Productivity day simulator: see what meetings, interruptions and breaks do to your capacity

What the simulator does

The panel above builds a working day at 15-minute resolution between 06:00 and 22:00 from eight settings: start and end time, number and length of meetings, number and length of focus blocks, interruption frequency and break pattern. From that schedule it derives four things: a conceptual capacity curve, an estimate of deep-work minutes, a fragmentation score (longest uninterrupted block and number of fragments) and a side-by-side comparison with a restructured day that applies three rules to the same inputs. The three presets — manager, maker, hybrid — are starting points, not diagnoses; change anything and every output updates.

Everything is a model, and a deliberately simple one. The curve is labelled conceptual because no study measures the minute-by-minute capacity of an individual knowledge worker; what the research does support are the directions the model uses, and that is what the evidence badges below describe.

How to read the capacity curve

The curve multiplies two things. The first is a circadian baseline that peaks mid-morning, dips after lunch and declines in the evening. The post-lunch dip is a well-replicated phenomenon in laboratory alertness and performance studies, largely independent of whether a meal is eaten B^[5]. The second factor is fatigue from accumulated unbroken work, which recovers at breaks and lunch. This follows the account of mental fatigue as a cost–benefit signal that reduces task engagement and performance monitoring the longer effort continues without reward or rest B^[2].

Breaks are modelled as partial recovery rather than a reset. A 2022 meta-analysis of 22 micro-break studies found small but reliable gains in vigour and reductions in fatigue after breaks of ten minutes or less, with performance benefits mainly for clerical and creative tasks and clearer effects for longer breaks A^[1]. Earlier reviews of rest-break research in shift and industrial work point the same way: fatigue and accident risk climb across long continuous spells and fall after a break B^[6]. The simulator's recovery factors (×0.6 at a short break, ×0.35 at lunch) are illustrative values chosen to reproduce that pattern, not estimates from any single study.

Why fragmentation matters more than hours

Two days with the same number of focus minutes can produce very different deep-work estimates, because the model discounts interrupted slots and the slot that follows them. Field observations of information workers describe work as a sequence of short "working spheres" averaging around 11 minutes before a switch, and found that interrupted work was resumed on average only after more than 20 minutes, with other tasks in between B^[7]. That is the time until people returned to the task, not the time needed to regain full concentration. In a laboratory experiment with email interruptions, people compensated by working faster, at the price of higher stress and workload B^[3]. Experiments on attention residue show that leaving a task unfinished before switching degrades performance on the next one B^[4]. The fragmentation score summarises that in one number: it rewards a long uninterrupted block and penalises many pieces.

The three restructuring rules

The restructured day keeps your meeting count, meeting length, focus block count and interruption rate exactly as you set them. It changes only three things, in a fixed order:

1. Cluster meetings back-to-back after lunch (or after the protected block when there is no lunch), so the morning is free of hard stops.
2. Protect your first focus block by moving it to the start of the day, treated as interruption-free — notifications off, status set, door closed. It keeps the length you set; 90 minutes is a practical length, not a biological constant; the related Focus Planner lets you test 50 or 25 minutes as well.
3. Add a short break after every 90 minutes of continuous work, which costs a 15-minute slot in this model but resets part of the accumulated fatigue A^[1].

The delta column shows what those three moves do to the same inputs. For meeting-heavy presets the gain usually comes from the protected block; for maker presets it comes from the breaks and from moving meetings out of the middle of long blocks.

Limitations

• The capacity values are conceptual and uncalibrated. They show direction and relative size, not minutes you can bank.
• Interruptions arrive on a fixed interval; real ones cluster, and self-interruptions are as common as external ones B^[7].
• Fatigue and recovery parameters are fixed; sleep, caffeine, task type and individual chronotype are not modelled.
• Meetings are treated as medium-load work; a good meeting can energise, a bad one can drain.
• Nothing is measured from your calendar or device; the inputs are your own assumptions. The simulator stores and sends nothing.

Use the export button to print or save the comparison as a PDF, then take the restructured day to the Focus Planner to turn it into a schedule you can actually test for a week.

Frequently asked questions

Is the capacity curve based on my data?

No. It is a conceptual model driven only by the settings you choose. It uses a circadian baseline with a post-lunch dip and a fatigue term that grows with unbroken work and recovers at breaks. It does not read your calendar or any device.

Why does a short break sometimes lower the scheduled focus minutes?

At 15-minute resolution a short break occupies one slot, so the restructured day can show fewer scheduled focus minutes but more estimated deep-work minutes, because the slots after a break run at higher capacity and fewer slots are discounted for interruptions.

Is 90 minutes the right length for the protected block?

It is a practical length that fits before most meeting-heavy afternoons and is long enough for one piece of demanding work. There is no strong evidence that 90 minutes is biologically special for desk work; 50 or 60 minutes are equally valid, and the Focus Planner lets you test them.

How is the fragmentation score calculated?

Sixty percent of the score comes from the longest uninterrupted block (a 120-minute block scores zero on that part) and forty percent from the number of work fragments (eleven or more fragments score the maximum). Lower is better; the exact formula is in the model assumptions panel.

Can I save or share a scenario?

You can print or export the comparison to PDF with the button under the panel. Settings are not stored or sent anywhere; reload the page and the hybrid preset returns.

Sources and evidence

1. "Give me a break!" A systematic review and meta-analysis on the efficacy of micro-breaks for increasing well-being and performance — Albulescu P, Macsinga I, Rusu A, Sulea C, Bodnaru A, Tulbure BT (2022), meta-analysis (PLOS ONE) A doi.org/10.1371/journal.pone.0272460 (retrieved 2026-11-09)
2. Mental fatigue: Costs and benefits — Boksem MAS, Tops M (2008), narrative review (Brain Research Reviews) B doi.org/10.1016/j.brainresrev.2008.07.001 (retrieved 2026-11-09)
3. The cost of interrupted work: more speed and stress — Mark G, Gudith D, Klocke U (2008), experiment (CHI 2008) B doi.org/10.1145/1357054.1357072 (retrieved 2026-11-09)
4. Why is it so hard to do my work? The challenge of attention residue when switching between work tasks — Leroy S (2009), experiments (Organizational Behavior and Human Decision Processes) B doi.org/10.1016/j.obhdp.2009.04.002 (retrieved 2026-11-09)
5. The post-lunch dip in performance — Monk TH (2005), review (Clinics in Sports Medicine) B doi.org/10.1016/j.csm.2004.12.002 (retrieved 2026-11-09)
6. The impact of rest breaks upon accident risk, fatigue and performance: a review — Tucker P (2003), review (Work & Stress) B doi.org/10.1080/0267837031000155949 (retrieved 2026-11-09)
7. No task left behind? Examining the nature of fragmented work — Mark G, Gonzalez VM, Harris J (2005), field study (CHI 2005) C doi.org/10.1145/1054972.1055017 (retrieved 2026-11-09)