How does the factory get deliveries started after the holidays without stress or unplanned shutdowns?

Five principles help the factory get back on track after the holidays:

1. known and agreed capacity,

2. documented and followed-up losses,

3. daily management with high precision regarding time off,

4. clearly communicated target states for the post-holiday period,

5. ongoing orders in all processes at closing with the next order prepared and ready.

Factories that work this way shorten the startup period from weeks to days.

The pattern is recognizable in most factories. The period before the holidays is characterized by a scramble to meet promised deliveries, every shift, every day, right down to the wire.

The causes behind the stress are well known:

• quality defects,

• maintenance-related stoppages,

• re-plannings,

• customer promises that do not match the capacity of the flow,

• material shortages

• unpredictable time off.

The last delivery is waved off with pride and the team goes on well-deserved leave. Then something strange happens.

The same characteristics return after the holidays, slowing down both deliveries and all good initiatives, often throughout August and well into September. The same thing is repeated around Christmas and New Year.

This guide goes through why the pattern returns year after year and what is required to break it.

Why is the startup after the holidays sluggish year after year?

The startup is sluggish because the problems that existed before the holidays were never resolved, only paused. The symptoms we see before and after the holiday periods can probably be seen as a receipt for all the deviations that occur every day of the year. They are just made extra visible during these specific periods. Holidays do not solve root causes.

The quality defects, maintenance needs, and planning deviations that created the stress in June remain and wait in August, now amplified by machines having stood idle, material not flowing for weeks, and parts of the staffing still being on leave or new.

The scope is larger than most admit. Overall, we can see periods of 2 to 6 weeks before the holidays and equally long periods after the holidays characterized by our holiday behaviors. This occurs in most operations during two shutdown occasions per year: summer as well as Christmas and New Year. A total of 4 to 12 weeks per year, i.e., 1 to 3 months annually, where we accept deviations from the norm.

To compensate for this, many try to reduce the holiday period, from a possible four weeks to three or even two. A better question is the reverse: could we shut down the production apparatus for a longer period, since more employees are off at the same time? What positive consequences would that have and what would be required?

Three mechanisms explain most of the sluggishness:

Losses are unknown or undocumented. Many factories know they have losses, but not exactly which ones, how large they are, or where they occur. Without that knowledge, nothing can be resolved during the summer, and the autumn begins with the same losses the spring ended with.

Capacity is assumed, not known. When planning, sales, and forecasting work against a capacity that does not match the actual capability of the flow, customer promises arise that production cannot keep. The gap grows faster than most realize. If the capacity in the flow is only 5% below the planned and thus promised capacity, production loses 1 day against plan per month. If the difference between actual capacity and promised planned capacity is 20%, the loss corresponds to one day per week. How do we catch up on lost production? In practice: overtime, extra shifts, hired staff, re-plannings, and express freights. What do these recurring, unjustified measures cost? Those questions are rarely asked, but those are exactly the costs driven by the gap between promise and capability, and the gap is largest precisely when the factory is running at half steam during startup.

The startup is guided by feeling and desire instead of facts. The first weeks after the holidays are the period when deviations are most common and experience in the shifts is often thinnest. Yet, that is often when follow-up is most sparse. The problem is discovered days or weeks after it has started driving up costs.

The question is therefore not why the startup is sluggish. The question is why we allow the condition to return when the causes can be measured, analyzed, and resolved.

Why should the goal be the desired state on the first working day after the holidays?

The goal should be the desired state on the first planned working day after the holidays, because that is when the customer meets the factory again and the goal forces a planned ramp-up instead of a forced shutdown.

A perspective we often hear is that "we work towards the goal of the last production day before the holidays". The difference in time between the two goals is marginal, or rather non-existent, but fundamentally large. Whoever aims for the last day before the leave optimizes to finish in time. Whoever aims for the first day optimizes to get started, and then prepared orders, set-up material, and verified processes become part of the target image instead of something that has to wait.

