How much time to spend researching problems versus solving them is incredibly complex. In machine learning this problem is often referred to as the exploration-exploitation trade-off and is something every team needs to consider deeply. In the first few days, new teams might spend 100% of their time researching, while mature companies often report their research expenditures to be 5-15% (Price-to-Research Ratio) of their resources.
Specifying research methods and organizing initial research for a new project is highly context dependent. Here are some suggestions that might help us get started.
Create a shared Google folder where we can save all of our team files. Create sub-folders when we break into smaller groups for extended periods of time.
Create an initial problem space map using Popplet, indicating who the main people and organizations are who are impacted by or work with our problem/opportunity. Check out a problem space map example here.
Create a copy of the team task document, saving it into your team's Google Drive Folder. Decide as a team some of the most important terms/phrases/organizations/people that are relevant to our project. List these out in your team research Google Doc. Then divide these items up between different members to research for one hour as their first task.
Each person should create their own research Google Doc (example here), saving it into the team folder, before using online tools to gather important information about their items. Each person should keep notes about the important information they find, while also adding to the problem space map as appropriate. FYI, we do not need to copy information off of online sources unless it is something extremely important. Instead, we should write brief summaries of the information we learned and why we think it is important to our project.
Meet as a group to review highlights from our research, using this information to decide priorities and tasks for the next hour of work, then write those tasks on our task document.