168 Hours a Week: Time Tracking for Developers and Analysts
A business analyst and developer decided to measure their 168-hour week without illusions about overtime. The result: instead of the expected 50+ hours of pure work—32 hours, 16 hours on social media disguised as breaks, and 11 hours on work distractions. A simple tracking method revealed hidden time losses and three key insights for optimizing remote workers' schedules.
Tracking Method: Notes and a Timer Without Extra Software
For the experiment, basic tools were used: phone notes and a system timer. No custom trackers—just recording reality.
Recording Rules
- Switch at the moment of activity change: record the time when starting each new task—from coding to coffee.
- Eight categories:
- Work: coding, reviews, calls, tests.
- Work switches: chats, info searches, off-topic browsing on Stack Overflow.
- Social media/YouTube: irrelevant content.
- Sleep: from falling asleep to waking up.
- Exercise: physical activity.
- Learning: courses, articles on Kotlin/Compose/Python.
- Chores: cooking, cleaning.
- Other: meals, socializing, rest.
- Emotional metric: after blocks >20 min—emoji (🔥 flow, 😐 neutral, 😩 struggle, 🫠 procrastination).
The key: don't adjust behavior under observation. Data from Thursday to Sunday is the most honest, without the Hawthorne effect.
Results: Breakdown of 168 Hours
| Category | Hours | % |
|-----------|------|---|
| Work | 31:50 | 18.9 |
| Switches | 11:15 | 6.7 |
| Social media/YouTube | 16:20 | 9.7 |
| Sleep | 48:10 | 28.7 |
| Exercise | 1:45 | 1.0 |
| Learning | 4:05 | 2.4 |
| Chores | 15:30 | 9.2 |
| Other | 39:05 | 23.3 |
At the laptop—55 hours, but pure work—32. The rest—distractions and gray areas.
Details of Losses
- Switches (11 hr): 3.5 hr messengers, 2.8 hr off-topic searches, 2.2 hr context recovery, 2.4 hr unscheduled chats.
- Social media (16 hr): 8 hr YouTube/Shorts, 4.5 hr Telegram, 3.8 hr browsing. 60%—on weekdays.
- Sleep: 6 hr 52 min/day, +45 min scrolling in bed (on social media).
- Exercise: 1% of the week—two runs.
Insight 1: The Cost of Context Switching
Average 14 switches/day during work hours. Each—3–5 min to return to flow. Example sequence:
10:12 — Work (22 min)
10:34 — Telegram
10:41 — Switch (corporate chat)
10:49 — Work (17 min)
11:06 — YouTube
11:27 — Switch
11:35 — Work (26 min)65 min of pure work out of 109 min. 40%—losses. Total 2+ hr/week on brain reboot.
Insight 2: Blurred Boundaries of Remote Work
"11 hours at the desk" ≠ 11 hours of work. The brain registers presence as effort. In the office, boundaries are clear; at home—everything blends: work at 10 PM, rest at 2 PM. Result: no focus, no recovery.
Insight 3: Emotions as a Productivity Metric
- Blocks 1.5–2.5 hr: 🔥/😐, tasks progress.
- Marathons 3+ hr: 😩/🫠, imitation. Two 4+ hr blocks—low output.
Optimal: 52 min work + 17 min rest (per DeskTime). Emojis reveal value:
- 🔥 on learning > half of "work" blocks.
- 🫠 on 4+ hr "work" = 1.5 hr real.
- Evening scrolling: always 😩—not rest.
What Matters
- 16 hr social media = 2 workdays, steals exercise/learning.
- Switches consume 40% of "work" time.
- Emojis + hours = full picture: how much and how useful.
- 32 hr real work vs 55 hr at PC—typical remote worker illusion.
- Track honestly for a week—see your 168 hours.
The method is scalable for teams: aggregate data by roles, identify common leaks (chats, searches). For senior developers—add task metrics (LOC, PRs).
— Editorial Team
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