1) Question, research, and learn. 2) The team cycles through the data together.
- Many organizations focus on key milestones.…The managers focus their energy on compliance and planning.…They have quarterly budgets and monitor them closely.…They look for cost or schedule variances.…If they see a change, then they quickly chase it down…and report it to executives.…These organizations are structured for compliance.…Think about your meetings.…Chances are you're planning.…Maybe you're presenting a plan.…You could also be coordinating with another team.…You might be asking for a budget increase.…You could be behind schedule.…
Working this way is not well suited…for data science teams.…Their work is exploratory.…They come up with questions, generate insights,…and then run experiments.…There are certainly companies…that are used to working with scientists.…They're usually in pharmaceuticals or academia,…and have been running experiments for years.…For most organizations, it won't seem natural…to have a data science team that focuses…on creating new knowledge.…In these organizations, you have to be especially…
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