Chinese New Year 2027: factory calendar and import timeline

Chinese New Year falls on 6 February 2027. Unlike a public holiday set by decree, this date follows the Chinese lunisolar calendar: it can be calculated years in advance and depends on no government announcement. The official public holiday schedule, by contrast, is published by the Chinese authorities only a few months ahead, usually towards the end of the previous year.

The period is officially called the Spring Festival. It marks the time of year when a large share of workers from rural areas or other provinces return to their families, often for several weeks. It is this movement of people, not just the public holiday, that explains the scale of the industrial slowdown.

The official public holiday usually lasts about a week, but the actual shutdown of a garment workshop or a small-parts factory often stretches over several weeks, before and after the date itself. Some workers leave earlier to avoid the transport rush, others do not come back straight away, and some never come back at all: staff turnover rises sharply after the Spring Festival in Guangdong's industrial zones.

The weeks before the shutdown see the opposite effect: factories run at full capacity to clear current orders, production lead times stretch, and freight rates rise on some routes under the pressure of demand. The weeks after reopening do not immediately return to a normal pace, as teams are rebuilt and new arrivals are trained.

The principle of a planning timeline is to start from the shutdown date, then count back production time, inspection time and transport time to fix the deadline for placing the order. A standard production lead time, a pre-shipment inspection, then sea freight together add up to several weeks that must be counted back from the shutdown date, not from the desired delivery date.

The calculation must also build in a safety margin, because factories rarely announce their exact closing date early in the year, and because production lead times tend to slip in the weeks before the cutoff. An order placed too close to the deadline risks tipping over into after the shutdown without the buyer being told in time.

A first mistake is negotiating a production lead time without checking the closing date of the chosen factory: two suppliers in the same sector can close weeks apart. A second mistake is underestimating transport time, particularly sea freight, whose actual duration varies with the season and port congestion.

A third, more subtle mistake concerns quality control: an order rushed through before the shutdown is more exposed to defects than one produced with a comfortable margin. A pre-shipment inspection then becomes particularly useful, precisely because the factory has less time left to fix a problem found late.

The period after reopening deserves the same attention as the one before it. Factories that have lost part of their workforce recruit and train new teams, which can affect the consistency of quality on the first batches produced after the break. Stepped-up inspection on the first orders of the year remains a reasonable precaution.

Some buyers instead use this period to prospect new suppliers or visit factories, since workshops are more available to receive visitors than during peak production season.

One last point worth remembering: an urgent order placed just before the shutdown usually costs more, in the form of a rush-production surcharge or express freight. A planning timeline built early in the year avoids this extra cost, which hits first the buyers who discover the closing date at the last moment.

Sorva tracks the real closing calendar of every factory we work with, beyond the official public holiday, and builds your order's planning timeline from that date, not the theoretical one. Our Chinese-speaking team in Guangzhou confirms the workshop's closing date and production capacity directly before the cutoff.

In most cases you pay no fees: you open a file, we negotiate the goods on your behalf, and we take a commission on their ex-factory value.