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© Tango. All rights reserved. www.tangoanalytics.com The Occupancy Tracking Maturity Model Or, a company may use occupancy data to pinpoint opportunities to close floors or wings of a building on days where occupancy is low, generating energy cost savings and making their operations more sustainable. Occupancy tracking maturity should lead organizations to analyze data at regular intervals— whether that's quarterly or monthly—to search for new opportunities, as well as on demand to investigate emerging challenges and anomalous usage. Mature organizations recognize occupancy data and space utilization metrics as an important indicator of workplace health. They know that it's an essential part of diagnosing issues in the workplace and determining how employees are responding to changes. 7 Intervals of analysis Companies that aren't mature in their understanding and use of occupancy tracking don't analyze this data often—because for their purposes, they don't need to. They're not using it to refine workplace policies or optimize operations. It's just a real estate planning tool. As they consider lease renewals and evaluate whether to close or consolidate offices, occupancy analytics point them to underutilized locations and potential cost savings. More mature organizations analyze occupancy data more frequently because they recognize it as a signal of workplace efficiency which they can affect through changes in policies and processes. For example, a company that wants to optimize their hybrid work schedule may use occupancy analytics to coordinate which groups should be in the office on which days, fine-tuning their policies to keep peak occupancy levels and average occupancy levels from inhibiting employee productivity and satisfaction. With every policy shift that could impact the workplace, organizations with a mature understanding of occupancy tracking will measure the impact, examining how the policy increased, decreased, or redistributed occupancy levels, using new patterns as markers of how people are responding to the change. Data transformation is an aspect of occupancy tracking that most organizations aren't very mature in. Even if they have the data coverage and granularity they need, they lack the capabilities they need to act on the information their technology collects. Data transformation is a key component of operationalizing occupancy data—moving from insight to action—and ultimately realizing value.

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