How to Forecast MSP Hiring Needs Using Device Growth Trends

One of the most important tasks for managed service providers (MSPs) is scaling staff to match client growth. However, it’s also one of the most difficult, as failing to hire enough people at the right time can lead to overworked teams and lower-quality services, while hiring too many too early can strain budgets and leave staff without enough meaningful work.

Instead of relying on gut feeling, waiting for teams to become overwhelmed with duties, or reacting once teams are overworked or underutilized, use device growth trends to forecast MSP staffing needs. Keep reading to learn the steps for proactively planning personnel hiring.

How to use device growth trends to predict MSP workforce needs

Forecasting MSP staffing needs should start with measuring device growth to turn the task from reactive hiring to a forward-thinking one. Doing so should help anticipate capacity limits, align recruitment with business cycles, and demonstrate that service delivery is scaling with demand. Follow the steps below to start using this strategy.

📌 Prerequisites:

• Reliable Remote Monitoring Management (RMM) or Professional Service Automation (PSA) data for device counts, technician tickets, and SLA metrics
• Defined benchmarks and baselines (such as devices per technician, average ticket load per device)
• HR and finance alignment on hiring lead times and onboarding cycles
• Documentation and reporting tools (for example, Excel, Power BI, NinjaOne Documentation) for forecasts and hiring plans
• Quarterly review cadence for adjusting staffing forecasts

Step 1: Define technician-to-device ratios

Before forecasting hiring needs, you need a baseline that links technician capacity to device counts. This ratio will objectively measure how much workload each of your technicians can realistically handle and help you predict staffing demand.

The industry average ranges from 250 to 350 endpoints per technician. However, you can adjust this ratio based on the following factors:

• Client complexity
  • Regulated industries (such as finance or healthcare) with IT compliance standards often require tighter ratios.
  • Mixed environments with legacy systems increase technician workload.
• Automation coverage
  • High levels of automated patching, monitoring, and remediation allow technicians to support more devices.
  • Low automation adoption reduces efficiency and pushes ratios downward.
• Technician skill levels
  • Senior technicians may manage higher device counts than new hires.
  • Balanced workloads prevent over-reliance on top performers.

By the end of Step 1, you must have a technician utilization model customized to your environment, outlining:

• Devices per technician baseline
• Adjustments by client segment or environment type
• Impact of automation on workload

Step 2: Track device growth trends

The next step is to measure how client environments are growing. Tracking device growth trends can help you anticipate future workload demands and make predictions based on real data rather than assumptions. To do this, you need to:

• Export device inventory reports: Pull device counts from your RMM regularly (monthly or quarterly).
• Calculate growth rates: Compare quarter-over-quarter or year-over-year increases in total devices.
• Segment by device type: Separately break down laptops, servers, SaaS endpoints, and mobile devices, as different device classes usually have different support demands.
• Spot high-growth clients: Identify accounts with outsized expansion and flag them for early staffing discussions in QBRs.

By the end of Step 2, you should have a device growth dashboard showing:

• Trend lines over time
• Breakdowns by device type and client segment
• Growth hot spots that may accelerate hiring needs

Step 3: Forecast technician demand

Now, determine when technician capacity will be reached so you can plan hiring before employees reach their limits. To forecast the demand:

• Apply your technician-to-device ratio to projected growth data to estimate the number of technicians required.
• Model different scenarios, including:
  • Baseline growth: Normal expansion pace based on historical averages
  • Accelerated growth: Faster client onboarding or new verticals
  • Churn or contraction: Client loss or reduced environments that may slow hiring needs
• Identify when staff will reach capacity by marking the month or quarter this occurs, and compare it against the current headcount for a clear forecast.

By the end of Step 3, you should have a staffing forecast chart showing:

• Current vs. projected technician demand
• Timeframes when additional headcount is needed
• Multiple scenarios to account for uncertainty

Step 4: Integrate hiring lead times

It’s important to include hiring cycles in staffing forecasts, as recruiting, onboarding, and training technicians require significant lead time. To prevent service delivery gaps, you want to ensure you anticipate the need for new staff before technicians exceed their capacity thresholds. Integrate lead times by doing the following:

• Map average hiring cycles: Work with HR to document typical timelines (for example, 2-3 months for recruiting, plus onboarding).
• Overlay hiring timelines on forecasts: If capacity will be exceeded in Q3, hiring must start in Q1 or Q2.
• Build hiring checkpoints: Review forecasts quarterly and set “trigger points” for when hiring processes must begin.
• Account for training and ramp-up: Include additional time for new hires to reach full productivity, especially in complex environments.

By the end of Step 4, you should have a hiring timeline overlay that connects device-driven staffing forecasts with actual recruitment cycles. This will ensure that hiring plans align with real-world timelines, prevent last-minute recruitment, and maintain consistent service quality.

Step 5: Present forecasts in business terms

Lastly, you must translate technical data into terms that resonate with leadership, HR, finance, and clients. Decision-makers only respond to things that can impact business, like risk, cost, service quality, not terms like device counts and ticket loads. Make sure you focus on clear, business-focused communications by doing the following:

• Use plain business language, such as:
  • “Device growth will exceed technician capacity in Q2 2025.”
  • “At 15% growth, we need one additional technician per 1,000 devices annually.”
• Highlight risks and impacts like:
  • SLA breach probability
  • Technician burnout risk
  • Potential client dissatisfaction or churn
• Show costs vs. value by comparing the cost of new hires against avoided SLA penalties or client loss.
• Make it visual using charts, dashboards, or capacity overlays that leadership can easily interpret.

By the end of Step 5, you should have a leadership-ready hiring justification report, client-facing slide, or QBR talking point that ties staffing needs directly to business outcomes, not just technical MSP metrics.

Summary table of steps and value

Here’s a quick rundown of all the steps mentioned and the value they offer for MSPs.

NinjaOne integration

NinjaOne offers various capabilities that can help MSPs streamline the process of translating device growth into actionable staffing forecasts.

Turning device growth into a workforce roadmap

Forecasting MSP hiring through device growth trends is an effective strategy for ensuring service delivery scales appropriately with client growth. The steps mentioned can help you anticipate workforce needs accurately while preventing technician burnout for workload planning.

Ultimately, you’ll have a repeatable framework that aligns staffing with your clients’ operational demands.

Related topics:

• A Killer Recruiting (and Sales) Tactic for your MSP
• IT Recruitment Guide for Help Desk
• Beating the Talent Shortage: How to Hire and Retain IT Employees Better Than Your Competition [PDF]