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How to use Athenian as a Team Lead?
How to use Athenian as a Team Lead?

As a team lead, when you look at Athenian you get lots of different data. But where should you start, and how do you support your team?

JosΓ© Caldeira avatar
Written by JosΓ© Caldeira
Updated over a week ago

Why is data relevant to a Team Lead?

As a team manager, you must check your team's pulse consistently. This is done based on qualitative and quantitative information. You want to do this to ensure the team is consistently and autonomously optimizing their engineering processes.

Team Leads use engineering metrics to foster and improve:

πŸ‘‰ Communication: Identifying, prioritizing, tracking, and communicating goals and initiative progress across the organization.

πŸ‘‰ Problem discovery: Discovering and correcting technical and managerial problems that can be more difficult or costly to resolve later on. This is done without micro-managing the team, as the overall progress is monitored at the team level.

πŸ‘‰ Measure the impact of decisions: Using metrics as evidence to justify the best alternatives. Team leads must be able to defend their decisions with historical data and justify plan changes with current data.

πŸ‘‰ Guidance and growth: Continuous usage of data to help the team steer in a direction where they autonomously drive improvement, by helping the team identify the core strengths and weaknesses.

πŸ€“ How do they do it?

With qualitative data, you have the capacity to get the team feeling, eNPS, but also where they are struggling the most. To get that information, you can use the following techniques:

However, engineering typically lacks the quantitative impact of changes that are made.

As a manager with Athenian, you want to get data to uncover insights and drive improvement opportunities in your delivery process and/or on the quality of your deliveries so that you measure the impact of your changes.

πŸ“ To do so, teams need to create healthy habits and follow a 3 step approach:

You can use our templates to follow up with the team consistently. But before you do so, remember to provide the context for the team as to why Athenian and engineering data are relevant for the team. As a leader, ensure you set the stage for making the best out of Athenian and what behaviors you want to promote.

1. πŸ‘€ Identify an actionable improvement opportunity and set it as a goal

Start by identifying the relevant context to explore data and identify improvement opportunities that are focused on what matters to your team.

What you have to do:

Pick your team and repos

e.g API team

Select a meaningful time window

1-3 months

Deep dive on an area of focus


Look for trends or spikes

Review Time

Set a goal

6 hours in Q4

Identify a list of activities

- Create a bot to accelerate fast approvals;

- Use team disruptions to review small PRs;

πŸ” Go to one of our dashboards, either Quality related or Velocity related, and start analyzing the data:

In the example above, we start in the Velocity Summary Dashboard, and we notice that PR Cycle Time has been increasing (increasing trend). We can observe that 1/3 of the time is spent on Review.

As a north star, we want to decrease PR Cycle Time by setting a target, but that's a lagging indicator. Focusing on the Review process is a great way to have an impact and measure improvement faster, allowing us to have a leading indicator. So we set the goal of making the review time get below 6 hours.

🚨Once you identify one or two opportunities, deep dive and discuss the actions with the team. You don't want the whole team to deep dive into Athenian, but you want to share findings with them. During this meeting, focus on asking 5 whys until you identify the root cause and list the activities you will implement to improve how the team works.

2. ⏰ Promote consistency through regular checkpoints

Use our Team Activity Log in your team retros to decide what actions you'll take to reach your objectives. Remember that you and the team want to be intentional about the process and the improvements. The template follows the following sequence of steps:

2.1. Set a goal for a specific period to promote alignment and focus

e.g. "Reduce review time to 6 hours"

Set an achievable goal that will help the team stay focused on a specific area of improvement. People easily get lost looking at all the data available.

2.2. Identify activities that the team will take on to improve

e.g. "Create a bot to call reviewers when the review is taking too long"

Identify 1 or 2 activities the team will do until the next checkpoint. Keep these activities simple.

πŸ“£ Team improvement comes from consistency and not from intensity.

2.3. Every 2-3 weeks, use team retros to course correct

e.g. "Review decreased from 8 to 7.5 hours, because the time to first review decreased"

Check Athenian and set last month's data to validate the short-term trend and to deep dive with the team. Always identify 1 improvement activity that the team will perform until the next checkpoint, and validate if the activity you have put in place in the previous iteration worked.

2.4. Monitor and celebrate progress regularly

e.g. "Let's celebrate because we have been consistent in the last 2 sprints"

Use 1:1s and dailies to remind team members of missing action items blocking the goal, coach them, and remove impediments (our training provides you with examples for each metric).

πŸ₯³ When you reach the end of a cycle, and you see an improvement remember to celebrate, as some of these will be small wins it's common to forget that they are wins.

3. 🎯 Reinforce a growth mindset

It's common to have team members eager to jump into data and others who mistrust it, so ensure you follow these important considerations when discussing data:

β˜‘ Never make it personal - people will make it a personal issue, but you are finding opportunities for improvement; places where the system is failing, so reinforce that message;

β˜‘ Be curious - don't expect Athenian to tell you what to do. Use the data and ask questions to identify opportunities;

β˜‘ Challenge the status quo - don't assume everything the team/organization is doing is at its best. You are responsible for setting the standards;

β˜‘ Avoid rabbit holes - as engineers, we tend to focus on the details. If you see a data point and feel odd, reach out to us, and we will help you read the data, but avoid deep conversations around a single data point. You want to focus on trends and patterns;

β˜‘ Drive consistency - the idea is not to create an overnight improvement. It's to create a repeatable process to drive improvement;

β˜‘ Don't look for benchmarks - define your own goals. You want to make changes and see how the team compares with itself over time. You want to create a better version of your team;

β˜‘ Look for best practices - everyone can see data in Athenian, so you should use Athenian to identify which teams are doing better at something. Engage with their leaders and leverage their findings if applicable;

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