Key Takeaways
- Use four capacity denominators—licensed, physical, staffed, and paid FTE—and label the one behind every utilization figure.
- National tuition data describe affordability and broad variation; center valuation requires realized child-level revenue and current local evidence.
- Required staffing follows ratios and schedules, so a labor percentage cannot substitute for a coverage grid.
- Classroom and monthly comparisons are more diagnostic than one annual center-wide average.
- No representative public dataset supports universal child care targets for occupancy, fully loaded labor, rent, margin, turnover, or value per slot across all models.
A benchmark is a defined comparison
A transaction benchmark should fit one of three classes. A subject benchmark compares the center with its own prior months, budget, rooms, or sites. A peer benchmark compares a documented cohort with similar model, size, geography, age mix, and accounting. A context statistic describes the wider industry but may not be suitable for underwriting. Label the class before interpreting the result.
The source record should include publication and data year, geography, provider definition, sample or coverage, numerator, denominator, exclusions, and retrieval date. If the report says “average price,” determine whether it refers to a mean, median, provider charge, family payment, center setting, family home, age group, or full-time schedule. If an operator says “occupancy,” ask whether the denominator is licensed seats, operational seats, or another measure.
Use benchmarks to generate questions, not to replace evidence. A labor ratio above a peer statistic might reflect infants, longer hours, benefits, low enrollment, or inefficient scheduling. Tuition below a state average might reflect part-time schedules, an older data year, a different county, or subsidy. The comparison becomes useful when the cause is identified.
| Metric | Required numerator | Required denominator | Essential qualifier |
|---|---|---|---|
| Licensed utilization | Enrolled or paid FTE | Licensed capacity | Age, date and schedule |
| Staffed utilization | Paid enrollment FTE | Seats current staff can serve | Grid and applicable rule |
| Tuition realization | Collected tuition and eligible fees | Contracted gross billings | Discounts, bad debt and period |
| Labor ratio | Defined labor cost | Defined realized revenue | Included benefits, owner and contractors |
| Revenue per paid FTE | Realized revenue | Average paid FTE | Payer, age and service period |
| Classroom contribution | Room revenue less defined direct cost | Room or service month | Allocation method and exclusions |
Enrollment needs more than one count
Licensed capacity is the maximum approved under stated regulatory conditions. Physical capacity reflects the rooms and usable setup. Staffed capacity is the number the scheduled qualified workforce can serve within current ratios, group sizes, and role rules. Enrolled headcount counts children, while paid full-time-equivalent enrollment reflects service schedules. Attendance measures presence. Each supports a different decision.
A center with 100 licensed places, 80 staffed places, 76 paid FTEs, 90 enrolled children, and 68 average daily attendees can be described as 76 percent utilized against license or 95 percent utilized against staffed capacity. Neither is inherently false; either becomes misleading when its denominator is omitted. For value and expansion, show the entire bridge and what it costs to activate additional capacity.
Measure by classroom and month. Annual average enrollment can conceal a graduation cliff, summer school-age swing, chronic infant vacancy, or room closure. Record starts, withdrawals, schedule changes, age transitions, discounts, payer changes, and vacancy days. Explain whether an open seat lacked demand, qualified staff, physical approval, or a matching schedule.
Waitlists are not enrolled children. De-duplicate siblings and repeated inquiries, preserve desired start date, age, schedule, price acceptance, contact date, and follow-up status, and calculate historical conversions. A family seeking an infant seat next month does not support a vacant preschool seat next year. Enrollment and waitlist diligence provides the operating review.
Occupancy has no universal national target
No current representative public dataset was located that defines and reports occupancy consistently across independent centers, family homes, nonprofits, franchises, employer-sponsored programs, and multi-site groups. Public-company disclosures apply to named operators and may use proprietary definitions. Listing claims are not an unbiased sample and often omit denominators.
That evidence gap matters. Publishing one “healthy occupancy” percentage would encourage owners to compare licensed seats with another operator's operational seats. It would also ignore the stepwise staffing economics of classrooms. Instead, compare the subject with its own staffed utilization history, budget, inquiry conversion, retention, and documented local supply.
For transaction analysis, report the twelve- or twenty-four-month classroom series and annotate rate changes, staffing gaps, public-program shifts, and unusual closures. Calculate both licensed and staffed utilization. Tie paid FTE to billing and collections. An occupancy improvement that did not improve revenue or contribution needs explanation.
