Measure what is important; don’t make important what you can measure.Robert S. McNamara
Understanding occupancy has never been more important. It is the fundamental driver of space demand and therefore corporate real estate costs, and it reflects the behaviours and choices the workforce make. In turn, this selection of the working environment and conditions is one of the key factors contributing to productivity.
These are now at the heart of workplace strategy, and there is broad recognition that understanding occupancy and workplace behaviour is fundamental to several key strategic goals of the corporate real estate executive: wellbeing; reducing cost; increasing productivity; reducing environmental impact; and attracting and retaining talent.
However, despite the importance of understanding occupancy, the industry seems to be struggling with two challenges:
- Articulating the business questions that occupancy analytics can help with, and bridging the gap between what gets measured and what matters; and
- Poor data quality, inadequate data governance and an analytical naivety that collectively prevent the analytics having legitimacy.
What follows sets out a framework that can help organizations begin to address both challenges. For the former, a rigorous vocabulary is established that allows dialog to take place and provides the building blocks for articulating quantitatively what is important about occupancy in a modern workplace. This is developed from the perspective of workplace behaviour and is independent of what can be measured.
The latter challenge is addressed by considering how these quantitative measurements can be made in the real world. It provides the basis of a method for the collection, management and use of occupancy data.
The language used is intended to be accessible to the layman but does attempt to be sufficiently rigorous for unambiguous adoption and implementation for analytical purposes. To this end, terms defined will be capitalized after their definition is introduced.
Anatomy of Occupancy Analytics – The Fundamentals:
- Occupancy and Utilization establishes the definitions of terms used throughout and which form the foundation of occupancy analytics, including headcount, space, time, occupancy and utilization
- Availability, Demand and Constraints goes on to provide vocabulary that expresses how the analysis of occupancy is not merely an analysis of space that is utilized
- Perception considers the impacts on choices that occupants make that are driven by how availability, demand and constraints are interpreted by them
- Other Core Dimensions brings the remaining terminology to the table, including identity, space type and place, activity and interaction, and productivity