Look before you leap: new trends in space utilization studies

Let’s say you are expected to use occupancy or utilization data for a pre-design phase of a workplace, but that’s not your sweet spot. You might be thinking, “Uh, does that mean sensors? What might we learn from the data? Do I have to be a data analyst to figure it out? How much is this going to cost? It sounds like a management nightmare.”

Point number 1: Don’t start with sensors

Most utilization studies do not use sensors. However, if your workplace has them already installed and if you have access to the data, use that data! Companies like FacilityQuest that already work with space utilization data can probably help you analyze it.

But sending real people into the workplace to gather observations-based data for 1-2 weeks is currently the best practice for utilization studies because observers gather data that goes beyond just occupancy. Information such as “how many people are doing what activities in what types of spaces.” 

For instance, “Temporarily unoccupied” means that there is an appearance of the space being used—someone left their stuff behind—even though no one is actually there. Additionally, data can be gathered on what equipment is being used and what secondary activity is also happening in the space, e.g. “people eating lunch while also having a meeting.” 

Sensors and other automated data can still play a role, however. More on that to come.

Point number 2: learn how space performs as-used vs. as-intended

To re-emphasize Point number 1, you learn “how many people are doing what activities in what types of spaces.” Example: conference rooms might have high occupancy, but by only one person more than half the time, even for rooms with a capacity of 10+. Workstations might be 95% assigned but 30% of them are empty for the entire day more than three days a week. Those learnings can figure into the programming for the next office space design. That data can help persuade decision makers to embrace your big ideas.

Point number 3: No statistical Analysis skills required

Depending on the tools you use, good reporting can make utilization data visual and digestible such that you can ask good questions and draw the right conclusions. And at FacilityQuest you also get help from real people. In a utilization study, the reporting phase includes a Q&A with an architect specializing in workplace strategy who guides you through the results and helps to digest the results. This allows you to dig deeper for more insights. It’s about your curiosity and appetite for seeing a result and asking “why.” The story-telling about key findings and design outcomes is what you bring to the table.

Options for Reducing Cost and Logistics

A full scale utilization study for a large workplace can get pricey when you have a team of temps being paid to walk around collecting data for a week or two. Let’s now entertain a few trending choices that some companies are making to get actionable data that drives their decision making. When appropriate, these options significantly reduce the costs and logistics for a utilization study. We’ll refer to these options collectively as “pulse” utilization studies because they share the attribute of “less is more.”

traditional space utilization studies

For comparison, a traditional space utilization study calls for ‘full coverage data’ in order to get optimal statistical understanding of utilization. Typically, this has been defined as observers documenting the activity in each space eight times per day, five days per week, for 1-2 weeks (i.e. 40 data points per space per week). This data shows the highs and the lows, the good-bad-and-ugly, whenever they occur. Typically these studies are staffed with temps.

Alternative: Measure Peak Utilization ONly

Contrast traditional data gathering with a pulse study where the hours and/or days to measure utilization are cherry-picked to measure only peak utilization. Measuring peak means you want to know the ‘worst case scenario’ of demand of space resources, and it also implies a  willingness to miss out on some aspects of how space is used in order to achieve a specific goal. 

By planning for peak, you recognize that your spaces will be underutilized at other times of the day or other days of the week, but you have confidence that your new design will accommodate the highest expected use. You also have data to show that you are not squandering resources for ‘beyond peak’.

The payoff can be lower cost, flexible logistics, or spreading the investment to multiple surveys that measure the impacts of change over time. We’ll get into how this is done, but first, a few more options to consider.

Alternative: A Pilot Study in a Test Area

Another variation on a pulse study is to survey a smaller selection of spaces and then extrapolate the results from that sampling to the larger workplace. A small pilot project could study a test area, such as a prototype of a new neighborhood layout, so that the patterns of utilization in the new space can be understood before rolling out similar designs  to other groups or offices.

While the extrapolation carries the risk of over-representing a certain result, many re-designs don’t make the investment in space utilization at all, so some data is better than no data. 

And, if a larger study is being considered, starting with a limited study in order to understand the value of the results is a valid way to prove the concept before committing to a larger investment.  A pulse study could simply be a pilot, or a phase 1, “Let’s try it out,” with a possible deeper dive to follow as needed. The pilot study creates the road map to a fuller understanding of the full scope of the workplace.

