1) Teams work towards consensus. 2) They look through a keyhole of an open door. 3) With data science and exploration that's bad.
- In most organizations,…people naturally try to reach consensus.…Some organizations call it different things.…Some encourage everyone to go along to get along.…Others use words like idea socialization.…Data science is very different.…Consensus can be a very big problem.…You want your team to explore new ideas.…If everyone comes to consensus too quickly,…that could mean that everyone shares…a common misunderstanding.…Remember that data science is about exploring.…You're looking for knowledge and insights.…
There's no need to get everyone on the same page.…In fact, you want everyone to be able to argue…about how to interpret the data.…The data science team should be more like a family dinner.…It shouldn't be like a quiet bus ride.…You want the team talking and exploring,…and even annoying one another.…This type of exchange is much more likely…to uncover new ideas.…There are a few things you can do to help keep your team…from reaching consensus too quickly.…The first thing is to be aware of the danger of consensus.…
Learn the holistic approach to building teams and deploying data science across disciplines. Identify the key roles and responsibilities, including research lead, data analyst, and project manager. Find out how to define areas of responsibility, foster effective communication, and build compelling reports and visualizations. Then see how to avoid the pitfalls of losing focus and arriving at false consensus. These techniques help you build highly skilled teams that produce deeper insights than you'll find from relying on data scientists alone.
- Creating a data-driven culture
- Defining team roles and areas of responsibility
- Finding wisdom in groups
- Presenting beautiful reports
- Thinking like a team
- Avoiding pitfalls