---
title: Adoption Metrics That Actually Matter
description: Most L&D teams report completions because it's the only number their systems track. Here's how to map one program to the metrics leadership watches.
image: https://learning.iorad.com/hubfs/Field%20Notes.png
---
[](https://www.iorad.com/)
- Product
#### Individual
[Tutorial Privacy Control who views your tutorials](https://www.iorad.com/pricing/feature/tutorial-privacy) [Mask Data Control who views your tutorials](https://www.iorad.com/pricing/feature/mask-data) [Basic Audio Text-to-speech & custom voiceovers](https://www.iorad.com/pricing/feature/basic-audio)
#### Team
[Branding Add custom branding](https://www.iorad.com/pricing/feature/custom-branding) [Premium Audio Neural voiceovers and CC](https://www.iorad.com/pricing/feature/premium-audio) [Collaboration Co-edit and publish tutorials](https://www.iorad.com/pricing/feature/team-collab) [Analytics See tutorial performance](https://www.iorad.com/pricing/feature/analytics)
#### Enterprise
[Translations Automatic language translation](https://www.iorad.com/pricing/feature/translations) [Team Accounts Allocate separate accounts](https://www.iorad.com/pricing/feature/team-collab) [Encrypt & Anti-Track Strict compliance & additional data protection](https://www.iorad.com/pricing/feature/encrypt-and-anti-track)
[All plans & Features →](https://www.iorad.com/features)
- Resources
#### Support
[Help Center](https://www.iorad.com/resources/help-center) [Learning Hub](https://learning.iorad.com) [Schedule Demo](https://www.iorad.com/demo)
#### Customers
[Testimonials](https://www.iorad.com/testimonials) [Case Studies](https://learning.iorad.com/customer-stories?_ga=2.48225895.1718347252.1788801042-1263284910.1780521832)
#### Marketplace
[Partnerships](https://www.iorad.com/partner-programs) [Integrations](https://www.iorad.com/connectIntegrations) [Services](https://www.iorad.com/services)
#### Company
[Privacy Policy](https://www.iorad.com/privacypolicy) [About Us](https://www.iorad.com/meet-the-team)
- Use Cases
[EDU](https://www.iorad.com/use-cases/education) [Customer Training](https://www.iorad.com/use-cases/customer-training) [Sales Enablement](https://www.iorad.com/use-cases/sales-enablement) [Learning & Development](https://www.iorad.com/use-cases/learning-and-development)
[HR](https://www.iorad.com/use-cases/human-resources) [Product Management](https://www.iorad.com/use-cases/product-management) [I.T.](https://www.iorad.com/use-cases/information-technology) [Operations](https://www.iorad.com/use-cases/operations)
[All Use Cases →](https://www.iorad.com/use-cases)
- [Pricing](https://www.iorad.com/pricing)
[Try it Free](https://www.iorad.com/signup) [Sign In](https://www.iorad.com/login)
The Adoption Curve
# Adoption Metrics That Actually Matter
*Most L&D and enablement teams report completions because it’s the only number their systems record on their own. The teams that prove impact define performance first: they borrow an outcome the business already tracks, measure the work people produce, count the friction a program should remove, and check whether people can do the job without help.*
[Learning Hub](https://learning.iorad.com/) → [Adoption Curve](https://learning.iorad.com/the-adoption-curve) → Adoption Metrics That Actually Matter
In this week's Field Notes edition of The Adoption Curve, we look at why so many L&D and enablement teams walk into leadership reviews with a dashboard full of completions, and walk out having been asked "so what?"
The problem is rarely a lack of data. It is a lack of definition.
This edition examines how learning and enablement teams can move from reporting activity to proving impact by defining performance first, then measuring the work and the friction that sit between a program and a business result.
## What you'll learn:
- Why completion rates win by default, even on teams that know better
- How to map any program from the business outcome down to one signal you can track
- What to measure when a usage number tells you people showed up but not whether anything changed
### About Field Notes
Each week, we speak with industry experts and iorad users around the world to understand how they're solving challenges in Enablement and L&D. We share those stories through The Adoption Curve.
But across those conversations, patterns have started to emerge.
Field Notes is where we capture them: distilling insights from interviews, customer feedback, and real-world experience into the trends that matter most.
## How do you measure whether training actually worked?
Every learning team has a number it can pull in thirty seconds.
Completions. Attendance. Satisfaction scores. Hours of content consumed. They show up in the LMS automatically, they trend in the right direction, and they fit neatly on a slide.
And they rarely answer the question leadership is actually asking.
How do you prove a program worked when the metric your system tracks has nothing to do with the result the business cares about? What should you measure when you can't draw a straight line from training to revenue? And how do you get there without a data team or a new analytics tool?
For most teams, the gap between reporting activity and proving impact comes down to one thing:
Definition.