At the conclusion of the pilot, everyone on the team  understands the process of data gathering and the value from the data. At that point, you may be ready to move to the next area to get another set of “surgical” results, or you may decide to move forward with a full-coverage traditional survey. Or you may decide to repeat the study again in six months to see what changes. And of course you may decide the takeaways from the pilot data are satisfying enough--or justifies what you already know--and you are now confident to move forward with your recommendations for the design phase.

Alternative: Limit the Scope to specific space types

And finally, you could pick a priority such as choosing to study only conference rooms to keep an initial project manageable without the cost and logistics of bringing in temporary staff. If you are only being asked for your recommendations on size and number of collaboration spaces, no need to gather data on assigned workstations. 

Using Internal Staff as Data Gatherers

The choice to measure fewer spaces or only during peak hours means that internal staff could be designated as part-time data gatherers. For a peak study, these internally assigned observers walk around gathering data with a tablet on a designated route, but only at the start of four peak-use hours, let’s say at 10am, 11am, 2pm, and 3pm. They might spend 10-20 minutes per hour to complete their routes. 

One person can observe 50 spaces in 10-15 minutes (and even faster after a short ‘getting used to it’ training period). So one person spending a total of one hour per day (split across four peak hours) could provide valuable insight into 50 or more spaces! Compare that to the cost and logistics of hiring a temp to do the same job full time for a week or more. And an internal person performing the data gathering is familiar with the space, so training is minimal. 

EXAMPLE: A Global Set of Pulse Studies

In Q2 of 2019 a global tech company decided to survey eight of its corporate campuses worldwide to get a measure of peak utilization. They chose the busiest three days of the week and observed during the the peak hours of 10am, 11am, 2pm and 3pm.  

This company has been measuring utilization in different ways for over a decade and had experience in analyzing badge (building access) data that could show which days of the week had the highest number of employees on premises. Interestingly, the peak days of the week were not the same across campuses, so for this company, guessing the peak days would have set a poor foundation for trusting the results. 

Takeaways from the 8-campus pulse surveys:

• It was easier to remotely manage the internally sourced observers.  The chosen observer--typically the facilities manager who already knew their way around--was a familiar face, so there was no need to prepare employees for unknown observers doing unfamiliar work. There was no need to grant temporary access to the space. And the assigned observer could do other ‘normal’ work between passes and thus avoid down time when they became efficient at taking data.

• Utilization rates were on average higher than our typical project, although this was impacted by how the project chose to look at workstations as clusters rather than as individual seats.

• If there was a "bad" day (e.g. the assigned observer got caught in a meeting), less data was gathered. And because only peak hours were being measured, missing a few hours of data had more impact on the project. However, observers were generally flexible enough to take "extra" data the next day or the following week to make up for missing routes. 

EXAMPLE: A Meeting Rooms Study

Utilization projects may answer an initial question, but lead to additional questions about how the workplace is being utilized. In a recent very small study measuring just meeting rooms and collaboration spaces, the office manager set up the survey and then performed all the observations for the week (the workplace strategist didn’t even get involved until the results were in. 

It was unique and refreshing that the same person involved with the goals of the study was also the one gathering the data and included in discussing the results. In this case, the study showed that 78% of the time the meeting spaces were utilized by 1-2 people, even though the rooms were built to accommodate 4-6+ people. This led to client to question how collaboration and individual work was happening in the rest of the work space, and what might motivate this pattern of use.

Key Takeaways

The takeaway from the trend of “pulse” studies might just be another truth of the 80/20 rule: some data is so much better than no data. Dashboards light up with some data as brightly as they do with lots of data. If the results of a small sample are not trusted enough for a high-stakes decision, the exercise can be repeated at a larger scale and with more confidence due to the ‘dress rehearsal.’

What version of ‘starting small’ makes sense in any given situation? As with any business challenge, it depends on the problem are you trying to solve. Here’s a list of a few of them, and let us know what else might benefit from limited utilization studies.

The Problem to Solve	Traditional Utilization Study 8x per day, 1-2 wks	Gather data for peak hours only	Gather Data for limited scope	Pilot project
Must have statistical confidence in data, e.g.  to be used for permanent CRE decisions	X
Decision timeline offers limited window to gather data		X	X	X
Workplace security concerns restrict data gathering to internal staff only		X	X	X
Validation of other utilization data, such as badge or Wi-Fi		X	X
Limited inquiry, such as analyzing conference room use			X	X
Proof of concept for testing logistical feasibility or evaluating results	X		X	X

All of the ‘problems to solve’ listed above are flavors of limitations that relate to time, money, or managing complexity. So the interesting outcome of this innovation is that these challenges are addressable and may put space utilization and occupancy data within the reach of more projects.