Most facilities that stock menstrual products are running an emergency-reorder routine with an inventory label on it. Someone notices an empty unit, someone places a rush order, and the days in between are a stockout that nobody logged.

Planning refill inventory replaces that cycle with numbers you can defend in a budget meeting. This guide covers the arithmetic behind stocking the feminine care dispensers already on your walls: demand estimates, par levels, reorder points, and restocking cadence.

How Refill Inventory Planning Works

The planning problem is matching supply to demand you cannot directly observe. Usage is privacy-sensitive, unevenly distributed across restrooms, and invisible until a dispenser runs dry. Overstock and you tie up closet space and cash. Understock and custodial staff learn about it from a complaint.

Every workable plan is built on three variables: the population served, the consumption rate per user, and the restock interval. Everything in this guide is a method for pinning those three down.

One distinction before the math. Inventory planning covers par levels and replenishment cadence, the questions of how much and how often. Vendor selection, contract pricing, and procurement workflow are separate decisions. Get the inventory numbers right first, because they tell you what any vendor arrangement needs to deliver.

Estimating Menstrual Product Demand by Facility Type

The estimation chain runs from total occupants to a menstruating population estimate, then through cycle frequency and products used per cycle to a monthly consumption figure. Peer-reviewed work anchors the first step: about 26% of the global population menstruates in a given month. For a mixed-gender U.S. building, 25 to 30% is a reasonable planning adaptation of that figure.

For the second step, peer-reviewed work on period poverty in the United States puts consumption at 10 to 35 products per cycle. That spread is too wide to budget against, so treat 15 to 20 products per cycle as a starting planning range and tighten it against your own counted usage.

Population estimates establish the potential population served. They do not forecast dispenser consumption. Actual use of facility-provided menstrual products varies substantially by setting and population. In some schools and community facilities, facility-provided products may cover a meaningful share of users' needs. In many corporate workplaces, dispensers serve mainly as a convenience or emergency resource for users who carry their preferred products.

Run the arithmetic on a 500-person building anyway, as a reference for potential total usage. At 26%, roughly 130 occupants are menstruating in a given month. At 15 to 20 products each, potential total consumption lands between 1,950 and 2,600 products monthly. That range describes total product usage among occupants. Dispenser draw will run well below it.

Treat the population figure as an initial planning reference only. The share your dispensers supply depends on your access model and setting, which is why the variables covered below matter more than the estimate itself. Track actual dispenser usage for 60 to 90 days, then set par levels and reorder points from measured results.

Facility type shifts the math before any of those variables apply.

Schools and Universities

Estimate from enrollment, and expect the menstruating share to run well above general-population averages because the population concentrates in a narrow age band. Demand follows the academic calendar: near zero over summer, then a spike in the first weeks of term when restocking has to be ready before students are.

Offices and Corporate Campuses

Headcount and daily occupancy are different numbers, and hybrid schedules can put real demand 30 to 50% below a headcount-based estimate. Track occupancy alongside usage. Floor-level variation matters too, since departments rarely distribute evenly across a building.

Venues, Stadiums, and Public Spaces

Plan demand per event; a monthly figure hides everything that matters here. Attendance and event type change the audience mix substantially between a concert and a sporting event. The harder constraint is peak load: most consumption happens in a 90-minute window, which makes per-unit dispenser capacity the binding constraint for a venue.

Healthcare and 24-Hour Facilities

Continuous occupancy layers patients, visitors, and staff into one building, and the expectation of always-stocked availability is higher than anywhere else. That expectation translates directly into more safety stock, which we cover below.

Consumption Variables That Break Estimates

Most plans fail after the initial estimate, when a variable the spreadsheet never captured shifts the consumption rate.

The largest is the access model. Removing payment typically multiplies consumption several times over, so a facility converting from coin-operated to free-vend dispensing has to rebuild its consumption baseline from scratch. Scaling the coin-operated history upward produces a number with no relationship to what free access draws.

Product mix is the second trap. The demand split between vended tampons and pads for dispensers varies by age group and region. A single assumed ratio stocks out one SKU while the other accumulates in the closet.

