Move to mass valuation when data and capacity allow

Use structured mass valuation methods to produce values more accurately, efficiently, and consistently across large numbers of properties. This is the scalable option once the city has enough data, quality control, and institutional capacity to support it.

• The city has a reasonably complete property roll and growing market evidence.

• Manual or parcel-by-parcel methods are too slow, inconsistent, or expensive.

• There is a medium-term commitment to professionalising valuation.

• Reasonably reliable property data, market proxies, and technical support.

• Quality assurance, documentation, and a route to explain results to non-specialists.

• Do not start here as a prestige project when data quality is still poor.

• Advanced models are not a substitute for good property facts and political preparation.

The technical risk here is overreach. Cities sometimes jump to a sophisticated model before they have the data, quality control, or communications capacity to defend the results, which can weaken the whole reform.

The full card would help the city plan the data architecture, modelling approach, quality assurance, staffing, external support, and communication that a scalable mass-valuation system requires.

• Bring sales, rents, and build-cost evidence into assessments

• Put revaluations on a rolling cycle

• Tighten valuation data and quality control.

Mass valuation becomes attractive when the city has a reasonably complete roll, a growing evidence base, and a need to value large numbers of properties more consistently than manual parcel-by-parcel work can deliver. Its promise is scale and consistency, not sophistication for its own sake. A workable mass-valuation system is therefore as much about data architecture, testing, quality control, and explainability as it is about modelling. Cities that rush into it as a prestige project usually discover that the technical model is not the only hard part.

• The city already has a reasonably complete property roll and some usable market or proxy evidence.

• Manual valuation is too slow, inconsistent, or expensive to keep the roll current.

• Leadership is willing to invest in a medium-term effort to professionalise valuation rather than chase a one-off jump.

• Assess readiness honestly before any procurement: the city needs credible property facts, usable evidence, and a governance model for updating both.

• If readiness is mixed, pilot one simpler mass-appraisal approach on one segment first instead of procuring a large citywide system.

• Plan from the start how the city will explain, review, and update the model, not just how it will build it.

• Whether to begin with a simpler tabular or factor-based mass approach, a more statistical model, or a hybrid of the two.

• Whether the city should build internal capability, rely on external technical support, or combine both with a clear transfer plan.

• How much controlled manual override will be allowed and under what rules so consistency is not undermined.

First 90 days

• Review data readiness, market evidence quality, and institutional capacity before choosing the modelling approach.

• Define the initial scope, such as one property class or one geography, and the success criteria for the first pilot.

• Set documentation and governance rules so every model input, assumption, and update can be traced later.

6 to 12 months

• Build and test the pilot model, compare results with known market evidence, and refine variables and groupings where needed.

• Run quality checks alongside the model from the start so accuracy and consistency are reviewed together.

• Prepare staff guidance and a taxpayer-facing explanation of the broad method before rollout expands.

12 to 24 months and beyond

• Scale only after the pilot performs credibly and the city can update the required data on a repeatable basis.

• Institutionalise the update rhythm, quality assurance, and documentation so the model does not decay after the first round.

• Use the mass-valuation experience to support a predictable revaluation cycle rather than sporadic major resets.

• Check whether current law recognises the planned form of mass appraisal and whether supporting regulations or manuals are needed.

• Clarify approval authority for model adoption, recalibration, and any significant manual overrides.

• Make sure the appeal or review process can interact with mass valuation without forcing the city back into ad hoc case-by-case practice.

• The city needs strong cooperation between valuation, IT, GIS, and management teams, even if external experts are involved.

• Quality-control capacity is not optional; a model without review will be difficult to defend publicly.

• Documentation and knowledge transfer matter as much as software, because staff turnover can quickly hollow out a system that is poorly understood internally.

• The most common risk is overreach: adopting a model that requires more data quality and specialist support than the city can sustain.

• Black-box outputs can damage legitimacy if staff cannot explain the broad logic to taxpayers or leaders.

• If the city ignores update and maintenance costs, the model may look impressive in year one and become stale in year two.

• Pilot performance against the evidence available and against simpler benchmark methods.

• Share of the roll covered by the required data fields at adequate quality.

• Frequency and type of quality-control adjustments after model runs.

• City capacity to refresh inputs and rerun the model on a planned schedule.

• Bring sales, rents, and build-cost evidence into assessments.

• Put revaluations on a rolling cycle.

• Tighten valuation data and quality control.

• Is the city genuinely ready for mass valuation, or only frustrated with manual practice?

• Which modelling approach matches the data the city can update reliably?

• What internal capacity must remain in place even if outside advisers help?

• How will the city explain the method in plain language once bills change?