Performance monitoring T-Codes in SAP
With such a critical, diverse and global SAP implementation, Fonterra decided to use an APM solution to assure uninterrupted access and a high quality end-user experience with the SAP ERP, worldwide. Fonterra extended the out-of-box reporting with a number of custom built reports that enabled focused views into specific SAP performance use cases relevant to Fonterra.
How Mexico is Different from São Paulo?
One of the first problems discovered by the operations team was that certain SAP transactions at the subsidiary in Mexico were much slower than other offices. Both offices in Latin America, i.e., in Mexico and São Paulo, unlike the subsidiaries in Tokyo or Dubai, are not connected directly to the SAP servers in New Zealand. Instead the traffic is routed through the office in the USA. However, only the office in Mexico was experiencing performance problems.
The operations team from Fonterra compared application and network performance between subsidiaries (see ). As expected, network time, network performance and client RTT metrics show that the quality of the network in LATAM sites is worse compared to other offices, especially the main office (Fonterra Centre). Still, the overall application performance (reported by operation time and server time metrics) does not seem to be affected by the geographical location of the branch office.
This report confirms that there is additional network latency from Mexico and São Paulo (see ) but it does not explain why employees from Mexico report poor performance while those from São Paulo do not? This required a deeper inspection into the transaction times across the four remote offices: São Paulo, Mexico, Dubai and Tokyo. All transactions had comparable operation times except for Sales Order Status Report. This transaction was more than three times slower in Mexico than in other locations, including São Paulo (see ).
Figure 3. Comparing performance of transactions across subsidiary locations shows the Sales Order Status report is significantly slower in Mexico than in São Paulo ↩
Lesson Learned: Monitor and Optimize T-Code Attributes for Performance
The question remained as to what was the key difference between Mexico and São Paulo? In order to answer this question the team looked even deeper into the specific SAP transaction code (T-Code) and the specific attributes that were used by users from the various locations. This revealed that users from Mexico were not using the specific attributes that were optimized for the specific custom T-Code.
In this case the problem was not related to the SAP application or the infrastructure, but rather a training issue. It turned out that employees from Mexico, who had not yet received adequate SAP training, did not know how to optimize attributes passed to the reports based on custom T-Codes.
To avoid similar performance problems in the future, Fonterra started to monitor performance of reports per employee (see ) to determine who else might need additional training to improve their skills in using SAP.
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