Managing maintenance for multifamily residential assets presents unique opportunities to operate more efficiently, regardless of whether you have dedicated maintenance teams assigned to each property or not. Operational inefficiencies such as ineffective contact centers, technicians with insufficient information, and repeated attempts to solve the same lingering problem all hurt profitability and erode resident satisfaction. But just as minor inefficiencies can contribute to a struggling operation, minor efficiencies can add up to a successful and profitable portfolio.

Aided by robust data tracking and analytics and AI, property management teams can identify and detect problems early, optimize processes, and better develop institutional knowledge to keep properties running smoothly. By leveraging the right AI and data-driven platform for automating maintenance, property management teams can rack up the many minor efficiencies that generate major success.

Small Repeated Problems = Huge Cost

Maintaining distributed properties is complicated. Each dedicated maintenance team must understand their property's unique needs and be equipped with the tools and data to resolve tickets as efficiently as possible.

Failing to solve problems efficiently creates considerable overhead. In such a situation, every minor oversight or error takes up more of a technician or even a team's time, making every ongoing operational inefficiency a drain on ROI. Not only is each successive failed attempt to complete any task a waste of time and resources, it also makes residents question the effectiveness of the maintenance team's overall ability to keep property maintained.

If repeated attempts to fix the same problem become a regular occurrence, the property management team faces an in-grown operational problem that will lead to significant losses over time, while eroding resident satisfaction. And maintaining a property while failing to gather useful data about its unique needs puts too much pressure on team members to maintain institutional knowledge.

No silver bullet

There is no single solution for fixing maintenance operations. Instead, replacing inefficiencies with efficiencies creates an overall upward trend in effective maintenance that creates a significant reward for multiple, small changes. These changes can best be implemented through AI and data-driven automation, making these efficiencies seamless and second nature to any property management team.

AI and data-driven automation directly counter the minor inefficiencies that compound to make distributed properties difficult and costly to maintain. By aggregating and analyzing performance data, these systems isolate any recurring hiccups and automate the processes that counter and eliminate problems. Rather than performing a long auditing process and still potentially missing key issues, AI systems can pinpoint all existing snags and immediately implement best practices to smooth and refine operations.

Inefficiency to efficiency

Take for example the case of the poorly handled maintenance ticket. If the resident or dispatcher doesn't offer the correct information, an on-site technician sent out to address a ticket will need to spend time diagnosing the true source of the problem. If they don't correctly find the source, they may end up not solving anything at all, and will need to be dispatched again to complete the job.

Suddenly, a task that could have taken a morning takes up a whole workday or more. Meanwhile residents grow more frustrated as seeing the same team members struggle to keep a property maintained does not instill occupants with confidence.

At every step, an AI-powered, automated maintenance platform solves these problems. AI-driven chat over phone or text can gather more useful information for the technician, and a data-driven system can extrapolate the likely source of the problem and its most effective solution. The chance of a single maintenance ticket turning into two, three, or more drops dramatically, making team members much more effective in their jobs. This in turn dramatically raises resident satisfaction.

Data and best practices

Data driven AI powered systems can stabilize and create efficiencies in maintenance processes, reducing the reliance upon institutional knowledge. Without a data-centric approach, individual team members become responsible for knowing the ins and outs of their building. This means veteran employees are more likely to troubleshoot and solve problems the first time, and must then teach new hires all these nuances. And considering most maintenance personnel only spend 6 months on average at one job, experienced personnel can be hard to come by, spiking the chances of mishandled maintenance attempts significantly.

Efficiency is thus about more than just each individual ticket — it's about letting an AI-driven system collect and analyze data to develop and maintain a nuanced understanding of each property, so that property's maintenance team doesn't have to. With an AI-powered chat system gathering the appropriate data (and using machine learning to ask better questions over time,) an analytics-powered system can determine the most likely cause and best repair procedure for any maintenance ticket.

While every property's team members eventually learn their assigned property's specific needs, the automated system keeps an ever-evolving picture of those needs on file, so that not only is institutional knowledge never lost, best practices are always improving and adapting. Technicians can always do their best work, regardless of who is on the clock that day.

Upward trajectory

Most importantly, switching to an automated system keeps these efficiencies consistent and reliable. Results don't improve for one ticket, or one day, but for every ticket, every day. This results in the kind of bankable upward trajectory that eliminates the challenges of a distributed property portfolio.

As team members perform their tasks more effectively day by day, properties not only remain in better repair and cost less to maintain, but resident satisfaction continually improves, as does the overall reputation of all properties. By adopting an AI-powered, data-driven maintenance automation platform, property managers overseeing distributed assets can turn a challenging portfolio into a well-oiled machine for generating ROI.