Purpose of this article
This article explains how Scaler data coverage is calculated and where it appears in the platform. Scaler data coverage measures actual data completeness at the meter level, revealing gaps that aggregated methodologies like GRESB-aligned data coverage cannot detect.
Use this metric for: Data quality assurance, validation, identifying missing or incomplete meters, and prioritizing data collection efforts.
Applies to: Energy, water, and waste
Comparing Scaler and GRESB-aligned data coverage
Scaler provides two complementary data coverage metrics. Each serves a different purpose:
Aspect | Scaler data coverage | GRESB-aligned data coverage |
Primary purpose | Data quality and completeness | External reporting and benchmarking |
Used in | Data Collection Portal only | Analytics Portal, reports, GRESB submissions |
Calculation level | Meter level (weighted) | Asset level (aggregated) |
Resources covered | Energy, water, waste | Energy, water, waste |
Area perspective | Weighted by meter covered area, evaluated against total floor area per area type | Sum of covered areas across all categories ÷ Sum of maximum areas |
Time perspective | Meter-level time availability, weighted by meter size | Single date range per resource; Scaler uses widest range to maximize coverage |
Treatment of gaps | Explicit — gaps are visible | Aggregated — gaps may be hidden |
On-site renewables | Included | Excluded |
What it tells you | Underlying meter data is complete | Asset-level completeness for GRESB reporting |
When to use Scaler data coverage: QA, data validation, identifying missing meters, prioritizing data collection
When to use GRESB-aligned data coverage: GRESB submissions, portfolio analytics, external reporting, benchmarking
What Scaler data coverage measures
Scaler data coverage measures how complete consumption data is across all meters in an asset, taking into account:
- Area coverage: How much of the asset each meter represents
- Time coverage: How much of the reporting period each meter has data for
This metric is designed for data quality assurance, not external reporting. It provides visibility into gaps that aggregated methodologies like GRESB-aligned data coverage cannot detect.
Key principle: Scaler data coverage weights each meter's time availability by its covered area, then applies corrective factors when the full asset area or reporting period is not covered by meters.
Applies to: Energy, water, and waste equally
Where Scaler data coverage appears in Scaler
Scaler data coverage appears in the Data Collection Portal:
- Asset List → Energy/Water/Waste (Data/Time/Area coverage) → Critical option
- Meters & Consumption → Asset-level summary → Scaler Data coverage
- Meter List → Time coverage column (per meter)
Scaler data coverage is clearly labeled as "Scaler" or "Critical” to distinguish it from GRESB-aligned data coverage.
Why Scaler data coverage exists
An asset can show 100% GRESB-aligned data coverage while still having:
- Missing months on individual meters (hidden by GRESB's single date range constraint and Scaler's widest-range interpretation)
- Meters with non-overlapping time periods that together span the full year
- Gaps hidden by GRESB's aggregation methodology
Example: One meter has data for January only, another has data for December only. Scaler reports 100% GRESB time coverage (full year span), even though 10 months have no data.
This is expected behavior. GRESB's methodology is designed for standardized benchmarking, not meter-level data quality assessment.
Scaler data coverage exists specifically to make these gaps visible. It answers the question: "How complete is our underlying meter data actually?"
How Scaler data coverage is calculated
Scaler data coverage uses a meter-weighted approach that evaluates data completeness relative to the asset's total floor area.
High-level calculation logic
- Calculate the time coverage of each meter individually
- Weight each meter's time coverage by its proportion of the total covered area
- Apply corrective factors where the full asset area or reporting period is not covered by meters
This approach avoids double penalization when meters are missing both time and area coverage.
