Most facilities and workplace managers conduct regular workplace utilisation surveys of desk usage either using manual counting or desk sensors. Reports generated from these show granular information about the average as well as peak utilisation of desk utilisation.
There are some easy wins to increase desk utilisation in your office.
1. Turn all desks used 0-20% of the time into hotdesking
Looking at your desk occupancy distribution chart (figure 1), we quickly identify the specific numbers of desks that are used 0-20% of the time over a given period. These desks can easily be repurposed as flexible working desks, without risking overutilisation.
Additionally, we identify that 10 desks are used 20-40% of the time. Allocating at least 5 of those desks to flexible desking will still give you enough desks.
2. Increase teams’ person to desk ratio
By tagging specific teams on your floor plans, you are able to view their utilisation rates and benchmark their performance.
In figure 2 it’s clear that this team has over 50 desks which are severely underutilised. The metric ‘peak occupied’ highlights that no more than 56 desks were utilised at the same time in the specified period.
3. Have better conversations with business unit leaders
With more accurate data in hand you can have better conversations with business unit leaders on how many desks they actually need. The conversations will shift from ‘how many desks do you need’ to ‘how can you use your space more productively’.
4. Use soft seating as overflow buffer
When looking at floor level heatmap data (figure 3), it’s easy to see which desks that are located near highly utilised areas. If for instance the green areas are soft seating, and the red areas hotdesks, you can safely optimise for very high desk occupancy rates (>80%). If all desks are full, employees can flow over to the soft seating. Caveat: this assumes good design where employees are as happy to work in alternative seatings as with desks.
5. Identify peak days and encourage work from home
Using the calendar function (figure 4), you can identify patterns at specific points in time. For instance, you can recommend employees to work from home on particularly busy days.
Figure 5 shows the pattern of utilisation for all Mondays over a 2 month period. We clearly see that the space is severely underutilised every Monday.