What does one hour of production downtime cost?

When the power disappears for an hour, the first reflex is often to calculate the lost production time: how many units could we have made, and what were they worth? That question is relevant, but it is far from the whole answer. Downtime sets off a chain of costs that can continue for hours or days after the power returns.

This article walks through why production downtime is more expensive and more complex than lost production time alone, which cost categories are actually in play, and how a company can set up a simple calculation model for what one hour of downtime actually costs. The purpose is not to give a single answer, but a basis for decision-making: what does it cost us if the power disappears at the wrong time?

Downtime is more than lost production time

The most intuitive way to calculate downtime is to multiply lost production time by the value of what is normally produced in that period. That is a sensible starting point, but it captures only one part of the picture.

The Danish Energy Agency (Energistyrelsen), which is Denmark's national energy authority, has itself built an official model for what electricity interruptions cost businesses, and the model consists of more than one component. Beyond the lost productive activity during the interruption itself, the Danish Energy Agency's method also includes the extra costs a company incurs if the lost production has to be caught up later, for example through overtime or extra shifts. The report also notes that for the large majority of companies, a power outage means that production effectively stops, but that the severity of the consequence depends strongly on how long the interruption lasts and when it hits.

That point is confirmed by how the Danish Energy Agency values the interruption itself. Value of Lost Load, abbreviated VoLL, is an EU-defined measure of how much customers on average are willing to pay to avoid a power interruption. The latest Danish estimate puts the average value at 176 DKK per kWh, but the figure is far from uniform across company types: large industrial companies value an interrupted kWh at around 200 DKK, while the figure for small industrial companies sits at around 76 DKK. The difference shows something central: the same amount of lost electricity has a very different economic consequence depending on who is hit, and that is precisely the logic that also applies inside a single company, depending on which process is interrupted.

An earlier Danish Energy Agency analysis of the costs of electricity supply interruptions, based on responses from 645 companies, points in the same direction: a typical industrial company facing a four-hour interruption has a cost of around 136 DKK per kWh, compared with 22 to 29 DKK for agriculture and households. The analysis also shows that advance warning changes the bill substantially. A warning of just two hours can on average reduce costs by nearly one third for several consumer groups. Both who is hit, and whether the interruption comes with or without warning, are therefore decisive for the price, not only how many minutes it lasts.

The cost categories behind one hour of downtime

One hour of downtime typically sets several cost types in motion at once, and most of them are invisible in a simple "minutes times production value" calculation:

• Lost revenue and contribution margin: the value of the production that is not made while the power is out.
• Wages during standstill: employees who remain on the payroll even though production is stopped.
• Machine idle time: equipment that is not producing, but that still ties up capital and in some cases still draws energy in standby.
• Production waste and discarded raw materials: material that is in process when the power disappears and that cannot be saved.
• Restart time: the period from when power returns until production is running at normal level again, which is often longer than the interruption itself.
• Cleaning and recalibration: necessary before production can resume in many types of process and food production.
• Delivery delays: when production that should have been delivered is delayed as a result of the stop.
• Penalties or compensation to customers: relevant if delivery agreements include consequences for delay.
• Loss of an entire batch: especially relevant in process and food industry, where an interrupted run can make a whole production unusable.
• Quality control after a stop: extra inspection of products made just after a restart, because quality is typically less stable in that period.
• Overtime to catch up production: extra shifts or overtime to reach the original production plan.
• Loss of customer trust: harder to measure directly, but real if repeated delays affect the customer's assessment of the company's delivery reliability.

None of these categories is necessarily expensive on its own. The problem is that they typically appear at the same time, and that several of them are never recorded as a consequence of downtime in the company's ordinary accounting practice. Wages during standstill are booked as wages, waste is booked as waste, overtime is booked as overtime, and none of them gets a label that says "this is due to a one-hour power interruption on the 14th of last month."

That picture is confirmed by international research in the area. A study from Siemens/Senseye, based on 181 interviews with maintenance and operations managers in large industrial companies over a five-year period, finds that unplanned downtime costs the world's 500 largest industrial companies the equivalent of 11 percent of their total revenue per year. Interestingly, the number of downtime incidents has fallen markedly in the period the study covers. What has risen is the cost per hour of downtime, because production has become more complex and interdependent. That is precisely the kind of development that makes "number of minutes" a poor measure of economic risk.

A simple calculation model

A workable approach is to set out the downtime cost as the sum of the most important categories, rather than trying to capture everything down to the last øre (cent):

Downtime cost per hour = lost contribution margin + wage cost during stop + waste + restart cost + delay cost

• Lost contribution margin is the value of the production that does not happen, minus the variable costs the company also saves while it is not producing.
• Wage cost during stop is the fully loaded hourly wage for the employees whose work depends directly on power being available.
• Waste covers raw materials, intermediates, or finished goods that are discarded as a direct result of the interruption.
• Restart cost covers the time and resources it takes to bring the process back to normal operation, including any cleaning, recalibration, and extra quality control.
• Delay cost covers the consequence of planned deliveries shifting, including any overtime to catch up production.

