Transforming social housing through effective data management
Social housing faces a significant challenge in the form of inadequate data management. The Housing Ombudsman describes that poor data and record keeping is ubiquitous. It poses a serious threat to the progress and success of HAs and LAs, staff morale, and overall tenant wellbeing. However, amidst this challenge lies a golden chance to transform the situation for the better. By acting now, we can quickly utilise data and leverage it to improve situations for tenants and staff alike.
The Consequences of Poor Data Management:
Social housing, like any other sector, relies heavily on data for decision-making, resource allocation, and improving services. However, the consequences of poor data management in this domain are far-reaching. Inaccurate, incomplete, or outdated data can lead to inefficient operations, misinformed decision-making, and a disconnection between social landlords and their tenants.
Turning The Picture Around:
Enhanced Decision-Making: High-quality and reliable data empowers housing officers, enabling them to make informed decisions based on accurate insights. By leveraging data analytics, organisations can reprioritise their existing workloads, identify tenants in need, and better allocate financial inclusion resources, leading to more efficient and effective services.
Improved Customer Experience: Access to enhanced and up-to-date customer data allows social landlords to personalise their services and address individual needs. With a deeper understanding of a tenant’s situation, organisations can tailor support, communication, and assistance to establish rapport and build stronger relationships.
Proactive Measures: Effective data management enables early identification of emerging hardship. By tracking patterns and analysing tenant data, organisations can promptly respond to issues such as rent arrears and maintenance requirements, well before they spiral, proactively safeguarding the well-being of their tenants.
Grasping the Opportunity:
Existing systems use outdated methods for organising and prioritising tenant data, and some, none at all. Consequently, this analysis is tedious and inconsistent, resulting in inefficiency and damaged tenant-organisation relationships. Thankfully, at Occupi, we can help.
Considering the endless possibilities for AI to enrich and enhance our lives, we knew there had to be a better way: An all-in-one platform that removes technical arrears, reduces a caseload by up to 40%, and uses a patterns and trends in customer data to identify when they are likely to need help.