Proactive support approach: How to reduce downtime and resolve issues faster

At GROWMARK, an agricultural cooperative with several business units, SAP jobs ran on SAP’s native scheduler and everything else ran on a separate on-premises scheduler. The team coordinated the two by clock time: an SAP job at three minutes past the hour, a downstream job at 23 past. When a long-running SAP job overran, the downstream job started anyway and reported success despite the missing output. Someone had to notice that the job finished unusually quickly or produced no results.

For an IT operations leader, that is a visibility problem before it becomes a support incident. Proactive support needs to cover how workflows behave and how the team responds when a dependency fails.

After GROWMARK moved to RunMyJobs by Redwood, every job sits in one view and later jobs recognize the status of earlier ones. The team also dropped about a third of the jobs in its legacy scheduler as redundant or unused. Read the GROWMARK customer story.

What is a proactive support approach?

A proactive support approach combines workflow visibility with tested recovery procedures, so your team can act before a delay affects the business. It also defines when to involve the vendor’s support team. 

The approach rests on five practices:

• Real-time visibility: Catch warning signs while there’s still time to act
• Problem-solving tools: Help operators diagnose common issues and escalate with relevant evidence
• Knowledge sharing and user training: Capture tested recovery steps
• Governed AI: Assistant diagnosis within defined permissions
• Continuous improvement: Measure results and fix the gaps you find

Redwood Software provides RunMyJobs alongside support services. To make that support effective, give operators a view of the full job chain and a way to pass evidence to a support engineer.

Real-time visibility: Downtime reduction starts with the dependencies

A delayed job or a missing output can put downstream work at risk even when no system is down. Monitor the handoff and job status, and route the warning to the team that can act.

Start with one question: can you follow a job chain from SAP through Amazon Web Services (AWS), including the dependencies between them? Check that the view shows whether each handoff was completed and the individual job status. Then ask a harder question: when that same chain crosses from SAP to AWS, does your team have a single way to orchestrate and troubleshoot it, or does each environment still need its own tooling?

RunMyJobs is an event-driven cloud orchestration platform for SAP and non-SAP workloads. Your team can follow managed workflows across cloud and on-premises systems in one view.

Redwood Insights adds observability and analytics across those workflows. RunMyJobs connects with SAP Cloud ALM and Dynatrace, while a user-authored Datadog connector template brings monitoring data into workflows. Use these integrations to connect a late job with its downstream impact.

Core elements of prevention:

• Workflow checks: Monitor the jobs and handoffs that matter most
• Remediation steps: Defined responses for common failure modes
• Runbooks: Clear instructions with safe retry conditions and rollback steps
• Change governance: Test and approve changes before production deployment

Map your highest-impact job chains. Give each one a defined check and a documented recovery action. Assign an owner so an alert reaches someone who can respond.

Problem-solving tools for your operations team

User empowerment means giving operators enough context to diagnose common issues and recognize when to escalate. Define their access to recovery actions before an incident, including which changes need approval.

Different teams need different support. Give each role what it uses:

• Developers: Clear API and event contracts for automated workflows
• IT leaders: One view of critical processes across hybrid environments
• Operators: Concise runbooks with rollback steps
• SAP teams: Documented procedures for SAP S/4HANA and SAP Cloud ERP tasks

RunMyJobs handles SaaS platform upgrades automatically. Most connections are agentless, and its lightweight agents update automatically. Your team still manages application connections and workflow recovery procedures.

Strong problem-solving tools share a few traits:

• Dashboards that show failed jobs and their run history
• Dependency views that help trace upstream delays
• Audit trails that show what changed during the incident

Run a two-hour simulation of your most common incident. Tie each step and capture every decision. Use the slowest step to identify what to automate or document in a tested runbook.

Knowledge sharing and user training make every fix stick

After the exercise, capture the recovery steps before the next shift takes over. Knowledge sharing keeps tested fixes available to the people who need them. Name one owner, usually the lead operator for that job chain, to keep the knowledge base current.

