Michelle is the CLO for a Fortune 500 health care firm. Due to the uncertainty in health care, her company hasn’t been investing in developing its leadership pipeline for the past few years.
Suddenly the CEO decides that developing leaders is urgent, and Michelle needs to do something big and global quickly, with minimal disruption to schedules.
Michelle gathers several possible options, ranging from a few dollars in cost to tens of thousands of dollars per leader. Her CEO is data-driven, so she needs to make an evidence-based choice. But the options are so different it’s hard to compare them. When Michelle meets with the CEO she finds it hard to argue against the cheapest option, and a webinar for her top 500 leaders is selected.
Michelle doesn’t have a robust way to think about measuring behavior change without delivering and measuring pilots across each idea, an expensive and time-consuming option. Without taking into account what will really work, executives assume all initiatives are equal, and the lowest-cost approach wins.
This would be like selecting a mode of transport without knowing the speed or distance each one goes, or the distance you need to travel, and choosing a bicycle each time. In short, we’re not thinking of what makes learning programs work very well.
Neuroscience can help. While understanding the whole human brain is a long way off, neuroscience has made big leaps in the past few decades in our understanding of how we learn, simply because studying how people recall information is one of the easier things to do in a lab. Recall is the first step to behavior change. Remembering isn’t the only step, but without it all is lost. We now have very good research showing that recall of ideas correlates to activation during an encoding task of a brain region called the hippocampus.
Basically, whether we remember something later closely links to how active this region is while we are learning. From 2008 to 2010, a team at the NeuroLeadership Institute worked with leading memory neuroscientists to review lab findings from across the globe on what makes the hippocampus activate, and we found a surprisingly robust pattern.
When designing learning events, research points to four must-haves to embed new ideas. First, attention has to be very high; multitasking dramatically reduces recall. The chemical processes to encode memories only activate when we’re very focused. Second, people need to generate their own mental maps around new ideas. They can’t just watch or listen; effort is central. Third, emotions need to be high; we only remember things we feel strongly about. Finally, we grow our memories, so spacing out learning is critical. These four elements — attention, generation, emotion and spacing — form the AGES model. High AGES is necessary for people to recall ideas before we even get to the question of how to build habits.
Understanding AGES helps us think about learning programs by beginning with the brain. This means making high attention, generation, emotion and spacing the non-negotiables first, then getting creative with how to execute this.
You can also use the AGES model as a lens to assess various interventions and identify which might generate the biggest impact. If any AGES domains are low, we can’t expect good idea recall.
For Michelle, using the AGES framework she could make a case, drawing on existing data, that less than 10 percent of an audience pays close attention during a webinar, with minimal generation, low emotions and no spacing. Therefore information embedding will be minimal.
Using AGES allows us to compare two digital programs, or a digital versus an in-person program, or two in-person programs, to see which has the likelihood of highest AGES. High AGES is likely to correlate to long-term embedding of ideas, which is essential for behavior change.
The AGES model is just one helpful insight from brain research. When it comes to designing learning for the enterprise, perhaps it’s time to begin with the brain.