Non-domestic National Energy Efficiency Data-Framework 2021
Source: environment.data.gov.uk (2025-08-21)

Non-domestic National Energy Efficiency Data-Framework (ND-NEED). The National Energy Efficiency Data-Framework was set up to provide a better understanding of energy use and intensity in domestic and non-domestic buildings.

These documents provide data on non-domestic energy use.

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The Non-Domestic National Energy Efficiency Data-Framework
2021 (England and Wales)
24th June 2021 Official Statistics

This report summarises analysis of the non-domestic building stock and non-domestic building
energy consumption in England and Wales using the latest version of the Non-Domestic
National Energy Efficiency Data-Framework (ND-NEED).
What you need to know about these statistics

The statistics in ND-NEED cover all non-domestic buildings in England and Wales, under
the ND-NEED definition. Information on the non-domestic building stock reflects the
position at the end of March 2020. Information on energy consumption covers 2012-2019,
and comprises electricity and gas consumed via the public distribution system (onsite
generated electricity consumption is not included).

The key results are:
• Non-domestic building energy consumption varies by building use.
o For electricity, the three highest consuming building uses excluding Other are
Factories (30%), Offices (15%) and Shops (13%). For gas, the three highest
consuming building uses excluding Other are Factories (37%), Education (8%)
and Offices (7%).
• Non-domestic building energy intensity also varies by building use, but with a different
pattern to energy consumption.
o The building uses with the highest median electricity intensities are Hospitality
(187 kWh/m2), Shops (125 kWh/m2) and Health (88 kWh/m2). The building uses
with the highest median gas intensities are Hospitality (284 kWh/m2), Shops (204
kWh/m2) and Emergency Services (189 kWh/m2).
• Non-domestic building energy consumption varies by building size. For both electricity
and gas consumption increases as building size increases.
o Buildings >1,000m2 are responsible for 61% of electricity consumption and 72%
of gas consumption (excluding buildings missing floor area information).
• Non-domestic building total electricity and gas consumption remained broadly stable
between 2012 – 2019. This pattern is seen across building uses.
Further detail including a breakdown of the non-domestic building stock by building age and
occupying business size, and a breakdown of electricity consumption/intensity and gas
consumption/intensity by building use, building size and occupying business size can be found
in the results section of the report.

Responsible statistician: Maya Fooks Media enquiries: xx-xxxx-xxxx
Email: xxx@xxx.xx Statistical enquiries: xx-xxxx-xxxx

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Figure 1: Summary graphic of the key ND-NEED 2021 results.

*ACL – Arts, Community and Leisure

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Contents
Contents __________________________________________________________________ 3
1. Introduction _____________________________________________________________ 5
What questions can be answered by ND-NEED 2021? ____________________________ 6
What questions cannot be answered by ND-NEED 2021? __________________________ 6
2. Results _________________________________________________________________ 7
England and Wales non-domestic building stock _________________________________ 7
Number of non-domestic buildings by year of construction ________________________ 7
Number of non-domestic buildings by business size ____________________________ 9
England and Wales non-domestic building energy consumption/intensity _____________ 11
Non-domestic energy consumption by building use ____________________________ 12
Non-domestic energy intensity by building use ________________________________ 21
Non-domestic energy consumption by building size ____________________________ 24
Non-domestic energy intensity by building size _______________________________ 26
Non-domestic energy consumption by business size ___________________________ 27
Non-domestic energy intensity by business size _______________________________ 30
How has energy consumption/intensity in non-domestic buildings changed over time? ___ 31
How has total energy consumption in non-domestic buildings changed over time (2012 –
2019)? _______________________________________________________________ 32
How has median energy consumption in non-domestic buildings changed over time (2012
– 2019)? _____________________________________________________________ 33
How has median energy intensity in non-domestic buildings changed over time (2012 –
2019)? _______________________________________________________________ 35
Investigating consumption from buildings with low-consuming non-domestic meters ____ 37
3. Methodology ____________________________________________________________ 40
ND-NEED building stock ___________________________________________________ 40
Converting NDR/SMV hereditaments to ND-NEED building stock dataset ___________ 41
Matching the ND-NEED building stock and Experian data _______________________ 42
Energy consumption ______________________________________________________ 42
Matching the ND-NEED building stock and energy consumption data ______________ 43
Weighting ______________________________________________________________ 43
Building weighting ______________________________________________________ 44
Energy weighting ______________________________________________________ 44
Removing non-buildings ___________________________________________________ 46
Comparing the results in ND-NEED to comparable figures from other publications ______ 46

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Current limitations of ND-NEED _______________________________________________ 50
Accompanying tables _______________________________________________________ 53
Related statistics __________________________________________________________ 54
Revisions policy ___________________________________________________________ 55
User engagement __________________________________________________________ 55
Contact __________________________________________________________________ 55
4. Annex A: Changes since the 2020 publication __________________________________ 56
5. Annex B: Understanding ND-NEED 2021 revisions ______________________________ 57
6. Annex C: Address matching ________________________________________________ 59
7. Annex D: Building use categories ___________________________________________ 60
8. Annex E: Removing inaccurate floor area data _________________________________ 61

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1. Introduction
The Non-Domestic National Energy Efficiency Data-Framework 2021 (ND-NEED 2021)
provides an insight into the electricity and gas consumption/intensity of non-domestic
buildings in England and Wales in 2019 (split by sector, building size and occupying
business size) and how this has changed over time. It also provides new information on
the non-domestic building stock, with a breakdown of non-domestic buildings by year of
construction and occupying business size. Further information on the number of
buildings in the non-domestic building stock and non-domestic floor area first published
in ND-NEED 2020 is also available.
ND-NEED is based on the Valuation Office Agency (VOA)’s list of all non-domestic premises
(“hereditaments”) in England and Wales (the non-domestic ratings list (NDR)) and the VOA’s
summary valuation data (SMV) which contains information on the premises’ size. Like ND-
NEED 2020, ND-NEED 2021 uses the position of the 2017 NDR/SMV as at the end of March
2020. BEIS have been given access to this data via a legal gateway (specified in an
information sharing agreement), and securely receives this data directly from the VOA.
In ND-NEED, the NDR/SMV data are aggregated to the building level (UPRN) and used,
following further processing, to provide information about the number, use, floor area and age
of buildings in the ND-NEED non-domestic building stock. As the NDR and SMV cover all non-
domestic buildings in England and Wales, these datasets cover all the 1,656,000 buildings in
the ND-NEED non-domestic building population.
As ND-NEED 2021 uses the same building stock data as ND-NEED 2020, information on the
number and floor area of the building stock (split by building use and building size) that was
published in ND-NEED 2020 are not updated in ND-NEED 2021. New analysis on the building
stock is presented, further disaggregating by year of construction and occupying business size.
The non-domestic building stock is then matched to information on electricity and gas
consumption (2012-19) at meter point level, held by BEIS. This gives a large sample of
847,000 non-domestic buildings with electricity consumption data and 373,000 non-domestic
buildings with gas consumption data. This sample is then matched to business characteristics
data (from Experian) to provide information on the size of the business occupying a building.
The matched dataset can then be used to analyse the electricity/gas consumption/intensity of
non-domestic buildings from a large sample size. The sample contains information on building
use, building size and occupying business size (for those successfully matched to the business
characteristics dataset), so the consumption data can be disaggregated by these
characteristics. The resulting consumption data for the sample are then weighted to be
representative of the population level.
More information about producing the ND-NEED sample and the weighting process can be
found in the methodology. The key limitations of the ND-NEED methodology, and a discussion
of the impact of these limitations on the ND-NEED results, can be found in the limitations
section.
The next update to ND-NEED is currently planned for the summer of 2022.

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What questions can be answered by ND-NEED 2021?
• How many non-domestic buildings are there in England and Wales and how do they
breakdown by building use and building size?
• What is the floor area of non-domestic buildings in England and Wales and how does
this breakdown by building use and building size?
• How does the non-domestic building stock breakdown by year of construction, and
occupying business size?
• How does non-domestic electricity/gas consumption/intensity change by building use,
building size and occupying business size?
• How has electricity/gas meter consumption/intensity of non-domestic buildings changed
over time (2012-2019)?
What questions cannot be answered by ND-NEED 2021?
• What is the electricity/gas consumption/intensity of non-domestic buildings in Scotland
and Northern Ireland?
• What are non-domestic buildings using their energy for (e.g. is energy used for
heating/lighting/industrial processes etc.)?
• How much of other fuels (e.g. biomass/LPG/oil) do non-domestic buildings consume?
• How much energy generated onsite is consumed by non-domestic buildings?
• How does non-domestic building energy use differ between rented/owner-occupied
buildings?
Further information related to these questions can be found in Energy Consumption in the UK
(ECUK)1, the Building Energy Efficiency Survey (BEES)2 and the Digest of UK Energy
Statistics3.

1 ECUK - https://www.gov.uk/government/statistics/energy-consumption-in-the-uk
2 BEES - https://www.gov.uk/government/publications/building-energy-efficiency-survey-bees
3 DUKES - https://www.gov.uk/government/collections/digest-of-uk-energy-statistics-dukes

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2. Results
England and Wales non-domestic building stock
In ND-NEED a building is defined as a property that has a unique property reference
number (UPRN). In general, each building has a distinct UPRN, so the information
presented in ND-NEED can be considered to be at the building level.
There are however a few exceptions to this. Where a single physical structure contains
multiple properties with UPRNs e.g. a shopping centre containing multiple shops each
with distinct UPRNs, then this is considered to be multiple buildings in ND-NEED. Where
multiple physical structures have a single UPRN e.g. a university campus or a hospital,
then this is considered to be a single building in ND-NEED.
Under the ND-NEED definition, there were 1,656,000 non-domestic buildings in England and
Wales at the end of March 2020.
There are some building types that are not covered by the ND-
NEED figures. These are:
• Agricultural Buildings, Places of Worship and Prisons as
these are not included in the VOA’s list of non-domestic
properties (the NDR) that ND-NEED is based on. It is
estimated these building types make up 4% of non-domestic
buildings in England and Wales4.
• Caravan Parks, Advertising Premises5, Car Parks, Beach Huts,
Quarries, and Telecoms6. These are included in the NDR but
are not considered to be buildings in ND-NEED and so are
excluded. The exclusion of these ‘non-buildings’ from ND-
NEED reduces the number of buildings in the stock by 8%.

Number of non-domestic buildings by year of construction
The ND-NEED non-domestic building stock can be split by year of construction. This is carried
out by using the building age variable in the VOA’s NDR list, which provides information on
when each building was built.

4 Figures based on the UCL Carb model, UCL’s non-domestic energy use model which provides estimates of total
number of buildings for different building types.
5 Places uses for advertisement e.g. roundabout adverts, bus shelter adverts, advertising banners.
6 Places used for communication e.g. communication stations, public telephones, telephone exchanges.
Figure 2: The number
of ND-NEED non-
domestic buildings in
England and Wales.

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Figure 3: Breakdown of the ND-NEED non-domestic building stock in England and Wales by
year of construction.

