Katie Selasco and Scope 5
Published 3 years ago.
About a 9 minute read.
Here, we discuss how companies — particularly larger, multi-facility enterprises — can ensure they are getting an accurate picture of their energy usage and GHG emissions.
Due to a growth in demand for sustainability reporting data in recent years,
many organizations have begun quantifying and reporting on their greenhouse gas
emissions (GHGs). Whether companies aim to confidently address stakeholder
questions, identify data-backed opportunities for operational improvement or
position themselves as a sustainability leader, GHG inventories are gaining
importance in both the corporate and public spheres. But the methodologies for
preparing these reports vary and present reporters with significant decisions.
First, organizations must choose a reporting framework. This involves selecting
a organizational boundary, understanding and identifying which
emissions-producing activities fall within the boundary, and determining which
type of activity data will drive the emissions results. Seemingly simple,
activity data often presents complex challenges.
Gathering actual utility consumption data — such as bills quantifying kilowatt
hours of electricity consumed at a particular facility — is always the preferred
approach. Not only is it the most accurate reflection of an organization’s
consumption, but it is also the most actionable; it can be used to drive
business decisions. However, as many reporters begin to seek this information
from their providers, they often find that actual data is incomplete, suspect —
or, as is frequently the case for leased facilities, simply unavailable.
In the absence of actual data, many turn to energy-use intensity (EUI)
benchmarking figures — which approximate energy usage per building area — to
estimate activity data. Reporters using this method enjoy complete, defensible
results but are unable to use their inventory to understand their specific
behaviors or measure emissions reductions from operational changes. Such
benchmark data is hardly actionable.
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This can leave reporters feeling they must choose between two suboptimal
Facing precisely this dilemma, one of our clients elected to generate two
emissions inventories for the same time period — one using EUI benchmarks and
the other using actual data — to determine which method would yield more
dependable results. Surprisingly, emissions produced by the benchmark-driven
report nearly doubled those of the actual data-driven one. Comparing the
inventories side-by-side revealed sources of errors and limitations faced by
many reporters. Below, we identify the three most common discrepancies and
discuss how to resolve them.
Missing facilities: GHG inventories typically begin by identifying all
the facilities the company operates, listing the facilities’ locations, and
surveying them to understand which emissions-producing activities occur at
each. This key step serves as a foundation from which subsequent emissions
inventory calculations follow. Many organizations — particularly large,
multinational companies — fail to capture all facilities. Exclusions of this
nature inadvertently understate reported emissions. Depending on the size,
function and location of these facilities, these gaps can have significant
Some facilities will provide unreliable data or no data: Many of the
organizations we work with do not own their facilities. When they attempt to
acquire actual utility data for these facilities, they find their lessor is
either unable or unwilling to provide it. Many lessors have not submetered
each office within a building, and simply include the cost of utilities with
rent. Even for submetered facilities, property management companies
frequently are not accustomed to tracking and providing this information to
their tenants. Sometimes, they’ll retain the most recent bill, but be unable
to provide actual data to adequately cover the entire reporting period.
Benchmarks won’t reflect actual behaviors: Any EUI benchmark will
inherently somewhat understate or overstate energy consumption. Facilities
with outdated equipment or high occupancy rates may consume more energy than
predicted by benchmarks; and conversely, those that have adopted
energy-efficiency initiatives or are only infrequently operated will consume
less energy than indicated by benchmarks. The ratio of conditioned to
unconditioned (ex: large closets, unfinished basements, infrequently used
meeting rooms) space of any given facility also may deviate from the ratios
of the facility set used in benchmarking figures’ underlying calculations.
Further, it’s harder to find EUIs for some countries than it is for others.
Authoritative sources of benchmarks exist for the US and the UK; but
they can be harder to source for smaller countries — and error may be
introduced if benchmarks are applied to a geography that wasn’t included in
the underlying benchmark data set.
What can you do? Follow the steps below to understand how to adopt what we
consider to be a hybrid methodology that employs as much actual data as
possible, evaluates the quality of that data prior to inclusion, and fills in
all data gaps with authoritative benchmarks.
Step 1: Capture all facilities. Make sure each facility operated by your
organization is included in your inventory. Understanding the location
(including climate region), size, and principle building function all
significantly impact energy use and emissions. Interview regional managers
and examine company real estate databases to ensure there are no exclusions.
Whether actual utility data is collected for that facility or that
facility’s area is used to approximate energy consumption, properly
accounting for all facilities avoids material gaps and creates a reliable
framework for the rest of the inventory.
