Chapter 5

Data Management is Risk Management

2022-2023 CBRE Global Workplace & Occupancy Insights

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Occupancy data plays a key role in business continuity

Real estate decision-makers relied heavily on occupancy data during the pandemic, from early measures to bring essential workers back into the office, to return-to-office planning, to reshaping work experiences to support hybrid working.

Through the journey, occupancy management helped drive business continuity and minimize operational risk, partnering with the C-suite, human resources, business units, information technology teams and other stakeholders.

Many stakeholders now view space occupancy and utilization data as an essential tool for business continuity and safety planning to mitigate operational risks caused by geopolitical conflicts, extreme weather and public health emergencies. The same data is critical to designing hybrid working and employee experience programs based on employee preferences and work styles. As a result, there’s an increased focus on workplace data quality and technology investments as occupancy data is used to develop business strategies beyond the real estate portfolio.

Image of office workers

  • 44%

    of Occupancy Management team leads are involved in the real estate decision-making process

Being prepared means maintaining your data

Teams are now considering the post-pandemic future of work armed with lessons learned over the last two years. Many companies who struggled with HR and space data for pandemic response and re-entry planning are considering data management and technology solutions to minimize future operational and safety risks.

Figure 22: Phases of pandemic response

Source: CBRE 2022 Occupancy Benchmarking Program.

Data maturity key to success

The rapid speed of the COVID-19 outbreak highlighted the importance of data maturity in business continuity planning. Companies with low levels of data maturity struggled with safely returning essential workers and return-to-office planning. Without up-to-date floor plans and space assignments, it was difficult to know who could safely be brought back while maintaining safe social distancing. By contrast, data-ready teams emerged from the pandemic as valued partners within their organizations because their trusted data enabled quick decision making.

Overall, 65% of respondents made improving data accuracy a goal for 2022. For some organizations, improving data accuracy will focus on implementing or strengthening a data governance program while others may invest in integrating space data management systems.

Figure 23: Stages of space and occupancy data maturity

Source: CBRE 2022 Occupancy Benchmarking Program.

65% of respondents made improving data accuracy a goal for 2022.

Four steps toward quality data

  1. Establish a data governance program

    Start by creating an end-to-end framework for gathering, storing and delivering data. While this will look different for every organization, best practices include creating data standards, identifying critical business data and generating data quality rules. Implementing a data governance program should include a change management plan to train, build support and drive adoption across stakeholder groups.

  2. Document the data in your process

    Leverage a workflow management tool to document how critical data is gathered, stored or delivered during a process. This not only clarifies how the data is used and by whom, it creates transparency so data can be gathered or updated if needed to respond to emergency situations.

  3. Integrate data streams

    Integrating systems automates data transfers to speed process execution and eliminate the risks of manual data entry. As the number of systems sharing data increases, an organization may establish a centralized data warehouse, making it easier for separate systems to contribute and feed from a single source.

  4. Rinse, repeat and fine-tune your program continuously

    A strong data management program takes time and needs continuous improving and ongoing communication and realignment with key stakeholders as enterprise goals evolve.

  • 91%

    of respondents are conducting recurring data accuracy audits as part of their data management routines, 78% of which are automated

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