Occupancy analytics

When it comes to optimizing the workplace, there are two dominant opportunities:

  • reduce the leasing costs per sqft/sqm; and
  • reduce the area per person.

My focus is on the latter. It is widely recognized that office space is utilized at between 30% and 40%. In principle, that provides for an opportunity to reduce the space needed – and hence the costs of that space – by 60% to 70%. This dwarfs the savings that are likely to be achieved through lease renegotiations and most location strategies.

But what space am I not using?

The challenge is identifying exactly which space really can be removed without adversely impacting productivity or employee engagement.

I have demonstrated – based on experience of analyzing millions of sqft of office space and the subsequent execution of restacks – that it is possible to apply robust analytical techniques to identify this surplus far more accurately than has been possible through simplistic security badge analysis or observational studies.

By using multiple data-sources to understand occupancy and behaviors in buildings, it is possible to model and correct some of the intrinsic unreliability in occupancy data.

The difference between what people are actually doing and what data we can obtain from proxies (like access control systems, reservation systems, IT networks etc.) is also often overlooked.

I can help you really understand what to measure, how to measure it, and how to interpret the results.

I can’t promise 70% savings, but in a typical location, it may well be possible to identify up to 50% surplus. This can be used to shape portfolio strategy (see demand based portfolio planning) or simply enable a consolidation or reduction.