Note, since the building stock data are as at end of March 2020, data for 2020 (and, due
to lags, possibly 2019) is not complete. This means that the number of buildings
constructed in 1996 – 2020 will be an underestimate.

From Figure 3 we can see that more than a quarter of non-domestic buildings in the ND-NEED
non-domestic building stock (with year of construction information available) were built before
1900, and almost two thirds were built before 1970. As building practices and standards,
particular around energy efficiency, have changed over time this has implications for the
measures that will be needed to decarbonise the non-domestic building stock.
Rate of non-domestic building construction
By looking at the year buildings in the ND-NEED building stock were constructed we can also
gain insight into how the rate of non-domestic building construction has changed over time
(see Figure 4).
Figure 4: Number of buildings in the ND-NEED non-domestic building stock constructed
between 1900 and 2018, by number and floor area.

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Note, Figure 4 uses a smoothed line graph. For buildings built between 1900 and 1970 (inclusive)
where data is only available as bands covering a period of several years, the data is averaged over that
time period and plotted for the middle year. For years between 1971 and 2018 (inclusive), the data is
presented as a 3-year rolling average. As 2019 and 2020 year of construction data are incomplete
these years have been omitted. This does not include the 249,000 buildings missing year of
construction data, or 401,000 buildings built pre-1900.
Figure 4 shows that there is a general trend that the rate of construction of the buildings in the
non-domestic building stock (as at end of March 2020) increased steeply between 1940 and
1970 and has remained at a new higher level since then, though there is substantial year to
year variation.
This could reflect an increase in the total rate of non-domestic building construction in this time
period, but it is important to note that this data does not capture buildings that were built
between 1900 and 2018, but that were removed from the stock before 2020 (e.g. buildings that
were demolished, buildings that were repurposed for domestic use etc.) which is likely to
disproportionately affect older buildings.
There is also evidence that the rate of construction of buildings in the non-domestic building
stock (as at end of March 2020) is impacted by economic events, with a substantial fall in
construction seen around the 1990 and 2008 recessions. This trend is seen across all ND-
NEED building uses.
The average rate of construction of buildings in the non-domestic building stock (as at end of
March 2020) between 2010 and 2018 inclusive was 7,000 buildings per year, representing
0.5% of the building stock in ND-NEED with year of construction data. The construction rate in
2010 – 2018 is lower than in previous years, with evidence of a reduction in the rate of non-
domestic building construction in 2008, potentially due to the 2008 financial crash.
Figure 4 also provides information on the rate of floor area construction in buildings in the non-
domestic building stock (as at end of March 2020). By comparing this to the rate of non-
domestic building construction this can provide an insight into changes in the average size of
new non-domestic buildings.
This provides some evidence that the average size of non-domestic buildings in the non-
domestic building stock (as at end of March 2020) has increased over time. For example,
around 10,000 buildings were built in each of 1958, 1971 and 2002, with the average floor area
increasing from 400m2 to 700m2 and then 800 m2. This trend is not driven by missing floor area
data in ND-NEED since the proportion of buildings missing this is relatively constant across
building ages, with slightly more floor area data missing from newer buildings.
Number of non-domestic buildings by business size
Business size information is obtained by matching Experian business characteristics data to
the 1,656,000 ND-NEED non-domestic buildings in the building stock. This gives the
breakdown of the non-domestic building stock by business size that can be seen in Figure 5.
Note, the number of employees refers to the number of employees employed by the
business as a whole, not just the employees that work in the building. This means that
small branches of larger businesses e.g. a corner shop that is part of a national chain, will
be in the larger categories.

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Figure 5: Breakdown of the ND-NEED non-domestic building stock in England and Wales by
business size.

Figure 5 shows that the majority of non-domestic buildings (for which business size data are
available) are occupied by SMEs (<250 employees), with micro businesses (1 – 9 employees)
being the most common business size.
However, almost 70% of the buildings in the non-domestic building stock are missing business
size information which limits the conclusions that can be drawn from this data.
There are two reasons why buildings cannot be matched to business size information:

1. The UPRN of the corresponding building is missing from the Experian dataset, either
because the building itself is missing, or because the building is in the Experian dataset
but we are unable to match it to its corresponding UPRN. This means the business size
cannot be matched to the building. This represents 90% of the buildings that are
missing building size information).

2. The UPRN of the corresponding building is in the Experian dataset but the business
size information for this building is missing. This represents 10% of the buildings that
are missing building size information).

Note, the proportion of buildings that are missing business size information is generally
consistent between building uses and building sizes.

Given the high number of buildings missing business size information, the number of buildings
occupied by a business of a particular size is likely to be a substantial underestimate as
buildings that are missing business size information will also fall into this category. It is also
possible that the true pattern of distribution of businesses in the non-domestic building stock is
different from what is presented here. This means these estimates should be used with caution
as they are associated with substantial uncertainty.

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England and Wales non-domestic building energy
consumption/intensity
According to ND-NEED, in total non-domestic buildings in England and Wales used 129 TWh
of electricity and 147 TWh of gas in 2019 (the most recent year for which data are available).
These consumption figures are based on a sample of the ND-NEED building stock that was
successfully matched to electricity and gas meter-point data (gas consumption figures are
temperature corrected). This sample is then weighted to be representative at the population
level. More information about the sampling and weighting process in ND-NEED can be found
in the methodology.
Note, these figures are not directly comparable to the 2018 consumption figures
published in ND-NEED 2020 due to methodological revisions. For more information on
these revisions please see Annex B. For comparable figures for 2018 consumption
please see the ND-NEED 2021 consumption time series in Table 5.

Because the consumption figures are based on meter-point data, any energy consumed that is
not via the electricity or gas grid e.g. energy generated onsite from renewables, is not included.
According to the Digest of UK Energy Statistics (DUKES)7 89% of non-domestic building
electricity consumption was from the grid in 2019.
The fact that ND-NEED is based on meter-point data also means that the consumption figures
cover all grid energy consumed by a non-domestic building, regardless of end-use e.g.
heating, lighting, industrial processes etc. This is different from some other publications such
as the Building Energy Efficiency Survey (BEES)8 which only covers energy consumed by the
building itself e.g. heating, lighting, but not energy consumed by activities within the building
e.g. industrial processes.

7 DUKES, Table 5.2, Sectors: Industry, Commercial, Public administration used as a proxy for non-domestic
buildings. Public Distribution System as a share of Total Consumption -
https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes
8 BEES - https://www.gov.uk/government/publications/building-energy-efficiency-survey-bees

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Non-domestic energy consumption by building use
Electricity consumption
Figure 6: The electricity consumption of ND-NEED non-domestic buildings in England and
Wales by building use, 2019.

*ACL – Arts, Community and Leisure
Figure 6 shows non-domestic building electricity consumption by building use. It shows that
Factories are the building use that consumes the most electricity (39 TWh in 2019). This is
twice the consumption of the next highest consuming building use, Offices (20 TWh).
This is despite there being more Shops (476,000) and Offices (335,000) than there are
Factories (227,000) in England and Wales. This suggests that Factories are carrying out
processes that have high electricity demands (such as industrial processes whose energy
consumption is captured in ND-NEED).
Distributional analysis: Electricity consumption
ND-NEED 2021 can also provide further information about how electricity consumption is
distributed within the non-domestic building stock. This analysis is based on the ND-NEED
2021 sample that is weighted to be representative of the non-domestic building population (for
more information see the methodology). For example, we can look at the frequency of different
electricity consumption values.

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Figure 7: Frequency of different electricity consumption values for all non-domestic buildings,
2019.

Note: This histogram has unweighted electricity consumption on the x-axis (ascending order), shown on
a base-10 log scale. The y-axis shows a frequency count, that is the weighted number of buildings that
have electricity consumption 2019 values within the corresponding consumption band.
Figure 7 plots electricity consumption against the frequency of buildings whose consumption
falls within that band. The highest bar on the chart represents consumption between 3,160
kWh (103.5 kWh) and 10,000 kWh (104 kWh) per year. This means that Figure 8 shows that a
plurality of buildings consume between 3,160 kWh (103.5 kWh) and 10,000 kWh (104 kWh) per
year, and fewer buildings have consumption at either the lower or higher extremes.
There are also a substantial number of buildings whose consumption is lower than average
domestic consumption (3,500 kWh)9 in 2019. This is 24% of buildings in the ND-NEED sample.
Note, that the distribution in Figure 7 is on a log-10 scale. This is because the underlying
data is very positively skewed with a long tail of high-consuming sites. This positive skew
can also be seen in the data when you look at the comparison between the weighted
median electricity consumption and the weighted mean electricity consumption. The
weighted median electricity consumption of non-domestic buildings is 7,700 kWh,
compared to a weighted mean electricity consumption of 69,600 kWh.

We can also present the data in Figure 7 split by building use. Figure 8 shows that the
distribution of electricity consumption remains broadly similar between sectors, with a peak of
buildings with similar electricity consumption values, and fewer buildings with both lower and
higher electricity consumption.

9 Subnational electricity and gas consumption summary report 2019-
https://www.gov.uk/government/statistics/sub-national-electricity-and-gas-consumption-summary-report-2019

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There are however some differences between building uses. Factories and Offices have a
longer tail compared to Shops and Hospitality, showing that there are proportionally more very
high and very low consuming Factories and Offices. The smaller tails and more uniform
distribution of the hospitality sector distribution suggest that hospitality buildings have more
homogenous electricity consumption than the other sectors.

Figure 8: Frequency of different electricity consumption values, by building use, 2019.

Note: This histogram has unweighted electricity consumption on the x-axis (ascending order), shown on
a base-10 log scale. The y-axis shows a frequency count, that is the weighted number of buildings that
have electricity consumption 2019 values within the corresponding consumption band.
Another way we can look at the distribution of electricity consumption in ND-NEED is looking at
the proportion of total electricity consumption that comes from a given proportion of the
building stock. This will help us to understand the impact of the small number of high
consuming sites (identified above) on total electricity consumption.

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Figure 9: The proportion of the building stock (in ascending consumption order) against the
proportion of total electricity consumption, 2019.

Note: This cumulative distribution plot has the proportion of buildings in the ND-NEED sample with
2019 electricity consumption on the x-axis (ordered by unweighted electricity consumption). The y-axis
shows the proportion of weighted 2019 electricity consumption that these buildings are consuming.
From Figure 9 we can see that the majority of non-domestic building electricity consumption
comes from a minority of non-domestic buildings (80% of consumption comes from the 8%
highest consuming buildings). This shows that the small number of high consuming sites
identified in Figure 7 have a substantial impact on total electricity consumption.

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Figure 10: The proportion of the building stock (in ascending consumption order) against the
proportion of total electricity consumption, by building use, 2019.

Note: This cumulative distribution plot has the proportion of buildings in the ND-NEED sample with
2019 electricity consumption on the x-axis (ordered by unweighted electricity consumption). The y-axis
shows the proportion of weighted 2019 electricity consumption that these buildings are consuming.
We can also split this analysis by building use (Figure 10). From Figure 10 we can see that the
overall pattern of a minority of high-consuming buildings being responsible for a majority of
electricity consumption is seen across all building uses.
For Factories, 80% of electricity consumption comes from the highest consuming 2% of
buildings. For Education, 80% of consumption comes from the highest consuming 28% of
buildings.