A thought experiment makes the principle clear. If we take the perspective that we could go on holiday basically any day of the year, the phenomenon would probably not occur. A factory that is ready to be paused and restarted has, by definition, control over its processes, its orders, and its capacity. Holiday readiness is, in this view, not an annual effort but a receipt of order and structure in everyday life.

Which five principles make shutdown and startup controlled?

Five principles make shutdown and startup controlled and predictable: known capacity, followed-up losses, daily precision, clear target states, and prepared orders.

1. Known and agreed capacity. That you know and agree on your actual capacity and plan based on this reality and these agreements.

2. Losses are documented and followed up in the same way as a White Sheet. Identifying, measuring, and following up on the losses that slowed you down before the leave constitutes a constant basis for future holiday periods. White Sheet is a specific way of working for the entire organization that standardizes and improves work methods for ramping down and up during holiday periods. Losses are addressed instead of waiting.

3. Daily management with high precision. The last weeks before the holidays and the first days after the holiday period are managed and followed up daily with high precision and high resolution. Factories working in this way shorten the startup period from weeks to days.

4. Clearly communicated and accepted targets. The targets refer to desired states after the holidays, and checks against the targets begin to be applied well in advance of the holiday period. Examples: utilization rate, backlog, cleared material, manufacturing order, and sequence accuracy.

5. Ongoing orders at shutdown, prepared for start. Strive for all processes in the flow to have ongoing orders at the time of closing, ready to be resumed immediately after the holiday period, and that subsequent orders are set up with material, instructions, tools, instruments, and the like. This avoids bottlenecking support functions and resource cannibalization.

What should be done before the leave to make the startup fast?

The foundation for a controlled and predictable ramp-up is created before the leave: prepare the next order per process to the greatest extent possible, document the losses and the work methods we consider deceptive and not beneficial, plan measures for the downtime, and ensure that the startup weeks are planned based on actual capacity.

Use the loss analysis as a packing list. An OEE system that has logged stoppages, causes, changeovers, and quality outcomes during the spring knows exactly what losses have slowed deliveries. Break them down by cause, line, and article. The largest and most recurring losses are candidates for action during the holiday shutdown, when maintenance and improvements can be carried out without disrupting production. These losses form the basis of the shutdown and startup document that will serve as the foundation for improvements ahead of the next holiday period.

Give maintenance facts, not gut feeling. The holiday shutdown is the best maintenance window of the year, but it is only enough for a fraction of everything that could be done. Data on which technical stoppages recur, on which machine parts, and at what cost, allows maintenance efforts to be prioritized based on the failures that actually disrupt deliveries. At Sibbhultsverken, technical stoppages were reduced by 73% in twelve months, precisely by identifying recurring errors in the data and addressing them at their root cause.

Align capacity with planning and sales. Before the leave is a good time to calibrate autumn plans against actual capacity. Actual capacity is not the theoretical speed of the machines, but what the flow actually delivers with the current OEE value. A line with an OEE of 55% delivers 55% of its theoretical capacity, and that is the figure customer promises should be built on until the losses have been addressed. When sales, planning, and production work against the same fact-based capacity, a large part of the re-plannings disappear before they even arise.

How are the startup weeks themselves best managed?

The startup weeks are best managed with daily management at a faster pace than normal, with real-time facts and lowered thresholds for flagging deviations. It is now crucial how quickly deviations are detected.

Run the morning meeting every day, preferably short and standing. Yesterday's outcome against plan, last night's stoppages with causes, and today's risks regarding staffing and material. During startup, some factories may also schedule a short check-in mid-day, as problems come fast in the first few days.

Let real-time data do the work. Dashboards showing status against plan allow production management to see within hours if a line is falling behind, not just at the end of the week. The timeline shows exactly what happened during the night, with stoppage causes coded by the operators who were there. Andon functions alert maintenance and quality immediately when something requires urgent help, so that waiting does not consume the shifts.

Verify data quality during the first few days. After a long shutdown, machine signals, shift schedules, or article data may have drifted. Check early on that the measurements are correct, otherwise you will be managing based on the wrong information during the weeks when you need facts the most.

