The XOPS impact calculator

How much of your IT operation still runs on human effort?

Your teams spend thousands of hours reconciling systems, chasing exceptions, managing assets and coordinating work. XOPS agents can take on much of that work autonomously. Calculate the impact of putting agents to work.

An ITAM savings and IT operations ROI calculator for CIOs, ITAM and finance leaders, covering software licenses, hardware refresh, employee lifecycle and AI spend. Compare them with results measured at customers.

Where is your enterprise losing the most value?

Each estimate measures something different and they overlap, so they are never added together.

Assumptions

Deployment ramp Year 1 % Year 2 % Year 3 %

Expected is the default. A scenario sets the realization assumptions on every tab; you can still change any of them. Three-year figures follow the ramp, because outcomes switch on progressively.

Your organization

Employees supported

People in the IT roles the agents cover

Assumption · follows employees until you edit it

About 33 people per 10,000 employees across software and hardware asset management, AI governance, HR partnering, identity and access, security and compliance, IT finance, service desk, fulfillment and workplace. A planning value, not a benchmark.

Average fully loaded annual cost per person

Time spent on manual coordination, reconciliation and verification 30%

Illustrative assumption · set it to match your team

Estimated share of manual work XOPS could eliminate 25%

Illustrative assumption · not an XOPS benchmark

XOPS already automates operational work across enterprise systems. Actual results depend on your environment, the processes in scope, and the exceptions that still need a person. Complex investigations are handled by specialized agents and aren't counted here.

Refine the assumptions

Productive hours per person per year

Your potential annual impact

4,455

hours of manual IT work, gone

worth of capacity returned to your organization: 2.5 FTE
in annual capacity value $928,125 over three years, with the ramp: $371,250

That is the equivalent of 2.5 people reconciling systems and chasing work instead of improving the business.

Your estimate is illustrative: it comes from the assumptions you set, not from a validated customer result. Actual results depend on contract timing, entitlements, usage and what is recoverable; an XOPS proposal works from your own contracts.

How the XOPS agents deliver this

Agents coordinate and verify the work across your systems and teams, and escalate only when a person is needed.

Reconcile the systems that disagree, continuously
Coordinate the work across IT, HR, procurement and vendors
Verify each outcome and keep the evidence
Resolve routine exceptions within your policy
Escalate complex investigations to a person, with the context attached

See how XOPS agents work

Today, your team spends an estimated 17,820 hours a year on manual operational work.

Eliminated by XOPS Still manual

What XOPS takes off your team today

Reconciliation across systems
Coordination across teams
Verification and reporting
Routine exceptions, within policy

Counted in this estimate.

Handled by specialized agents

Complex investigations
Ambiguous exceptions
Decisions requiring deeper analysis

Not counted in this estimate.

This is capacity, not headcount. The spend XOPS brings under control, from software and hardware to AI, is on the other tabs.

That is 3.3 people in these roles per 1,000 employees supported.

Measured at a customer · Fortune 15 pharmaceutical

92%

of contractor lifecycle work completed with no human intervention

Scope: contractor lifecycle. A production result at one customer, shown for context and separate from your estimate above; not a forecast for every IT function.

See how XOPS agents would deliver this in my environment

How we calculated this

How this is calculated: people in the roles the agents cover x productive hours per person gives total capacity. The manual-work share gives the hours spent on manual operational work, and the automated share gives the hours eliminated. Recovered FTE is hours eliminated divided by productive hours per person, and its value is recovered FTE x fully loaded cost. Complex investigations and ambiguous exceptions are handled by specialized agents and left out here, so set the share with that in mind. Capacity value isn't equivalent to cash savings unless the organization reduces or avoids spending: it is time returned to your team for higher-value work. The three-year figure applies the deployment ramp. Both percentages are your assumptions, not XOPS benchmarks or customer results.

Your software estate

Employees

Assumption

Software and SaaS spend per employee per year

Source

Zylo 2025 SaaS Management Index: SaaS spend averages $4,830 per employee. Leave AI assistant seats out: they are on the AI tab.

Share of licenses unused 46%

Source

Zylo 2026 SaaS Management Index: organizations use 54% of the licenses they provision. Unused is not the same as recoverable; the next assumption sets that.

Share of unused spend recovered a year 10%

Assumption

Reclaimed, reassigned or removed at renewal. The scenario buttons set it to 7.5%, 10% or 13.5%.

Users moved to a lower license tier 5%

Assumption

Licenses that are in use but on a tier the user does not need, such as Microsoft 365 E5 where E3 or F3 would do. These are used licenses, so they never overlap with unused-license recovery.

