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Understanding CAGR

Further understanding Compound Annual Growth Rate as it relates to QS HolonIQ datasets

Updated over 3 weeks ago

What is CAGR?

CAGR stands for Compound Annual Growth Rate.

In very simple terms, CAGR tells us:

“On average, how fast did something grow each year over a period of time?”

Instead of looking at lots of yearly changes, CAGR summarises growth into one clear, easy-to-compare number.

You can think of it as the smooth, long-term growth speed of a metric.

Imagine an occupation had:

  • 1,000 employees five years ago

  • 1,500 employees today

CAGR answers the question:

“What steady yearly growth rate would explain going from 1,000 to 1,500 employees over five years?”

It does not mean growth happened evenly every year. It simply gives a clear summary of the overall trend.


Why CAGR is used in QS HolonIQ datasets?

Datasets focus on long-term performance and trends, not just single-year results.

CAGR is useful because it:

1. Shows long-term progress

CAGR highlights:

  • sustained improvement

  • consistent strategic growth

  • long-term direction


2. Allows fair comparison

Markets differ greatly in size and context.

CAGR helps compare:

  • large and small regions

  • mature and emerging markets

  • fast-growing and stable markets

Because CAGR is a percentage, it focuses on rate of growth, not raw size.


3. Why not just use year-over-year (YoY) growth?

Year-over-year growth can be misleading because:

  • one exceptional year can distort results

  • data can fluctuate due to reporting changes

  • external events (e.g. COVID, funding cycles) can cause temporary spikes or drops

CAGR solves this by:

  • smoothing short-term ups and downs

  • reducing the impact of one-off events

  • reflecting the overall trend, not noise

This leads to more stable, fair, and meaningful comparisons.


Common QS HolonIQ datasets where CAGR may be applied

You will find CAGR:

-In the Labour Data & Reports from the Labour Market Intelligence Dataset

-In the Flows Data & Reports from the Global Student Flows Dataset


Key takeaway

CAGR helps analysis by:

  • summarising growth in a simple way

  • focusing on long-term performance

  • avoiding over-reaction to short-term changes

In short, CAGR helps ensure rankings reward consistent progress, not just temporary success.

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