

Hal Weitzman: Okay. So, just so I understand, what was the nudge that you used?

Pradeep Chintagunta: We made sure that we sent them messages on their smartphone to ensure that they actually input that information. Now, I think we also made sure that this was not terribly onerous for the business owners, because that's sort of the trade-off in a lot of these exercises. If you ask too much information from these business owners, then they might be more reluctant to provide that information. So, on a daily basis, the only information we tried to get from the owner was whether or not the store was open or the business was open and what their total revenues were. And then the other pieces of information we gathered were at a much lower frequency than the frequency at which we measured or we got them to input their sales and revenue numbers.

Hal Weitzman: I see. So, you mean weekly? Or what was it?

Pradeep Chintagunta: Yes. So, this was biweekly. So, every other week, we would ask them to provide information on their top three products, on their different customer segments. And in the weeks where we did not ask them these questions, we would ask them information about their marketing activities, et cetera.

Hal Weitzman: And it's interesting that you say that they didn't use it at first, because you sort of would think there's something novel. If you haven't had a smartphone, there's something fun or novel about it. And you might see the opposite. They might like going to the gym. You go on first week of January, then you never go back. You might've thought they would do it first and then forget about it, but you found the opposite.

Pradeep Chintagunta: Right. So, I mean, you're right. I mean, I think if you think of this as the new toy, they had a smartphone, maybe they'd be more willing to do it. But I think these are all businesses, and they spend a lot of time working in their business. So, I think unless they really see value from inputting the information... They might have been on Facebook or Instagram. That's certainly possible. But as far as the experiment was concerned, I think unless they were convinced that this is information that was ultimately going to be useful for them, I think there was some reluctance in the initial part of their engagement.

Hal Weitzman: Right. They just weren't used to it, it sounds like. I mean, how many businesses and what kind of businesses were involved in this study?

Pradeep Chintagunta: Yeah. As I said before, there were about 250 businesses in the treatment and control groups. A vast majority of them happened to be retail businesses. Some of them were in services, like hair salons, et cetera. A lot of them were, as I said, shops. There are very few in other sectors, like manufacturing, et cetera.

Hal Weitzman: So, we can imagine a small grocery-type store or newsagent-type store and they're selling lots of products. And I'm guessing that they're not being particularly scientific or data centric right up until your intervention.

Pradeep Chintagunta: That's exactly right. In fact, one of the big insights that we got was, when we asked them about their top three selling products, one of the things that we asked them to provide us information with was both the price at which they sold the product and also how much it cost them to procure the product and make it available to the customer. And then, using those two pieces of information, one of the things the app does is it computes the net margin on each of these products.

One of the things we noticed is that getting the business or entrepreneur familiar with whether or not they were making money on a product has a big impact on how they choose, for example, which products to actually have in the store, whether they need to change their prices, et cetera. So, I think the task of inputting that information, I think, gives them details about their business that they probably hadn't thought about before.

Hal Weitzman: Okay. So, just give us a complete sense of what were the data that you asked them to input. So the top products. You mentioned some other ones [inaudible 00:12:54]-

Pradeep Chintagunta: Yeah. So, first of all, the sales and revenues every day. And then we ask them for their top three products, what their prices were, what their costs were. And then we also asked them about different types of customer segments. "How many regular customers do you have?" "How many occasional customers do you have?" "How many new customers you have?" And we also ask them about things like, "Did you change your prices? Did you introduce new products," and other marketing activities they might have engaged in.

Hal Weitzman: Okay. So, you said that these entrepreneurs or these business people are not necessarily... They're not necessarily entering or keeping information, the kind of information at the detail that you're giving them access to previously, previously to your study. But do you know anything about if they're comfortable with digital tools at all of any kind?

Pradeep Chintagunta: Not really. I don't think that's one of the things that we had measured. At the end of the experiment, we went back and looked at the placebo group to see whether having access to the smartphone essentially motivated them to look for these kinds of apps. And it turns out that it does not. Most of them ended up-

Hal Weitzman: They're on Instagram.