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Gas consumption
Figure 11: The gas consumption of ND-NEED non-domestic buildings in England and Wales by
building use, 2019.

*ACL – Arts Community and Leisure
Figure 11 shows that the pattern for gas consumption by building use is similar to that of
electricity consumption. Factories have the highest gas consumption, at 54 TWh in 2019. This
is over four times higher than the gas consumption of any other building use (excluding the
‘Other’ category). This is despite the fact that Factories are not the largest building use
category in terms of building numbers.
As with electricity consumption, the high gas consumption of Factories is in part driven by their
large size and in part by the high gas consuming processes they carry out:
• Factories account for 14% of non-domestic buildings, but 25% of non-domestic building
floor area (of the buildings with floor area information available).
• From Energy Consumption in the UK (ECUK)10 we can see that industrial processes
(high and low temperature processes, drying/separation, motors, compressed air) are
responsible for around three-quarters of gas use in industry, and so a large part of gas
consumption in Factories is likely to be driven by these processes.
Most other building types consumed around 10 TWh of gas in 2019. The exceptions to this are
Arts, Community and Leisure where the buildings consumed 6 TWh of gas, and Emergency
Services where the buildings consumed 2 TWh of gas.

10 ECUK, End-use data tables, Table U2 - https://www.gov.uk/government/statistics/energy-consumption-in-the-
uk

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Distributional analysis: Gas consumption
As we did for electricity consumption, we can also apply the distributional analysis to gas
consumption from non-domestic buildings.
Firstly, we can look at the frequency of different levels of gas consumption to understand the
most common gas consumption level from non-domestic buildings.

Figure 12: Frequency of different gas consumption values for all non-domestic buildings, 2019.

Note: This histogram has weighted gas consumption on the x-axis (ascending order), shown on a log
scale (log10). Placeholder values of <1 kWh have been excluded. The y-axis shows a frequency count,
that is the number of buildings that have gas consumption values within the corresponding consumption
band.
Figure 12 plots gas consumption against the frequency of buildings whose consumption falls
within that band. The highest bar on the chart represents consumption between 10,000 kWh
(104 kWh) and 31,600 kWh (104.5 kWh) per year. This means that Figure 12 shows that a
plurality of buildings consume between 10,000 kWh (104 kWh) and 31,600 kWh (104.5 kWh) per
year, and fewer buildings have consumption at either the lower or higher extremes.
Note, Figure 12 is presented on a log10 scale because the underlying data is very
positively skewed with a long tail of high-consuming sites. This positive skew can also be
seen in the data when you look at the comparison between the weighted median gas
consumption and the weighted mean gas consumption. The weighted median gas
consumption of non-domestic buildings is 27,100 kWh, compared to a weighted mean
gas consumption of 225,000 kWh.

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We can also present the data in Figure 12 split by building use. Figure 13 shows Shops,
Factories and Offices all have a modal consumption of 10,000 kWh to 31,600 kWh (104 kWh to
104.5 kWh). Hospitality has a higher modal class at 31,600 kWh to 100,000 kWh (104.5 kWh to
105 kWh), which is consistent with Hospitality having a higher median gas consumption than
Shops, Factories or Offices (Table 11).
Figure 13: Frequency of different gas consumption values, split by building use, 2019.

Note: This histogram has unweighted gas consumption on the x-axis (ascending order), shown on a
base-10 log scale. Placeholder values of <1 kWh have been excluded. The y-axis shows a frequency
count, that is the weighted number of buildings that have electricity consumption 2019 values within the
corresponding consumption band.
To further understand the distribution of gas consumption within the non-domestic building
stock we can also look at the proportion of non-domestic building consumption that comes
from the highest consuming buildings. This will help us to understand how the few extremely
high consuming sites (identified above) impact total gas consumption.

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Figure 14: Proportion of the building stock (in ascending consumption order) against the
proportion of total gas consumption, 2019.

Note: This cumulative distribution plot has the proportion of buildings in the ND-NEED sample on the x-
axis (ordered by unweighted gas consumption). The y-axis shows the proportion of weighted 2019 gas
consumption that these buildings are consuming. Placeholder values of <1 kWh have been excluded.
From Figure 14 we can see that majority of non-domestic building gas consumption comes
from a minority of non-domestic buildings (80% of consumption comes from the 5% highest
consuming buildings). This shows that the small number of high consuming sites identified in
Figure 12 above have a substantial impact on total gas consumption. This is the same pattern
that is seen for electricity consumption.
We can also split this analysis by building use (Figure 15). From Figure 15 we can see that this
pattern is seen across all building uses. As for electricity this pattern is most convex for
Factories, with 80% of consumption coming from the 1% highest consuming buildings, and
least extreme in the Education sector, with 80% of consumption coming from the 31% highest
consuming buildings.

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Figure 15: Proportion of the building stock (in ascending consumption order) against the
proportion of total gas consumption, by building use, 2019.

Note: This cumulative distribution plot has the proportion of buildings in the ND-NEED sample on the x-
axis (ordered by unweighted gas consumption). The y-axis shows the proportion of weighted 2019 gas
consumption that these buildings are consuming. Placeholder values of <1 kWh have been excluded.

Non-domestic energy intensity by building use
The level of energy consumption in a building use category is in part driven by the number and
size of buildings of that type. To control for this, energy intensity can be used. Energy intensity
is the average amount of energy used in a square metre of a building. Differences in energy
intensity between sectors are therefore not affected by differences in the number or size of
buildings.
The electricity intensity figures presented in ND-NEED are the median electricity intensity,
weighted by the energy weight. Buildings which are missing floor area information are
excluded (see Non-domestic energy consumption by building size).

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Electricity intensity
Figure 16: The median electricity intensity of ND-NEED non-domestic buildings in England and
Wales by building use, 2019.

*ACL – Arts Community and Leisure
Figure 16 shows that median electricity intensity by building use has a very different pattern to
total electricity consumption. Hospitality is the building use with the highest median electricity
intensity (187 kWh/m2), despite having relatively low total electricity consumption (9 TWh). This
high electricity intensity is likely driven by the fact that hospitality buildings generally operate in
small building premises and often perform activities such as catering which have high
electricity demands11.
By contrast, Factories have a relatively low median electricity intensity (33 kWh/m2) but high
total electricity consumption (39 TWh). The low electricity intensity of Factories suggests that
their high electricity demands driven by the industrial processes they carry out, are
counterbalanced by the large size of these sites.

11 ECUK, End-use data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-uk

23

Gas intensity
Figure 17: The median gas intensity of ND-NEED non-domestic buildings in England and Wales
by building use, 2019.

As for electricity, Hospitality is the building use category with the highest median gas intensity
(284 kWh/m2), consuming almost 40% more gas per square meter than any other building
type. As for electricity, this is at least at least partly due to the high gas demands of the
catering activities that often occur in hospitality buildings. This can be seen in other
publications that split energy consumption by end-use (ECUK12 and BEES13).
The lowest gas intensities are seen in Factories and Warehouses with 82 kWh/m2 and 61
kWh/m2 respectively. A key driver of the low gas intensities of Factories and Warehouses is
likely to be their large building size. Together, Factories and Warehouses occupy 58% of non-
domestic building floor area, despite only accounting for 26% of non-domestic buildings.

12 ECUK, End-use data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-uk
13 BEES, Overarching tables, Figure 3.13 - https://www.gov.uk/government/publications/building-energy-
efficiency-survey-bees

24

Non-domestic energy consumption by building size
Electricity consumption
Figure 18: The electricity consumption of ND-NEED non-domestic buildings in England and
Wales by building size, 2019.

There is a clear trend that as building size increases the share of total electricity consumption
increases. This is particularly true for buildings that are over 1,000m2.
This trend is not driven by the number of buildings as there are more buildings in the smaller
floor area categories than there are in the larger ones. Instead, this trend is at least partly
driven by the floor area of buildings in these categories. The total floor area has a similar
pattern to the electricity consumption figures with a greater floor area in the larger floor area
bands.
Note, there is a proportion of non-domestic buildings in ND-NEED that are missing
building size information – 16% of non-domestic buildings in the ND-NEED sample with
electricity consumption in 2019 are missing floor area information. These buildings are
responsible for 45 TWh (35%) of electricity consumption. This means figures on the
electricity consumption of a particular building size should be used with caution as they
are likely to be an underestimate. It also means that there is some uncertainty associated
with the building size trend presented above.

25

Gas consumption
Figure 19: The gas consumption of ND-NEED non-domestic buildings in England and Wales by
building size, 2019.

As with electricity consumption, gas consumption tends to increase as building size increases.
Again, this trend is at least in part driven by the larger total floor area of the buildings in the
larger floor area bands.
It is again important to note the substantial size of the ‘Building size missing’ category
which makes up 63 TWh (42%) of consumption, more than any other building size
category. This consumption comes from the 20% of buildings in the ND-NEED gas
consumption sample that are missing building size information. The size of the missing
category means that that the consumption figures for each building size category are
likely to be underestimates and so should be used with caution. It also means there is
some uncertainty associated with the results above.

26

Non-domestic energy intensity by building size
Electricity intensity
Figure 20: The median electricity intensity of ND-NEED non-domestic buildings in England and
Wales by building size, 2019.

Median electricity intensity shows the opposite trend to total electricity consumption with
smaller buildings generally using more electricity per square metre than larger buildings.
Gas intensity
Figure 21: The median gas intensity of ND-NEED non-domestic buildings in England and Wales
by building size, 2019.

27

Like electricity, median gas intensity shows the opposite trend to gas consumption with smaller
buildings using more gas per square metre. This trend is stronger for gas intensity than it is for
electricity intensity.
Non-domestic energy consumption by business size
Non-domestic building energy consumption can also be broken down by business size. In ND-
NEED business size refers to the number of employees of the business occupying the building.
As is the case for the building stock, in the energy consumption business size categories the
number of employees refers to the number of employees employed by the business as a
whole, not just the employees that work in the building. This means that small branches of
larger businesses e.g. a corner shop that is part of a national chain, will be in the larger
categories.
A Micro business has less than 10 employees, a Small business has 10 - 49 employees, a
Medium business has 50 - 249 employees, a Large business has 250 - 999 employees and a
Very Large business has 1,000 employees or more.
Note, the weighting used to scale up consumption from the ND-NEED sample to the
population does not account for potential differences between the size of businesses in
the sample and the size of businesses in the population. This means there is more
uncertainty around whether the energy consumption figures by business size are
representative of the population, than for the consumption figures by building use or by
floor area.

Electricity consumption
Figure 22: The electricity consumption of ND-NEED non-domestic buildings in England and
Wales by business size, 2019.

