Our Methodology
How we collect, process, and present data about NSW strata managers. We believe in full transparency—here’s exactly how Compare Strata Managers works.
Our Data Sources
Every manager profile on Compare Strata Managers is built from publicly available, verifiable data. We do not rely on self-reported information from strata management companies. Instead, we aggregate data from five primary sources and cross-reference them to build a comprehensive picture.
What We Track
Each strata manager profile on Compare Strata Managers presents the following data points, all drawn from the sources described above. Our goal is to give owners corporations the information they need to make an informed choice—without editorialising.
The total number of strata schemes (strata plans) currently managed by the agent, as recorded in StrataHub. This is a key indicator of a manager’s scale and capacity.
The total number of individual lots (apartments, units, townhouses) across all schemes managed. A manager with 50 schemes of 200 lots each has a very different workload than one with 50 schemes of 6 lots.
Which local government areas the manager operates in, based on the locations of their managed schemes. This helps you find managers with experience in your area.
Where StrataHub data is available, we calculate the proportion of a manager’s schemes that held their annual general meeting within the required statutory timeframe under the Strata Schemes Management Act 2015.
NCAT, Supreme Court, and Court of Appeal decisions linked to the manager’s schemes. We distinguish adverse findings (substantive orders made) from total cases and use the adverse rate per 100 schemes—not raw counts—to determine record badges, so large managers are compared fairly.
Current licence status from NSW Fair Trading, including licence number, class, and whether any conditions or restrictions are recorded. We flag managers whose licence could not be verified.
Average star rating and total review count from Google. We display this as-is from Google Places and do not filter or weight individual reviews.
Registered business name, ABN where available, office locations, and contact information sourced from public business records and StrataHub registrations.
Tribunal Data & Adverse Findings
One of the most important data points on Compare Strata Managers is tribunal history—specifically, adverse findings. Not all tribunal cases are equal: a levy recovery application brought by the owners corporation is very different from a finding of agent misconduct. We distinguish between the two.
How we collect it: We search caselaw.nsw.gov.au for decisions from the NCAT Consumer and Commercial Division, the Supreme Court, and the Court of Appeal that relate to strata schemes. Relevant decisions are typically filed under the Strata Schemes Management Act 2015 or the Home Building Act 1989 where they involve strata-managed properties.
How we match cases to managers: Tribunal decisions frequently reference strata plan (SP) numbers. We extract these SP numbers from the decision text and match them against our StrataHub dataset to identify which managing agent was responsible for that scheme at the time the application was filed. Where a case names the managing agent directly (for example, in agent conduct complaints), we use that direct reference instead.
Total cases vs. adverse findings: We track both the total number of cases involving a manager’s schemes and the subset where the outcome was adverse—meaning substantive orders were made against the scheme or its management. Cases that were dismissed, withdrawn, settled, or brought by the owners corporation (such as levy recovery) are counted in the total but are not classified as adverse. The adverse count is the metric we use for badges and comparisons, as it is a more meaningful indicator of actual problems.
Rate-based badges: A raw adverse count can be misleading. A manager with 5,000 schemes and 3 adverse findings has a fundamentally different track record from one with 50 schemes and 3 adverse findings. To address this, our record badges use the adverse rate—adverse findings per 100 schemes managed—rather than the raw count:
Zero adverse findings, or an adverse rate below 0.5 per 100 schemes (for managers with 50+ schemes). These managers have either no adverse outcomes or an adverse rate well below the industry average.
Adverse rate between 0.5 and 2.0 per 100 schemes. These managers have some adverse findings relative to their portfolio size. Worth reviewing on the manager’s profile page for context.
Adverse rate above 2.0 per 100 schemes. A higher proportion of this manager’s schemes have been subject to adverse tribunal findings. Review the specific cases before making a decision.
For managers with fewer than 50 schemes, the sample size is too small for a rate to be statistically meaningful. In these cases, we fall back to the raw adverse count (0 = clean, 1–2 = caution, 3+ = elevated).
Industry average: Across all NSW strata managers, the weighted adverse rate is approximately 0.32 adverse findings per 100 schemes. This is calculated as total adverse findings divided by total schemes across the entire industry—not as an average of individual manager rates, which would skew towards smaller operators. We cite this figure in manager narratives to provide context.
