A 10 Minute Read Could Save you 9 Million Dollars Next Year

From Occupancy Data to $9.7M in Identified Value: What the First Year of Workplace Intelligence Can Look Like

For most enterprise Corporate Real Estate teams, the business case for workplace utilization technology sounds straightforward.

• Understand how space is being used.
• Make better decisions.
• Reduce costs.

The harder question comes from Finance and the executive team: What is that actually worth?

That is the question one of our large enterprise clients set out to answer during its first year working with InnerSpace. The organization had a substantial corporate office portfolio, changing workplace requirements, active return-to-office planning, and the same challenge facing many CRE leaders today: it was paying for a lot of space, but it didn't have a continuous, sufficiently detailed picture of how that space was actually being used.

The initial deployment covered approximately 2 million square feet across six buildings, 69 floors and roughly 3,900 tracked zones.

What followed wasn't simply an occupancy study. The organization began using workplace intelligence to influence real decisions:

→Where to recover capacity

→What types of spaces to build

→Where not to renovate

→How to approach restacks

→How to accelerate planning.

When those decisions were then translated into financial terms using conservative industry benchmarks, the analysis identified $9.7 million in annual value against a $900,000 annual program cost, representing 10.8x value-to-cost coverage. Of that total, $8.6 million was associated with actions already taken and another $1.1 million with opportunities identified but not yet captured.

That distinction matters. These figures represent estimated financial value and avoided costs based on industry benchmarks and actual decisions made. They do not mean the company has already realized $9.7 million in direct cash savings. The underlying ROI model intentionally used assumptions at or below published benchmarks.

For CRE leaders considering a utilization platform, the more interesting story isn't the headline number. It's how the organization got there.

The Starting Point: Stop Asking "How Full Is the Office?"

Enterprise workplace programs can easily become trapped in an occupancy conversation.

• How many people came on Tuesday?
• What's our average occupancy?
• Which day is the busiest?

Those questions are useful, but they don't necessarily tell a CRE leader what to do. Our client needed to move further.

The objective for our client became understanding the relationship between the space being provided and the space people were actually using: which room types were oversupplied, where demand was concentrated, how long people stayed, which teams worked together, and where seemingly empty space was actually serving an important purpose.

That required establishing a continuous data foundation.

Across the deployment, InnerSpace measured approximately 3,861 zones on 69 floors. The measured foundation used for the ROI analysis covered 1.7 million square feet across six buildings, with observations and analysis from January through June 2026.

That scale matters because it has changed the way our client now approaches workplace planning. Instead of commissioning a study every time someone asks a new question, the organization starts with data that already exists.

And that became one of the first sources of ROI.

Phase One: Build the Baseline Before Making the Big Decisions

One of the most important lessons from the deployment is also one of the simplest: collect the data before you need the answer. Traditional utilization studies can work well for a defined project. But they are point-in-time exercises.

Our ROI analysis estimated that recreating a comparable portfolio study externally could cost approximately $650,000 per cycle, while completing similar work internally could represent around $200,000 in analyst time and 1,900-2,600 employee hours. The estimated timelines were 8-14 weeks externally and 10-18 weeks internally.

With continuous workplace intelligence already operating, a new question doesn't necessarily require a new study. The data is already there.

This gives our client real data it can use to guide planning at similar locations. Questions that previously could have required months of validated data, can instead begin with existing evidence. The ROI model conservatively valued avoided studies and analyst effort at approximately $500,000 annually.

Phase Two: Find the Capacity You're Already Paying For

Next came the much larger financial opportunity: the existing portfolio. The utilization data exposed space that wasn't being used as expected. That gave the client team evidence to support room conversion and reallocation and, critically, to consider using existing capacity before adding more square footage.

This is where occupancy becomes an OPEX conversation.

