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Quick answer: True cost per site for onsite IT support services adds five components for each location over 12 months: direct support spend, travel, site-specific vendors, allocated overhead and estimated downtime. With US private employers paying $46.89 per hour in total compensation (BLS, 2026), lost hours often outweigh the invoices.
Most companies know what they spend on IT in total. Few know what it costs to support any individual location. That makes basic questions hard to answer: Which sites are unusually expensive? Is that remote office costing more than it should? Would preventive visits pay for themselves? Should we keep a local vendor or move to one provider?
Cost per site is the metric that answers them. For multi-location IT support teams in law, financial services, banking, real estate and retail, it turns one large IT budget into a set of location-level numbers you can compare, explain and improve. This guide shows how to calculate it with data you likely already have, how to read the results and what to do about the outliers.
Five components make up a complete picture. Leave one out and the expensive sites will look cheaper than they are.
| Component | What to include | Where to find it |
|---|---|---|
| Direct support spend | Onsite IT support services invoices, internal staff time at or for the site | Provider invoices, timesheets, tickets |
| Travel | Internal staff travel to the site, mileage, lodging, trip charges | Expense reports, invoices |
| Site-specific vendors | Local IT vendors, circuits, equipment leases, maintenance contracts | Accounts payable |
| Allocated overhead | Share of help desk, tools and management time | Allocation by tickets or users |
| Downtime cost | Estimated lost productivity or revenue from outages | Incident records, ticket timestamps |
Hardware purchases can be included or tracked separately. Many teams track them separately so cost per site reflects support rather than refresh timing. If you do include hardware, spread it over its expected life rather than booking it in the year it was bought, or a site that got new switches will look like a problem when it is actually the opposite.
Pull 12 months of data. A full year smooths out seasonal peaks, one-off projects and the occasional bad month.
If spend is not coded by site, start coding it now. Even three months of clean data is more useful than a year of guesses. Requiring a site code on every work order and purchase approval is the simplest fix. See approval workflows for on-demand IT work.
For each site, add three numbers:
Fully loaded cost matters. Wages are only part of what an employee costs. BLS data shows that benefits made up 30.0% of private industry compensation costs in June 2026 (BLS, 2026). Use your own payroll figures where you can, but never use base salary alone.
Travel is easy to underestimate because time behind the wheel is not counted as support work. Count it anyway. The IRS raised the business standard mileage rate to 76 cents per mile from July 1, 2026 (CPA Practice Advisor, 2026). A 150-mile round trip costs more than $100 in mileage before you count a single hour of the technician’s time on the road.
Choose a simple, defensible allocation method and use it consistently:
Overhead includes help desk costs, monitoring and ticketing tools, and IT management time spent on site-related work. Ticket share rewards well-run sites and highlights noisy ones. User count is more stable and easier to explain to finance. Whichever you choose, write it down so next year’s numbers are comparable.
For each outage:
Keep assumptions conservative and document them. Not every employee is fully idle during an outage, so many teams apply a productivity loss factor (for example, 50%) rather than assuming zero output. The point is a defensible estimate, not a dramatic one.
Pay attention to cause as well as cost. Nearly 40% of organizations have had a major outage caused by human error in the past three years (Uptime Institute, 2025). At remote sites, that often means an undocumented change, a mislabeled cable or an unplugged device. Runbooks and good documentation lower downtime cost directly. Our post on the hidden cost of IT downtime at scale covers estimation methods in more depth.
Raw totals favor small sites. Normalized metrics let you compare a 10-person branch with a 200-person regional office.
| Metric | Formula | Use |
|---|---|---|
| Cost per site | Sum of all five components | Absolute comparison and budgeting |
| Cost per user at site | Cost per site divided by users | Compare sites of different sizes |
| Cost per ticket | Cost per site divided by tickets | Efficiency of support |
| Downtime share | Downtime cost divided by cost per site | How much outages drive cost |
| Travel share | Travel cost divided by cost per site | How much getting there drives cost |
Here is an illustrative example for two branch offices of a regional firm. The figures are made up to show the method; use your own data.
