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This month, Insight In Person looks at how to incorporate games and game theory into savings and investment strategies.
Ben Iverson, a professor of finance at the Kellogg School, discusses prize-linked savings accounts, which are a novel way to turn people’s love of the lottery into a vehicle for growing personal savings.
James Schummer, a professor of managerial economics and decision sciences at the Kellogg School, discusses how game theory can be incorporated when calculating the risks and rewards of investing.
Willemien Kets, a professor of managerial economics and decision sciences at the Kellogg School, joins the podcast to describe her research into how the wisdom of crowds can help ensure the accuracy of prediction markets.
The enthusiasm that David Schonthal has for startups is not based solely on how much funding they might raise, the chance they may come up with a giant-killing innovation, or the potential for a massive buyout from an established firm. Instead, Schonthal, an entrepreneur focused on the health care industry and a clinical professor of entrepreneurship at the Kellogg School, is fascinated by how start-ups exploit their constraints.
“The interesting thing about constraints is how they can be used positively,” Schonthal says.
Let’s face it: given limited funding, a small-if-intrepid staff, and unproven—or even nonexistent—products, most startups have to be creative just to get off the ground. But being small has the advantages of high-speed product adaptability and close contact with customers. Having little funding means throwing money at whatever problems arise is not an option. So other creative solutions arise.
“A lot of entrepreneurs go out to try to get affirmation or pushback on something that they believe they know to be true,” Schonthal says. “I have worked for startups where we weren’t even asking the right questions or doing the right research. We never really went through the exercise of asking, ‘what assumption is the whole business hinging on?’”
Failing to answer that core question can lead startups to spend time solving problems that are not really problems at all, as Schonthal came to learn in the course of one of his early ventures, a medical-device company. This company developed a holster for a disposable Yankauer wand, which is used to suction out the respiratory systems of unconscious patients. The wand is important, but it typically had no designated resting place in a care setting. As a result, nurses and doctors tended to store the wand under the patient’s pillow or dangle it off the side of the bed, neither of which is hygienic.
“In the early days, you go out to learn, not to validate.”
Armed with the assumption that the device needed a designated home when it was not in use, Schonthal’s company poured money into sales force–led research to prove the need for the product. But they asked the wrong question—essentially, “wouldn’t it be great if this holster existed?” They realized later that all those nurses and doctors who told them, “sure, it would be great,” were telling the truth. But they were also not ready to incorporate a new habit—putting the wand into the holster after each use—into their rounds. That disconnect between what people say and what they actually do posed a huge problem for the company.
Since people are creatures of habit, asking them to change their behavior can be a huge obstacle, no matter how convincing the data may be. The experience of the Yankauer wand has led Schonthal to be aware of users’ ingrained habits when thinking about innovation, rather than creating devices that require users to adopt new ways of working.
Being convinced of a great idea is crucial to getting a company off the ground. But certainty can also limit flexibility. A startup has to question everything about itself—from the nuances of product development to core existential questions about whether or not the business even solves a worthwhile problem.
It has taken Schonthal years to learn how to incorporate his own blind spots into the way he researches and tests the products he hopes to bring to market. Some of these blind spots have turned out to be fundamental to reasons the products were conceived.
So how does an entrepreneur figure out the right questions to ask? One way is to use the constraint of a small staff as an advantage. Most startups have no choice but to be close to their customers.
“In the early days, you go out to learn, not to validate,” Schonthal says. “Be really honest with yourself: you don’t go out to sell and scale as quickly as you can. Rather, you reduce the size of the experiment to be just big enough to answer some key questions, and do anything you can to get the thing in people’s hands so you can watch how they use it in the wild.” This allows for the kind of authentic feedback that only users can provide.
Observing how people interact with a product may lead to some very important, if painful, realizations: that you misinterpreted who your customer are, how the value proposition resonates with them, or whether they care about your product at all.
One great advantage startups have over established companies stems from the size and funding constraints most startups share. In the absence of the budget it would take to hire an R&D team, the founders themselves spend time in the field gathering information. “When you’re small, everybody’s interfacing with customers every day, talking to them. When you hear feedback from the market, the whole team is hearing the same thing.”
