Business Objective
Our client, a healthcare Real Estate Investment Trust, wanted to understand future senior housing supply/demand dynamics to plan investment strategies. The client wanted us to build submarket (micro-market) regions for senior housing portfolio and a comprehensive Supply inventory database. They wanted to implement a rule-based engine to estimate future demand and develop an automated supply demand estimation framework to continuously estimate supply and demand metrics.
Challenges
- Lack of consolidated supply sources and data on senior housing occupancy
- Data quality and completeness issues
- Data sufficiency issues with multiple attributes within available datasets
Solution Methodology
- Utilized existing data to understand prevailing trends and optimized market boundary maximizing demand coverage for each property.
- Combined census tracts around each property to form submarkets.
- Sourced property inventory data from multiple vendors and built Name – Entity & Address Match logic to de-duplicate data.
- Analyzed historical construction trends to estimate likely opening dates.
- Consolidated supply, demographic, and occupancy rate data and built a linear regression model to predict demand at the submarket level and identify key drivers of demand.
Business Impact
- Developed proprietary senior housing submarkets capturing >80% market demand
- Predicted demand & Identified areas with low supply for potential investment opportunities
- Automated data acquisition process enabling less manual effort and faster strategic decisions
