Too often, when looking to increase programmatic engagement, we forget to look at the mentees and mentors that are low performers. This is natural - our attention sways to those that are not meeting the expectations we have set for them in order to get them to do so. However, taking a step back to consider the "champions" within a group of pairs to determine why they are doing exactly what is asked of them (or more) can provide a beneficial lens into motivating others to do the same.
This article focuses on drilling engagement data down to the individual level to recreate the success of champion participants to those not meeting expectations. This is a great exercise for team meetings rallying around increasing pair engagement.
Finding Your Champions
There are many ways to identify pairs exhibiting exemplary engagement levels. Below, one method for doing so is outlined using iMentor Chicago's entire portfolio as an example:
- Navigate to the PM Summary S.T.E.V.E. dashbaord;
- Within the In-Person Meeting Distribution bar chart, select pairs that have met the most (as show in the graphic below, multiple categories can be selected simultaneously by holding the Ctrl key and clicking on two bars);
- Hover over the selection you have made and click on the "View Data" option in the menu that appears;
- In the resulting pop-up window, click the "Full Data" tab and then "Download all rows as a text file";
- Open the file once it has downloaded and place filters on the top row of the dataset;
- Use the filters to find champion pairs. In this example, we have already generated a list of pairs that have already met 5 or more times, but now we will use filters to show pairs that have also completed 75% or more of the lessons assigned to them (this can be done a number of ways, but in this example, it is done by un-selecting all values below 75).
Leveraging Your Champions
Through the process above, a relatively short list of highly engaged pairs has been created that can be used to foster discussions such as:
- What are the common characteristics among these pairs? How can this information be leveraged to support pairs less engaged toward increasing their online communication or in-person meeting frequency?
- What are the reasons the pairs on the list engage more frequently? How can this information be leveraged to foster increased engagement across the cohort?
- Identifying mentees that are higher performing that have peers that are lower performing. Perhaps the higher performing mentee would be willing to share what it is that motivates her to engage with the lower performer;
- Identifying mentees that are higher performing that might be willing to share something interesting about their mentor or their relationship in hopes to generate more excitement across the entire class.
Still have questions or need assistance with this pro-tip? Click HERE to contact a member of the National team for help!