From innovation and knowledge to competitiveness and inequality, composite indices have become central to how we interpret complex socio-economic phenomena. These measures condense large amounts of data into a single number, supporting decision-making and measuring progress in various policy domains. Composite indices also allow policymakers and researchers to compare performance across countries and/or over time. While their appeal lies in their ability to simplify multifaceted concepts, it is important to recognize that such indices serve as guiding tools rather than precise measurements.

A composite index does not measure a concept directly. Instead, it signals its presence, strength, or direction by combining multiple proxies, each reflecting one aspect of a broader dynamic. The methodology behind this process is usually detailed in the reports published by the organizations that develop these indicators. For example, knowledge cannot be measured as a single observable variable. It emerges from patterns in education, research, infrastructure, and digital readiness, among other areas. Such indices aggregate these dimensions to provide a clearer narrative of these patterns.

The value of an index, therefore, lies less in the precision of its scores and more in its capacity to interpret multilayered ideas. It helps identify trends, gaps, and correlations that might otherwise remain hidden in raw data. When used correctly, it guides inquiry, inviting deeper analysis rather than replacing it.

Perhaps an analogy for how composite indices work can be found in the everyday act of asking for directions. Suppose you’re in Abu Dhabi, planning to travel to Dubai. You ask someone which way to go, and they point towards the road you should take. While their hand is unlikely to be pointed exactly 46.70º northeast, it still indicates the general direction you should take. Reaching Dubai, of course, depends on preparing your vehicle, refuelling, and taking the correct exits along the way, all of which are details you cannot reasonably expect from the person you asked.

The danger arises when composite indices are treated as definitive rankings or absolute truths. Doing so risks overlooking contextual differences, data limitations, and the assumptions embedded both in the construction process, such as variable selection, normalization, weighting, and aggregation, and in the variables themselves, which often carry implicit assumptions.

It is logical, then, that composite indices should be seen as signalling tools. They point towards opportunities worth exploring, or risks to be avoided, but they cannot, on their own, capture the full reality of the phenomenon or concept they seek to explain.

Nizar El Kotob is a research professional specializing in humanitarian affairs and development. At UNDP’s Knowledge Project, he contributes to the Global Knowledge Index and other strategic initiatives.