Choosing an EnPI for a Hotel with Variable Occupancy
Solstice Hotel has 210 rooms plus a spa, restaurant and on-site laundry. Its monthly EnPI is total electricity consumption in kWh. In 2023 the hotel used 3.9 GWh, compared with 3.7 GWh in 2022. The facilities manager says energy performance has worsened and proposes a staff awareness campaign. The sustainability lead notes that occupancy rose from 71% to 77% and heating degree days were 18% higher, while cooling degree days were 9% lower. Electricity is metered only at the main incoming supply; there are no sub-meters for laundry, kitchen or spa. The hotel has an objective to reduce energy consumption by 5% by 2025 against a 2022 baseline. A guest-complaint log shows hot-water complaints in summer. The general manager wants a defensible way to judge performance and to set next year's target without spending heavily on metering.
1. Critique the use of total electricity in kWh as the hotel's EnPI.
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Total kWh is an energy consumption metric, not a performance indicator, because it is not normalized for factors that drive consumption. Occupancy, weather, restaurant covers and laundry volume all affect electricity use. The 2023 increase from 3.7 to 3.9 GWh may reflect 6 percentage points more occupancy and 18% more heating degree days rather than worse management. Using raw kWh would penalize the hotel for higher business activity and could lead to wrong decisions, such as cutting services. A suitable EnPI could be kWh per occupied room-night, possibly with weather normalization, or separate EnPIs for guest rooms, kitchen, laundry and spa once data allow. The EnPI should be relevant, measurable and able to distinguish performance from activity. The current main-meter-only data limit normalization, so the indicator should be chosen with the data actually available.
2. How should the hotel judge 2023 performance and set a target for 2024?
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First, normalize the comparison. Use occupancy data to calculate kWh per occupied room-night for 2022 and 2023. If heating dominates, apply a weather correction using degree days; this is a simplified normalization, not a full regression. Compare like with like and state uncertainty. Then investigate the hot-water complaints and the spa/laundry loads with temporary metering or sub-metering before committing capital. For the 2024 target, set a performance target on the chosen EnPI, not only on absolute kWh. For example, target a 3% reduction in weather-normalized kWh per occupied room-night, plus an absolute cap to control total consumption. The 5% by 2025 objective should be restated on the same basis. Record the baseline, normalization method and assumptions. If data are insufficient, set an interim target to install sub-metering and improve the model.
3. What are the risks of a staff awareness campaign as the main response?
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Awareness can help, but it addresses behavior only and assumes the increase is caused by waste. If the rise is driven by occupancy, weather or an inefficient laundry or hot-water system, the campaign will not deliver the expected savings and may damage credibility when results do not appear. It also cannot be verified without normalization. A better response is to combine low-cost operational checks with analysis: review hot-water setpoints and circulation, laundry scheduling, kitchen equipment shutdown, and spa plant operation. Use the EnPI to test whether the campaign has an effect after adjusting for activity and weather. Set a measurement period and compare normalized results. Staff awareness should be one action in the action plan, not the sole explanation or solution.