The model is deliberately simple. It does not capture loss of customer trust, which is real but hard to put a number on in a single calculation. It is still more accurate than multiplying minutes by an average production value, because it forces the company to engage with the categories that otherwise hide in other budget lines.

Two companies, the same interruption, a different bill

The value of the model becomes clear when you compare two companies hit by exactly the same one-hour power interruption.

Company A has a short and well-tested restart procedure. The process tolerates a short stop without losing material in process, and there is no requirement for extensive cleaning or recalibration before production can resume. Here the bill consists primarily of lost contribution margin during the interruption itself and a modest amount of wages during standstill. Restart cost is low, waste is minimal, and the delay can often be caught up without significant overtime.

Company B has a process where a power outage interrupts material mid-batch that cannot be saved or resumed. Restart requires cleaning, recalibration, and a period of heightened quality control before production is stable again. Here waste and restart cost stack on top of the lost contribution margin, and if the delivery was promised to a customer with tight deadlines, delay cost comes on top of that again, possibly supplemented by overtime to catch up the lost production.

The same one-hour interruption can therefore produce two very different bills, even with identical duration and timing. Two companies with the same statistical exposure to interruptions can have a very different economic consequence, because it is restart time, waste risk, and delivery obligations that determine the bill, not the interruption's duration in itself.

Why interruption minutes are not the right question

National statistics for electricity interruptions, planning targets for interruption minutes, and average security-of-supply figures say something important about the Danish electricity system as a whole. They say very little about what a concrete interruption costs a concrete company. A survey from ABB, based on responses from more than 3,200 maintenance managers globally, finds that over two thirds of industrial companies experience unplanned downtime at least once a month, and that a single breakdown on an ordinary working day can cost significant sums if it drags on. Frequency and duration alone say nothing about how expensive it becomes for the particular company that is hit.

The decisive question is therefore not how many minutes the electricity grid is statistically down over the year. It is: what does it cost us if the power disappears at the wrong time, mid-critical batch, just before a delivery deadline, or in the hour when most equipment is running at once? That can only be answered with knowledge of the company's own processes, restart time, and delivery obligations, not with a national average interruption statistic.

The limits of the calculation

The model is a decision tool, not a guarantee of precision. Loss of customer trust is difficult to quantify and should enter as a qualitative consideration rather than a number in the formula. The calculation also says nothing about how likely a power outage is for this particular company. It answers only the consequence question: if it happens, what does it cost. Probability must be assessed separately, among other things from grid connection, local grid conditions, and history.

A calculated downtime cost is also not in itself an argument for a particular technical solution, but an input to a decision on whether an investment in backup, reserved capacity, or other resilience makes sense relative to the risk it is meant to cover. That requires a separate technical and economic assessment of what a given solution actually costs and can deliver.

ZynexGroup's approach to system assessment

We do not recommend a particular solution before we know the downtime cost. When a company approaches us wanting to assess backup, reserved capacity, or other resilience, we therefore start by asking how production is actually structured: which processes are most sensitive to interruption, how long the real restart time is, and which delivery obligations are in play.

That picture, together with data on grid connection and consumption profile, is the basis for a data-based dialogue about what makes sense for that particular company: whether the standard model's commercial optimisation is sufficient, or whether there is a concrete business case for looking more closely at add-ons such as reserved capacity. When we assess that installation is technically and economically realistic at a grid connection of at least 400A, it also forms part of the picture that we offer an actual 6-year payback guarantee on BESS systems. But the commercial assessment always comes after, not instead of, an understanding of the underlying production risk.

Overall perspective

One hour of production downtime is rarely just one hour of lost production. It sets a series of costs in motion, from wages during standstill and waste to restart, delay, and in some cases loss of customer trust, and most of them are invisible if you only calculate in minutes and average production value. Both the Danish official method and international industry studies point in the same direction: the real consequence of downtime depends on which process is hit, how long the restart time is, and when the interruption occurs, not only on how many minutes it lasts.

A simple calculation model that brings together lost contribution margin, wage cost, waste, restart, and delay gives a far more accurate picture than an average view, and it makes it possible to compare two companies or two processes with the same statistical interruption risk but a very different economic consequence. That is the basis any assessment of backup or reserved capacity should build on.

An internal downtime calculation before assessing backup

Before a conversation about backup, reserved capacity, or other resilience measures makes sense, it is worth making an internal calculation of what one hour of downtime actually costs in your most critical process. It does not require a large project: an overview of lost contribution margin, wage cost during stop, typical waste, restart time, and any delivery obligations is often enough to give a usable picture.

If you want to take the assessment further with us, we are happy to use your own data, including grid connection, consumption profile, and knowledge of critical processes and restart times, as the starting point for an initial assessment of whether there is a match. You are welcome to contact us here.