To Achieve Your Goals, Lump and Slice

If you’re having trouble keeping your New Year’s resolutions, you might chalk it up to what MIT Professor Drazen Prelec calls “scale mismatch”—the challenge of achieving a large goal that turns on many small decisions distributed over time. No one trains for a marathon, saves up to buy a home, or completes a dissertation without piecing together contributions from many temporal selves. That includes the today-self who reasons that tomorrow would be a better day for running, saving, or writing—or who doesn’t trust her future selves to see through any project that she begins.

Reconciling immediate preferences (another half-hour of your favorite television show, say) with long-range aspirations (like learning to play the clarinet) is a familiar problem. But it can be approached from a fresh perspective by focusing on two key moves: recognizing the value in assembling right-sized lumps of resources or effort, and engineering the slices necessary to get there.  

Even when it comes to money, that most fungible of resources, lumps matter. Consider, for example, taxpayers who were shocked and angry to receive smaller tax refunds from the IRS last year. Their checks shrank because they had overpaid less during the year—that is, the amounts withheld from their paychecks had more accurately tracked their tax liability. Hanging onto more of one’s own money might seem like a good thing, but that misses the significance of how the money is configured. A refund takes a lumpy form—it’s a big chunk of money all at once—while the unwithheld bits of each paycheck are so fragmented that they can scarcely be detected. Piecing together the same lump of cash from these fragments is difficult, yet a lump sum may be needed to cover an all-at-once outlay, like for a car or a home. Because lumps of cash are hard to put together and hard to do without, we should not be surprised to see people relying on the tax system to solve their cash-assembly problems.  

Reconciling immediate preferences with long-range aspirations is a familiar problem. But it can be approached from a fresh perspective.

A very different example of the same principle is recounted by Abhijit Banerjee and Esther Duflo in their book, Poor Economics. Unfinished houses are prevalent in many developing countries. A home is a lumpy good, similar to a bridge; you need a complete structure to have much of value. Why then would we see so many houses in various states of completion? Banerjee and Duflo found there was a simple explanation: this was how people saved. By investing in home construction piecemeal, people could physically aggregate their funds in a form that resisted raiding or dissipation. The partially built house, like the withholding system, worked as a resource-assembly tool.

Of course, neither the withholding system nor partially built homes are ideal savings vehicles—they tie up resources in cumbersome ways without paying out interest. Yet they illustrate the value of mechanisms that can collect contributions toward lumpy goals. And they demonstrate that behaviors that might seem puzzling at first glance can appear much more comprehensible once we take the value of lumps into account.

Another example can be found in lottery play, which involves making bad bets. Rather than simply writing off this behavior as a symptom of overoptimism or irrationality, some scholars have observed that the lottery offers a chance—if a very remote one—to turn fragments of money that are nearly meaningless on their own into a large lump sum that could have a transformative effect on one’s life. In other words, lottery tickets offer a way to pursue a lumpy goal that cannot be obtained in any other way—a risk-taking variation on the cash-assembly benefits of tax refunds.

If lumps are so valuable, how do we put them together? A first step is to see that our lump-assembly problems—whether we are talking about putting together resources, effort, or exertions of willpower—are also tricky burden-division problems. Splitting up goals into smaller pieces allows more of our temporal selves to pitch in, but it also makes each contribution seem less essential and easier to skip. The problem is one of optimal granularity—ideally, each contribution would be crucial yet manageable. In short, to get the lumps we want, we must do some artful slicing.

If lumps are so valuable, how do we put them together?

The increments into which resources or choices are divided can make a difference. For example, physically partitioning or splitting up tempting foods (such as making smaller cookies) can help limit consumption. Division works because it constructs new stopping points. But reducing portion sizes is not the only way to encourage better choices. In fact, some consumers might actually do better if small or intermediate sizes were taken off the table. Ted O’Donoghue and Matthew Rabin posit a variation on this theme: very expensive smoking licenses that would entitle the holder to a large allotment of tax-free cigarettes. Because the up-front cost would only make sense for those planning to pursue a serious smoking habit, would-be dabblers would never start smoking at all—possibly side-stepping an unwanted addiction. Less momentously, consider the person who mildly craves a candy bar but upon finding that only oversized “movie theater” versions are available, decides against buying one; it’s more candy and more money than she had in mind.

Because not everyone will react the same way to a particular choice set, we might enable people to personalize the menus they will confront—and pre-commit to them. For example, restaurants or coffee shops might win loyalty among consumption-conscious customers by devising apps that let people create customized menus—and perhaps even self-select restrictions on revising that menu (e.g., foregone discounts) to make those elections stickier.     

The power of slicing and segmentation also surfaces in the realm of personal finance. Dilip Soman and Amar Cheema found that dividing earmarked savings into two envelopes rather than one increased savings among one population of low-income workers. Households with high savings targets were quite likely to break open one envelope, but doing so did not derail their savings plans altogether; the separate second envelope offered a way to arrest the slide. To aggregate savings, then, one might do well to start with division. 

The problem is one of optimal granularity—ideally, each contribution would be crucial yet manageable. In short, to get the lumps we want, we must do some artful slicing.

Another tactic involves limiting financial commitments that cannot be resized as circumstances change. A mortgage is inflexibly lumpy—once you’ve bought a house, there’s no simple way to make that house ten or twenty percent less expensive. Of course, you might use a platform like Airbnb to parcel out part of your living space. But that’s an involved and often unsuitable alternative. By contrast, a family can trim back on meals out or entertainment expenses without consulting or contracting with anyone. Reducing the lumps in one’s budget (and, counterintuitively, allocating more funds to discretionary categories), is a simple and powerful way to increase financial resilience

Well-designed policies might transform our preferences for lumpy earnings into better financial outcomes as well. Consider, for example, prize-linked savings accounts—bank accounts that offer savers returns on their deposits in a form that many may find more attractive than traditional interest payments: lottery chances at larger lump sums. Even those who lose this lottery still win—by saving.

What all of these examples have in common is a powerful but easily overlooked fact about human choice: configuration matters. Behavior is remarkably sensitive to how resources, tasks, or choices are divided up or bundled together—an observation that can be leveraged into better policies. Finding ways to help people assemble useful lumps and carve out tailored slices represents a promising and largely untapped avenue for policy innovation and an important research direction for behavioral economics.