Snowmaking accounts for roughly 17% of daily operating costs at larger Swiss resorts (those above CHF 25M revenue), according to Vorkauf et al. 2022 in the International Journal of Biometeorology. It is one of the largest controllable line items on a resort P&L — and unlike most cost lines, it is the one that also determines whether the resort has a product to sell.
That dual character is what makes snowmaking difficult to manage as a cost. Cut it and you protect margin while eroding the asset. Spend into it and you protect the season while compressing margin. Most cost levers on a mountain do not carry that trade-off. This piece sets out what the line item actually contains, what the published data says it costs, and where the remaining efficiency sits once the conventional levers are exhausted.
Key takeaways
- Snowmaking runs to about 17% of daily opex at Swiss resorts above CHF 25M revenue (Vorkauf et al. 2022).
- In Canada, snowmaking has been reported at roughly 50% of the electricity bill, and about 67% of energy use between October and January — the cost is concentrated in exactly the months that decide the season.
- Austrian snowmaking consumes 281 GWh and ~51 Mm³ of water per season — 0.46% of national electricity, ~2,900 m³/hectare, ~130 g CO₂ per skier visit (Aigner, Steiger & Mayer 2026).
- The line item is not discretionary: skiing is over 85% of revenue and about 95% of profit for major operators, and terrain coverage is already ~90% in Italy and ~75% in Austria.
- The four standard efficiency levers — renewables, water reclamation, automation, demand reduction — all reduce the cost per m³ or its carbon. None of them reduce the m³ required.
- Chemistry is the lever that moves the denominator. SL6733's modelled +3 °C wet-bulb advantage targets water and energy per m³ of snow directly. Modelled, pre-commercial.
What does the 17% figure actually measure?
It measures snowmaking's share of daily operating costs at large Swiss resorts. The source is Vorkauf et al. 2022, a study centred on Andermatt in the International Journal of Biometeorology, which found snowmaking at approximately 17% of daily opex for resorts above CHF 25M in revenue. It is a share of running costs, not of total cost including capital.
Two qualifications keep the figure honest. It is drawn from Swiss operations at a particular scale, so it is a well-sourced reference point rather than a universal constant — a low-elevation resort with thin natural cover will sit above it, a high-altitude resort with reliable natural snow below. And it excludes the capital cost of the snowmaking plant itself: the pumps, compressors, pipe, reservoirs, and guns are capex, amortised separately. The 17% is what it costs to run the system, on top of what it cost to build.
What is inside the line item?
Four things, in roughly this order of weight:
- Electricity — pumping water uphill, compressing air, and running fan guns. The dominant component in most cost stacks.
- Water — abstraction, storage, and in many jurisdictions the permitting and rights that go with it. Sometimes near-free at the meter, rarely free in practice.
- Labour — snowmakers, night shifts, and the systems staff who run the plant through the marginal windows.
- Maintenance — a plant that runs hard for a hundred nights a year and sits idle for two hundred and sixty.
The concentration is the part that catches CFOs. Snowmaking has been reported to consume roughly half of a Canadian resort's electricity bill, and about 67% of its energy between October and January. The load lands in the pre-season and early-season months — before the revenue does. It is a cash-flow shape as much as a cost shape: the resort pays for the season before it sells it.
What does that look like at national scale?
Large, and rising. The best recent accounting is Austrian: Aigner, Steiger & Mayer 2026 put Austrian snowmaking at 281 GWh per season — 0.46% of national electricity consumption — and about 51 Mm³ of water, roughly 2,900 m³ per hectare, or about 130 g CO₂ per skier visit.
| Metric | Austria (Aigner et al. 2026) | Canada (Steiger et al. 2024) | |---|---|---| | Electricity per season | 281 GWh (0.46% of national) | 478,000 MWh | | Water per season | ~51 Mm³ | 43.4 Mm³ | | Snow produced | — | 42 Mm³ | | Carbon | ~130 g CO₂ / skier visit | 130,095 t CO₂ | | Projected demand growth | — | +55–97% by 2050 |
The Canadian figures come from Steiger et al. 2024 in Current Issues in Tourism, which projects snowmaking demand rising 55–97% by 2050 and frames the trajectory as potential "(mal)adaptation" — more energy and water spent to hold the same product line. That is the strategic problem in one word. If demand for snowmaking grows faster than the efficiency of making snow, the line item grows with it, and the adaptation eats the margin it was meant to protect.
