Scientific Method and Teams

“The first principle is that you must not fool yourself, and you are the easiest person to fool.”
~Richard Feynman

It has been extremely busy the last few weeks as the team and I put the final touches on our near-term strategy for NASA’s mission operations in Houston.  With national space policy remaining in a state of flux, we announced our strategy to extend the current Integrated Mission Operations Contract. As a result, the team’s activities are winding down.  I reflected on the experience over the last 4-plus months with this team, compared to the experience I was envisioning.

As I’ve shared repeatedly here on LeadingSpace, I read.  A lot.  I’m constantly searching for insights and perspectives that are new to me and that I can incorporate into my own leadership view.  I liken it to “panning for gold” – searching for those nuggets of knowledge and expertise with proven outcomes, and weaving those into my own tapestry on actions and decisions I should consider.  Yet in my weaving I am seeking simplicity, a clear understanding about how the universe works, no matter the domain in which I’m working.  Lately my interests have gravitated towards teams, and towards this question: why do some teams fail while others are successful?

Observe, reason, and experiment.

Borrowing from my long interest in science and my background in physics, I’m approaching an answer to the question rooted in the scientific method: observe, reason, and experiment.

Observe.  Let’s start at the beginning.  All science starts with observations and the curiosity that arises from the observation.  In my role of leading teams, I want to be a successful leader and have the team achieve successful outcomes.  I’ve noticed that some teams are successful, and others are not.  Why is that? And just as important, what can I do to tip the scales in favor of success?

Reason.  Clearly, a team has to have the right set of knowledge, skills, and understanding of the problem to be solved.  Call it the right skills.  Yet have you ever worked on a team of absolutely brilliant people who don’t talk to each other?  I have, and more often than not my experience has been that those teams tend to fail.  Therefore, there is another ingredient – a capability of the team members to work together and interrelate.  Call it the right aptitude.  Yet even that is not enough, because so far we’ve gathered together smart people who are capable of working together.  The last ingredient is to do something: to bring to bear the natural talents of individuals in a diverse way that maximizes the problem-solving capabilities of the team and actually achieve measurable results.  Call it the right talents.  Part of reasoning involves making a model and making a testable prediction from that model.  Here, I claim that the likelihood of success will increase if all three factors – the right skills, the right aptitude, and the right talents – are taken into account.  The verifiable converse is that the likelihood of team success decreases if any one factor is ignored or not optimized.

Experiment.  This is what I love to do, which is why I gravitated towards experimental physics while I was in college.  My latest experiment in setting up the current team was three-fold:

  1. I requested representation from experts from key areas across our organization, and could tell by the individual mail codes that I got a diverse setting,  I also knew from first-hand experience that the individuals represented some of the best and brightest we have.
  2. Next, I consulted with our organization’s top leaders to find our how well these people interrelated.  I had some experience working in team settings with some, but not all, the members.  We eliminated a few people from the list who are not known for their team-playing capabilities.
  3. Lastly, I wanted to maximize the diversity of problem-solving talents for the ones to be selected for the team.  For that, I’m relying upon material from Kathy Kolbe and the Kolbe Wisdom, where I attempted to identify behavior characteristics of each of the twelve Kolbe problem-solving zones.  From that, I believe I got a good distribution of problem-solving talents that I intend on confirming soon by having the team take the Kolbe A Index.

To make this a true scientific exploration I still have a lot of work to do.  Clearly, one of the key indicators of validity comes from this quote from Feynman: “If there is an exception to any rule, and if it can be proved by observation, that rule is wrong.” So, I would need to work hard to find a result that invalidates the line of reasoning, or show that to the limits I can test, none exists. I would need control cases, objective measures, and repeatability over a wide set of teams.  Finally, I would need a definition of a key term: what constitutes success?  I’m still thinking about all of these, so clearly this is a work in progress.

Yet I think I’m onto something here.  What would you add?

Text © Joe Williams 2011
Photo courtesy of iStockphoto

Scientific Method and Teams