Hopefully, with every project that you work on, you learn new things. For example, how to effectively break down work to ship more incrementally. Or, a new programming language the engineering team has tried. Or, more depth into your problem domain from customer feedback. In most cases, this tacit knowledge lives and leaves with you.
Knowledge-sharing across teams is hard and as a result, it rarely happens. It's often undocumented, lost in a silo, or locked down in some random Drive folder. And this comes at a cost. Studies have found that when an employee leaves their job, coworkers are unable to do 42% of that job due to inefficient knowledge-sharing.
What if knowledge could be retained and shared openly? If future teams working on similar projects could continue to build on that knowledge? if anyone across your company could quickly get the context they need and easily identify experts in various topics?
Picture this: Your team has been given a new project on an unfamiliar topic. Usually, in order to get started, you’d need to spend a lot of time conducting research and trying to identify who knows about the topic in your company in order to slowly build context.
What if instead you could get a jumpstart based on what’s already known by contextually discovering learnings recorded by other teams that have worked on projects tagged with the same topic? By connecting learnings to updates on how a project is progressing in Atlas, we enable anyone to get additional context and identify the best teams to speak with based on what they’re trying to achieve. That’s the power of Atlas projects, teams and knowledge in motion.
Sold? Great. Here’s how it works
As a project owner or contributor, as you write your weekly update, we encourage you to reflect on what you learned during the week. You can also capture a learning at any time by visiting the Learning tab for a project you own or contribute to.
Contributors and other teams are notified of new learnings in-app and by email.
And, learnings also show up in Atlas search results.
But the real beauty of capturing learnings in Atlas is that they are ready for the next team that comes along to benefit from. When you create a new project and tag it based on topics it’s based on, Atlas will recommended related learnings from similar projects also tagged with those topics.
The ingredients of an effective learning
At Atlassian, we’ve defined a learning as:
Knowledge gained on a topic from your environment (customers, analytics, team processes, research, etc.) that is useful for relevant teams, both direct and external to the work.
Learnings should be curated, shareable, and evolve over time. That’s why we can always update an existing learning as your knowledge grows and understanding of it deepens.
When it comes to capturing a learning, we encourage you to ask yourself, “what do I wish I knew when I first started this project?”, and, “what would I tell someone else working in this space?”.
But, what’s the difference between an Atlas learning and a retro item?
Retros may take fortnightly/monthly and is tied to the team running them. Learnings tend to occur at any time as a project progresses, and they are tied to the work, not the team.
While the audience for a retro is the direct team, learning should be useful outside of the team. Hence, we believe that a retro item summarises what’s happened within the team, whereas a learning is an insight from the discussion that’s of utility to other teams.
Ready to starting learning? 😉 Jump into a project you own and hit the Learnings tab to capture in your first one.