Forecasting used to be simple. Headcount projections were set annually. Real estate plans followed. Workplace teams adjusted space based on expected growth or contraction. The inputs were stable, so the outputs were predictable.
That world no longer exists.
Today, both headcount and workplace demand are far more dynamic. Hiring plans shift. Teams grow at different rates. Hybrid policies evolve. And attendance patterns fluctuate in ways that are difficult to predict using traditional methods.
As a result, workplace and real estate leaders are being asked to answer a new kind of question:
Not just what will happen, but what might happen.
And more importantly, what each of those possibilities means for space, cost, and employee experience.
At its core, forecasting is about understanding demand.
Each of these questions has become harder to answer.
Headcount forecasts are often built in partnership with HR, using a mix of hiring plans, budget assumptions, and business projections. In some cases, organizations apply simple growth rates. In others, forecasts are more detailed, varying by team, region, or function.
But regardless of the method, one challenge remains consistent: forecasts are inherently uncertain.
As Jenny Lum, Director of Global Projects & Workplace Technology at Autodesk, explained at the 8th Occupancy Intelligence Summit:
“Prior to us being hybrid, we were very office based. Everything was very predictable. Now, it’s much more complex. Being hybrid first, we want to offer flexibility. We no longer have that 1 to 1 desk ratio that we can predict who’s coming in.”
Even small changes in hiring plans, team structures, or policy decisions can significantly impact how many people show up and when. And because workplace demand is not evenly distributed, those changes often show up as spikes, not smooth averages.
This makes it difficult to translate headcount projections into clear space requirements. Headcount does not directly translate to space demand. What matters is how many people are present at the same time, and what types of spaces they need when they are there.
Two organizations with identical headcount projections may require very different space strategies depending on:
Without accounting for these dynamics, forecasts quickly become misaligned with actual demand.
One of the most important shifts in modern workplace planning is moving away from single-number forecasts.
Instead of asking: What will our headcount be next year?
Leading organizations are asking: What are the most likely scenarios, and how would each impact our space?
For example:
Each of these scenarios has different implications for space capacity, cost, and employee experience.
As Jenny Lum described at the 8th Occupancy Intelligence Summit:
“We still go with our growth forecast. We look at our attendance trends, and we look at utilization data. That really tells us how people are behaving in the space. At this point, we’re looking at 8-day peak averages per month.”
This shift reflects a broader reality. Understanding future demand is no longer about a single input like headcount. It requires combining multiple signals, including attendance patterns, utilization data, and peak demand trends, to build a more complete picture.
Historically, evaluating these scenarios has been difficult. It required manual modeling, complex spreadsheets, and significant time to validate assumptions. As a result, many teams were limited to exploring only a handful of possibilities.
That constraint often led to decisions that were either overly conservative or overly aggressive.
A New Approach to Forecasting: Predictive Planning
There is a better way. One that treats forecasting as a continuous, scenario-driven process rather than a static exercise.
Predictive Planning from VergeSense, powered by the industry's largest spatial dataset of 200M+ square feet of real-world occupancy data, enables organizations to model how changes in headcount, policy, and workplace behavior will impact space demand.
Unlike static ratio-based models or consultant-driven studies that take months, Predictive Planning uses a proprietary large spatial AI model to run millions of simulations, translating workforce inputs into space-level outcomes in hours instead of quarters.
It incorporates:
These inputs are used to simulate how employees will actually use space under different conditions, allowing teams to quickly test a wide range of scenarios and understand their impact:
What was once a slow, manual process becomes a dynamic planning capability that keeps pace with how fast conditions actually change.
Connecting Forecasting to Cost and Investment Decisions
More accurate forecasting does more than improve planning. It directly impacts financial outcomes.
When workplace teams can confidently model future demand, they are better equipped to:
Most importantly, it allows teams to make these decisions proactively rather than reactively.
Instead of responding to space shortages after they occur, organizations can anticipate when demand will exceed capacity and take action in advance. This shift from reactive to predictive planning is what enables more efficient, resilient portfolios.
From Uncertainty to Confidence
Uncertainty will always be part of forecasting.
Headcount will change. Policies will evolve. Workplace behavior will continue to shift.
The goal is not to eliminate uncertainty, but to manage it.
By modeling multiple scenarios, understanding how demand and supply interact, and continuously updating forecasts with new data, organizations can move from static planning to a more adaptive approach.
As Gary Gaughan, Workplace & Data Manager at Indeed, shared at the 7th Occupancy Intelligence Summit:
“Be inquisitive. Really strive to understand the why. Why are you measuring this data? Why is the data telling you this particular story, and why are you implementing a specific program?”
This mindset is what separates reactive planning from strategic decision-making. It ensures that data is not just collected, but interpreted with purpose and applied in a way that drives meaningful outcomes.
7. Define Success in Threes: Right-Sizing, Flexibility, ExperienceThe Bottom Line
Forecasting headcount and space needs is no longer a one-time exercise. It is an ongoing process that requires both data and flexibility.
Organizations that rely on static assumptions will continue to struggle with misalignment between space and demand. Those that embrace scenario-driven, predictive approaches will be better positioned to adapt, optimize costs, and support how work actually happens.
The question facing every CRE and workplace leader today isn't what the future looks like. It's whether your planning approach can keep pace with how fast that future is changing.
Connect with a VergeSense specialist to explore how data-driven workplace strategy can help you plan smarter in 2026 and beyond.
FAQ: Forecasting Headcount and Office Space
How do companies forecast office space needs? Companies forecast office space needs by analyzing headcount projections, attendance patterns, and workplace usage data. More advanced teams use predictive planning tools to model different scenarios and understand future demand rather than relying on static ratios or annual planning cycles.
Why is headcount forecasting not enough for space planning? Headcount alone does not determine space needs. What matters is how many employees are present at the same time, what types of spaces they require, and how attendance is distributed across the week. Two companies with identical headcount can have very different space requirements.
What is predictive planning in workplace strategy? Predictive planning uses data and AI modeling to simulate how employees will use space under different scenarios. It helps organizations forecast demand, test the impact of changes to headcount, policy, or design, and make more informed decisions backed by real behavioral data rather than assumptions.
How can companies plan for uncertainty in hybrid work? By modeling multiple scenarios, continuously updating forecasts with real-time data, and using tools that account for attendance patterns and peak demand trends, companies can adapt their workplace strategy as conditions change rather than relying on a single fixed plan.