Applied Intelligence Briefing
Edge Analytics / Applied Intelligence BriefingCase study
Locating and Counting Cellared Properties
Edge Analytics combined property datasets to quantify the prevalence of cellared homes and support Yorkshire Water's evidence to Ofwat on sewer flooding risk.
- Client
- Yorkshire Water
- Method
- Property data model
- Purpose
- Ofwat evidence
Linked property intelligence for fairer assessment of local flood exposure
The business challenge
How many cellared properties sit within the operating area - and what does that mean for flood risk?
Context
Cellared homes face a higher risk of sewer flooding and are more prevalent in older housing. Yorkshire Water needed a countrywide benchmark to establish whether its operating area contained a disproportionate concentration and to support evidence to Ofwat on the achievability of common flooding targets.
Requirement
Create a defensible, geographically consistent estimate despite the absence of a complete, readily available dataset of cellared properties.
Method
- 01
Property inventory
Identified detached, semi-detached, terraced and flatted properties across England and Wales.
- 02
Age + cellar signals
Linked property age with basement records to classify the likely prevalence of cellared homes.
- 03
Geographic benchmarking
Cross-tabulated property variables by water-company geography to compare Yorkshire Water with other operators.
Outputs & significance
Cellared stock changes flood risk
150%above the England and Wales average
National property model
Combined 15 property-age classes, seven property types, a cellar flag and water-company area identifiers.
Higher cellared stock
Estimated Yorkshire Water’s cellared-property total at almost 150% above the England and Wales average.
Unequal risk exposure
About 9% of all properties sat within the area, but it contained nearly 25% of all cellared properties.
Significance
Standard targets can mask local exposure
Linked property evidence demonstrated a disproportionate concentration of cellared homes and a materially different sewer-flooding risk profile.