Organizations struggle to reduce office space waste, not because they’re unaware of it. Instead, they lack tools to spread attendance and reduce space without creating peak-day shortages or disruption.
The data makes this clear.
Leaders widely acknowledge that average office utilization sits at 38–40%. For a mid-sized organization in Munich paying roughly €3 million for a 4,500 m² office, that level of underuse can translate into up to €2.0 million in annual waste.
In response, many leaders attempt to fix utilization by investing heavily in sensors before reducing desks or consolidating floors. However, they often discover that measurement alone doesn’t resolve the issue. It makes it worse, locking space into rigid configurations, slowing adaptation, and reinforcing the very underutilization they set out to eliminate.
Why The Sensor-based Optimization Model Keeps Failing
After switching to a hybrid model and identifying underutilization as a key challenge, the instinctive response was to measure resource usage more precisely. Sensors became the default solution.
But after significant investment in sensor infrastructure, companies have discovered a trend: sensors confirm the utilization issues they already suspect, but don’t assist in solving them.
The limitation is structural. Sensors reveal utilization patterns but cannot address the constraints that make leaders rationalize retaining empty spaces:
- Peak attendance still concentrates on 2-3 days. Sensors show clear Wednesday-Thursday peaks, but can’t help distribute demand across the week. Organizations still need to maintain near-full capacity on peak days, leaving 60-70% of space unused for the rest of the week while incurring full costs.
- Empty spaces persist as sensors create lock-in. Reconfiguring space requires uninstalling sensors, sourcing components, and recalibrating systems. Faced with competing priorities, workplace leaders choose to maintain outdated configurations containing empty spaces. Plus, without dynamic scaling capability, buffer space remains a necessary safeguard against future growth.
- Sensors document behavior but cannot influence it. They show occupancy levels, but can’t help employees find colleagues, coordinate team overlap, or make informed decisions about when the office will deliver collaboration value. Without forward-looking visibility, employees default to safe mid-week days—creating the peaks sensors measure but cannot prevent.
The fundamental limitation is clear: sensors are passive measurement tools. They excel at documenting the problem—showing which spaces remain empty and when—but they cannot resolve underutilization.
As a result, many hybrid workplace leaders accept empty spaces as the unavoidable cost of preserving flexibility and employee experience.
But that trade-off isn’t inevitable.
Experience from successful space optimizations– Mölnlycke Healthcare and Sweco Oslo—shows that organizations can reduce space without harming employee experience or retention. The difference isn’t better measurement; it’s active demand management.
Demand Distribution Management: The Operating Principle Behind Successfully Optimized Spaces
Demand distribution management shifts the focus from measuring what’s empty to actively coordinating when and how teams use space. This approach enables organizations to shape attendance patterns before they create peaks.
Three architectural principles enable this shift:
Principle 1: Demand orchestration
The peak capacity problem is a coordination failure that sensors can measure but cannot solve. Conversely, demand orchestration shapes attendance patterns through coordination, spreading demand across the week instead of concentrating it.
Too often, however, organizations that are not aware of this system default to return-to-office mandates as the primary means of achieving coordination. Instead of solving coordination, they remove flexibility and introduce new risks—employee frustration, disengagement, and higher attrition—without addressing the underlying dynamics of demand.
Demand orchestration is not limited to return-to-office mandates. It is implemented alongside three components, each designed to enable coordination without restricting choice:
- First, there is team-level autonomy. Instead of every employee independently optimizing for themselves, teams coordinate as units. They decide internally when overlap matters most, then communicate those patterns so others can coordinate around them.
- Visibility is the second component. Cross-functional groups can see each other’s attendance patterns and each day’s capacity levels. Thus, they can coordinate internally on schedule overlaps rather than make decisions in isolation.
- Thirdly, a coordinating framework. Leadership sets the overall framework—such as minimum office days expectations—while teams retain control of the final decision.
A key concern with demand orchestration is that spreading attendance dilutes collaboration. The opposite is true. Demand orchestration employs intentional overlap rather than random overlap.
When teams coordinate their presence, they achieve higher-quality collaboration on fewer days rather than accidental hallway encounters spread across the week. The office becomes a tool for purposeful interaction, not a default location.
Principle 2: Rational tradeoffs to elicit beneficial behavioural change
After getting measurement data, organizations typically ask employees to accept restrictions—reduced desks, scheduled days, assigned areas—without offering tangible value. The implicit trade-off is ‘sacrifice flexibility so the company can cut costs based on utilization data.’ Employees see through this immediately, and resistance follows.
Reciprocity addresses this by driving behavior change aligned with sustainable optimization through mutual benefit rather than enforcing compliance. The reciprocal exchange has three structural components:
- Guaranteed advance resource availability: Employees provide advance notice of their attendance via booking systems, in exchange for assurance that the resources they need—desks, rooms, or adjacent spaces—will be available. This removes the risk of commuting to the office only to encounter scarcity.
- Consolidated coordination: A single booking flow eliminates friction caused by using multiple platforms. The easier it is to plan an office day, the more reliably employees provide the visibility that the system depends on.
- Fair-access rules: Employees obey specific booking rules—time limits, release windows, or check-in requirements. In exchange, they’re assured of access to resources once they’re no longer in use.
This shouldn’t be mistaken for incentivization, which typically means rewards or punishments layered onto an existing system, like free lunch for coming into the office on off-peak days. These interventions require continuous external motivation to sustain. Conversely, reciprocity embeds the reward into the architecture itself.
To further strengthen the acceptance of your reciprocal gestures, try the initiative with specific teams, instead of requiring company-wide adoption from day one. Once teams see the benefits other teams are enjoying from the reciprocal initiatives, 100% adoption becomes the logical next step.
Principle 3: Software-first operational model
Sustainable space optimization requires an operating model that can adapt as quickly as employee behavior does. Systems that depend on fixed infrastructure—hardware installations, static layouts, or long reconfiguration cycles—cannot keep pace with that variability.
A software-first model shifts control from physical installations to systems with minimal hardware overlay. Capacity, availability, booking, and sharing are managed digitally, whereas hardware is used only where it provides unique value—security, access control, compliance, and sensing.
This enables the iterative adaptation required by demand orchestration. As teams coordinate, attendance patterns shift, and resource needs change, workplace teams can reconfigure spaces.
Critically, this model provides flexibility. If attendance patterns shift due to policy changes, market conditions, or organizational growth, capacity adjustments don’t require hardware reinstallation or lease renegotiation. Booking rules, space allocations, and resource availability can be reconfigured digitally in days, not months.
You can scale space usage up or down without the capital expenditure or lead time that makes traditional optimization irreversible. This flexibility transforms space optimization from a high-risk capital decision into a manageable operational adjustment.
Space Optimization Can Be Implemented Without Risks
Evidence from successful implementations (such as Mölnlycke Healthcare and Sweco Oslo) indicates that organizations can optimize space and reduce costs without compromising employee experience or retention. The key is implementing principles that do three things:
- Actively manage and spread out when different departments come in, rather than letting everyone default to the same 2-3 days.
- Incentivize employees to take actions that facilitate sustainable optimization
- Make spaces flexible, able to adapt to new trends in minutes
If you’d like to see how organizations put these principles into practice, you can explore how Awaio supports workplace teams in managing space dynamically. Or, if you prefer a deeper look, book a demo to see how a unified, software-first workplace system helps reduce space waste while preserving—rather than compromising—employee experience.
