Data is an integral part of engineering at Student Beans. We rely on data to know we’re building the right product, to find flaws in our systems, and to measure our company's performance.
In the same way, engineering managers use data to understand the teams’ performance and to debug problems with their processes. We use DORA metrics, among others, to do this.
Lead Time to Change - Average number of hours to complete one change (first commit to deploy)
Deployment Frequency - Average number of deploys per day
Change Failure Rate - Percentage of changes that fail
Productivity Score - Average rating out of 5 for the question “How productive do you feel?”, asked each week
The data is averaged over a 30-day period.
The dataset is contained in the eng_metrics.csv file.
The CSV contains data for three teams. All teams consist of both Backend and Frontend engineers, all at a similar skill level. The teams follow the same processes and are working on one feature each.
The teams are led by a PM, a Delivery Manager, and a Technical Lead - Frank, Laura, and Rob.
This team’s performance is your responsibility, and this data is your insight into their successes and challenges. Interpret the data and highlight:
- Any successes the team are having
- Metrics that indicate there is a problem
- Possible causes for those unsatisfactory metrics
- Actions you would take to help the engineers move those metrics in the right direction
In the interview, you will talk us through your interpretation and the actions you recommend taking. This only needs to be a conversation - no presentation or slides are necessary. But you’re welcome to screen share the data to help your explanation.