How will the new housing policy align prices with local incomes?

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New National Housing Policy to Align Prices with Local Incomes Using Big Data Analytics

The upcoming National Housing Policy 2026-2035 (DRN 2026-2035) will implement a data-driven approach to ensure affordable housing prices are more closely matched with local income levels and resident needs. This policy aims to move away from a uniform pricing model and better reflect the diverse economic conditions across different districts and locations by leveraging big data analytics. Developers will be guided by this data to determine the most suitable types of housing, pricing, and locations that align with local demand, thereby reducing the issue of unsold properties.
Data-Driven Assessment of Housing Needs

The DRN 2026-2035 will utilize big data analytics to conduct detailed assessments of housing needs at the district and local levels. This system will consider factors such as the number and types of homes required, local income levels, and existing property prices. By analysing this comprehensive data, the policy intends to define affordable housing in a way that accurately reflects the specific economic realities of each area, moving beyond a generic one-size-fits-all approach.
Tailoring Housing Development to Local Demand

This new policy will enable housing development to be planned according to specific local requirements and market demand, a significant shift from previous practices. The insights derived from big data analytics will empower developers to make informed decisions about their projects. They will be able to identify the types of housing units, their price points, and the most appropriate locations that are likely to meet the demand of the local population, thereby addressing the persistent issue of unsold housing stock.
Addressing Regional Price Disparities

A key objective of integrating big data analytics is to rectify the incongruity of applying uniform housing prices across vastly different economic regions. For instance, the policy highlights the impracticality of having the same affordable housing price in a less affluent area like Kuala Krai, Kelantan, as in a prime urban centre such as Bukit Bintang, Kuala Lumpur. The data-driven approach is designed to establish pricing structures that are scientifically grounded in local economic conditions, ensuring greater affordability and accessibility for residents across the nation.

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How will the new housing policy align prices with local incomes?

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