Personal productivity: what actually works, according to research

How to read a productivity study

Productivity advice is full of “studies show”. Before rating techniques, here are three questions worth asking of any claim.

What kind of study is it? A meta-analysis of randomized trials (where chance decides who uses the technique) beats a single trial, which beats a correlation. If organized people earn more, that doesn’t prove organization causes the income. Both could come from something else.

What was measured? Many studies ask people whether they feel more focused or less stressed. That matters, but it isn’t the same as measuring output. We flag it each time.

How big is the effect? Researchers often report Cohen’s d. By Jacob Cohen’s rule of thumb, 0.2 is small, 0.5 medium and 0.8 large. A technique that “works” with d = 0.2 helps a little. It won’t remake your week.

The scorecard: techniques rated by strength of evidence

Rows already covered in depth on this blog link to their guide. The rest of this page covers evidence we haven’t written about yet.

Setting goals: a real effect, but a modest one

In 2017, Tracy Epton, Sinead Currie and Christopher Armitage at the University of Manchester pulled together randomized trials that isolate the effect of setting a goal, and nothing else. Their meta-analysis covers 141 papers, 384 effect sizes and 16,523 participants, across areas such as health, sport and study.

The result was an effect the authors describe as small but positive: d = 0.34. Goals worked better when they were:

• difficult rather than easy;
• set publicly;
• shared by a group.

So “make progress on my dissertation” is a wish. “Write 1,500 words by Friday and tell my advisor I will” is a goal in the sense these studies test. It gets stronger when paired with a concrete plan and progress tracking, which our guide on how to stop procrastinating covers.

Sleep: the most underrated productivity tool

Productivity listicles rarely mention sleep, yet it’s one of the areas with the clearest experimental evidence.

In a 2010 meta-analysis in Psychological Bulletin, Julian Lim and David Dinges pooled 70 articles and 147 cognitive tests run after less than 48 hours without sleep. The biggest hit was to simple attention: lapses rose sharply (g = −0.78, a large effect). Reasoning accuracy barely moved (g = −0.13, not significant). Tiredness first erodes vigilance, the ability to stay on a task without drifting off.

Partial sleep loss is sneakier. Hans Van Dongen and colleagues (2003) studied 48 adults aged 21 to 38 in a sleep lab. In one of two experiments, people were randomly assigned to 4, 6 or 8 hours in bed a night for 14 days; in the other, they went three nights without sleep. At 6 hours or less, performance slid day after day, reaching deficits equal to up to two nights of total sleep deprivation. Meanwhile, participants felt only slightly sleepier. They largely didn’t notice their own decline.

For wind-down habits that help, see our evening routine guide. The point here is simpler: guarding your sleep is part of being productive.

Long hours: more time, diminishing returns

Stanford economist John Pencavel reanalyzed British data from 1916 on munitions workers, most of them women, collected for a government committee on workers’ health. The data are useful because hours varied widely: from 24 to 72.5 a week in one of the datasets.

What he found:

• below roughly 49 hours a week, output rose in step with hours;
• above that, each extra hour added less, with output peaking at around 63 hours;
• output at 70 hours differed little from output at 56;
• holding weekly hours constant, weeks with no day of rest produced about 10% less.

The limits are obvious: factory work, more than a century ago, with no random assignment. But the mechanism, fatigue piling up, matches the sleep studies.

The most recent large test is the four-day-week trial published in Nature Human Behaviour in 2025 by Wen Fan, Juliet Schor and colleagues at Boston College. It followed 2,896 employees at 141 organizations in the US, UK, Canada, Ireland, Australia and New Zealand for six months, with no pay cut. Burnout, job satisfaction, and mental and physical health all improved, a pattern not seen in 12 comparison companies. The more an individual cut their own hours, the bigger the gain, which the authors trace to better self-rated work ability, less fatigue and fewer sleep problems.

Two caveats: the companies volunteered (no random assignment), and the outcomes are self-reported. The paper measures well-being, not output.

Your phone: what holds up and what doesn’t

What holds up: batching notifications. Nicholas Fitz, Kostadin Kushlev, Dan Ariely and colleagues randomly assigned 237 smartphone users in India to one of four setups for two weeks, using an app that controlled when notifications arrived: as usual, batched three times a day, batched every hour, or never.

• Three times a day: less inattention (d = −0.65), better concentration (d = 0.54), more sense of control over the phone, lower stress.
• Every hour: little difference from the control group.
• No notifications at all: few benefits, and more anxiety and fear of missing out.

Even the three-times-a-day group reported more fear of missing notifications (d = 0.68). Outcomes came from nightly self-reports, over just two weeks. The result points the same way as the email study summarized in our time blocking guide.

