1) It's very difficult for one person to know more than a group. 2) When exploring you need a group to challenge assumptions.
- One of the misconceptions about data science…is that it's best left to a like-minded team…of highly trained data scientists.…Many organizations feel that you need specialized training…to ask interesting questions.…Anyone without this training would be…overwhelmed by the data.…There's also the misconception…that a small group of like-minded professionals…will always have the best insights.…The idea is that this group of specialists…will always be the best problem solvers.…
A uniform group of deep thinkers…will always ask the best questions.…And yet, this uniformity can stifle creativity.…It can also lead to blind spots.…Data scientists are usually more similar than they realize.…They'll be prone to groupthink.…They'll think we all agree, so we must be right.…Academics who study group creativity…place a much higher priority on diversity.…Not just gender or racial diversity,…but also a diversity of opinions and background.…They found that team uniformity usually stifles innovation.…
There were two Harvard business school professors…
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