What eNPS is and how to calculate it
eNPS (Employee Net Promoter Score) is a simple employee-loyalty metric: how willing people are to recommend the company as a place to work. One question, a clear index, and a regular trend.
How eNPS is calculated
Employees are asked: “How likely are you to recommend the company as a place to work?” on a 0–10 scale. Answers of 9–10 are promoters, 7–8 are passives, 0–6 are detractors. eNPS = % promoters − % detractors, so the result ranges from −100 to +100.
How to read the result
A positive eNPS means promoters outnumber detractors. The absolute value depends on industry and culture, so the trend over time and the breakdown by unit matter more than a single number. An open comment on the score explains what drives it.
How often to measure
A once-a-year survey gives a snapshot but not timely reaction. Pulse surveys (monthly or quarterly) on a small sample catch the trend and the effect of changes. Anonymity and a sufficient sample size are needed for honest answers.
How to improve eNPS
The index rises not from the survey itself but from acting on it: analyzing drivers (manager, workload, recognition, growth), closing the feedback loop and communicating changes. Driver analysis shows which factors move the score most.
Key takeaways
- eNPS = % promoters (9–10) − % detractors (0–6), range −100…+100
- Trend and per-unit slices matter more than the absolute number
- Pulse surveys catch the trend better than a single annual survey
- The index moves from acting on drivers, not from the survey itself
FAQ
How is eNPS different from an engagement survey?
eNPS is one short loyalty metric (willingness to recommend). An engagement survey is a broader tool with many questions about different aspects of work. They are often used together: eNPS as a fast pulse, the survey as deeper diagnostics.
What counts as a good eNPS?
There is no universal threshold: the value depends heavily on industry, region and culture. Aim for a positive result and for growth over time against your own baseline.
Is anonymity required?
Yes. Anonymity and a sufficient sample size improve honesty; with too small a group results are withheld so participants cannot be de-anonymized.