In the ’80s, Van Halen was the biggest rock band in the world.
Their live performances were legendary, as was their artist rider—the part of the performance contract that specifies everything the artist required to perform that day.
The long rider contained a clause requesting that “a large bowl of M&Ms with all brown ones removed” be placed in the dressing room.
And while it was frequently dismissed as typical rock star diva behavior, it turns out it was an astute business move.
By inserting the M&M line after many pages of technical and safety specs, the band could use it as an easy indicator of whether the promoter had carefully read every page.
All the band had to do was look in the M&M bowl.
If they saw any brown ones, they knew their road crew would have to perform a thorough safety check of the entire stage setup, as something subtle but VERY IMPORTANT could be out of place.
In much the same way, I use “easy indicators” when troubleshooting progress plateaus with clients.
By asking questions or requesting certain pieces of data, I can find out where to start troubleshooting.
How many calories do you eat a day?
If the answer is, “I don’t know,” then it’s probably too many or not enough—which paves the way for the keep-a-food-log lecture.
Same with how much protein they eat in a day.
“I don’t know” suggests it’s probably not enough and time to check the food log.
What’s your favorite exercise?
If the answer is bench press, they probably need a lot more rowing and may have to start dating a squat rack.
The key is the WHY behind every answer—not the answer itself.
Why is getting enough protein a problem? Is it a palate preference or just poor planning?
Why is sleep so lousy? Is it job stress, kids, or too much exercise?
This sets you on the path toward SOLVING problems, not just identifying them.
So rather than telling someone with a stressful job to simply “chill out more” you can help pinpoint what is ACTUALLY stressing them and perhaps offer solutions.
It all starts with trying to collect a little data.
What that process reveals is often far more important than the data itself.
– Coach Bryan