Monthly price gap between the two tiers, per user

Assumption

Use your agreement prices.

Agreements renewing or truing up in the next 12 months 33%

Assumption

Unused licenses usually become cash at renewal, true-up or avoided expansion. 33% fits a typical three-year agreement cycle.

Software audit spend per year

Assumption

Flexera 2025: 45% of organizations spent over $1M on software audits in three years.

Audit spend avoided 20%

Assumption

A continuous license position, with evidence on demand.

Your annual software optimization opportunity

recoverable a year, with your assumptions

Opportunity range for your estate: - Conservative to aggressive assumptions, with your other inputs.

unused license spend today total addressable, not all recoverable: -
realizable in the next 12 months as agreements renew, plus audit spend avoided: -

How the XOPS Software Asset Manager delivers this

Agents continuously reconcile entitlements, assignments, actual usage and contracts, then reclaim or right-size the licenses themselves.

Reconciles entitlements, assignments, actual usage and contract terms, continuously
Finds unused, duplicate and misallocated licenses, and seats on a tier nobody needs
Reclaims, reassigns or right-sizes them within your policy
Prepares renewal and true-up positions, with audit evidence on demand
Escalates only the exceptions that need a human decision

Meet the Software Asset Manager

Unused licenses recovered-
License tiers right-sized-
Audit spend avoided-
Over three years, with the deployment ramp-

Measured at a customer · Fortune 250 financial

40%

license spend reduced, once entitlement, usage and ownership were continuously reconciled

A production result at one customer, shown for context. It is separate from your estimate above.

See how XOPS agents would deliver this in my environment

How we calculated this

How this is calculated: employees x spend per employee gives software spend in scope, and the unused share gives the unused spend: the total addressable opportunity. Only part of it is recoverable each year, so the recovered share gives unused licenses recovered. License-tier right-sizing is users moved to a lower tier x the monthly price gap x 12; those licenses are in use, so the two never overlap. Audit spend avoided is your annual audit spend x the share avoided. Most of it turns into cash as agreements renew or true up, so the 12-month figure applies the share renewing. The range swaps in conservative and aggressive values for the recovered share, the tier share and the audit share. All percentages are your assumptions; the customer result shown is one measured outcome, not a forecast.

Sources: Zylo, 2025 SaaS Management Index (January 16, 2025) for SaaS spend per employee, and 2026 SaaS Management Index for license utilization; Flexera, 2025 State of IT Asset Management Report (June 18, 2025; 506 IT professionals) for audit spend. All are vendor research.

Your fleet and workforce

Employees and contractors supported

Assumption

Follows the IT operations tab until you edit it.

Devices per person

Assumption

Laptops, desktops and workstations, including shared and loaner devices.

Refresh cycle 4 yrs

Assumption

How often devices are replaced by age today.

Labor rate basis

For senior IT operations staff, other countries or an outsourced provider, choose your own rate below.

Fully loaded IT labor rate per hour

Source

BLS May 2025 national medians: computer user support specialists $61,860 and computer network support specialists $76,220, in a 70/30 mix, 1.35x benefits and overhead, 1,760 productive hours.

Autonomy realization 80%

Assumption

Scales the autonomous share of each of the 33 lifecycle activities. Hands-on work counts at half, and no activity goes above 95%.

Share of devices still healthy at refresh time 30%

Assumption

Kept in service on condition instead of replaced by age.

Years of life added to healthy devices 1 yrs

Assumption

Customers have measured 1-2 years of added life on healthy devices.

Refine the assumptions

Joiners a year (% of people) Leavers a year (% of people) Internal moves (% of people) Remote or hybrid (%) Repair events (% of fleet) Lost or stolen (% of fleet) Average device cost ($) Two-way shipping per device ($) Shipping avoided (%) Leaver devices never recovered today (%) Recovered device value (% of new) Never recovered with XOPS (%) Employee cost per day ($)

Include device support tickets, day-1 tickets and compliance exceptions (off by default: they have no Work Catalog outcome yet)

Your annual hardware opportunity

direct savings a year: refresh deferred, devices recovered, shipping avoided

Opportunity range for your estate: - Conservative to aggressive assumptions, with your other inputs.

hours of device lifecycle work removed a year -: -
IT capacity returned a year time for higher-value work, not cash unless you reduce or avoid spend: -

How the XOPS Hardware Asset Manager delivers this

Agents decide whether to refresh, repair, redeploy or recover each device, then coordinate the work with your vendors to the end.

