Learning from the “data poor”: energy management in understudied organizations

Date01 July 2014
Pages424-442
Published date01 July 2014
DOIhttps://doi.org/10.1108/JPIF-03-2014-0018
AuthorKathryn B. Janda,Catherine Bottrill,Russell Layberry
Subject MatterProperty management & built environment,Real estate & property,Property valuation & finance
Learning from the data poor:
energy management in
understudied organizations
Kathryn B. Janda
Environmental Change Institute, University of Oxford, Oxford, UK
Catherine Bottrill
Pilio Ltd, London, UK, and
Russell Layberry
Environmental Change Institute, University of Oxford, Oxford, UK
Abstract
Purpose – The purpose of this paper is to present new empirical data on leases, energy management,
and energy meters in the UK, with a particular focus on small and medium enterprises (SMEs) and
other “minor” players. The paper develops a new segmentation model that identifies six different
combinations of energy and organizational conditions.
Design/methodology/approach – The authors surveyed participants in an online energy
management and data analytics service. A 30-question online survey gathered data from 31
respondents on three kinds of infrastructure – legal, o rganizational, and technical.
Findings – SMEs and other minor players are generally “data poor,” lack energy managers, and have
legacy meters that are read only annually or quarterly; some rent via leases that inhibit permanent
alterations to the premises, including the meter.
Research limitations/implications – The research is exploratory and subject to self-selection bias.
Further research is needed into: lease language, governance structures, social practices to facilitate
cooperation between tenants and landlords; the scope for energy management positions in small
organizations; low-cost “smart-er” meters that can be reversibly retrofitted onto existing energy
meters; and the combination of these areas.
Practical implications – Organizations may need to augment a combination of legal,
organizational, and technical infrastructures to enable better energy management.
Social implications – SMEs and other “minor” energy users are important to society and the
economy, yet they are often overlooked by government programs. This developing data set can help
policymakers include these groups in their programs.
Originality/value – This paper presents a new conceptual framework for future research and new
empirical data on understudied groups.
Keywords SMEs, Energy management, Small and medium enterprises, Churches,
Legal infrastructure, Organizational infrastructure, Technical infrastructure, Tenanted property,
Non-profit sector, Theatres
Paper type Research paper
Introduction
The non-domestic building and organizational infrastructure in the UK is highly
varied. Most larger organizations operate in a mix of older and newer properties with
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1463-578X.htm
Received February 2014
Accepted March 2014
Journal of Property Investment &
Finance
Vol. 32 No. 4, 2014
pp. 424-442
rEmeraldGroup PublishingLimited
1463-578X
DOI 10.1108/JPIF-03-2014-0018
Portions of this work have been supported by the second phase of the UK Energy Research
Centre (UKERC) under its Demand Theme (www.ukerc.ac.uk). UKERC is funded by the UK
Research Councils’ Energy Programme through Grant No. NE/G007748/1. A version was
presented at the 2014 Improving Energy Efficiency in Commercial Buildings Conference
(April 1-3, 2014).
424
JPIF
32,4
different physical and technical energy characteristics. Some organizations have
energy managers; others do not. Some organizations have smart meters and data to
analyze; some even have analysts to work with the data, but many do not. Some
organizations are owner-occupiers; others are landlords or tenants. A lack of
information about the distribution, combination, and effects of these variables turns
energy management in the non-domestic sector into a stubbor n and “wicked” problem
(Rittel and Webber, 1973) rather than one that is “tame” and easy to solve.
From a policy perspective, little is known about physical and energy characteristics
of the UK non-domestic stock, let alone the distribution of its energy management
opportunities. Government models for the sector are based on data from the 1990s
which are in urgent need of updating (Nicholls, 2013). The Department of Energy and
Climate Change has launched a project to develop a new data set, but these efforts are
concentrating on larger sectors and are therefore unlikely to capture the full diversity
of issues for small and medium enterprises (SMEs). The energy managem ent problem
is particularly acute for many SMEs, typically without an energy manager, who have
been shown to not be able to understand their existing energy bills, let alone improve
their energy usage profiles using comparative feedback (Payne, 2000). Further,
there may be problems with access to data, control, and authority in buildings that are
leased rather than owner-occupied.
Much of the energy research on non-domestic buildings focusses on largest end-use
sub-sectors. The UK Valuation Office Agency (VOA) defines four high-level bulk
classes of premises: shops, offices, factories, and warehouses; at the lowest level of
detail, however, the VOA identifies as many as 400 categories (Bruhns and Wyatt,
2011). Most of the energy end-use attention focusses on the first two high-level
categories (office and retail), and there are specialists who focus on hotels, schools,
hospitals, and other “major” building types. “Major” in this instanc e is often defined in
terms of percentage of floor area; social or econo mic importance; or energy intensity.
However, we also know that these major sub-sectors alone do not capture the
complete picture of the non-domestic market. The full picture includes a much mo re
diverse mix of activities ranging from abattoirs (slaughterhouses), to dry ski
slopes, museums, village halls, and zoos (UK VOA, 2014). As carbon reduction targets
ratchet up, is it possible to achieve 80 percent reductions just by looking at the major
sectors? Is it fair to leave smaller, more diverse, or less energy-intensive users to
fend for themselves? What are the opportunities to make change in and across smaller
or more diverse building types?
This paper explores issues of energy management in SMEs and other understudied
building types. It begins with a background section on some problems involved in
under-explored areas: what is (un)known about SMEs and other minor subsectors,
leases, energy management practices, and metering infrastructure. This bac kground
builds a concept of the groups that have lower ability to measure and manage their
energy use, which we call the “minor leagues.” These groups are often either data poor,
analytically underprivileged, or both. Next, it describes the wo rk of a small company
called “Pilio” that works with several different types of “minor league” players,
assisting them to enrich their data streams and analytical capabilities. It then presents
new empirical data on the existing landscape of meters and leases in the UK, with
a particular focus on art venues and chu rches. Through survey results coupled
with Pilio’s contextual knowledge of the data set, it provides a snapshot of the energy
interests and challenges faced by organizations that are not the main target of
government policies, regulations, or assistance. In conclusion, it offers some insights
425
Learning from
the “data poor”

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