Most productivity advice is presented as established fact when it is actually untested personal preference. Someone tries a system, it works for them, and they write about it as though it will work for everyone. The to-do list vs done list debate is a prime example: advocates on each side present compelling arguments, cite psychology research, and claim superiority – but rarely subject their preferred system to any structured comparison.
This article documents a 30-day experiment designed to do exactly that. The structure borrows from single-subject research design (commonly used in behavioral psychology and clinical practice), adapted for practical productivity measurement rather than academic rigor. The intent is not to prove which system is “better” in universal terms but to observe how each system affects specific, measurable aspects of daily work.
The Hypothesis
Based on existing psychology research – particularly the Zeigarnik Effect (incomplete tasks create cognitive load), the progress principle (small wins drive motivation), and self-determination theory (autonomy and competence drive engagement) – the prediction going into this experiment was:
To-do lists will produce higher task completion rates for defined projects, but done lists will produce higher satisfaction, lower anxiety, and better recognition of unplanned but valuable work.
Methodology
Structure
- Days 1-10: To-do list only (no done list tracking)
- Days 11-20: Done list only (no to-do list planning)
- Days 21-30: Hybrid approach (combining both systems)
- Daily logging: Same metrics recorded each day at 6:00 PM
Metrics Tracked
- Tasks completed: Total count of meaningful work items finished (excluding routine tasks like email and meetings)
- Planned vs unplanned ratio: What percentage of completed work was pre-planned vs emerged during the day
- Satisfaction score: Self-rated 1-10 at end of day for how productive the day felt
- Anxiety score: Self-rated 1-10 at end of day for residual work-related stress
- Focus time: Hours of uninterrupted deep work (tracked via screen time monitoring)
- Decision latency: Subjective assessment of how quickly and easily task-switching occurred
Controls and Limitations
This is a single-person experiment, not a controlled study. The results are suggestive, not conclusive. Variables that could not be controlled include: varying workload across the month, external stressors, meetings and interruptions from others, and the novelty effect (any new system feels different simply because it is new).
The experiment used a typical knowledge worker’s day: a mix of writing, coding, email, meetings, and administrative tasks. Days with unusual circumstances (sick days, travel, all-day conferences) were excluded and replaced.
Phase 1: To-Do List Only (Days 1-10)
Setup
Each evening, a list of tasks for the following day was prepared, ordered by priority. The list typically contained 8-12 items. Tasks were specific and actionable (“Write draft of Q2 report sections 1-3” rather than “Work on Q2 report”). Time estimates were included but not rigidly scheduled.
Week 1 Observations (Days 1-7)
Day 1-2: The first two days followed the classic to-do list experience. Starting the day with a clear list felt organized and purposeful. Checking off items produced a small but real dopamine hit – the same reward mechanism that makes gamification effective. By 5:00 PM on Day 1, 6 of 9 items were completed. The 3 unchecked items carried a disproportionate psychological weight.
Day 3-4: The planning fallacy appeared on schedule. The list for Day 3 contained 11 items. Only 7 were completed. Rather than feeling good about 7 accomplished tasks, the dominant feeling was “4 things are behind.” The uncompleted items were rolled to Day 4’s list, which now started with 4 carried-over items plus 8 new ones – 12 items total, a number that already felt overwhelming at 8:00 AM.
Day 5: A critical observation: the to-do list punished unplanned work. At 10:00 AM, a colleague asked for help with a technical problem that took 90 minutes to resolve. This was genuinely important, high-value work – the kind of thing that builds team relationships and solves real problems. But on the to-do list, it did not exist. It was invisible. The net effect was that 90 minutes of valuable contribution made the day’s list look worse, because fewer planned items got done.
Day 6-7: Adapted by adding a “buffer” slot to the list: “(unplanned work - 1 hour).” This helped but felt like gaming the system. The core problem remained: to-do lists measure plan adherence, not value delivered.
Days 8-10 Observations
By the end of the to-do list phase, a pattern was clear. On days with predictable workloads (no interruptions, no emergent requests), the to-do list was excellent. Tasks were completed in order, progress was visible, and the checked-off list at end of day was satisfying. On days with unpredictable workloads (which was most days), the to-do list became a source of stress rather than a tool for clarity.
Phase 1 Metrics (Averages)
| Metric | Average (Days 1-10) |
|---|---|
| Tasks completed per day | 7.2 |
| Planned vs unplanned ratio | 78% planned / 22% unplanned |
| Satisfaction score (1-10) | 5.8 |
| Anxiety score (1-10) | 6.1 |
| Focus time (hours) | 4.3 |
| Decision latency | Low (list provided clear direction) |
The surprise: satisfaction was mediocre despite decent productivity numbers. The anxiety score was the most telling – a persistent feeling of being behind, even on days with high output. The to-do list’s structure made it easy to see what was not done and hard to appreciate what was.
