SAP business app support teams optimize process flows with New Relic

Business-process-flow challenges

Business processes that rely on SAP infrastructure, such as order-to-cash and procure-to-pay, span across multiple systems and can be interrupted by Intermediate Document (IDoc) errors, remote function call (RFC) communication failures, and batch job delays or failures. 

Slowed or stalled business processes—from whatever cause—ultimately result in negative financial impact to the business. To expedite resolutions and ensure better business process uptime, organizations and their IT teams need to be able to trace any SAP issues end to end at the transaction, order, or invoice level. 

Manual troubleshooting slows resolution times

Despite these high stakes, when organizations that use SAP for mission-critical business processes become aware of an incident, addressing the root cause and remediating the issue just using existing monitoring tools like SAP Solution Manager can require considerable effort. Resolution is often performed manually, requiring digging through numerous SAP screens, tables, and logs. And further complications arise when the business and IT teams aren't in sync because systems, operational data, business process knowledge, or other information are not shared.  

Evolve from monitoring to intelligent observability 

New Relic monitoring for SAP solutions enables SAP business application support teams to quickly understand the performance and overall health of entire business processes. Users can eliminate the manual and slow processes of notification and quickly identify the root cause of performance problems or bottlenecks within the application and/or infrastructure layers.

Optimize Fiori end-user experiences

Optimizing Fiori application response times and experiences is easier with New Relic Monitoring for SAP solutions. You can get automatic insights into the root causes of issues using an end-to-end trace from the SAP Fiori frontend, directly to the SAP backend systems, including databases and programs. Distributed traces are available for every transaction that’s executed, without the need to install any agents in your SAP production systems.

Identify process bottlenecks faster 

In addition to monitoring your SAP system and application layers, with New Relic you can also monitor key business process flows at the transaction, order, or invoice level. For example, see the distribution of background jobs over time to quickly identify any uneven distribution and easily zoom in on a timeframe where spikes or anomalies occur to determine root cause and take corrective action.

Improve operational efficiency: MTTD, MTTA, and MTTR

When you shift from monitoring to intelligent observability there are three operational metrics that can be reduced: 

• Mean time to detect: MTTD is the time it takes an organization to detect a problem with their SAP systems. New Relic reduces time to detection with AI-powered proactive alerts. These alerts are easy to set up, with no need for traditional static thresholds. Instead, they use dynamic baselining that automatically learns patterns over time and detects anomalies, allowing for more accurate alerts and early detection. This is how you can proactively eliminate potential interruptions.
• Mean time to acknowledge: MTTA is the time it takes a team member to recognize an incident and react. Using at-a-glance views and centralized dashboards of your entire SAP ecosystem that are shared by all admin and support teams, New Relic helps organizations eliminate the previously manual and slow correlation of signals and root cause analysis caused by data silos and isolated teams.
• Mean time to resolve: MTTR is the time it takes from when an incident occurs to when the issue is resolved. New Relic reduces time to resolution with visualizations that combine end-to-end views and traces of multiple SAP systems and non-SAP systems in order to correlate various signals and drill downs to specific errors. As a result, the ability to resolve incidents can be significantly improved.