28

Figure 22 shows the contribution of buildings occupied by businesses of different sizes to non-
domestic building electricity consumption.
Buildings occupied by Very Large businesses consume the most electricity (21 TWh), followed
by buildings occupied by Medium sized businesses (16 TWh), with buildings occupied by
Micro, Small and Large businesses consuming the least electricity (around 12 TWh each).
This is a different patten than is seen in the number of buildings in the non-domestic building
stock (see above), where the largest category is Micro businesses (300,000 buildings),
followed by Small businesses (99,000 buildings), Very Large businesses (70,000 buildings),
Medium businesses (35,000 buildings) and Large businesses (21,000 businesses).
Note, 58 TWh of electricity consumption is missing business size information. This is the
electricity consumption of the 422,000 buildings of the 814,000 in the ND-NEED electricity
consumption sample with 2019 electricity consumption, where information on the occupying
business size is not available.
In ND-NEED the business size information comes from the Experian business characteristics
dataset which is matched onto the non-domestic buildings and energy consumption data.
There are two reasons why business size information may not be available:
• The Experian dataset may not contain business size information for a building.
• The Experian dataset may contain business size information, but this cannot be
successfully matched to the corresponding building.
Because of the substantial size of the ‘Business size missing’ consumption category, the
consumption figures for other categories e.g. Micro, Small etc. should be used with caution as
they are likely to be underestimates (as some of the consumption in the ‘Business size
missing’ category should be in those categories). It also means that there is substantial
uncertainty around the pattern of results.

29

Gas consumption
Figure 23: The gas consumption of ND-NEED non-domestic buildings in England and Wales by
business size, 2019.

Gas consumption by business size shows a different pattern to electricity consumption.
Buildings occupied by businesses with more than 50 employees (Medium, Large and Very
large businesses) tend to consume more gas, than buildings occupied by businesses with
fewer than 50 employees (Small and Micro businesses).
It is again important to note the substantial consumption of 56 TWh from the ‘Business size
missing’ category. This is because 167,000 of the 358,000 buildings in the ND-NEED gas
consumption sample are missing business size information. Because of this, the consumption
figures for each business size category are likely to be underestimates (as some consumption
from buildings that are missing business size information is likely to fall into each category),
and there is substantial uncertainty around the pattern of results seen.

30

Non-domestic energy intensity by business size
Electricity intensity
Figure 24: The median electricity intensity of ND-NEED non-domestic buildings in England and
Wales by business size, 2019.

From Figure 24 we can see that electricity intensity tends to increase as the size of the
business occupying the building increases.
As with the electricity consumption figures it is important to note the substantial size of the
business size missing category – almost half of buildings in the ND-NEED sample that have
floor area information are missing business size information. This makes it difficult to draw any
firm conclusions from the results as they are associated with a high degree of uncertainty.

31

Gas intensity
Figure 25: The median gas intensity of ND-NEED non-domestic buildings in England and Wales
by business size, 2019.

Gas intensity by business size shows a different trend to electricity intensity. The gas intensity
of a building is more stable across all business sizes, decreasing slightly as the size of the
business occupying the building increases.
Again, it is important to note the substantial size of the business size missing category – over
two-fifths of buildings in the ND-NEED sample that have both gas consumption and floor area
information are missing business size information. This makes it difficult to draw any firm
conclusions from the results.
How has energy consumption/intensity in non-domestic
buildings changed over time?
ND-NEED can also provide information on the electricity and gas consumption/intensity over
time, which can be disaggregated by building use.
Note the electricity consumption year is a calendar year (Jan – Dec), the gas
consumption year runs from mid-May to mid-May.

In this update we have presented several energy consumption/intensity time series:
1. Total electricity and gas consumption over time (2012 – 2019)
2. Median electricity and gas consumption over time (2012 – 2019)
3. Median electricity and gas intensity over time (2012 – 2019)

32

Note, because the ND-NEED statistics are created by scaling up the results from a
sample of buildings to the population level (rather than from the whole population directly)
there is some degree of uncertainty surrounding all ND-NEED estimates. Because of this
uncertainty small changes in the ND-NEED consumption figures over time could just be
noise rather than showing a true change.

How has total energy consumption in non-domestic buildings changed over time
(2012 – 2019)?
Note, due to revisions in the methodology the ND-NEED 2021 total energy consumption
figures for 2016 – 2018 differ slightly from the figures presented in ND-NEED 2020. For more
information on the reasons for these revisions please see the methodology.
Electricity consumption
Figure 26: Total electricity consumption in ND-NEED non-domestic buildings in England and
Wales (2012-19).

Figure 26 shows that, according to ND-NEED, the electricity consumption of non-domestic
buildings in England and Wales remained relatively constant between 2012 and 2019 with
some evidence of a slight decrease. This is broadly consistent with the trend seen in other
publications such as the Subnational electricity consumption statistics14 and DUKES15.

14 Subnational electricity consumption figures - https://www.gov.uk/government/statistical-data-sets/regional-and-
local-authority-electricity-consumption-statistics
15 Dukes, Table 5.2, Sectors: Industry, Commercial, Public administration -
https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-kingdom-energy-statistics-dukes

33

Unlike other publications, in ND-NEED this time series can also be split by building use. This
shows that all building uses show a similar pattern to total consumption, with consumption
remaining broadly stable between 2012 and 2019 (see Table 5 in the accompanying data
tables).
Gas consumption16
Figure 27: Total gas consumption in ND-NEED non-domestic buildings in England and Wales,
2012-19.

Note, the gas consumption figures in ND-NEED are temperature adjusted so any
temperature differences between years will not influence the ND-NEED gas consumption
trend.

Figure 27 shows that, according to ND-NEED, gas consumption in non-domestic building
remained broadly stable between 2012 and 2019, varying between 146 TWh and 153 TWh.
This is consistent with the trend seen in the Subnational gas consumption statistics17 and
DUKES18. As is the case for electricity, this trend is seen across building uses.
How has median energy consumption in non-domestic buildings changed over
time (2012 – 2019)?
Another way to investigate how non-domestic building energy use has changed over time is to
the look at median consumption. This will be less affected by consumption from a few high
consuming buildings than the total consumption time series.

16 ND-NEED gas consumption years are not calendar years but run from mid-May to mid-May. For example, data
from 2019 is data from mid-May 2019 – mid-May 2020. For more information see the methodology of the
Subnational gas consumption statistics which provide the gas consumption figures in ND-NEED -
https://www.gov.uk/government/publications/regional-energy-data-guidance-note p.12
17 Sub-national gas consumption statistics - https://www.gov.uk/government/collections/sub-national-gas-
consumption-data
18 DUKES, Table 4.2, Sectors: industrial, commercial, public admin and misc –
https://www.gov.uk/government/statistics/natural-gas-chapter-4-digest-of-united-kingdom-energy-statistics-dukes

34

Electricity consumption
Figure 28: Median electricity consumption in ND-NEED non-domestic buildings in England and
Wales, 2012-19.

Figure 28 shows that median electricity consumption in non-domestic buildings has decreased
by 17% between 2012 and 2019. This decreasing trend is the same as that seen in the
Subnational electricity consumption data19. This trend is also seen across the building uses
(Offices -21%, Factories -16%, Shops -19%).
The overall median electricity consumption in non-domestic buildings in ND-NEED in 2019 is in
line with what is seen in the Subnational electricity data at around 8,000 kWh a year.
Gas consumption20
Gas consumption shows a similar trend to electricity consumption with evidence of a slight
decrease in median gas consumption between 2012 – 2019. This trend is also seen in the
Subnational gas consumption data21. This slight decrease is seen across all building uses.
There is evidence of a larger decrease in median gas consumption between 2018 and 2019.
As the gas year in ND-NEED runs from mid-May to mid-May the 2019 data covers mid-May
2019 to mid-May 2020 and so includes the first two months of the Covid-19 lockdown. Many
non-domestic buildings closed during this period with only essential services allowed to open
and people told to work from home where possible. This will have decreased non-domestic
consumption across a range of building uses and may explain the decrease in consumption
seen.

19 Subnational electricity consumption data - https://www.gov.uk/government/statistical-data-sets/regional-and-
local-authority-electricity-consumption-statistics
20 ND-NEED gas consumption years are not calendar years but run from mid-May to mid-May. For example data
from 2019 is data from mid-May 2019 – mid-May 2020. For more information see the methodology of the
Subnational gas consumption statistics which provide the gas consumption figures in ND-NEED -
https://www.gov.uk/government/publications/regional-energy-data-guidance-note p.12
21 Subnational gas consumption data 2019 - https://www.gov.uk/government/statistical-data-sets/gas-sales-and-
numbers-of-customers-by-region-and-local-authority

35

Note, the median gas consumption in non-domestic buildings in ND-NEED (around
30,000 kWh) is much lower than is seen in the Subnational gas consumption data
(around 150,000 kWh). This is because the Subnational data uses a consumption
threshold of 73,200 kWh to identify non-domestic buildings which means some low
consuming non-domestic buildings are not included. Consumption from these buildings is
captured in ND-NEED which leads to the lower median consumption values.

Figure 29: Median gas consumption in ND-NEED non-domestic buildings in England and Wales,
2012-19.

How has median energy intensity in non-domestic buildings changed over time
(2012 – 2019)?
ND-NEED can also be used to track changes in median energy intensity over time.
Note, the floor area information in ND-NEED is only available for a single point in time
(end of March 2020). This means that any changes in the energy intensity time series are
being driven by changes in consumption alone, as the impact of any changes in floor
area will not be captured.

36

Electricity intensity
Electricity intensity has fallen gradually between 2012 and 2019, decreasing by 20% in the
time period. This trend is seen across all building uses.
Figure 30: Median electricity intensity in ND-NEED non-domestic buildings in England and
Wales, 2012-19.

Gas intensity22
Gas intensity shows the same pattern as electricity intensity showing a gradual decrease over
time, falling by 12% across the time period. Again, this trend is seen for all building uses.
Figure 31: Median gas intensity in ND-NEED non-domestic buildings in England and Wales,
2012-19.

