I had a conversation this week that stuck with me. A PI told me about a postdoc in her group who is sharp, motivated, and proactive. Exactly the kind of person most of us would be happy to have on the team.
Even so, she’s frustrated.
The postdoc doesn’t follow certain lab standards. Information is hard to track down. Data isn’t documented in a way others can use. Presentations take longer to prepare than they should because everyone is starting from scratch or reworking old files. And while the PI values independence, she’s spending a lot of time fixing the ripple effects.
It is not a matter of poor quality science. It is the absence of shared routines. Everyone works in a slightly different way, and that difference becomes expensive.
Why High-Performing Teams Still Slow Down
Many of us encourage autonomy because we want people to solve problems and move projects forward without constant input. That works well when everyone shares a basic structure for how things are done. When they don’t, things start to fall apart.
Without consistency, a team doesn’t operate as one. We duplicate work. We interpret results differently. We waste time realigning.
It’s easy to think of this as a communication issue, but in most cases it’s a structural one. Each person works hard and wants to be efficient. The problem is that the systems they’re working within aren’t compatible. Everyone is optimizing locally. The team doesn’t reach its full potential.
This happens quietly, over time. Most teams don’t notice it right away. The issue becomes visible only when things take longer than they should or when frustration builds around unclear expectations.
The real problem is not how skilled each person is. It is that we lack a shared approach for recurring tasks. Without that, everyone builds their own version of “done,” and the team loses the ability to build momentum.
Think of It Like a System
If you’ve ever worked with modeling or optimization problems, this will sound familiar. When each person optimizes their own workflow, the team reaches several small, individual peaks of efficiency. These peaks look good in isolation. But they rarely combine into something greater.
What we want instead is one high, shared team productivity peak. A structure that helps every person contribute in a way that strengthens the whole.
What Shared Rules Look Like
You don’t need a policy document to get started. A few agreements can already reduce friction and make collaboration smoother. For example:
- Agree on where and how data gets stored and documented
- Use a common template for presentations and figures
- Ask around before placing orders to bundle purchases and save costs
- Define what “ready for review” means in your lab
Each of these avoids a common point of breakdown. Each creates clarity, without adding bureaucracy. And the most important thing: Make it clear again and again why following the standards matters. How the team as a whole loses time and energy when everybody optimizes for themselves.
Who Decides?
This is something you can define together with your team. Bring it into a lab meeting. Ask what part of their workflow feels unclear, inconsistent, or tedious. That is usually where structure is missing. Let the team suggest what would help, then test it.
Shared rules work best when everyone sees how they improve the work. That happens when the team is involved in defining them.
Start Small
Choose one recurring activity in your lab. Something where people often spend extra time fixing, clarifying, or redoing work. Then create a standard for how that task should be handled. Make it visible, make it simple, and ask for feedback. If it helps, keep it. If not, change it.
This kind of structure creates time, not overhead. And the benefits build quickly.
We often talk about growing capacity in research teams. This is one of the quietest, most reliable ways to do it.