Parkinson’s Law in Software Engineering

If you've ever finished a task at the very last minute, despite having more than enough time, you've already experienced Parkinson's Law. It's the idea that "work expands to fill the time available for its completion." Cyril Northcote Parkinson first described the concept in Economist in 1955, and it has since become a well-cited principle in productivity studies.

If you give yourself a week to do a task, you'll take a week. If you give yourself four months, you'll still find a way to make it last four months. And in software engineering, where deadlines, sprints, and priorities shift constantly, this principle shows up everywhere.

How I've Seen It Happen First-Hand

The API

At one company, we started working on an API feature that should have taken two or three weeks (at most). Straightforward stuff, wire up a couple of endpoints, add tests, ship it. Instead, it dragged on for nearly four months. Why? Every week we'd add "one more thing", debating naming conventions, attaching edge-case functionality, or rewriting parts to make it "future proof™." The work didn't get harder; we just let the available time invite more work into the room.

The Feature Flags

Another time, we were tasked with removing a batch of old feature flags. On paper, this was cleanup work. A day or two, maybe a week. But because there wasn't a sharp deadline, it ballooned. We delayed, dependencies shifted, and soon those flags were entangled with new features. What could have been a tidy sweep turned into a gnarly refactor. The longer we waited, the harder it got.

Flaky Tests

At one of my previous companies, flaky tests were a recurring pain point. Initially, they should've been quick to fix, a 30-minute job here, an hour there. But when they got left for "later", suddenly they piled up into a backlog that took a whole week just for categorization. It took months to fix them all and bring the CI back to a stable state. Parkinson's Law doesn't just stretch individual tasks, it compounds when you defer maintenance.

Why Engineers Fall Into the Trap

The more time we think we have, the more we delay starting. By the time the deadline finally feels real, we're scrambling to finish anyway. Sound familiar?

Procrastination Disguised as Preparation

Without pressure, it's easy to tell yourself you're "planning" or "polishing." I've spent afternoons renaming variables and rewriting the code to be more performant and nicer when the real fix was already done an hour earlier.

Overengineering by Default

When there's time, scope expands. A hotfix turns into a refactor. A CRUD API becomes a new framework. Sometimes we call it "doing it right", but often it's Parkinson's Law whispering in the background. This overlaps with the Law of Triviality, where teams spend disproportionate effort on small details while bigger issues wait.

Management Isn't Immune Either

It's not just engineers who fall prey to Parkinson's Law. Managers fall into the same trap when planing sprints, setting timelines, or scheduling meetings. The same rule applies: the more time and space you give, the more things tend to expand and drag out.

Sprints Expand to Fit

If you give a team a two-week sprint, the work will stretch to fill two weeks. Even tasks that could be done in three days get scheduled and discussed until they spill over.

Meetings

If the calendar says 1 hour, the meeting will last 1 hour. I've seen 10-minute discussions dragged out just because the slot was there.

Big Project Deadlines

Give a team a vague "end of quarter" target, and you'll see Parkinson's Law bloom into endless scope creep, extra reviews, and "one last tweak."

Turning Parkinson's Law to Your Advantage

The trick isn't fighting it, it's using it.

Time-boxing

At another company, I've seen how time-boxing can save a messy discovery call. A concise 25-minute agenda forces clarity that an open-ended meeting can never deliver. The same applies to coding: two hours for a spike means you actually spike instead of redesigning the system. Agile teams rely heavily on this principle, framing all work within sprints or fixed blocks (Atlassian on timeboxing).

Artificial Deadlines

When I know a task could balloon, I try to give myself an earlier "fake" deadline. For example, I'll aim to finish a feature by Wednesday, even if the sprint closes Friday. That gap is my buffer for polish, rather than panic.

Smaller Work Units

Breaking a large ticket into smaller ones makes Parkinson's Law work for you. Each unit has a tighter deadline, which keeps the scope from sprawling.

Hackathon Constraints

I've seen hackathons produce working prototypes in 48 hours that would have taken months in a normal sprint. Why? The constraints kill off overthinking. You don't have the luxury to debate naming conventions, you just ship.

The Trade-Offs

Of course, speed isn't always better. Some work needs breathing room. Designing a distributed architecture or building core SDK APIs can't be rushed without long-term pain. The key is knowing when Parkinson's Law is helping you focus, and when it's luring you into cutting corners.

Another common trap: new managers who read about Parkinson's Law sometimes take it too literally. They assume that if shorter deadlines make people more efficient, then unrealistic deadlines must make them even faster. In practice, this backfires. Instead of encouraging focus, it creates a culture of constant firefighting, technical debt, and burnout. Deadlines should constrain scope, not crush the team. The art is in balancing enough pressure to avoid bloat, without crossing into "death march" territory (Asana's guide).

Wrapping Up

Parkinson's Law isn't just a productivity idea, it's a pattern I've seen in every engineering role I've had. Whether it's a sprint's work stretching over multiple sprints, a cleanup task turning into a refactor, or a project ballooning because "we have time," the principle holds: work expands to fill the space you give it.

The good news? With the right constraints, time-boxing, artificial deadlines, smaller tasks, you can flip Parkinson's Law into an advantage. The next time you're estimating a feature or planning a sprint, ask yourself: how much time does this really deserve? You might find that less time gives you better results.