Survey Data vs. Behavior Data for Space Management - Which Do You Trust?

In today's data-driven world, gathering insights about physical spaces has become increasingly important. Whether it's an office space, a retail location, or an educational institution, understanding how people use these spaces can help operators and owners make informed decisions about design, operations, and resource allocation. However, the data we use to track this utilization can make a significant difference in the accuracy and usefulness of our insights.

Traditionally, surveys have been a popular way of collecting data about physical spaces. With surveys, people self-report their behavior, preferences, and opinions through questionnaires or interviews. While they can provide valuable information about people's attitudes and perceptions, surveys have limitations when it comes to tracking actual behavior.

One of the most significant limitations of survey data is that it relies on people's self-reports, which may not always be accurate or reliable. People may overstate or understate their behavior for various reasons, such as social desirability bias, memory errors, or misunderstandings of the questions. Say, for example, a survey asks people how often they go to a specific office floor, but people may forget or underestimate the frequency of their visits.

Another limitation of survey data is that it often provides only a snapshot of people's behavior at a particular moment in time. Surveys may be conducted at specific times of the day, week, or year, and may not capture variations in behavior across different contexts or seasons.

Another limitation of survey data is that it often provides only a snapshot of people's behavior at a particular moment in time. Surveys may be conducted at specific times of the day, week, or year, and may not capture variations in behavior across different contexts or seasons.

Behavior Data Reflects Actual Use vs. Self-reported Use

In contrast, behavior data - in this case, tracked by occupancy sensors in a given space - tracks actions in real time and provides a more accurate and comprehensive picture of how people actually use physical spaces.

Behavior data can be collected through various methods, such as sensors, cameras, or mobile apps, that record people's movements, interactions, and activities. By analyzing utilization data, building operators and owners can gain insights into patterns of usage, traffic flow, occupancy rates, and other metrics that are difficult or impossible to capture through surveys.

Architecture and design firm Perkins&Will is leaning toward gathering more modern behavior data versus solely relying on survey data as they evaluate master planning and design for their clients.

"We all know that what people say they do or want in a survey versus what they actually do or want are not always aligned," said Derek Jones, practice leader and principal at architecture firm Perkins&Will. Perkins&Will uses Occuspace's real-time and historical foot traffic data in customer locations to drive design decisions.

One of the key advantages of behavior data is that it provides ground truth data, which is data that reflects what people actually do rather than what they say they do. This data can be invaluable for decision-making, as it can reveal discrepancies between people's self-reports and their actual behavior. For example, space utilization data analysis may show that people tend to spend more time in a particular area of an academic library than they reported in a survey, which could lead to design changes that better accommodate this behavior.

"As we discover more about the benefits of visitor behavior in space design and planning, we are relying on technology-driven measurement of space occupancy," said Jones, speaking about Perkins&Will's recent work on the Purdue University Libraries 2022 Master Plan.

Behavior data is also more actionable than survey data, as it can help identify specific opportunities for improvement or optimization. For example, behavior data may reveal that a particular pathway in a retail store is frequently congested, which could prompt managers to reorganize the layout or add more staff to that area. Behavior data may also show that a particular office space is underutilized, which could prompt managers to adjust the allocation of resources or consider redesigning the space to better meet the needs of employees.

While surveys have been a popular method of collecting data about physical spaces, they have limitations when it comes to tracking actual behavior. Behavior data provides a more accurate and actionable picture of how people use physical spaces and can help reveal discrepancies between self-reports and actual behavior.

As data-driven decision-making becomes increasingly important for building and workplace operations, behavior data is likely to become an invaluable tool for understanding and optimizing physical spaces.

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