The formula
SCALER_DATA_COVERAGE = Σ(METER_WEIGHT × METER_TIME_COVERAGE) × CORRECTIVE_FACTORS
Where:
- Meter weight = Covered area of meter ÷ Total covered area of all meters
- Meter time coverage = Days with consumption ÷ Total days in reporting period
- Corrective factors = Adjustments for incomplete area or time coverage at asset level
Key variables used in this calculation
Input fields (meter configuration):
Area type
Covered area
Meter version start date
Meter version end date
Include in calculations
Subcategory
Input fields (asset configuration):
Status(inclusion NOT adjusted for asset status)
Calculated metrics:
Scaler data coverage
Time coverage (per meter)
Scaler time coverage (asset level)
Scaler area coverage (asset level)
The role of total floor area
Scaler evaluates data coverage within each Area type, relative to that area type's total floor area as defined in Reporting Data → Floor Areas
For each Area type:
- The total floor area represents the maximum area that can be covered by meters
- Meter
Covered areavalues are evaluated against this maximum
- Coverage is capped at the total floor area to prevent overstatement
Total floor area is used to:
- Determine whether meters fully cover the asset for a given area type
- Apply area-based corrective factors when coverage is incomplete
Total floor area mapping
Reporting Data → Floor Areas | Meter Area Type |
Gross floor area (GFA) | Whole Building, Shared Services |
GFA - Common area | Common Area |
GFA - Tenant area | Tenant Space |
Meter-level time coverage
Definition: Time coverage represents the proportion of the reporting period for which a meter has consumption data.
Calculation per meter:
TIME_COVERAGE = DAYS_WITH_CONSUMPTION ÷ TOTAL_DAYS_IN_REPORTING_PERIOD
Important characteristics:
- Time coverage is calculated per meter
- Meter version start date and Meter version end date define the period during which coverage is expected
- Time coverage is later aggregated to asset level using meter weighting
- Asset
Status(e.g., Major Renovation, New Construction) does not modify time coverage calculation
Meter weighting by covered area
Each meter contributes to Scaler data coverage in proportion to the floor area it represents.
Covered area assumptions
Scaler assumes that:
- Meters of the same resource (energy, water, waste) in the same
Area typedo not overlap in the floor area they cover
- Covered areas are summed across all Subcategories (e.g., Natural gas, Off-site electricity, District heating & cooling)
- The total covered area is capped at the floor area defined for the relevant
Area type
Meters that are excluded:
- Inactive for the reporting period, or
- Excluded via
Include in calculations=no/false
These meters do not contribute to coverage.
Weighted aggregation of time coverage
Each meter's time coverage is weighted by its share of the total covered area:
METER_WEIGHT = COVERED_AREA_OF_METER ÷ TOTAL_COVERED_AREA_OF_ALL_METERS
Scaler data coverage is then calculated as the weighted average of meter-level time coverage:
SCALER_DATA_COVERAGE = Σ(METER_WEIGHT × METER_TIME_COVERAGE)
This ensures that:
- Larger meters have a proportionally larger impact
- Missing data on a large meter affects coverage more than missing data on a small meter
Corrective factors
After meter-level aggregation, Scaler applies corrective factors to account for incomplete coverage at asset level.
Time corrective factor
The time corrective factor adjusts for periods in the reporting year where:
- The asset is active, but
- No meters exist to cover that period
Purpose: This prevents overstating coverage when meters are created mid-year.
Example: If meters only exist for the last 6 months of the year, the time corrective factor is 50%.
Area corrective factor
The area corrective factor adjusts for cases where:
- Meters do not cover the full floor area of the asset for the relevant
Area type
Purpose: This ensures that coverage reflects actual meter completeness, not just the presence of some meters.
Example: If meters cover 600 m² but the total floor area is 700 m², the area corrective factor is 600 ÷ 700 = 85.7%.
Relationship to Scaler time and area coverage
Because Scaler data coverage is calculated using meter-weighted time availability, it cannot be derived from:
Scaler time coverage × Scaler area coverage ❌ (This formula does NOT work)
Each metric serves a different diagnostic purpose:
Scaler time coveragehighlights temporal completeness at the asset level
Scaler area coveragehighlights spatial completeness at the asset level
Scaler data coveragereflects their combined effect at the meter level
Why this matters: You cannot simply multiply time coverage by area coverage to get Scaler data coverage. The weighting happens at the meter level before aggregation.