Phase 2: Done List Only (Days 11-20)
Setup
No pre-planning. Each day began with a blank page (using The Done List on iPhone for quick capture throughout the day). Whenever a task was completed – any task, whether it was planned or spontaneous – it was recorded. At the end of the day, the list was reviewed.
Week 3 Observations (Days 11-17)
Day 11: The first morning without a to-do list felt genuinely unsettling. There was a moment at 8:15 AM of staring at an empty page and wondering: “What should I do first?” Without a prioritized list, the decision of what to work on fell entirely on in-the-moment judgment. This was both liberating and anxiety-producing.
By 10:30 AM, the anxiety had disappeared. Without a list of obligations to fall behind on, work became responsive to actual priorities as they emerged. An urgent email was handled, a project milestone was advanced, and a colleague’s question was answered – and each of these was recorded as an accomplishment rather than a deviation from the plan.
Day 12-13: The “empty page in the morning” experience became less unsettling and more energizing. The psychological difference was subtle but measurable: instead of starting the day with debt (10 things I owe), the day started with zero and everything was a gain.
Day 14: A potential downside emerged. Without a plan, it was easy to gravitate toward reactive work: answering emails, responding to messages, handling whatever was in front of me. By 3:00 PM, the done list showed 11 completed items, but most were small, reactive tasks. The larger, more important project work had been quietly deferred in favor of quick wins.
This is the done list’s structural weakness: it rewards completion quantity over completion quality. Answering 15 emails looks impressive on a done list, but it may represent 15 tasks that were less important than the one strategic document that did not get started.
Day 15-17: Compensated for the reactivity problem by adding a mental “big rock” check each morning: identifying the single most important task for the day and starting with it before opening email. This was, admittedly, a form of planning – but it was minimal enough to preserve the done list’s blank-slate benefits while preventing the worst of the reactive drift.
Days 18-20 Observations
The done list’s greatest strength became apparent in the daily review. At 6:00 PM, looking at a list of 8-12 items that were all accomplished – not owed, but done – was consistently motivating. The Zeigarnik Effect was inverted: instead of 4 unchecked items generating anxiety, every item on the list generated a small sense of competence.
The done list also captured work that to-do lists miss entirely. A 30-minute conversation with a team member about their career development. Troubleshooting a production issue that was not on anyone’s roadmap. Reading an industry report that informed a strategic decision the following week. These are all real, valuable work that to-do lists structurally ignore.
Phase 2 Metrics (Averages)
| Metric | Average (Days 11-20) |
|---|---|
| Tasks completed per day | 6.8 |
| Planned vs unplanned ratio | 35% planned / 65% unplanned |
| Satisfaction score (1-10) | 7.4 |
| Anxiety score (1-10) | 3.9 |
| Focus time (hours) | 3.8 |
| Decision latency | Higher (some morning uncertainty) |
The numbers tell a clear story: slightly fewer tasks completed, significantly higher satisfaction, dramatically lower anxiety. The focus time drop was concerning – without planned deep-work blocks, focus sessions were shorter and less frequent.
Phase 3: Hybrid Approach (Days 21-30)
Setup
The hybrid system combined elements of both approaches:
- Morning: Identify 1-3 “must-do” items (not a comprehensive to-do list – just the non-negotiable priorities). Use a planning app like My Agenda Planning to block time for these priorities.
- Throughout the day: Record everything completed on a done list, including the planned items and unplanned work.
- Evening review: Review the done list. Check whether the 1-3 must-do items were completed. Celebrate the unplanned work captured alongside them.
Observations (Days 21-30)
Day 21-23: The hybrid immediately felt like an improvement over both pure approaches. The 1-3 must-do items provided enough structure to prevent reactive drift without creating the pressure of a full to-do list. The done list captured everything else, preserving the psychological benefits of accumulating accomplishments.
The key insight: limiting the to-do portion to a maximum of 3 items prevented the planning fallacy from kicking in. With only 3 planned items, most days saw all 3 completed by early afternoon, which created a “bonus time” feeling for the rest of the day. Additional work was recorded on the done list as genuine wins rather than as catching up.
Day 24-26: Experimented with different numbers of must-do items. One item felt too loose – some days needed more structure. Five items started to feel like a to-do list with all its associated pressure. Three was the consistent sweet spot, aligning with research on working memory capacity (most people can hold 3-5 items in active focus without external reminders).
Day 27-30: The system stabilized. Mornings took about 5 minutes: scan calendar, identify the 3 most important outcomes for the day, write them down. Everything else went on the done list as it happened. The evening review was consistently positive – the planned items were almost always done, and the done list showed 5-10 additional completed items that provided a fuller picture of the day’s value.
