How RepairSense’s Unique Approach to Damp & Mould Management Can Save Your Team Hours Every Week
Damp and mould are persistent issues in social housing, requiring fast, effective responses to protect tenant health and maintain housing stock. However, traditional reactive maintenance approaches often lead to repeat repairs, inefficient scheduling, and excessive resource use. With the introduction of the Tenant Satisfaction Measures (TSMs) under the Social Housing (Regulation) Act 2023 and the upcoming enforcement of Awaab’s Law in October 2025, social landlords must now prioritise proactive damp and mould management.
Mobysoft’s RepairSense Damp & Mould Module provides AI-powered damp and mould solutions that save housing providers hours every week by streamlining repair processes, reducing repeat jobs, and optimising resource allocation. Here’s how…
Proactive Damp & Mould Management: The Key to Efficiency
Traditional repairs often focus on speed rather than long-term resolution, leading to a cycle of repeat fixes. The RepairSense Damp & Mould Module takes a predictive maintenance approach, using AI-driven insights to identify high-risk properties before problems escalate.
By analysing historical housing repairs data, the module allows maintenance teams to:
- Identify properties prone to damp and mould before tenants report issues.
- Prioritise repairs based on severity, preventing minor cases from escalating into major health risks.
- Reduce avoidable repair requests, freeing up resources for urgent cases.
This results in a more efficient use of time and personnel, ensuring compliance with TSM RP02 (repairs completed within target timescales) while reducing long-term costs.
Eradicating Repeat Repairs Jobs with AI in Property Maintenance
Repeat repairs drain resources and contribute to tenant dissatisfaction. Many social housing providers focus on quick fixes rather than addressing the root cause, meaning the same problem resurfaces repeatedly.
The RepairSense Damp & Mould Module leverages AI and machine learning to:
- Detect patterns of repeat repairs.
- Flag unresolved issues before they become complaints.
- Provide a comprehensive damp and mould history for each property, ensuring operatives have full context before attending a job.
By ensuring issues are resolved correctly the first time, social landlords can improve TSM TP02 (satisfaction with repairs) and TSM TP03 (satisfaction with time taken to complete most recent repair), ultimately reducing tenant complaints and increasing trust in the housing provider.
Optimising Scheduling and Resource Allocation
Managing a damp and mould caseload is time-consuming, especially when dealing with urgent repairs and compliance requirements. The RepairSense Damp & Mould Module streamlines housing repair processes by:
- Automatically prioritising cases in order of severity.
- Flagging jobs that fall out of due process, ensuring no cases are missed.
- Tracking the status of all damp and mould repairs in a single dashboard, reducing admin time and improving team efficiency.
With better scheduling, maintenance teams can complete repairs faster, reducing backlogs and ensuring quicker response times for tenants. This supports TSM TP04 (satisfaction that the home is well maintained and safe to live in) while also helping landlords meet the strict timeframes mandated by Awaab’s Law.
Enhancing Compliance and Tenant Satisfaction Measures
With regulatory changes placing greater scrutiny on social landlords, having robust damp and mould risk assessment tools is essential for demonstrating compliance. The RepairSense platform provides a full audit trail of repair jobs, ensuring landlords can:
- Easily evidence compliance with Awaab’s Law and other regulations.
- Show clear records of when damp and mould investigations began and when repairs were completed.
- Monitor tenant satisfaction trends and address concerns proactively.
By proactively preventing complaints and ensuring repairs are completed effectively, landlords can improve TSM TP05 (satisfaction that the landlord listens to tenant views and acts upon them).
Cost Savings Through Predictive Maintenance in Housing
Beyond saving time, implementing AI-powered damp and mould solutions leads to significant cost reductions. By tackling damp and mould issues before they escalate, landlords can:
- Reduce the volume of emergency repair requests.
- Extend the lifespan of housing stock through better maintenance.
- Lower legal costs associated with disrepair claims and tenant complaints.
These efficiencies make a strong financial case for adopting AI in property maintenance, allowing housing providers to reinvest savings into further service improvements.
The Bottom Line
The RepairSense Damp & Mould Module transforms damp and mould management in social housing by providing predictive insights, streamlining repair workflows, and reducing repeat jobs. With compliance pressures increasing under Awaab’s Law and the Tenant Satisfaction Measures, social landlords need a robust, proactive solution to manage damp and mould efficiently.
By adopting AI-driven housing repairs data analytics, social housing providers can save hours every week, enhance tenant satisfaction, and ensure long-term sustainability in their repairs and maintenance operations.
To find out more about how RepairSense can help your organisation use data to drive efficiencies within its repair and maintenance operations and manage resources more effectively, watch our short RepairSense overview video.