The French Alps data points the same direction: Spandre et al. 2019 models snowmaking water demand rising from 13 Mm³ to 42 Mm³ and 54 Mm³ across warming scenarios.
Can a resort simply spend less on it?
Not without spending the asset instead. Skiing generates more than 85% of revenue and around 95% of profit for major operators, and snowmaking is what makes skiing available on a schedule. Cutting the line item cuts open days, and open days are not evenly valuable — missing a major early-season opening around Thanksgiving or Christmas can cost on the order of 20% of annual revenue (industry estimate).
Coverage confirms the point: roughly 90% of skiable terrain in Italy and about 75% in Austria is already served by snowmaking (2024, Statista — directional figures). At that penetration, snowmaking is not an enhancement to the product. It is the product's delivery mechanism, and the cost of running it is closer to cost-of-goods than to discretionary spend. We work through what a marginal open day is actually worth in the value of one open day, and the per-unit cost build in snowmaking cost per acre-foot.
Which efficiency levers actually move the number?
The four conventional ones all attack the cost or carbon of each cubic metre. That is worth doing, and every serious operator is doing it. But it is worth being precise about what each one does and does not touch:
| Lever | What it reduces | What it does not reduce | |---|---|---| | Renewable power | Carbon and, over time, cost per kWh | The kWh required | | Water reclamation and storage | Abstraction pressure, water cost | The m³ of water required | | Automation and control systems | Waste — guns running outside the viable window | The physics of the window itself | | Demand reduction (grooming, depth targets) | Total m³ demanded | Cost per m³ produced | | Additive chemistry | Water and energy per m³ of snow | Not a substitute for the above — it compounds with them |
The first four are levers on the numerator or on scheduling. None of them change how much water and electricity it takes to convert a given wet-bulb temperature into a cubic metre of snow. That conversion efficiency is set by physics — specifically by how far the ambient wet-bulb sits from the temperature at which a droplet will reliably freeze and stay frozen. We set out the mechanics in the wet-bulb temperature guide, and the broader argument in chemistry as the missing fifth lever.
Where does chemistry fit on a P&L?
On the denominator. An additive that shifts the effective wet-bulb window changes how many cubic metres of snow a given night of pumping and compressing yields — and whether marginal nights produce anything at all. SL6733 is a two-component polymer system dosed at roughly 6–7.6 ppm: an ultra-high-molecular-weight anionic poly(acrylamide-co-sodium acrylate) that inhibits ice recrystallization, plus a cold-water-swelling starch nucleant.
The modelled operator outcome is a +3 °C wet-bulb advantage, which translates to roughly 300–500 additional snowmaking hours per season and a modelled $2.4–2.8M EBITDA uplift at a mid-sized EU resort. The same advantage can be taken two ways — as approximately +50% more snow, or as roughly −50% water and energy for the same snow. Operators choose the setting on the dial that fits their constraint: a water-stressed resort takes the water saving, a coverage-constrained resort takes the snow.
Every figure in that paragraph is modelled, and SL6733 is in pre-commercial EU pilot phase. They are engineering and financial models, not audited commercial results, and we label them that way consistently. There are also markets where the question does not arise: Austria and Bavaria prohibit all additives in snowmaking water by law, SL6733 included. The addressable regulated markets are France, Italy, Switzerland, and non-Alpine geographies — the detail is in the country-by-country rules.
What this means for the P&L conversation
The three facts that matter to a finance function: the line item is large (~17% of daily opex at scale), it is front-loaded into the months before revenue arrives, and it is projected to grow 55–97% by 2050 on current trajectory. The conventional levers make each cubic metre cheaper and cleaner. Nothing in the standard toolkit makes the snow itself cheaper to form.
That is the specific gap chemistry addresses, and it is why an additive is priced as a share of the operating value it creates rather than at a per-kilogram markup. A dose measured in parts per million looks trivial priced as a commodity and is not trivial priced against 17% of daily opex. We cover the reasoning in how to reduce snowmaking costs.
If you want to model what a +3 °C modelled wet-bulb advantage would do to your own snowmaking line — in your water regime, your power tariff, and your season shape — request a pilot or send us a message.
Cost shares vary by resort, elevation, and market; the 17% figure is specific to Swiss resorts above CHF 25M revenue (Vorkauf et al. 2022). SL6733 operator outcomes are modelled and pre-commercial; EU pilots are targeted for 2026/27. DeepSnow is the platform brand of SnowLabs Limited (Ireland); DeepSnow Srl (Italy) is in formation.