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OriginAI
ROI

Model your operational lift

Tune volume, handling time, and loaded cost to stress-test operational savings for Technology Ops or People Ops. Cloud savings and avoided delivery delay are scoped separately during solution design.

Domain

Modeled on standardized, scriptable IT requests — access, provisioning, routine pipeline fixes.

Queue workload
1,200 h/mo
Team capacity (12 FTE)
2,078 h/mo
Assumed automation
60% over 3 months

Cost per productive hour is $79.19, based on 85% of paid hours net of leave and non-queue time.

Model uses illustrative automation and cost assumptions. Replace with your enterprise economics during a formal business case.

Estimated impact

Estimated annual savings updated to $720,652.

Hours saved / mo
758

720 h automated, 38 h rework avoided

FTE equivalent freed
4.38

of 12 FTE in scope

Annual savings at run rate
$720,652

$630,570 in year one after a 3-month ramp

Rework reduction
40.0%

8% rework rate falls to 4.8%

Year-one ROI
425%

501% once fully ramped

Payback (illustrative)
3 months

Counts only labor and rework inside this queue, against an internal placeholder platform cost for demo purposes. Cloud savings, avoided delivery delay, and risk reduction are scoped separately during solution design.