Where’s the model? Why can’t I find it?
In a previous article, we introduced a simple way of structuring OKRs in L&D (referred to as SCOPE) to bridge the gap between learning activity and business outcomes. This post builds on that section and clarifies the logic behind it. Not to formalise it, but to make it easier to apply.
OKRs are moving quickly through L&D. In practice, application is uneven.
Teams use the language. Objectives, Key Results, cadence. The structure is visible. What’s less clear is whether anything is improving.
You can see activity. The harder part is seeing a shift in performance. That gap usually sends people looking for something more concrete.
So you look for a model. A named framework. A defined method. And then you realise there isn’t a single, agreed way of doing this in L&D.
So what does that mean? Is the approach flawed, or is something missing? The tension sits here.
The logic behind effective OKRs in L&D does exist. You can find pieces in goal-setting, performance management, evaluation models, and in how experienced teams operate. It just isn’t packaged in a usable way.
So teams fall back on familiar patterns. Learning first. Activity first. Measurement that reflects what’s easy to track.
The format changes. The behaviour largely stays the same. This isn’t a tooling issue. It’s a translation issue.
The problem is not that the model does not exist. It is that the logic has not been made usable.
If OKRs are simple, why do they break in L&D?
OKRs themselves are straightforward.
The structure is well documented. Set a small number of Objectives. Define measurable Key Results. Review progress regularly.
That part isn’t the problem. Things become harder when this structure meets how L&D typically works.
In many organisations, learning is treated as the outcome. Courses delivered. Participation tracked. Engagement measured.
The business is looking for something else. Capability. And beyond that, performance.
That’s where friction shows up.
You have a framework designed to track outcomes, applied in an environment that defaults to tracking activity. Objectives drift toward delivery. Key results settle on completion and feedback.
Progress appears visible. Impact is less so.
You can see what people did. It’s much harder to see what changed. Without that, decision-making becomes guesswork.
So the gap isn’t about understanding OKRs. It’s about translating them into a context where success is defined differently.
That requires a shift in thinking.
From courses to capability. From participation to performance. From reporting to results.
That shift is where most implementations slow down. It challenges long-standing habits in L&D.
So the real question isn’t whether OKRs work. It’s whether we’re applying them to the right problem.
The gap is not knowledge. It is translation.
What do OKRs that actually work have in common?
If you look at OKRs that work in L&D, they aren’t complex. They start in a different place.
They begin with a problem. Not a programme or a platform. A business issue that needs to shift. Slow onboarding, inconsistent management, declining customer outcomes. Something real and visible.
From there, the focus moves to the outcome. What should be different if this works? What changes in the business, not just in learning?
Then comes measurement. How will progress show up? What signals indicate behaviour change? What reflects performance improvement?
This is where teams revert to familiar territory. Completion rates, attendance, feedback. Useful, but incomplete on their own.
Stronger OKRs combine indicators. Behavioural signals, operational data, and business metrics. Together, they show whether change is happening.
Ownership follows. If the outcome matters to the business, it needs ownership there. L&D supports the change; it doesn’t carry the outcome alone.
And then cadence. Regular check-ins. Adjustment. Iteration. Performance shifts over time.
Put together, a pattern emerges. Start with the problem. Define the outcome. Measure progress. Assign ownership. Review and adapt.
Five steps. Not formal. Not branded. But consistently present where OKRs work.
Once you notice it, it’s easier to see why some OKRs drive change and others stall.
Effective OKRs follow a pattern, whether we name it or not.
Is this new, or are we just applying old ideas better?
It’s reasonable to ask where this comes from.
If you can’t find it written down, it can feel uncertain.
There isn’t anything fundamentally new here. This is a combination of established ideas, applied in sequence.
Goal-setting provides the foundation. Clear, specific targets focus effort and improve performance.
OKRs add structure and cadence. A small number of objectives. Measurable results. Regular reviews.
Evaluation frameworks add evidence. Models like Kirkpatrick and LTEM emphasise that learning isn’t the end point. Behaviour and performance are.
And then iteration. Continuous improvement relies on cycles of review and adjustment.
Put together, these ideas form a coherent flow. Clear outcomes. Measurable progress. Evidence of change. Regular review.
None of this is new. What’s often missing is the connection.
That’s the gap this approach addresses. Not by introducing something different, but by making existing ideas easier to apply together.
This is not a new model. It is a clearer way to apply what we already know.
So how do you apply this in practice?
Start with the problem.
Focus on the performance issue the business is trying to solve. Where is progress slower than expected? Where are results inconsistent despite ongoing learning?
Then define the outcome.
What should be different if this works? What changes in day-to-day performance?
Holding that line prevents the conversation drifting into courses and content.
Next, measurement. Use a mix of indicators. Leading indicators show behaviour. Lagging indicators reflect business impact. Together, they give a complete picture.
Relying on one or the other creates blind spots.
Ownership follows. If the outcome matters, the business needs to be directly involved. Not just informed, but accountable. L&D supports the change; it doesn’t own the result in isolation.
Then cadence. Regular reviews keep things moving. They create space to adjust and refine.
Over time, OKRs shift from static targets to active management. A way to guide performance, not just report on it.
Follow the pattern, and OKRs start to drive change rather than describe activity.
Am I missing a framework, or missing the connection?
This is where doubt sets in.
Is this a real framework? Why can’t I find it? Am I doing it wrong?
Those questions make sense.
L&D is used to named models and defined structures. This feels less concrete.
But the issue isn’t the absence of a model. It’s the absence of connection.
The components are familiar. Goals, measurement, performance, OKRs, evaluation. The challenge is that they’re applied separately.
Goals live in one place. Learning in another. Measurement somewhere else.
There’s no flow. So when you apply OKRs, things feel disjointed. It’s easier to fall back on activity because that’s what systems support.
Not because the framework is unclear. Because the pieces haven’t been connected. That’s where most implementations stall.
Not at the level of tools, but at the level of thinking.
Once the connection is clear, the need for a formal framework becomes less important.
You don’t need a new model. You need a clearer way to apply the ones you already have.
What actually needs to change?
Stepping back, the shift is smaller than it seems.
There’s nothing new to adopt. No additional layer. No framework to roll out. What changes is how existing tools are applied.
When the starting point is performance, the rest aligns. Objectives sharpen. Measurement becomes more useful. Learning becomes more targeted.
The components remain the same. The sequence changes. That shift moves OKRs from a reporting structure into a practical mechanism for improving performance over time.
This is where maturity shows up. Not in the tools, but in how consistently they are applied.
The value is not in the name. It’s in the discipline of how you apply it.
