Real Estate

Assessing smartness in smart buildings

Written by lketr

To overcome the challenges posed by the dominance of
technology in the built environment in the digital era, it
is important that tools enabling a precise measure of buildings’ smartness be readily available to real estate players
who, by training, are not technology experts. One such tool
is a scoring methodology for smart buildings which would
lay the foundations to a greater standardization of commercial real estate in smart cities.
Similar to green buildings’ Leadership in Energy and
Environmental Design (LEED) certification, smart buildings will need to come with standards to assess their performances and guide commercial real estate players.
Attempts to design evaluation frameworks and smartness
scores have been hindered by the lack of consensus stemming from multiple and diverse stakeholders (private sector, public authorities, technology companies, and real
estate specialists). Private companies have been the first
to develop their own sets of metrics, which are customarily
designed around their clients’ demands and/or product
As countries across the globe have adopted different
KPIs for smart buildings, the resulting indicators tend to
reflect deeply rooted interpretation of smart buildings’
essence and contributions to a smart environment. While
Europe’s ongoing Smart Readiness Index (SRI) (Stijn et al.,
2017) spearheaded by the European Commission
Directorate-General for Energy is geared toward sustainability, the United States (Building Intelligence Quotient
(BiQ)) emphasizes the performance and cost effectiveness
of smart buildings (Katz and Skopek, 2009). By the same
token, Asian countries have adopted a wide range of indicators with very different KPIs (Ghaffarianhoseini et al.,
Irrespective of their KPIs, most existing scores embody
an engineering view of smart buildings. An engineering
view tends to define smart buildings as highly sophisticated, self-contained ‘‘machines,’’ by stressing out their
technology rather than their interactive dimension. Noticeably, despite covering a wide array of elements, these
scores overwhelmingly ignore a building’s ability to interact with the smart environment.1 As identified by Alwaer
and Clements-Croome (2010), key performance indicators
(KPIs) for assessing sustainable intelligent buildings
should be based on ‘‘people, products and processes, and
their inter-relationships.’’ Therefore, in their current versions, existing scores of smart buildings are not sufficient
for commercial real estate. This article lists three directions
that future endeavors to build scores should follow.
Firstly, to be relevant to commercial real estate, scoring
methodologies should capture buildings’ ability to adapt to
technological changes. Assessing adaptability in the midst
of an industrial revolution with discontinuous innovations
is a challenge. As pointed out by Gaffarianhoseini et al.
(2016), the key to designing a relevant scoring methodology is to treat smart buildings as ‘‘dynamic and evolutionary entities rather than static and fixed ones’’. For instance,
Europe’s SRI stresses the importance of buildings’ future,pub-1336910036217970 , DIRECT, f08c47fec0942fa0

proofing and establishes a difference between ‘‘smart
ready’’ and ‘‘smart now.’’ Smart ready describes a building
that is ‘‘itself smart but its potential to realise the benefits
from smart services may be constrained by limiting factors in the capability of the services it connects to as its
boundary’’ (Stijn et al., 2017). Smart now captures a
building’s operational smart capability. The SRI methodology focuses on smart ready, by allowing ‘‘relevant new
capabilities to be reflected as soon as possible and address
future proofing needs.’’
Secondly, in addition to setting industry standards,
smart building scores should reflect buildings’ value drivers in smart environments, that is, flexibility and versatility of the physical structure, smart readiness and future
proofing of the enterprise, as well as ability to interact
with digital space to meet their occupants’ changing
needs. The ‘‘omni-use’’ property type introduced in this
article would potentially allow maximum versatility of
physical structure.
Thirdly, smart buildings scores should be designed with
the concept of index in mind. In effect, real estate in smart
cities which is still in its infancy offers a unique opportunity to adopt a bottom-up approach to index construction,
by aggregating individual scores at the building level into
price indices of smart buildings at the neighborhood, city,
country, and region levels. Individual scores could be
aggregated by predefined ranges of smartness (e.g. derived
from scores or smart certifications).
The analysis presented in this article only focuses on the
fundamental principles that the scoring methodology
should follow. Further research is needed to develop a fully
blown methodology. Assessing buildings’ smartness with a
standardized framework is a crucial step toward setting up a
market for smart buildings in smart cities as no market can
properly function without widely agreed norms

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