Ancoris Maps for Housing is a web application that empowers housing associations to reduce costs, improve operations and enhance tenant satisfaction. It works with major housing systems, visualise the data on Google Maps and makes it accessible to everyone in the office and in the field.
Improve officer productivity
- Assign optimum geographic areas and improve patch working.
- Improve travel planning and increase the number of daily tenant visits that officers can make.
- Access all housing information in one place on a map and improve time management.
Example: Estate officers can access live information and filter that status of rent arrears for their assigned properties on a map. This displays their schedule of visits and automatically suggests the optimum route.
Reduce rent arrears and increase revenues
- Visualise information to allow proactive action to prevent arrears
- Proactively plan and visit tenants at risk of rent arrears
Example: Directors visualise all rent arrears along with any agreement in place, court action or universal credit and spot trends and patterns in the data. They layer demographic data for greater context. A course of action is agreed, such as running campaigns in hotspots and working with tenants to improve their situation.
Ensure gas safety checks are valid and SLA’s met
- Proactively visit tenants when in the close vicinity and gain timely access
- Identify location patterns and trends and take proactive action to avoid lapsed checks
Example: Estates officers filter gas safety checks on a map to identify those that are invalid or about to lapse They access this information when they are in the field and visit properties nearby there and then.
Ensure repairs are done on time and SLAs met
- Allocate maintenance crews based on location and optimise job routing with live traffic information and estimated times of arrival.
- Identify location patterns and trends.
Example: Jobs are allocated to maintenance and repair crews based on the job location, the crew operating area or even live location. Information on areas that are underperforming are analysed so that action, such as appointing additional crews to an area, may be taken.
Reduce void housing
- Identify single or cluster of voids and take remedial action.
- Fill void properties quickly with appropriate tenants.
Example: The use of heat and clustered maps to visualise all void properties, past and present, identifies a trend in the data. The analysis is run against demographic data to give it greater context and highlights an area of high voids. This will help plan for future housing stock, potentially selling properties in that area and planning new builds in areas with higher demand.
Improve customer service and satisfaction
- Match tenants’ personal needs to local areas.
- Provide prospective tenants with relevant information so they can make quicker and better informed decisions.
Example: A family with two young children would ideally like a home within walking distance of a primary school and close to a play area. The ability to layer the information on available homes with additional local data means this can be visualised easily within the application. There is no need to search multiple sources.