Schedule and Activities

Space serves activities, and activities have rhythms. A workplace sized for average activity fails at peak rhythm; a setting mix built on job titles rather than actual activity proportions mis-provides systematically. This method consolidates the diagnosed evidence into the organisation's activity profile — the proportions of focus, collaboration, meetings, learning, social and specialist work — and its temporal structure: daily curves, weekly rhythms, monthly cycles. It is the quantitative bridge between demand evidence and every spatial model that follows.

• In Define, after Dynamics Alignment, as direct preparation for Taxonomy Alignment and the Kit of Parts
• Before Sharing Ratio, which is meaningless without the rhythm structure
• When activity assumptions in an existing programme of requirements need evidence-based replacement
• Per major population where activity profiles diverge sharply — one organisational average can misfit everyone

• Workplace strategist and spatial analyst
• Project team consolidating Dynamics and Occupancy evidence
• Team leads validating activity profiles for their populations
• FM contributing operational rhythm knowledge (events, cycles, seasonal patterns)

• Dynamics Assessment activity data: reported activity proportions per team
• Occupancy Assessment temporal analysis: measured curves, peaks, duration patterns
• Business Needs Interviews: management rhythms and recurring events
• Balance output: required-overlap patterns that create scheduled demand concentrations

1. Consolidate reported activity proportions with observed setting use into a reconciled activity profile — where they diverge, the reconciliation logic must be explicit and documented.
2. Segment the profile by population where variance is structural: an organisational average that fits no actual team is a modelling input, not a finding.
3. Build the temporal structure: daily occupancy curves, weekly rhythm (the Tuesday–Thursday concentration and its causes), monthly and seasonal cycles, and event-driven spikes.
4. Overlay required-overlap patterns from Balance: scheduled team days convert smooth averages into demand cliffs that spatial models must survive.
5. Distinguish rhythm that is structural (client cycles, regulatory calendars) from rhythm that is policy artefact (anchor days chosen by habit) — the second is a design variable, the first a constraint.
6. Produce the activity-and-rhythm model: proportions, populations, curves, peaks and their confidence levels.

• Reported focus proportions exceeding observed focus-setting use — usually a supply failure, not a reporting error
• Peak rhythms that are coordination artefacts and could be flattened by scheduling rather than served by space
• Populations whose profiles diverge so far the average misleads (field-based vs desk-based)
• Activity proportions contaminated by current supply: people report doing what the building lets them do
• Meeting activity measured in bookings rather than actual meeting behaviour

• Reconciled activity profile, segmented by population
• Temporal rhythm model: curves, peaks, cycles, event structure
• Structural-versus-artefact rhythm classification
• Confidence annotations per input, feeding the assumption register

The activity profile is the primary quantitative input to Taxonomy Alignment (setting mix) and the Kit of Parts (setting types and proportions). The rhythm model drives Sharing Ratio peak assumptions and Hybrid Balance capacity implications. Artefact rhythms flagged here become policy design variables in Hybrid Balance rather than spatial requirements. Confidence annotations flow into Calibration.

Reconciling reported and observed activity requires judgement about which source to trust per activity type — people report focus work reasonably and meeting time poorly; sensors measure presence well and activity content weakly. Deciding whether a peak should be served, flattened or governed is a strategic call, not an arithmetic one.

• Using reported activity proportions unreconciled with observed behaviour
• Modelling on organisational averages when population variance is structural
• Sizing for average occupancy and discovering the Tuesday problem after handover
• Treating policy-artefact rhythms as immovable constraints
• Presenting the profile without confidence levels, so Calibration inherits false precision

A professional services firm reported 30% meeting activity; observed data showed meeting settings occupied 19% of measured time, with median duration half the booked slots. Reconciliation attributed the gap to booking padding and no-shows. The reconciled profile cut the meeting-seat requirement by a quarter — and flagged the Thursday demand cliff created by three departments' independently chosen anchor days, which Hybrid Balance later redistributed at zero spatial cost.