All good managers do it...
Being a good team manager is tough...
Often uncertainty is your biggest enemy, and one of your most important goals is to provide predictability of team results in terms of quality and timings.
So, how to achieve predictability?
This is not a simple question, because software development is not only about algorithms, system analysis and data centers. It ismainly about people and those who believe that their work is kind of art and self-realization.
Not very seasoned managers may think that the only way to go is to rely on a subjective assessment of the team's performance.
This may work in some situations, but it will be useful to combine subjective assessment with more rigorous metrics-based analysis using a Data-Driven Team Management approach. What is it?
Your team generates a lot of digital breadcrumbs and artifacts when it works. These may be issues in Jira, commits in Gitlab, messages in a corporate messenger. Using this data, you can analyze your team, building metrics. Of course, such analysis cannot completely replace the subjective assessment, but it can be an important source of interesting insights.
What tools can you use for building such metrics?
Ad-hoc tools.
Many people prefer to create their own tools. For example, you may download data from Jira and analyze it using Excel. The advantage of this approach is simplicity. The main disadvantage is that such tools do not have the proper level of automation and it is difficult to use them on a regular, daily basis.Built-in analysis tools in Jira, Github, etc.
The advantage is seamlessness. The disadvantage is that such tools can be unavailable to you or not flexible enough, so you cannot analyze specific cases specific of your team.Special DDTM tools.
We can mention, for example, open-sourced Captain-Bridge, with realy good documentation and growing community. It allows you to create custom metrics using syntax of mongo or python and data of Jira, Github, Gitlab, Telegram and Discord.
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