SPSS continues to matter because it gives researchers, M&E specialists, and programme teams a dependable route from data cleaning to descriptive analysis and reporting. Its interface lowers the barrier for non-programmers while still supporting disciplined workflows.
For many NGOs, universities, and government teams, the value of SPSS is not novelty. It is consistency, familiarity, and fit for structured survey data. When teams need clear output, repeatable analysis, and accessible training pathways, SPSS remains a strong option alongside R, Python, and SQL.
The point is not to choose one tool forever. Strong analytics practice matches tools to purpose. SPSS remains part of that toolkit because it supports credible analysis in settings where speed, quality, and usability all matter.