How Qualitative Data Transforms Commercial Real Estate Decision-Making

At first blush, initial data and interviews with employees from Organization A revealed low space utilization rates within the current facility due to new hybrid and remote work policies. The team proceeded to collect additional input related to the company’s future operational and real estate strategies.

Upon studying demographic data, the workplace strategy team discovered that 73% of staff were Gen-Xers or older, with most employees falling into the Gen-X cohort. This may seem inconsequential for operational and real estate priorities, but two qualitative factors arose. First, leadership had shared that older, more experienced staff are the organization’s lifeblood, playing a critical role in mentoring, training and transferring industry knowledge to newer talent. As such, the organization’s continued success relies heavily upon this cohort. The second factor to consider is that this demographic group was experiencing common challenges associated with the “sandwich” generation: Those caring for aging parents and their own children while also juggling work-related responsibilities.  

While relocating to a new urban space in a reduced footprint was initially appealing, leadership recognized it could further disrupt Gen-X employees and cause unwanted staff attrition. Considering these factors, they prioritized retaining current talent over relocation. SmithGroup then planned a reinvestment and modernization strategy to upgrade building systems, optimize office space and enhance amenities to better support work-life balance for all employees.    

Circumstances for Organization B were different. Here, perceived space shortages prompted the company’s facilities team to develop a master space strategy for campus growth over the next decade. As a data-driven organization comprised of economists and analysts, it was essential that the business case for this new strategy be rooted in hard data. SmithGroup’s workplace strategy team analyzed eight different types of data (see graphic above). Data sets were analyzed in terms of finite numbers and were effective in providing strategists with historical context regarding how space was distributed, occupied and used across the campus over time. On-site observation also helped strategists gain a first-hand understanding of employee interactions and space utilization.

At the beginning of the study, hard data and existing standards suggested that the company needed 45 more private offices and nearly 100 additional workstations. Raw data also implied that many conference rooms were underutilized and that no new meeting space was needed. On the surface, these numbers suggested that the organization needed to substantially increase its real estate holdings or consider an open-office model to drive density. However, qualitative data obtained through workshops and surveys provided the team with a richer understanding of space inefficiencies, work modes and workstyles unique to the organization, as well as cultural norms impacting day-to-day activities.

During user engagement sessions, staff expressed reluctance to move between floors for meetings. If no conference room was available on their floor, most staff opted to take calls from their offices rather than travel to another floor where large conference rooms sat empty. Private offices were also crucial to staff, representing status in the hierarchy, fostering belonging and pride, and serving as a home-away-from-home for many international staff. Strategists discovered that staff needed quiet, enclosed spaces for focused work, their primary work mode, making open office design impractical. To optimize staff productivity, prioritizing individual space was a must.

Here, a combination of quantitative and qualitative factors led to a strategy that accommodates 10-year growth without altering the real estate footprint comprised of individual, enclosed workspaces—rebranded as “dens” to help begin the process of disassociating space with hierarchy—paired with departmental “neighborhoods” that enhance culture and a sense of belonging. This customized space strategy will support Organization B’s operations and growth for the next 10 years.

A fast-growing and tech-savvy company, Organization C, used traditional calculations, ratios and formulaic standards to allocate space based upon staff headcount. Given the company’s tremendous growth projections, leadership set out to proactively assess current space utilization and standards to develop a future-focused campus master plan that would align real estate needs with predicted growth trajectories.

While the application and degree of work modalities, including hybrid work, varied drastically across demographics and departments, badge data consistently showed high levels of workplace occupancy. Relying solely on badge data to drive a new real estate master plan would have indicated high future space demand, suggesting the organization would run out of contiguous space within its current leased building within five years.

Looking beyond the hard data, the team conducted interviews with four primary user groups to better align space strategy needs. This exercise revealed that each group had unique and distinct workstyles and that one-size-fits-all standards would not adequately support staff or organizational goals.

For example, one group was highly transient, suggesting that its “home base” could be a lighter, shared footprint similar to that of a co-working space. This group's space usage patterns also skewed occupancy data due to the fact that individual badge counts were registered multiple times as a result of the "in and out" nature of employees' workstyles. At the same time, another group needed teaming spaces to support its project-based workflow when teammates were in the office. Current standard ratios would not effectively translate such a broad range of differing factors. This revelation required that a new set of variables be applied in order to build an effective and robust space utilization strategy. Ultimately, new calculations revealed a viable path whereby three of the groups could remain in their current building and maintain modest growth trajectories by adopting a mobility strategy, while a fourth group with substantial forecasted growth required a second campus location.

Using only hard numbers and fixed space standards would have resulted in an oversized campus strategy with underutilized spaces. Instead, understanding varying work modes helped better align the space approach with working groups and provide a roadmap for an optimized real estate plan.

CONCLUSION

Creating a real estate strategy that balances quantitative and qualitative data can be daunting. Often, framing the data strategy can be simplified by starting with the end in mind and asking: What are we aiming to achieve?

The data framework illustration above does not cover every possible data point that can be used to develop a successful strategy. Key quantitative inputs, such as people and space data, should be balanced with those that are more qualitative in nature, like culture, talent perspectives, workstyles and workflows. Each organization, its goals, and the problems it needs to solve are unique. Ultimately, it is the combination of hard and squishy qualitative data that will allow organizations to create an insightful and robust strategy for the workplace and real estate.