SHLC Educational ROI Dashboard

SHLC Wealth Index

See how better GCSE grades and university degrees increase your child's lifetime earnings.

What is Undiscounted?

The total money your child will earn over a 45-year career. This is the actual cash they'll see in their bank account.

What is Discounted (PV)?

What those future earnings are worth in today's money after accounting for inflation (3.5% rate).

1. CUMULATIVE GCSE IMPACT (AVERAGES)

Choose GCSE subjects to see how higher grades increase lifetime earnings.

+1 Grade +4 Grades
Avg. Discounted Return £0
Avg. Cash Value £0

2. UNIVERSITY ROI HEATMAP (AVERAGES)

See how different university degrees affect your child's career earnings.

Degree Trajectory

Select a degree above to see specific career earnings data.

3. INVESTMENT LOGIC

Research suggests an average of 6 hours of targeted support correlates to a 1-grade gain.

Avg. Net Profit (PV)

£8,320

Book Consultation

What subject choices are actually worth over a career

This index compares typical lifetime earnings across GCSE and degree subjects. It is a blunt instrument and it deliberately measures one thing, so it is worth being clear about what it can and cannot tell a fifteen year old choosing options.

Why maths sits where it does

Maths appears near the top of almost every earnings analysis, and the reason is not that maths itself is lucrative. It is that maths is a gate.

A grade 4 in maths is required for most sixth form courses, most apprenticeships and a very large share of employers. Without it, a student is not choosing between careers, they are choosing between whichever ones remain open. Higher grades open A level sciences, economics, computing and engineering, which are themselves gates to other things.

So maths earnings figures are measuring optionality more than they are measuring the subject. That is still worth knowing, and it is a more honest framing than "maths pays".

What the numbers do not capture

  • Fit. A student who is miserable in a subject will underperform in it, and underperforming in a high-earning subject beats nothing about performing well in another.
  • Variation within a subject. The spread inside any single subject is far wider than the gap between subject averages.
  • Non-financial return. Teaching, nursing and the creative industries sit low on earnings indices and high on most measures of whether people want to keep doing them.
  • Changing markets. These figures are backward looking. They describe what previous cohorts earned, not what this one will.

Useful way to use this with a teenager: not "pick the one at the top", but "here is what the door being closed costs". The argument for maths is about keeping options open, and that is an argument most fifteen year olds actually accept.

How to have the options conversation

Two questions do most of the work. What do you want to keep possible, and what would close if this subject went badly?

That framing avoids the trap of asking a fifteen year old to name a career, which almost nobody can do usefully, and it turns subject choice into a decision about flexibility rather than about prediction.

Our guide on what a GCSE maths grade is worth makes the same case with the numbers laid out, and the piece on navigating subject choices covers the wider decision.

If maths is the subject at risk

A grade 4 is the gate, and it is reachable from further back than most families assume with the time still available.

Our interactive lessons start at the genuinely basic version of each topic, and the grade boundary tool will tell you how far off a grade 4 actually is, which is usually less far than the last mock felt.

Questions parents ask

Where does the data come from?

Published earnings analyses by subject, which draw on longitudinal education and tax data. They describe past cohorts.

Treat them as a guide to which doors tend to stay open rather than as a prediction for any individual.

Should my child pick subjects based on earnings?

Not primarily. Fit and grades matter more, because a good grade in a mid-earning subject beats a poor one in a high-earning subject on every measure.

Earnings data is most useful for the negative case: understanding what dropping a subject closes off.

Where to go next