With over 14,000 active employees and nearly 15,000 user accounts at any given time, Identity and Access Management was a major challenge. Add in the fact that over 200 applications are used on a daily basis, from point of sales, to financials and human resource information systems, you’ve got yourself a seemingly impossible task to manage identities securely and efficiently.
Engineering leaders know on-call is broken. Finance leaders don't know it costs $2–5M a year. Here's how to make the case — and what the ROI actually looks like.
Engineering leaders live inside this problem. They know which incidents repeat. They know which engineers are burning out. They know the rotation is two people short of sustainable.
What they often lack is the language to take it upstairs. "My team is exhausted" is a people problem. "We're spending $3M a year on a solvable infrastructure gap" is a business problem — and it gets a different kind of attention.
This is a guide to making that translation.
Finance thinks in line items. The first step is converting on-call dysfunction into categories your CFO already tracks: downtime cost, labor cost, and attrition cost. Most organizations have never put these in a single spreadsheet.
These numbers are conservative and based on a mid-size org with 10 on-call engineers. Two line items tend to land hardest with leadership: the productivity tax — which is invisible in most headcount models — and the turnover cost, which at $310K per engineer replacement represents a quiet eight-figure exposure over a three-year horizon.
"You're already spending $2–5M a year on this problem. The question is whether you keep paying it — or invest a fraction to fix it."
Once the cost stack is visible, the ROI case is straightforward. Conservative projections — 50% MTTR reduction, 30% fewer pages, one fewer engineer lost to burnout — generate savings that exceed typical solution costs within a single quarter.
Not all numbers land equally in executive conversations. In practice, three figures tend to shift the dynamic from "interesting" to "let's act on this."
The productivity tax is often the surprise. Finance leaders who have modeled headcount carefully haven't accounted for the 20% output reduction that on-call engineers carry the day after a page — let alone the accumulated cost across a full rotation, quarter over quarter. Putting a dollar figure on it reframes the conversation entirely.
The instinct is to present this as an engineering investment. Resist it. The framing that moves CFOs is operational risk reduction — a category they already track, budget for, and care about.
On-call dysfunction is a retention risk, a revenue risk (downtime), and a productivity drag. The solution isn't a new engineering tool — it's closing an operational exposure that's been accruing quietly for years.
Start with your own numbers. Pull 90 days of incident data. Calculate your actual downtime cost using Gartner's $5,600 per-minute benchmark. Estimate your rotation's productivity tax. Add one hypothetical turnover event. Most teams land well north of $1M before they've finished the spreadsheet.
That's the number to bring to the room. Not a vendor estimate — your number, built from your data. It's harder to argue with, and it anchors the conversation where it belongs: on the cost of doing nothing.
The first step toward a healthier on-call culture is a single conversation. Reach out to our team today and let's talk about what's possible for your organization. Contact the Arisant experts at 303-330-4065 or email us at polaris_monitoring@arisant.com
Polaris is a monitoring tool with self-healing capabilities that can augment or replace your current monitoring solution. Please reach out if you'd like additional information.
This analysis draws on industry research from Gartner, PagerDuty, and first-party incident data. Cost estimates reflect conservative projections for a mid-size technology organization operating with 10 on-call engineers.
