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Suggested Measures are a curated set of energy conservation measures (ECMs) that Abisko recommends for a given property, based on its property type and climate zone. Each suggested measure includes estimated electric and gas savings, implementation cost, annual cost savings, and payback period, so property teams can quickly compare options and prioritize what to implement first.
Suggested Measures are modeled estimates based on general industry-typical savings ranges and directional climate logic, not measurements taken from the specific property. Users should treat them as a starting point for evaluation, not a substitute for a site-specific audit.
Property → PARC → Measures

Save Suggested Measures

Abisko generates Suggested Measures automatically for any property in your portfolio:
  1. Click N suggested measures next to the search box
  2. From the panel that opens, check the measures that you would like to save as Proposed Measures for a property.
  3. This will save the suggested measure to the property with the following defaults:
    1. Status: Proposed
    2. Completion Date: 12/31/2029 (impacts take effect in 2030)
    3. Estimated Costs & Annual Savings: Calculated based on property size

Edit & Analyze Measures

After saving a suggested measure, users can edit the measure to change any of the default attributes, including the estimated implementation costs, energy and cost savings. Users can also analyze the potential impact of suggested measures on decarbonization pathways in the context of different BPS policies and CRREM. Suggested measures are treated exactly the same as any other proposed measure. Click here to learn more.

Advanced AI-based Analysis

Ask Claude, or any AI client connected to Abisko’s MCP, to retrieve and analyze suggested measures tracked in Abisko. Claude will retrieve a property’s tracked systems, completed measures, historical energy and emissions data, and much more to provide users a comprehensive energy efficiency or decarbonization plan that fits their budget and priorities. Click here to learn more.

Methodology

Abisko generates Suggested Measures using a combination of property attributes, climate data, and modeled savings logic:
  • Property type matching: Each property type is mapped to a functional category (for example, Office, Retail, Multifamily, Healthcare, Warehouse) that determines which ECMs are most applicable and how they’re prioritized.
  • Climate zone adjustment: Each property’s climate zone, including moisture subzone (humid, dry, or marine), scales expected savings. Electric savings scale with a cooling factor that increases in hotter zones; gas savings scale with a heating factor that increases in colder zones. Zone 1 (very hot) assumes no heating load, so gas savings are set to zero. Image
  • Suggested measures: A core set of suggested ECMs is selected per property category. A lighting retrofit measure is always included, regardless of property type, along with additional, general lighting and plug-load control measures (e.g. occupancy sensors, daylight controls, computer sleep-mode settings). Other measures are selected according to climate zone. For example, on-site renewable energy in hotter zones, smart building technology in mixed zones, and wall/roof insulation in cold zones.
    Suggested measures do not change based on other property attributes, systems, or completed measures. For more tailored analysis, users can leverage Abisko’s AI-based decarbonization features. Click here to learn more
  • Cost and savings modeling: Implementation cost and annual cost savings are estimated in dollars per square foot, using category-level baseline energy cost intensities and implementation cost ranges. Costs and savings vary by the specific attributes most often associated with a particular measure and property type (e.g. refrigeration equipment for a supermarket versus service hot water systems for a hotel).
  • Prioritization: Suggested measures are ranked by simple payback period (implementation cost divided by annual cost savings), from fastest to slowest.