How to Make Portfolio Right-sizing and Neighborhood Planning Decisions with WiFi Data

In the dynamic world of hybrid work, you need a way to understand occupancy trends across your portfolio, and this requires a streamlined way to analyze data from your existing building systems. It takes a variety of data inputs to truly understand how your spaces are being used, extract meaningful insights, and action on optimization opportunities.

For workplace leaders, this once meant spending countless hours sifting through tabs, data sheets, and windows—manually analyzing occupancy data from different sources. But that's no longer the case. The next generation of occupancy intelligence is here. 

The Occupancy Intelligence Platform allows you to unify and analyze all your occupancy data in one place, from WiFi, to space booking systems, to sensors, and other existing building systems. From there, you can leverage personalized, AI-powered recommendations that allow you to make better decisions, faster.

By analyzing your WiFi data with the Occupancy Intelligence Platform, you can understand people count at the building, floor, and neighborhood level. Let’s explore how this analysis supports neighborhood planning and portfolio evaluation, and can lead to better optimization decisions.

Get More from Your Existing WiFi Infrastructure

WiFi data refers to the information collected from a building's WiFi network that can provide insight into how people are moving throughout a space. By analyzing how connected devices such as phones and laptops move throughout a building, you can understand occupancy trends with up to 85% accuracy, and make better data-driven portfolio, floor, and neighborhood-level decisions.

One of the great things about leveraging WiFi data for occupancy intelligence is that you can tap into your existing network infrastructure, requiring no additional installation, which makes implementation quick and easy. For some spaces within your portfolio where you don’t want to install sensors but still would like to understand occupancy trends, WiFi data offers a cost-effective and scalable alternative. With this approach, you can start understanding occupancy patterns immediately to identify gaps in your workplace layout and strategy.

Analyzing WiFi Data with VergeSense

With the introduction of support for WiFi, VergeSense customers can now harness their existing WiFi infrastructure alongside other data sources like sensor data, to gain a deeper understanding of space utilization. With an accurate representation of people count and a holistic view of occupancy trends across buildings and floors, leaders can make more efficient decisions about neighborhood planning and portfolio evaluation.

Deciding between sensors and WiFi data

Depending on your priorities (granularity of information or cost) or use cases, you have a couple of different options. For portfolio evaluation, if data granularity (+95% accuracy) is the driving factor, entryway sensors can provide you with the level of information needed. If you're comfortable with a little less granular information (80-85% accuracy) at a scalable, lower cost, WiFi data might be sufficient. Both sensors and WiFi data can help you understand people count, average person count, and peak person count at the building and floor levels.

For neighborhood planning, granularity of information becomes more of a concern and area sensors are recommended. WiFi data loses accuracy the more granular you try to get given the variance of AP types and distributions the precision of device location is unreliable at scale. VergeSense allows customers to be able to set up large zones (minimum 5,000 SQFT) as Neighborhoods, contingent on surveying their AP layout.

Neighborhood planning and portfolio evaluation decisions with WiFi data

You can now unify and analyze your existing systems data, like WiFi, to understand occupancy trends across floors, buildings, and neighborhoods. Measure person count and peak person count, and view heat maps all within a single platform to better understand the true capacity of your spaces. 

For portfolio right-sizing projects, you can use building and floor-level data to understand occupancy trends, peaks, and averages over time to eliminate excess capacity or identify expansion opportunities. For neighborhood planning efforts, you can use occupancy data at the neighborhood level to continually balance space allocation as teams evolve.

In addition to understanding trends at the building, floor, and neighborhood level, personalized recommendations powered by Workplace Assistant make it easy to implement data-driven adjustments within your portfolio that optimize space utilization and enhance the workplace experience—without hours of manual analysis. You can easily identify ways to support more employees without impacting experience, or eliminate excess space for cost savings.

All the data and insights needed to drive your workplace forward are available in a single platform. Making smart portfolio and neighborhood planning decisions has never been easier.

Make Faster, Better Data-Driven Decisions

With a single platform for occupancy intelligence, leaders can simplify the once complex data analysis process, and spend more time on experimenting and making meaningful changes. Enter the next generation of occupancy intelligence and optimize spaces to reduce costs, ensure sustainability, and improve employee experience.

Streamline how you analyze occupancy data & make better data-driven workplace decisions with VergeSense. To learn more, book a demo.