Designing Learning Experiences for Data and Impact
For decades, learning design has followed a predictable, yet flawed, waterfall model: identify a need for training, devise a “first best guess" about a learning solution to meet the need, develop it, deploy it, and move on to the next project.
Measurement has largely been an afterthought, with data limited to attendance, completion, or Level 1 “smile sheets.”
The problem with this approach is that it produces discrete, static learning experiences disconnected from on-the-job practice, and learning solutions take a relatively long time to execute.
L&D leaders are often caught in this cycle of creating, delivering, and moving on to their next “first best guess” without ever discovering what truly changes learners’ behavior, improves their on-the-job performance—or what’s getting in their way.
Today, two major forces are making this approach obsolete
scrutiny of L&D as a cost center
and insatiable demand for data fueled by genAI.
This convergence is pushing L&D leaders away from the one-and-done, waterfall approach to learning toward a new philosophy: designing for—and with—data.
To prove our value in the increasingly data-driven world of work, L&D leaders must go beyond Level 1 measures and focus on impact.
The Golden Opportunity: Designing for Data Insights
The shift to designing for and with data requires us to ask a critical question long before we begin ideating on a learning solution: What do we need to know about our learners?
For starters, we often want to know what learners know and don’t know, what they can and can’t do, and how confident they are in their abilities.
Our goal, then, is to build a learning solution that generates answers to these questions. By designing for this data, we ensure that the solution yields key insights and delivers value in the forms of behavior change and improved on-the-job performance.
For a high-level overview, read on. If you prefer a detailed deep dive into designing for data, click here.
Correlating Training with Real-World Performance
The most valuable learning metric is establishing a correlation between training and performance via real-world performance measures. Training is just one among many factors influencing performance, but the performance of learners who access or complete a program offers a gold mine of evidence.
For example, do they show significantly higher retention rates, employee satisfaction, rates of promotion, or use of software? Having these numbers helps us to:
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Understand why a learning solution is successful, so that we can replicate our success, and
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Validate our stakeholders' investments in learning.
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To access this data, L&D leaders must use our skills as connectors who see across the numerous business units and functions in our organizations—especially in the areas of Talent Management and HR.
Some organizations have higher walls between L&D and Talent functions, and finding ways to trace the impact of learning requires more creativity and “working across the aisle.” Discover creative ways to locate meaningful learning data in our companion article.
Data for Learning Design Optimization
Designing for data about the learning experience itself helps us measure our understanding of learning outcomes beyond our first best guess. Creating an ongoing feedback loop empowers us to improve our learning solutions by:
Finding obstacles and hotspots to track where learners are dropping off, getting stuck, racing through, engaging, and returning.
Implementing iterative improvement by refining subsequent versions of the learning experience.
Predicting learner behavior by analyzing learner characteristics based on experience, region, assessment scores, and so on.
Overcoming Barriers: The Path Forward
There’s tremendous opportunity here in data, and it comprises a major part of the L&D glow-up. But let’s address the elephant in the room:
The biggest barrier to data-driven L&D is organizational and operational friction.
If data isn’t an established part of our organization’s process, that’s our call to action: Here’s where we can leverage our position as connectors across siloes to identify and gather any data at all that may serve as an indicator of the outcomes we’re most interested in.
Data is the language of the business, and L&D leaders must become at least conversational, if not fluent, to demonstrate the value of our partnership.
As we level up, it’s important to remember: This is a moment of convergence and opportunity for L&D leaders and teams, not an extinction event. Embracing data as a tool for learning design, evaluation, and storytelling supports our long-term role as valued strategists and partners.
As we level up, it’s important to remember: This is a moment of convergence and opportunity for L&D leaders and teams, not an extinction event. Embracing data as a tool for learning design, evaluation, and storytelling supports our long-term role as valued strategists and partners.