Lower the threshold for coding and commenting. New or rusty staffing more easily misses coding stoppages. Remind them why stoppage coding is important and make it simple. A growing "Other" category during startup is an early warning sign that the analysis is losing its foundation. At Orkla Nidar, the "Other" category disappeared completely when operators were given tools that made it easy to code the correct cause directly.

How do you break the pattern long-term?

The pattern is broken by the factory getting to know its actual capacity, systematically working away losses during the year, and holding planning, sales, and production together around the same facts. This eliminates both the rush before the leave and the sluggishness afterwards.

Four questions are a good starting point for that reasoning:

Do we know our actual capacity? Not the theoretical but the measured one. If the answer is no, continuous OEE measurement is the first step.

Are we aligned with planning, sales, and forecasting on what capacity we should relate to? If production and the sales organization work against different numbers, customer promises will always break somewhere, and it usually happens in production, in the weeks before a holiday.

Do we allow sequence deviations in the run plans during the year that must be tied together in an unreasonably short time before the holidays? Deviations accumulated over several months cannot be caught up on in two weeks. The data shows where deviations occur and how large they are, long before they become a June crisis.

What losses do we have in our processes and do we have a plan to address them for the coming year? This is the core question. A factory that systematically measures, analyzes, and addresses its losses increases its actual capacity step by step. This shrinks the gap between promise and capability, and with it, both the rush and the backlog.

The answer to all four points in the same direction: start measuring and following up with high resolution and bend over facts instead of memories. Kavli, the Norwegian food group, produced 5,000 tons more than the previous year without more shifts or more machines. This shows that the capacity was in the factory all along. It became available after the losses were made visible and worked away.

How does Good Solutions' platform help with startup and capacity optimization?

Good Solutions' platform is built to drive improvement work based on facts, and that is exactly what a fast startup requires. The loss analysis shows, before the holidays, which losses can be addressed during a potential summer shutdown. Dashboards and timelines provide daily management with real-time facts during startup weeks. The operator tool ensures that stoppage causes are coded exactly when they occur, even by new or temporary staff. Reports give planning, sales, and management the same view of the actual capacity that production works against.

Two parts are particularly relevant for factories wanting to break the startup pattern. Good Solutions' startup program is a five-day program that secures data quality, verifies machine signals, increases competence in different roles, and sets a clear structure for improvement work, precisely what a factory needs after a period when work has lost momentum. The OEE policy workshop brings together decision-makers and key personnel for a half-day to define and document what is measured and how, which is the foundation for planning, sales, and production to be able to work against the same capacity figures.

The platform currently supports 300+ factories. The pattern among those who succeed is the same: the startup is fast when losses are known, capacity is measured, and the first weeks are guided by facts.

See more examples of results from many different factories here.

FAQ

How long should a startup after the holidays take? With prepared measures, verified data quality, and daily management of facts, production should be back to normal pace within a few days to a week. If startup regularly takes all of August, it is a sign that the root causes of the problems have not been addressed.

What is the most important thing to do before the holidays? Three things.

1. Use the loss analysis to list the largest and most recurring losses.

2. Prioritize the holiday shutdown's maintenance and improvement efforts based on the list.

3. Align autumn plans with planning and sales against actual, measured capacity instead of theoretical.

How do we know our actual capacity? Through continuous OEE measurement. Actual capacity is theoretical capacity multiplied by actual OEE. A line with an OEE of 55% delivers 55% of its theoretical capacity, and that is the figure plans and customer promises should build on until the losses have been worked away.

Why is it not enough to run harder in the weeks after the leave? Because forcing does not address the underlying causes. Running harder with the same losses yields the same results, plus more stress, more scrap, and a higher risk of new stoppages. Capacity is freed up by addressing losses, not by pressing the same flow harder.

We have lost momentum in our OEE work during the year. How do we get started again? Start by verifying data quality, as trust in the numbers is the foundation for everything else. Then restart daily management with short meetings based on production facts and select 2 to 3 prioritized losses to address first. A structured restart program, like Good Solutions' Startup Program, which in five days, gives the process a clear framework and ensures that data, competence, and work methods fall into place simultaneously.