Decides for each device: refresh, repair, redeploy or recover, from health, warranty and role
Keeps healthy devices in service instead of replacing them on age
Recalls, tracks and wipes leaver devices until they are back and redeployed
Coordinates deployment, repair, loaners and shipping with your vendors
Escalates only the exceptions that need a human decision

Meet the Hardware Asset Manager

Shipping avoided-
Leaver devices recovered-
Refresh spend deferred-
Direct savings over three years, with the ramp-
Employee productivity recovered (not cash)-

Risk exposure, not in the savings: -

Hours removed, by lifecycle stage

Plan & procure-
Provision & deploy-
Operate & support-
Refresh & redeploy-
Recover & offboard-
Retire & dispose-

Measured at a customer · Fortune 500 technology

$4.3M/yr

device lifecycle savings, with 1-2 years of added device life

A production result at one customer, shown for context. It is separate from your estimate above.

See how XOPS agents would deliver this in my environment

How we calculated this

How this is calculated: your workforce and fleet set yearly volumes for 33 device lifecycle activities, from purchase orders and new-hire deployments to refreshes, repairs, leaver recoveries and disposal. Each activity has hours per event and a base-case autonomous share; hours removed are hours x the share x your realization, hands-on work at half, capped at 95%. Labor capacity is hours removed x the labor rate: capacity returned to your team, not cash. Shipping avoided, devices recovered and refresh deferred are direct savings, and they lead the result; a recovered device counts at a share of a new one (60% by default) because it is redeployed or resold, not bought new. Employee productivity is shown separately and is not cash. The range swaps in conservative and aggressive values for realization, healthy devices and shipping avoided. Annual values are steady state; the three-year figure applies the deployment ramp.

This is the same activity model XOPS uses in device lifecycle proposals, so the same inputs give the same labor results. All values are your assumptions except the labor rate, sourced from BLS May 2025 national medians; the customer result shown is one measured outcome, not a forecast.

Your AI workforce

Employees

Assumption

Employees with a paid AI assistant seat 25%

Assumption

Copilot, ChatGPT Enterprise, Gemini and similar seats.

AI assistant price per seat per month

Source

Microsoft 365 Copilot enterprise list price, US$ 30 per user per month.

Seats idle in a given month 20%

Assumption

Seats paid for but not used.

Idle seats reclaimed or reassigned 50%

Assumption

After a grace period, by policy.

Prepaid AI credits and committed spend per year

Assumption

Committed or prepaid capacity across providers.

Share of commitments that would expire unused 15%

Assumption

Share of that waste XOPS prevents 50%

Assumption

Reallocating capacity before it expires and right-sizing the next commitment.

Usage-based AI spend per employee per year

Assumption

Tokens, API calls and agent consumption billed on use.

Share of usage-based spend that is unplanned overrun 20%

Assumption

Zylo 2025: 66.5% of IT leaders reported unexpected charges from consumption-based or AI pricing.

AI spend with an accountable business owner today 40%

Assumption

Every agent, key and seat needs an owner and a budget.

Your AI workforce, governed

avoidable AI commitments a year

Opportunity range for your estate: - Conservative to aggressive assumptions, with your other inputs.

AI spend at risk a year unplanned overrun on usage-based spend; not counted as savings: -
AI spend with no accountable owner a governance measure; not counted as savings: -

How the XOPS AI & Agent Governance agent delivers this

Agents enforce ownership, budgets and consumption policies as AI is used, rather than reporting overruns after the bill arrives.

Gives every AI agent, key and seat an accountable owner and a budget
Enforces spend thresholds and throttles runaway consumption as it happens
Reclaims idle seats and reallocates commitments before they expire
Revokes orphaned keys and credentials
Escalates only the exceptions that need a human decision

Meet the AI & Agent Governance agent

Idle seats reclaimed-
Expiring commitments reallocated-
AI spend in scope a year-
Avoidable commitments over three years, with the ramp-

AI is a new workforce: its spend, ownership, permissions and consumption need continuous governance. Only avoidable commitments are counted as savings here; the overrun and unowned figures show what is exposed until every agent, key and seat has an owner and a budget. Risk context: IBM and Ponemon's Cost of a Data Breach Report 2025 found a high level of shadow AI added USD 670,000 to the average breach cost.

See how XOPS agents would deliver this in my environment

How we calculated this

How this is calculated: employees x the seat share gives paid AI seats; idle seats x the share reclaimed x the seat price x 12 gives seats reclaimed. Commitments x the share that would expire unused x the share prevented gives commitments reallocated. Together they are the avoidable commitments, the only figure counted as savings. Usage-based spend x the overrun share is spend at risk, and total AI spend x the share without an owner is unowned spend; both are shown, not added. All values are your assumptions.

