An adaptive workplace is not simply a floor that can be rearranged. It is a capability: leaders define an operating goal, use evidence to understand how people work, and choose infrastructure and policies that make the next change faster, less disruptive and less wasteful. Ryan Mullenix’s May 15, 2026 article in Building Design + Construction frames adaptability as the combination of analytics, strategy and building systems rather than permanent flexibility for its own sake.
What an adaptive workplace is—and what it is not
Work patterns change when teams reorganize, leaders alter attendance expectations, technology changes how tasks are completed, or employees discover better ways to collaborate. A workplace that adapts treats those shifts as an operating requirement. It can continue supporting the organization while space, services and settings evolve.
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That definition is narrower and more useful than calling any movable furniture or open plan “flexible.” An endlessly changeable floor can still be expensive to operate, difficult to measure and poorly matched to the organization’s culture. Adaptability starts with priorities: Which work needs proximity? When is quiet focus essential? How much choice should teams have? Which changes are likely enough to justify infrastructure investment?
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| Form of adaptability | What it means in practice | Evidence of success |
|---|---|---|
| Change without disruption | Keep the workplace operating while updates, moves or technology changes occur. | Teams remain productive; downtime, temporary moves and service interruptions are limited. |
| Change through learning | Use pilots to test layouts, furniture, technology and collaboration models before scaling. | Feedback and measured behavior lead to a better second iteration. |
| Change with speed | Use infrastructure that permits rapid reconfiguration rather than construction-heavy replacement. | A restack or team move can happen quickly and predictably. |
| Change without waste | Anticipate plausible future scenarios so that later demolition, disposal and rework are reduced. | More components remain reusable; future options cost less to preserve. |
| Change through agency | Give teams control over settings through movable elements and adjustable environmental controls. | People can shape spaces for different tasks without waiting for a building project. |
These forms are related but not interchangeable. A building may offer team-controlled furniture yet lack the electrical capacity for a fast restack. Another may have sophisticated data but no process for acting on what the data shows.
Why workplace analytics matters
Attendance counts alone rarely explain why a space succeeds or fails. Mullenix says LinkedIn developed an internal workplace analytics capability that combined attendance, behavioral insights, spatial utilization and collaboration indicators. In his account, the combined view revealed patterns that assumptions could miss: attendance changed with team proximity and leadership presence, commute friction influenced participation, and market-specific conditions—including dew point—shifted behavior.
Those are claims from an authored industry perspective, not a universal benchmark. Their value is methodological: a decision about space should be tested against several signals rather than a single utilization percentage.
Choose measures that answer a decision
Start with the decision the organization may need to make. If the question is whether a team needs more project space, measure how often members collaborate, how long spaces turn over between uses and whether demand is concentrated at particular times. If the question is whether a location remains attractive, examine attendance patterns alongside commute friction, team distribution and service demand.
- Utilization: Which settings are occupied, when and by whom?
- Collaboration frequency: How often do teams work together in person, and what kinds of settings do those interactions require?
- Space turnover: How quickly does a room or workstation become available for the next use?
- Service demand: Which building services, support areas or amenities experience peaks that affect the workday?
- Behavioral context: Do leadership presence, team proximity, travel time or local conditions help explain the pattern?
Define the period, location and population for each measure. A weekly average across an entire portfolio can hide a team-level constraint, while a short event period can exaggerate one. Establish who can access the data, how it will be interpreted and what action it can trigger; collecting information without a decision path creates activity rather than adaptability.
A three-step planning framework
Mullenix’s framework is deliberately simple: define the goal, establish what can be measured, then adapt based on evidence. The sequence prevents a workplace project from becoming a collection of attractive features without an operating purpose.
1. Define the goal and intended outcome
State the business or organizational outcome in observable terms. Examples include supporting a reorganization without relocating a department, increasing useful collaboration, keeping a site operational during a phased upgrade, or preserving options for a likely change in headcount. Specify the time horizon and the constraints—budget, schedule, leases, technical capacity and service continuity.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteAlso define what “better” means for employees. A faster restack is not automatically a better workplace if teams lose focus areas or control over settings. The goal should connect organizational performance with the experience required to achieve it.
2. Establish what can be measured
Build a baseline before changing the environment. Map attendance, space use, collaboration patterns, turnover and service demand to the teams and work modes involved. Pair quantitative signals with structured feedback from employees, facilities staff and managers. Their observations can explain why a space is underused or why a nominally available room is avoided.
Document data quality and limits. Sensors, booking records and surveys describe different aspects of work and may disagree. Treat a measure as an indicator, not a complete account of productivity or employee commitment.
3. Adapt based on evidence
Use the baseline to run a bounded change: a pilot neighborhood, a revised booking rule, a different furniture kit or a technology adjustment. Set a review date and compare the result with the original goal. Preserve options for the next iteration instead of locking every decision into permanent construction.
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Successful change, in this framework, is measurable, minimally disruptive, less costly and effort-intensive over time, and simpler to decide on later. That is a cumulative standard: each intervention should make the next one easier to plan and execute.
Infrastructure that makes change faster
Adaptability depends on what sits behind the visible workplace. Power, data, air distribution, lighting controls and partitions determine whether a team move is a short operational exercise or a major renovation.
Raised floors and underfloor systems
Raised floors can provide accessible routes for power and data. Underfloor air and power can support restacking without opening ceilings or rebuilding large portions of a slab. The benefit is not that every project needs these systems; it is that a building can be configured around future moves when the expected rate of change justifies the investment.
Wireless lighting and demountable partitions
Wireless lighting controls can reduce the wiring changes associated with a new layout. Demountable partitions can be taken apart and reused when teams or room proportions change. Both systems require coordinated standards, storage and a process for documenting components; otherwise, supposedly reusable elements become surplus materials.
