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What is Occupancy Analytics?

The  modern workplace will continue to undergo major changes next year and beyond. Crowded offices and tightly-packed cubicles are artifacts of the past. Today’s workforce seeks flexibility and mobility. And that’s where occupancy analytics comes in.

By gaining visibility into how your spaces are being occupied and utilized, you can uncover peak activity times in your spaces, spot areas that are not fully utilized, and locate opportunities for improvement. The result is a workspace that adjusts fluidly to individuals’ work preferences. Meetings run smoothly in appropriately sized rooms, teamwork flourishes with the optimal balance of team and private areas, and expenses decrease as you align facilities with actual requirements.

Occupancy Analytics Defined

Occupancy analytics is a data-driven approach to understanding how spaces are used by factoring in occupancy rates, peak usage times, underutilized areas, and trends in user behavior. It leverages technology and data collection methods to track the occupancy and usage patterns of offices, meeting rooms, retail floors, and other public spaces.

Occupancy analytics is becoming an increasingly critical capability as businesses and organizations adapt their spaces to accommodate changes in work models. It helps ensure that resources are used efficiently, like scheduling maintenance and cleaning activities around peak usage times. The increased visibility from occupancy analytics means organizations can tailor spaces to better suit the needs of employees, visitors, and customers. 

Additional benefits from occupancy analytics include reduced costs through aligning energy consumption with actual usage and the ability to plan more effectively for growth by making more informed data-driven decisions about expanding and consolidating.

Tracking Spaces, Not People

According to Richard Scannell, CEO of Lambent, occupancy analytics is about “trying to help people understand how their spaces are being used. There’s a subtle difference between tracking people in spaces and tracking spaces and how they’re used by people, and occupancy analytics is the latter,” Scannell says. “This segment is not in the business of tracking whether a given person is in a building but how the building is being used by all the people who are using it or not using it, as the case may be.”

“There is occupancy, which is the number of people in a space,” Scannell says. “Then there’s utilization, which is reflected by the context of a space. If there are 50 people in a building, that’s important — it’s occupancy. If that building was designed for 60, that’s good utilization. But if it was designed for 500 people, that’s poor utilization. Occupancy is the raw count, and utilization is the count in the context of the intended use of that space. Occupancy analytics examines utilization. It’s an MRI for space.”

Benefits of Modern Occupancy Analytics

Modern occupancy analytics solutions leverage advanced technology and data analytics to provide comprehensive insights into space utilization and occupant behavior. These solutions typically include the following components:

  1. Sensors, IoT devices, or Wi-Fi networks: Occupancy analytics relies on a network of sensors, IoT devices, or existing Wi-Fi networks. Sensors can include occupancy detectors, motion sensors, light sensors, and environmental sensors. Occupancy analytics leveraging Wi-Fi means no new hardware is required.
  1. Data Collection: The occupancy analytics solution continuously collects data on occupancy, movement patterns, environmental conditions, and other relevant metrics. This data is often transmitted in real-time to a central platform for analysis.
  1. Cloud-Based Platforms: Data is processed and stored in cloud-based platforms, enabling scalability, accessibility, and the ability to analyze large datasets.
  1. Data Analysis: Advanced analytics techniques, including machine learning and artificial intelligence, are used to analyze the collected data. This analysis can reveal occupancy patterns, peak usage times, and trends over time.
  1. Occupancy Visualization: Users can access visual representations of occupancy data through dashboards and reports. This helps facility managers and stakeholders understand space utilization and make informed decisions.
  1. Integration: Occupancy analytics solutions often integrate with other building management systems, such as HVAC, lighting, and security systems, to optimize resource allocation based on occupancy. In Higher Education, integrations with systems such as Archibus are common.
  1. Mobile Apps: Some solutions offer mobile apps that allow employees or occupants to check space availability, find colleagues, or book meeting rooms in real-time.
  1. Privacy and Security: Robust privacy and security measures are implemented to protect occupant data, ensuring compliance with data protection regulations.
  1. Adaptive Workplace Features: Some advanced solutions can dynamically adjust office environments, such as lighting and temperature, based on real-time occupancy data to enhance comfort and energy efficiency.
  1. Predictive Analytics: Predictive models may be used to forecast future occupancy trends, helping organizations proactively manage space and resources.
  1. Space Optimization Recommendations: These solutions often provide recommendations for optimizing space usage, which can include desk-sharing strategies, room reconfigurations, or expansion plans.