“By the time customer information reaches the innovation department of a large company, it is usually presented as statistically significant survey results,” Schonthal says. “Thousands of people now become one synthesized voice of some artificial customer archetype—‘Meet Joe. Joe is a 35-to-37-year-old urban male who makes $65,000 to $75,000 per year and has 1.5 kids’—these kinds of abstract representations of real people.”
While useful for established companies, that kind of synthesized, humanized data is less valuable to entrepreneurs in early testing than hearing the voices of the individuals who are using the prototype. This feedback has a different value: it can clue the company into the motivations, emotions, and behaviors of the user and may reveal the true utility of the product in question. But knowing how to interpret what you hear—and knowing what questions to ask—can be a tall order no matter how big or established your company.
“If you go right to secondary data and focus groups, you lose that ability to walk into the clinic and see somebody shove the Yankauer wand under the pillow,” Schonthal says. “That kind of information doesn’t typically get translated through spreadsheets, charts, and reports. You have to be there to see it and understand why people are doing what they do. Understanding the ‘why’ needs to be the first step in creating a better ‘what.’”
Benjamin Iverson gets one of two distinctly different reactions when he tells people about his recent research into prize-linked savings (PLS) accounts. The accounts, which are popular overseas, accrue little to no interest. Instead, account holders get entered into jackpot drawings, earning more chances to win as they invest more in the account.
“One reaction is, ‘This is the greatest idea ever! We’re going to help people save,’” says Iverson, an assistant professor of finance at the Kellogg School of Management. “The other reaction is, ‘Are you crazy? We’re going to trick people into gambling instead of saving? That’s a terrible idea.’”
Iverson himself was firmly in the second camp before he began his research. After crunching the numbers, he changed his mind.
“I’ve really come around,” he says.
He was convinced through his research, which shows PLS accounts attract new people into the banking system who do not have other savings accounts. And those account holders increase their savings by more than the average across all types of savings accounts, including standard accounts. Additionally, PLS accounts appear to reduce the number of people who buy lottery tickets.
In other words, PLS accounts offer an attractive alternative to a particularly financially vulnerable population—those with no savings who are one large medical bill or car wreck away from fiscal disaster—while decreasing overall spending on lotteries, where the vast majority of people reap no benefit.
“Can we get people sitting outside the savings system to come in and then move toward more traditional products?”
Iverson is not the only one who has been convinced. In December, President Obama signed into law a bill that makes PLS accounts legal in the U.S. Previously, they had only been allowed in a few states through credit unions, whose pilot programs were quite successful. The new federal law does not override any current state laws that prohibit the accounts, so states can still opt out if they want.
Iverson says he expects to see the accounts become very popular in the U.S., just as they were in South Africa. “There are cultural differences, but in terms of how much we like to gamble, we’re just like everybody else in the world,” he says. “We love to gamble.”
The attractiveness of PLS accounts is tied to the idea of a “poverty trap,” Iverson says. For the impoverished, tiny incremental interest payments are not going to make a dent in their debt. “They need a bigger chunk of money and they’re actually willing to give up the sure thing [of interest] to have a chance at the bigger chunk of money,” he says. “And, if they don’t get it, they’re really not that much worse off.”
There has been virtually no research into PLS accounts, even though they have been around for more than 100 years and are a popular in much of the world. Iverson knows of only a handful of studies that have looked at them.
So, when a professor of his wrote a case about PLS accounts based on the experience of a large South African bank, Iverson was intrigued. After Iverson mentioned his interest, he and his professor, Peter Tufano, who is now at the University of Oxford, and Tufano’s case study coauthor, Shawn Cole at Harvard, looked at the underlying data from the bank in order to study the accounts in more detail.
The data come from First National Bank, one of South Africa’s largest, which started offering PLS accounts in 2005. It was called the “Million-a-Month Account,” because of the million-rand jackpot, and nicknamed MaMa.
One randomly selected MaMa holder each month was awarded the grand prize, which was announced on national television. The bank also gave out a number of smaller prizes monthly.