Tuition comparisons must preserve age and place
Child Care Aware of America publishes state price and supply research, and the U.S. Department of Labor Women's Bureau maintains the National Database of Childcare Prices with county-level estimates derived from state market-rate surveys. These sources are valuable and methodologically bounded. Survey years and methods vary, data can lag, and estimates distinguish ages, settings, and price concepts.
Do not take a national average and call it the market rate for an infant in a particular county. Use the closest current age- and setting-specific source, inspect methodology, and supplement it with verifiable local center offerings. Record hours, meals, registration and supply fees, discounts, schedule, school calendar, and included services. A website price may be stale or may not reflect what current families pay.
The subject benchmark is realized tuition. Sum contracted gross billing, then show sibling and employee discounts, scholarships, credits, subsidy limitations, copays, write-offs, refunds, and bad debt. Reconcile net receipts to the bank. Compare realized revenue per paid FTE by room over time, taking care with partial months and annual fees.
Tuition growth is not automatically upside. Review notice requirements, recent changes, withdrawal after increases, competitor responses, household affordability, public alternatives, and whether higher tuition requires wages, curriculum, meals, or facility investment. Tuition pricing and collections explains the evidence trail.
Labor starts with required coverage
All states regulate center ratios, but the federal 2020 licensing trends study shows that requirements varied materially by state and child age, and group-size regulation varied too. That historical study is context; the current state rule and license conditions control the center. Translate them into a time-based staffing grid.
Map children present or scheduled by room at short intervals, then required qualified adults, actual scheduled staff, breaks, planning, opening and closing, transport, food, director time, floaters, leave, and vacancies. Reconcile hours and employees to timecards and payroll. This determines whether current cost is sufficient, excessive, or temporarily supported by owner labor.
BLS reports a May 2025 national median hourly wage of $16.82 for childcare workers and a separate May 2025 median annual wage of $38,140 for preschool teachers. Occupational definitions differ, and both are national. Use state and metro data for context, then actual payroll, current job postings, offers, benefits, credentials, and hiring outcomes for underwriting.
Fully loaded labor should state what it includes: wages, overtime, bonuses, payroll taxes, workers' compensation, health and retirement benefits, paid time off, substitutes, contractors, training, recruiting, and owner replacement. A reported “labor percentage” that omits half those items cannot be compared with one that includes them.
Why payroll-to-revenue can mislead
Payroll divided by revenue compresses several operating decisions into one ratio. A center can lower the ratio by raising tuition, filling seats within existing staffing bands, understaffing, deferring a hire, using unpaid owner coverage, or misclassifying contractors. Those paths do not have the same quality or durability.
Census industry aggregates can provide payroll and revenue context for an employer-firm population, but payroll is not total labor cost and the industry includes taxable and tax-exempt providers of different sizes and models. An aggregate ratio is not a target for a single site. Compare consistently defined subject labor with consistently defined subject revenue.
Use a labor bridge instead: required classroom hours, actual classroom hours, coverage variance, wage by role, payroll burden, benefits, shared support, administration, director, and owner replacement. Then connect additional labor to capacity or service. A qualified hire that opens a full room can improve both cost and revenue; a percentage alone misses the causal relationship.
Classroom contribution is the useful middle layer
Center-wide profit is necessary, but classrooms explain how it is produced. Assign directly attributable tuition, subsidy, fees, classroom wages and burden, food, and consumable supplies. Keep common occupancy, administration, insurance, and central costs separate unless a transparent allocation is needed.
Contribution is not GAAP profit and should not be presented as such. It is a managerial view for questions: Which room loses the most when a seat opens? Which closed room becomes feasible with one hire? Does a rate increase cover its wage effect? Which age transition creates an enrollment gap? Use actual records and state rules in every case.
Avoid treating contribution from one period as permanent. Child age transitions, teacher turnover, public school calendars, subsidy authorizations, and tuition notices shift the room. Review monthly patterns and a future roster with known graduation dates. A transaction model should show the opening twelve months, not merely trailing averages.