22 ND-NEED gas consumption years are not calendar years but run from mid-May to mid-May. For example, data
from 2019 is data from mid-May 2019 – mid-May 2020. For more information see the methodology of the
Subnational gas consumption statistics which provide the gas consumption figures in ND-NEED -
https://www.gov.uk/government/publications/regional-energy-data-guidance-note p.12

37

Investigating consumption from buildings with low-consuming
non-domestic meters
ND-NEED can also provide information on the number of non-domestic buildings that have
‘domestic-like’ or low consuming electricity or gas meters. This can provide an indication of the
proportion of non-domestic buildings that share similar consumption characteristics as
domestic buildings, and how much they contribute to overall non-domestic consumption.
Electricity consumption
There are two key reasons why it is important to understand the number of non-domestic
buildings that have ‘domestic-like’ electricity meters:
1. In ND-NEED the non-domestic electricity meter population is defined as all meters that
are in ‘non-domestic’ profile classes (0, 3 – 8)23, and any meters in a ‘domestic-like’
profile class (1,2) that can be matched to a non-domestic building address via an
address-matching algorithm. The ND-NEED address matching algorithm is estimated to
have a match rate of around 50% which means we know that we are missing some
‘domestic-like’ meters from the ND-NEED population. Understanding how many non-
domestic buildings have these ‘domestic-like’ meters will help us to understand how
many of these meters and what level of electricity consumption is currently being
missed in ND-NEED.
2. The profile class of an electricity meter is used by other electricity consumption
publications such as the Subnational publication24 to identify non-domestic meters and
so to estimate non-domestic building consumption. Understanding how many non-
domestic buildings have these ‘domestic-like’ meters therefore informs how much non-
domestic consumption is being recorded as domestic consumption in these
publications.
In the ND-NEED sample (a sample of 847,000 non-domestic buildings that have been matched
to their corresponding electricity meter) 96% of buildings have information about the profile
class of their electricity meter(s).
Of these buildings, 89,000 (11%) have ‘domestic-like’ meters (meters in profile classes 1 or 2).
These may have previously been domestic property which have now been converted to non-
domestic usage.
These buildings with ‘domestic-like’ meters are responsible for 1 TWh of electricity
consumption, less than 1% of electricity consumption from buildings with profile class
information.
This shows that while these ‘domestic-like’ meters are relatively common in the non-domestic
building stock, they make very little contribution to overall electricity consumption. This means
that although the ND-NEED meter population is likely missing a substantial number of these
‘domestic-like’ electricity meters, this has little impact on the overall electricity consumption
reported. This will also be the case for other electricity consumption publications that use
profile class to define meters as ‘domestic’ or ‘non-domestic’.

23 https://www.elexon.co.uk/knowledgebase/profile-classes/
24 https://www.gov.uk/government/collections/sub-national-electricity-consumption-data

38

Gas consumption
As gas meters do not have profile classes or similar which could indicate whether a meter
is located in a domestic or a non-domestic building the metered consumption level is
used instead.

BEIS uses the gas industry standard “Annual Quantity” (AQ) cut-off point of 73.2 MWh to
determine whether a gas meter is classified as domestic or non-domestic. Meters that
consume <= 73.2 MWh are classified as domestic and meters that consume >73.2 MWh
are classified as non-domestic.

In ND-NEED this classification is refined by also matched low-consuming sites to non-
domestic buildings.

For gas consumption there are three key reasons why it is important to understand the number
of gas meters that are low-consuming/’domestic-like’:
1. In ND-NEED the non-domestic gas meter population is defined as all meters that
consume >73.2 MWh and any meters that consume <= 73.2 MWh that can be matched
to a non-domestic building address via an address-matching algorithm. The ND-NEED
address matching algorithm is estimated to have a match rate of around 50% which
means we know that we are missing some ‘low-consuming’ meters from the ND-NEED
population. Understanding how many non-domestic buildings have these ‘low-
consuming’ meters will help us to understand how many of these meters and what level
of gas consumption is currently being missed in ND-NEED.
2. The consumption level of a gas meter is used by other gas consumption publications
such as the Subnational publication25 to identify non-domestic meters and so to
estimate non-domestic building consumption. Understanding how many non-domestic
buildings have these ‘low-consuming’ meters therefore informs how much non-domestic
consumption is being recorded as domestic consumption in these publications.
3. Not all non-domestic buildings will have a gas meters - they may be in an area where no
gas connection is available, or they may be in an area where a gas connection is
available but choose not to be connected. Understanding how many buildings with gas
meters are currently being missed in ND-NEED will help us to estimate the number of
non-domestic buildings with no gas connection. This is important as there are
differences in decarbonisation policy for buildings that use gas and those that do not.

In the ND-NEED sample there are 337,000 non-domestic buildings that have been matched to
their corresponding gas meter(s), where consumption is >1 kWh in 2019 (values of 1 kWh or
less are placeholder values).
Of these 337,000 buildings, 266,000 buildings consumed <=73.2 MWh of gas in 2019. That is
79% of all buildings with gas consumption information. These buildings are responsible for 11
TWh of gas consumption, which is around 7% of gas consumption from the whole non-
domestic building stock.

25 https://www.gov.uk/government/collections/sub-national-gas-consumption-data

39

This shows that ‘low-consuming’ gas meters are common in the non-domestic building stock
and have a non-negligible impact on the total gas consumption level. This means that the ND-
NEED meter population is potentially missing a substantial number of gas meters and is
slightly underestimating the total gas consumption from non-domestic buildings. This will be
even more true for other publications which just use the 73.2 MWh cut-off to identify non-
domestic consumption as they don’t use address matching to identify any lower consuming
sites.
It also means that the ND-NEED data cannot currently be effectively used to estimate the
number of non-domestic buildings which do not have a gas connection (either because they
are in an area where no gas connection is available, or they are in an area where a gas
connection is available but choose not to be connected). This is because we know that lots of
buildings with low consuming gas meters are currently missing from the ND-NEED data.
Note, typical domestic gas consumption is much lower than 73.2 MWh. Ofgem estimates
that the medium domestic gas consumption is 12 MWh and high domestic gas
consumption is 17 MWh26.

If 17 MWh a year is used as the cut-off for non-domestic consumption, then 137,000 buildings
(40% of buildings in the ND-NEED gas sample) have ‘domestic-like’ gas consumption in 2019
(<17 MWh). These buildings are responsible for 2 TWh of consumption.
If 12 MWh a year is used as the cut-off for non-domestic consumption, then 100,000 buildings
(30% of buildings in the ND-NEED gas sample) have ‘domestic-like’ gas consumption in 2019
(<12 MWh). These buildings are responsible for 1 TWh of consumption.
Overlap between buildings with ‘domestic-like’ electricity meters and ‘domestic-like’ gas meters
Another area we can investigate with the ND-NEED data is the extent to which the buildings
with ‘domestic-like’ electricity and gas meters overlap.
For this analysis a gas meter will be considered ‘domestic-like’ if it consumed less than
Ofgem’s ‘high domestic consumption’ level27 of 17 MWh in 2019.
There are 89,000 non-domestic buildings with ‘domestic-like’ electricity meters and 137,000
non-domestic buildings with ‘domestic-like’ gas consumption in the ND-NEED sample.
Of the 137,000 non-domestic buildings with ‘domestic-like’ gas consumption 27,000 also have
‘domestic-like’ electricity meters. That means that 20% of the buildings with ‘domestic-like’ gas
consumption also have ‘domestic-like’ electricity meters.
Of the 89,000 non-domestic buildings with ‘domestic-like’ electricity meters 43,000 have gas
consumption >1 kWh in 2019. Of these 43,000 buildings, 27,000 have ‘domestic-like’ gas
consumption. That means that 62% of the gas consuming buildings with ‘domestic-like’
electricity meters also have ‘domestic-like’ gas consumption.

26 https://www.ofgem.gov.uk/gas/retail-market/monitoring-data-and-statistics/typical-domestic-consumption-values
27 https://www.gov.uk/government/collections/sub-national-gas-consumption-data

40

Figure 32: Overlap between buildings with ‘domestic-like’ electricity meters and ‘domestic-like’
gas consumption meters.

3. Methodology
ND-NEED building stock
To calculate the building stock figures in ND-NEED, the 2017 version of the VOA’s non-
domestic ratings list (NDR) and the VOA’s summary valuation data (SMV), as at the end of
March 2020, are used.
This data is collected by the VOA as part of their business rate calculations. Almost all
properties that are not used for domestic purposes are valued for business rates and so are
included in the NDR.
There are however a few non-domestic building uses that are exempt from business rates.
These are not included in the NDR and so are also not covered by ND-NEED. Non-domestic
buildings that are exempt from building rates include agricultural buildings, prisons, military
buildings and places of worship.
The NDR and SMV contain information on the number of non-domestic hereditaments in
England and Wales, the size of these and their use. A hereditament can be a building, but
there can also be multiple hereditaments within a single building.

41

Each hereditament in the NDR/SMV has a unique address reference number (UARN). Each
hereditament also has a unique property reference number (UPRN), which is a unique building
reference. Two hereditaments in the same building will have different UARN’s but the same
UPRN.
Converting NDR/SMV hereditaments to ND-NEED building stock dataset
Before analysis of the NDR/SMV data can be carried out, any hereditaments which do not
have a UPRN or that have a null rateable value are removed. This takes the number of
hereditaments in the dataset from 2,111,000 to 1,915,000.
The 1,915,000 remaining hereditaments must then be aggregated to the building (UPRN) level,
which results in 1,798,000 unique UPRNs.
Table 1: Single versus multiple hereditaments in ND-NEED non-domestic buildings in England
and Wales (end of March 2020).
Number of hereditaments in a building
Number of buildings (UPRNs)
Buildings (UPRN) containing a single
hereditament (UARN)
1,751,000
Buildings (UPRN) containing multiple
hereditaments (UARN)
47,000

To determine the floor area of buildings containing multiple hereditaments, the floor area of the
hereditaments within it are summed. If a hereditament has a floor area of less than 15m2 this is
not included in the building floor area as this floor area data is thought to be unreliable for the
purposes of ND-NEED as it results in some extremely high energy intensity values.
The NDR/SMV also contain hereditament floor area information for some building uses for
which this floor area information is thought to be unreliable for the purposes of ND-NEED as
the floor area does not inform the business rating. The floor area for these building uses is
therefore removed. A list of the building uses which have their floor area information removed
can be found in Annex E.
If a building contains hereditaments with multiple building uses, the building use of the
hereditament with the largest floor area is taken to be that for the building.
Once the NDR/SMV data has been aggregated to the building level there is some further
processing before the building use analysis is carried out.
The NDR/SMV contain some building uses which are not considered to be non-domestic
buildings for the purposes of ND-NEED. These ‘non-buildings’ are removed before the building
stock figures are calculated. The building types that are removed are: Caravan Parks,
Advertising Rights and Premises, Car Parks, Beach Huts, Quarries and Telecoms. The
removal of the ‘non-buildings’ takes the number of buildings from 1,798,000 to 1,656,000.
The data can then be used to provide information on the building number, use and size of the
ND-NEED non-domestic building stock in England and Wales.

42

Figure 33: The key steps from the NDR/SMV data from the VOA to the ND-NEED building stock
population.

Matching the ND-NEED building stock and Experian data
The 1,656,000 buildings in the non-domestic stock (excluding non-buildings) are then matched
to the Experian business characteristics dataset (which BEIS has attached UPRNs to) using
UPRNs. This dataset contains information about the number of employees of the business
occupying the building.
Just under 40% of business in the ND-NEED sample successfully match to the Experian data.
However, there are some buildings which match to the Experian data, but the Experian data
does not have information on their occupying business size. This means that only 32% of ND-
NEED non-domestic buildings have information about their occupying business size.
Note, the Experian business characteristics dataset is a bespoke dataset that BEIS
receives from Experian.

