Analytics, however, are more than a way to verify outcomes at the end of training. Effective measurement guides the training process as it unfolds. Sales professionals discover where they need to focus their attention and where their blind spots reside. Measurement is for the learner as much as it’s for the leadership.
Despite these benefits, many selling organizations fail to generate and measure data. Often, the data sits in disparate systems. This separation makes it difficult to connect the data to business impacts. Moreover, the available data represents different levels of accuracy, forcing the user to qualify the analytics first. Even after meeting these challenges, it is difficult to know what to measure.
Here, we simplify the process by segmenting measurement into what we call the E3 of learning metrics.
These three metrics are:
- Engagement: Engagement is a critical measurement because learning is no longer an event. It is an ongoing journey. Measurement of engagement includes capturing data around enrollment, activation, completion, progression, frequency, and channel.
- Experience: A good learner experience matters because it drives adoption of skills and ultimately better outcomes. Therefore, experience measurements should not be “one and done.” Experiential measurements can include metrics like net promoter score, commitment to change, course rating, qualitative sentiment, and confidence. Each of these measurements provides timely info for managers who want to ensure skills will survive into selling situations.
- Effect: This is an area in which the traditional Kirkpatrick training evaluation model is strong. The Kirkpatrick model evaluates training effectiveness across four levels: engagement, knowledge retention, behavior change, and business results. We often think of effect as the business impact. However, the Kirkpatrick model reminds us that we only reach business impact when we have a high degree of confidence in the other three levels of data.
The challenge with using data to expose learning impact is that the metrics often live in different sources. Tracking each of them is labor-intensive. Querying each system, then attempting to line up the data over time, demands too much time. Visualizing data to makes it more actionable. Doing so allows leaders to query and coalesce the information so they can use it to make informed business decisions.
To learn more download the brief: Using Analytics to Expose Impact by clicking here.