Understanding Multiverse completion rates — and why context matters

Qualification Achievement Rate (QAR) is a metric used by the Department for Education to measure the proportion of learners who successfully complete an education or training programme. In the government’s own framing, it gives “one measure” of a provider’s performance.

Multiverse’s current apprenticeship completion rate is 52.6% — below where we want it to be, and below its peak in recent years. It will improve by June, when the current academic year ends, and more improvements will follow as we invest in other changes required to get QAR back to where it belongs.

But we also believe, as the regulators do, that QAR is one measure of training quality. It is not the complete picture. There are specific reasons why ours sits where it does, and those reasons are tied to our mission to build a world where tech skills unlock people’s potential and output.

Three reasons for Multiverse’s current QAR

We’re an AI training pioneer

Multiverse invested early in making AI skills training available, before the apprenticeship system had created a designated AI standard. This created a structural mismatch between what employers needed and what the regulated framework prescribed — an almost inevitable consequence of a disruptive technology moving faster than the system designed to support it. 

We acted fast and first because our view is that when AI can already automate tasks someone has spent twenty years mastering, the responsible response as a technology training provider is to make training available to them now, not after they’ve been made redundant. But innovating ahead of the regulatory system has a cost, and some of that cost shows up in our QAR.

The launch of a designated AI apprenticeship standard has addressed this directly. And when the regulatory framework catches up with businesses' needs, so too will our QAR.

We prioritised inclusive enrolment

The single biggest driver of completion rates, whether it’s apprenticeships or degrees, is who you allow to start. On our AI programmes, we made a deliberate choice to optimise for access and tolerated lower completion rates as a result. We thought it more important to give as many people as possible a shot at AI readiness than to filter for those most likely to complete. That’s a decision we stand by, even if we’ve subsequently taken steps to create a more even balance.

The success of our more inclusive approach is reflected in a 50/50 gender split across our largest AI programmes, at a time when external research shows women are significantly less likely than men to engage with AI. Across our entire portfolio, 40% of learners did not previously hold a degree, and  26% of our learners have a contextual flag, meaning they meet one or more markers of socio-economic disadvantage, such as being care-experienced. 

Our impact-first programme design

Multiverse apprenticeship programmes are designed so learners start solving real problems at work from day one, not after 18 months of theory. Many learners deploy new skills during their programme, earn the promotion or pay rise they came for, and then leave before completion. QAR registers that as a dropout but we see it differently.

Our data shows that 45% of learners receive a promotion during or within 12 months of their programme, and 60% secure a pay rise. These are strong proxy measures for employers receiving the outcomes they commissioned. If someone achieves what they set out to achieve, for themselves and their business, and then moves on, we don’t consider that a failure.

What the data really shows

The countless individual, impactful learner outcomes that sit alongside our QAR tell the full story of the value Multiverse delivers.

In a typical example, a Royal Free London NHS Foundation Trust administrator digitised an entire patient journey during his apprenticeship — doubling his department's daily caseload from 30 to 60 patients, reducing non-discharged patients by 93%, and cutting waiting times from over 30 minutes to 10. He was promoted to data coordinator as a result. That is a meaningful measure of success, and the kind of return we routinely track for our customers.

Additionally, across our customer base, 98.4% of learners who complete their course achieve a pass or above. Net Revenue Retention stands at above 100%, meaning employers consistently invest more with Multiverse after their first programme. Last year, Multiverse accounted for more than half of total growth in apprenticeship starts across the entire system. This is the side of the story that completion rates don’t capture.

Working with the system, while sticking by our convictions

As one of the largest apprenticeship providers in the country, Multiverse takes its responsibilities to the wider system seriously. Wherever regulators identify areas for improvement, we will act on them. Not as reluctant concessions, but because that’s how a serious provider engages with a regulatory framework that it’s committed to improving alongside. 

We know what it takes to have high completion rates and we know what we need to do to get back there. Elsewhere, our completion rates are higher: our degree-level programme completes at c.70%, and our software engineering programme sits well above national average at 90%.The changes underway to our apprenticeship programmes in enrolment criteria, programme design and how we support learners through to the finish line are already moving the dial and will be reflected in our numbers following the end of this academic year.

What will not change, however, is our conviction that programme completion is a means to an end, but not the end in itself. Our mission is to create a workforce equipped to win in the AI era. Everything we build, measure and invest in is pointed towards that.

Read our latest Impact Report to discover how Multiverse is transforming the way people learn and work, and helping thousands of workers unleash AI's potential. Or get in touch to learn more about how Multiverse can support your workforce.

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