The challenges posed by flexible workspaces are outpacing the space planning tools used for occupancy management. The manual nature of solutions like clicker studies, employee surveys, and manual door counts is time consuming and doesn’t deliver the insights space planners need to get ahead of occupancy trends. Companies are turning to space planning tools that use artificial intelligence (AI) to root out untapped occupancy patterns with predictive insights to gain an advantage over space planning complexity.
Here’s how AI is augmenting traditional space planning tools:
INSIGHT SAVES TIME AND RESOURCES
Space planning conflicts are becoming more common in the wake of hybrid work that gives employees the flexibility to work from anywhere and use their office when and how they want. According to a Lambent survey, 85% of space planners need help handling their organization’s day-to-day seating and office space problems, and 80% are tasked with resolving disputes over space issues. The inability of space planners to accurately predict space needs causes organizations to waste time and money on inefficient and often reactive changes, which are costly to the business and disruptive for employees.
Manual space planning solutions, such as people-counting and over-the-door counters, take resources and only measure occupancy at a point in time. Adding tools like sensors and video helps collect more real-time occupancy data. Still, adding separate space planning tools creates complexity, and insight isn’t captured across all the data sources.
AI-based space planning tools use machine learning to analyze all the occupancy data points across all space planning inputs. It relies on machine learning to find patterns of use to reveal untapped opportunities to optimize space by reducing, increasing, or reimagining spaces to fit the needs of workers. For example, Lambent Spaces is a SaaS-based tool powered by AI and predictive analytics to provide deep insight into occupancy data. This type of algorithm-based software can help space planners:
- Accurately forecast future occupancy based on historical data
- Make better decisions about space occupancy fluctuations associated with hybrid work
- Allocate workspaces with more accuracy to avoid workplace conflicts
- Reduce the time and manual labor associated with occupancy data analysis
FORECASTING DRIVES DECISIVE ACTION
Wasted space is bad for business. It’s believed that globally, companies can save up to $1.5 trillion if their workspaces are optimized. In North America alone, office space is unused about two-thirds of the time—and private offices are unused 77% of the workday. It’s estimated that European businesses could save $243 billion by reducing wasted space in office buildings. Yet today’s space planners make crucial lease and space occupation decisions with limited insight into how their spaces are being over- or underutilized. Consider that 85% of executives plan to change their real estate strategy over the next 12 months, and you can see how crucial occupancy data is to business outcomes.
AI-driven space planning tools can take a holistic view of your portfolio and deliver intelligent recommendations using predictive analytics. They can quickly analyze data from multiple sources to surface critical insights, letting space planners see utilization rates across buildings, floors, and departments. AI helps space planners access reliable utilization data for their entire portfolio, making more informed space planning decisions.
The analytics derived from AI-driven space planning tools change how companies optimize their office layouts for ROI. They can be used to validate new design strategies for existing space, optimize space design, and measure pilots and test cases for future activity. The insight revealed can also be used to reallocate the operating budget toward high-impact use cases and find new revenue streams by commoditizing high-traffic spaces.
LESS BIAS CREATES BETTER OUTCOMES
Not all data is good data. Sensitive data can put a company at risk of compliance issues if personally identifiable information (PII) is collected and shared. Or biased data can send space planners in the wrong decision-making direction if there’s bias in how data is captured or analyzed.
Take privacy, for example. Maintaining privacy is a core initiative for many companies, and in some cases, it’s a mandate for compliance. Lambent’s survey also reveals that 91% of surveyed space planners say it is essential to maintain privacy for employees or students by not showing PII when tracking occupancy. The challenge of monitoring employee use of spaces can violate the privacy expectations of these tenants. AI-driven space planning tools can anonymize the data to protect occupants’ privacy rights and adhere to PII compliance.
Data bias is equally problematic. Many types of bias can occur with manual data analysis, including
- Selection bias: Choosing a sample that doesn’t represent the wider population.
- Loss aversion bias: Avoiding data outcomes that point to losses rather than gains.
- Framing bias: Presenting data to highlight the positives and downplay negatives.
- Anchoring bias: Letting preexisting data influence decisions about new data.
Space planning tools that rely on manual inputs can result in bias in captured data or in actions derived from it. For example, space planners might reject data that puts their assumptions into question or doesn’t align with their perceived ideas about space planning needs.
AI uses machine learning to remove bias from decision-making and delivers accurate recommendations based on actual data points rather than intuition or guesswork. AI collects anonymous data from Wi-Fi to ensure that space planning decisions are always made with accuracy—which means less money wasted on expensive office spaces that aren’t being used properly.
For example, Lambent Spaces uses AI to analyze historical data or occupancy levels incrementally over time, with reports showing only anonymous data to protect privacy and remove bias. It can reveal patterns at the seat level or across departments or specific zones. Contact firstname.lastname@example.org to learn how Lambent Spaces can help you modernize your space planning operations.