Create your own dashboards

Giving the engineering team the power of deciding what to track is the biggest motivator for us to create the custom dashboard feature. The idea is to have the capabilities of a BI tool without the hassle of integrating multiple data sources, linking them, and defining metrics on your own. Custom dashboards allow you to create your own visualizations over the metrics you want and define your own way to look at these over different groupings and save and share with your team members on AnalyticsVerse.

The use case is stemming from the primary idea that no two engineering teams are identical, not even within the same organization. With different dynamics, teams want to define their own ways to improve things and want the ability to mix and match metrics and insights across different processes and have their own dashboards created that are tailor-made for them.

Where do I start my journey of tracking engineering metrics?

We are always in favor of starting small, we know it better than anyone else. And every team can take any 5 metrics from each of the different processes and start tracking them, and over time learn which one works for them better. And eventually, try to expand their horizon of metrics to improve on. Often when you are starting in this journey of engineering improvements, you want to eliminate all the noise and want your team to focus on the metrics that matter, thus creating your own dashboard of things that matter to you could be the best way to get started.

Also, it’s often the case that different functions within the same team would need to look at different aspects of data, example your scrum master may be super interested in looking at an overall sprint level and other metrics related to planning whereas a view of an engineering lead could be overall health on the processes and the team. Creating views by function is something we wanted to enable for your teams as well.

An example of creating your own dashboard

Let’s say we want to create a dashboard “Engineering metrics” which consists of metrics we want to be tracked for this quarter at an organization level.

Creating our dashboard with the right name and description

We will then configure our first metric Average MR open time across all teams. (Selecting multiple projects and selecting the time period using the date picker)

Configuring our first visualization

And then configure our second visualization to track churn across the last 5 sprints (selecting churn metric and view over as the last 5 sprints)

Adding a visualization of churn across sprints

And then add a visualization to look at risky commits across our team members across the org (selecting the risky commits metric for all projects and selected team members including the team average over a time period of the last 3 months)

Risky commits by team member

This is how our dashboard looks after creating these visualizations

A complete view of our dashboard

Once we have created this dashboard we can also zoom into any of the visualizations by interacting with the chart and get a detailed view of these metrics as well

Detailed view of a visualization

Also super easy to share this with any team members using the share button on the top

Share access with team members

Use cases of custom dashboards

There are a good amount of use cases that we have tried to achieve using the custom dashboard feature, enlisting a few ways of what you can achieve using this for your engineering teams.

1. Combined view across value streams One of the very common use cases is when you have multiple projects (representing teams/value streams in your organization) you would want to also have a rolled-up view of how a particular product line or an entire division is doing.
2. Look at trends across sprints/iterations Looking at trends of a metric across sprint gives you a view into how your team has been doing at a sprint level and drives action, as an example in our dashboard above we see churn trends over the last 5 sprints.
3. Individual team member level metric You can easily view metrics that matter like merge request reviews done by each team member within the team to understand the amount of review workload on individual team members.
4. Time period based view View your own metrics across custom time periods, like we created a dashboard for a quarter, whereas someone else can create for an entire year or a month based on their cycles.
5. Complete detailed driven visualization Looking at trends definitely gives you a picture of where things can be going wrong, but to understand why and what needs to be done to improve you need to get into the details of why things are the way they are for which we had created the zoom/details view to look into every data point in detail so you can genuinely drive action looking at this data.

How is this different from Jira Dashboards?

1. Within our custom dashboards, you get detailed metrics from your git repositories which include your commit activities, merge requests, tags, and deployments. Which helps you get a broader picture of your different engineering processes.
2. Even for Jira data like issues, sprints, and epics, we have a lot of co-related and actionable metrics to make this more meaningful for your teams, for example, we automatically link your commits, merge requests, and even deployment metrics to sprints and epics so you can easily look at trends across the past sprints and epics. One good example is the type of work your team is doing in a sprint.
3. AnalyticsVerse allows you to create your own visualizations on the metrics that matter to you rather than selecting from a list of pre-built components.
4. AnalyticsVerse is built with keeping continuous improvement in mind, thus looking at a number alone may not always be sufficient, we give a seamless way to look at trends across time, sprints epics, and many more to help you understand what part of your processes you need to pay attention to.

Can’t I achieve the same using a standard BI tool?

Yes, definitely you can, if you want to go through the process, let me list down what you would need to do.

1. Integrate with all your data sources
2. Create the right project/value stream/team segregation for your organization
3. Co-relate data across users within different domains
4. Compute not only statistical metrics but ones that depend on your historical data
5. Co-relate data across different entities, example figure out a way to relate commits to sprints
6. Have a way to view trends as well as details into the metrics

I know this doesn’t sound easy. And although theoretically it can be done, it is not at all practical. Because BI tools will not give you these metrics computed out of the box and computing them is a task, believe us.

What’s coming up?

We are also constantly trying to hear out the early feedback from our users and figure out the most valuable additions to this feature. A few of them are listed here

1. We have already added 30+ metrics that you can view, and are soon planning to add 25 more to this dashboard
2. We are soon going to support different types of components as well like tabular data, or a number representing an average over time, this gives more flexibility over the type of visualizations.

If you like the idea of creating your own dashboards for your engineering teams to experiment and explore what works best for you, you can visit here and start your free trial today.