Modern occupancy analytics solutions offer organizations the ability to create more efficient, cost-effective, and flexible workplaces by leveraging real-time data and insights to align physical spaces with the evolving needs of employees and occupants.

What is Occupancy Analytics for?

Occupancy analytics provides evidence-based information regarding space utilization, employee behaviors, and people movements in an office or other public setting. Once this data is collected and analyzed, it reveals clues to space planning improvements and optimizations including:

  • Space utilization: Identify whether office spaces are being used efficiently or if there are areas that could be repurposed or redesigned for better use.
  • Activity-based metrics: Measure employee office utilization patterns, including which teams need collaborative spaces, how frequently various teams and departments meet, and which days are busiest.
  • Resource allocation: Optimize resource allocation based on occupancy data. For example, adjust HVAC settings, lighting, or cleaning schedules to match occupancy patterns, reducing energy and maintenance costs.
  • Workplace design: Use occupancy data to inform office layout and design decisions. Ensure that workspaces are configured to accommodate peak occupancy times.
  • Flexible work: Explore flexible work arrangements and desk-sharing options based on actual space usage trends, allowing for a more agile workplace.
  • Productivity enhancements: Understand when employees are most productive and tailor work schedules or task assignments accordingly.
  • Cost reduction: Identify opportunities to reduce operational costs by efficiently managing office resources and real estate.
  • Health and safety: During times of health concerns, such as pandemics, occupancy analytics can be crucial for ensuring safe social distancing and compliance with occupancy limits.

Occupancy analytics serves as a foundation for data-driven decision-making in office management, leading to more efficient, cost-effective, and adaptable workplaces that align with the needs and behaviors of employees.

A Brief History of Occupancy Analytics

For most of the 20th century, occupancy analytics consisted of rudimentary, manual methods to study people movements, like clickers and turnstiles. The advent of computers in the mid-20th century enabled more sophisticated data collection and analysis. However, it was in the late 20th and early 21st centuries that advancements in sensor technology, Internet of Things (IoT), and data analytics revolutionized occupancy analytics. With the proliferation of smart buildings and IoT, real-time monitoring emerged as the predominant use case. Today, occupancy analytics is a crucial aspect of workspace management, offering data-driven insights into space usage, energy efficiency, and workplace design, facilitating smarter, more adaptable, and efficient environments, and more favorable employee experiences.

Occupancy analytics can provide valuable insights into space utilization and occupant behavior, but it also comes with several challenges:

  1. Privacy: Collecting occupancy will sometimes raise privacy concerns. Employees and students may feel uncomfortable with people-counting technologies, especially as some rely on cameras. Most customers searching for solutions want a privacy-first solution – one that does not surface any PII.
  2. Data security: Occupancy data can be sensitive, and ensuring its security is crucial. Only rely on a trusted vendor and cloud provider, and ask where and how data is processed.
  3. Maintenance: Maintaining and calibrating sensors and IoT devices over time can be labor-intensive and require ongoing investments.
  4. Data accuracy: Often, organizations are not asking the correct questions. Rather than determining exactly how many people are in a meeting at one precise moment, advanced occupancy analytics surfaces utilization rates across a floor, building or portfolio.
  5. Interpretation: Interpreting the data collected from occupancy analytics can be challenging. Understanding the meaning behind occupancy patterns and converting data into actionable insights requires expertise. Reporting and context are critical components in many solutions.
  6. Scalability: Scaling occupancy analytics solutions for larger facilities or organizations can be complex and may require significant infrastructure upgrades for hardware-based solutions.
  7. Changing work patterns: Workplace behavior and needs evolve over time, which means that occupancy analytics solutions must adapt to these changes to remain relevant.
  8. Regulatory compliance: Depending on the jurisdiction, there may be legal and regulatory requirements governing the collection and use of occupancy data, adding complexity to implementation.
  9. Energy efficiency trade-offs: Optimizing energy use based on occupancy data may lead to trade-offs between energy savings and departmental preferences. Striking the right balance can be a challenge.

It’s important to consider the ethical, legal, and technical aspects of implementing occupancy analytics solutions. Transparency, clear policies, and ongoing communication with employees are essential to ensure acceptance and compliance. Additionally, organizations should prioritize data security and privacy throughout the process.

