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01/07/2026 6:49 pm
TL;DR: Backlog grading helps IT teams prioritise repetitive work using task scoring and a separate problem score, because manual friction wastes time and broken prioritisation keeps urgent noise ahead of real automation candidates, according to JumpCloud. The key insight is that automation only helps when the underlying process is stable enough to support it.
NHIMG editorial — based on content published by JumpCloud: Your IT backlog is full of tasks that should not exist
By the numbers:
- Approximately 46% of AI and advanced automation proofs of concept are scrapped before they reach production.
Questions worth separating out
Q: How should teams prioritise automation work in a busy IT backlog?
A: Start by scoring tasks on repeatability, frequency, risk of human error, and implementation effort.
Q: When does automation create more risk than it removes?
A: Automation creates more risk when the underlying process is still unstable, undocumented, or full of exception handling that only humans currently understand.
Q: What is the difference between task scoring and problem scoring?
A: Task scoring ranks individual items by how suitable they are for automation.
Practitioner guidance
- Score repetitive tasks before assigning automation work Use complexity, frequency, human-error risk, and implementation effort to rank each task.
- Separate task automation from problem automation Treat repeated tasks and recurring business problems as different backlog classes.
- Stabilise the workflow before building automation around it Document inputs, exception paths, and handoffs before automating.
What's in the full article
JumpCloud's full blog covers the operational detail this post intentionally leaves for the source:
- The exact four-dimension scoring quiz for ranking repetitive tasks.
- The problem score worksheet for comparing recurring operational issues.
- The financial modelling logic behind automation prioritisation.
- The practical automation recipes and implementation examples used in the eBook.
👉 Read JumpCloud's guide to grading IT backlog work for automation →
Backlog grading for automation: what should IT teams prioritise first?
Explore further
01/07/2026 6:49 pm
Backlog prioritisation is a governance control, not just an efficiency exercise. The article’s scoring model is really a control-selection method disguised as an operations workflow. For identity teams, the same logic decides whether manual approvals, recertification checks, or secret-handling steps should stay manual or move into repeatable automation. The implication is that backlog order shapes control maturity, so weak triage produces weak governance.
A few things that frame the scale:
- 88.5% of organisations acknowledge that their non-human IAM practices lag behind or are merely on par with their human identity and access management efforts, according to The 2024 Non-Human Identity Security Report.
- Only 19.6% of security professionals express strong confidence in their organisation's ability to securely manage non-human workload identities, according to The 2024 Non-Human Identity Security Report.
A question worth separating out:
Q: How do teams know whether a backlog item is ready for automation?
A: A backlog item is ready when the steps are stable, the inputs are clear, and the exception paths are already understood. If the process still changes every week or depends on informal knowledge, the work is not ready for automation. Readiness is a process-quality question, not a tooling question.
👉 Read our full editorial: Backlog grading shows why automation should start with repeatable tasks
