Coding Days

Coding days represent the average number of days per week each developer commits their code to Git. This metric is different from Coding Time.

To calculate Coding Days, Typo counts the number of days for each developer with registered commits in a given week. The same method is used to calculate Coding Days for a team - it’s the average of Coding Days for each developer of that team. As a default, 5 days are considered as a work week. In case this needs to be changed, the configuration can be done accordingly.

Measuring coding days can be a useful metric to assess bottlenecks in the development process, improve Workload Balance & estimate accuracy.

Benchmarking coding days enables engineering teams to optimize resource allocation, evaluate performance, streamline processes, and mitigate risks, ultimately enhancing overall productivity and efficiency.

How does measuring coding days help in improving the Engineering teams' efficiency?

Measuring coding days offers valuable insights into the efficiency and productivity of engineering teams, facilitating continuous improvement and optimization efforts. Here are a few points highlighting how tracking coding days contributes to enhancing engineering team efficiency:

1. Resource Allocation: By monitoring coding days, teams can better allocate resources based on the complexity and duration of tasks. This ensures that team members are assigned tasks effectively, maximizing productivity and reducing idle time.

2. Identifying Bottlenecks: Tracking coding days helps identify bottlenecks in the development process. Teams can analyze patterns of prolonged coding days for specific tasks or projects, allowing them to address underlying issues such as unclear requirements, technical challenges, or resource constraints.

3. Performance Evaluation: Coding days metrics serve as a quantitative measure of team performance. By comparing actual coding days against planned estimates, teams can assess their efficiency and identify areas where improvements can be made.

4. Process Optimization: Insights from coding days data enable teams to optimize their development processes. By analyzing factors contributing to extended coding days, such as inefficient workflows, excessive rework, or inadequate tooling, teams can implement process improvements to streamline development cycles and reduce time to delivery.