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AppWork Maintenance Insights: Key Data to Drive Multifamily Operations

April 24 Multifamily Maintenance Data

In the multifamily housing industry, efficient maintenance management is crucial for tenant satisfaction and operational success. At AppWork, we're committed to providing actionable insights to help property managers and maintenance teams excel. We've aggregated real-time usage data from our platform to offer valuable benchmarks and trends that can inform decision-making across the industry.

Most Common Work Orders

Understanding the most frequent maintenance issues can help teams prioritize and allocate resources effectively.

HVAC > No A/C: The top spot goes to HVAC-related issues, specifically the non working air conditioning. This highlights the importance of HVAC system maintenance and readiness, especially during peak seasons.

Plumbing > Drainage Issue: Plumbing problems, particularly drainage issues, come in second. Proper plumbing maintenance can prevent costly water damage to the impacted unit and the surrounding units.

Most common work orders

Emergency Work Orders

Emergency situations require immediate attention. Our data shows that emergency work orders make up 6.67% of all work orders processed through AppWork. This underscores the need for preparedness and quick response times in maintenance operations.

Callback Rates

Reducing callbacks is a key performance indicator for maintenance efficiency.

Overall Callback %: 2.01% Average Callback % per Technician: 0.74%

Most Common Work Orders Called Back:

HVAC > No A/C: The most common callback issue is still related to HVAC, emphasizing the need for thorough initial diagnostics and repairs.

Pest Control > Roaches: Pest control callbacks rank second, indicating the importance of effective and lasting pest management solutions.

Work Order Callbacks

Work Order Saturation

Work order saturation, calculated as the number of open work orders divided by the number of units, stands at 5.98%. This metric can help teams gauge workload and capacity, ensuring that maintenance teams aren't overwhelmed and as an overall metric to the properties performance. The industry typically considers work order saturation of 10% or less to be acceptable with sites 5% or less to be doing exceptional.

Work Order Saturation

Completion Times

Efficiency in completing work orders is vital for resident satisfaction and operational flow.

Average Work Order Completion Time: 3.88 Days (From creation to completion) Average Technician Completion Time: 2.61 Days (From assignment to completion)

Fastest and Slowest Categories Fastest: General > Locked Out (indicating quick resolution times for lockout situations) Slowest: HVAC > Kitchen Exhaust Not Working (highlighting potential challenges in repairs)

Rapid Response and Volume

% of Work Orders Completed Within 24 Hours: 66% Average # of Work Orders Completed by Techs Each Month: 109.5 Average # of Work Orders Completed by Techs Each Year: 1,314

Resident Ratings

Maintaining high-quality service is paramount, as reflected in our average ratings:

Average Technician Rating: 4.2 Stars Average Vendor Rating: 3.6 Stars

In-House vs Vendor Work Orders

% of Work Orders Completed In-House: 93.14% % of Work Orders Completed by Vendors: 6.86%

Work orders completed in house vs vendors

By leveraging these insights, multifamily property managers and maintenance teams can make informed decisions, optimize workflows, and enhance tenant satisfaction. At AppWork, we're here to support your maintenance management journey with data-driven solutions. Stay tuned for more updates and insights to help you excel in the multifamily industry!

AppWork is a revolutionary multifamily maintenance management software designed to streamline operations, enhance efficiency, and improve tenant satisfaction. Our platform empowers property managers, maintenance teams, and vendors with innovative tools and actionable insights to tackle maintenance challenges effectively. Visit us online at or me directly ( to learn more.

Disclaimer: It's essential to note that this data is generalized and not broken down based on asset type, age, geographic location, size, etc. Variations may occur based on how each company utilizes AppWork.