ServusConnect Blog

5 Keys to Unlocking The Potential of Multifamily Maintenance Data

Mar 8, 2019 1:52:00 PM / by Jamie Wohlschlegel

Read Time: 8 minutes

As much as multifamily has become data-driven, there are a few major areas of operation that still operate in the dark from a data perspective.

 

Multifamily Maintenance Operations is one of them.

 

The reasons why vary, but the primary one seems to be centered around the fact that maintenance is a hands-on operation, performed in the field, and capturing good field data is hard. This is fueled by a common industry misconception that maintenance personnel are not capable of using technology to enable more accurate capture of repair data.

 

This could not be further from the truth! There is a ready and willing workforce that is well positioned to turn a light onto a new subset of data that will fuel the next transformation in multifamily operations.

 

Maintenance data is a hidden gem and here your 5 Keys to Unlocking The Potential of Multifamily Maintenance Data:

 

Key #1. Get Rid of Paper & Go Mobile

A shockingly large percentage of multifamily operators still print out work orders and manually distribute them to their maintenance teams. Not only does this contribute to a large amount of wasted motion retrieving and keeping track of these documents throughout the lifecycle of service requests, realistically paper is not the ideal medium to capture repair data. Lost papers, dirty hands, bad handwriting, spilt coffee, little context...it's kinda like your teenage son's homework!

 

And then there is the bane of every management offices' existence - doing closeouts/filing on a pile of completed work orders. Regardless of what is written on the paper, the only thing that makes it back into the system is, "work completed".

 

No wonder maintenance data is terrible!

 

Getting rid of paper and going mobile with maintenance is critical and the first step to unlocking the potential of maintenance data. Between the ubiquity of smartphones and the prevalence of unlimited data plans by all of the wireless carriers, your maintenance team members are already carrying the necessary tool in their pocket.

 

As far as the paperless mobile work order is concerned, your existing property management software may have basic mobile capabilities that can be leveraged - this is a great start. It they don't cut it, or your existing system doesn't offer this capability, solutions like ServusConnect specialize in multifamily maintenance and mobility. These provide higher-fidelity features & reporting, along with integration with other systems - even end-user support & training, which makes deployment much easier.

 

Your key objective here is to get good field data using a mobile app that is simple for your team members to use. Ideally, your mobile maintenance app will automatically capture incremental timestamps from field technicians such that service cycle times, and are depicted accurately.

 

A major bonus would be the ability to capture additional electronic documentation like photos, videos and timestamped technician comments that help capture repair details and form a storyline that might be helpful later in the event of a dispute.

 

Key #2: Categorize Early & Often, But Don't Over-Do It!

If mobility is the key to collecting maintenance data, categorizing is the key to sorting it. Different software vendors call this different things (at ServusConnect we refer to this as "tagging"), but just think of it as different buckets you want to associate each work order to that make them easier to search for and analyze later.

 

ServusConnect SR tagging

 

Your categorization methodology is analogous to your chart of accounts in accounting. Better categorization leads to better reporting and improved analytics, just as accuracy in cost-center allocation leads to tighter expense management and forecasting. And, as managers, we want as much granularity as possible, right?

 

Not so fast my friend!

 

The issue here comes down to the team members doing the categorization. They are often leasing or maintenance office personnel, which, happen to be high-turnover positions. Essentially consistency & training can be an issue.

 

If given too many options, they will categorize too specifically; or maybe not at all because they are overwhelmed or unsure. In both instances, the opportunity for inaccurate categorization is highly likely and significantly handicaps your ability to generate meaningful business insights from large aggregated data-sets later on.

 

We'll discuss an ideal service request categorization model in a future blog post, but in general, keep your options simple and high-level such that an untrained person, maybe even the resident, could logically categorize correctly. For example:

 

  • Type: Occupied or Unoccupied
  • Severity: Emergency, Urgent, Normal
  • Category: Electrical, HVAC, Plumbing, Cleaning, Flooring, Paint, Drywall, Appliance, Pest Control, Misc

 

Again, these are just examples - you may have more or less based on maturity or if you are trying to specifically track something in your portfolio. Auto-categorization can also be used to streamline the user experience.