Build the habit in four steps:

• Identify repeat incidents: Review the past six months of support records
• Document the resolution: Keep each fix in a shared, searchable place
• Test reusable fixes: Turn recurring fixes into templates and test them in staging
• Review after changes: Check runbooks and automation logic every quarter and after workflow changes

User training helps operators apply those procedures consistently. Redwood University offers role-based learning, so new operators can practice the tasks they own. Pair training with tested runbooks so another operator can handle a recurring issue.

After your next incident, write a short, plain-language summary of what happened and how you fixed it. Share it widely. Over time, these summaries become a knowledge base that the next operator can use.

Governed AI that speeds up issue resolution

With tested runbooks in place, AI can help operators investigate exceptions. Redwood’s agentic orchestration runs agents inside controlled workflows with auditability and human oversight. Operations owns the outcome at every step: AI suggests, a named approver signs off.

Redwood RangerAI provides troubleshooting guidance through Automation Co-pilot. Operations Agent enriches alerts with job history and downstream impact, plus a service-level agreement (SLA) countdown and a recommended next action.

Use these controls for an AI-assisted recovery pilot:

1. Start with investigation: Use a read-only assistant to suggest next steps for a failed job
2. Define recovery permissions: Set approval steps for automated remediation
3. Scope external access: If an external agent needs to act on workflows, use RunMyJobs’ Model Context Protocol (MCP) server to expose business logic to trusted agents. This step isn’t required, and access should go through approved permissions
4. Review agent actions: Record the outcome and keep people in control of exceptions

Pilot an assistant on one recurring job failure. Check whether its recommendation is correct for the environment and whether an operator can use it to shorten investigation time. Record incorrect suggestions before expanding the pilot.

Customer success: What to expect from a support partner

The same recovery procedure also needs a clear escalation path when your team cannot resolve the issue. Before you choose or renew a platform, ask four questions:

• What response and escalation commitments apply to each incident severity?
• Who owns platform, maintenance and application-level recovery?
• What training and knowledge resources do your users get?
• How does the vendor help you find issues before they cause downtime?

RunMyJobs has a 99.95% SaaS uptime commitment. Redwood also reviews support history twice a year to identify recurring incidents and recommend training. Its Customer Success team provides health checks and upgrade guidance. Review the support agreement for response terms and the recovery responsibilities of each team.

Platform availability is only part of the picture, so also check the security credentials behind it. Redwood holds ISO 27001 and TX-RAMP certifications and a SOC 2 Type II attestation. Customers include Airbus, Allianz, Boeing, Ford and UBS. See more RunMyJobs customer stories.

Metrics that prove continuous improvement

Use support reviews to identify recurring failures and gaps in recovery procedures. Then check whether the changes reduce disruption.

Track these metrics:

• Mean time to detection, including missing-output incidents
• Mean time to resolution (MTTR)
• Downtime minutes and number of missed processing deadlines per month
• Percentage of incidents resolved by runbook or automation
• Automation coverage for critical processes

Use Redwood Insights to review workflow performance alongside incident records from your service desk. Keep detection time separate from recovery time so you can see which change helped. Fewer interruptions and less time spent recovering are operational efficiency gains your team can measure.

Set a 90-day goal to reduce MTTR against your current baseline. Publish a weekly dashboard and use the gaps you find to plan the next quarter. Name an owner for that dashboard, the same person accountable for the metrics improving.

Your first step toward proactive support

Start small. Pick one high-impact job chain to review in the next 30 days. Test what happens when an upstream task finishes late or produces no output. Assign a recovery owner and document the response. Compare detection and resolution times before and after the change. It’s the same discipline that helped GROWMARK turn a hidden scheduling gap into measurable, faster resolution times, which are results you can aim to replicate on your own job chains.

Explore broader automation adoption findings in the enterprise automation index 2026 report, or request a demo of RunMyJobs to review one of your own support scenarios.