If you are bemoaning the season’s colder weather and darker days, here’s something to cheer you up: You and your staff are probably getting more work done.

While you might think that people are more productive in good weather, just the opposite is true, according to research from Harvard University and the University of North Carolina. On warm, sunny days worker productivity actually decreases because people are distracted by thoughts about what they could be doing if they weren’t coding or doing backups. “On a bad-weather day, people are better at focusing on their work, not because the weather makes them grumpy, but because they have fewer distracting thoughts about what they might otherwise be doing outside,” writes researcher Francesca Gino, an associate professor of business administration at Harvard Business School. “Indeed, cognitive distractions and error rates were greater on nice days than on bad-weather days.”

The research consisted of two separate studies. First, researchers looked at employee productivity field data, associated with processing loan applications, collected from a midsize bank in Tokyo in 2007. Researchers then matched these figures to meteorological data in the city during that period. They found that an increase in rain correlated with a decrease in the time it took for workers to complete their tasks—a one-inch increase in rain was related to a 1.3 percent decrease in worker completion time per transaction. Low visibility and extreme temperatures also matched periods of high worker productivity. On clear, sunny days, however, productivity fell, researchers found.

While a 1.3 percent difference in completion time may not sound like much, it adds up. “With about 100 workers in the operation, a 1.3 percent productivity loss is similar to the organization being short one worker on a given day,” Gino writes. “Based on the average yearly salary of the associate-level employees at this bank and the average frequency of precipitation, this loss could cost this particular operation approximately $18,750 annually. When accumulated over time for the entire bank of nearly 5,000 employees, a 1.3 percent productivity loss could be judged to be a significant revenue loss for the bank: at least $937,500 a year.”

In a separate study, researchers brought in 136 students in February and March—when the weather in Boston is in flux—and encouraged some of them to think about nice-weather activities. “In total, there were four groups of participants: rainy-day participants who were induced to daydream about sunny-day activities; sunny-day participants who were induced to daydream about sunny-day activities; rainy-day control group participants; and sunny-day control group participants,” writes Carmen Nobel in the Harvard Business School blog.

The results? Top performers—those who completed the task the fastest and the most accurately—were the rainy-day control group participants; people who had seen neither the actual sun nor pictures of the sun before doing the task. On the other hand, exposure to the sunny-day photographs significantly decreased the performance of participants who came to the lab on rainy days. But for those who came in on sunny days, the added distraction of the sunny-day photographs had little effect on performance.

There are other nuances to consider. For example, during really bad weather, employees may work at home, which Stanford research has shown makes them more productive. “Home working led to a 13 percent performance increase, of which 9 percent was from working more minutes per shift (fewer breaks and sick days) and 4 percent from more calls per minute (attributed to a quieter and more convenient working environment),” researchers write.

Now that we know weather affects productivity, how should organizations react? Gino offers several recommendations:

  1. Assign more clerical work—tasks that don’t require sustained attention —on sunny days than on rainy days.
  2. Offer productivity feedback to each employee and allow flexible task assignments that could maximize productivity.
  3. Maintain a consistent work output by using the weather forecast as a factor in a staffing model.
  4. Locate operations in places with less preferable weather conditions.

Perhaps we’ve finally discovered the reason for Seattle’s success. 

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