Why ScoreView
Why boards use ScoreView instead of a spreadsheet
Four things ScoreView does that a spreadsheet, a general BI tool, or a generic AI assistant cannot. Each one shows up in the board pack, not just in the product.
1. The record is already loaded, cleaned, and joined
ScoreView ingests every published Housing Ombudsman determination, every Regulator of Social Housing judgement letter, every published Tenant Satisfaction Measures return, and the Companies House and Charity Commission filings for each registered provider. The corpus is deduplicated, disambiguated across landlord identity changes, and refreshed weekly.
You do not have to build the pipeline. You do not have to reconcile landlord names across sources. You do not have to spot when a landlord has merged with another. The joins are already done.
2. Every number is traceable to a published source
Every headline figure, every category count, every trend line links back to a specific determination reference, a specific judgement letter, or a specific TSM return. Board members can click through from the pack to the source document.
A spreadsheet cannot show you provenance. A BI dashboard does not have the source layer. A generic AI can generate prose, but it cannot cite the case reference behind the sentence: and the difference matters when the board asks “where does that conclusion come from?”
3. The framing is the Regulator’s framing
The Regulator of Social Housing inspects against four Consumer Standards. ScoreView’s outputs: Inspection Pack, Risk forecaster, per-landlord profile, Investment Cases: are all organised around those four standards. The pack you take into a Regulator engagement session is already in the language the Regulator uses.
A generic analytics tool organises by category. ScoreView organises by regulatory question. That alignment removes a translation step that otherwise sits in every board conversation.
4. Cohort comparison is fair, not just aggregated
Cohort comparison in ScoreView uses structural matching: same landlord type, similar stock size, refinable by region and RSH grade. When fewer than three structural peers exist, ScoreView tells you so rather than showing a misleading average. Ranking bands (top 25% to bottom 25%), category comparisons, and per-10,000-homes rates all normalise for size so large and small providers can be read side by side.
A spreadsheet cannot maintain a live peer cohort. A BI dashboard averages the sector. ScoreView does the comparison the way a Regulator or a Board actually needs it done.
What ScoreView deliberately does not do
- No per-landlord adverse data on the public surface. Named intelligence sits behind authentication.
- No predictive claim attributed to a named entity. Sector-level trend detection only.
- No ingestion of tenant or complainant personal data. Published record only.
- No third-party display advertising. No user data sold.
The self-imposed limits are the reason the outputs are defensible in front of counsel and the Regulator alike.