What is SPLH (Sales Per Labor Hour)?
SPLH (Sales Per Labor Hour) measures the revenue generated for each hour of labor worked at a restaurant. Calculated by dividing total sales by total labor hours, this metric is the fundamental efficiency measure for QSR operations. Industry averages range from $30-60+ per labor hour depending on segment and market. Voice AI dramatically impacts SPLH by maintaining or increasing sales while reducing labor hours required—particularly for order-taking positions that can be automated.
SPLH is where labor efficiency meets revenue reality.
Why SPLH Matters for QSRs
Profitability Driver
Labor is largest controllable cost:
- Typically 25-35% of revenue
- Higher SPLH = better margins
- Direct impact on profitability
- Primary efficiency lever
Operational Efficiency Indicator
SPLH reveals:
- How productively labor is used
- Revenue generating effectiveness
- Operational quality
- Management efficiency
Investment Decision Guide
SPLH helps evaluate:
- Technology ROI
- Process change impact
- Staffing model effectiveness
- Improvement priorities
Competitive Benchmark
Compare against:
- Similar brands
- Same market peers
- Historical performance
- Industry standards
Calculating SPLH
Basic Formula
SPLH = Total Sales / Total Labor Hours
Example Calculation
Restaurant data:
- Daily sales: $5,000
- Labor hours worked: 100 hours
- SPLH: $5,000 / 100 = $50/hour
Calculation Considerations
What to include in sales:
- All revenue streams
- Drive-thru + dine-in + delivery
- Before or after discounts (be consistent)
What to include in labor hours:
- All worked hours
- Including management typically
- Overtime hours count
- Consistent methodology
SPLH Benchmarks
By QSR Segment
| Segment | Typical SPLH | High Performer |
|---|---|---|
| Burger | $40-55 | $60+ |
| Chicken | $35-50 | $55+ |
| Mexican | $35-50 | $55+ |
| Pizza | $40-60 | $70+ |
| Coffee | $50-70 | $80+ |
Performance Levels
| SPLH | Assessment | Implication |
|---|---|---|
| $60+ | Excellent | Highly efficient |
| $50-60 | Good | Above average |
| $40-50 | Average | Industry typical |
| $30-40 | Below average | Improvement needed |
| <$30 | Poor | Significant issues |
Components of SPLH
Revenue Side
Sales drivers:
- Transaction count
- Check average
- Upsell success
- Operating hours
- Channel mix
Labor Side
Hours drivers:
- Staffing levels
- Shift scheduling
- Task efficiency
- Automation level
- Training effectiveness
The Ratio
Improving SPLH requires:
- Increasing sales with same labor
- Maintaining sales with less labor
- Growing sales faster than labor
- Any combination above
Voice AI Impact on SPLH
Labor Reduction
Order-taker hours saved:
- Reduce or eliminate dedicated order-taker
- 3-8 hours/day removed or repurposed
- Particularly impactful at peak hours
- Night shift labor reduction
Revenue Protection/Growth
Sales maintenance or improvement:
- Consistent upselling maintains check average
- Fast service maintains throughput
- Accuracy reduces remakes
- Potential revenue increase
SPLH Math
Example calculation:
Before Voice AI:
- Sales: $5,000/day
- Labor: 100 hours
- SPLH: $50
After Voice AI:
- Sales: $5,100/day (+2% from upselling)
- Labor: 92 hours (-8 hours order-taking)
- SPLH: $55.43 (+10.9%)
Annual Impact
Single location savings:
- 6 hours/day saved × $15/hour = $90/day
- $90 × 365 = $32,850/year in labor
- Plus revenue improvement from upselling
- Plus reduced remake costs from accuracy
Improving SPLH
labor optimization
Efficiency strategies:
- Voice AI for order-taking
- Task automation where possible
- Better scheduling
- Cross-training for flexibility
- Reduce unnecessary hours
Revenue Growth
Sales strategies:
- Consistent upselling
- Throughput optimization
- Operating hour optimization
- Marketing effectiveness
- Menu engineering
Technology Investment
Automation impact:
- Voice AI for orders
- Digital ordering channels
- Self-service options
- Kitchen automation
SPLH Analytics
Tracking Approaches
Time-based analysis:
- Daily SPLH tracking
- Daypart breakdown
- Day-of-week patterns
- Seasonal trends
Comparative analysis:
- Location benchmarking
- Period-over-period
- Before/after changes
- Peer comparison
Key Reports
Operational dashboards:
- Current SPLH
- Trend over time
- Contributing factors
- Improvement opportunities
SPLH vs. Related Metrics
Labor Cost Percentage
- Labor %: labor cost as percent of sales
- SPLH: sales generated per labor hour
- Inverse relationship
- Both measure efficiency differently
Revenue per Employee
- Per employee: annual revenue / headcount
- SPLH: more granular (hourly)
- SPLH more operational
- Per employee more strategic
Transactions per Labor Hour
- Measures count, not value
- SPLH includes check average impact
- Both operational indicators
- SPLH more comprehensive
SPLH Considerations
Quality Balance
Don’t sacrifice:
- Customer experience
- order accuracy
- Food quality
- Staff wellbeing
SPLH vs. quality:
- Not purely maximize SPLH
- Balance with customer metrics
- Sustainable efficiency
- Long-term thinking
Regional Variation
Market factors:
- Wage rates differ
- Revenue levels differ
- Acceptable SPLH varies
- Local benchmarks matter
Seasonal Patterns
Volume fluctuation:
- High season SPLH different
- Staffing lag affects SPLH
- Plan for patterns
- Evaluate appropriately
Common SPLH Mistakes
Over-Optimization
Risks:
- Understaffing hurts service
- Burnout increases turnover
- Quality suffers
- Customer experience damaged
Wrong Comparisons
Invalid benchmarks:
- Different markets
- Different concepts
- Different cost structures
- Different volumes
Short-Term Focus
Sustainability:
- One-time cuts not lasting
- Systemic improvement needed
- Technology investment worthwhile
- Long-term thinking
Common Misconceptions About SPLH
Misconception: “Higher SPLH is always better.”
Reality: SPLH must be balanced with service quality, customer experience, and staff wellbeing. Extremely high SPLH might indicate understaffing that hurts long-term performance. Optimal SPLH varies by brand and market.
Misconception: “SPLH improvement means cutting staff.”
Reality: SPLH can improve through revenue growth, not just labor reduction. Voice AI enables both—reducing order-taking labor while improving upselling and throughput. The goal is efficiency, not just headcount reduction.
Misconception: “Voice AI’s labor savings are theoretical.”
Reality: QSRs deploying Voice AI are removing 3-8 hours of order-taking labor per day per location—real hours that either aren’t scheduled or are redeployed to other tasks. The savings are measurable and substantial.