InsightsBeyond the Survey: Design Learning Data for Real-Time ImpactSusan Douglas, Ph.D.August 5, 2025ThomasVogel/Getty ImagesIn brief:Learning data becomes most valuable when its connected directly to business impact.Transparent conversations about learning effectiveness are foundational to building organizational cultures that value getting it right AND making it better.A human-centered approach that embeds evaluation into the learning experience itself creates richer, real-time actionable insights that drive better decisions.This post is co-authored by Susan Douglas, Ph.D., Professor of Practice at Vanderbilt University and an executive and team coach, and Patrick Voorhies, Ed.D., Manager, Talent & Development, Motiva Enterprises.What if your learning data didnt just prove that people liked your programs, but actively fueled curiosity, conversation, and change while learning was happening?In a highly competitive and volatile global market, organizations have become increasingly attuned to the need for evidence-based or data-informed decision making. Organizations analyze and report on a host of measures, delivering data to senior executives to guide their decisions. Advancements in technology, such as generative AI, are making data capture and use increasingly accessible to better build the evidence base.While it is widely recognized that leaders must demonstrate how their investments drive organizational objectives, the challenge lies in consistently meeting this expectation. Talent development leaders already understand how important it is to:Articulate the story of how learning and development programs contribute directly to business outcomes.Establish clear learning and development metrics, targets, or benchmarks to use to assess the value of learning to the organization.Efficiently deliver learning and talent analysis and insights aligned with organizational goals and objectives.Leverage data to evaluate workforce skills, competencies, and capabilities in relation to business needs.The struggle comes when organizations try to show the close connection between learning interventions and business objectives. In our examination of how organizations measure learning and leadership development, we frequently encounter three myths that drastically disconnect learning metrics from organizational learning.Myth #1Measuring satisfaction with a learning program tells us something important.Measures related to how much learners enjoyed an experience dont usually connect to the real impact on the business unless they are wildly dissatisfied. In fact, research on learning suggests that challenging experiences that lead to growth often dont earn the most positive ratings from participants. We have too often seen measurement focus on what can be measured rather than what is meaningful to measure.Attendance and net promoter scores have their rightful place in a comprehensive learning evaluation system. They help you understand the whole picture of what is going on with a program and provide useful insights for quality control and benchmarking. But they are not the best way to answer stakeholders and executives concerns around a programs ability to influence business outcomes. They are only the first step in what we call a chain of outcomes that integrates a series of measures of how a program was experienced. This approach applies theory-based measures of short- and long-term changes in knowledge, skill, and behavior that predict real business impact.Myth #2Connecting learning experiences to behavior change is too difficult.We acknowledge that survey fatigue is real and that attempts to collect data in the weeks and months after a learning program are minimally useful. Self-reporting provides only a limited slice of a leaders behavior. Research methods that control for all the reasons why people change that have nothing to do with training are costly and lack fit with the dynamic business context.Instead, imagine what data might result if you drop the surveys altogether (most of them anyway) and instead embed micro-data collection points throughout a learning experience. This creates opportunities for feedback loops that can be part of the learning experience itself. This is a better fit for how adults learn and even better, it transforms the why behind data collection.Our research on measurement-based health care shows that people are much more willing to answer questions that directly impact their experience, which ultimately contributes to more and higher quality data that can then be aggregated to benefit organizational learning.Myth #3We evaluate to know what something is worth.Okay, we recognize this is a controversial thing to say when we are talking about evaluation. Now that weve got your attention, heres what we mean. Collecting data to evaluate the merit or worth of something is always a political activity. Emerging leaders want the program to continue because it will enhance their chances of promotion. Senior leaders believe in the program because it enhances the companys reputation as a place that develops leaders. And yes, talent development leaders want to prove that their programs matter and enhance the business. When these things are true (and even when they are not?), organizations tend to hold learning data too close.While talent development leaders may share metrics with HR or management, they often dont put the data in the hands of those who can make the biggest difference with it. Its not enough to generate data dashboards and produce reports. Whats needed is to integrate real-time relevant data into a dialogue about what we can do more of, do less of, or do differently to increase impact.Its time to move beyond using data only to prove something. The real power of data comes when organizations use it as a catalyst to spark curiosity, fuel shared learning, and inspire collective actionan essential shift too many still overlook.From Transaction to Transformation: Embedding Micro-Data for Real-Time LearningToo often, learning data collection is treated as a post-training transaction a quick survey asking participants to rate their experience after the fact. The result? Feedback becomes an afterthought, disconnected from the actual learning. And learning and development (L&D) teams are left relying on goodwill for insights that may never arrive.We propose a shift: from evaluation as an endpoint to evaluation as a learning strategy. When you embed data collection directly into the learning experience, you turn insight into action in the moment.This approach puts learning data closest to where decisions are being made. Heres how to start:Ask Questions that Shift the LearnerDesign questions that do more than gather opinions ask ones that evoke insight, awareness, or behavior change. These questions should feel like part of the learning itself, not a separate task. When data collection deepens the learners engagement, you get useful data for evaluation and training impact.Share Results in Real TimeAs data is collected, make results visible immediately within the learning experience. Show participants how their responses are shaping the journey. This not only builds trust but creates opportunities for real-time customization even in asynchronous settings.Build a Feedback loop that Powers LearningWhen questions are well-designed and responses are used immediately, you unlock a powerful feedback loop. Data isnt just captured it is applied. Even self-reported outcomes, gathered throughout the experience, can be woven into a story of change that speaks to both learner and organizational impact.This model requires more intention from L&D teams but delivers far greater value to learners and to the organization. Measurement of leadership development that is embedded in the Why? what we call the theory of change creates a pathway that shows impact across individual leaders, teams, and the organization. Visualizing the path, as shown below, helps create the connections forward when planning leadership programs and backward when measuring crucial outcomes.Pathway to Embedding Leadership Development OutcomesThe key question isnt Can we do this? but How might we?The real magic happens when we use data as a starting point to explore, engage, and evolve together. Ultimately this is about strengthening a culture that values execution, which is about getting it right, and learning, which is about getting it better. Creating data transparency and pushing information access to the people who can drive the change requires shifts in candor, as it changes how we lead, listen, and design programs.Our model is more than a method its a mindset. If youre ready to move beyond proving value to creating it in real time, we invite you to experiment, reflect, and learn with us. In our next post, we will showcase organizations that are taking a human-centered systems thinking approach with learning measurement.Read more:Breaking Through: People-Centered Transformation Powered by LearningHow to Assess Leadership Skills for a Leadership Development ProgramStrategic AlignmentTalent ManagementShare this resourceShare on LinkedInShare on FacebookShare on XShare on WhatsAppEmail this PageConnect with usChange isnt easy, but we can help. 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