Why this methodology is used
Scaler's meter-weighted approach provides several advantages:
- Prevents double penalization of missing meters (both time and area gaps are accounted for once)
- Reflects the true impact of missing data on large meters
- Makes partial data gaps visible that aggregated methods hide
- Supports targeted data completion efforts by showing exactly which meters need attention
Key insight: An asset may show 100% GRESB-aligned data coverage while still having materially incomplete meter data. Scaler data coverage is designed to reveal those gaps.
Scaler data coverage calculation example
This example demonstrates how Scaler data coverage is calculated when meters do not cover the full floor area of an asset.
Scenario
An asset has a gross floor area (GFA) of 700 m² and three energy meters covering the same Area type (Whole-building):
Meter | Covered area | Meter time coverage |
Meter A | 100 m² | 100% |
Meter B | 200 m² | 100% |
Meter C | 300 m² | 0% |
Additional context:
- Total covered area by meters = 600 m²
- Total asset floor area (GFA) = 700 m²
- All meters are active for the reporting period and included in calculations
- Gap: 100 m² of the asset has no meter coverage
Step 1: Calculate meter weights
Meter weights are based on each meter's share of the total covered area:
Meter | Calculation | Weight |
Meter A | 100 ÷ 600 | 16.7% |
Meter B | 200 ÷ 600 | 33.3% |
Meter C | 300 ÷ 600 | 50.0% |
Step 2: Apply meter-level time coverage
Each meter's time coverage is multiplied by its weight:
Meter | Calculation | Contribution |
Meter A | 16.7% × 100% | 16.7% |
Meter B | 33.3% × 100% | 33.3% |
Meter C | 50.0% × 0% | 0.0% |
Aggregated meter-level result:
Weighted time coverage = 16.7% + 33.3% + 0.0% = 50.0%
Step 3: Apply the area corrective factor
Because meters cover 600 m² out of 700 m², Scaler applies an area corrective factor:
Area corrective factor = 600 ÷ 700 = 85.7%
Step 4: Calculate Scaler data coverage
Scaler data coverage = 50.0% × 85.7% = 42.9%
Interpretation
What this tells you:
- Two meters have full data, but they do not cover the full building
- The largest meter (300 m²) has no data
- An additional 100 m² of the asset has no meter at all
As a result:
- Only 42.9% of the asset is fully represented by consumption data
- Scaler data coverage reflects both missing meter data and missing area coverage
This behavior is intentional and helps surface:
- Where meters are missing
- Which gaps have the largest impact
Why total floor area matters
Total floor area (e.g., GFA) is used to:
- Detect whether meters collectively cover the full asset
- Prevent overestimating data completeness when only part of the building is metered
Critical insight: Even if all existing meters have complete time coverage, Scaler data coverage will remain below 100% until the full floor area is covered by meters.
Key assumptions
Scaler data coverage operates under these assumptions:
- Meters of the same resource (energy, water, waste) within the same
Area typeare assumed not to overlap in covered area - their covered areas are summed even if they physically serve the same space (e.g., natural gas and electricity both serving a 300 m² common area = 600 m² total covered area)
- On-site renewable electricity meters are included (unlike GRESB-aligned coverage, which excludes them)
- Asset construction status does not modify time correction logic (no special treatment for Major Renovation or New Construction)
- Coverage reflects data completeness, not data accuracy (Scaler data coverage does not validate whether the data is correct, only whether it exists)
Comparing calculation approaches
How GRESB-aligned data coverage is calculated:
Area coverage: Sums covered areas across all categories, divides by sum of maximum areas
Time coverage: Single date range per resource; Scaler interprets this to maximize coverage by using the widest range
Final coverage: Area coverage × Time coverage
Result: Aggregated view optimized for standardized benchmarking
How Scaler data coverage is calculated:
Time coverage per meter: Calculated individually for each meter
Meter weighting: Each meter's time coverage is weighted by its proportion of total covered area
Corrective factors: Applied when full asset area or reporting period is not covered
Final coverage: Weighted sum of meter-level contributions, adjusted by corrective factors
Result: Meter-level view optimized for data quality assurance
What high and low Scaler data coverage means
100% Scaler data coverage means:
✓ All relevant area types have meters covering 100% of floor area
✓ All meters have consumption data for every day of the reporting period
✓ No gaps exist in the underlying meter data
Low Scaler data coverage (<80%) typically indicates:
- Missing meters for certain area types or energy types
- Meters with partial time coverage (missing months or days)
- Large meters with incomplete data (disproportionate impact)
Use Scaler data coverage to prioritize: Focus data collection efforts on the largest meters with the most missing data for maximum impact.