Step 2: Seek actual data first. Unlike benchmarking figures, actual data
is actionable — meaning it can be used to drive and measure changes in
behavior. In pursuit of this actionability, survey property managers and
speak to lessors to understand for which facilities’ actual data will be
available. Explain the period for which you’re seeking data and clarify that
you’ll need consumption totals — such as kilowatt hours of electricity or
therms of natural gas — and not just the cost of these services. Aim to
obtain actual data for every facility possible — particularly large
facilities, facilities that you know use considerable amounts of energy, and
facilities over which your organization can exercise significant operational
control. To streamline future inventories, ask your contact to provide this
data on an ongoing basis. This greater temporal granularity will give you
the opportunity to continually monitor progress and make decisions in real
time. Tracking and analyzing this data in a cloud-based sustainability tool
will further facilitate this process by identifying outliers, highlighting
gaps and extrapolating any missing data.
Step 3: Wherever actual data is provided, evaluate its quality. Prior to
including actual data in an emissions inventory, evaluate its quality to
make sure it is both complete and defensible. Complete means the data
reflects usage from the entire reporting period. Next, confirm the actual
data is defensible by determining an outlier threshold and comparing the
data to a benchmark such as
CBECS. Our client applied a
factor of three: If data was less than one-third of the benchmark, or
three-times higher than the benchmark, that data was deemed unreliable. Data
defensibility can also be checked by performing approximate calculations for
expected energy use for that facility, based on building use and occupancy.
For example, a typical desktop computer uses about 100 watts of electricity.
If it runs for eight hours per day, 250 days per year, it would consume
roughly 200 kilowatt hours per year. If ten employees share this office,
each using only a desktop computer and not using energy for lighting or
other purposes, we could anticipate 2,000 kWh for the year. But, if this
facility reports 3,000 kilowatt hours for the year, and the facility
supports fifty employees and a variety of activities, something is amiss.
Ensuring actual data passes both completeness and defensibility checks will
give you confidence that you can trust the data you’re using.
Step 4: Wherever actual data is absent, use an EUI benchmark. Use energy
use benchmarks to fill in the gaps for the remaining facilities for which
actual data is unavailable or deemed indefensible. Benchmarking figures,
sourced from a reliable agency such as CBECS, are a credible and commonly
used method that avoids understating emissions. Whenever possible, choose
benchmarks from authorities that offer EUIs based on granular categories
that impact energy use. For example, a benchmark that describes energy use
in an office building in a marine climate will yield more specific and
accurate results than a broad, country-average benchmarking figure that does
not differentiate by climate region or facility type.
Step 5: Survey each year to identify whether anything has changed. With
contacts established and this hybrid methodology in place, subsequent
emissions inventories should require less communication and discovery. Each
year, repeat the process of evaluating actual data quality and ensure your
benchmarking figures and their source activity (typically building area) are
This approach offers three critical benefits: It eliminates data gaps, reduces
tedious data maintenance work; and most importantly, focuses on actionability of
No gaps: Using either a benchmark or actual activity data for each
facility operated by your organizations ensures you have a complete and
dependable base from which you can compare future inventory results.
Limits data maintenance: Adopting a hybrid approach that
compartmentalizes facilities by activity data type limits data maintenance
for subsequent inventories. If your facility contact has identified that
they are unable to provide actual utility bills for your GHG inventories,
you know for future years you only need to understand whether that
facility’s benchmarking data (i.e. its area) has shifted. This is especially
relevant for small facilities that have minimal impact or over which your
organization has limited operational control to begin with. This reduces the
tedious tasks of identifying who to speak to and clarifying needs to
ascertain whether data will even be available.
More actionability: Most critically, this hybrid approach empowers
reporters to direct their focus and effort towards where they can have the
most impact: large, important facilities for which actual data is
available. Firstly, this method makes it easy to identify outliers. Since
every facility is accounted for, and all actual data has been compared to a
benchmark, it's easy to identify which facilities are performing better or
worse than expected. Reporters can seek to understand key behaviors or best
practices from efficient facilities, and implement those learnings at other
locations. Inefficient offices can be targets for sustainability projects
and emissions-reduction initiatives. Finally, it’s possible to define
relevant and data-backed targets, suitable as science-based
for the entire organization and monitor progress towards them over time with
Actual utility data and energy-use intensity benchmarks each present reporters
with limitations and advantages in greenhouse gas reporting. In pursuit of
actionability, many reporters aim to use actual data but encounter difficulties
in obtaining it. Benchmarks yield complete — but inactionable — results. Instead
of choosing one or the other, reporters can adopt the hybrid methodology
described above to balance accuracy, effort and actionability — and produce a
defensible emissions inventory. The results of this inventory can be used to
monitor year-over-year change in a consistent manner, streamline data collection
and communication with data providers; and most critically, empower reporters to
use data to make decisions.
Published Jan 29, 2021 10am EST / 7am PST / 3pm GMT / 4pm CET
Katie is a lead sustainability consultant at Scope 5 and oversees client support. Her work has included conducting emissions inventories for Fortune 500 multinationals, advancing the Greenhouse Gas Protocol’s Scope 2 market-based reporting, and supporting municipalities in publishing public data-driven storyboards that detail progress on climate goals. Katie takes particular interest in health, food, and regenerative agriculture.