Pradeep Chintagunta: Yeah. They're on Instagram or Facebook, or they certainly have WhatsApp. So, I think those are the kinds of things that I think these businesses that were not given the app gravitated to. So, my sense is that just having access to the smartphone itself doesn't necessarily nudge them to seeking out these kinds of apps.

Hal Weitzman: If you're enjoying this podcast, there's another University of Chicago Podcast Network show that you should check out. It's called Entitled, and it's about human rights. Co-hosted by lawyers and law professors Claudia Flores and Tom Ginsburg, Entitled explores the stories around why rights matter and what's the matter with rights.

Pradeep Chintagunta, in the first half, we talked about your research in Rwanda with small business people and how you gave them smartphones, you gave them an app, which I think was called Market Manager, right?

Pradeep Chintagunta: That's correct.

Hal Weitzman: And with that Market Manager app, you found that they could do all sorts of things that they had probably not been doing before, like work out net margin on each product and that kind of thing. And we'll talk a little bit about how that changed their behavior. But I'm interested in how you isolate the effect of the app and the sort of analytics that it provides, but rather than... I mean, for example, rather than just having the information. So if they just journaled more or done some basic math and worked out some of their basic metrics, would that have worked as well? Or is there something special about technology, do you think?

Pradeep Chintagunta: I think there are a couple of things there. First of all, one of the things that we did record at the start of the experiment was whether they maintained records of any kind. Now, it turns out that a lot of these businesses do not necessarily maintain records, but they were about, if I recall correctly, close to about 30% of the businesses that actually did so. So, one of the things that we tried to do is to go back to that subset of businesses to see whether we saw an improvement in those businesses as well, and we did. So, that leads us to believe that it's maybe something a bit more than recordkeeping, because if we're just recordkeeping, then we wouldn't have seen a big improvement in these businesses.

Now, obviously, with 30%, you're not powered to detect statistical significance. Nevertheless, I think directionally, those results were very consistent with those who did not maintain record. So, there has to be something more in the app than simply recording.

Hal Weitzman: Okay. And I know as part of this, you hired some tech support specialists. And I'm wondering, same kind of question, how do you know it's the technology that's doing it? So, how did you set boundaries to make sure what you were measuring was the technology, not just some business consulting that they might help with?

Pradeep Chintagunta: That's, I think, a really good question. And I think that's a question that comes up all the time. I think one of the things that we made sure about these tech support folks... By the way, just to clarify who these folks were, they were essentially people who'd show up at these businesses to, in the treatment group, make sure they understood how to input the information and how to read the information that was provided to them. For the placebo group, it was also to make sure that they frequently top up their calling plan. And so, since we were providing them the data plan with the smartphone, we essentially made sure that the tech support person topped up the plan for the placebo group. So, that is the context.

We also chose these tech support personnel who were largely undergraduates from college. And so they really did not have much business experience at all. And so, we chose that purposefully because if we had chosen people who had had business experience, then they might have been tempted to provide guidance beyond the information that's available in the app. But these were folks who were selected such that they really did not have experience. And in fact, if they did try to offer guidance, it's not clear what the outcome might have been. It's possible that the businesses would have ended up doing worse rather than doing better.

Hal Weitzman: You mean because they're not really-

Pradeep Chintagunta: Because they don't know the business.

Hal Weitzman: Yeah. They're not really the McKinseys or whatever. They're tech support people. Okay.

Pradeep Chintagunta: And they rarely have entrepreneurial backgrounds [inaudible 00:18:43].

Hal Weitzman: Right. That makes sense. Okay. So, you said in the first half that you saw this interesting pattern where people were reluctant to... I guess they saw it as a burden to put in the data at first. And then over time, they saw the importance and they relied on this app more and more. What do you think prompted them to increase their use of the app?

