Industry News and Insights

How AI Can Improve Your First-Time Fix Rate

With the help of AI and automation, you can prevent unnecessary dispatches for your maintenance technicians, increase resident satisfaction, and improve NOI.


How often does your maintenance team dispatch a technician, who arrives at a unit only to find that they are not equipped to make the repair that day? According to industry benchmarks, this happens at least 20 to 30% of the time — even for highly efficient properties. For portfolios that lack a centralized maintenance team or digital processes for maintenance ticket intake, this figure is likely much higher.

Why Does First-Time Fix Rate Matter?  

Every time a technician needs to come back to a unit multiple times to make a repair, you are spending time on their travel and labor. Plus, when they are dispatched for a site visit without making a repair, they are effectively reducing the number of repairs that they can complete per day — reducing their efficiency.

Not to mention, residents feel the frustration of slow maintenance quickly. In a recent survey we conducted, renters who reported long wait times for maintenance tickets to be resolved were much more likely to be very dissatisfied with their property management company than those who saw quick fixes.

A high first-time fix rate (defined as the percentage of maintenance requests resolved successfully on the first visit) indicates a healthy portfolio with an efficient operations team, well-maintained units, and happy residents. A low FTFR, on the other hand, is a red flag that could lead to higher turnover rates, a worse company reputation, and, over time, a lower NOI.

How To Calculate Your Portfolio’s First-Time Fix Rate

First-time fix rate (FTFR) is defined as the percentage of maintenance requests resolved successfully on the first visit.

Use the following formula to calculate FTFR:

(Total Tickets Resolved on First Visit Per Month ÷ Total Monthly Tickets) × 100 = Monthly FTFR

 

How Can AI Improve a Property’s First-Time Fix Rate?

One of the primary causes of an unsuccessful maintenance dispatch is incomplete information. When tickets or work orders don’t include detailed information about the issue, the steps taken by the resident to attempt to resolve the issue, or photos, technicians often have no choice but to make one consultative site visit, and then to return at a later date with the proper tools. There are also many cases in which a technician is dispatched to make a repair that a resident could have done on their own with the proper guidance, like flipping a circuit breaker to fix a dishwasher that won’t turn on.

That’s where AI and automation–driven tools like ApartmentAdvisor ASSIST come in. When a resident submits a ticket, the ASSIST AI agent responds to them instantly with follow-up questions that help property diagnose, categorize, and prioritize the issue. Because residents are being engaged in the moments when their attention is most focused on the ticket, they are more likely to continue the conversation and provide the necessary details.

Our customers see, on average, over 70% of their tickets enhanced thanks to AI triage. Enhanced tickets include accurate details about the make and model of appliances, photos of issues, and AI summaries of steps already taken by tenants to help resolve issues. They give technicians a direct view into how to resolve an issue, improving FTFR and reducing unnecessary, consultative site visits.

Demo Environment - Ticket Summary with AI Comments - Unresolved Ticket

This is an example of an AI-generated ticket summary on ASSIST. 

Interested in Trying an AI Solution?

Are you interested in learning more about what an AI solution might look like for you and your residents? Fill out the form below to schedule time with our team.

 

 

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