The bank ended the MaMa program after three years because the country’s supreme court deemed it a violation of the Lottery Act. The program’s abrupt end was unfortunate for the researches, Iverson explained, because they were not able to tell what the saturation point looked like in terms of people losing interest in opening new accounts. The MaMa program was still growing steadily when it was shut down, meaning people’s odds of winning were getting smaller and smaller. Iverson would have liked to see at what point “people would have said, ‘my chance is too small now. I’m going to go into a regular account or I’m going to play the lottery’” or do something else with their money.
Still, one interesting and encouraging statistic emerged because of the program’s termination: when the MaMa accounts closed and the bank converted the accounts into traditional savings accounts, 77 percent of people kept their money in those new, non-PLS accounts.
An analysis of the bank’s data shows a number of clear benefits of the MaMa program in terms of incentivizing savings.
First off, the program was incredibly popular. Though the total amount of money in the PLS accounts was less than what was held in traditional savings accounts, the raw number of PLS accounts eclipsed traditional savings accounts within 18 months.
Among the information the bank supplied was anonymous data about its employees. In analyzing this, the researchers found that employees with no other accounts at the bank were 4.6 percent more likely to open a MaMa account. And those who had borrowed a large amount from the bank were nearly 18 percent more likely to open a MaMa account.
Iverson had expected to find that MaMa accounts were simply cannibalizing money away from traditional savings accounts. But the researchers found no evidence that MaMa account holders took money from their regular accounts to feed money into the MaMa program.
MaMa account holders saved at a faster rate than the average across all savings-account holders at the bank, to the tune of roughly 1 percent of annual income more. This equates to a nearly 40 percent increase in total savings for MaMa account holders. And MaMa account holders who also had traditional savings accounts increased their savings in those traditional accounts as well.
The researchers also found some interesting behavior among the 4,341 MaMa prizewinners.
Those who won prizes both large and small kept substantially more in their MaMa accounts than non-winners, even a full year after they won. For some, their savings increased by more than the amount of their prize.
Iverson believes this can be tied to the excitement of winning—a “self-generating effect” so to speak. Once bitten by the PLS bug, account holders wanted to increase their chances of winning again by keeping more money in their accounts.
It was not just the prizewinners themselves who caught PLS fever. There was a distinct buzz effect for the branches that awarded the million-rand prizes. In the month following a jackpot-winning drawing at a particular branch, that branch would see a nearly 90 percent increase in the growth rate of deposits in MaMa accounts compared with a typical month. And non-MaMa savings accounts got a boost from a local winner, too. There was a 4 percent increase in the balances in traditional accounts in the month after a local winner was announced.
It is not hard to see how this buzz is generated.
“When I get interest from my bank, I don’t go tell you that I got 45 cents,” Iverson says. But he would likely be singing from the rooftops if he won a jackpot prize.
In addition to encouraging more savings, the MaMa program appeared to reduce participation in the lottery. The researchers base this conclusion on the fact that when the national-lottery jackpot was especially large because the jackpot was rolled over from the previous draw, deposits in MaMa accounts slowed. They then picked up again when the jackpot amount fell.
While some of the savings in MaMa accounts likely came from money that was not spent on lottery tickets, Iverson would like to know more about where the rest of it came from. He knows people were not taking money out of other savings accounts. But the funds deposited in prize-linked savings—where there had not been savings before—had to come from somewhere.
“Are they hurting themselves somehow or are they reducing frivolous things?” he wonders.
While the PLS accounts are a great entry into the banking system and can build up an important precautionary savings, they are not a replacement for long-term savings accounts such as a retirement fund. PLS accounts may be a good tool to get non-savers into a bank, but Iverson would like to know whether they can be converted into more traditional savers who would benefit from compound interest.
“Is this a gateway to more long-term savings?” Iverson wants to know. “Can we get people sitting outside the savings system to come in and then move toward more traditional products?”
A big part of this potential transition to traditional savings accounts, including in the U.S. now that PLS accounts are legal, is the question of how much banks encourage customers to move from PLS accounts to more traditional ones that earn interest.
“I don’t see banks having a huge incentive to do that,” Iverson says, given that the PLS structure is cheaper for them than paying interest.
But even without these answers, Iverson, the former PLS skeptic who has never been a gambler himself, would encourage those who play the lottery and lack savings to open a PLS account.
“Even if they stop at this account,” he says, “they’re better off.”
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