The Happiness Index: what it measures and what it doesn't

The Happiness Index (HI) starts from a single question — "How happy are you at work today?" — with four answer options, from "Pretty bad" to "Awesome". It is available every day; each person answers when and if they want to.

Answers are mapped onto a 0 to 100 scale and aggregated with a recency-weighted rolling window: recent votes weigh more than older ones. This gives the index two properties by design — it reacts to what is happening now, without swinging because of a single bad Monday.

Aggregates are always computed at team, area or company level. Never individually.

The HI is a measure of momentary affect and, cumulatively, of subjective wellbeing: each person's own perception of how they are. This matters: happiness is not something we define on people's behalf, it is something each person reports for themselves. That is how the field has defined wellbeing since Diener's foundational work (1984), and it is the same principle the World Happiness Report tradition rests on.

The HI is not an engagement score. Mood and engagement are related but distinct constructs, and confusing them is a common mistake in this industry. In our model, the constructs closest to engagement live in the Scores; the HI is the fast thermometer.

Single-item wellbeing measures have a real research pedigree: they show adequate reliability and strong convergence with multi-item scales (Abdel-Khalek, 2006), and the OECD Guidelines on Measuring Subjective Well-being (2013) endorse single-item affect measures for exactly this kind of repeated, low-burden measurement.

What a single item loses in granularity it gains in frequency — and frequency is what makes the time series work.

Sensitivity to real events. When Spain declared the COVID-19 lockdown in March 2020, the HI dropped sharply across our entire client base: an average fall of 19 points within days, visible company by company and team by team. An indicator that had not moved under the largest workplace disruption in decades would not be measuring anything. It then recovered at different speeds in different organisations, which was itself diagnostic information.

Relationship with turnover. In peer-reviewed research on Happyforce data (Berengueres, Duran & Castro, 2017), happiness-derived variables contributed to ranking employees by turnover risk. The most interesting finding was methodological: absolute average happiness was not a significant predictor, while relative happiness — the individual level normalised by their company average — was among the top three.

The trend is the signal, not the absolute number. Read evolution and deviation rather than snapshots, and always alongside the number of responses behind them.Keep reading