 

And don't worry so much about categorizing locations inside of units, such as "bedroom", "kitchen" or "bathroom". These values aren't really usable when looking at large aggregates of data, plus they likely exist already in titles and descriptions. In this instance, a more valuable query mechanism might be to isolate by a general category and then perform a keyword search to find what you are looking for.

 

Key #3: Don't Forget Your Vendors

An often overlooked, but significantly important element to unlocking the value of your maintenance data is including outside service vendors in your service request workflow. Data shows that the average multifamily property in the US outsources anywhere between 20-30% of all service requests to external service vendors.

 

Insist your staff create service requests for this work and treat it just as they would for on-staff maintenance team members. Higher fidelity multifamily maintenance platforms, such as ServusConnect, extend service requests to external vendors, providing them the same opportunities to digitally document their work as your on-staff team members.

 

"20-30% of total service request volume in multifamily are performed by outside vendors"

 

Major benefits come in the form of improved analytics of what type of work your properties are outsourcing, the volume at which it is happening on a week-to-week and month-to-month basis, vendor response times, time-to-invoice, etc. Over time, these will become one of your KPIs of overall property performance & maintenance-ops health.

 

Key #4: Resident Feedback Data Is Icing On The Cake

So you've gone mobile, simplified your categorization schema, are including vendors in your workflow...now it's time for the final piece: your resident maintenance survey data.

 

Including resident feedback/survey results in with your maintenance stats closes the loop from a data standpoint concerning a critical vector in assessing the true health of maintenance operations. Ie., how do your residents feel about each service experience.

 

ServusConnect Phone Resident Notification

 

Seriously, this is really important.

 

With much of the multifamily market adopting electronic resident services such as online rent payments and other self-service portals & apps, maintenance performance has become a critical aspect of resident satisfaction, and a major influencer in resident experience.

 

Take a quick scan of online property reviews for apartments in your area on Google Maps or elsewhere. Whether the reviews are good or bad, a high percentage of them mention maintenance as one of the main reasons they love or hate the place! (my sampling was around 75%)

 

There are direct correlations between service cycle times and resident sentiment when compared side-by-side. You'll also start to get a handle on what categories of maintenance illicit the most emotional responses. (hint: it's a toss-up between HVAC and bugs)

 

The results may end up being drivers for changes in, or creation of, specific SLA's with residents that can also be leveraged for marketing purposes. Clients have also found this correlation to be super helpful in identifying maintenance team members that would benefit from additional customer service training.

 

However you end up using it, keeping track of how residents feel about each service experience will become a critical KPI to assess maintenance-ops health.

 

Key #5: Don't Boil The Ocean With Reporting

Chances are most multifamily operators are capturing some baseline operational maintenance metrics beyond how the department is running against budget. A common one is open service requests over a certain number of days.

 

Once you implement these steps, not only will you start collecting more data, more quickly and accurately, it will become much more accessible because it is collected in structured formats directly from the field.

 

This is where it's easy to get into the weeds with data. Initially, focus on higher level optics like overall volume, volume by technician and then cross reference that with Service Cycle Times and resident survey results.

 ServusInsight Maintenance Dashboard

 

This, along with maintenance metrics you're already managing to, will start to create a more complete picture of site & portfolio operational health, as well as individual maintenance team member performance. (incidentally, this is a great baseline to start building maintenance technician incentive programs)

 

Monitor weekly over a few months and you'll start to see patterns emerge that you'll want to explore. The good news is that you'll already be collecting the data that you want to dig into!

 

If you have questions on data correlation in this space, please email us at info@servusconnect.com. We love maintenance data and have experimented with all sorts of ways to extract and analyze it - most importantly, we are happy to share our learnings!

Topics: technology, multifamily, apartments, operations, apps, data

Jamie Wohlschlegel

Written by Jamie Wohlschlegel