Building Consensus in a Biotech Organization
Simple in theory. Messy in practice.
In my posts over the last few months, I've been exploring how differences in mental models can get in the way of integrating data teams into a biotech organization. It's been a lot of doom and gloom. But as my last few emails have hinted at, it's finally time to shift gears and start exploring solutions. So in my latest blog post, I describe an approach that I've found effective to get a diverse group of people onto the same page about a specific decision or plan
To get a sense of the kinds of things I’m talking about, here are the three examples I use throughout the post:
Getting bench and data teams to agree on consistent standards and better tools for collecting and sharing lab data.
Defining machine learning projects that can help answer your lab teams' key questions.
Adopting a collaboration model that ensures your data teams have input into
If these sound like the kinds of problems you’ve encountered, you can read the whole post here: