Walk around the floors of just about any office building and you will typically see a fair number of empty desks, offices and cubicles. Some desks belong to those on vacation or working in another location, there’s the cube that those summer interns used up until two weeks ago, there’s the cube that nobody’s sure what it’s for but it seems to have accumulated an impressive collection of office plants, there’s… well you get the idea.
In high-end markets the annual real estate cost of a simple office cubicle setup is easily $15k or more. Add on the related costs such as higher energy, maintenance and security costs and that wasted space quickly adds up to lots of wasted cash.
Modern office designs with flexible seating arrangements like hot desking or hoteling help to an extent, but these arrangements still frequently suffer from low utilization.
Any management consultant can put a PowerPoint slide together saying there are savings opportunities in reducing real estate costs, but realizing those savings is where real skill is required. Why is it so hard for corporate managers to optimize their real estate expenditure and realize such savings?
In many firms, the root cause of such waste boils down to antiquated budgeting processes and a failure to take full advantage of all the data currently available on presence management.
On the budgeting side, most real estate budgets allocate space on a division or departmental level. If 95% of seats in an office building are allocated to budgets and ‘paid for’ via annual internal chargebacks then from the corporate real estate perspective utilization is 95%. In this case there is a managed vacancy of 5%.
The reality is that actual observable daily utilization is likely closer to 75-80%, and potentially much lower. This so called unmanaged vacancy is typically 15-20% when measured and often much more in most large firms. This is further compounded by cyclic vacancies, such as the additional 10-20% of physical spaces that are unutilized on Fridays.
"The data and tools to provide these powerful real estate insights likely already exist inside most firms today."
One of the reasons for the outdated budgeting practices is that it’s perceived as the best approach given the data currently available. If you ask a typical corporate real-estate manager what their percent space utilization was last year they can likely whip out a nice Excel or PowerPoint document with those figures—problem is, as highlighted above, though those figures are usually wrong.
Ask what the actual utilization of the offices and cubicles on the 4th floor in building 7 was last Wednesday at 2 PM and most will say “we don’t have that sort of data, but we wish we did.” The reality is that this data likely already exists, it’s just difficult to extract and is not currently being used to generate real estate insights. There’s the obvious data, like badge swipes, and the less obvious like network port analyses, environmental sensors within buildings and VPN access records to name a few.
Skilled data science teams can integrate across multiple datasets to generate valuable insights on current utilization trends and predictions of future space needs. The insights are based on measurable facts, which gives this approach far more credibility than traditional analytics approaches such as desk surveys.
The power of this empirical data often results in a complete change of direction in real estate planning strategy. A manager that previously thought they needed to expand from 10 to 11 floors can suddenly see that actually they will have ample space with 8 floors.
With the right data, these insights also extend towards understanding how teams work—which can lead to additional improvements in designing workspaces that facilitate effective collaboration between key teams.
Of course, savings from real estate optimization do not materialize overnight. Leases may need to be renegotiated and one can’t just magically remove floors from a building. However, it is this slow movement that often further compounds poor strategies that are based more on surveys and gut feel than hard data. Without solid analytics, most managers naturally take an overly conservative approach towards future forecasting to ensure allocated space is sufficient—the net impact being that inefficiencies are simply locked in even further into the future.
The data and tools to provide these powerful real estate insights likely already exist inside most firms today. What’s missing isn’t some magic analytics software or black-box algorithm, but rather solid data science skills and experience in integrating multiple unwieldy datasets on people and real estate analytics. Off the shelf software solutions for managing real estate assets are also poorly equipped to tackle the challenge of integrating the vast variety of datasets required for gaining actionable insight.
CKM Advisors has extensive experience in this space and a solid track record of delivering results for our clients. If you’re looking at a lot of unutilized real estate space and would like solid data-driven decision support, please contact Curtis Morikawa at: