When planning out software development, it is important to include Agile Metrics into your process. This is because they can help with the quality of your software as well as help with monitoring the productivity throughout every stage.
With the introduction of Agile metrics into the software development process, it will also give a clearer understanding of the process. Agile metrics also make it easier for a scrum master to manage their teams’ progress.
It’s no surprise that there are multiple different kinds of metrics, however the most useful metrics for software quality, productivity, performance/well-being and general project metrics are agile metrics.
With that being said, the main 3 types of agile metrics are:
Scrum Metrics - the most common
Kanban Metrics - this is an agile software development structure similar to the scrum methodology
Lean Metrics - used to streamline the manufacturing process of both the kanban and scrum metrics.
Agile Quality Metrics
A group of agile software development metrics that will help you monitor the software development process. This will help determine if the target audience will approve.
Escaped Defects:
These will help you identify bugs that are within the software after it is in production. This metric allows your team to access the quality of your software in a raw format.
Failed Deployments:
These will assist with determining the amount of deployments to testing and production. Failed deployments will shed light on how reliable the software is.
Release Net Promoter Score (NPS)
This will measure the reaction of users to a given release.
This metric will help determine who will recommend the software product
Net Promoter Score is also known as a customer satisfaction metric
Agile Productivity Metrics
With agile productivity, it helps with keeping your team on track when completing stories, and tasks. Agile productivity also has the ability to make predictions for future projects so your team can try to avoid any unexpected changes.
Lead Time:
This allows for constant monitoring on a project, from backlog to release.
The goal is to ensure the lead time is low, because that means it is more effective.
Lead time is an agile metric that allows for an overarching view on the various productivity methods
Cycle time (Control Chart):
This helps you measure the average time needed to complete a task.
The shorter the better
Sprint Burndown:
This is one of the most effective agile productivity metrics.
It allows you to monitor the process of task
It provides you with data on how agile your team actually is
Epic and Release Burndown:
The biggest benefit to the Epic and release burndown, is the ability to track and manage the scope creep - the addition of new requirements after project scope is established.
This metric will assist you and your team to make sure you won’t fall behind in productivity
Velocity:
This allows you to check on the average number of finished points on past sprints.
Benefits of velocity include:
Easy to measure
Showing a concise result immediately
Lower velocity may be a sign of emerging sprint inefficiencies
Agile Project Metrics
This is a cool addition to the previous metrics, because it gives you a chance to grab the information that involves action, and apply it to your development processes.
Cumulative Flow:
This is one of the most powerful agile project metrics for kanban. It offers an overhead view of the status of every task that’s being completed.
Code Coverage:
This will help you measure the amount of your product’s code that is monitored by unit tests. This metric does not measure other types of testing.
Health Metrics for Agile Teams and Agile Performance Metrics
Agile software development metrics is typically geared toward monitoring software quality and team productivity at each stage.
Happiness:
Individually we don’t specifically go by a way to monitor happiness in a software development team. The easiest way to do this is just to ask each team member to rate how they are feeling.
Team Morale:
This allows for a subtle approach for sudden mood swings that may occur within the team.
Core Lean and Kanban Metrics
Exploring the lean key metrics and kanban methods that are common for both software development and goods manufacturing.
Story Lead and Cycle Time - (SLT):
This helps you track the amount of time passed from when a task is started to when it is finished. The ultimate goal for SLT is to assist teams in checking and reducing the speed of the value chain. Story Cycle Time (SCT) is a part of Story Lead Time, however it only assesses the time of a task. This helps track and reduce the hours spent on it.
Feature Lead and Cycle Time - (FLT) and (FCT):
Similar to Story lead and cycle time, feature lead time is the same concept, except instead of being for the overall story/task it's for the major features. Feature cycle time is also identical to story cycle time, just for features.
Story Wait Time - (SWT):
Another component that is linked to Story lead time. This metric helps you manage the resting time of a task. Each team should aim to reduce the SWT as much as possible.
Story Throughput - (ST):
This is a similar concept to Sprint Velocity in a sense that it helps count the number of stories finished in a sprint. Story throughput works best when it works with smaller stories.
Created to Finished Ratio:
This means that too many projects are on backlog and not enough have been finished. This metric is helpful because it helps control the number of project bottlenecks, ensuring there’s a balanced number between projects started and projects finished.
Measuring Software Quality in Agile
In today’s world everyone expects things to happen instantly, and that’s no exception to the software industry. Using Agile metrics to measure the software quality makes the process just that much quicker. With that being said, despite the fact agile helps quicken the process, it is inseparable from security.
When preparing code for agile metrics, it is crucial to be as comprehensive as possible. There are 2 code analysis systems and one comprehensive approach to help streamline the process of quality assurance.
Here they are listed:
Static Code Analysis:
Allows you to check on the source code without having to run the software. It detects bugs, security issues and other shortcomings before they become bigger problems. This allows time for your team to create a product with clean code.
Dynamic Code Analysis:
This is the opposite to what static code offers, where it lets you evaluate the code when it is running. Static code analysis takes dominance when analyzing code, but dynamic code allows the quality assurance team to detect different problems from static.
Neither Static Code analysis or dynamic code should be a step that is skipped; they work best as a team.
Quality Intelligence tools provide a plan for helping teams retrieve information from the whole software development process, and then analyze it and improve how it functions.
This selection of Agile Software Development metrics will help you create a software that will function for years. If you’re confused on how any of it works, reach out to one of our experts at ISU Corp today!
