Problem management ·
Why the Same IT Problems Keep Coming Back — A Practical Guide to Root Cause Analysis
A practical guide to investigating recurring IT problems: connect incidents, test hypotheses, verify corrective actions and document what the next engineer needs.
The laptop works after a restart. The meeting starts after a driver reinstall. The ticket closes.
Then the same issue returns.
Recurring IT problems consume time twice: first when users cannot work, then when support repeats an investigation that should already have moved forward. Root cause analysis in IT support creates a structured way to connect those incidents, test explanations and reduce recurrence.
This guide focuses on the practical investigation. For the wider service mindset, see what modern IT support in Copenhagen should look like.
When does a recurring incident need a problem investigation?
There is no useful universal rule that says the third identical ticket must become a problem record. Consider business impact, frequency, risk and the time spent applying workarounds.
Start investigating when:
- The same symptom returns after an apparently successful fix.
- Different users or devices show a similar failure pattern.
- A workaround restores service but the cause remains uncertain.
- Repeated interruptions consume more support capacity than an investigation would.
- A single serious incident reveals a weakness that could affect other services.
Do not group tickets by wording alone. Two users reporting “Teams audio does not work” may have different causes. Conversely, reports of missing microphones, failed calls and missing audio devices may belong to one investigation.
Link related incidents, explain why they appear connected and keep exceptions visible.
Incident management vs. problem management
Incident management aims to restore service and limit the immediate impact. Problem management investigates causes and manages the risk of future incidents.
| Question | Incident work | Problem work |
|---|---|---|
| What needs attention? | The current interruption | Its cause and recurrence risk |
| What is a useful output? | Verified service recovery | Evidence, a documented workaround and corrective action |
| When can it close? | Recovery meets the agreed criteria | Agreed problem objectives are met, or residual risk is explicitly accepted |
| Who owns the next step? | The incident owner | A named problem owner coordinating the investigation |
A restored service does not prove the underlying problem is resolved. A problem investigation may also end with an accepted limitation rather than a permanent technical fix. Record that decision honestly.
The broader operating model is covered in my guide to building and scaling a technical support organization.
A six-step method for root cause analysis in IT support
1. Describe the failure precisely
Replace “the laptop is unstable” with observable information:
- What action failed, and what should have happened?
- Which users, devices, locations and services are affected?
- When did it start, and when was it last known to work?
- Is the failure reproducible?
- What is the business impact?
- What restores service, and for how long?
Record timestamps with time zones. Capture relevant versions, error messages and the conditions under which the issue appears. Collect only the evidence needed, and store logs where access is appropriate.
A precise statement keeps everyone investigating the same issue.
2. Compare affected and unaffected cases
An unaffected device can be as useful as a failing one.
Compare relevant characteristics: hardware model, driver and firmware versions, operating system build, application version, network path and configuration assignments.
For example, if audio fails only on one device model after an update, that gives you a testable direction. It does not establish that the update caused the failure.
Avoid changing several variables at once. You lose the ability to explain which change mattered.
3. Build a timeline and separate facts from assumptions
Create a short sequence of events: the last known healthy state, relevant changes, first observed failure, recovery attempts and recurrence.
Keep three categories separate:
| Category | Illustrative example |
|---|---|
| Observation | Affected devices share a driver version |
| Hypothesis | That version may interact badly with a particular configuration |
| Test | Compare a controlled remediation against an otherwise similar affected device |
Use methods such as the “five whys” to uncover missing questions. They do not replace technical evidence. If the answer becomes “the user made a mistake,” investigate the surrounding design, instructions and controls as well.
There may be several contributing causes. Do not force a complex incident into a single convenient explanation.
4. Test the smallest useful hypothesis
Write down the expected result before testing.
If you suspect a driver issue, define the affected configuration, the proposed change, the validation steps and the recovery path. Start with a suitable test device or a small pilot where the risk is understood.
A successful restart shows that a restart helped. It does not establish why the failure occurred.
Increase confidence by reproducing the issue where practical, checking whether the proposed correction consistently changes the outcome and looking for evidence that contradicts your explanation. Keep uncertainty visible when controlled reproduction is impossible.
5. Implement the correction with ownership
Once the evidence supports an action, agree:
- Who owns the change and approves the risk.
- Which devices or services are in scope.
- How the change will be tested and deployed.
- What happens if it fails.
- How users and support teams will be informed.
Automation becomes useful when the procedure is understood and repeatable. Include scope checks, logging and a recovery path appropriate to the action.
Do not use a successful pilot as permission to change every device without considering differences across the environment.
6. Verify that the problem stays resolved
Choose an observation period that fits the original failure pattern. A problem that returned weekly cannot be verified by checking the device once after installation.
Confirm the original workflow with users, review relevant monitoring and compare recurrence with the baseline. Account for changes in device population or usage: fewer tickets can reflect fewer active users.
If the issue returns, reopen the hypothesis. Preserve what the previous test established and continue from there.
A practical example: recurring audio driver issues
In my enterprise audio driver automation case study, multiple clients experienced repeated audio and firmware problems. I developed a batch-based remediation that replaced the affected components with compatible vendor versions and made the procedure repeatable.
The lesson is to turn an understood remediation into a consistent process. A script can standardize recovery, but its success alone does not prove every contributing cause has been removed.
For a similar investigation, I would document the affected configurations, prerequisites, deployment scope, recovery steps and recurrence checks before widening the rollout.
A reusable problem investigation template
Copy these fields into your ticketing system or knowledge base:
| Field | What to record |
|---|---|
| Problem statement | Observable failure and expected behaviour |
| Business impact | Interrupted work, affected users and operational risk |
| Related incidents | Linked records and the reason for grouping them |
| Scope | Affected and unaffected configurations |
| Timeline | Relevant changes, failures and recovery attempts |
| Evidence | Log references, timestamps, versions and reproduction steps |
| Hypotheses | Possible explanations and contradictory evidence |
| Workaround | Recovery procedure, limitations and prerequisites |
| Corrective action | Proposed change, owner, approval and recovery plan |
| Validation | Success criteria, observation period and recurrence checks |
| Residual risk | Remaining uncertainty, accepted limitations and decision owner |
| Review | Next action, responsible person and review date |
Keep the record short enough to maintain. Another engineer should be able to understand what is known, what remains uncertain and what happens next.
Measure improvement beyond ticket closure
Useful measures include repeat incidents for the same problem, time spent on repeated workarounds, user disruption and overdue corrective actions.
Define the scope and calculation consistently. A repeat-incident rate becomes misleading if ticket grouping changes halfway through the reporting period.
Review the measures with user feedback. A falling ticket count is encouraging only when people can actually complete their work.
Frequently asked questions
Does every incident need root cause analysis?
No. Prioritize serious impact, recurrence and unresolved risk. Routine incidents with a reliable documented resolution may not justify a separate investigation.
Can a small IT team use problem management?
Yes. Start with linked tickets, one named owner, a short investigation record and a regular review. A separate platform is not required to establish those habits.
Is reinstalling software a permanent fix?
It may be, but the reinstall itself does not prove it. Document what changed, test the original workflow and observe whether the failure returns.
What if the root cause cannot be confirmed?
Record the evidence, remaining hypotheses and known workaround. Agree who accepts the residual risk and what would trigger further investigation. Avoid presenting an unverified explanation as a confirmed cause.
Turn recurring issues into a defined improvement task
If your team repeatedly handles the same failures, choose one costly problem and work through it with clear ownership, evidence and follow-up.
If you are looking for IT support in Copenhagen, I can help connect hands-on troubleshooting with practical improvements across devices, Microsoft 365 and support workflows.