When operations managers ask about return on investment for voice automation, they usually want a single number. Something they can put in a spreadsheet, compare against a monthly subscription, and call it done. The honest answer is that the number depends entirely on inputs specific to your operation, and the calculation is not complicated once you know which inputs to use.
This piece works through the model. Bring your own numbers and the output is specific to you. The framework applies to any monitoring center evaluating a voice triage layer for overnight call handling.
The Three Inputs That Drive the Calculation
1. Overnight call volume
Start with your average inbound call count between 10pm and 7am on a typical weeknight. Most monitoring centers can pull this from their call logging system with moderate granularity. If you only have monthly totals, divide by 30 and estimate the overnight share. A typical ARC handling commercial accounts will see a disproportionate share of its false-alarm volume in the overnight window: HVAC cycles, temperature differentials triggering sensors, motion detectors in office buildings that nobody switched to vacancy mode before leaving for the weekend.
The overnight period is where the ratio of false positives to genuine events is highest, and where the cost of staffing to handle that volume is also highest. Both factors move in the same direction: the case for pre-screening is strongest precisely when and where the pain is greatest.
2. Your false positive rate for overnight calls
This is the percentage of overnight calls that close without any emergency services dispatch or confirmed incident. If you log call outcomes, you can calculate this directly. If you do not, a reasonable working estimate for a commercial-account-heavy portfolio is somewhere in the range of 80 to 92 percent. The national-level data from police and fire services on unnecessary dispatch activations consistently falls in that range for alarm-triggered callouts.
The false positive rate is important because it determines how much of your overnight call volume is theoretically eligible for automated pre-screening. Calls that resolve as routine false positives without account-specific judgment are the target population for triage automation. Calls that require an experienced dispatcher's contextual knowledge or that escalate to genuine incidents are not.
3. Cost per overnight dispatcher hour
In Ireland, the fully loaded cost for a shift-work dispatcher position covering overnight hours sits in a range broadly consistent with other shift-based operational roles: base pay, shift premium, employer PRSI, and a portion of supervisory and HR overhead. This figure varies by center size, location, and whether you use in-house staff or outsourced monitoring services. Use your own number. The point is that staffing the overnight window costs real money per hour, and the relevant question is: how many hours are required to handle the call volume you actually have?
Building the Model
The simplest version of the ROI model looks like this:
Monthly overnight calls x false positive rate = calls eligible for automated handling
Average call handling time (logging, clearing, documentation) x eligible call volume = dispatcher-hours consumed by false positive processing monthly
Multiply dispatcher-hours by your cost-per-hour to get the staffing cost attributable to routine false positive processing. That is the addressable cost pool.
Voice automation does not eliminate that cost entirely. There are configuration costs, oversight requirements, and the ongoing management of account profiles. A realistic capture rate for a well-configured triage system in a commercial ARC context is somewhere between 65 and 80 percent of the eligible call volume. Not every false positive call will flow cleanly through automated triage. Some will hit ambiguity thresholds and route to a dispatcher anyway.
So the return looks something like: 70 percent of the addressable staffing cost minus the monthly subscription cost equals the monthly net financial benefit. Most centers doing this calculation honestly find the financial case is solid, particularly for overnight volumes above 400 calls per month.
The Costs That Do Not Appear in the Spreadsheet
The financial model above captures the direct staffing reduction. It does not capture some costs that are real and worth naming.
Dispatcher quality at the end of a high-volume shift. The cognitive cost of processing 200 zero-value calls before a genuine incident arrives is not a line item. But it affects response quality. A center that reduces the routine call burden on its overnight team is likely improving the quality of the decisions that matter, not just the efficiency of the routine ones. Quantifying this is hard. Ignoring it as if it does not exist is also wrong.
Account retention downstream of response quality. Monitoring centers that respond faster to genuine alerts, because their dispatchers are not cognitively depleted from false positive volume, tend to see fewer account-level complaints. Whether that translates to measurable retention improvement depends on how you track it.
Recruitment and training for overnight shifts. Finding experienced dispatchers willing to cover regular overnight shifts is a consistent challenge. A center that reduces the pure volume grind of the overnight role may find the position marginally more retainable. Not a primary ROI argument, but real over a longer time horizon.
What the Model Does Not Justify
We should be clear about what a positive ROI calculation does not mean. It does not mean automation handles all calls. It does not mean overnight staffing levels can be cut proportionally to the call volume reduction. Monitoring centers have minimum staffing requirements for safety reasons that are independent of average call volume. A center with two overnight dispatchers handling 180 calls per night may see 130 of those handled through automated triage, but they still need those two dispatchers for the 50 that require judgment, the account-specific escalations, and the genuine incidents that arrive without warning.
The ROI of voice automation is best understood as a reduction in the cost of the work that does not need a human, not as a substitute for the staffing required to do the work that does. Any vendor framing it differently is being imprecise about what the technology actually does.
Running the Numbers for Your Center
The calculation is worth doing with your own figures before evaluating any specific solution. Most centers that go through it find the financial case is clear at moderate overnight volumes. What matters more than the headline number is whether the design of the triage system matches the actual call categories in your overnight queue. A technically positive ROI from a poorly-designed triage layer that creates operational friction is not a good outcome.
The right sequence: understand your overnight call profile, build the model with your actual numbers, and then evaluate whether a specific system's design fits the calls you actually have. The financial case follows from the operational fit, not the other way around.