Workplace intelligence
Workplace Intelligence vs Occupancy Analytics: What Should Buyers Actually Measure?
For Workplace strategy, corporate real estate, FM, HR, IT and procurement.
Evidence checked · Guide updated
Occupancy data can describe space use. It cannot, by itself, tell an organisation whether people can do their best work or whether a proposed change is justified.
Independent educational decision guidance, not an assessment of an individual supplier or a certification, compliance determination or guarantee of outcomes. Check current sources and organisation-specific constraints.
Start with the decision, not the dashboard
A dashboard answers the question it was designed to measure. It does not necessarily answer the question a workplace leader needs to decide. Before buying sensors, changing space or declaring a utilisation target, write down the proposed decision, the organisational purpose and the evidence that would count as success. The first question is not “How full are we?” but “What work are we trying to support, at what cost and under which constraints?”
Occupancy, utilisation and intelligence are different concepts
Presence can be observed through appropriate measurement. Desk or room utilisation additionally needs a clear numerator, denominator, time window and distinction between bookings and actual use. Workplace intelligence brings those observations together with activity needs, people’s experience, work patterns, business objectives and operating constraints. A space may be heavily used because it is appropriate or because alternatives are unavailable.
Beware the denominator
In the keynote’s illustrative example, 37 of 100 desks occupied is 37%. If the same 37 people are counted against 50 available desks, the reported utilisation rises to 74%. That does not establish a saving, a productivity improvement or harm. It is arithmetic about availability at one point in time. A decision needs additional evidence about demand at peak periods and the consequence of removing space.
Peaks and variation matter
An illustrative week of 22%, 91%, 94%, 83% and 17% averages 61.4% across equally weighted measurement windows. However, the middle of the week could still constrain people. Review distributions by day, setting and demand type, not only means. Ensure comparisons use compatible opening hours, effective capacity, sensor coverage and observation periods.
Ask why people use a setting
A collaboration area may be full of employees doing individual focus work because the quiet rooms are unavailable. This is the fictional *Stockholm West* example from Frederik Joustra’s presentation, not a customer case study. Use interviews, short pulse questions and booking information where appropriate. More intrusive employee monitoring should not be the default response to an unclear metric.
Compare explanations before interventions
Possible causes include unnecessary area, inappropriate setting mix, booking policies, team schedules, inaccessible services, outdated configuration or behaviour shaped by an earlier policy. Compare retaining, reconfiguring, changing operating practices and acquiring additional capability. Do not allow a product demonstration to redefine the requirements retrospectively.
Use proportional evidence
For a reversible adjustment, a small set of observations and a bounded trial may be appropriate. An irreversible lease or capital decision normally requires stronger evidence. Record missing information and material uncertainties rather than presenting every data point as equally reliable.
Preserve employee trust
Consider whether the proposal relies on data about identifiable workers. Establish necessity, transparency, safeguards and the applicable legal basis before processing personal information. Aggregate data and less intrusive methods may often be more suitable for the decision than individual tracking.
Evaluate outcomes after intervention
Decide in advance what should improve: access to suitable settings, employee experience, service reliability, operating costs, capacity at peaks or other organisation-specific outcomes. Keep the record of what changed, so subsequent measurements are not interpreted as if the intervention had never occurred.
A defensible next step
Document the purpose, competing explanations, candidate interventions, relevant evidence, responsible owner, stop conditions and review point. Only then decide whether additional technology is justified. The right answer may be to retain what is already in place.
Questions buyers ask
Practical questions, bounded answers.
What decision will improved space data actually support?
What is the precise definition of occupancy or utilisation used here?
Are bookings, presence and activities being confused?
Does the measurement cover the busiest days and relevant workplace settings?
How accurate and complete is the data, and how was accuracy assessed?
What alternative explanations could produce the same pattern?
What information can be gathered without individual employee surveillance?
Which needs cannot be inferred from sensor data alone?
What would disprove the proposed intervention?
Could an operating-policy or configuration change solve the problem?
Which outcome measures will be examined after the change?
Who can review, reverse or stop the intervention?
Evidence and standards context
Sources, status and scope.
Source status describes the cited material, not a vendor or product certification. Confirm the applicable version, jurisdiction and implementation context for each decision.
Royal Society · Published; verify latest version · See publisher
Research from two headquarters, interaction volume only.
UK ICO · Published; verify latest version · See publisher
UK employment monitoring guidance.
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