Quantifying the impact of green leasing on energy use in a retail portfolio: limits to big data analytics

The retail sector is a significant contributor to any industr ialised economy and, as a result, a major consumer of energy. Large retailers are aware of the contribution energy makes to their operational costs and of many opportunities available for efficiency measures. However, many retailers are tenants rather than owner-occupiers greatly complicating the implementation of energy and carbon saving technologies (‘energy upgrades’) because of this predominance of leasehold properties. This introduces a barrier as many of the larger, and hence more impactful, energy efficiency measures require active collaboration between the (landlord) owner and (tenant) occupier for successful implementation, possibly requiring changes to either the building fabric or plant/equipment. New mechanisms have been developed aiming to smooth this possible barrier, through the use of environmentally conscious legal instruments: either Memorandum of Understanding (MoU) between parties with existing tenancy agreements; or directly inserted clauses specifying mechanisms for collaboration between parties within new lease agreements, so called ‘Green Leases’ (GL). This paper aims to explore whether there are quantifiable benefits from their use. Using data from a large UK retail chain we have investigated, using a number of different analytical methods, the visibility of consumption changes after the introduction of an MoU or GL for a number of different classes of stores operated. With the limited dataset available it is, however, difficult to establish a clear causal link between their introduction and statistically significant consumption changes. As such we discuss these limitations and how with the addition of further sources of information we may be able to improve on the analyses performed.