## Why completions win by default
Nobody chooses vanity metrics on purpose. Completions win because they are the only number recorded without anyone deciding to record it. Everything else has to be defined before launch, and by the time someone asks for impact, the window to capture a baseline has usually closed.
[Heidi Kirby](https://learning.iorad.com/the-adoption-curve/how-to-say-no-in-ld), founder of Useful Stuff, ran into this directly when she led customer education. A leader asked her team to measure the success of a new onboarding program by course completions. She pushed back.
A user who finishes every module may be one who couldn't find the answer they needed. A user who watched ninety seconds and went back to work may be your best outcome.
Completion measures time spent with the content. The business is paying for what happens after.
So Heidi's team tracked different signals: how many customers came back more than once, and where people paused, rewound, or dropped off a video. They borrowed the video platform their marketing team already used.
The data was never the hard part. Deciding what to look for was.
## Start by defining performance
[Nick Lawrence](https://learning.iorad.com/the-adoption-curve/enablement-that-drives-revenue), Manager of Global Sales Enablement at Databricks, started his career as an instructional designer who saw every problem as a knowledge gap. Over time, his view shifted from what people know, to what they do, to what they actually produce on the job. That shift led him to a simple model with three parts: **outcomes, outputs, and obstacles.**
It starts with a step most measurement plans skip.
Outcomes are the results the business already tracks. Outputs are the work people have to produce to get there. Obstacles are whatever stands in the way of producing that work to standard.
Most L&D reporting lives below all three. It measures whether people attended the event that was supposed to help them produce the work that was supposed to move the result.
Nick's model flips the order. Define the result first, then work backward.
## Outcomes: borrow the business's numbers
You don't need to invent an outcome metric. The business already has one, and it is usually already underperforming somewhere.
[Eileen Cook](https://learning.iorad.com/the-adoption-curve/how-to-scale-behavior-change)e, VP and Chief Learning Officer at Amtrak, has led learning functions inside very large organizations. Her approach starts with a conversation many learning teams still avoid.
Before that, Eileen describes where to point the flashlight: wherever there's friction, wherever things are slower than leaders want, wherever the workforce isn't yet doing what leaders promised the board they'd be able to do.
That is your outcome metric. It is already on someone's dashboard, with an owner who cares about it. And it gives your program a baseline before launch, the one thing you can't recover afterward.
Ask for the KPI before you scope the program.
## Outputs: measure what people leave behind
Outcomes on their own are hard to claim. Pipeline, retention, and win rates move for dozens of reasons, and a training program is only one of them.
Nick's test for finding the right output is a single question.
For a seller, that might be an account plan, a business case, or a current state assessment from discovery. For a support agent, it might be a resolved ticket that never gets reopened. For someone using a new system, it might be a record entered correctly the first time.
These are things you can inspect. You can set a standard for what good looks like, and you can check whether the work meets it before and after a program.
That is a far more honest signal than whether someone sat through the module. It also solves the attribution problem. Nick's advice is to break performance down to what you can reliably influence: pipeline conversion is hard to hang your hat on, but whether reps are engaging the right buyer persona is something enablement can move and defend.
Credibility comes from claiming the right number, not the biggest one.
## Obstacles: the data hiding in plain sight
The third layer is where most programs get stuck, because it is where teams assume they need data they don't have.
Heidi hears this constantly: "My company doesn't collect any data." Her answer is that data is anything the organization already collects. Exit interviews. Engagement surveys. Glassdoor reviews. Help desk tickets. If a request for a leadership program comes with exit interviews blaming managers and two years of falling manager scores, you already have a baseline to measure against.
Her customer education team used the same approach to measure the obstacles their program was meant to remove.
The ticket queue did two jobs at once. It told the team what to build, and it gave them a number to watch after they built it.
That is what measuring obstacles looks like: a count of the friction that was there before and should be smaller after.
Heidi is also clear that no single number proves the case. Help desk tickets can fall because the company hired better IT people. So she pairs sources: tickets, time saved for onboarding managers, logins to the new content. Taken together, they tell a story one metric can't.
## How you know it's working
Even with outcomes, outputs, and obstacles mapped, there is one signal teams forget to look for.
Usage tells you people showed up. It doesn't tell you whether they can do the work on their own.
A system everyone was required to log into will always show high usage. The real question is whether people can use it without pinging their supervisor or a friend in IT. Watch for it in practice where you can, and ask directly where you can't: do you feel confident doing this now?
Nick adds a qualitative method: Robert Brinkerhoff's Success Case Method. Ask the people who improved most what made the difference, and the people who saw no change what would have helped. Bring both stories to leadership alongside the numbers.
If adoption is real, you should see it in specific signals: the friction metric you picked is below its baseline, the output you defined meets the standard more often, and people can describe what changed for them without being prompted.
