“My people aren’t working hard enough. They should be in the lab all the time.” proclaims a frustrated PI.

What does that even mean?! Just because people are in lab, that doesn’t necessarily mean they’re producing.

In a world where the productivity relies on the creative experimentation of theories and hypothesis, time and effort are seldom synonymous to hard work and dedication.

Some spend more time thinking and strategizing to help eliminate the need for troubleshooting at the bench.

Whereas, others like to tinker and to experiment at the bench. Some of them find that the tactile feedback helps them learn better and improves their technical skills.

People learn and work at different rates and through different methods. Therefore to use abstract feelings to measure a person’s productivity and their level of dedication is counter productive.

However, identifying specific tasks and tangible results are great measures of productive behavior.

We once had a grad student who seldomly came to lab during daytime hours. He tended to work only in the late evenings.

Many people used to complain about his lack of presence. Some would claim that he was “slacking”.

However, the amount of data and experiments that he produced to move his project forward, was at least twice that of anyone in lab. Because of his quality data, our PI understood that his student was truly dedicated to the project.

The student still managed to attend all mandatory meetings and contributed great insight to everyone else’s projects. Therefore, our PI pushed back on other protesters. He told everyone that he looking to see data, not time clocks.

When it comes to highly specialized fields, like the STEMs fields (Science, Technology, Engineering, & Math), traditional industrial work management strategies fail miserably. However, encouraging a person’s unique skillset and talent requires a teaming strategy. (Check out Harvard Business School’s Amy Edmonson’s work in Teaming, where she nicely illustrates this.)

The stress and pressure to produce breakthrough discoveries requires a skilled leader to keep everyone focused. It’s up to him/her to ensure that everyone is contributing equally, but in their own unique way. It requires both technical and leadership training.

We’re making independent scientists, my old boss used to say. That independent training relies on the way a person is productive. Not everyone is creative and learns the same way.

He was able to recognize that within his team, and was able to hone each of their unique skills and talents.

Here are four strategies that will help you to become the leader of future leaders:

  1. Learn to delegate by being specific. Saying “work harder” is abstract. Define specific tasks, experiments, or data that you expect to see from your own people.
  2. Always communicate the big picture. Have your people explain how their work contributes to the over picture. Solicit ideas from them on how they would reach those goals.
  3. Hold everyone accountable. This includes yourself. Solicit feedback to continue to motivate your people to perform at their best. Holding each other equally accountable is necessary for teaming within a creative and diverse skill set work group.
  4. Lead by example. This may be the most obvious leadership trait. You cannot expect your people to work hard at tasks that you’re not willing to do yourself. I’m not saying to do their work for them, but you should be willing to do it, if need be.

Leading people to do repetitive, perfunctory tasks may be more easily definable and manageable. (We can thank the industrial revolution for that.) However, the ever changing and diverse field of independent research requires a whole different set of management and leadership skills. It requires us to train current students, postdocs, and techs as we if we’re training leaders.

What mentor or leader has encouraged you to be a better leader? Share with us. Leave a comment below.

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