How to Measure Training Effectiveness Beyond Completion Rates: Lessons from Yoodli and Intellum

Most L&D teams still measure training effectiveness by completion rates. Few can show that anyone actually got better at the job.

That gap was the starting point for “What We Got Wrong About Readiness,” a webinar hosted by HR Executive on October 14, 2026. Mike Rich, Head of Partnerships at Yoodli, the skills readiness platform, sat down with Matt Gilley, Co-founder and Principal at Intellum, for a candid conversation about why checklist training falls short and how to build skills that show up on the job.

Gilley brought 26 years of perspective, going back to when online learning meant replacing the pen-and-paper safety quiz. Rich brought the view from Yoodli’s partner ecosystem, where training and methodology providers build skills practice on top of the platform. Here is what stood out.

Key takeaways

• Completion rates measure activity, not readiness. Track what learners can do, not just what they finished.
• AI lets every learner practice in their own context while being scored against the same skills rubric.
• Baseline skills before training so you can show leadership measurable lift.
• Start vetting learning platforms six months before renewal, and pilot with a small cohort before you scale.

Why training completion rates don’t measure readiness

Gilley told a story from early in his career. He took a safety director from a Savannah manufacturer out for golf, and halfway down the fairway the man asked: if I sign up, do I get fired? Gilley’s answer was that online training should free the safety lead to be on the floor, making sure people actually stay off the top rung of the stepladder. The point was never the record of completion. It was the behavior.

He framed the problem plainly: it is a data model problem, not a training design problem. If a system only records who finished, no amount of good design will show who is ready. That is why Intellum rebuilt its platform around how learners, content, enrollments and outcomes relate to each other, tied to event-level activity. The system can then reason about what someone did, not just whether they reached the end.

Rich described the shift as moving training from insurance to investment. Insurance is the course people take so the box is checked. Investment is the experience people walk away from saying it was a good use of their time, and that their team needs it too.

Gilley pointed to customer education as the model. Companies cannot compel customers to take training, so the experience has to be worth showing up for. His example was a small seller who learns to use an ad platform well, sells more, and in turn buys more ads. Bringing that same “want to, not have to” standard into employee education, he argued, is where the real upside sits.

How AI makes skills practice relevant without losing consistent scoring

When the audience was polled on the biggest barrier to engagement, two answers dominated: training that feels like a checkbox, and no time in the workday.

Rich’s answer to both is relevance. Generic discovery-call training used to be the only option. Now a rep can practice for tomorrow’s discovery call with a specific customer, a colleague can practice for a completely different call, and both are scored against the same skills rubric. That combination of individual context and a shared standard was hard to do at all a few years ago, and impossible at scale.

Timing matters as much as relevance. Rich described an approach Yoodli has been prototyping where a coach checks in during the two minutes before a call and reminds the rep what they are working on, such as closing. That is the moment the reminder is useful, not three months after the training ended.

Gilley added that the goal is for practice to become part of the daily routine, the same way people check their phones each morning. People make time for what proves useful to them. And because AI can turn a first draft of a module around in minutes rather than the old rule of thumb of 100 hours per hour of e-learning, teams can launch, measure and revise far faster than before. Rich’s caution: speed makes it easy to produce filler, so use the fast first draft as a starting point and spend the saved time refining it.

How to measure training effectiveness: baseline first, then show lift

Rich came to L&D from market research, where everything is measured as lift: where someone started and where they ended up. Training rarely works that way. The usual report says everyone finished and 75% said they would apply it. That no longer satisfies a leadership team.

His recommendation is to baseline before the training starts. Put people through the scenario you want them to master and score it the same way you will score it at the end. They will score low, and that is fine. They get immediate feedback, they walk into the training knowing which parts matter most for them, and you get a starting point you can report against.

Clari is a good example. The company wanted its customer-facing teams to lead more consultative conversations about revenue orchestration, and needed to prove to leadership that skills were actually improving. Using Yoodli alongside its own internal data, Clari defined the skills it cared about, measured a baseline, and tracked the lift. The resulting view showed strong gains in setting the agenda, some gains in closing, and clear gaps in aligning the value proposition and in client retention strategies. That one view also set the agenda for the next program.