The ROI model assumed an all-in Class A carrying cost of approximately $30 per square foot per year. Recovering, consolidating or repurposing just 10% of the approximately 1.7 million-square-foot portfolio produced an estimated $5.1 million in annual value. The analysis deliberately used a 10% recovery assumption, despite citing a significantly higher published benchmark for organizations using occupancy tracking.

The goal wasn't simply to find empty space. It was to turn unused capacity into a financial lever.

For an owned portfolio, recovered capacity might create room for future growth without another acquisition. In a leased environment, it could inform a future give-back, consolidation or renewal. Elsewhere, the answer might simply be repurposing existing square footage so the organization doesn't build more.

Different actions. Same principle. → Before you buy, lease or build more, understand what you already have.

Phase Three: Stop Building the Wrong Space

Finding excess capacity was only part of the story. The data also exposed a mismatch between what had been built and what employees were actually demanding.

In one analyzed floor;

• Focus rooms represented 21.2% of rooms but only 13% of observed demand
• Open mobile zones represented 10% of rooms but 17.6% of demand and were operating at 79% utilization
• Mobile offices, meanwhile, were almost perfectly aligned: approximately 30% of supply versus 29.9% of demand.

That is much more useful than knowing a floor is "40% utilized". It tells the workplace strategist what to change.

Using a conservative fit-out assumption of approximately $225 per square foot and an illustrative 100,000 square feet of annual restack or refresh activity, the analysis estimated that correcting an approximately eight-point gap between space provision and measured demand could prevent roughly $1.8 million of capital from being directed toward the wrong space types.

• For Finance, that's capital efficiency.
• For CRE, it's better programming.
• For Workplace Experience, it's an environment better aligned to employee needs.
• And for the Executive Team, it's evidence that workplace investment is being directed toward demonstrated demand rather than assumptions.

Sometimes the Best ROI Comes From the Decision You Don't Make

Our data insights also challenged assumptions. Some neighborhoods believed to be underutilized showed unexpected activity once they were examined continuously. Instead of immediately converting those spaces, the organization investigated further. That avoided a familiar CRE problem: acting on an incomplete picture.

Consider a 5,000-square-foot neighborhood. At the model's $225-per-square-foot fit-out assumption, converting it represents more than $1 million in capital before considering disruption or the possibility of having to reverse the decision.

The ROI analysis therefore assigned $500,000 per year in risk avoidance, based on preventing approximately one wrong-way conversion every two years across an active 69-floor portfolio.

It's a useful reminder for anyone building a workplace technology business case.

ROI isn't exclusively about finding savings. Reducing the probability of an expensive mistake has value too.

Phase Four: Move from Floor Planning to How People Actually Work

As the program matured, the conversation expanded again.

• Presence answered where people were
• Dwell patterns began revealing where people stayed
• Collaboration and adjacency patterns began showing which teams were actually working together

Those insights changed workplace planning for our client. Rather than automatically undertaking a full-floor restack, collaboration patterns could support targeted seat swaps and more precise adjacency decisions. The ROI model estimated approximately $300,000 annually from replacing one roughly 350-person full-floor restack with targeted moves for the people whose adjacency actually mattered.

Dwell data provided another lens.

The analysis found that certain floors and neighborhoods generated two to five times the vibrancy of the quietest floors despite identical layouts. That insight fed conversations about employee experience and future design standards. The financial model conservatively associated $400,000 of annual retention value with this experience dimension, based on retaining only five additional employees annually within a roughly 20,000-person workforce.

This may be a softer ROI category than a lease avoidance or fit-out calculation, but it demonstrates an important evolution. Although workplace data started as a CRE tool, It is quickly becoming an enterprise decision-making essential asset.

The Adjustment Along the Way: From Occupancy Analytics to Workplace Intelligence

One of the most important lessons for enterprise teams is that workplace data needs will evolve over time. As our client began using the insights, their needs became more sophisticated, expanding to include campus-level reporting, forecasting and recommendations, peak-demand analysis, clearer team structures, more context around metrics, improved floor plans, and tools to support large-scale portfolio planning.