What doesn’t hold up well: “brain drain”. In 2017, Adrian Ward and colleagues at the University of Texas at Austin reported two experiments with nearly 800 people in total: those whose phones were in another room did better on working memory and fluid intelligence tests than those whose phones sat on the desk. The finding went viral.

Then came the checks. In 2022, Ana Ruiz Pardo and John Paul Minda at Western University in Canada ran a pre-registered direct replication of the second experiment: phone location made no difference. A 2023 meta-analysis (Böttger and colleagues, 22 studies) found a small negative effect, mainly on memory (g = −0.23). A 2024 meta-analysis by Andree Hartanto and colleagues, covering 33 studies, found an effect close to zero (d = −0.02) that wasn’t statistically significant.

The practical advice still stands: putting the phone out of reach makes it less tempting to pick up, a situation strategy covered in how to be disciplined. What’s shaky is the idea that its mere presence makes you less smart.

Multitasking: the people who do it most are worst at it

Switching tasks costs time; our time management tips cover that. The question here is different: does doing a lot of multitasking train you to be good at it?

In 2009, Eyal Ophir, Clifford Nass and Anthony Wagner at Stanford surveyed 262 students, then compared small groups of heavy and light media multitaskers (for example, 19 against 22). Heavy multitaskers were more easily distracted by irrelevant information and, surprisingly, worse at switching tasks.

The finding has been contested. In 2017, Wisnu Wiradhany and Mark Nieuwenstein ran two replications with 14 tests; only 5 went in the expected direction. Their meta-analysis of 39 effect sizes found a weak link that became non-significant after correcting for small-study bias. A 2018 review by Melina Uncapher and Anthony Wagner concluded that, on balance, heavy media multitaskers perform worse in several areas, that many studies find no difference, and that the direction of cause and effect is unknown.

A separate study explains part of the puzzle. David Sanbonmatsu and colleagues at the University of Utah tested 310 undergraduates in 2013. Those who multitasked most tended to have lower working memory scores, yet 193 of the 277 people tested rated their multitasking as above average, and those ratings didn’t track their real ability. It’s correlational, but it suggests people juggle tasks because they struggle to tune out distractions, not because they’re good at it.

Myths worth dropping

The Yale study of written goals. The story says 3% of Yale’s class of 1953 had written goals, and twenty years later they were worth more than the other 97% combined. In 1996, journalist Lawrence Tabak traced it for Fast Company: the class secretary had never taken part in any goals survey, and a Yale research associate who searched the alumni archives found no evidence it ever took place. The real data on goals are Epton’s, above: a genuine effect, much smaller than the legend.

Willpower as a fuel tank. Two large multi-lab replications failed to find the effect. See how to be disciplined.

5 a.m. wake-ups, the 52/17 rule, “eat the frog”. As far as we know, none has been tested in a controlled trial. They may suit some people; they aren’t research findings. For whether your best hours are really in the morning, see our daily planner guide.

Putting the evidence to work with Binome360

Three findings here turn into simple settings: a specific goal with a set time, messages handled in batches, and protected sleep.

To batch messages, give them two fixed slots. Other apps’ notifications are managed in your phone’s settings (on iPhone, Scheduled Summary delivers them at set times). A reminder tells you when to open your inbox.

For sleep, the easiest route is to make it a tracked habit with a check-in each evening.

For the goal itself, give it a time: “Remind me Thursday at 9 am to write the 1,500 words for chapter 2.” The reminder is drafted from one sentence, and nothing is saved until you confirm.

Frequently asked questions

What is the most effective productivity technique according to science?

No single technique wins. The best-supported effects come from if–then plans (d = 0.65 in Gollwitzer and Sheeran’s meta-analysis), progress tracking and specific goals. Enough sleep is the condition that makes all of them work.

Is working more than 50 hours a week counterproductive?

In Pencavel’s data on 1916 munitions workers, hours beyond about 49 added less and less, and 70 hours produced barely more than 56. That was physical work in another century. No study sets a precise cutoff for knowledge work, but the same mechanism, fatigue, applies.

Should I turn off all notifications?

Not necessarily. In the trial by Fitz and colleagues, removing notifications altogether mainly raised anxiety. Batching them three times a day gave the best self-reported results. Silence them during focus blocks and check at set times.

Can you train yourself to multitask?

The evidence doesn’t show it. People who multitask most aren’t better at it and often overrate themselves. Most studies are correlational, so it’s unclear whether multitasking harms attention or whether more distractible people multitask more.

