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Spot Productivity Outliers Through Process Improvements

Learn how executives can spot productivity outliers, hidden high performers and quietly disengaging employees, using workforce data instead of guesswork.

Sarah Altemus

By Sarah Altemus

Spot Productivity Outliers Through Process Improvements
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Every team has outliers. Some are quiet high performers carrying more than their title suggests. Others have mentally checked out while still logging hours.

Executives who rely on manager judgment or an annual survey to find either group are usually months behind. The only reliable way to catch both is behavioral work data, not self-reporting.

What is a productivity outlier?

A productivity outlier is an employee whose behavioral data sits meaningfully outside the norm for their team. The outlier can be a hidden top performer or an early flight risk. Output metrics alone tend to miss both.

Most performance reviews measure results, such as deals closed, tickets resolved and projects shipped. Outliers reveal themselves in the patterns underneath those results, like focus time, session length and collaboration load. Two employees can hit identical results while one is burning out and the other is coasting.

Why outliers hide in plain sight

Most performance tools look for extremes in output, not in behavior. That leaves a wide blind spot for anyone whose daily patterns tell a different story than their deliverables do.

Behavioral analysis also catches shifts earlier than people-based methods do. Research on communication patterns among high performers has found that behavioral signals can flag departure risk many weeks before a resignation, well ahead of what engagement surveys typically pick up.

The quiet high performer

This employee delivers consistently without drawing attention to it. They rarely dominate meetings, and a manager may undervalue them next to louder colleagues who advocate for their own work. Traditional competency models often reward visibility over results, which is exactly why this group stays invisible.

The disengaged employee

This employee still meets the bare minimum of the job description while withdrawing discretionary effort. Gallup’s global engagement research found that engagement has hit an all-time low. The warning signs show up in behavior long before a performance review.

Quiet high performer vs. disengaging employee: How the data differs

Behavioral signal Quiet high performer Disengaging employee
Focus session length Longer and steady Shrinking or erratic
Collaboration load Selective, high-value Withdrawing or avoidant
Daily consistency Predictable patterns Increasingly inconsistent
Visibility in meetings Low, doesn’t grandstand Present but not contributing

The data points that reveal outliers

Three categories of behavioral work data consistently separate outliers from the rest of a team: focus patterns, collaboration load and timing consistency. Each one flags a different type of outlier, so they’re most useful viewed together rather than one at a time.

Focus and session patterns

ActivTrak’s 2026 State of the Workplace report revealed that focus efficiency significantly decreased by 60% across industries – the average focus time is only 13 minutes 7 seconds. An employee whose focus sessions run well above or below that baseline is behaving differently than their peers, for better or worse.

Collaboration and multitasking load

Collaboration time rose 34% industry-wide, according to ActivTrak’s State of the Workplace report, and now consumes roughly 13% of the average workday. An outlier here might be someone drowning in meetings with no time left to execute, or someone who has quietly disappeared from collaborative work altogether.

Location matters, too. The report found remote-first employees log the most collaboration time of any group but the lowest focus efficiency, a reminder that more connection doesn’t automatically mean more depth. Comparing collaboration load against focus data, rather than looking at either alone, gives a fuller picture of what’s actually happening.

Work timing and consistency

Consistent start times and steady daily patterns tend to track with healthy utilization. Erratic timing, a sudden drop in productive hours or an unexplained spike in weekend activity can all signal a shift worth a closer look.

Interruptions compound the problem. Deloitte research names interruptions as the top productivity barrier across every workforce segment, which makes an employee’s ability to protect uninterrupted time a meaningful signal on its own, separate from how many hours they log.

How to spot outliers without guesswork

Guesswork rewards whoever is most visible, which skews toward extroverts and squeaky wheels. A distribution-based view removes that bias by comparing every employee against the same behavioral baseline, rather than a manager’s impression of who’s working hardest.

Work intelligence platforms surface these patterns automatically, flagging employees whose data sits meaningfully outside the norm. That gives leaders a starting point for a conversation, not a verdict.

What to do once you’ve found outliers

A flagged outlier isn’t an automatic red flag or reward. Use the data to initiate discussions; Open and honest communication helps you uncover the ‘whys’ behind the raw numbers. 

For a hidden high performer, that might mean a stretch assignment, a public thank-you or a closer look at promotion readiness. For a disengaging employee, it might mean a workload check-in before performance slips further. Performance management tools help managers act on the signal instead of guessing at the cause.

Turning outlier data into action

Spotting outliers only pays off if leaders build a habit of reviewing the data on a regular cadence, not just once a year during review season.

Dashboards that surface focus, collaboration and utilization trends give executives a repeatable way to catch shifts early. ActivTrak’s 2026 State of the Workplace report found disengagement risk grew 23% in a single year, the kind of trend that’s easy to miss without ongoing visibility.

Assessing data and metrics to uncover productivity outliers early gives you the information you need to initiate conversations and take steps to address the issues for impactful and strategic process improvements.

See which of your productivity outliers are quietly disengaging, and who deserves recognition. Request a demo of ActivTrak’s work intelligence platform.

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Meet the author

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Sarah Altemus
Manager, Productivity Lab
Sarah Altemus is Productivity Lab Manager at ActivTrak, where she contributes to the company’s research and advisory efforts focused on work intelligence in the AI era. Working with one of the world’s largest datasets on how work actually happens, she partners w... Read more
Sarah Altemus is Productivity Lab Manager at ActivTrak, where she contributes to the company’s research and advisory efforts focused on work intelligence in the AI era. Working with one of the world’s largest datasets on how work actually happens, she partners with global enterprises to benchmark performance, apply best practices and translate behavioral data into measurable improvements in productivity, workforce effectiveness and organizational design.

Sarah brings a decade of experience advising organizations through complex, large-scale transformations where workplace strategy, culture and business operations must evolve simultaneously. Her work spans global enterprises including Expedia Group, ExxonMobil and Wizards of the Coast, where she shaped the human-centered strategies required to sustain performance through periods of significant disruption — including headquarters relocations, mergers, operating model shifts and digital transformation.

At Expedia Group, Sarah directed change management for the relocation of 5,000 employees to a new headquarters, developing enterprise-wide readiness programs, behavioral research initiatives and cross-functional alignment strategies. When COVID-19 emerged during the transition, she supported the company’s pandemic response, enabling a rapid and coordinated shift to remote work at scale. At ExxonMobil, she supported leadership through the organizational and cultural complexities of one of the largest corporate headquarters projects in the world, alongside a concurrent merger integration.

Earlier in her career, Sarah advised enterprise organizations including Amazon, Nordstrom and Philips Healthcare on workplace strategy and new ways of working, applying human-centered research and design thinking to align employee experience with business performance. She also served as a researcher at APQC (the American Productivity and Quality Center), where she developed expertise in benchmarking, process improvement and organizational effectiveness.

At ActivTrak, she focuses on helping organizations operationalize work intelligence — enabling leaders to embed data-driven ways of working and drive adoption at scale. Her work emphasizes that sustainable performance gains require not just new technology, but a fundamental redesign of how work happens, supported by continuous measurement and organizational accountability.

Sarah’s areas of expertise include organizational design, workforce analytics, return-to-office strategy, employee listening at scale and change management in the context of AI and productivity technologies.
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