AI-informed Data Enables Peak Performance in Workplaces
Functional data helps employers optimize workplace design by revealing how employees work best.
In the last few years, we’ve learned a lot about what employees want most from their workplaces. Collaboration spaces? Yep. Quality hybrid-meeting technology? Definitely.
But companies may still be missing an important piece of the employee-data puzzle, says Brian Zuercher, whose company helps employers and those in commercial real estate navigate what he refers to as the “North Star around functional data.”
“All the information they have around employees tends to be around employee engagement, to employee sentiment, to the organization's vision, mission, and values,” Zuercher says. “Companies actually don’t know much about what people do, how they do it … and what would ultimately result in what we would call ‘peak performance work.’”
Zuercher, CEO of artificial intelligence (AI)-based space planning company Align, believes it’s important to learn how to enable an ideal functional work journey for both individuals and teams.
AI-based space planning helps to uncover this functional data, and machine learning can be used to assess occupant data and draw out key insights:
It can reveal why employees are thriving in the work they do (or not).
It can identify which technology is helping or fatiguing people.
It can determine the best way to configure physical space to support all the types of work that need to happen .
At Zuercher’s firm, for example, team members are asked to complete an in-depth assessment of how they engage in seven key work modes. These types of work include everything from time spent developing ideas and strategies, to collaborating with co-workers, to giving presentations.
Individual data is then aggregated and AI outlines key themes based on what a team has reported. It will identify obstacles that stand in the way of productivity, as well as highlight opportunities for improvement.
With this functional data, companies can improve the full “experience equation” of a workplace, which Zuercher says is made up of a “three-legged stool” — workplace policies, available tools and tech, and physical environments.
What does functional data tell us about CRE trends and employee demands?
While the functional data that Align’s AI gathers is specific to each team or company being analyzed, Zuercher says broader trends about employee work habits and demands emerge when client data is aggregated.
For instance, there’s increased interest in real estate consolidation, based on quality rather than quantity.
Before hybrid work, the amount of workspace a company needed was traditionally calculated based on desks and headcount. Now, companies are more focused on investing in the right type of consolidated physical spaces, specifically looking for space that fosters connection, collaboration, and team engagement.
Zuercher compares this shift to your experience when riding an exercise bike.
Riding alone at home you’re still getting a workout, but other things are missing, he says. “You’re not getting in a hot room with other people, sweating, talking to people before class.” He believes that “community camaraderie,” is why many people prefer both in-person fitness and in-person work.
Another key trend is widespread demand for flexibility, says Zuercher.
“A common denominator around what the individual is looking for is autonomy. And it’s usually described as flexibility,” in terms of workplace policy, access to tech and space.
Of course, policy is written by people and can be shifted as needed, Zuercher notes. And tools can be upgraded as technology advances. But what about workplaces?
Offices built with conventional materials such as drywall can't adapt and change without a fair amount of construction, time, and cost. Modular solutions, on the other hand, allow a space to be whatever its occupants need in the moment — while also enabling future changes as required, quickly, and inexpensively.
Modular solutions are ideal for AI-based workplace designs
Adaptable industrialized construction solutions are well-suited to implement workplace designs that are informed by AI-based space planning, and it enables easy reconfiguration when required.
Zuercher shares a case study that showcases how complementary the two solutions can be. In this example, DIRTT’s industrialized construction system helped to customize a historic space in Louisville, Kentucky that was designed based on his team’s AI-space planning insights.
The bright, brick-and-beam workspace features modular electrical cabling with outlets and connections that are easy-to-change or upgrade, as well as retractable walls that can divide or open rooms, among other features.
“After a year, we changed about 15 to 20% of the space,” Zuercher says. DIRTT’s modular interiors allowed for quicker reconfiguration, in two-week increments, each time. “It’s monumentally faster than anything with traditional construction.”
Ultimately, when you can make flexible changes on the fly, organizations can optimize the working experience — and thus the efficiency — of their teams, says Zuercher.
“If you need to make a change and reclassify space… all those conveniences just add up to a better and more incremental and changing experience.”
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