Why ROI for Learning and Development is Hard to Measure?

've sat in enough budget reviews to know how this goes. The CFO asks what return the company is getting on its training spend. The L&D lead pulls up a slide with completion rates and satisfaction scores. The CFO nods slowly, in the way that means he's already moved on mentally. The budget gets trimmed.

It's not that leadership doesn't believe in training. It's that the numbers L&D teams present don't connect to anything the business actually cares about. And that gap (between what we measure and what matters) is why training is consistently the first budget cut when things get tight.

I'm not going to tell you measuring training ROI is easy. It isn't. But I will tell you that most teams are measuring the wrong things entirely, and there are better alternatives that are actually achievable without a six-month evaluation cycle.

Why Training ROI Calculation Usually Fails

The standard formula for training ROI looks clean on paper:

The problem isn't the math. It's that the inputs are nearly impossible to isolate.

Training isn't the only variable affecting performance. Market conditions change. Managers leave. A product update shifts how reps sell. A hiring wave drops average team experience. By the time you've tried to control for all of that, you've spent more on the evaluation than on the training itself.

Toby Newman, an L&D professional with over a decade of experience, put it plainly when we asked him about this: "We never really looked at ROI as, to be honest, the leaders were simply not interested in that." His team produced the standard metrics — number of sessions, participants, content consumed — but meaningful business attribution was never on the table.

That's not an unusual experience. CriticalPedagogue, an instructional designer with 19 years in the field, was even more direct in a recent r/instructionaldesign thread: "I've never seen a company even try to calculate ROI." Not occasionally. Never. The thread drew dozens of responses with near-identical answers.

A 2024 survey by the Association for Talent Development found that only a minority of L&D teams attempt to measure training at the business results level (Kirkpatrick Level 4). Most stop at Level 1 (reaction), or Level 2 (learning acquisition).

One r/instructionaldesign commenter put a number on the gap: "Kirkpatrick Jr himself said at an ATD session that they've only actually done it once and it was incredibly expensive." When the people most invested in a model's legacy admit it's almost never actually used, that's worth sitting with.

The issue isn't the Kirkpatrick framework. Levels 3 and 4 (behaviour change and business results) are exactly where the real signal lives. The problem is that getting there requires time, manager involvement, and data infrastructure that most L&D teams simply don't have access to.

The 3 Metrics That Actually Tell You Something

If full ROI calculation is out of reach for most of your programs (and honestly, it should be reserved for maybe 15% of what you run) here's what I'd track instead.

1. Time to proficiency

This is the metric I'd argue L&D teams are most consistently underusing. It's concrete, it's directly tied to business value, and it's a number leadership immediately understands.

Time to proficiency measures how long it takes a new hire or newly trained employee to reach independent, competent performance in their role.

Antoine Ménager, co-founder and CEO at Equos, tracks exactly this: "We track attempt frequency, session completion rates, and time to proficiency mostly." He also shared what actually moved the needle: "What's worked — making practice feel low-stakes so people repeat more. What failed early on — over-engineering feedback instead of letting learners just do more reps."

That's an underrated insight. Time to proficiency isn't just a number you read, it's a number you can influence, and the way you design practice directly affects it. If your onboarding takes new sales reps from six weeks to three and a half weeks to reach quota, that's revenue impact you can actually calculate.

2. Assessment variance

This is one most teams collect data for but rarely analyse properly.

Assessment variance tracks the spread of scores across your learner cohort, not just the average pass rate. Average pass rates are nearly useless. An 88% pass rate sounds fine until you notice that every failure is clustered in the same two modules, or concentrated in one regional team, or happening disproportionately among employees hired in the last six months.

Variance tells you where the actual knowledge gaps are.

One senior L&D professional we spoke to (who asked not to be named by company) described their approach: "Immediate measures we look at include attendance, marks on training-related projects, and surveys. More long-term signals are more efficient processing times — though that assumes an organisation was tracking production times in the first place."

