By Melissa Marsh - 12th December, 2021
At the recent University Facilities for the Sciences and Advanced Technologies conference presented by Tradeline, PLASTARC founder Melissa Marsh joined facility planners, architects, engineers, and lab managers to explore new and proven ways of creating better learning and laboratory facilities. Often ones that blur the lines between physical, digital, and experiential learning, and turn out high-level technology professionals, poised for success in research, data-driven fields, and entrepreneurial pursuits.
Marsh and Lois Mate, an Associate Partner at leading architecture firm Ennead, discussed how they’ve worked together, employing new methods to map the ways people use spaces in a building. This type of data analysis both tracks and predicts such factors as how people find their own workspaces during the day, offering a new approach for behavior-informed space planning.
Their proposition: if we’re designing buildings for research on artificial intelligence and next generation technology, we should be using similar methods to inform those designs.
Traditionally, real estate professionals have operated from the premise that there is a firm distinction between the “hard” metrics of a building (the price of the building, how much it costs to operate, etc.) and “soft” metric (how buildings perform for people, how many social interactions they facilitate, etc). But actually, the locations of social interactions are predictable, based on space-layout and other details, such as where tea and coffee stations are.
In these models, occupancy data indicates whether something needs to be changed or left as is. For example, if occupancy rates are at less than 20-percent, a space can probably be adapted to be more useful.
PLASTARC offered case studies including several Bay Area clients in technology and consumer products. According to usage data collected prior to COVID-19, occupancy rates varied between 40-60%. Once workplace designs enabled choose-your-own workspace, the occupancy might approach 100%, with meeting rooms being used more than desks, and lounge spaces also accommodating full day working.
To survive the transition to hybrid, offices must be more flexible than in the past. One option is activity-based workspaces, or work areas that aren’t assigned one-on-one to individuals the way traditional desks are. This means allocating more space to conference rooms or balconies, to encourage collaboration and offer occupants more choice as to where they work. The ideal office has both social sections and secluded areas, to accomodate collaborative tasks in addition to tasks that require extreme focus.
One audience member asked how this sort of change can actually be put into effect. It’s a concept called “hackability,” Marsh said. “Even a lightweight chair with a handle can be seen in this light. The handle invites you to move it around much more readily than one without a handle. Every single design decision you make allows the space to say change me or leave me alone.”
Another example of user led changeability is an app called Comfy, which uses a real-time data feed to help building occupants find their ideal workspace. If somebody's too cold where they are, they can be directed to warmer areas in the building. This creates a dynamic where users are not only benefiting from the data, but contributing to further research just by using the app in their day-to-day lives. With return to office post COVID-19, a wide range of technologies deployed for desk cleaning or contact tracing could be repurposed to enable such improved user experiences of space.
“It’s no longer just a person walking into a building,” Marsh said, “it’s a tech-enabled, tech-savvy person walking into a building, and making it work for them.”
Comfort levels with data collection and overall costs must be mitigated. A basic principle is that in return for user data, a data collector should provide an equivalent benefit to their users. For instance, when using a car ride app, you have to offer your location (by way of your phone) to get picked up by a driver. You are providing the app with your data in exchange for the service of a smooth pickup.
Mate referenced the work that their team has been doing over the years and the potential for real change ahead in academic spaces. Where once federal research dollars may have incentivised traditional space allocations, new users are demanding new amenities and research facilities. This also points to the benefits of our team’s knowledge-sharing, with PLASTARC’s and Ennead bringing the best from academia and corporate design strategies to bear on this work.
It’s time to challenge our assumptions of how, when, and where we work. "When we think about the future of work, or a place, or learning environments… none of us know the answer,” Marsh said. But the answers will be found in responsibly-collected and utilized data. For PLASTARC, data analysis is a key part of fulfilling its mission to make work better, one workplace at a time.