Why enterprise IT complexity is growing faster than headcount and what to do about it

When every user only needed one desktop computer, per-device IT software pricing made a lot of sense. Now, multiple endpoints per user has changed the calculus for IT leaders, especially as technician hiring has stayed flat. It’s time to shift how you think about pricing to better tackle enterprise IT complexity.

How many devices does one business user need? The answer keeps growing, from one desktop computer 20 years ago to three or more these days. Laptops, mobile devices, smart watches, printers, and more have all combined to overwhelm IT teams supporting all these endpoints.

SaaS licenses per user also keep increasing. The software as a service (Saas) market is busy and growing, with the global SaaS market projected to grow at an 18% CAGR rate through 2032.

Hiring budgets, though, are not showing that kind of growth. Overall, aggregate IT spending continues to grow, but spending on new head count isn’t growing proportionally. IT decision makers are working to reduce excess spend under pressure from leadership to work more efficiently and strategically. A Spiceworks survey found that 31% have implemented a hiring freeze or slowdown as part of operational efficiency goals.  

Why the linear per-device staffing model is breaking

Traditionally, the IT staffing model was pretty linear: one user needed one desktop computer, so each new user would generate more help desk tickets, which led to the need to hire more technicians. 

Enterprise IT teams now handle much more than one computer per user. The perimeter has expanded even over the last decade, so that now each user might have a laptop, smartphone, home office router, tablet, and other devices. It’s scaled in a non-linear way, but the same lean IT teams still have to support users across all those potential endpoints.

Hiring in the old linear, one-device-per-user way is now unsustainable for most businesses. The cost of human labor hours to handle these new volumes quickly eats into corporate margins. This widening device-to-technician ratio won’t be solved with linear hiring.

For example, take Trapp Technology — the IT service provider manages 140,000 endpoints across its 2,500 clients, with endpoints ranging from end user workstations to server infrastructure. Before adopting Atera, the company saw high operating costs without a clear return on investment (ROI). In-house enterprise IT teams might not be managing this number of clients, but the endpoint explosion affects teams across all industries and business sizes.

Trapp adopted Atera for a per-technician pricing model, allowing them to manage unlimited endpoints without adding costs. The AI and automation features helped to deploy common tasks and fixes quickly, such as patch management, software deployment, and infrastructure monitoring. Trapp can tailor monitoring by client needs as well. More headcount wasn’t the logical fix, but a structural change to the pricing model helped add predictability and true scalability.

How to calculate your own staffing model ratio

The first step toward understanding how to tackle your own growing complexity is to calculate your team’s staffing model ratio based on device per technician. Once you assess where you fall in this ratio, you can understand the structural economics involved and the resource capacity of the current team, then decide what to optimize to best support the IT team’s work. 

Step 1: Determine how many hours each device requires per year, or estimate based on number of endpoint tickets multiplied by average time per ticket resolution, to get the time per device number.

Step 2: Add in any particular complexity according to your business, or remove it. For example, a good RMM solution allows your technicians to support more endpoints, since they can take advantage of the always-on device monitoring. But a complex environment with legacy apps, varying access policies, bring-your-own-devices, and other factors can require a lot more work and time per endpoint.

Step 3: If you don’t already have this data, isolate the number of hours a technician spends solving tickets across the same time period as step 2. 

Step 4: Divide the technician’s hours by the time per device to get the endpoint-to-technician ratio.

Step 5: See how your business compares to industry benchmarks and adjust accordingly. Anywhere from 250 to 500 endpoints per technician can be considered standard, depending on  RMM and automation technology use.

Focus on licensing models, not hiring plans

If you’re seeing a constant ticket backlog and slow MTTR numbers, you likely want to adjust the IT staffing ratio for the team. Instead of reevaluating your hiring plan, first evaluate the licensing and platform models of the team’s software. How are licensing fees calculated, and does that model match how your business runs? 

If you’re still paying for help desk and monitoring software per-device, consider whether a per-technician model is a better fit. Business growth doesn’t have to be so expensive with a per-technician model, particularly if users each require multiple endpoints. Per-technician pricing keeps the focus on efficiency, TCO, and bottom-line business results, plus brings stability to IT budgeting. Atera’s RMM and help desk ticketing software helps IT teams to monitor servers, workstations, and other devices all within the same pricing model.See how Atera’s pricing model works and what option is best for your team.