A facility produces 1M units/year with 45 employees. A competitor produces 1.2M units/year with 38 employees. Both are profitable, but the competitor has better labor productivity—1.6% lower labor cost per unit.
Over a 10-year period, this difference compounds: The less efficient facility spends $5M more in labor than necessary.
Yet many facilities operate without formal staffing standards. Staffing decisions are historical ("we've always had 45 people") rather than data-driven.
Developing Staffing Standards
Effective staffing standards define labor requirement by function:
Production Operations:
- Direct production labor: Per line, per shift (e.g., 6 operators x 3 lines x 2 shifts = 36)
- Quality control: Per 500K units produced (e.g., 3 QC technicians)
- Shift supervision: 1 supervisor per 8 direct labor
Maintenance:
- Preventive maintenance technicians: Per $X of equipment value (e.g., 1 per $500K)
- Reactive maintenance: On-call coverage (1 person per 15 equipment items)
Administrative/Support:
- Scheduling and planning: 1 person per 3 production lines
- Materials handling: Based on throughput (1 person per 200K units/year)
The Benchmark Approach
Industry benchmarks provide reference points (though wide variation exists):
| Function | Benchmark | Notes |
|---|---|---|
| Direct Production | 1.2-1.8 per line shift | Depends on automation, product complexity |
| Quality Control | 1-2 per 500K units | Depends on testing intensity |
| Maintenance | 1-1.5 per $1M equipment | Depends on equipment age, reliability |
| Supervision | 1 per 8 direct labor | Standard ratio |
A facility with 4 production lines, 2 shifts, $4M equipment:
- Direct production: 4 x 2 x 1.5 = 12 operators (using 1.5 benchmark)
- Quality control: 1 per 500K = 2 QC technicians
- Maintenance: 4 technicians (based on 1 per $1M)
- Supervision: 2 supervisors (12 direct labor / 8)
- Total: ~20-22 core operations staff
The Data-Driven Approach
Rather than relying on benchmarks, analyze actual data:
1. Define Standard Work: For each role, document expected activities and time requirements.
- Example: One production operator should manage 3 parallel CIP systems, monitor quality, perform changeovers.
2. Measure Current State: Track what people actually do (time studies, work sampling).
- Example: One operator spends 40% time on CIP management, 30% changeovers, 20% quality, 10% paperwork.
3. Identify Improvement Opportunities: Where can efficiency improve?
- Example: Automate paperwork (reduce 10% to 3%), combine role with quality (15% overlap)
4. Calculate Required Staffing: Once standard work optimized, calculate staffing need.
The Productivity Improvement Path
Most facilities can improve labor productivity 10-15% through:
- Standardized work procedures (reduce variability)
- Equipment automation (reduce manual tasks)
- Cross-training (improve flexibility, reduce idle time)
- Process improvements (reduce waste)
For a 45-person operation, 10% improvement = 4.5 fewer people. At $60K fully-loaded cost per person per year, that's $270K annual savings—without reducing production.
The PE Value Creation Opportunity
PE firms often identify labor productivity improvement as key value creation lever. A facility with 15% above-benchmark staffing represents opportunity for 10-15% cost reduction without production loss.
For food manufacturing companies, developing data-driven staffing standards and targeting industry-leading labor productivity improves profitability while freeing capital for growth investments.
