Methodology for realising ESG performance of corporate real estate assets through digital data architectures

From investors, to governments, to tenants and end-users, stakeholder needs around building data are profoundly changing, putting a greater emphasis on performance on environmental, social and governance (ESG) key performance indicators (KPIs) alongside traditional financial returns. This environment necessitates building owners and property managers to look at the ESG data they have today, assess how this data will be used differently in the future, and predict what gaps may need to be filled in order to create a dynamic building data management ecosystem that is responsive to investor, manager, tenant and the wider regulatory demands of tomorrow’s commercial real estate (CRE) assets. This paper explores the importance of advanced data collection and management in accelerating the ESG performance of buildings. A solid data strategy and system modelling is the gateway to understanding, calculating and mitigating the environmental impact of buildings and creating resilience in an increasingly uncertain and volatile landscape. The paper defines the types of data required and explains how this data feeds into a modelling and simulation software. It also discusses considerations for the tools needed to make a model more representative of the property and varied future scenarios. It then illustrates these best practices using real customer examples and examining critical KPIs that many CRE managers and building owners need to track and manage today.