In short

The solid evidence on productivity fits on an index card: a specific goal, a plan with a time attached, progress tracking and enough sleep. Extra hours, multitasking and viral tricks pay off less than they promise. First step: pick this week’s top goal and give it a day and a time.

Sources

• Tracy Epton, Sinead Currie and Christopher J. Armitage, “Unique effects of setting goals on behavior change: Systematic review and meta-analysis”, Journal of Consulting and Clinical Psychology, 85(12), 1182–1198, 2017: doi.org/10.1037/ccp0000260.
• John Pencavel, “The Productivity of Working Hours”, The Economic Journal, 125(589), 2052–2076, 2015: doi.org/10.1111/ecoj.12166; working paper version, IZA DP No. 8129, 2014: iza.org.
• Wen Fan, Juliet B. Schor, Orla Kelly and Guolin Gu, “Work time reduction via a 4-day workweek finds improvements in workers’ well-being”, Nature Human Behaviour, 9(10), 2153–2168, 2025: doi.org/10.1038/s41562-025-02259-6.
• Julian Lim and David F. Dinges, “A meta-analysis of the impact of short-term sleep deprivation on cognitive variables”, Psychological Bulletin, 136(3), 375–389, 2010: doi.org/10.1037/a0018883.
• Hans P. A. Van Dongen, Greg Maislin, Janet M. Mullington and David F. Dinges, “The cumulative cost of additional wakefulness”, Sleep, 26(2), 117–126, 2003: doi.org/10.1093/sleep/26.2.117.
• Nicholas Fitz, Kostadin Kushlev, Ranjan Jagannathan, Terrel Lewis, Devang Paliwal and Dan Ariely, “Batching smartphone notifications can improve well-being”, Computers in Human Behavior, 101, 84–94, 2019: doi.org/10.1016/j.chb.2019.07.016.
• Adrian F. Ward, Kristen Duke, Ayelet Gneezy and Maarten W. Bos, “Brain Drain: The Mere Presence of One’s Own Smartphone Reduces Available Cognitive Capacity”, Journal of the Association for Consumer Research, 2(2), 140–154, 2017: doi.org/10.1086/691462; University of Texas at Austin news release via ScienceDaily, 23 June 2017: sciencedaily.com.
• Ana C. Ruiz Pardo and John Paul Minda, “Reexamining the ‘brain drain’ effect: A replication of Ward et al. (2017)”, Acta Psychologica, 230, 103717, 2022: doi.org/10.1016/j.actpsy.2022.103717.
• Tobias Böttger, Michael Poschik and Klaus Zierer, “Does the Brain Drain Effect Really Exist? A Meta-Analysis”, Behavioral Sciences, 13(9), 751, 2023: doi.org/10.3390/bs13090751.
• Andree Hartanto et al., “The effect of mere presence of smartphone on cognitive functions: A four-level meta-analysis”, Technology, Mind, and Behavior, 5(1), 2024: doi.org/10.1037/tmb0000123.
• Eyal Ophir, Clifford Nass and Anthony D. Wagner, “Cognitive control in media multitaskers”, PNAS, 106(37), 15583–15587, 2009: doi.org/10.1073/pnas.0903620106.
• Wisnu Wiradhany and Mark R. Nieuwenstein, “Cognitive control in media multitaskers: Two replication studies and a meta-analysis”, Attention, Perception, & Psychophysics, 79, 2620–2641, 2017: doi.org/10.3758/s13414-017-1408-4.
• Melina R. Uncapher and Anthony D. Wagner, “Minds and brains of media multitaskers: Current findings and future directions”, PNAS, 115(40), 9889–9896, 2018: doi.org/10.1073/pnas.1611612115.
• David M. Sanbonmatsu, David L. Strayer, Nathan Medeiros-Ward and Jason M. Watson, “Who multi-tasks and why?”, PLOS ONE, 8(1), e54402, 2013: doi.org/10.1371/journal.pone.0054402.
• Lawrence Tabak, “If Your Goal Is Success, Don’t Consult These Gurus”, Fast Company, December 1996/January 1997: fastcompany.com.
• Peter M. Gollwitzer and Paschal Sheeran, “Implementation intentions and goal achievement: A meta-analysis of effects and processes”, Advances in Experimental Social Psychology, 38, 2006.
• Benjamin Harkin et al., “Does monitoring goal progress promote goal attainment?”, Psychological Bulletin, 142(2), 2016.
• Jacob Cohen, Statistical Power Analysis for the Behavioral Sciences, 2nd edition, Lawrence Erlbaum, 1988 (the 0.2 / 0.5 / 0.8 benchmarks).
• Apple Support, “Change notification settings on iPhone” (Scheduled Summary): support.apple.com.

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