Gilley cited a 2026 survey of 190 practitioners in which 81.6% named revenue growth as a primary objective for learning and 76% measured impact within three months of launch. Business outcomes, not activity, are the measure.

Rich added a caution. Connecting data across the LMS, HRIS and CRM is only half the job. He has seen dashboards comparing people who completed training with people who didn’t, and calling the difference impact. That may be correlation, not cause. Ask why the data looks the way it does, and whether you are surfacing the right business results at all.

How to choose L&D tools and plan an LMS migration

Every booth at every trade show now claims AI. Rich’s filter is breadth versus depth. Decide where your program needs broad coverage and where it needs to go deep, whether that is skills practice for sellers or microlearning for frontline workers. Every vendor will check the box on a feature. Where depth matters, you may need a platform built for that job.

Gilley described Intellum’s approach the same way: don’t build AI for its own sake, and don’t try to do everything. Integrate with strong partners through their APIs, and aim to be the hub. With MCP connections, he noted, it is now much easier to pull context from an LMS, an HRIS and other systems into one place than it was when stitching data together took an operations team.

On migrations, his advice was specific. Start vetting about six months before renewal and decide about three months out. Rushed migrations, often triggered by a leadership change or a budget cut, are where training gaps open up. As he put it, this is mission-critical technology, and when it goes wrong, it goes badly.

The final poll asked what makes adding or replacing a learning platform hardest. Budget was not the top answer. Technical integration and getting buy-in from IT were. Rich noted that most L&D leaders are instructional designers, not project managers, yet they are expected to handle security reviews, finance approvals and migration logistics. His suggestion: treat the vendor’s account executive as a resource. Ask what belongs on the one slide you need for leadership, and ask for the sales engineer when an integration needs solving.

Where to start: pilot your readiness program before you scale

Asked what one change they would make to a readiness program next quarter, both speakers said the same thing: pilot first. Gilley described a customer with close to 350,000 users who wanted to launch everywhere at once. He pushed for a 350-person pilot instead, then a larger one, adjusting at each step. You will get things wrong early, and a small group is where you want to find out.

Rich added that pilots are also where you tune the AI. Yoodli lets program owners set how much latitude the AI has to improvise. A cold-call scenario benefits from a lot of it. Safety certification should have almost none. Getting that dial right before you scale keeps results clean enough to guide the next version.

How long between baseline and reassessment depends on the skill. Leadership development takes longer. A new product pitch can be baselined Monday, trained Tuesday and checked Wednesday. RingCentral used to spend a full day of manager time reviewing new contact center hires’ recordings, and the judgment was still subjective. With consistent scoring, manager review is down to about an hour.

The three things to take back to your team:

1. Use AI to make practice relevant to each person while scoring everyone against the same standard.
2. Baseline before you train, so you can show leadership real skill lift.
3. Let your strategy drive tooling and migration decisions, not the other way around.

Gilley closed on why any of this matters. The best part of the work, he said, is watching someone grow from where they started into a senior leader. Readiness done right is how that happens.

Frequently asked questions

How do you measure training effectiveness beyond completion rates?

Score the skill itself, not attendance. Assess learners on a realistic scenario before and after training using the same rubric, then connect the change in scores to business results like revenue or retention.

How do you set a training baseline if you’ve never measured skills before?

Put learners through the scenario you want them to master before any training, and score it the same way you will at the end. Low scores are expected. The baseline gives learners immediate feedback and gives you a starting point to report against.

How long should you wait between a baseline and a reassessment?

It depends on the skill. Leadership and soft skills take longer to show change. A product pitch can be baselined, trained and reassessed within a few days.

When should you start planning an LMS or learning platform migration?

Matt Gilley recommends starting vendor evaluation about six months before renewal and making a decision about three months out. Rushed migrations are where gaps in training open up.

Watch the full session on demand through HR Executive, or see how Yoodli helps teams build and measure skills readiness.