Continuous improvement in enterprise support: A 30-day playbook
Continuous improvement in support processes is a repeatable cycle: you collect feedback, prioritize it, fix the cause and confirm the fix worked. For IT operations leaders, the test is whether the same failure or manual workaround keeps returning.
GROWMARK rebuilt its automation one job at a time after moving to SAP. Along the way, it dropped about a third of the jobs in its legacy scheduler because they were redundant or unused. After consolidating on RunMyJobs by Redwood, its team could view jobs across systems in one place.
That cleanup shows the value of questioning existing workflows. Support records can help you decide where to start. This guide provides a three-step feedback funnel and a 30-day playbook to test improvements with your automation vendor.
Continuous improvement, defined for support teams
Continuous improvement turns support signals into service and product changes on a regular cadence. An adaptive approach responds to customer needs while distinguishing a configuration fix from a product enhancement request. A configuration or runbook fix is one your team can resolve within existing settings. A product enhancement request is a change only the vendor can ship. It follows four steps:
- Collect feedback from every support channel
- Prioritize the impact and assess how often each issue occurs
- Assign the fix to your team or the vendor
- Confirm the fix and share what changed
Treat support as a ticket queue, and the software stays the same. Treat it as an input, and it gets better every quarter. When feedback drives the roadmap, you stop working around your tools and start relying on them.
Redwood Software reviews customer support history twice a year to identify trends and recommend training. Ask how those reviews will address your recurring incidents and which actions your team should own.
Turning user feedback into a feedback-driven support model
A support request should explain what failed and how it affected processing. Include the execution ID and environment, with the expected output and observed result. During migration, that context helps the vendor distinguish a setup issue from a product limitation.
When critical processes depend on your automation, agree on an escalation path for urgent incidents. Track enhancement requests separately so longer-term improvements do not obscure work needed to restore service.
Ask these three questions the next time you file a support request:
- How does this feedback reach your product team?
- How will you tell me what changed because of it?
- How do you keep me from explaining the same problem twice?
A partner committed to continuous improvement answers all three with specifics. Use the answers to check how feedback reaches an owner and how you will hear about the outcome.
Capture and prioritize user feedback in three steps
Many teams collect feedback and never act on it. A lightweight funnel turns that input into work with a clear owner. Your support team can use these three steps:
- Ingest: Collect feedback from tickets, chat, surveys and monitoring.
- Classify: Tag each item by workflow and business impact to distinguish symptoms from confirmed causes.
- Prioritize: Rank each item by severity and recurrence, then assess effort and assign an owner.
Make the priorities visible. Review the highest-impact items each week with owners and current status. A rare failure that threatens a processing deadline may warrant attention before a frequent inconvenience.
Signals worth combining
Pair user feedback with workflow telemetry to check which problems recur and what they affect. Telemetry can narrow the likely cause, but it does not confirm the fix is correct until you test the result. Combine these signals:
- Automation logs and runbooks for recurring incidents
- Operator feedback captured after recovery or handover
- Observability signals such as failed jobs and missed processing deadlines
- Ticket metadata and resolution notes
Responsive service starts with observability
For a recurring incident, support needs more than a ticket description. Responsive service depends on evidence from the affected job chain, including upstream delays that may explain a downstream failure.
Redwood Insights adds observability and analytics to RunMyJobs workflows. RunMyJobs also integrates SAP Cloud ALM and Dynatrace. A user-authored Datadog connector template brings monitoring data into workflows. Use this evidence alongside incident records to investigate recurring failures.
For each incident, link the affected workflow and execution history to the support request. Agree who will investigate and who will test the proposed fix. Workflow analytics and your service-desk records provide different parts of that evidence.
The test is whether the agreed change reduces recurrence. Record the current failure rate before deployment so the next review can compare similar workflow runs.
Close the loop with iterative development
Closing the loop means checking that your fix solved the problem without introducing regressions. Use the same evidence that led you to prioritize the issue. Apply this pattern to each change:
- Test and deploy: Validate a targeted fix or configuration change before production
- Monitor the result: Track the same signals that identified the issue
- Compare outcomes: Review before-and-after metrics alongside operator feedback
- Share the resolution: Tell affected users what changed and update runbooks
Iterative development also needs a decision when a fix falls short: revise and retest it or escalate with the new evidence. Apply that discipline during migration, when dependencies and support responsibilities may change.
