Log downtime by cause
When it may fit: Causes are not known.
Evidence needed: Reason codes and timestamps.
Trade-off: Needs floor discipline.
Manufacturing Intelligence Brief
How Downtime Affects Production Economics
A stopped line makes nothing and still costs money. Downtime reduces output, adds overtime and expediting, and can hold back sales if demand is waiting.
1. The business problem
How much is an hour of unplanned downtime actually costing?
Downtime comes from breakdowns, changeovers, material shortages and waiting. It is visible to the floor but often invisible in the financial statements, where it is buried in lower output or higher overtime.
Putting a dollar value on an hour of downtime makes it comparable with other priorities and helps justify preventive maintenance and fixes.
2. What the evidence can reveal
The cost of downtime has several parts:
- Calculated Lost output: units that could have been made and sold.
- Calculated Added cost: overtime, expediting and idle labor.
- Calculated Downtime hours by cause and by line, which show what to fix first.
- Information gap Whether lost output could have been sold, and whether it could be made up later.
If the plant is capacity-constrained, lost hours are lost sales. If demand is the limit, the loss is smaller.
3. Investigate the problem
In the synthetic plant, Calculated downtime rose 35.5%, from 3,100 to 4,200 hours, while units produced grew 8.8%. Quarterly downtime ran from 740 to 810 hours in FY25 and from 1,010 to 1,090 hours in FY26: a step up that persisted all year.
Calculated Scrap and rework rose in step, from 4.7% to 5.7% of production cost, and operating margin fell. In the scenario, a 1% change in volume is worth about $262K a year. Illustrative If the plant scheduled about 24,000 line-hours a year (an invented figure), the extra 1,100 hours of downtime would be about 4.6% of scheduled time, and if all of that output could have been sold, it would be worth about $1.2 million.
Hypothesis The step change suggests a specific cause that started at the beginning of FY26, such as aging equipment, a new product or a staffing change, not a gradual drift. Information gap Downtime by cause and line is not in the demo. Logging each stop with a reason code for a month usually shows a handful of causes that account for most of the lost hours.
4. Explore the interactive experience
Investigate it yourself.
Manufacturing Performance Dashboard: a product-line dashboard with downtime and scrap, a scenario simulator for volume, price, materials and scrap, evidence-linked answers from APIS, and a sample brief, all on synthetic data.
The experience below is built on a synthetic manufacturer, “Demo Components Inc.,” analyzed by product line. It has no station-level, machine-level or line-level records, so product lines are used to show the method. Nothing in it is real.
- Click the Downtime hours card and read the quarterly trend. When did the step up occur?
- In the Scenario tab, lower volume by 4%, a stand-in for lost output. Note the profit effect.
- Ask APIS why higher production volume does not always improve profitability.
5. Evaluate possible solutions
Reducing downtime starts with knowing the causes.
6. What leadership should do next
Questions to answer
- How many hours were lost, and why?
- What did the step up in FY26 coincide with?
- What is an hour worth?
- Which causes are fixable?
Data to gather
- Downtime log by cause and line
- Maintenance records
- Changeover times
- Demand by product
Steps to take
- Start logging.
- Rank causes.
- Fix the top three.
- Track weekly.
7. Engage Two Pillars
Identify Opportunities Across Production, Costs, and Capacity
Two Pillars can help manufacturers investigate production performance, cost structure, inventory and capital investment decisions using your own plant data. A good first step is a downtime analysis that logs causes and puts a dollar value on each hour.
Sources and data notes
- The organization, its figures, and every number in this article and its interactive experience are synthetic and illustrative. They are not real data, a benchmark, or a forecast.
- Reviewed October 2026. This article describes an approach to investigation. It does not replace review by qualified professionals.