Training – Should We or Shouldn’t We?
“What if we train them and they leave?”
“What if we don’t and they stay?”
Which kind of company mentality lends itself to top performers? According to one of the articles we ran across, Top Performers might actually want to stay and grow with more training.
What if we were to compare a Top Performer in our Multiphysics and Computational Analysis industry to an Olympic Athlete? Both are at the top of their game. Both are among the best at their chosen pursuit. Both are elite. And both have an interdependent approach to training… they do not have to keep training because they are already among the best at what they do, but they continue to choose additional training because they want to get better and better as long as they can get better and stay among the best at what they do as long as possible.
So when it comes to training, there appears to be a compelling reason to continue to invest in Top Performers – Top Performers want to get better… and better! And they want to stay if possible.
Here is our encouragement. People do not enter the Multiphysics and Computational Analysis Industry without proving that they are learners. In fact, looking at the total number of people in the world who do this type of work, we would have to make an educated guess and say that when it comes to learning, the people in this industry are at the top of their game. And those who want to get better and better as long as they can get better choose additional training. And then we see the Top Performers emerge – they start to stick out like an Olympic Athlete. We know the Top Performers in our industry are committed to, invested in, reliant on continued training.
Maybe we should consider this question instead… “What could happen if we train them and train them and train them… and they stay?”