Energy consumption
To calculate the non-domestic energy consumption figures in ND-NEED, the list of non-
domestic buildings in England and Wales with building use, building size and occupying
business size information is matched with energy consumption data (at the meter-point level)
held by BEIS. This creates a sample of non-domestic buildings with energy consumption and
building/business characteristic information. This sample is then weighted to scale the results
up to the population level.
The gas consumption meter data is temperature corrected so ND-NEED gas consumption
figures are all temperature corrected.
Note, all 1,798,000 buildings are matched to the energy consumption data (including non-
buildings).

43

The reason non-buildings are not removed before matching is that some of the energy
consumption in the consumption data is thought to come from non-buildings. Therefore, if the
non-buildings were removed before matching, the energy consumption for non-domestic
buildings (excluding non-buildings) would be artificially high as it would be scaled up to
population figures that include non-building consumption.
To prevent this the non-buildings are matched to the energy consumption data and included
when the weights are calculated to scale the sample up to the population. After the weights
have been calculated the non-buildings are removed.
Matching the ND-NEED building stock and energy consumption data
The 1,798,000 buildings in the ND-NEED building stock and the energy consumption data do
not share a common unique identifier. Therefore, to match the datasets together address
matching is used.
Address matching is when two addresses from different datasets are deemed to correspond to
the same property. Address matching of non-domestic buildings can be difficult as non-
domestic addresses are often complex. For example, a non-domestic building may occupy a
range of building numbers or list the company name in the address. More information about
the address-matching process in ND-NEED can be found in Annex C.
Using address matching almost 50% of buildings in the ND-NEED stock (858,000 buildings)
were successfully matched to electricity meter data. Of these 858,000 buildings, 375,000 were
also successfully matched to gas consumption meter data. This reduced sample size is
because not all non-domestic buildings have a gas connection.
Weighting
As not all non-domestic buildings can be matched to energy use data, weights are used to
scale up the ND-NEED sample to population. Weighting is used to ensure the results from ND-
NEED are as representative of the non-domestic building population as possible.
As there is not a dataset that contains all non-domestic buildings and all non-domestic building
electricity/gas consumption, this weighting takes place in two stages (the building weight and
the energy weight).
For the weighted sample figures to be representative of the population, the weighting must
account for the key characteristics that could influence energy consumption. Both building use
and floor area are used to inform the weighting, so the ND-NEED consumption figures should
be representative for these characteristics. However, where floor area information is missing
the weighting is less effective as buildings missing floor area in the sample will be weighted up
to buildings missing floor area in the population, even though the actual floor sizes of buildings
in these groups might differ. For this reason, there is more uncertainty around the ND-NEED
consumption figures by floor area than by building use (where there is no missing information).

44

Note, the weighting used to scale up consumption from the ND-NEED sample to the
population does not account for potential differences between the size of businesses in
the sample and the size of businesses in the population. This is because of the poor
coverage of business size information in the building stock (only 32% of non-domestic
buildings have business size information).

This means there is more uncertainty around whether the energy consumption figures by
business size are representative of the population, than for the consumption figures by
building use or by building size.

Building weighting
The building weights scale up the number of buildings in the ND-NEED sample to the number
of buildings in the ND-NEED building population.
To account for biases in the ND-NEED sample the building weights are constructed based on
building use and building size. A single building weight is calculated for each building in the
ND-NEED sample.
The building population and sample are stratified into 35 building uses and 17 floor area bands
to form a matrix. A few of the building types have too few counts in either the population or the
sample to be stratified into an area band (a count of below 5 was used as the minimum cut-
off). In these cases, two or more area bands were merged (in both the population and the
sample).
For each cell in the matrix, the population count is divided by the sample count. For example, if
there were 1,000 cinemas with a floor area of >500 – 1,000m2 in the population, and 500
cinemas with a floor area of >500 – 1,000m2 in the sample these buildings would be assigned
a building weight of 2.
Energy weighting
The next stage of the weighting process is to calculate the energy weights. The energy weights
scale up the energy meters in the ND-NEED sample to match the number of energy meters in
the non-domestic meter population. The weights for electricity meters and gas meters are
calculated separately.
The non-domestic meter population contains some building uses that are not covered by ND-
NEED. These are agricultural buildings, place of worship and prisons. The meters associated
with these building uses are therefore excluded from non-domestic meter population before the
energy weights are calculated.

To do this, a profile for each of the excluded building types is created from the meter data.
Each of these building types is then grossed up to an estimated population from the UCL Carb
model28. The resulting population of these building types was then removed from the total
population of all consumption meters.

28The UCL Carb model is UCL’s non-domestic energy use model which provides estimates of total number of
buildings for different building types.

45

Electricity weight
The population for the electricity weight is all the non-domestic electricity meters in the Sub-
national consumption statistics (profile classes of 0 and 3 – 8)29, and any other electricity
meters that match to a building in the ND-NEED building stock dataset. The sample is the
number of electricity meters in the ND-NEED sample.

To account for biases in the ND-NEED sample the electricity weights are constructed based on
their average electricity consumption in 2017 - 2019 and meter profile class. The population
and sample of meters is stratified into 17 consumption bands and into seven profile classes to
form a matrix. A few of the cells in the matrix have too few counts in either the population or
the sample to be stratified into a consumption band (a count of below 5 was used as the
minimum cut-off). In these cases, two or more consumption bands were merged (in both the
population and the sample).
For each cell in the matrix, the ratio of population count to sample count is calculated. Any
meters in the sample with a profile class of 1 or 2 are given a weighting of one, as they will also
appear in the population.

If a building has multiple meters the total consumption for the building is divided by the number
of meters and assigned the resulting consumption band.

For each combination of consumption band/profile, a single electricity weight is calculated, as
the population to sample ratio, averaged over the last three years (2017-2019). This is then
applied to all years of electricity consumption, for each building in the sample, in the
corresponding band.

Gas weight
The population for the gas weight is all the non-domestic gas meters in the Sub-national
consumption statistics30 (meters than consume more than 73,200 kWh a year), and any other
gas meters that match to a building in the ND-NEED building stock dataset. The sample for the
gas weight is the gas meters in the ND-NEED sample.

To account for biases in the ND-NEED sample the gas weights are constructed based on their
average gas consumption in 2017 - 2019. The population and sample of meters are stratified
into 17 consumption bands. For each cell in the matrix, the ratio of population count to sample
count is calculated.
A few of the cells in the matrix have too few counts in either the population or the sample to be
stratified into a consumption band (a count of below 5 was used as the minimum cut-off). In
these cases, two or more consumption bands were merged (in both the population and the
sample).
Any gas meters with a consumption of less than 73,200 kWh a year are given a gas weight of
one as all meters in the population will also be in the sample.

29 Profile classes 1 and 2 indicate a domestic property. Profile classes 0 and 3 – 8 indicate a non-domestic
property.
30 Sub-national gas consumption statistics - https://www.gov.uk/government/collections/sub-national-gas-
consumption-data

46

If a building has multiple meters the total consumption for the building is divided by the number
of meters and assigned the resulting consumption band.

For each consumption band, a single gas weight is calculated, as the population to sample
ratio, averaged over the last three years (2017-2019). This is then applied to all years of gas
consumption, for each building in the sample, in the corresponding band.
Removing non-buildings
Once the electricity and gas weights have been calculated the buildings that were originally
included in the ND-NEED electricity/gas consumption sample, but that are not considered to be
non-domestic buildings in ND-NEED (‘non-buildings’), are removed. The buildings that are
removed are: Caravan Parks, Advertising Right and Premises, Car Parks, Beach Huts,
Quarries and Telecoms.
The removal of these ‘non-buildings’ reduces the size of the ND-NEED electricity consumption
sample from 858,000 buildings to 847,000 buildings, and the size of the gas consumption
sample from 375,000 buildings to 373,000 buildings.
Figure 34: The removal of non-buildings from the ND-NEED electricity and gas consumption
samples.

The removal of non-buildings from the sample also removes the energy consumption
associated with these non-buildings from the ND-NEED consumption figures (18 TWh for
electricity and 16 TWh for gas in 2019).
The removal of non-buildings from the ND-NEED sample is one of the reasons that the ND-
NEED energy consumption figures for non-domestic buildings are generally lower than
comparable figures from other sources such as the Subnational consumption statistics.
Comparing the results in ND-NEED to comparable figures from
other publications
Consumption by building use
The electricity/gas consumption of non-domestic buildings broken down by building use is
available in other publications as well as in ND-NEED.

47

Figures 35 and 36 compare the total electricity and gas consumption figures for non-domestic
buildings from three different sources (ND-NEED, BEES31 and ECUK32).
In general, all three publications have similar electricity consumption figures by building use.
The figures in ECUK are generally higher than the figures in ND-NEED and BEES. This is
consistent with the fact that ECUK covers the whole of the UK, whereas the ND-NEED and
BEES just cover England and Wales. Methodological differences also account for some of this
difference.
The notable exception to this is Factories where consumption in BEES is much lower than in
ND-NEED (11 TWh in BEES compared to 40 TWh in ND-NEED). Factory consumption figures
are not available for ECUK. This difference can be explained by a difference in the BEES and
ND-NEED methodologies. The BEES consumption figure refers to all electricity consumed by
the building whereas the ND-NEED figures, as they are based on meter point data, refer to all
energy consumed by the building and any activity inside the building. In the case of Factories,
this means that industrial processes are not included in the BEES consumption figures, but
they are included in ND-NEED.
The gas consumption figures show a similar pattern to the electricity consumption figures. For
all sectors except Factories the consumption figures are relatively consistent across all three
publications. The ND-NEED consumption figures for Factories is much higher than the BEES
consumption figure for the reason stated above.
Figure 35: Non-domestic building electricity consumption from this version of ND-NEED for
2016, BEES for 2014-1533, and ECUK for 201634

31 BEES, Overarching report tables, Figure 3.1 - https://www.gov.uk/government/publications/building-energy-
efficiency-survey-bees
32 ECUK, End uses data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-
uk
33 BEES, Overarching report tables, Figure 3.1. BEES does not have figures for gas so non-electric consumption
is used
34 ECUK, End uses data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-
uk

48

Figure 36: Non-domestic building gas consumption from this version of ND-NEED for 2016,
BEES for 2014-1535, and ECUK36 for 2016

Consumption over time
The total electricity/gas consumption from non-domestic buildings over time is also available
from other publications.
Figures 37 and 38 compare the normalised change in non-domestic electricity and gas
consumption over time from three different sources (ND-NEED, DUKES and Subnational37).
The total non-domestic building consumption from these sources varies due to methodological
and definitional differences. Because of this normalised electricity/gas consumption is
presented so the trends over time can be easily compared.
Note for gas consumption both the subnational and ND-NEED gas year runs from mid-
May – mid-May, while the DUKES gas year is the calendar year Jan – Dec. This may
cause differences in the trends seen in these publications.

All 3 data sources show that non-domestic building electricity/gas consumption has remained
broadly stable between 2012 – 2019, with some evidence of a decrease for electricity
consumption.

35 BEES, Overarching report tables, Figure 3.1. BEES does not have figures for gas so non-electric consumption
is used
36 ECUK, End uses data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-
uk

49

Figure 37: Non-domestic building normalised electricity consumption 2019 from ND-NEED,
Subnational38 and DUKES39.

