Optimization in SAP best practices

Optimization

Optimization best practice is about continuously improving performance, cost and process efficiency, driven by measurement, not guesswork.

Quick answer

Optimization keeps a growing system fast and cost-effective.

Key takeaways

Measure first (ST03, ST05, HANA plan analysis) before optimising.
Fix the biggest bottlenecks (usually custom SQL/code) first.
Push logic to the database (CDS/Open SQL) on HANA (code-to-data).
Watch out: Skipping the discipline under delivery pressure.

Key practices

Measure first (ST03, ST05, HANA plan analysis) before optimising.
Fix the biggest bottlenecks (usually custom SQL/code) first.
Push logic to the database (CDS/Open SQL) on HANA (code-to-data).
Partition heavy jobs; schedule batch off-peak.
Right-size resources; archive old data to control volume.

Why it matters

Optimization keeps a growing system fast and cost-effective. The golden rule is measure-then-optimise: target the real bottleneck, change one thing, and re-measure. Blind tuning wastes effort and can make things worse.

Common pitfalls

Skipping the discipline under delivery pressure.
Not documenting decisions.
Ignoring the clean-core principle.

Practice challenge

+0 XPStreak ×0

Question 1 of 3

Which statement is true of Optimization?

Frequently asked questions

What does the term Optimization refer to in SAP?

Optimization best practice is about continuously improving performance, cost and process efficiency, driven by measurement, not guesswork.

What else is worth knowing about Optimization?

Optimization keeps a growing system fast and cost-effective.

What is the practical takeaway on Optimization?

Measure first (ST03, ST05, HANA plan analysis) before optimising. Fix the biggest bottlenecks (usually custom SQL/code) first. Push logic to the database (CDS/Open SQL) on HANA (code-to-data).

What tends to go wrong with Optimization?

Skipping the discipline under delivery pressure. Not documenting decisions. Ignoring the clean-core principle.