Throughout the years, evaluation for talent development professionals has evolved from course surveys and facilitator assessments to measuring results, meeting business goals, and changing behaviors. Effective evaluation is now centered on proving the impact of the talent development program on business goals.
Evaluating impact, one of the 23 capabilities in the Talent Development Capability Model, correlates with learning and business effectiveness and is part of the Developing Professional Capability domain. TD professionals should be able to implement a multilevel, systematic method for gathering, analyzing, and reporting on information about the effectiveness and effort of learning programs. Collecting data relevant to business strategies and goals helps decision making, improves learning programs, and increases the value proposition of learning with senior leaders and business stakeholders.
Why Evaluate?“I see L&D as drivers of impact on performance, behavior, organization goals, and business strategy with our training and learning solutions,” Kevin Yates, a self-proclaimed L&D detective who helps solve what the impact of learning is, writes in a March 2019 ATD Links newsletter article. “Measurement is more than just an action, though. It’s a mindset.”
Isolating a learning program’s impact on results was cited as the top barrier to conducting evaluations by 41 percent of respondents, according to the Effective Evaluation: Measuring Learning Programs for Success research report. The report recommended control groups or interviews to help gather estimates of the effects of training.
“Identify people who have visibility into how the training activity translates to results on the job,” explains Tom Atkinson, president of Atkinson Analytics, in the report. “It could be a manager, a participant, or a subject matter expert. Have them estimate how much difference the training has made."
Key Knowledge and SkillsA TD professional with capability in this area will need knowledge of:
- Models and methods to evaluate the impact of learning and talent development solutions
- Qualitative and quantitative data collection methods, techniques, and tools (for example, observations, interviews, focus groups, surveys, and assessments)
- Research design methodologies and types (for example, experimental, correlational, descriptive, meta-analytic, longitudinal, and cross-sectional)
An effective TD professional will need skill in:
- Creating data collection tools (for example, questionnaires, surveys, and structured interviews)
- Selecting or designing organizational research (for example, defining research questions, creating hypotheses, and selecting methodologies)
- Identifying and defining individual or organizational outcome metrics based on the evaluation strategy or business objectives of a solution
“At Comcast, telling business impact stories is part of our DNA,” Martha Soehren writes in her June 2019 TD magazine article “It’s All About the Impact.” She adds: “My team holds sessions throughout the year during which individuals volunteer to share the learning programs they implemented and the results, such as increasing an employee's proficiency in a certain skill or growing sales revenue. These ongoing impact stories are part of the company's culture and serve to elevate the TD function's work and link it to business-critical activities. I've never asked my team to prove their value collectively because our value shows in how we align and deliver to our business partners in every TD interaction.”
The addition of data and analytics has made evaluation a lot more complicated but understanding how to use business-relevant data, aligning that data to the strategic goals of the organization, and communicating the results will increase talent development’s value with the C-suite.
“Measuring impact for learning is hard work and it can be difficult. However, difficult doesn’t mean impossible. You can show impact for learning,” Yates adds. “Measuring the impact of learning is about investigating what happened. What makes it so uncomfortable is that it is not an exact science. But we can absolutely show whether or not anything at all changed as a result of learning, and we can use data, analytics, and storytelling to do that.”