My last weekend was spent reading 33 college scholarship applications from some amazing kids.
They didn’t just volunteer, they started charities. They didn’t just have high GPAs, they were nationally recognized for science, debate or a jazz band currently playing Lincoln Center in New York. They were Eagle Scouts and all-state athletes.
It was difficult to narrow down to the 12 that would receive scholarships. However, there was a clear break-point in my scoring – kids that clearly stood above, having demonstrated depth, diversity, and a commitment to some passion.
I thought the committee review would be a 10-minute rubber stamp. Everyone would have come to the same conclusion, surely.
When recognition goes wrong
I found myself in some alternate universe with people arguing that some of these kids were “too good” and surely didn’t need the scholarship.
They probably already had a full ride. They were all-stars and therefore someone else had already done the recognizing. They were the popular, pretty girls that didn’t have a prom date because everyone assumed they were already taken.
I’ve seen this fallacy a lot when it comes to recognition. It goes like this:
- They already know how good they are.
- More praise will give them a big head; OR,
- In a sea of recognition, mine won’t mean anything.
- Someone who doesn’t get recognized much should get the award.
The cost of rewarding the “good” instead of “great”
But at what cost? Here’s what happens in that scenario …
- The star starts to question his/her worth and its value or the organization.
- The herd sees mediocrity held up as the paragon of performance.
- The herd realizes good is the new standard of excellence and performance follows.
- The star becomes disengaged, stops trying, and/or leaves.
Some would argue that it’s disheartening for the same person to always reap the rewards, but I would argue it’s more harmful if he/she doesn’t.
In this case, the equal distribution of recognition sinks all ships.
This was originally published on PeopleResult’s Current blog.