Figure 38: Non-domestic building normalised electricity consumption 2019 from ND-NEED,
Subnational40 and DUKES41.

38 Subnational electricity consumption data 2019 - https://www.gov.uk/government/collections/sub-national-
electricity-consumption-data
39 DUKES electricity consumption- https://www.gov.uk/government/statistics/electricity-chapter-5-digest-of-united-
kingdom-energy-statistics-dukes. Industry, commercial and public administration used as a proxy for non-
domestic buildings. Electricity from the public distribution system.
40 Subnational gas consumption data 2019 - https://www.gov.uk/government/collections/sub-national-gas-
consumption-data.
41 DUKES gas consumption - https://www.gov.uk/government/statistics/natural-gas-chapter-4-digest-of-united-
kingdom-energy-statistics-dukes. Industry, commercial, public administration and misc used as a proxy for non-
domestic buildings. Total natural gas.

50

Current limitations of ND-NEED
There are several aspects of ND-NEED’s methodology which currently limit the insights that’s
ND-NEED can provide. Before the next publication of ND-NEED, work will be undertaken to
see if any of these limitations can be addressed.
The key limitations of ND-NEED are:
Address matching
• Incorrect matches between the non-domestic buildings data and the energy
consumption data (see Annex C).
o Due to difficulties with the address matching process used to match the energy
consumption data to AddressBase, some matches will not be correct. It is
estimated that around 5% of address matches are incorrect.
o If an energy meter data has been matched with the wrong address in
AddressBase it will then match to the wrong address in the ND-NEED building
stock. The consumption of that building with therefore be assigned to the wrong
building and business characteristics information, and weighted accordingly,
causing distortions in the data.

• Around 50% match rate between the non-domestic buildings data and the energy
consumption data (see Annex C).
o Only 48% of non-domestic buildings in the ND-NEED building stock are matched
to electricity consumption data and only 21% are matched to gas consumption
data (including non-buildings).

Weighting (see weighting section of the methodology)
• Because we cannot match all non-domestic buildings data with their energy
consumption data, weighting is needed to ensure the ND-NEED consumption figures
are representative of the population.
o There are however several limitations of the ND-NEED weighting process. Firstly,
there is currently no information in ND-NEED about business size at the
population level. Business size is therefore not accounted for in the weighting
process. Secondly, although floor area is a factor in the weighting process, the
relatively high rates of missing floor area information in ND-NEED reduces the
efficacy of the floor area weighting.
• Applying energy weights to energy intensity figures.
o Energy intensity is influenced by both the energy consumption and the floor area
of a building, whereas the energy weight currently applied to energy intensity
figures is just influenced by a building’s energy consumption. This means that
differences in floor area between the buildings in the sample and the population
are not accounted for.

51

• Manual elements of the weighting process
o The current ND-NEED weighting processes requires subjective decisions to be
made about when to merge adjacent cells when there are a low number of
buildings/meters in a particular cell and which cell to merge these ‘low value’ cells
with. This means that two people running the weighing process would calculate
slightly different weights, and as a consequence slightly different consumption
values. This adds to the uncertainty surrounding all ND-NEED consumption
estimates.
Time series
• There are several reasons why consumption in the earlier years in the time series
maybe being underestimated in ND-NEED:
o The building stock figures used in ND-NEED, based on position of the 2017 NDR
at March 2020, do not include sites that have closed (or no longer attract
business rates, for example, if converted to domestic use). Because of this, any
buildings that do not exist in March 2020 will not be included in the ND-NEED
stock and so cannot be matched to energy consumption data.
o The energy consumption data used in this version of ND-NEED only includes
meters which are active in 2019. Because of this, any energy consumption from
meters that have now been deenergised e.g. because the building has been
destroyed, is not captured.
o The address matching algorithm uses addresses from Jan 2019 Addressbase
and Sep 2020 Addressbase. This means that any old addresses that no longer
exist in Addressbase (because the building no longer exists or because the
buildings address has changed e.g. if a new business is occupying the building)
will not be matched.

• The weighting process
o The weighting process in ND-NEED is currently unable to account sufficiently for
the underestimation of consumption in earlier years. This makes it difficult to
create a robust time series from the ND-NEED. Energy consumption in earlier
years is likely to be underestimated, as energy consumed by buildings/meters
that no longer exist would not be captured.
o The manual element of the weighting process (see above) introduces uncertainty
into the consumption figures which can also have a small impact on the time
series trend presented. This means that it is not possible to determine whether
small changes in the time series trend are real changes in consumption or
caused by noise in the data.
Missing data
• Many buildings in ND-NEED are missing information on business/building size (see
Annex E).
o The main consequences of the high level of missing data in ND-NEED is that the
consumption value associated with a particular business or building size will likely
be an underestimate, as some consumption from buildings that are missing
business/building size information will likely fall into that category.

52

Mixed building use
• Assigning building use to buildings containing multiple hereditaments of different
building uses.
o The data received from the VOA (NDR/SMV) is at the hereditament level and
must be aggregated to the building level for use in ND-NEED. Where a building
contains multiple hereditaments of different building uses the building use of the
hereditament with the largest floor area is assigned to the building. However, it is
possible that the building use of the hereditament with the largest floor area does
not best represent the building use of the building as a whole. Improving the
building use classification for building uses with multiple hereditaments would
improve the accuracy of ND-NEED’s energy consumption and energy intensity
figures by building use.
Business size
• The business size information in ND-NEED is the size of the business that occupies the
building, not the number of employees that work in the building. Because of this a small
branch of a national store will be a large business in ND-NEED, even if there are only a
few employees in the building.

53

Accompanying tables
The following tables are available on the department’s statistics website:
https://www.gov.uk/government/collections/non-domestic-national-energy-efficiency-data-
framework-nd-need

1
Number and total floor area of ND-NEED non-domestic buildings by
building use, end of March 2020. (Not updated from ND-NEED 2020).
2 Number and total floor area of ND-NEED non-domestic buildings by floor
area bands, end of March 2020. (Not updated from ND-NEED 2020).
3 Number of ND-NEED non-domestic buildings by year of construction, end
of March 2020. (New for ND-NEED 2021).
4
Number of ND-NEED non-domestic buildings by business size, end of
March 2020. (New for ND-NEED 2021).
5
ND-NEED non-domestic building number and floor area by building use
and building size, end of March 2020. (Not updated from ND-NEED 2020).
6
ND-NEED non-domestic building number and floor area by building use
and business size, end of March 2020. (New for ND-NEED 2021).
7
ND-NEED non-domestic building number and floor area by building size
and business size, end of March 2020. (New for ND-NEED 2021).
8
ND-NEED non-domestic building electricity and gas consumption by
building use, 2016-2019. (2016 - 2018 updated from ND-NEED 2020,
2012 - 2015 and 2019 new for ND-NEED 2021).
9 ND-NEED non-domestic building median electricity and gas intensity by
building use, 2016 - 2019. (2016 - 2018 updated from ND-NEED 2020,
2012 - 2015 and 2019 new for ND-NEED 2021).
10
ND-NEED non-domestic building electricity and gas consumption by
building size, 2019. (2019 new for ND-NEED 2021).
11
ND-NEED non-domestic building median electricity and gas intensity by
building size, 2019. (2019 new for ND-NEED 2021).
12
ND-NEED non-domestic building electricity and gas consumption by
business size, 2019. (2019 new for ND-NEED 2021).
13 ND-NEED non-domestic building median electricity and gas intensity by
business size, 2019. (2019 new for ND-NEED 2021).
14 ND-NEED non-domestic building median electricity and gas consumption
by building use, 2012 - 2019. (2019 new for ND-NEED 2021).
15 Electric meter profile classes of buildings in the ND-NEED sample, 2019.
(New for ND-NEED 2021).
16 Gas meter consumption of buildings in the ND-NEED sample, 2019.
(New for ND-NEED 2021).
17
ND-NEED non-domestic building electricity and gas consumption by
building use and building size, 2018-2019. (Updated for ND-NEED 2021).
18
ND-NEED non-domestic building electricity and gas consumption by
building use and business size, 2018-2019. (Updated for ND-NEED 2021).

54

19
ND-NEED non-domestic building electricity and gas consumption by
business size and building size, 2018-2019. (Updated for ND-NEED
2021).

Related statistics
Non-domestic National Energy Efficiency Data-Framework 2020
Previous release of the ND-NEED statistics, November 2020
Non-domestic National Energy Efficiency Data-Framework: energy statistics 2006-2012
Previous release of the ND-NEED statistics, March 2015.
The non-domestic National Energy Efficiency Data-Framework (ND-NEED)
Overview of the concept of ND-NEED, known issues, plans for improvement, preliminary
results and the proposed weighting methodology, May 2014.
National Energy Efficiency Data-Framework (NEED)
Summary statistics of domestic energy consumption 2005-2018, June 2020.
Subnational electricity consumption data
Local authority level electricity consumption statistics (2003 – 2019).
Subnational gas consumption data
Local authority level gas consumption statistics (2004 – 2019).
Energy consumption in the UK (ECUK)
Information for overall energy consumption in the UK with details of the transport, domestic,
industry and services sectors.
Digest of UK energy statistics (DUKES)
Detailed and comprehensive picture on the production and consumption of individual fuels and
energy as a whole.

55

Revisions policy
The BEIS statistical revisions policy sets out the revisions policy for these statistics, which has
been developed in accordance with the UK Statistics Authority Code of Practice for Statistics.

User engagement
Users are encouraged to provide comments and feedback on how these statistics are used
and how well they meet user needs. Comments on any issues relating to this statistical release
are welcomed and should be sent to: xxx@xxx.xx.
The BEIS statement on statistical public engagement and data standards sets out the
department’s commitments on public engagement and data standards as outlined by the Code
of Practice for Statistics.
Contact
• Responsible statistician: Maya Fooks
• Email: xxx@xxx.xx
• Media enquiries: xx-xxxx-xxxx
• Statistical enquiries: xx-xxxx-xxxx

56

4. Annex A: Changes since the 2020
publication

ND-NEED was last published in November 2020. Since 2020 there have been several
changes to the methodology.
The key changes are listed below:
• Improvements to address matching (see Annex C)
• Updated meter data

A further change between the 2020 and 2021 versions of ND-NEED are the charts and data
tables that have been published.
The 2021 version of ND-NEED includes new information about the business size and year of
construction of the non-domestic building stock. This was not presented in the 2020 version of
ND-NEED.
The 2021 version of ND-NEED also contains a slightly different combination of charts and data
tables for the energy consumption data. The charts and data tables included in the 2021
version of ND-NEED contain more detailed information about the distribution of energy
consumption within sections of the building stock.

57

5. Annex B: Understanding ND-NEED 2021
revisions
The consumption figures published in ND-NEED 2021 show some revisions from comparable
figures that were published in ND-NEED 2020. Some examples of these revisions can be seen
in Tables 2 and 3 below.
Table 2: ND-NEED electricity consumption 2016 – 2018, from ND-NEED 2020 and ND-NDEED
2021.