Don't expect your workplace intelligence strategy to be fully formed on day one. Start with the decisions that matter. Learn how stakeholders use the data. Identify where the platform needs to go deeper. Then evolve. The goal isn't to implement a dashboard, it's to build a new decision-making capability.

The Next Frontier: Connecting CRE Data to Facilities OPEX

By the end of the analysis, another opportunity had emerged. The same presence data used to make real estate decisions could potentially inform how buildings are operated. Our analysis identified approximately $1.1 million in additional annual opportunity that had not yet been captured, spanning cleaning, HVAC and washroom servicing.

• For cleaning, the analysis modeled a 20% reduction from shifting toward occupancy-triggered service, producing an estimated $600,000 annual opportunity across the portfolio.
• For HVAC, the opportunity came from the gap between fixed building schedules and actual presence. Using published energy benchmarks and a 25% reduction assumption for occupancy-based HVAC scheduling, the analysis estimated approximately $360,000 annually in potential avoided energy cost.
• Presence-matched washroom servicing represented another estimated $150,000 annually.

Importantly, these remained identified opportunities rather than decisions already implemented. But they illustrate why the value of utilization intelligence can expand over time. The first question may be, "Do we have too much space?" The next becomes, "Are we building the right space?" Eventually, Finance and Facilities can ask, "Why are we operating every square foot as though it's equally busy?"

Putting the First-Year ROI in Perspective

Our analysis at the end of the first year attributed;

→$5.1 million to footprint right-sizing

→$1.8 million to restack and fit-out precision

→$500,000 to avoiding incorrect conversions

→$500,000 to study and decision velocity

→$400,000 to retention and experience

→$300,000 to adjacency precision

That produced approximately $8.6 million in benchmarked value associated with decisions already made, plus approximately $1.1 million in additional identified opportunities.

But the 10.8x value-to-cost measure may be the more useful lens for an enterprise buyer because this is an ongoing technology program producing recurring decision value, not simply a one-time investment.

What Enterprise CRE Leaders Should Take From This

The biggest lesson from year one isn't that every enterprise should expect exactly $9.7 million in value. They shouldn't.

Portfolio economics, leases, labor costs, utilization patterns, fit-out costs and operating expenses differ substantially between organizations. The analysis itself was designed so benchmark inputs could ultimately be replaced with the customer's actual costs.

The lesson is how to build the business case. Don't begin by asking whether a utilization platform can produce a better occupancy percentage. Begin with the decisions your organization makes every year.

• What does one unnecessary floor cost?
• What does getting a 100,000-square-foot fit-out wrong cost?
• What does a full restack cost compared with targeted moves?
• How much does another utilization study cost?
• How much are you spending to clean, heat and cool spaces people aren't using?
• And what is the financial value of answering those questions in days rather than months?

That's when workplace utilization stops being another CRE metric and becomes financial intelligence.

Year Two: From Measuring Space to Continuously Optimizing It

The first year established the foundation.

The next phase is about making that intelligence more continuous, more predictive and more deeply connected to enterprise decisions. The roadmap identified campus-level analysis, peak-demand intelligence, forecasting, recommendations and large-scale planning workflows as logical next steps. That progression matters.

For CRE, that means moving from reporting utilization to proactively identifying consolidation opportunities, capacity pressure, room-mix changes and future portfolio requirements.

For Finance, it means connecting workplace behavior to OPEX and capital allocation.

For Facilities, it means operating buildings based on actual demand.

For Workplace Experience, it means designing around observed behavior.

And for Executives, it means making workplace decisions with a much clearer understanding of the financial consequences.

That is ultimately the business case for workplace intelligence.

Not another dashboard.

Not another study.

A continuously growing body of evidence that helps an enterprise spend less where it can, invest more intelligently where it should, and make expensive workplace decisions with significantly greater confidence.