Revenue-per-slot and per-child rules need guardrails
Revenue per licensed slot divides defined revenue by the license maximum. It can be useful for detecting a data problem or comparing one site with itself, but it punishes unused capacity and ignores age and schedule. Revenue per enrolled child depends on whether “child” means headcount, average FTE, month-end census, or attendance. Neither measure establishes value.
Never multiply a national per-slot figure by a subject license to estimate sale price. No authoritative public dataset supports a universal value per child or licensed slot across models. Value is grounded in normalized transferable earnings, supported assets, real estate where included, and transaction evidence. Per-slot and per-child rules gives the valuation caveats.
If a comparable calculation is used, align revenue definition, period, ages, schedule, payer mix, geography, staffed capacity, and facility structure. Explain differences. A lower revenue-per-license-slot center may have expansion capacity; a higher one may be physically constrained. The metric becomes informative only after the operating facts are known.
Build a center scorecard that can be audited
Use a monthly table with paid FTE by room, staffed capacity, licensed capacity, realized revenue, gross billing, collections, receivable aging, classroom payroll hours, fully loaded payroll, vacancies, overtime, starts, withdrawals, and room closures. Add short annotations for rate changes, grants, weather closures, subsidy delays, or staff disruptions.
Every metric should link to a source export. Roster numbers tie to agreements and billing; billing ties to receivables; receipts tie to the bank; staffing ties to schedules, credentials, and payroll. Freeze the version used for a transaction. A dashboard without field definitions or source retention is not diligence evidence.
Benchmark first against the center's prior period and budget. Then compare rooms within the center where definitions match. Use external data last, with documented limitations. This order produces explanations before rankings and keeps the decision anchored in controllable facts.
Apply benchmarks to valuation cautiously
Benchmarks support normalization and risk assessment. They can show that current tuition differs from documented local evidence, a room has persistent vacancy, payroll hours do not match scheduled needs, or receivables have lengthened. They cannot set a multiple automatically or replace a buyer's cash-flow model.
Translate each variance into mechanism, cost, timeline, and evidence. If tuition is below comparable offerings, determine the notice, family response, and service investment required to change it. If licensed utilization is low, identify staff, demand, and room work needed. If labor is high, determine whether it protects compliance, reflects age mix, or contains inefficiency.
Do not count an improvement in both earnings and multiple without evidence. A seller's upside case belongs beside historical performance, not inside it. A buyer's downside should be tied to an identifiable risk, not a generic haircut. The result should be a range with assumptions, not false precision.
Frequently asked questions
What is a good occupancy rate for a daycare?
There is no defensible universal target across center models, age mixes, schedules, states, and staffing conditions. Define the denominator first: licensed, physical, staffed, or paid full-time-equivalent capacity. Compare each classroom with its own history and documented local opportunity, then explain vacancies by age, schedule, duration, price, staffing, and season.
What percentage of child care revenue should labor be?
No representative public national target was found that consistently includes wages, payroll tax, benefits, contractors, owner labor, and shared management across all provider models. Build required coverage from current ratios and schedules, reconcile it to payroll, and compare the result with realized revenue. A percentage cannot determine whether the center is safely staffed.
Can national average tuition be used in a valuation?
Not as the subject center's rate. National prices combine states, ages, settings, schedules, and collection methods. Use child-level realized tuition, current local age-specific evidence, subsidy schedules, and documented competitor offerings. State the year and source for external data and test whether families actually accepted the center's recent price changes.
How should part-time children count in enrollment?
Keep headcount and paid schedule separate. Convert schedules into a clearly defined full-time equivalent only when that helps compare occupied service units, and disclose the conversion. Two children alternating days may fill one seat operationally while remaining two family relationships, two billing records, and different attendance and transition risks.
Is revenue per licensed slot a useful benchmark?
It is a rough cross-check only when the period, revenue definition, licensed capacity, age mix, and schedule are clear. It penalizes intentionally unused or unstaffed capacity and can reward a center whose license is constrained. Use staffed capacity, paid enrollment, classroom contribution, and normalized earnings alongside it rather than applying a national value per slot.
How should a transaction team document a benchmark?
Record the exact metric, numerator, denominator, period, geography, provider population, sample size when available, source URL, retrieval date, and limitation. Then state whether it is context, a subject calculation, or a valuation input. If definitions do not match the center, treat the difference as a question instead of forcing a comparison.