Taxonomy Alignment

This is the method where strategy becomes quantity. Everything before it produced evidence, positions and principles; Taxonomy Alignment converts them into the numbers a building must satisfy: how many settings of which type, at what capacity, sharing ratio, density and enclosure, in which adjacencies and zones. Done rigorously, every number carries its evidence chain back through the demand position to the diagnosis. Done casually, the programme of requirements becomes precedent dressed as analysis — and every downstream spatial decision inherits the fiction.

• In Define, once Dynamics Alignment, Schedule and Activities, Hybrid Balance and Spatial and Cultural Needs have produced their outputs
• Before Scenario Development, which varies this demand model across futures
• When an inherited programme of requirements needs evidence-based reconstruction
• Re-run in Recalibrate whenever assumptions shift enough to invalidate the demand model

• Workplace strategist and spatial analyst building the model
• Project team validating inputs
• CRE for portfolio and building context
• Leadership team reviewing and accepting the demand model — the numbers require the same ownership discipline as the findings did

• Aligned demand position and its priority ranking
• Activity profile and rhythm model from Schedule and Activities
• Presence logic and capacity implications from Hybrid Balance
• Annotated spatial requirements from Spatial and Cultural Needs
• Supply baseline and gap structure from Taxonomy Spatial Benchmarking
• Building constraint register

1. Translate the activity profile into setting demand: which setting types, in what proportions, derived from measured and reconciled activity — not from typology catalogues.
2. Derive capacity assumptions from the presence logic: peak-adjusted population per rhythm scenario, not headcount multiplied by a borrowed attendance factor.
3. Set sharing ratios per population from overlap patterns and rhythm evidence, differentiating where the evidence differentiates rather than averaging to one organisational number.
4. Define density and enclosure requirements from focus demand, sensory and accessibility findings, and cultural conditions — with the Spatial and Cultural Needs annotations attached.
5. Construct adjacency and zoning logic from the interdependency matrix and confidentiality requirements: what must be near what, what must be separated, where customer-facing and secure zones sit.
6. Assemble the programme of requirements: settings, quantities, capacities, ratios, adjacencies, zones — each line annotated with its evidence source and confidence level.
7. Test the demand model against the building constraint register and record where demand exceeds what any configuration of current supply can deliver.
8. Present to the leadership team for acceptance, with the sensitivity structure visible: which numbers are robust, which move if assumptions move.

• Numbers without evidence chains — every unexplained ratio is a future dispute
• Averaging across populations whose evidence diverged, quietly undoing the diagnosis
• Precedent contamination: ratios drifting toward industry norms because they feel defensible
• Demand that violates building constraints being reconciled silently instead of escalated as a portfolio question
• False precision: single-point numbers where the evidence supports ranges

• Quantified demand model: settings, capacities, sharing ratios, density, enclosure
• Adjacency and zoning logic
• Evidence-annotated programme of requirements
• Constraint-conflict register
• Sensitivity structure per key number

The demand model is the base case Scenario Development varies and Calibration governs. The programme of requirements anchors Workshop III option comparison, Sharing Ratio, Stacking and Blocking and the Kit of Parts. Constraint conflicts escalate into portfolio decisions. Because the platform maintains the model, Recalibrate can regenerate it when assumptions change instead of commissioning a new study.

The platform computes the model; judgement sets its parameters. Deciding how much differentiation between populations is governable, where a range must collapse to a number for decision purposes, and when demand exceeding supply is a design problem versus a portfolio problem — these are strategic calls the arithmetic cannot make.

• Building the programme from typology catalogues instead of the organisation's measured activity
• One sharing ratio for everyone because differentiation is administratively inconvenient
• Hiding the sensitivity structure and presenting the model as more certain than its inputs
• Skipping leadership acceptance, so the numbers get relitigated at concept stage
• Treating the model as final rather than regenerable — the assumption register exists so it can be rebuilt

A utilities company's evidence supported sharing ratios from 0.5 (field engineering) to 0.9 (regulatory affairs). Administrative pressure pushed for a single 0.7. The alignment retained three governed ratio bands with evidence chains; the constraint test then showed the 0.9 populations couldn't be accommodated on their preferred floors — escalated as an explicit adjacency trade-off, decided by the leadership team in one session because every number in the room could defend itself.