Pradeep Chintagunta: I think it's precisely the usefulness of the app that they perceived. In the beginning, since they didn't really know much about the app at all, there was reluctance to spend their time inputting all the information that we required them to do. But as they saw the reports come out of the app, the reports basically now were potentially perceived as containing useful information for them. And once they saw that information, then I think they became much more likely to respond because now they know that unless they put in that information, they're not going to get the useful data for them to then make their decisions.

So, my sense is that this ability to get these reports out of the app... Right? So the inputs are one thing, but the app also gives them outputs, which makes it easier for them to do things like comparisons as to how they did last month, how they're doing across products, et cetera. And that kind of information, I think, really helped in them convincing themselves that this was an activity worth investing in.

Hal Weitzman: Okay. Now, I mean, just tell us a little bit more, because you mentioned net margin. What else did they get? What other metrics did they get from the app?

Pradeep Chintagunta: So, the big thing that the app does for them is it provides them trends over time. So, they know, for example, "If I made a margin of so much in this month," the next month, whether the margin increased, decreased, et cetera. And so, I think they also get to keep track of whether their sales are going up, whether their sales are going down. Are the sales flat? Are their number of regular customers, is that going down? Is that going up? If it's going down, then maybe that's signaling a problem that they have to deal with. So, I think there's a lot of information that's coming out of the app because it's capturing their own information, but it's translating it into a way that is then useful for them for their decision-making. And I think that's really the power behind the app.

Hal Weitzman: Okay. So, let's talk about this big finding that we mentioned at the beginning, that this technology didn't just give them interesting data, like you say, but actually enhance their core mental capabilities, their ability to reason, the memory, logic, calculation. That's astonishing. Tell us how you found that.

Pradeep Chintagunta: Yeah. So, to us, that was also one of the things that we were not sure going in that we would find. And I think it is very heartening to actually find that result. And I think the way we would like to interpret this is that a lot of these folks went to school. It's not as if they didn't know numbers at all. But just interacting with the numbers on a regular basis, I think, gives them some skills when it comes to numeracy. And so, they get more comfortable dealing with numbers. They get more comfortable interpreting numbers. And so, when it comes to the point where we are actually putting them through these objective numerical tests, they have improved enough that we are able to show that their level of ability when it comes to numbers and math is actually better than the control group. And I think that was-

Hal Weitzman: So, how do you actually know... How do you test their cognitive abilities?

Pradeep Chintagunta: Okay. So, we tried a bunch of different tests that we ran with these entrepreneurs. The first test that we ran was something called a cognitive reflection task. And just to give you an idea of what that task might look like, a typical question here would be that "A bat and a ball costs 110. A bat costs 100 more than the ball. How much does the ball cost?" And instinctively, I think a lot of people would say 110. But to get the right answer, you'd have to think a little bit more. And then, if you spent that additional cognitive processing effort, you would come up with the right answer.

So, it turns out that while there was not a large numerical increase, the increase was certainly statistically enough that we were able to conclude that the treatment group entrepreneurs actually did better than the control. So, just to make that more specific, the control group essentially got less than one question right, so about 0.7 of a question right, whereas the treatment group got about one question right. And this was a set of three questions that they were asked. So, one out of three versus less than one out of...

Hal Weitzman: So, they seemed to be more comfortable with these kind of mental math.

Pradeep Chintagunta: Right. That's right. And we also asked them several questions about just numerical calculations. These were just additions, subtractions, those kinds of questions. And again, the treatment group seemed to do much better than the control group. So, we ran a battery of these tests. And pretty much, I think, across the board, what we find is that the treatment group performs better than the control group.

Hal Weitzman: Okay. And then as well as this improvement in mental performance, you've got these other what you call spillover effects in business practice. So, tell us about those.

