The beginning of the year is often a time for fresh starts. It marks a new period — a distinct point between the past and the future — which motivates people to set new goals. But what if you were already doing pretty well? Would a fresh start still be motivating? Or might it actually set you back? In the context of work performance, new research finds that a fresh start (a “performance reset”) can affect people’s motivation and future performance differently, depending on their past performance. Those with lower performance became more motivated and improved after their performance was reset, while stronger performers found resets demotivating. Why does this happen? The research suggests that resets influence people’s self-efficacy, or their belief in their ability to perform well.

Photography by Jacqueline Foss/Flickr/Getty Images

The beginning of the year is often a time for fresh starts. It marks a new period — a distinct point between the past and the future — which motivates people to set new goals and strive for self-improvement.

But what if you were already doing pretty well? Would a fresh start still be motivating? Or might it actually set you back?

I explored these questions in the context of work performance. Across one field study and three laboratory experiments, I found that a fresh start on people’s performance records — what I call a “performance reset” — affected their motivation and future performance differently, depending on their past performance. Those with lower performance became more motivated and improved after their performance was reset, while stronger performers found resets demotivating.

What happens when performance is reset?

Performance resets — when employees’ performance records get wiped clean, their past performance decoupled from their future performance — are common in organizations. For example, performance on a specific metric (e.g., sales tallies, billable hours) or on a general evaluation can be reset to zero at the beginning of a calendar cycle, when a new manager takes over, or when you start a new job. In an online survey I conducted of 572 full-time employees from a variety of occupations, 40% indicated that they’d experienced their performance being reset at least once in their job.

To investigate whether performance resets affect subsequent motivation and performance, I first conducted a field study using archival data from a high-stakes setting, one where individuals’ performance is occasionally reset and is relatively independent of their teammates: Major League Baseball (MLB).

The MLB consists of two comparable leagues: the American League and the National League. During the regular season, players can be traded to teams within the same league or across leagues. Their season-to-date statistics are reset if they are traded across leagues — they get a clean slate in their new league — but if they’re traded to a team in the same league, their statistics will be continuously tracked from before the trade. I used across-league trades as the “treatment” that induced performance resets, and within-league trades as the “control” without resets.

To measure effects, I focused on players’ batting performance, obtaining 40 years of data (1975-2014) from Retrosheet to track what happened each time a batter was at bat. Using 269,623 observations of “at bats,” involving 701 regular-season trades, I found that being traded across leagues had a bigger effect on players’ performance than being traded within a league; but whether this effect was positive or negative depended on the players’ performance prior to being traded.

When players’ pre-trade batting averages were relatively low (e.g., one standard deviation below their league average), a performance reset was associated with a subsequent increase in hit probability, as compared to players who did not experience a reset. However, when players’ pre-trade batting averages were relatively high (e.g., one standard deviation above their league average), a performance reset was associated with a subsequent decrease in their hit probability, relative to no resets.

Even though I carefully controlled for numerous factors that might influence players’ batting performance (e.g., the number of times a batter encountered the same pitcher, team performance) and conducted additional analyses to address alternative explanations, this study didn’t establish that performance resets caused changes in motivation. To do this, I conducted a laboratory experiment with 202 MTurk participants, asking them to work on a word-search game.

Participants were told they would be paid based on the total number of correct words they submitted across 10 trials of the game. They saw their performance tracked on a graph, so after each trial, they could see the number of correct words they submitted. After five trials, half of the participants were randomly assigned to experience a reset and see a clean graph, without their performance on the first five games, whereas the other half continued to see all of their performance tracked. Consistent with what I found with the MLB players, the reset affected people’s performance based on their past — participants with weak performance in the first five trials did better if they experienced a reset than if they did not, whereas those with strong early performance did worse if they experienced a reset than if they did not.

Why do performance resets affect us?

I propose that one underlying mechanism is self-efficacy — a person’s belief in her ability to perform well in a task, and a strong, positive driver of motivation. By mentally breaking with the past, resets may lead people to perceive their past performance as less indicative of their future capabilities. As a result, resets may make people feel less tarnished by past failures and thus more confident about their future than they would otherwise; and resets may reduce people’s tendency to base their self-efficacy on their past successes and thus make them feel less confident than they would otherwise.

To examine the role of self-efficacy, I conducted another laboratory experiment, in which I introduced a reset and manipulated people’s perceptions of their past performance. I recruited 408 participants from MTurk to complete 24 trials of a task: unscramble letters to form English words. They had the opportunity to receive a bonus based on the total number of correct words they generated overall. Participants saw a graph showing whether or not they met “researchers’ expectations” on each trial. During the first 12 trials, half of participants were told that they met expectations on 10 trials, whereas the other half were told that they met expectations on only 4 trials.

After 12 trials, I introduced a reset: some participants learned they would proceed with a clean graph, whereas others were told their performance would continue to be tracked on the same graph. At this point, I measured participants’ self-efficacy (or how confident they were that they could perform well in the next 12 trials) and gave them an opportunity to switch to a different task. Their choice was my behavioral measure of motivation — continuing with the word task indicated greater motivation than switching to a different task.

Here’s what I found: When participants were led to view their early performance as weak, the reset treatment increased their self-efficacy and boosted their motivation to continue the word task; but when participants were led to view their past performance as strong, the reset treatment decreased their self-efficacy and decreased their motivation to continue. We replicated these results in another experiment.

My research suggests that while fresh starts are often thought to be motivating, they can be a double-edged sword. When given a chance to put past performance failures behind them, employees may be able to become more motivated and perform better in the future. However, for employees with recent strong performance, resets can be demotivating and costly, even if the decrease in motivation takes subtle forms, such as switching projects.

More work is needed to further understand how this plays at work. One limitation of this current research is that it focused on unanticipated performance resets — most baseball players do not know whether and when they will be traded, and participants in my experiments were unaware of the performance resets. In theory I expect my findings to extend beyond unanticipated resets, but in practice, how anticipated and recurrent resets affect motivation remain open questions.

In the era of big data, managers can use all kinds of performance-tracking software to monitor employees and deliver feedback. By recognizing that a “fresh start” does not affect people equally, managers may be more equipped to leverage resets as a motivational tool. The opportunity to reset performance numbers may help employees psychologically cope with unsatisfactory performance. Managers may also enhance the benefits of resets by communicating their belief in employees’ ability to turn around after a fresh start. On the other hand, managers should consider communicating positive expectations to and instilling confidence in top performers when a reset occurs.