Sources: Zylo, 2025 SaaS Management Index (January 16, 2025) for unexpected consumption charges; Microsoft 365 Copilot list price; IBM and Ponemon Institute, Cost of a Data Breach Report 2025 (July 2025; 600 breached organizations) for the risk context.

Employee lifecycle: every transition completed. Nothing left behind.

From the first day to the last, XOPS agents coordinate employee transitions across HR, IT, identity, software and hardware systems, continuously verifying that the intended outcome actually happened.

Your workforce

Employees

Assumption

Follows the IT operations tab until you edit it.

Joiners a year 15%

Assumption

New hires and contractors starting, as a share of employees.

Movers a year 10%

Assumption

Role, department or location changes that change access, software or equipment.

Leavers a year 12%

Assumption

Employees and contractors leaving.

Automation potential 80%

Assumption

Share of the IT work in each event that XOPS agents carry out and verify. The scenario buttons set it to 70%, 80% or 90%.

Loaded hourly rate of the people who handle these events

Assumption

Blended across IT, identity and HR staff. The Hardware tab uses a device-support rate (BLS) instead.

Refine the assumptions

IT hours per joiner IT hours per mover IT hours per leaver Licenses per person License cost per month ($) Months sooner a leaver's licenses come back Licenses a mover no longer needs Value of a recovered device ($) Leaver devices never recovered today (%) Never recovered with XOPS (%) New-hire days gained by day-one readiness Employee cost per day ($) Days a leaver's access stays open today

Your employee lifecycle impact

hours of joiner, mover and leaver work returned a year

Capacity value range for your workforce: - Conservative to aggressive automation, with your other inputs.

joiner, mover and leaver events a year: -
annual capacity value time returned to your teams; not cash unless you reduce or avoid spend: -

How the XOPS Workforce Lifecycle Manager delivers this

Agents coordinate every joiner, mover and leaver across HR, identity, software, hardware and workplace systems, then verify the intended outcome actually happened.

Joiners: provisions identity, applications, device and services, and verifies readiness before day one
Movers: detects the role or department change, reconciles access and entitlements, and adjusts software and equipment
Leavers: revokes access, reclaims licenses, recovers the device and closes open dependencies
Verifies completion in every system, not just that a ticket closed
Escalates only the exceptions that need a human decision

Meet the Workforce Lifecycle Manager

Joiners a year-
Movers a year-
Leavers a year-
Capacity value over three years, with the ramp-

Also in this lifecycle, shown separately

Licenses reclaimed from leavers and movers a year-
Leaver devices recovered a year-
New-hire productivity gained (not cash)-

Not added to the capacity value. License reclamation overlaps the Software tab and device recovery overlaps the Hardware tab, so each tab stays a standalone scenario and the tabs are never summed.

Risk exposure, not in the savings: -

Measured at a customer · Fortune 15 pharmaceutical

92%

of contractor lifecycle work completed with no human intervention

Scope: contractor lifecycle. A production result at one customer, shown for context and separate from your estimate above; not a measured result for every joiner, mover and leaver process.

See how XOPS agents would deliver this in my environment

How we calculated this

How this is calculated: employees x the joiner, mover and leaver shares give the events a year. Each event has its own IT hours (3 per joiner, 2 per mover and 3 per leaver by default), so hours today are the sum of events x hours, and hours returned are hours today x the automation potential. Capacity value is hours returned x the loaded hourly rate; it is time returned to your teams, not cash unless you reduce or avoid spend. Licenses reclaimed are leavers x licenses per person x the monthly cost x the months they come back sooner, plus movers x licenses no longer needed x the monthly cost x 12. Devices recovered are leavers x the drop in devices never recovered, at the value of a recovered device. New-hire productivity is joiners x days gained x half the daily cost. These are shown, not added: they overlap the Software and Hardware tabs. The range swaps in 70% and 90% automation. All values are your assumptions.

What customers measured

Your numbers are an estimate.
These ones were measured in production.

92%

Of contractor lifecycle work completed with no human intervention.

Fortune 15 pharmaceutical · measured

$4.3M/yr

Saved by refreshing devices on their actual health instead of their age.

Fortune 500 technology · measured

40%

Software license spend reduced, once entitlement, usage and ownership were continuously reconciled.

Fortune 250 financial · measured

How much of your IT operation still runs on human effort?

Where is your enterprise losing the most value?

Employee lifecycle: every transition completed. Nothing left behind.

Your numbers are an estimate. These ones were measured in production.

Your numbers are an estimate.
These ones were measured in production.