Pradeep Chintagunta: So, that, to us, also was quite interesting. Because if the mechanism by which the ultimate performance of the business is improving is because of their numerical abilities, then you would expect that maybe this might spill over to other aspects of the business, which also require numbers. And a typical example of this would be something related to accounting or finance. And so, what we do find is that these entrepreneurs in the treatment group started maintaining what you might consider rudimentary cashflow statements. They would try to make sure that they separated their business finance numbers from their personal finance numbers. So, this-

Hal Weitzman: Without you telling them to [inaudible 00:25:17]-

Pradeep Chintagunta: Without us telling them. This had nothing to do with the app. The app had no questions about any of this stuff. But with their comfort level with numbers, they started doing things like this. They started keeping track of inventory. They would note down the number of used shirts or used trousers they had. And so, this, to us, was an important consequence of this numerical ability that they seem to have gotten through the app, was that they were able to translate this now to other contexts, such as accounting and finance.

Hal Weitzman: All right. So, you talked about how these entrepreneurs that you studied were in Rwanda. And this was a while ago. It was before mobile, the smartphones were really dominant, I guess. So, when did you conduct this research?

Pradeep Chintagunta: So, this was 2019, 2020. It actually ended around the time of COVID.

Hal Weitzman: Okay. So, it was a while ago. And I'm just wondering, hearing you speak about metrics and how metrics change people's behavior and even intelligence, if we can call it that, whether that would work in the United States. You have a lot of small businesses. I'm thinking of, like, your local bodega or someone who sells ice creams in the park. Do you think they're really tracking metrics in the way that this app allowed them to? And if not, why wouldn't this work here?

Pradeep Chintagunta: First of all, I must acknowledge that we haven't actually tried running this study in the U.S. So I can't give you a scientific answer to the question. However, anecdotally, I think it is the case that there are lots of businesses all over the world that actually don't track their business outcomes or even their business inputs to the extent that even a simple app like the one we designed does. So, to me, if a business hasn't really focused on the key metrics that are important for them to grow their business, I think such an app would definitely be of help. So, thinking about what the right metrics are for each business could be different. And those metrics could be different here versus in Rwanda. It's possible. But I think once you understand what metrics are important or key to a business's performance, then making sure that businesses systematically track them, see the information, see the outputs of a simple analysis like we provide, I think, could help businesses all over the world.

Hal Weitzman: Now, I know you don't want to universalize too much from this research because it took place in a particular place with a particular group of people. However, I'm going to ask you to do a little bit.

Pradeep Chintagunta: All right.

Hal Weitzman: I mean, what do you think this research tells us about human capital?

Pradeep Chintagunta: Yeah. I think there are many different ways of building the human capital. And when I talk about human capital, I would like to focus more narrowly on managerial capital because I think that's what I have tended to focus on in my research. And I think the research has shown that there are many different ways of building this managerial capital. I think some of it is through remote mentorship programs. Some of this is through training. Some of them variety consulting, variety of other ways in which managerial capital can be enhanced.

I think what our study shows is that there's another dimension of this managerial capital, which is having the ability to use data, to use information, and use it in a way that's going to be helpful for the business performance. And to the extent that our study highlights the fact that a technology, even as simple as the app we create, can in fact enhance the ability of the businesses to make better decisions, I think it feeds into the broader discussion about how various inputs, including like the one we provide in this study, help enhance both managerial capital and, as a consequence, human capital at large.

Hal Weitzman: Well, thank you very much, Pradeep. This is a fascinating research. Technology could actually help make us a bit smarter.

Pradeep Chintagunta: That's what we believe. Thank you very much, Hal.

Hal Weitzman: Okay. All right. Love it. Thank you very much for coming on the Chicago Booth Review Podcast.

Pradeep Chintagunta: Happy to do that.

Hal Weitzman: That's it for this episode of the Chicago Booth Review Podcast, part of the University of Chicago Podcast Network. For more research, analysis and insights, visit our website, chicagobooth.edu/review. When you're there, sign up for our weekly newsletter so you never miss the latest in business-focused academic research. This episode was produced by Josh Stunkel. If you enjoyed it, please subscribe and please do leave us a five-star review. Until next time, I'm Hal Weitzman. Thanks for listening.