oDifficulty: novice
Content
Learning Objectives
After reading this article, you’ll be able to:
- Understand the Space Occupancy dashboard
The Space occupancy per hour dashboard gives insight in the historical data collected by motion sensors, with values per hour during a rolling timeframe of 6 months.
It provides a complete, data-driven view of how your workplace is actually used across buildings, floors, and individual spaces.
It combines occupancy, headcount, and utilization insights to help you move from assumptions to facts, enabling smarter decisions on space optimization, workplace design, and cost reduction.
Each page of the dashboard builds on the previous one, moving from high-level portfolio summary to detailed, actionable analysis at the most granular level.
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Dashboard overview
- Summary: High-level view of occupancy, headcount, utilization time and portfolio performance
- Occupancy analysis: Understand when, where, and how different space types are used
- Utilization time analysis: Reveal how long spaces are used and identify time-based inefficiencies
- Building analysis: Deep-dive into one building to uncover opportunities
- Floor analysis: Pinpoint exactly which spaces are used, ignored, or overloaded on a floor
- Data: Access granular data per space and per time unit for validation and deep analysis
- Targets: Define optimal occupancy and utilization targets
- Monitored spaces:
“Summary” page
This page contains
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High-level KPIs across the portfolio
Buildings, monitored spaces, total seat capacity
Average and max occupancy
Average daily headcount and utilization time
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Time-based occupancy trends
Hourly evolution of average occupancy
Identification of peaks, dips, and patterns over time
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Location comparison
Occupancy % per site/building
Utilization time per site/building
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Behavioural patterns
Occupancy by weekday / hour of day
Headcount by weekday / hour of day
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Fully interactive filtering
Drill down by region, building, floor, space type, capacity, etc.
“Occupancy analysis” page
This page zooms in on the occupancymetric.
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Portfolio breakdown by space class / room category / capacity range
Compare workspaces, meeting rooms, focus rooms or specific capacity ranges (in terms of seats capacity) -
Occupancy trends over time
Per hour / day / week / month
Week pattern -
Distribution insights
How occupancy spreads across locations
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💡 What insights you can extract?
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Which types of spaces are actually in demand?
Compare work vs. meeting vs. focus spaces
- Example: meeting spaces peaking higher than desks → collaboration-driven usage
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Are we using the right mix of space types?
If focus rooms or meeting rooms consistently outperform desks, your layout is likely misaligned with behavior
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Are there structural underused space types?
Low occupancy in specific categories signals redesign or repurposing opportunities
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Do all locations behave the same?
Some buildings may rely heavily on meetings, others on individual work
- One-size-fits-all workplace strategies will fail here
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Is demand predictable or chaotic?
Smooth curves vs. sharp spikes indicate whether flexible or fixed setups make sense
“Utilization time analysis” page
This page zooms in on the utilization time metric:
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Portfolio KPIs on utilization time
Average daily utilization time
Maximum daily utilization time
Total seat capacity -
Time-based trends
Daily evolution of average utilization time -
Location comparison
Avg utilization time per site/building/floor
Comparison of locations vs. their capacity (scatter plot) -
Space-level insights
Utilization time per room type (e.g. desks, booths, coffee areas, meeting rooms) -
Fully interactive drill-down
Filter by building, space type, room category, etc.
This page shifts the conversation from “are spaces occupied?” to “are they actually used in a meaningful way?”
The key insight here is not just low occupancy, but short duration of use. That combination is powerful and often overlooked.
If people only stay ~2 hours on average, your workplace is no longer a “place to work all day.” It’s a destination for specific activities.
That has major implications:
•You likely don’t need as many desks as you think
•You should prioritize high-value spaces that support short, intentional visits
•Large, underutilized offices with low utilization time are strong candidates for consolidation
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💡 What insights you can extract
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Are spaces being used long enough to justify their existence?
Average ~2 hours per day is very low compared to a full working day
- Indicates transient, short-stay usage
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Which locations are truly “sticky” vs. “pass-through”?
Some buildings show longer stays, others very short stays
- Helps differentiate core offices vs. satellite hubs
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Do larger offices actually perform better?
Scatter plot reveals if higher capacity leads to longer usage
- Often shows no clear correlation → oversizing risk
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Which types of spaces drive longer engagement?
Example: coffee areas or collaboration zones may have higher utilization time
- Indicates where value is actually created
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When do people stay the longest?
Weekday patterns show stronger engagement midweek
- Fridays often underperform
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Where are we wasting time capacity?
Spaces with consistently low utilization time are prime candidates for repurposing or removal
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Are we designing for full-day work or short visits?
Low average time strongly suggests hybrid, activity-based usage
“Building analysis” page
Use this page to deep dive into 1 specific building to uncover floor-level inefficiencies and optimization opportunities.
This page contains:
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Floor-level occupancy trends
Occupancy evolution per floor
Comparison of floors against building average -
Occupancy trends per space class / room category
Occupancy evolution per type of space -
Utilization time vs. capacity
Scatter plot comparing how each location is used compared to its seats capacity -
Headcount information
Complementary to the occupancy rate, which is always a relative value, this page also shows absolute values.
When using a headcount sensor in a space, the sensor can detect the actual headcount value.
When using a motion (presence) sensor in a space, the sensor only detects 0 or 1 as headcount value. -
Headcount vs. workspace capacity over time
Compare headcount against seats capacity to observe how “full” the location is at any day.
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Headcount values are always estimated, based on sensor data. They don’t represent the real number of persons present in a building, which should come from access control systems/badge readers.
For more details on how Spacewell determines headcount values, see here.
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💡 What insights you can extract
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Which floors or space types are underperforming?
