Photo by Faisal Latif on Unsplash
Coaching A PARTICIPANT THROUGH OUTLIER OBSERVER DATA
If you coach participants who have taken any sort of 360-degree assessment, I bet you’ve encountered this question, but especially if you facilitate Leadership Challenge® Workshops or coach people through their LPI® 360 assessment results like I do. In fact, this question kept coming up so frequently that I started addressing it before it was asked.
“But what about this one observer’s scores? Why are they so different from the rest?”
HOW DO YOU DEAL WITH THE QUESTION OF THE “OUTLIER” IN SOMEONE’S 360 ASSESSMENT REPORT?
In the LPI® 360 assessment, leaders are rated on the frequency of 30 behaviors, grouped into The Five Practices of Exemplary Leadership®.
Our job as a facilitator or coach is to help leaders approach assessment feedback with an open mind, so giving people a lens from which to view their feedback is a pivotal part of our role. We help set the tone for how they react. Do they spend time trying to figure out who rated them so differently from others, or why one Practice is so different from the rest, or do they look to the greater meaning and themes in the data?
Let’s start with the basics.
WHAT IS AN OUTLIER ANYWAY?
It’s essentially a data set from an observer that is significantly higher or lower than the leader’s self-scores and/or any of the other responders.
It can be the leader’s own self-scores that are the outlier – showing up markedly different than combined observer responses. Often, outlier data from someone else can trigger emotional responses from the leader.
WHAT ARE PEOPLE’S NATURAL RESPONSES WHEN THEY SEE OUTLIER DATA IN THEIR REPORTS?
That depends on what kind of outlier data it is.
If it’s higher outlier data, people often approach it with a “Well, wasn’t that person overly kind to me!” type of comment.
On the other hand, lower outlier data is a flashing neon arrow bringing the leader’s gaze straight to it! Common responses include, “Well, I sure must have ticked this person off the day they filled this out!” to “This person is out to get me!”. Low outlier data has the potential to trigger our defense mechanisms and can send us straight into assigning blame.
HOW TO HELP THE LEADER PROCESS LOW OUTLIER DATA IN A HEALTHY MANNER THAT INVITES DEEPER REFLECTION
In the context of the LPI® assessment, it’s key to first remind the leader that the numbers represent FREQUENCY OF OBSERVED BEHAVIOR – they are NOT an indication of whether they are a ‘good’ or ‘bad’ leader.
Second, you may want to gently remind the leader that people’s perception IS their reality. So, even if the outlier data is significantly different from the rest, the leader should ask themselves what they can take away from it, even if they don’t agree with it.
After that, you can:
- Encourage the leader to look for overarching messages in the data and not to get hung up on the individual scores. If it’s a low outlier, point out to them that the majority of their observers experience their leadership behavior more frequently, so that is great news!
- Invite the leader to consider the observer category that the outlier is in. Are some of their coworkers are in a different location from them? If so, lack of proximity and exposure to the leader’s behavior on a consistent basis could influence the scores. Have the leader think through practical changes in behavior that might impact their remote colleagues the most. You may often find that leaders register people as observers who simply don’t have the consistent interaction to speak to their leadership behavior; in which case, low frequencies are simply an honest response.
- Have the leader look for specific leadership practices where the outlier scores are especially low compared to other practices. What might that tell the leader? For example, with the LPI®, if there is a Direct Report response with significantly lower scores in the Encourage the Heart behaviors than the Model the Way behaviors, that could indicate to the leader that this person may need more focused encouragement than they feel they are currently getting. Try to help the leader identify ways to generally increase the frequency of those behaviors across the board, so that direct report starts to get more of what they need. Plus, it won’t hurt the other direct reports to have more of a good thing!
- Point the leader toward the open-ended comments (if the assessment includes them). Is there anything there that provides more context for some of the outlier scores they are seeing?
Again, the goal is to help steer the leader toward the main themes and messages in the data. What are actionable things they can take away and start applying?
Make sure you point them toward their strengths and encourage them to keep their foot on the gas of the things they are doing frequently. Their outlier data is a part of their feedback story – valuable and important, but it shouldn’t be derailing.