Table 3: ND-NEED gas consumption 2016 – 2018, from ND-NEED 2020 and ND-NDEED 2021.

There are several differences between ND-NEED 2020 and ND-NEED 2021 that have
contributed to these revisions.
• The new 2021 address match algorithm will match a slightly different set of buildings to
their corresponding meters than were matched using the 2020 address matching
algorithm.

• The historic address-matching list (see Annex C) increases the number of buildings with
consumption data in the ND-NEED sample.

• The ND-NEED weighting process contains a manual element where subjective
decisions need to be made. This means that if the weights were recreated using the
exact same data there could be differences in the final consumption values.

Electricity
consumption 2016
(TWh)
Electricity
consumption 2017
(TWh)
Electricity
consumption 2018
(TWh)
ND-NEED 2020
137
139
140
ND-NEED 2021
132
133
133
Size of revision
-5
-6
-7

Gas consumption
2016
Gas consumption
2017
Gas consumption
2018
ND-NEED 2020
147
148
153
ND-NEED 2021
148
150
153
Size of revision
+1
+2
No change

58

• The ND-NEED weighting process calculates weights based on consumption in the latest
three years and applies these weights to all years in the time series. In ND-NEED 2020
the weights were therefore calculated from 2016 – 2018 consumption data, but in ND-
NEED 2021 they are calculated from 2017 – 2019 consumption data.

• The meter level data which ND-NEED is based is revised each year so we would expect
subsequent revision in the ND-NEED data.

These reasons highlight the uncertainty that surrounds the ND-NEED consumption figures.
Because of this, small revisions to the ND-NEED consumption data or small changes in ND-
NEED consumption over time should be interpreted with caution as they may be a result of the
methodological issues described above, rather than reflecting a true trend in the data.

59

6. Annex C: Address matching
The ND-NEED sample is created by matching the ND-NEED building stock with corresponding
meters from BEIS’s energy meter data. However, the non-domestic building stock and BEIS’s
energy meter data do not share a unique identifier and so cannot be directly matched.
Instead, the energy meter data is first matched to the AddressBase dataset. This is an
Ordnance Survey dataset that contains the addresses of all buildings in Great Britain as well
as their Unique Property Reference Number (UPRN). As both the energy meter data and the
AddressBase dataset contain the buildings address, address matching is used to match these
datasets together.
In ND-NEED 2021 there were two parts to the address matching process:
1. An algorithm was used to carry out the address-matching. This was the broadly the
same algorithm that was used for the address-matching in ND-NEED 2020, with some
small changes to improve match quality. Where buildings in the energy meter dataset
successfully match to AddressBase, the UPRN for the building can be identified. As the
non-domestic building stock contains UPRN information, the UPRN can then be used to
match the energy meter and building stock datasets.

2. Where meters could not be match to an address using the address matching algorithm
described above, a list of Meters-UPRN from a different address matching algorithm
was used. The address matching algorithm was developed for BEIS by GB consultants
and used as part of the address matching process in 2015. This was not used in ND-
NEED 2020.
The addition of this historic address matching algorithm improves the match rate between the
buildings stock and the energy meter data from 43% to 49%.

60

7. Annex D: Building use categories
The building use categories that are used in this version of ND-NEED have been chosen to
align as far as possible with the categories used in the Energy Consumption in the UK
(ECUK)42 and Business Energy Efficiency Statistics (BEES)43.

In the March 2015 publication of ND-NEED, six building use categories were used: Factories,
Offices, Restaurants, Shops, Warehouses and Other.

In this publication 10 building use categories are used: Arts, Community and Leisure;
Education; Emergency Services; Factories; Health; Hospitality; Offices; Shops; Warehouses
and Other. Details of the buildings uses that are included in these 10 categories can be found
in Table 4 below.

Table 4: The building uses included in the 10 building use categories in ND-NEED.

42 ECUK, End uses data tables, Table U5 - https://www.gov.uk/government/statistics/energy-consumption-in-the-
uk
43 BEES, Overarching report tables, https://www.gov.uk/government/publications/building-energy-efficiency-
survey-bees
44 Note – some military premises are not included in the NDR and so are not covered in ND-NEED.
Building use
Buildings included
Arts, Community and Leisure
Cinemas, Community centres, Libraries/Museums, Sports
centres, Sports grounds
Education
Nurseries, State schools, Private schools, Universities
Emergency Services
Ambulance/Fire stations, Police stations
Factories
Factories
Health
Healthcare
Hospitality
Restaurants, Hostels, Hotels, Holiday homes/Guesthouses,
Pubs
Offices
Offices
Shops
Shops
Warehouses
Warehouses
Other
Bus stations/moorings, Cemeteries, Docks, Electricity
hereditaments, Garages, Markets, Military premises44,
Sewage treatments

61

8. Annex E: Removing inaccurate floor area
data
The NDR/SMV received from the VOA contains information on floor area. This floor area
information is at hereditament level. For some hereditaments, this floor area information is
missing in the VOA’s data. As ND-NEED presents information at the building level, when there
are multiple hereditaments in a single building are the floor area of the constituent
hereditaments are added together.
Before hereditament floor areas are aggregated to the building level all hereditaments with a
floor area of <15m2 have their floor area value are removed. This is because, for the purposes
of ND-NEED, these floor area values are thought to be inaccurate.
The floor area of building uses for which floor area is not used to inform VOA’s building rating
are also removed.
This occurs for the building uses:

Abattoirs and
Slaughterhouses,
Agricultural Showgrounds,
Air Ports,
Air Strips,
Aluminium Smelting Works,
Amusement Parks,
Aquaria,
Archives,
Arenas,
Army Hereditaments,
Artificial Fibre Works,
Asphalt Plants,
Beet Sugar Factories,
Bingo Halls,
Bird Sanctuaries,
Bowling Centres,
Brickworks,
Bulk Cement Storage
Depots,
Bus Garages,
Bus Stations,
Caravan Parks,
Caravan Sites and Pitches,
Cattle Breeding Centres,
Cement Tiles Works,
Cement Works,
Cemeteries,

Chalet Parks,
Chemical Works,
Cinemas,
Civic and Public Buildings,
Civic Amenity Sites,
Civil Airports,
Coaching Inns,
Coastguard Stations,
Courts,
Coking and Carbonising
Plants,
Colleges of Further
Educations,
Communication Stations,
Concert Halls,
Concrete Batching Plants,
Concrete Block Works,
Concrete Product Works,
Conference and Exhibition
Centres,
Conference Centres in
Country Houses,
Country House Hotels,
Courts,
Crematoria,
Cricket Centres,
Cricket Grounds,
Crown Miscellaneous,

District Heating Undertakings
and Networks,
Docks and Harbours,
Domestic Fuel Installations,
Effluent Minewater
Treatment Plants and
Premises,
Electricity Undertakings,
Field Study Activity and
Adventure Centres,
Fire Stations,
Fish Farms,
Flour Mills,
Football Stadia,
Formula Assessed
Miscellaneous,
Game Farms,
Gas Processing Plants,
Go Kart Rinks,
Golf Driving Ranges,
Grain Silos,
Greyhound Racetracks,
Hatcheries/Poultry Farms,
Health Farms,
Heliports,
Heredits used for Primary
Treatment/Processing of
Minerals,

62

Heritage Railways,
Holiday Centres,
Horse Racecourses,
Hospitals and Clinics NHS,
Hospitals and Clinics Private,
Hotels (3 star and under),
Operated,
Ice Rinks,
Information/Visitor Centres,
Iron and/or Steel Works,
Lakes with Water Sport
Facilities,
Land used for Car Boot
Sales,
Landfill Gas Generator Sites,
Land used for Waste
Composting,
Leisure Miscellaneous,
Libraries,
Lifeboat Stations,
Liquid Bulk Storage,
Livestock Markets,
Local Authority Schools,
Lodges,
Marinas,
Markets,
Mineral Depots and
Premises,
Minerals Miscellaneous,
Mineral Producing
Hereditament – Blockstone,
Mineral Producing
Hereditament – Brine,
Mineral Producing
Hereditament – Chalk,
Mineral Producing
Hereditament – China Clay,
Mineral Producing
Hereditament – Clay,
Mineral Producing
Hereditament – Coal,
Mineral Producing
Hereditament – Fluorspar,
Mineral Producing
Hereditament – Gas,
Mineral Producing
Hereditament – Hardrock,

Miniature Railways,
Model Villages,
Mineral Producing
Hereditament – Inert,
Mineral Producing
Hereditament – Oil,
Mineral Producing
Hereditament – Other
Mineral Categories,
Mineral Producing
Hereditament – Putrescible,
Mineral Producing
Hereditament – Sand,
Gravel, and, Slates,
Mortuaries,
Motor Racetracks,
Motor Vehicle Works,
Motorway and Major Road
Service Areas,
Museums and Art Galleries
(Contractors),
Museums and Art Galleries
(Non-Contractors),
Nuclear Establishments,
Nursing Homes,
Observatories,
Oil Refineries,
Oxbridge Colleges,
Peat Fields,
Petrol Filling Stations,
Pipelines,
Pitch and Putting Greens
Pleasure Piers,
Point to Point and Eventing
Courses,
Police Stations,
Police Training Colleges,
Power Generators,
Prison Service
Hereditaments,
Property used for Secondary
Aggregate Processing,
Provender Mills,
Public Conveniences,
Public Halls,
Public Houses/Pub
Restaurants,

Public Houses/Pub
Pumping Mines
Railways and Tramways,
Religious Retreats/Study
Centres (Residential),
Restaurants (inc. Lodge),
Roller Skating Rinks,
Rugby League Grounds,
Sea Dredged Aggregate
Processing Plants and
Depots,
Sewage Works,
Ship Building Yards,
Ship Repair Yards,
Ski Centres,
Showhouses,
Speedway Racetracks,
Spoil Heap Workings,
Sporting Rights,
Sports and Leisure Centres
(Wet and Dry),
Sports and Leisure Centres
Within/Part of Specialist
Property,
Sports Stadia,
Stately Homes and Historic
Houses,
Statutory Docks and
Harbours (Formula),
Statutory Docks and
Harbours (Non-Formula
Prescribed),
Statutory Docks and
Harbours (Other),
Surgeries Clinics Health
Centres (Contractors
Valuation),
Swimming Pools (Local
Authority),
Swimming Pools (Private),
Telecommunications Cable
Networks,
Telecommunications
Switching Centres,
Telescope Sites,
Tennis Centres,
Theatres,
Theme Parks,
Timeshare Complexes,
Tolls,

63

Totalisators on Horse
Racecourses,
Tourist Attractions/Dark
Rides,
Training Centres
(Residential),
University – Ancillary Land or
Buildings,
Universities (excluding
Oxbridge),

War Game Courses/Misc.
Agriculture Use,
Universities (excluding
Oxbridge),
University Occupation Within
Hospitals,

Waste Incinerator Plants,
Waste Transfer Stations,
Water Undertakings (Non-
Statutory),
Windmills,
Zoos and Safari Parks.

64

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