Troubleshooting & common questions
Why is my Scaler data coverage much lower than GRESB-aligned data coverage?
This is expected when you have meters with different time availabilities or when meters don't cover the full floor area. GRESB's aggregated approach can hide these gaps, while Scaler's meter-weighted approach reveals them. Both are correct for their intended purpose.
Can Scaler data coverage be higher than GRESB-aligned data coverage?
Yes, in certain scenarios. For example, if GRESB area coverage is penalized due to missing categories but Scaler calculates based only on existing meters covering a large portion of the floor area.
Why can't I calculate Scaler data coverage by multiplying Scaler time coverage × Scaler area coverage?
Because Scaler data coverage weights each meter's time availability by its covered area before aggregation. The weighting happens at the meter level, not at the asset level. Simply multiplying the two asset-level metrics does not account for this meter-level weighting.
What should I do if Scaler data coverage is below 100%?
- Navigate to Data Collection Portal → Portfolio → Meter List
- Sort by Time coverage to identify meters with missing data
- Focus on meters with large
Covered areavalues (biggest impact)
- Fill missing consumption data or create additional meters to cover missing floor area
- Monitor Scaler area coverage and Scaler time coverage to identify whether the issue is spatial (missing meters) or temporal (missing data)
Why does Scaler data coverage include on-site renewable electricity when GRESB excludes it?
Scaler data coverage is designed for internal data quality assurance. On-site renewable electricity is part of your metering infrastructure and should be included when assessing data completeness. GRESB excludes it for benchmarking purposes, but Scaler includes it for QA purposes.
How do I know if my meters cover the full floor area?
Check the Meters & Consumption view for your asset. The "Floor area covered" section (available under the down toggle within each Area type section) shows the total covered area compared to the total floor area for each area type. If covered area < total floor area, you need additional meters.
Does this methodology apply to water and waste too?
Yes! The same meter-weighted methodology applies to water and waste data coverage. The examples in this article use energy for illustration, but the calculation logic is identical across all resources.
Key differences from GRESB-aligned data coverage
Feature | Scaler data coverage | GRESB-aligned data coverage |
Calculation method | Meter-weighted time availability with corrective factors | Asset-level aggregation across categories |
Reveals meter-level gaps | Yes | No |
Accounts for partial time coverage per meter | Yes (weighted by meter size) | No (single date range; Scaler uses widest to maximize coverage) |
Includes on-site renewables | Yes | No |
Can show 100% when gaps exist | No | Yes (due to aggregation) |
Best used for | Data quality assurance | GRESB reporting |
Use cases for Scaler data coverage
1. Data quality assurance
Goal: Identify incomplete meter data before generating reports
Action: Sort Asset List by Scaler data coverage to find assets with gaps
2. Prioritizing data collection
Goal: Focus efforts on meters with the largest impact
Action: Use Meter List to sort by Covered area × (100% - Time coverage) to identify high-impact gaps
3. QA before GRESB submission
Goal: Understand the gaps that GRESB's aggregation will hide
Action: Compare Scaler data coverage to GRESB-aligned data coverage for each asset to identify where hidden gaps exist
4. Tracking data completion progress
Goal: Monitor improvement over time
Action: Track Scaler data coverage month-over-month as you fill gaps and add meters