| Component (12 months) | Branch A (40 users, 20 miles from HQ) | Branch B (35 users, 180 miles from HQ) |
|---|---|---|
| Provider spend | $4,000 | $2,500 |
| Internal labor | $6,000 | $7,500 |
| Travel | $600 | $5,400 |
| Local vendors and circuits | $9,000 | $12,000 |
| Allocated overhead | $8,000 | $7,000 |
| Estimated downtime | $3,000 | $14,000 |
| Total cost per site | $30,600 | $48,400 |
| Cost per user | $765 | $1,383 |
Branch B is not more expensive because of its invoices. It is more expensive because staff drive three hours each way, fixes wait for the next available trip, and outages last longer as a result. Travel and downtime together are 40% of its cost. That points to a clear fix: local technicians for break/fix and a scheduled visit to address recurring issues, rather than more internal trips.
Group sites by type (large office, small office, retail store, warehouse, clinic, branch) and compare within groups. A warehouse and a law office will never have the same cost profile. Within a group, look for:
| Signal | Likely cause | Response |
|---|---|---|
| High downtime | Aging equipment, no redundancy, no spares | Preventive work, spares on site, backup connectivity |
| High travel | Internal staff driving to remote sites | Use local on demand IT support technicians |
| High vendor costs | Expensive or overlapping local IT vendors | Consolidate vendors. See vendor consolidation |
| High ticket volume | Poor site readiness, recurring user issues | Site readiness work and scheduled visits |
| High return trips | Weak intake, missing parts or no runbooks | Improve intake, ship parts ahead, document the site |
Network closets are a frequent root cause behind the first and last rows. A messy closet with unlabeled cables turns a ten-minute swap into a two-hour trace. Onsite IT network services that clean up and document network closets and IDFs often pay back through shorter outages and fewer repeat visits.
Onsite IT support services with local technicians cut travel, scheduled visits reduce downtime, and one provider can replace several expensive local vendors. Fast IT technician dispatch shortens outages at remote sites because nobody waits for the next internal trip. Track cost per site before and after changing your onsite IT support services to prove the impact.
Techmate works with 7,000+ vetted technicians across 450+ US cities, with a 97% resolution rate and a 4.7 out of 5 CSAT. See how Techmate dispatch works and what a field technician does for how local onsite work fits into your process.
Cost per site turns IT spending into something you can manage location by location. Combine direct support, travel, vendors, overhead and downtime, normalize by users and tickets, compare within site types and act on outliers. It is one of the most useful numbers a multi-site IT leader can have.
Techmate helps multi-site organizations lower cost per site with onsite IT support across 450+ US cities. Contact us.
Add direct support spend, travel, site-specific vendors, allocated overhead and estimated downtime cost for each site over 12 months. Then divide by users and tickets so sites of different sizes can be compared. Use fully loaded labor rates and a consistent allocation method so the numbers hold up with finance.
Provider invoices, internal labor at fully loaded rates, travel time and expenses, local vendors and circuits, a share of help desk and tools, and estimated downtime. Hardware can be included if it is spread over its useful life, but many teams track it separately so the metric reflects support rather than refresh timing.
Use a simple method such as share of tickets or share of users, applied to help desk, tools and management costs. Ticket share highlights noisy sites, while user count is steadier and easier to explain. A blended method works too. The key is to document it and keep it the same each year.
It can be, but many teams track hardware separately so cost per site reflects support rather than refresh timing. If you include it, spread each purchase over its expected life. Otherwise a site that just received new switches or laptops will look like an outlier when it is actually lower risk.
Common reasons include aging equipment, lack of redundancy, long travel to remote locations, expensive local vendors, poor site readiness and weak documentation. Breaking cost into its components shows which one is driving the total, which tells you whether the fix is preventive work, local technicians, vendor consolidation or better runbooks.
Target the biggest component first: preventive work and spares for downtime, local on-demand technicians for travel, vendor consolidation for vendor costs, and better readiness and runbooks for tickets and return trips. Measure cost per site again after six to twelve months to confirm the change worked.
It varies widely by site type, size, distance and risk, so a single benchmark is rarely useful. Calculate your own baseline across all locations, compare within site types, then price onsite IT support services options against that baseline to see where outside help lowers total cost.
Want a second set of eyes on your numbers? Book a free 30-minute IT support audit and we will walk through your cost per site data and where onsite coverage could bring it down.