
Imagine this: you’re in a group project.
You built the entire presentation, another person approved it, and the third team member disappeared until the last minute. Yet, everyone got the same grade.
Was that fair? Not really.
But was it common? Oh, absolutely.
Now, translate this scenario to workplaces, research teams, and remote companies involving dozens or thousands of people. Suddenly, understanding who actually contributed to what project isn’t about fairness but about the success of each project and the company. Productivity, accountability, motivation, and compensation are also at stake.
Quantifying individual contributions is such a necessity. And we’re here to explain why that is.
The Visibility Bias
Back in the day, work was simpler. One person had one role and was supposed to make one clear output. They built a thing, wrote the report, and closed the deal. And credit was given where credit was due.
Today is a different story. Most meaningful work happens in teams, often large ones. In science, business, and tech, collaboration is how things get done.
Teamwork makes the dreamwork, right? Yep, that’s what we were taught.
But it also makes it harder to recognize individual effort. Researchers support this claim.
A recent arXiv preprint looked at how people contribute in large teams and found that as groups grow, it becomes harder to see and fairly acknowledge each person’s effort.
The research suggests that recognition often goes to a smaller subset of contributors, even when the work is shared pretty evenly. This pattern is known as visibility bias, where more noticeable or outspoken personas receive disproportionate credit. This kind of visibility gap matters a lot, as it affects motivation, performance reviews, and even long-term career opportunities.
In other words: the bigger the team, the harder it is to answer the question, “Who actually did what?”
The Cost of “Everyone Gets Credit”
When individual contribution isn’t tracked or acknowledged, bad things happen:
- High performers burn out. If top contributors feel their efforts go unnoticed, they stop going the extra mile or simply leave the company. And you lose your top talent.
- Free-riding becomes a thing. When output is measured at the team level, people will feel encouraged to contribute less because, in the end, they’ll all benefit equally.
- Managers rely on recency (or visibility) bias. This means the loudest person in meetings looks like the hardest worker. The premise is pretty simple: because they have charisma and they are so loud, they must be the hardest-working individual on the team. Of course, this is a faulty premise.
- There’s no need for feedback. It’s hard to give someone feedback on improvement if you can’t pinpoint what they actually worked on (or avoided?).
All of these points are here to make one thing clear: when there’s no clear contribution, there’s no accountability.
Now, what do we mean by “clear contribution”?
Well, contribution isn’t always obvious. It’s not just about who wrote the most code, closed the most tickets, or sent the most emails. Contribution can be seen across various aspects, like in planning and strategy, problem-solving, mentorship, coordination, execution and delivery, and creative ideation.
Plus, you can’t always see thinking, research, experimentation, or problem-solving. Just think about it: when marketing, engineering, product, data, and design collaborate, contribution becomes harder to compare or evaluate unless it’s thoughtfully documented (and it never is).
That’s why measuring contribution requires nuance, not just counting tasks.

Contribution Metrics
The only way to quantify individual collaboration is to build fair ways to measure individual impact. And that’s easier said than done.
This study highlights just how tricky it can be to figure out who contributed to what when people work together. The researchers found that combining peer feedback (how teammates rate each other’s contributions) with activity data (like how active someone is in shared workspaces) can give a fairly accurate sense of each person’s effort.
The study also suggests that we shouldn’t rely on a single metric but should blend human judgment with behavioral data.
The more metrics there are, the fairer the evaluation is.
But is that really the way to go? Can you base all metrics of individual contribution on tracking activity and collaboration data?
What if there is a method that doesn’t require your team to rely on personal judgment and evaluate other people’s behaviors?
I’m talking about time tracking.
A Word on Time Tracking
Time tracking is the topic everyone loves to hate.
But the thing is, when used poorly, it feels like an ankle monitor.
Used thoughtfully, it shows you how work actually gets done.
Time tracking can help reveal where effort truly goes, ensure work is shared more evenly, provide clear proof of each person’s contribution, and support teams in planning projects more realistically. But only when it’s not loud or intrusive.
In fact, the best time tracking systems work in the background, automatically logging activity and helping teams understand patterns. They passively capture how time is spent, so your team doesn’t have to constantly start and stop timers.
These tools are designed to give teams a clear picture of how time is spent team-wide. They can show you where work flows smoothly, where it gets stuck, and where workloads are uneven.
For teams, automatic time tracking means they can spot bottlenecks earlier, rethink and adjust responsibilities, and make better decisions about deadlines and resources.
For individuals, it offers a better sense of where their energy goes, so they can prioritize meaningful work over constant busywork.
Perhaps most importantly, automatic tracking supports fairness and transparency. When contributions are backed by accurate data instead of guesswork or he-said-she-said, recognition and credit are based on reality. And when everyone gets the recognition they deserve, you can create a healthier, more collaborative work culture.
Some tools, like Memtime, take this a step further by recording activity in the background and letting users review and categorize their time later. That way, tracking doesn’t interrupt focus or force people to change how they work; it simply creates a log of their time for them to reflect on.
With tools like Memtime, your team doesn’t have to remember what they worked on at the end of the day or week; they already have detailed timelines to guide them. That makes reporting more accurate and way less stressful.
Final Thoughts
When you can clearly see who did what, everything gets simpler.
You know who deserves a shoutout, who might need a hand, and you avoid rewarding the loudest person in the room by accident. That’s how work stays fair, motivating, and fully human.
Disclaimer: This post was provided by a guest contributor. Coherent Market Insights does not endorse any products or services mentioned unless explicitly stated.