Three more variables deserve a line in any plan. A newly installed or newly visible dispenser sees an initial usage surge that settles well below the first month's rate. Unmonitored high-traffic public restrooms see some bulk-taking. Occupancy cycles move demand too: academic terms, event seasons, and seasonal staffing all show up in the consumption log.

The practical rule: after any change to access model, dispenser placement, or occupancy, run a 60- to 90-day observation period before treating a consumption rate as reliable. Ninety days captures seasonality; thirty does not.

Setting Par Levels and Reorder Points

Three numbers run the whole system, and they are frequently confused. The par level is the target on-hand quantity you order up to. The reorder point is the lower trigger quantity: when stock crosses it, you place the order. The reorder quantity is how much you buy, usually rounded to case packs.

The reorder point formula in practical terms:

Reorder point = (average daily usage × lead time in days) + safety stock

Average daily usage comes from counted data: units consumed divided by days in the period. Lead time is your measured order-to-shelf time, meaning order placed through product received, shelved, and accessible. Use your own measured figure, since the distributor's quoted transit time excludes your receiving and stocking, and that gap is where stockouts live.

Safety stock depends on two things only: demand variability and supplier lead-time reliability. A workable rough cut is 25 to 50% of your lead-time demand. Use 25% for stable, predictable buildings and 50% where usage spikes or the supplier wobbles. Event venues and schools sit at the high end.

Statistical safety-stock formulas exist, but the rough cut is close enough for most facility programs, and it runs in a shared spreadsheet.

The Three Inventory Layers

Most facilities plan one number when they need three. Dispenser capacity is the first inventory layer, the janitorial closet is the second, and the central stockroom is the third. Each needs its own par level, because each has its own restock interval and its own failure mode.

A copyable structure for the closet layer:

The figures are illustrative; substitute your counted usage and measured lead time. One row per stocking location, with the par and reorder point derived from that location's own numbers.

Dispenser capacity itself is an inventory lever. High-capacity units stretch the restock interval and shrink the closet inventory a facility has to carry between rounds. Our SD9000 high-capacity dispenser holds approximately 50 tampons and 24 pads, helping extend restocking intervals in high-traffic restrooms. Divide that capacity into a location's monthly usage before standardizing on a platform.

Comparing Restocking Cadence Models

Four cadence models cover nearly every facility program. Each fits a specific building profile, and each fails in a specific way.

Fixed-Schedule Rounds

Every unit gets restocked on a set interval regardless of level. This fits predictable, evenly used buildings, and it is the simplest model to staff and audit. The failure mode is mismatch: low-traffic restrooms get over-serviced while high-traffic ones run dry between rounds. Labor cost is steady and easy to budget.

Demand-Triggered Replenishment

Restocking happens when a threshold is hit, reported through inspection logs, staff reports, or QR-code requests. This fits buildings with wide variance between restrooms. The failure mode is reporting discipline: menstrual product outages are chronically under-reported because users rarely complain about an empty dispenser. Labor is efficient when reporting works and invisible when it fails.

Hybrid Zone-Based Servicing

Restrooms get tiered by traffic, and each tier gets its own interval. For multi-floor or multi-building portfolios this is usually the practical middle ground. Tier using door counts, prior consumption data, and proximity to high-traffic areas like lobbies, gyms, and event spaces. Labor concentrates where usage does.

Vendor-Managed and Service-Contract Models

A third party handles stocking, and the facility pays for a service and hands off the inventory work. Compare cost predictability, control over product quality, and data visibility. The trade-off is real: less labor, but less granular usage data of your own.

When the vendor sets your par levels and controls order timing, you lose visibility into your own consumption and the volume leverage that comes with it. A managed service should hand your usage data back to you, and that belongs in the contract.

Consolidating SKUs and Storage Requirements

The smallest viable SKU count is the cheapest inventory to run. Fragmentation costs show up as mismatched dispenser models with incompatible refills, dead inventory for retired units, and a closet where nothing is interchangeable.

That makes dispenser standardization an inventory decision with cost-of-ownership stakes.

One dispenser platform across a portfolio collapses several refill SKUs into one or two. Non-proprietary hardware does the same work from the dispenser side. Our SD2000 accepts most retail-style sanitary napkins rather than one branded refill, and our other vending-style dispensers take standard No. 4 vending box refills, so a facility can source compatible product from more than one supplier.