An example: The move from SAP ECC to SAP S/4HANA
During a move from SAP ERP Central Component (ECC) to SAP S/4HANA, use the same feedback cycle to review changed dependencies and recovery procedures. RunMyJobs supports SAP and non-SAP orchestration and is the only workload automation solution in the RISE with SAP reference architecture. If RISE with SAP is in scope, agree which team owns each connection before testing the workflow.
RunMyJobs handles SaaS platform upgrades automatically. Most connections are agentless, and lightweight agents update automatically too. Your team still validates application connections and workflow behavior after relevant changes.
Signs your platform is built to improve
Look for these signs in any platform:
- Governance that keeps new capabilities safe to adopt
- Regular releases shaped by customer feedback
- Clear communication about what changed and why
- Automatic platform upgrades with clear customer responsibilities for validation
Process optimization across SAP and cloud workloads
Process optimization should reduce a recurring operational burden. Choose a job chain that repeatedly requires manual intervention, such as an SAP output feeding a cloud data process.
Record the failure condition and the recovery steps operators currently perform. Bring that evidence to the support review, then agree on whether the remedy belongs in the workflow configuration or requires vendor investigation.
An IT operations leader needs to know if the change reduced repeat incidents. Compare runs with similar volumes and dependencies and ask the operators if the workaround is still necessary.
For Amazon Web Services (AWS), RunMyJobs provides connectors for services including AWS Batch and Amazon SQS. For a recurring SQS handoff failure, compare message operations with downstream job results before and after the fix.
A quick test: map one recurring manual task your team repeats every month. Ask whether the agreed change reduced that work. If it does not, use the result to choose the next improvement.
Improve the user experience with governed autonomy
Once a recovery procedure is tested, AI can assist with investigation or workflow changes. Keep that assistance within the same feedback cycle by checking the recommendation and recording the outcome before expanding its use.
For this support workflow, two RunMyJobs capabilities are relevant:
- Operations Agent enriches alerts with job history and downstream impact, plus a service-level agreement (SLA) countdown and a recommended next action
- Workflow Builder creates workflow drafts from natural language or documented procedures, with IT review and approval before deployment
Pilot AI assistance on one recurring issue. Check if the suggested action fits your environment and helps the operator investigate. Record incorrect recommendations as feedback for the next review.
Use governed autonomy only within approved permissions and recovery procedures. An AI recommendation still needs validation before it becomes a reusable fix.
Your 30-day continuous improvement playbook
Start with one recurring incident and an owner. Use the first 30 days to establish a baseline and test a limited change:
- Review recurring tickets in week one and ask operators what remained unresolved after closure
- Record incident frequency and time to restore the affected workflow to establish a baseline in week one
- Select one high-impact change in week two and assign implementation and validation owners
- Test the change and recovery plan in week three before deploying to production
- Compare similar workflow runs in week four and report the results to affected users. Then, update the runbook and continue monitoring if the workflow has not run often enough to assess the change
Keep the cycle manageable
- Reuse a triage template for known issues
- Request operator feedback after the next affected workflow run
- Share a weekly update on the agreed fixes
For SAP or cloud workloads, begin with the handoff that generates repeat incidents. Track resolution time separately from recurrence, because closing a ticket quickly does not mean the underlying issue has stopped.
Next steps for a support model that keeps improving
A commitment to continuous improvement shows up in behavior. Look for these five signs in every vendor you trust with critical work:
- Feedback-driven service with a clear owner for accepted improvement requests
- Governed AI assistance with tested recovery procedures
- Iterative development with validation after relevant changes
- Process optimization measured against recurring operational work
- Responsive support that shares evidence and reports outcomes
Pick one recurring issue for your next support review. Agree on what will change and how you will check the result.
For broader automation adoption research, read the enterprise automation index 2026 report or request a demo of RunMyJobs and bring a recurring support scenario from your environment.