Phase 3 Metrics (Averages)
| Metric | Average (Days 21-30) |
|---|---|
| Tasks completed per day | 7.8 |
| Planned vs unplanned ratio | 55% planned / 45% unplanned |
| Satisfaction score (1-10) | 8.1 |
| Anxiety score (1-10) | 3.2 |
| Focus time (hours) | 4.7 |
| Decision latency | Low (clear morning priorities, done list for everything else) |
30-Day Results: Side-by-Side Comparison
| Metric | To-Do Only | Done Only | Hybrid |
|---|---|---|---|
| Tasks completed/day | 7.2 | 6.8 | 7.8 |
| Satisfaction (1-10) | 5.8 | 7.4 | 8.1 |
| Anxiety (1-10) | 6.1 | 3.9 | 3.2 |
| Focus hours/day | 4.3 | 3.8 | 4.7 |
| Decision latency | Low | Higher | Low |
| Captures unplanned work | No | Yes | Yes |
| Prevents reactive drift | Yes | No | Partially |
| End-of-day feeling | Behind | Accomplished | Accomplished + focused |
Was the Hypothesis Correct?
Partially. The prediction that to-do lists would produce higher task completion was correct for the pure comparison (7.2 vs 6.8), but the hybrid approach outperformed both (7.8). The prediction about satisfaction and anxiety was confirmed strongly: done lists produced 28% higher satisfaction and 36% lower anxiety than to-do lists. The hybrid approach improved on both metrics further.
The unexpected finding was that the hybrid approach also improved focus time. The hypothesis had not predicted this, but in retrospect it makes sense: having a clear, minimal plan (3 items) provided direction for deep work, while the done list removed the anxiety that often interrupts focus.
Psychological Mechanisms at Work
Why To-Do Lists Generate Anxiety
The Zeigarnik Effect is real and powerful. Uncompleted tasks occupy working memory and generate background stress. A to-do list with 10 items is a list of 10 open cognitive loops. Even when 7 are closed, the 3 remaining feel more salient than the 7 completed. This is not a personal failing – it is a documented cognitive bias that operates below conscious awareness.
Daniel Kahneman’s prospect theory adds another layer: humans feel losses roughly twice as strongly as equivalent gains. A missed to-do item (loss) feels worse than a completed to-do item (gain) feels good. The net emotional experience of a to-do list tends negative even when the majority of items are completed.
Why Done Lists Boost Satisfaction
Teresa Amabile’s research on the “progress principle” at Harvard Business School demonstrated that the single strongest driver of positive work emotions is making progress on meaningful work. Done lists operationalize the progress principle by making progress visible and concrete. Every entry is evidence of forward motion.
Self-determination theory (Deci & Ryan) identifies competence as a fundamental psychological need. A done list is a daily competence record – tangible proof that you are capable and effective. To-do lists, by contrast, tend to highlight the gap between aspiration and execution, which can undermine the sense of competence over time.
Why the Hybrid Works Best
The hybrid captures benefits from both sides. The minimal to-do list (1-3 items) provides enough structure to satisfy the need for direction and prevent the decision paralysis that pure done lists can create. The done list captures everything else, providing the progress visibility and competence reinforcement that long to-do lists undermine.
Critically, limiting the to-do list to 3 items ensures that the Zeigarnik Effect works for you rather than against you. Three incomplete items generate enough cognitive activation to drive focus without the overwhelming background load of a dozen open loops.
Who Should Use Which System
The experiment suggests different people will benefit from different approaches, and the right choice depends on work style, role, and psychological tendencies.
Pure to-do lists work best for:
- Roles with highly predictable, defined work (manufacturing, scheduled tasks, routine operations)
- People who rarely experience unplanned work demands
- Individuals with naturally low anxiety who are not bothered by unchecked items
- Project phases with clear sequential dependencies (where order matters)
Pure done lists work best for:
- Roles with highly reactive, unpredictable work (customer support, management, creative work)
- People prone to perfectionism or work-related anxiety
- Individuals who undervalue their own contributions and need visibility into their actual output
- Recovery from burnout, where reducing perceived pressure is more important than optimizing output
The hybrid approach works best for:
- Most knowledge workers with a mix of planned and reactive work
- Anyone who has tried to-do lists and found them more stressful than helpful
- People who want structure without rigidity
- Teams where visible daily planning helps with coordination but comprehensive to-do lists create performative busy-work
The strongest recommendation from this experiment: if your current to-do list consistently has more than 5 items and you rarely finish all of them, try the hybrid approach for two weeks. Keep your planning minimal (3 items maximum), add a done list for everything else, and see whether your satisfaction and anxiety numbers move in the same direction they did here. The experiment costs nothing but two weeks of attention, and the downside risk is minimal – you can always go back.
