I Tracked My Tasks for 30 Days. Here's What I Learned About My Own Productivity.

I've been freelancing for six years, and I thought I had a pretty good handle on my productivity. I work from home, manage my own schedule, and consistently hit deadlines. By most measures, I'm doing fine.

But I had this nagging feeling that I wasn't being honest with myself. How much of my day was actually productive? How accurate were my time estimates? What was I avoiding?

So I ran an experiment: for 30 days, I tracked every single task I worked on, how long it actually took, and how I felt while doing it. Not for a client or a boss—just for me.

The Setup

I created a personal Gryphin board with columns for each stage of my work: To Do, In Progress, Review, Done, and one I added called "Avoiding."

Every morning, I'd add my planned tasks. Throughout the day, I'd move them and log actual time spent.

I also rated my energy level (1-5) and focus quality (1-5) for each work session. Seemed like overkill at first, but this data turned out to be the most valuable part.

Week 1: The Delusion Phase

The first week was humbling. My self-image as a productive person took some hits.

The pattern in the "Avoiding" column was interesting: mostly tasks that required reaching out to people (sending proposals, asking for feedback, scheduling calls) or tasks with unclear next steps. The coding work? That moved smoothly. The human stuff? Stuck.

Week 2: The Patterns Emerge

By week two, the data started telling stories.

Pattern #1: Energy follows a predictable curve

My energy ratings weren't random. They followed a consistent daily pattern:

This seems obvious in retrospect, but I'd been fighting it for years—scheduling important meetings at 2pm, trying to start deep work at 9am.

Pattern #2: Task switching is expensive

Every time I switched between tasks, the next task took about 15 minutes longer than it should have. This was consistent. I was bleeding time every time I bounced between a coding task, an email, and back to code.

Pattern #3: Estimation accuracy varies by type

Week 3: The Experiments

Armed with data, I started making changes.

Experiment 1: Batch the human stuff

Instead of letting emails and outreach tasks sit in "Avoiding," I scheduled a daily 30-minute block specifically for "people tasks." Having a container for them made them less daunting.

Result: My "Avoiding" column dropped by about 60%.

Experiment 2: Protect the peak hours

I blocked 10am-12pm as "deep work" time—no meetings, no email, phone on DND. This felt indulgent at first, but my output in those two hours often exceeded the rest of the day combined.

Experiment 3: Pad estimates by type

I started using different multipliers:

• Familiar tasks: 1.3x buffer
• Unknown tasks: 2.5x buffer
• Creative tasks: Marked as "variable" with no hard deadline unless necessary

Week 4: The Unexpected Insights

The final week brought some surprises.

What Stuck (6 Months Later)

I didn't keep tracking everything at this level of detail—that would be exhausting. But some habits stuck:

• I still maintain a personal kanban board, just less granularly
• Deep work blocks are non-negotiable
• I batch communication tasks instead of doing them ad-hoc
• My estimates are genuinely better now because I have reference data
• I stopped trying to be productive outside my actual productive hours

That last one is maybe the biggest shift. I used to feel guilty about the 2pm slump or the 6pm fadeout. Now I just accept them. I'm not a productivity machine—I'm a person with energy cycles.

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Should You Try This?

Maybe. It's not for everyone. The first two weeks are uncomfortable because you're confronting the gap between how you think you work and how you actually work. Some people would rather not know.

Just be prepared: the data doesn't always tell the story you want to hear. Sometimes it tells you the story you need to hear.