RESEARCH · DATA & METHODOLOGY

Real data.
Handled properly.

Cyberate's research uses operational, public and partner data under explicit boundaries: what the research question needs, what can be analysed, what must be de-identified, and what cannot be used without permission.

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Three kinds of data.
One set of rules.

Every research question draws on some combination of three source families, each with its own governance.

  • From live group operations: Generated by DDDI Group's development, construction and supply businesses, and by Cyberate systems in live deployment. This is the operational core most research teams never get. (Operational data) (Development milestones and project status; Scheduling and site records; Procurement events; Quoting workflow data; Reporting dashboards): De-identified before research use.
  • From open and government sources: The public data layer under every housing decision, assembled and quality-checked before analysis. (Public data) (Planning records and development applications; Housing market data; Census and demographic data; Infrastructure data; GIS and spatial data): Public does not mean unrestricted: sources and licences are respected.
  • From partners and fieldwork: Data generated by the research itself, with university partners and industry participants. (Research data) (Surveys, interviews and workshops; University partner datasets; Model evaluation datasets): Collected under agreed research protocols.

01

Eight steps.
Every question.

The same methodology carries a question from definition to something the industry can use, with governance built into the middle, not bolted on at the end.

  1. Define the question: Frame it precisely, and agree what a useful answer looks like.
  2. Identify the sources: Which operational, public and partner data the question actually needs.
  3. Assess data quality: Coverage, gaps and bias, established before analysis begins.
  4. De-identify & govern: Sensitive data de-identified; access limited to the research team on the question.
  5. Analyse & model: Trends, timelines, patterns and the factors behind different outcomes.
  6. Validate live: Findings tested against live operations and practitioner experience.
  7. Document limitations: What the data supports, and what it does not, stated plainly.
  8. Translate: The answer ships as a system, report or dashboard, not just a finding.

The boundaries we don't cross.

Trust in the research depends on how the data behind it is handled. These rules apply to every engagement, commissioned or internal.

  • De-identification by default: Operational data used in research is de-identified; commercial specifics stay confidential.
  • Client data stays client data: Customer systems' data is never used for research without explicit agreement.
  • Agreed purposes only: Data is used for the research purpose it was agreed for. No quiet reuse.
  • Governed access: Access is limited to the research team working on the question.
  • No manufactured findings: We publish what the data supports, including the null results.
  • Limitations disclosed: Coverage, assumptions and methodological limits are stated, not hidden.

02

What the method looks like
on a real question.

Chapter 2 of the Australia Housing Market White Paper (2026) is this methodology applied end to end: a defined scope, a consistent platform record, staged analysis, and a published statement of what the evidence does not support.

Evidence base: 20,000+ residential subdivision planning consent applications via PlanSA, South Australia's statewide digital planning portal, January 2022 to June 2025, across 18 Adelaide metropolitan councils. Lodgements over this period were proportionally sampled across the 18 councils; the published analysis does not state the sample size.

  1. Define scope: Jurisdiction, councils, time window and proposal type.
  2. Extract records: From the portal, register or council system.
  3. Tag workflow switches: Verification, pathway, referrals, notification.
  4. Run the diagnostics: Bivariate first, then multivariate, so correlation is separated from what persists under controls.
  5. Turn results into actions: Reduce loops, clarify pathway rules, improve referral coordination, publish benchmarks.

See the white paper

What a published finding
is not allowed to claim.

Documenting limitations is step seven of the method, not a footnote. These are the limits published alongside our own flagship white paper - the same discipline applies to commissioned work.

Evidence note

Publication
Australia Housing Market White Paper (2026), published by RESI, the Australian Residential Construction Institute.
Method
Bivariate analysis of each driver independently, then multivariate modelling to separate association from what persists under controls.
Data currency
Data to 2025.
  • The white paper is published by RESI and analyses public data to 2025. Cyberate researchers are named in its core research team; Cyberate is not its publisher.
  • Chapter 2's evidence base covers residential subdivision consent applications in 18 Adelaide metropolitan councils. It is a South Australian study, not a national benchmark, and findings are directional rather than a prediction of any single application's timeline.
  • Delivery-gap figures are the Productivity Commission's (2025), cited by the white paper. They are not Cyberate measurements.
  • Nothing drawn from the white paper on this site is a valuation, a forecast, or planning, financial or legal advice.

Data you can trust
the boundaries of.

If your question involves your own operational data, the boundaries are agreed before the research starts. Bring the question; we'll bring the method.

Talk to our research team · Commission research