The key phrase there is "more efficient processing times." That downstream signal is only visible if you're tracking who failed, not just how many. If you know the pattern, you can fix it. If you only know the average, you're flying blind.

3. Observable behaviour change

Logan Black, Head of People and L&D Manager, described this one better than most formal frameworks do: "I've observed that if nothing changes in how someone acts, there's no sustainable ROI. I tend to see behaviour change as the point where learning becomes real — but the actual ROI is what that behaviour produces."

That's the correct sequence. Behaviour change is the leading indicator. Business results are the lagging one. Most teams try to jump straight to business results without establishing whether behaviour changed at all, which is why the numbers don't hold up.

Behaviour change is measurable without a six-month research project.

Sara Niezgoda, a Knowledge Architect and leadership coach, tracks it practically: pulse surveys post-program, post-program check-ins with direct reports, and manager feedback one to three months later. She's specifically looking at whether feedback quality improved, whether 1-to-1s are more useful, whether psychological safety is increasing.

That's a lean approach. Manager observations, direct report surveys, before-and-after comparisons on specific behaviours you defined upfront. It's not academically rigorous ROI, but it's the closest most teams will realistically get to answering whether training actually worked.

What Actually Makes Measurement Work

I'd argue the single biggest failure in L&D measurement happens before any training runs at all.

Most programs define their evaluation approach after the fact — often after someone in leadership asks for data. By then, you're reverse-engineering metrics to justify a decision that's already been made. That's not measurement. That's theatre.

The teams that measure effectively do one thing differently: they tie training to specific business metrics before the program starts, not after. If you can't name two or three KPIs that the training is meant to influence, you're not ready to run it yet.

This is particularly true for leadership and communication training, where the link to business outcomes is least obvious. It's harder to quantify than sales training, where you can track deals closed or ramp time. But it's not impossible. Engagement survey results pre- and post-program, manager feedback scores, retention rates among teams led by trained managers — these are all signals, even if they're not a clean ROI figure.

The data infrastructure question is real. Most L&D teams don't have access to the business metrics they'd need to close the loop. That's an org-level problem, not an L&D problem. If you don't have access to performance data, the first conversation to have isn't about measurement methodology — it's about getting a seat at the table where that data lives.

When the Full ROI Calculation Is Worth It

I said earlier that full ROI calculation should be reserved for roughly 15% of programs. Here's how I'd pick that 15%.

Run the full Phillips ROI model (or a version of it) when the training is expensive, the outcome is measurable in monetary terms, and the stakes are high enough that leadership will actually act on the results.

Sales onboarding is a strong candidate. If you can show that reps trained on a new program ramped three weeks faster, and your average ramp-to-revenue is $40,000 per rep per month, that's a number with weight.

Compliance training is usually not worth the effort. The counterfactual (what would have happened without it) is too hard to model, and the cost of non-compliance is a threat rather than a return.

For everything in between, the three metrics above will serve you better than a formula that requires you to assign a dollar value to things that aren't easily monetised.

One alternative I found genuinely interesting came from Puzzled-Yam5109 in the same r/instructionaldesign thread — a metric they call TSPE, or time saved per employee: "If you can change behaviors and measure the time saved for an individual employee, you can scale that up to understand how much time you've saved across the organization."

If your average employee earns $50,000 a year and training saves them 30 minutes a week, that's calculable. It won't satisfy a CFO looking for revenue attribution, but it reframes L&D from cost centre to value creator — and that framing shift matters.

What a Modern LMS Should Be Doing for You

One reason measurement feels hard is that data collection is fragmented. Completion rates live in one system, performance data in another, manager feedback in email threads.

A platform like EducateMe pulls this together — tracking learner progress, assessment scores, and engagement patterns in one place, so variance analysis doesn't require a spreadsheet project. The AI Assistant handles things like rubric-based practice feedback, which makes it significantly easier to track behaviour change in skills like sales conversations or customer handling, where consistency of feedback matters.

That said, no LMS solves the underlying problem of not having defined your measurement approach upfront. The tool helps with data collection. The strategic part is still yours.