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Infrastructure walls
Infrastructure walls consolidate power, data and mechanical services in a repeatable element. They can establish a service spine while adjacent areas change. This approach is most useful when the organization expects recurring team reconfiguration and can maintain a consistent kit of parts.
What the case examples illustrate
The examples below are reported by Ryan Mullenix in his 2026 article. They illustrate possible approaches, not independently verified performance benchmarks for every workplace.
LinkedIn: combining context with utilization
Mullenix says LinkedIn built an internal workplace analytics capability that combined attendance, behavioral insights, spatial utilization and collaboration indicators. His account links attendance variation to team proximity and leadership presence, identifies commute friction as a participation factor, and notes that local conditions such as dew point shifted behavior.
The lesson is to resist a single cause for attendance. A lower presence rate may reflect team structure, travel burden, leadership routines or environmental conditions rather than a simple preference for remote work. An analytics program is useful when it helps leaders distinguish among those possibilities and choose a targeted response.
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BlackRock: designing for a weekend reorganization
Mullenix reports that the BlackRock workplace used raised floors, underfloor air and power, wireless lighting and demountable partitions. He says large workforce reorganizations could occur over a weekend, with less downtime and capital reinvestment than a traditional renovation or relocation.
The planning implication is to design the service infrastructure and move process together. Components must be accessible, compatible and documented; teams need a sequence for disconnecting, moving and recommissioning them. The claimed advantage is operational speed and reduced disruption, not a promise that every reconfiguration will fit within one weekend.
Brooks Running: phased change and operational feedback
Mullenix says infrastructure walls consolidated power, data and mechanical systems at the Brooks Running workplace. He describes phased planning and operational feedback guiding later changes, and reports that the workplace could flex by roughly 50% capacity with minimal disruption.
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The article does not define that percentage’s metric or independently verify it, so it should not be used as an industry-wide capacity standard. Its practical point is the feedback loop: build or modify in phases, observe how the space performs, and use what operations reveal to inform the next phase.
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When evaluating a conventional renovation, a modular fit-out, a pilot or an infrastructure-heavy solution, use the same questions for each option.
| Decision axis | Questions to ask |
|---|---|
| Speed | How quickly can the change be designed, approved and executed? |
| Continuity | Can people keep working during the intervention, and what temporary arrangements are required? |
| Recurring effort | What labor, coordination and maintenance are required each time the workplace changes? |
| Waste and rework | Which elements can be reused, and what must be demolished, discarded or rebuilt? |
| Proof | Which analytics or feedback will show whether the change met its goal? |
| Agency | How much control do teams have over layout, privacy, lighting, air and work settings? |
A low initial construction cost can look attractive while recurring moves remain slow and disruptive. Conversely, a sophisticated infrastructure package may be unjustified where change is rare. Compare the full pattern of effort over the expected life of the workplace, not just the first project invoice.
A practical implementation roadmap
- Map likely changes. List organizational, staffing, technology and policy scenarios that could alter space demand. Separate probable changes from remote possibilities.
- Set a measurable objective. Choose one primary outcome and a small set of supporting indicators. Record the baseline and the review date.
- Audit the existing building. Document floor-to-floor access, power and data routes, air distribution, lighting controls, partitions, furniture standards and any constraints that limit reconfiguration.
- Run a contained pilot. Test one neighborhood, team or work mode. Keep the intervention reversible where practical so learning does not require demolition.
- Collect operational feedback. Ask employees, managers and facilities staff what worked, what failed and what created hidden effort. Compare those observations with utilization and service data.
- Scale with a kit of parts. Standardize components, connection details and documentation so future moves use known elements rather than bespoke redesign.
- Review and preserve options. Decide what to keep, change or retire. Update the baseline and reserve capacity for the next plausible scenario.
Common failure modes and corrections
Designing flexibility without a decision model
A large menu of settings does not tell leaders when to change them. Tie each major feature to a use case, an owner and a measure.
Relying on occupancy alone
Occupancy shows presence, not whether a setting supports concentration, collaboration or belonging. Pair utilization with interaction patterns, turnover, service demand and direct feedback.
Making a permanent bet too early
When uncertainty is high, a pilot can test the operating model before a full build-out. Keep the pilot long enough to observe normal variation, and define the conditions for scaling.
Ignoring the work required to reconfigure
Reusable partitions and accessible services still need inventories, trained teams, safety checks and commissioning. Include those tasks in the operating plan and measure the time they consume.
Confusing a case claim with a benchmark
Figures such as the roughly 50% capacity flexibility reported for Brooks Running describe that article’s case example. They are not a promise for another building with different systems, climate, lease terms or work patterns.
What to measure after a change
At the review date, compare the intervention with the original goal rather than asking whether people simply “like” it. Check whether the intended work mode occurs more reliably, whether space turns over as expected, whether service demand is manageable and whether teams can make small adjustments without a new project. Record downtime, temporary moves, material reuse and staff effort so the next decision includes the costs that are often invisible in a capital estimate.
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Why adaptability is an ongoing capability
Change will continue even after a workplace project is complete. Derek Thompson, identified by Mullenix as an Abundance co-author, captures the tension this way: “Growth is good. Change is hard. Both are true. And stasis sucks.” An adaptive workplace acknowledges the disruption of change while building the analytical habits, infrastructure and team agency needed to handle it.
The durable strategy is therefore sequential: define the outcome, measure the conditions that matter, make a reversible or infrastructure-supported change, learn from operations, and keep future options open. That approach turns adaptability from a slogan about movable furniture into a managed organizational capability.
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