Best practices when implementing occupancy analytics

Implementing occupancy analytics effectively and responsibly requires balancing the strategic needs of the organization versus the need for ethical and secure data collection that benefits all parties. Here are some best practices for implementing occupancy analytics:

  • Clearly define objectives: Establish clear goals and objectives from the beginning. What specific insights or improvements are you seeking to achieve? Having a well-defined purpose will guide your implementation strategy.
  • Privacy and consent: Be transparent about the data collection process, always obtain informed consent where necessary, and clearly communicate how data will be used and protected.
  • Regulations: Familiarize yourself with relevant data privacy and security regulations, such as GDPR or HIPAA, and ensure that your implementation aligns with these legal requirements.
  • Data retention: Establish a data retention policy that outlines how long occupancy data will be stored and when it will be deleted to align with privacy principles and policy.
  • Anonymize data: Whenever possible, choose a solution that focuses on anonymous occupant data to protect individual privacy. Aggregate data to analyze trends without identifying specific individuals.
  • Continuous Improvement: Use the insights gained from occupancy analytics to drive ongoing improvements in space utilization, energy efficiency, and occupant satisfaction.
  • Regular Audits: Conduct regular audits of your occupancy analytics system to identify and address any vulnerabilities or issues.

By following these best practices, organizations can harness the power of occupancy analytics while addressing privacy concerns, ensuring data security, and using the insights gained to create more efficient and user-friendly spaces.

Trends and future outlook for occupancy analytics

Occupancy analytics is a dynamic field that continues to evolve in response to changing workplace dynamics, technological advancements, and sustainability goals. Here are several trends that will likely shape the sector over the near future.

  • Hybrid work models: With the rise of remote and hybrid work models, occupancy analytics will play a crucial role in optimizing office spaces for flexible work arrangements. Data will be used to determine which days and times employees are most likely to be in the office.
  • IoT and sensor innovation: Advances in IoT and sensor technology will lead to more sophisticated occupancy sensors, offering greater accuracy and versatility. This will enable better data collection and analysis.
  • AI and predictive analytics: Artificial intelligence and machine learning will be increasingly integrated into occupancy analytics systems. Predictive analytics will help organizations anticipate space needs, optimize resource allocation, and plan for future growth.
  • Real-time decision support: Occupancy analytics platforms will provide real-time decision support, allowing facility managers to adjust building systems and resources on the fly in response to changing occupancy patterns.
  • Health and safety: The ongoing importance of health and safety in the workplace, driven by factors like the COVID-19 pandemic, will lead to greater use of occupancy analytics for monitoring social distancing, occupancy limits, and air quality.
  • Sustainability: Organizations will use occupancy analytics to support sustainability goals by optimizing energy usage, reducing carbon footprints, and minimizing the environmental impact of office spaces.
  • Occupant experience: Focus on improving the occupant experience will continue, with analytics helping to create more comfortable and productive work environments tailored to individual preferences.
  • Privacy and ethics: As the use of occupancy data grows, there will be a heightened focus on privacy and ethical considerations. Organizations will need to navigate the delicate balance between data collection and respecting employee and student concerns.
  • Integration with smart buildings: Occupancy analytics will become more integrated with overall smart building management systems, allowing for seamless control of lighting, HVAC, security, and more based on occupancy data.
  • Data sharing and benchmarking: Organizations may share anonymized occupancy data to benchmark their performance against industry standards, enabling them to identify areas for improvement.
  • Remote monitoring: Remote monitoring of occupancy data, especially in multi-site organizations, will become more common, allowing centralized control and analysis.
  • Post-pandemic workplace: The post-pandemic workplace will continue to evolve, with occupancy analytics helping organizations adapt to changing expectations and health protocols.
  • Customization and personalization: Occupancy analytics will enable greater customization of workspaces to suit individual or team preferences, leading to more comfortable and productive work environments.
  • Cost reduction: Organizations will increasingly use occupancy analytics to reduce operational costs, including real estate expenses, by aligning their physical space with actual needs.
  • Urban planning: Beyond workplaces, occupancy analytics will play a role in urban planning, helping cities optimize public spaces and services based on real-time data.

As organizations adapt to evolving workplace dynamics and sustainability goals, occupancy analytics will continue to be a valuable tool for optimizing space usage, enhancing occupant experiences, and achieving greater operational efficiency.

Do you want to learn more about occupancy analytics? Talk with one of our industry experts today and find out if Lambent can help you with space management strategies, hybrid work, and student/employee experience.



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