The Maintenance Problem
Maintenance teams are under-resourced across the industry. Staffing shortages are driving delays in work orders, unit turns, and capital upkeep. This isn’t an isolated issue—it’s systemic.
Operators are relying on outdated models that no longer reflect the scale or complexity of modern portfolios. The result is rising resident churn, missed financial targets, and operational burnout.
The 1:100 Math: What’s Driving It
The “1 tech per 100 units” rule isn’t a benchmark—the rule of thumb is based on a supply standard that’s largely grounded in an onsite approach to maintenance.
Let’s break down the work 300 units demand:
6 work orders per unit/ year = 1,800 work orders
50% turnover = 150 unit turns
Unit turns average 16 hours = 2,400 hours
Work orders (2 trips × 45 min) = 2,700 hours
➡️ Total = 5,100 hours/year
➡️ One tech covers ~1,750 hours/year
➡️ Result: 3 techs needed = 1:100
But this doesn’t include:
Guest interaction
Cleaning and grounds keeping
Repeat supply trips
Half-done jobs broken by interruption
These invisible friction points compound until the system breaks.
Unless the model changes, burnout is inevitable.
Demand Is Up. Techs Are Down. Going Without Isn’t Working.
Increased demand + lower supply = operational risk.
Yet many operators are still choosing to “go without”—leaving roles unfilled and shifting budgets to temporary solutions like rent concessions, vendor bursts, or marketing spikes.
RealPage projects 500,000 units will come online in 2025. At a 1:100 ratio, we’d need 5,000 new techs. That workforce doesn’t exist.
Meanwhile, SLA targets remain at 48 hours for non-critical issues, yet average work order age sits at 17 days. Pencilling 1:100 with a centralized organizational model isn’t realistic or defendable.
You can’t solve systemic demand with temporary workarounds. You need an operating model that scales.
Org Models Designed to Scale
Decentralized (Onsite-Centric)
Dedicated techs per property
Strong property-level relationships
Vulnerable to absenteeism, redundancy, and variable standards
Networked (Floating)
Staff are deployed across sites by need
Centralized triage, QA, and routing
Great for structured tasks like inspections or complex tech work
Requires SOPs and technology for task assignment and tracking
Think of it like Omaha supporting Austin and Atlanta on Monday. Then Austin floats to cover the other two on Wednesday. The model is dynamic and resilient.
Centralized (Hub-and-Spoke)
Core operations run from a centralized location
Minimal onsite presence
High efficiency, ideal for automation and remote coordination
Cultural and change management investments are critical
Transitioning: From Decentralized to Centralized or Networked
This isn’t a switch—it’s a roadmap. Here’s how to make the leap:
1. Assess Your Starting Point
What roles are truly onsite? Where do we have unfilled roles?
How does the team spend most of its time?
Where is work getting stuck?
2. Define Your Target Model
Centralized = control, standardization
Networked = flexibility, expertise pooling
3. Start Small, Pilot a Region or Function
Pick one: turns, inspections, after-hours
Define a workflow and service level
Track performance and refine
4. Train and Iterate
Equip teams for new responsibilities
Clarify communication and accountability
Use dashboards and mobile tools to close feedback loops
Success isn’t hitting a ratio—it’s building an org that absorbs change and delivers consistently.
The Financial Impact: Why Org Design Drives NOI
Operations aren’t just back-office—they’re bottom-line.
Faster Turns = Less Vacancy Loss
Shrink downtime across units
Centralized or networked teams close gaps faster
Turnkey scheduling improves uptime
Quicker Repairs = Lower Churn
Faster diagnostics → fewer missed service promises
Shared support improves resolution time
Even 5% churn reduction drives major returns
Better Preventive Maintenance = Longer Asset Life
Standardized PM work saves on early replacements
Avoids deferred capital piling up
Fewer reactive tickets = fewer costly repairs
Predictable Ops = Smarter Budgets
Centralized models make vendor billing, labor distribution, and staffing levels visible
Fewer surprises = stronger forecasting
Strategic Use of Service Contracts
Some work doesn’t need to be kept in-house.
Major Equipment (HVAC, Elevators, Boilers)
Use manufacturer-aligned service contracts
Schedule inspections and seasonal servicing
Vendors often resolve faster, and with fewer re-visits
Site Services (Cleaning, Landscaping, Trash Rooms)
Offload predictable labor to fixed-scope providers
Free your techs to focus on reactive demand
Sync contract tasks with turn schedules to reduce overlap
These contracts create breathing room—and protect your in-house labor for the work that matters.
What Model Is Right for You?
Don’t aim for a staffing ratio. Design for real-world workload.
Ask:
What’s the actual shape of your maintenance demand?
What work could be routed, pooled, or outsourced?
Are you building a structure that can flex—or just survive?
The winners in this cycle won’t be the fastest to hire. They’ll be the ones who rethink how the work gets done.