A completion rate can't show you any of that.
## The cultural shift
Better metrics alone won't fix this. The identity behind them has to change too.
Eileen is direct about the habit that keeps learning teams stuck: bringing their own data into every room.
Earlier in the conversation, she makes the same point about pilots. Showing a leader what a new tool can do might get you a meeting. Showing them what changed because of it is what gets you the second one. Participation numbers don't show change.
You don't have to claim credit for the whole result. You do have to show up with the same number the business is watching, and point to the part of it you helped move.
Participation is a prerequisite. It was never the proof.
## The tactical starting point
You don't need to rebuild your reporting this quarter. Start with one program.
1. **Pick one live program.** Choose something launched recently or launching soon, so you can still capture a baseline.
2. **Ask the business owner for their KPI.** Use Eileen's three questions: where do you stand, what are you doing about it, and what's at risk?
3. **Name one output.** Ask what someone produces when they do this work well. Write down what "good" looks like.
4. **Name one obstacle you can count.** Tickets, rework, escalations, time to complete a task. Pull the number as it stands today.
5. **Add one confidence check.** A single question, asked a few weeks after launch: can you do this without help now?
6. **Report all four layers together next time.** The outcome you support, the output you improved, the friction you reduced, and what people told you changed.
Don't try to fix every dashboard at once. One program, mapped all the way down, will tell you more than a dozen completion reports.
The teams that earn trust with the business won't be the ones with the most data.
They will be the ones who defined performance before they tried to measure it.
## Downloadable Resources
Workbook
Map one program from the business outcome down to the output, obstacle, and confidence signal you'll track, so your next report shows what changed instead of who showed up.
[Download](https://learning.iorad.com/hubfs/iorad_Metric_Map_Worksheet.pdf)
#### Support
- [Help Center](https://www.iorad.com/resources/help-center)
- [Learning Hub](https://learning.iorad.com/)
- [Schedule Demo](https://www.iorad.com/demo)
- [Releases](https://www.iorad.com/release)
- [FAQ](https://www.iorad.com/faq)
#### Pricing
- [Business](https://www.iorad.com/pricing/business)
- [Education](https://www.iorad.com/pricing/education)
- [Non-Profit](https://www.iorad.com/pricing/non-profits)
#### Company
- [About](https://iorad.com/about)
- [Leadership](https://www.iorad.com/leadership)
- [History](https://www.iorad.com/history)
- [Culture](https://www.iorad.com/culture)
- [Careers](https://www.iorad.com/careers)
#### Explore iorad
- [What is iorad](https://www.iorad.com/tutorialbuilder)
- [Features](https://www.iorad.com/features)
- [Compare iorad](https://www.iorad.com/compare)
- [How to use iorad](https://learning.iorad.com/use-cases)
- [Testimonials](https://www.iorad.com/testimonials)
#### Connect
- [Partners](https://www.iorad.com/partner-programs)
- [Integrations](https://www.iorad.com/connectIntegrations)
- [Helping Hands](https://www.iorad.com/helping-hands)
- [Services](https://www.iorad.com/services)
- [Adoption Curve](https://learning.iorad.com/the-adoption-curve)
#### Fine Print
- [Terms of use](https://www.iorad.com/termsconditions)
- [Privacy Policy](https://www.iorad.com/privacypolicy)
- [Cookie Policy](https://www.iorad.com/cookiepolicy)
- [Accessibility](https://www.iorad.com/accessibility)
- [System Status](https://status.iorad.com/)
© Copyright 2026 – iorad Inc. All rights reserved.
[/LinkedIn.png)](https://www.linkedin.com/company/iorad) [/Facebook.png)](https://www.facebook.com/iorad) [/Instagram.png)](https://www.instagram.com/iorad) [/YouTube.png)](https://www.youtube.com/@iorad) [/Twitter.png)](https://twitter.com/iorad)
```json
{
"@context" : "https://schema.org",
"@type" : "BlogPosting",
"author" : {
"@type" : "Person",
"name" : "Tania Blake",
"url" : "https://learning.iorad.com/author/tania-blake"
},
"dateModified" : "2026-10-14T14:33:53.376Z",
"datePublished" : "2026-10-14T14:25:38.000Z",
"headline" : "Adoption Metrics That Actually Matter",
"image" : [ "https://learning.iorad.com/hubfs/Field%20Notes.png" ],
"mainEntityOfPage" : {
"@id" : "https://learning.iorad.com/the-adoption-curve/adoption-metrics-that-actually-matter",
"@type" : "WebPage"
},
"publisher" : {
"@type" : "Organization",
"logo" : {
"@type" : "ImageObject",
"url" : "https://learning.iorad.com/hubfs/iorad_logo_colour_2021%20(1).png"
},
"name" : "iorad"
}
}
```