The presence of cases on a manager’s profile does not necessarily indicate wrongdoing by the manager. Many tribunal applications are brought by lot owners against their owners corporation (not the manager), and the manager may appear only because they administered the scheme. Levy recovery cases, which make up a large proportion of NCAT strata matters, are typically initiated by the owners corporation (often on the manager’s advice) to collect unpaid levies—this is generally a sign of active financial management, not mismanagement. This is why we focus on adverse findings rather than total case counts when assessing a manager’s record.
Matching limitations: Not all tribunal decisions contain SP numbers, and not all SP numbers can be matched to a current managing agent (some schemes have changed managers since the case was heard, or the scheme may be self-managed). Our tribunal matching is therefore a lower-bound estimate: the true number of cases involving a manager’s schemes may be higher than what we report. We are continually improving our matching algorithms and expanding our coverage of historical decisions.
Limitations & Caveats
We work hard to present accurate, fair information, but no dataset is perfect. Here are the known limitations you should be aware of when using Compare Strata Managers.
- StrataHub data completeness. StrataHub is the most comprehensive register of NSW strata schemes, but it relies on schemes and managing agents submitting up-to-date information. Some records may be out of date—for example, a scheme that recently changed managers may still show the previous agent. We update our data regularly, but there is always some lag between a real-world change and its appearance on our site.
- NCAT case matching accuracy. Our automated matching of tribunal decisions to managers relies on SP numbers extracted from decision text. In some cases, SP numbers are mentioned in passing (for example, as a neighbouring scheme) rather than being the subject of the dispute. While we apply filtering rules to minimise false matches, some cases may be attributed to the wrong manager. If you spot an error, please let us know.
- AGM compliance data. AGM compliance rates are calculated from StrataHub records where meeting dates are available. Not all schemes have complete AGM records in StrataHub, so the compliance rate we calculate may not reflect the full picture. A manager showing a lower compliance rate may simply manage schemes that are less diligent about updating StrataHub, rather than actually missing AGM deadlines.
- Google Reviews are unverified. Google review ratings and counts are presented as-is from Google Places. We have no way to verify whether reviews are genuine, whether they were left by actual lot owners, or whether a manager has actively solicited positive reviews. Treat review data as one signal among many, not as a definitive indicator of quality.
- Licence status is point-in-time. We verify licence status periodically via the NSW Fair Trading API. A licence that was valid when we last checked may have since lapsed, been suspended, or had conditions added. For the most current licence information, check directly with NSW Fair Trading’s Verify a Licence service.
- Historical changes. Our profiles show a manager’s current portfolio. If a manager recently took on (or lost) a large number of schemes, their profile may not yet reflect the change. We do not currently track historical portfolio size over time, though we plan to add this in future.
- No quality score or ranking. Compare Strata Managers does not assign scores, ratings, or rankings to strata managers. We present data and let you draw your own conclusions. The absence of a scoring system is deliberate: we believe any single number would oversimplify a complex decision and could be gamed.
Editorial Independence
Compare Strata Managers is editorially independent. We do not accept payment from strata managers to improve how they appear on the site, to suppress negative information, or to prioritise their listing in search results. No manager can pay to have tribunal cases removed, reviews hidden, or their profile enhanced.
Our revenue model is based on advertising and lead generation, clearly separated from our data presentation. Advertising content is always labelled. The data shown on manager profiles is identical whether or not the manager has any commercial relationship with us.
If a strata manager believes we have published inaccurate information about their company, we welcome corrections. We will investigate any claim and update our data if we find an error. However, we will not remove accurate information simply because a manager finds it unfavourable. Our commitment is to lot owners and owners corporations who rely on this data to make decisions.
If you believe any information on Compare Strata Managers is inaccurate, please contact us with the specific details. We take data accuracy seriously and will investigate and correct any verified errors promptly.
Updates to This Page
This methodology page was last updated in February 2026. As we add new data sources, improve our matching algorithms, or change how we present information, we will update this page to reflect those changes. If you have questions about our methodology that aren’t answered here, please get in touch.