The Maxithins MT48044C is one retail-style napkin we stock that runs well in the SD2000. We sell it in bulk cases of 288, packed 24 per pack and 12 packs per case. We do not recommend panty liners or very thin pads for the SD2000.

Refill lock-in works the other way. A dispenser that only accepts a proprietary refill hands SKU control to the manufacturer, and the SD9000 is built to take standard products instead of a branded refill program.

Storage math is cases per month times months of coverage, checked against the physical space and access constraints of your janitorial closets. A vending-tube case like the Tampax T500 holds 500 tampons, so a location consuming 250 a month carries two months of coverage per case.

Follow each manufacturer's storage and shelf-life guidance for the refill products you stock, since recommendations vary by product and packaging. The practical ceilings on bulk purchasing are closet space and cash. Even so, holding more than 3 to 6 months of coverage usually means the money is better spent elsewhere.

One more consolidation move: disposal-side consumables deplete at a rate tied to product usage, so sanitary napkin disposal bags and receptacle liners belong in the same reorder cycle as refills.

Pairing a liner SKU like the sanitary napkin receptacle liner case of 6 to the same order day as your refill SKUs keeps the disposal chain from stocking out on its own schedule.

Stocking Obligations Under State and Local Mandates

A growing number of states require schools and certain public buildings to provide free menstrual products, a pattern we covered when new legislation for free menstrual products in schools began rolling out. The operational consequence is blunt: a legal minimum availability standard turns a stockout into compliance exposure.

A mandate changes the plan in three specific ways. Free-vend consumption baselines apply from day one, since mandates require free access. Coverage counts may specify how many restrooms per building must be stocked, which multiplies your stocking locations.

Documentation of stocking also becomes part of the program, because an empty or jammed unit in a covered restroom is a compliance gap even when the closet is full.

Requirements vary enough by jurisdiction, and change often enough, that we recommend verifying your own state and local rules directly, since published lists date quickly.

ADA considerations run alongside the mandates. Accessibility standards govern mounting height, reach ranges, and operable-part force, which constrains where units can go and which models a facility can standardize on. Our guide to menstrual product dispenser types, features, and accessibility standards covers the dispenser-selection side of that decision. Mounting dimensions and rough-in details for each model live on our specifications page.

Tracking Usage Data and Measuring the Plan

You only need four metrics: stockout incidents per location per month, refills consumed per location, labor hours per restock round, and cost per occupant per month. Anything beyond those four is optional.

Data capture scales in sophistication: paper inspection logs, digital checklist apps, QR-code reporting, and sensor-equipped dispensers. The cost-benefit cliff arrives early, and consistent manual logs deliver most of the value.

A minimal sheet with date, SKU, location, opening count, and closing count takes about an hour a week across a few buildings.

Recalculate par levels quarterly, and immediately after any change to occupancy, dispenser type, or access model. Thirty days of new data is enough to flag an emerging change. Establishing a reliable new baseline, and resetting a par level from it, takes the full 60- to 90-day window.

Two diagnostic signals tell you what to fix. Frequent stockouts in one location mean that location's par level is wrong. Consistently full dispensers at restock time mean the interval is too short and the labor is being spent on units that did not need it.

Planning Mistakes That Cause Stockouts

The failure modes repeat across facility types, and every one of them is checkable before it costs you a rush order:

• Estimating from total headcount when actual daily occupancy is lower

• Carrying one blended consumption rate across all restrooms

• Ignoring lead-time variability and holding no safety stock

• Failing to rebaseline after converting to free access

• Mixing dispenser models across a portfolio

• Treating receptacle liners and disposal bags as a separate, unlinked reorder

• Relying on user complaints as the outage-detection mechanism

The pattern behind all seven is the same: a number that was never counted. Track usage for 60 to 90 days, set par levels and reorder points from that data, and revisit them quarterly.

A facility that runs that loop treats menstrual products the way it already treats toilet paper and hand soap: a restroom consumable with a budget line and a plan behind it. If you are standardizing dispensers or consolidating refill SKUs across a portfolio, request a quote and we will spec the platform and case-pack math against your locations.