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© Tango. All rights reserved. www.tangoanalytics.com The Occupancy Tracking Maturity Model Mature organizations will also leverage predictive analytics to forecast future demand for space and test the impact of various scenarios, such as new office configurations or changes in their hybrid work policy. AI is now playing a greater role in occupancy data analysis as well. Whether analyzing utilization patterns, investigating the cause of changes in demand, or even determining which utilization metrics to explore, AI is bolstering the analytics capabilities of more mature organizations. 6 Factor 2: Analysis Collecting occupancy data can only take you so far. In order to use it and reap the benefits, organizations need to perform regular analysis. An organization's maturity when it comes to occupancy data analysis is based on their performance in three key areas: 1. Data sophistication 2. Data transformation 3. Intervals of analysis Data sophistication On some level, your occupancy data sophistication is limited by your sources. There are only so many ways to analyze badge data. But your occupancy analytics system should enable you to segment and explore your raw data in multiple dimensions and convert it into meaningful metrics, too. Depending on what insights you're trying to uncover, you may want to segment your data by department, team, space type, role, or other space allocation categories. Ideally, with a mature occupancy analytics system, you should be able to combine these dimensions to evaluate, for example, how many workstations a given department may actually need, or how well they've utilized dedicated meeting rooms. Or, perhaps you want to know which days and times a department is most or least active. Organizations with mature occupancy tracking solutions and practices will also use the same underlying data to analyze a range of space utilization metrics, such as average and peak occupancy levels—even average peak levels—to develop a more comprehensive understanding of how typical operations and abnormal conditions affect the workplace. Data transformation Occupancy tracking data is useful even if you only ever analyze it in spreadsheets. But it becomes immensely more valuable when you have the ability to integrate and reformat occupancy data in more meaningful ways. Space management processes like stack planning, scenario planning, and move management (moves, adds, and changes) can all incorporate this data to improve analysis and discover new opportunities. As you visually organize your allocated space into blocks to consider high-level options for your portfolio, individual buildings, and specific floors, occupancy data allows you to block out underutilized space and analyze alternative possibilities. Some occupancy analytics or space management solutions also enable you to visualize occupancy data directly on a floor plan, augmenting your CAD files with information about how well each space is being used. If your data is collected in real time, you can even create live floor plans to identify issues that are arising right now. This is especially valuable when rolling out major policy changes or overseeing special events that may fall outside typical utilization patterns.

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