Operations leadership treated 22% overtime as a fixed cost of running 24/7. The diagnostic revealed three distinct drivers — only one was actually structural.
Pulp & PaperA kraft pulp and paper mill running four-crew, 24/7 continuous operations had been carrying overtime in the 22% range for years and had come to treat it as the cost of doing business. The diagnostic phase revealed three distinct overtime drivers operating simultaneously: chronic vacancy on one specific crew, absence-coverage cascading across crews, and structural understaffing on a single critical operation. The redesign addressed each driver with a separate intervention — not a single schedule change — and cut total overtime by more than half within nine months.
A kraft pulp and paper mill running pulping, recovery, and paper machine operations on a four-crew 24/7 continuous schedule (Day, Afternoon, and Night shifts staffed by four rotating crews). ~720 mill workers including operators, maintenance, and dedicated support staff. Unionized workforce under a collective bargaining agreement that included specific overtime rules: voluntary-first assignment, mandatory rotation when voluntary failed, and double-time premium beyond defined thresholds. Mill had operated on the same crew structure for over a decade.
Overtime had been running at approximately 22% of straight time for the prior three years. The mill leadership team had concluded that the high overtime was a structural feature of the operation — the mill simply needed more bodies than the four-crew structure could comfortably provide. A plan was being drafted to add a fifth crew, with projected payroll impact in the range of $9 million annually. The plan had not yet been presented to the union.
Beyond the projected fifth-crew payroll, the operations team had concerns about whether adding bodies would actually solve the problem or whether it would simply absorb the same root causes at higher cost. The union was likely to push back on a fifth crew in any case, given the implications for crew assignment seniority and shift differential structures. Leadership wanted a rigorous answer to the question of what was actually causing the overtime before committing to a structural change.
Phase 1 · Business Assessment
We pulled three years of overtime records and broke them down by crew, shift, day of week, week of month, operation, and reason code. We mapped overtime against vacancy rates, absence patterns, scheduled training, equipment downtime, and maintenance turnarounds. We compared overtime hour-for-hour against straight-time productivity to test whether overtime hours were actually delivering production or simply backfilling absence. We examined the crew-by-crew distribution to check whether overtime was evenly spread or concentrated on specific groups.
Three distinct drivers, not one. First: one of the four crews carried 41% of the total overtime — significantly disproportionate to its size. That crew had three long-vacant positions that had been carried at reduced staffing and covered through overtime for over two years. Second: absence-driven overtime cascaded across crews due to a coverage rule that triggered overtime backfill within four hours of an absence call-in, regardless of whether the absent worker’s tasks were truly time-critical. Third: a single operation in the recovery boiler area was structurally understaffed by one position relative to its actual workload — the operation needed three operators per shift but had been running with two.
Overtime is rarely one problem. The mistake is treating it as one and reaching for one solution — usually more bodies. The cheaper, more effective approach is to diagnose each driver separately.
Phase 2 · Workforce Assessment
We met with operators, line leads, and union representatives across all four crews. The conversations confirmed what the data showed but added important detail: workers on the high-overtime crew expressed fatigue and frustration but also a financial dependence on the overtime that made them ambivalent about losing it. Workers on the lower-overtime crews expressed resentment that the high-overtime crew was getting all the premium hours. Recovery boiler operators confirmed they had been running understaffed and that the operation routinely required pulling support from adjacent areas. The workforce was open to changes that addressed the genuine fatigue and inequity, but skeptical of any change that would be perceived as removing earnings opportunity.
Phase 3 · Solution Design
Three separate interventions, each targeting one driver. First: the three long-vacant positions on the high-overtime crew were filled through internal posting, with a clear pathway for inter-crew transfer to spread the recruitment burden. Second: the absence-coverage rule was rewritten to distinguish time-critical positions (immediate coverage required) from non-time-critical positions (next-shift coverage acceptable), eliminating the four-hour backfill trigger for roughly 60% of absence events. Third: the recovery boiler area was restructured to add the missing third operator per shift, with crew assignment rotated through the pool to spread the new positions across the workforce.
Phase 4 · Implementation Preparation and Rollout
The implementation manual documented each intervention separately along with the underlying rationale. The union ratified the package because the changes addressed concerns the workforce had been raising informally for years — the inequity in overtime distribution, the fatigue on the high-overtime crew, and the chronic understaffing of the recovery boiler. Management sign-off was straightforward once the case had been built. Rollout took twelve weeks, with the absence-coverage rule change implemented first (lowest-risk, highest-immediate-impact), followed by the recovery boiler restructure, and the vacant-position fill completing the package.
Measured against the client’s stated objective:
| Metric | Before | After |
|---|---|---|
| Total overtime as % of straight time | 22% | 9% |
| High-overtime crew share of total OT | 41% | 27% |
| Absence-driven overtime hours per month | ~1,860 | ~640 |
| Recovery boiler area overtime hours per month | ~340 | ~80 |
| Annual payroll impact of fifth-crew alternative | +$9M projected | $0 (avoided) |
Workforce satisfaction across all four crews improved measurably, driven primarily by the more equitable distribution of overtime and the resolution of the recovery boiler understaffing. The high-overtime crew reported that even with reduced earnings, the lower fatigue level and the resolution of long-standing understaffing was a net positive. Union relationship strengthened because the engagement addressed concerns that had been raised at the table for years without resolution. The schedule has held with overtime in the 8–10% range for over eighteen months.
The Design Principle: Overtime is rarely one problem. Diagnose each driver separately — vacancy, absence-coverage, structural understaffing, scheduled events — and address each with the intervention that fits it. A single solution applied to multiple drivers either over-corrects, under-corrects, or both at once.
The pattern in continuous-operation environments is that overtime accumulates from multiple distinct sources, and the operations team often cannot see the breakdown clearly because the overtime appears in the aggregate as a single line item. Without rigorous attribution — by crew, by reason code, by operation, by time period — the diagnostic conversation defaults to the simplest explanation, which is usually “we need more people.” The actual answer is almost always more granular and more solvable than that.
A second pattern: long-running overtime creates workforce expectations that have to be managed in any redesign. Workers who have come to depend on overtime earnings will resist changes that reduce those earnings, even when the underlying schedule is genuinely unhealthy. The workforce assessment is critical for surfacing those concerns and designing the change in a way that addresses them honestly — through differential adjustments, rotation, or transition periods — rather than ignoring them.
If your operation is carrying overtime that has come to feel like a fixed cost, the highest-leverage early step is the attribution analysis: breaking the overtime down by crew, shift, reason, and operation to identify what is actually driving it. The answer is rarely a single cause — and the cost of finding out is small compared with the cost of a structural change that does not address the underlying drivers.
Shiftwork Solutions LLC has guided hundreds of engagements across food manufacturing, distribution, pharmaceuticals, automotive, and other 24/7 and shift-based operations over more than three decades. Visit shift-work.com to start a conversation.