Easily spot floors or space types consistently below average occupancy
- Example: some floors barely reaching 20–30% while others peak above 50%
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Are people clustering or spreading evenly?
Heatmaps reveal concentration patterns across floors
- Indicates preferred vs. ignored locations
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Which floors justify their space and which don’t?
Scatter plot highlights floors with high capacity but low utilization time
- These are prime candidates for closure or repurposing
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Where can we take immediate action?
Locations with low occupancy AND low utilization time = quick wins
“Floor analysis” page
Use this page to deep dive into 1 specific floor to pinpoint exactly how spaces are used throughout the day.
It’s the only page that gives access to the corresponding floor plan.
This page contains
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Visual floorplan with utilization times
Color-coded view of each space based on daily utilization time (in hours).
Each monitored space is highlighted (green/orange/red)
The colors reflect the targets set for metric “daily utilization time”
The tooltip shows the name of the space + the average daily utilization time (in hours) -
Space-level headcount heatmaps
Average (estimated) headcount per weekday or per room category
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Headcount vs. workspace capacity over time
Compare headcount against seats capacity to observe how “full” the location is at any day.
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Utilization spreading
Boxplot for daily utilization time per space
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💡 What insights you can extract
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Which exact desks or rooms are never used?
Visual floorplan immediately highlights cold spots
- Ideal for removing or repurposing unused spaces
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Where are people clustering?
Identify “hot zones” where utilization is consistently high
- Indicates preferred locations (light, proximity, amenities, etc.)
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Is the floor layout working as intended?
Compare planned use (e.g. focus vs. collaboration) vs. actual behaviour
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Are certain spaces overperforming or underperforming?
Boxplot reveals which spaces are consistently used vs. rarely touched
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Do we have hidden capacity on this floor?
Headcount vs. capacity shows if the floor could handle more people or if it’s oversized
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Is usage evenly distributed or highly fragmented?
Strong variation between spaces indicates poor layout or user experience
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Which spaces should be redesigned first?
Low occupancy + low utilization time = low hanging fruit
This is the most actionable level of insight in the entire dashboard.
At this level, you’re no longer talking about buildings or floors, you’re looking at real behaviour in real spaces.
What typically emerges here is very clear:
• Some spaces work extremely well and attract people naturally
• Others are completely ignored, regardless of availability
That’s not a capacity issue, it’s a design and experience issue.
The biggest opportunity on this page is:
•Replicating what works (hot spaces)
•Eliminating or redesigning what doesn’t (cold spaces)
Instead of asking “do we need less space?”, this page helps you answer:
“how should this space actually be designed to match user behaviour?”
“Data” page
Use this page to access the truth behind every space and every timeframe to validate, deep-dive, and take precise action.
This space contains two tables:
- Metrics per monitored space
Gives full details of all metrics per individual, monitored space
- Metrics per hour
Metric values per hour, across all monitored spaces
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This page is your source of truth and your safety net.
Everything you’ve seen in previous pages is aggregated and simplified for decision-making.
This page allows you to challenge, validate, and explain those insights with precision.
It’s especially powerful in real-life situations:
•A manager claims “meeting rooms are always full” → you verify per room, per hour
•A location is flagged as underperforming → you identify exactly which spaces and when
•A redesign is planned → you validate assumptions with actual usage patterns
This is not about storytelling, it’s about evidence.
“Targets” page
Use this page to set your optimal workplace targets and compare actuals against them.
The whole page is read-only except the four target sliders:
Target |
Default value |
|---|---|
Daily utilization time - low target (h) |
2 hours |
Daily utilization time - high target (h) |
4 hours |
Occupancy - low target (%) |
25 % |
Occupancy - high target (%) |
50% |
Users can adjust these targets by sliding the value left and right. These adjustments are applied immediately across the entire dashboard (all pages).
However, they are not saved permanently.
Currently it’s not possible to change the default values upon customer demand.
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💡 What insights you can extract
What is our “ideal” occupancy and utilization level?
- Define realistic targets instead of relying on industry assumptions
How far are we from optimal performance?
- Instantly see the gap between current performance and desired targets
Which parts of the portfolio fail to meet targets?
- Identify underperforming buildings or space types based on your own benchmarks
Are our targets even achievable?
- Test different scenarios to ensure goals are realistic given current behaviour
“Monitored spaces” page
Use this page to understand how many monitored spaces you have and where they are located.
It’s crucial to understand that the Space Occupancy dashboard reports on SPACES, not on SENSORS.
The reason is that a sensor is not linked to a space permanently. Organizations sometimes swap sensors from one space to another depending on business needs.
Therefore, Spacewell dashboards report on what happens to SPACES, using sensor data as input.
For example:
If your meeting room “ABC” has sensor “123” in 2024 and then you replaced it with sensor “456” in 2025, this operation does not affect your Space Occupancy dashboard.
The dashboard will show a continuous stream of data across 2024 and 2025.
Good to know:
- Metrics “Spaces with presence sensor” and “Spaces with headcount sensor” represent the CURRENT situation in your portfolio
- All other metrics in the top row also represent the CURRENT situation
Monitored spaces - timeline
- This chart shows how many spaces are monitored over time
- If the line rises, it means that you are installing more sensors
- If the line falls, it means that you are decommissioning sensors
- If the line has bumps, it means that some sensors were temporarily offline
Good to know
The “Space Occupancy - per hour” dashboard takes into account following data:
- Business hours only, configured in Studio > Default Regional Settings (allowing for 1h margins both in the mornings and the evenings)
- Weekends are excluded
- 6 months of hourly sensor data
More information
Frequently Asked Questions on Dashboards
Check out FAQ on Dashboards