The ROI of XR training: real numbers from industrial use

Yes. In 20+ independent studies with 800+ trainees, XR training cut errors by 40%, sped up task completion by 3.25x and lifted quality-compliant output by 30% - while removing machine downtime, material waste and instructor time from the cost of training. The return shows up in four places: speed, errors, downtime and people.

The headline results

AtlasVR's outcomes come from 20+ independent studies, and its training methods are grounded in 32 published scientific papers:

• 40% fewer errors vs traditional training
• 3.25x faster task completion
• 30% more quality-compliant output
• 800+ trainees tested, 2,530 hours logged in XR

The studies and numbers in detail are on Why AtlasVR. What XR training is and how it works: What is XR training?

Where the ROI actually comes from

1. Faster time-to-productive

New and temporary staff reach competence sooner because they can practise the real task unlimited times. 3.25x faster learning means employees become productive sooner.

2. Fewer errors and less rework

A 40% error reduction flows straight into less scrap, less rework, fewer warranty issues and fewer safety incidents - the costs that quietly add up.

3. No machine or vehicle downtime

Traditional training stops production. XR doesn't. You can even train before the machine is on site. For a busy production line or workshop, recovered uptime alone can justify the investment. On the crane simulator, a whole class trains at the same time, each trainee with their own headset and controls, in an ordinary training room.

4. Experts freed, materials saved

No consumables, no equipment wear, and your scarce expert instructors are freed from repetitive demonstrations. How much that can matter shows in an example from our research: vocational schools do not train the pressing of large steel pipes at all, because the material costs hundreds of dollars per training session (Gisler et al., 2021). In VR, that cost disappears with every repetition.

A simple way to model it

You don't need a complex business case. Estimate the annual cost of:

1. Training downtime (machine/vehicle hours lost x hourly value)
2. Materials and consumables used in training
3. Instructor time spent on repetitive demos
4. Errors and rework attributable to under-training

Then weigh that against a one-time XR build plus headsets. For most industrial trainers, items 1-4 recur every year - XR converts them into a largely fixed, reusable asset.

Why these numbers hold up

AtlasVR is an ETH Zürich spin-off. Its training methods are grounded in published research and in research collaborations with industry leaders including Hilti and Geberit, and its outcomes are measured. Which studies are behind them and what they show is summed up, with all sources, in The science behind XR training. That is the difference between engagement and measurably better work. The modules show where it applies.

Frequently asked questions

Does XR training pay off?
Yes, when your employees learn hands-on procedures. In 20+ independent studies, XR training cut errors by 40%, sped up task completion by 3.25x and lifted quality-compliant output by 30%. The return shows up in speed, errors, downtime and people.

How do I calculate the ROI of XR training?
Estimate the annual cost of training downtime, materials and consumables, instructor time spent on repetitive demos, and errors and rework. Weigh that sum against a one-time XR build plus headsets. The four cost items recur every year; the XR build is largely fixed and reusable.

Does a machine have to stop for XR training?
No. People practise on a virtual replica while the real equipment keeps running. You can even train before the machine is on site.

Where do the numbers come from?
From 20+ independent studies with 800+ trainees and 2,530 hours logged in XR. The training methods are grounded in 32 published scientific papers. AtlasVR is an ETH Zürich spin-off.

Want a payback model for your operation? Book a 30-minute demo and we will build one with your numbers.

Sources

• Gisler, J., Holzwarth, V., Hirt, C. & Kunz, A. (2021). Work-in-progress - Enhancing training in virtual reality with hand tracking and a real tool. 2021 7th International Conference of the Immersive Learning Research Network (iLRN), IEEE. doi.org/10.23919/iLRN52045.2021.9459332 · Full text: ETH Research Collection