Most organisations know they carry tech debt. Far fewer know how much, where it lives, or what it costs.
This post looks at how Platform Health Analytics in the Impact Store App can help ServiceNow Impact customers find it, size it and fix it, using Australian federal and commercial examples.
The scale of it
The ANAO's 2025-26 interim audit results, covering 27 of the largest Commonwealth entities, found that 71 per cent of all findings related to IT controls (up from 65 per cent at the same point last year), and 85 per cent of findings were carried over unresolved from earlier years. The weaknesses were familiar ones: IT security made up 64 per cent of IT control findings, with managing and monitoring user access a recurring theme, and change management findings were still on the list. Progress is real, with total findings down from 118 to 86, but the carried-over share shows how slowly known issues close. Not all of that is tech debt in the strict sense, but it is the same family of problem: controls never finished, reviewed or maintained. And when a finding is known yet still open a year later, the gap is rarely awareness. It is visibility and prioritisation: knowing what each one costs and which to close first.
The DTA's 2026 Major Digital Projects Report puts $1.3 billion into 14 active government projects, with legacy modernisation a major focus because ageing systems struggle with demand, compliance and cyber threats.
The commercial sector shows the same pattern under different pressure. IDC's late-2025 survey found that 58 per cent of Australian organisations say their architecture is too rigid, costly and slow to build new applications without extensive modernisation, and 96 per cent have experienced a failed modernisation initiative. IDC also predicts that organisations ignoring technical debt will see 50 per cent higher failure rates and rising costs on AI initiatives by 2027. With nearly every organisation having seen a modernisation effort fail, starting by measuring what you already have is a sensible first step.
Government carries debt as an accountability risk: audit, continuity and security. Business carries it as a competitiveness risk: speed and AI readiness. Both are paying interest.
How it shows up on ServiceNow
ServiceNow’s flexibility is a powerful feature, yet it requires intentional governance. Technical debt accumulates quietly through working scripts, shared ownership gaps, and updates promoted without clear documentation. Each is a reasonable choice in isolation, but they collectively impact upgrade velocity and audit scope.
Where ServiceNow Impact helps
The Impact Store App brings everything ServiceNow Impact offers into your own instance, and its Platform Health suite was born from ServiceNow's acquisition of Bravium Labs' applications. Three pieces matter here:
The Impact Scan Engine is the scanner: it examines your instance for findings against a set of active definitions. Platform Health Analytics is the layer on top, turning those findings into dashboards, trends and a technical debt value. Around them sit real-time scanning, Otto code fixes, and custom definitions. These have been available in the Impact Store App since December 2025, with 10 active custom definitions on Guided plans and unlimited on Total.
What Platform Health Analytics measures
The Scan Engine checks your instance against a large library of definitions across security, performance, manageability, upgradeability and user experience. There are hundreds, and the three below are just samples. Every finding carries an impact score, an estimated time to resolve, supporting documentation and resolution steps.
Customers can also set their estimated average developer hourly cost, even with a custom workday schedule. Combined with the estimated time to resolve, that turns a list of findings into a total technical debt value. Take the three samples below, assume one occurrence each, and you have eight hours and twenty minutes of work, or $1,000 at an illustrative $120 an hour. A real instance has far more findings, and many occurrences of each, which is why seeing the total matters.
Three sample definitions
| Finding | Severity | Impact score | Est. time to fix |
|---|---|---|---|
| sn_SE10033: gs.setProperty() shouldn't be called within scripts | High | 10 | 8 hours |
| sn_SE10317: Groups should have a manager | Medium | 5 | 5 minutes |
| sn_SE10051: Update sets should have a meaningful description | Low | 2 | 15 minutes |
High: gs.setProperty() in scripts. ServiceNow's documentation notes that every system property change flushes the cache across the cluster, at a high performance cost of one to ten minutes, and can cause an outage if it happens excessively. Nobody notices until a citizen portal or checkout page slows at the worst moment. At eight hours, it is a genuine refactoring job, which is why it rarely gets done until someone can see it.
Medium: groups without managers. A group with no manager points to poor data management. For federal agencies, unclear ownership is an accountability question, and it is the kind of control hygiene auditors look for. Five minutes to fix.
Low: update sets without a meaningful description. Fifteen minutes, and easy to skip. But the description is the record of why something was promoted, which is exactly what you reach for during troubleshooting or an investigation.
Notice what does not line up. The score 10 finding takes eight hours, the score 5 takes five minutes, and the score 2 takes fifteen. Impact and effort do not move together, so resist clearing the quick ones first. Sort by impact, then use effort to sequence the work.
Getting started
Start small. Set your developer hourly cost so every finding carries a dollar value from day one, then run a diagnostic scan across the instance. Triage by impact score, and perhaps push the work into the tools your developers already use: the suite integrates with Azure, Jira and ServiceNow, so findings become user stories. Switch on real-time scanning so new code is checked as it is written and the debt stops growing while you pay it down. Then, use the dashboards to show the trend to your audit committee or board.
Executive Narrative
Outside the platform team, executives often don't care about cache flushes or update sets. They care about risk, cost and capacity, and a total technical debt value speaks to all three. For a federal accountable authority, it shows that known control weaknesses are being found and closed before an auditor raises them.
For a commercial leadership team, it shows how much delivery capacity is tied up in rework that could fund the next initiative, including the AI programs now on most agendas. The dashboards give the platform team their evidence: a debt value trending down, findings closed each quarter, and real-time scanning stopping new debt at the door.
So, report it in the language of the business, such as dollars retired, risk reduced and estimated hours returned to the roadmap, and technical hygiene becomes a story leaders want to fund.
Tech debt stops feeling overwhelming when it becomes a list with a dollar value. Run a scan, sort by impact, knock over the five-minute fixes, and put the eight-hour one in the sprint (for example).
Let me know how you're using the tool, feedback, wins, and any questions in the comments below!
