Debt Snowball Works Better Than the Math Says, per 5,943 Clients

Of 4,169 people who started a debt settlement program, 43.2% finished it. Among clients still going after a year who had paid down little of the dollar total, completion climbed from roughly 35% to roughly 80% as the fraction of accounts closed rose. The dollars paid barely mattered. That is the finding of David Gal and Blakeley McShane (Journal of Marketing Research, 2012), and it answers the question “where do I start when everything is a mess?” with something the math crowd dislikes: start where you can finish something.

What did Gal and McShane actually measure?

They got records from Freedom Financial Network, a debt settlement company, for a random sample of 5,943 clients who enrolled before 2007. Settling debts there takes three to four years. Their question was narrow. Two clients owe the same total and have settled the same dollar share after a year, but one has closed half her accounts and the other a quarter. Who is likelier to reach zero?

The one with more accounts closed. In logistic regressions on the 2,609 clients active at one year, the share of accounts closed stayed significant, and the dollar share did not once both were in the model. The authors’ reading: “completing discrete subtasks might motivate consumers to persist.”

Why isn’t this just rich clients being organized?

It might partly be. But the firm decided which account to negotiate, not the client, and the monthly payment depended on total debt rather than the number of accounts. The authors say this approximates a natural experiment. Still, it is observational data from a single company, and they caution that the number of accounts people enrolled with may be tangled up with personal traits.

Is the snowball even rational?

No, and the field knows it. Amar and colleagues (2011) ran four experiments with an incentive-compatible debt game. Participants kept paying off small debts first even when larger ones carried higher interest. Their name for it is debt account aversion.

So the snowball is a bet that finishing beats optimizing. Gal and McShane found that the bet shows up in real data.

What does a closed account look like outside of debt?

This part is my extrapolation, not theirs. A life in pieces has account-shaped items: the unanswered insurance letter, the overdue dentist visit, the dead phone plan, the 7 a.m. wake time you keep missing. Each is either closed or open. Another post here argues for fixing the most depleted basic need first. The debt data adds a tiebreaker: among items of similar urgency, take the one you can close this week.

There is a counterweight. The hungry-judge studies are usually read as “do hard things early,” and nothing here says avoid hard things forever. The sequence is a motivational one, small closures first so you are still around for the big one.

Where does a wake-up alarm fit?

A wake time you actually hit is a daily item that is either closed or not by the end of the morning. DontSnooze makes the closing visible to other people: you record a short video within 30 seconds of the alarm, and if you don’t, a random photo from your camera roll goes to your friends. The consequence is real, and the closed account is witnessed. The same logic holds for debt payoff with someone watching.

A cap on open items makes the same idea easier to apply outside debt; a personal Kanban board with a limit of three is one way to set it up.

The practical version is small. Write down your five oldest open items, circle the one that takes under an hour, and close it before Sunday. Then count what is left.