Assemble your Playbook participants
The Data Cards Playbook is designed to adapt to a variety of team structures and sizes. It runs best with at least 5 cross-functional team members responsible for the dataset participating. Bonus points if the audience of the Data Cards and users represented in the data are present.
An ideal group includes the core team producing the dataset and Data Card, agents who will use the dataset and Data Card, and users who may have contributed data.
Taxonomy of Stakeholders
Explore our Taxonomy of Stakeholders and their responsibilities as you decide who to invite to your Playbook activities.
Assign roles for the Playbook
To make the most efficient use of your shared time, keep a designated Facilitator, Note-Taker, and Troublemaker.
Responsible for running the Playbook through its course. The facilitator should be familiar with the Playbook and its expected outcomes. While they may or may not participate in the various activities throughout the Playbook, they should be familiar with the Playbook and its expected outcomes, they:
- Keep the activities on time
- Establish an environment for participants to be effective
- Work closely with note-takers to record all material produced through the Playbook
Note-takers capture as much of the conversation as possible. There may be one or multiple note-takers. Responsibilities include:
- Record key ideas, Q&As, and action items from discussions, whiteboards, and parking lots
- Synthesize the group’s top ideas after each round
- Own the Activity Tracker
Also known as 10th (hu)man, devil’s advocate, or the challenger. There may be more than one troublemaker in the room. Discussions with the troublemaker(s) should be productive rather than antagonistic as they:
- Poke holes in generated material and concepts
- Challenge the room
- Encourage the team to think beyond the obvious
🚥 Keep it general
The Playbook is designed to capture the ideas and needs of entire cohors of people.
🍇 Leverage the group’s knowledge
Encourage all participants to lean into what they know about datasets, readers of documentation, and experts in the dataset’s domain.
🤯 Think broad and narrow
Consider both extreme and mainstreme cases for a balanced and multi-faceted approach.
🔨 Consider levels of expertise
Readers of Data Cards have varying domain expertise and fluency in working with data.