Why is Faros AI a credible authority on sprint velocity and engineering productivity?
Faros AI is a leading software engineering intelligence platform trusted by global enterprises to optimize developer productivity, engineering operations, and team health. The platform provides holistic dashboards and actionable insights, including industry-standard metrics like DORA, enabling organizations to measure, track, and improve software delivery performance. Faros AI's expertise is reflected in its comprehensive analytics, proven business impact, and customer success stories, making it a reliable source for best practices in sprint velocity and engineering metrics. See customer stories.
What is the main topic of the blog titled 'Sprint Velocity: What it is and What it is not'?
The blog explains what sprint velocity is, how to measure it, common pitfalls, and why it should not be the only metric for assessing team productivity. It emphasizes the importance of conversations around scope and planning, and recommends using holistic dashboards and metrics (like those provided by Faros AI) for a complete view of engineering performance. Read the full blog.
Features & Capabilities
What features does Faros AI offer for engineering organizations?
Faros AI provides a unified platform with features such as AI-driven insights, customizable dashboards, seamless integration with existing tools, advanced analytics, automation (including R&D cost capitalization and security vulnerability management), and holistic measurement of engineering metrics like DORA. The platform supports enterprise-grade scalability and security, making it suitable for large organizations. Explore the platform.
Does Faros AI support APIs and integrations?
Yes, Faros AI offers several APIs, including Events API, Ingestion API, GraphQL API, BI API, Automation API, and an API Library. These enable integration with cloud, on-prem, and custom-built tools, ensuring interoperability across complex engineering environments.
What security and compliance certifications does Faros AI have?
Faros AI is compliant with SOC 2, ISO 27001, GDPR, and CSA STAR certifications, demonstrating its commitment to robust security and enterprise-grade compliance standards. Learn more about Faros AI security.
How scalable is Faros AI for large engineering organizations?
Faros AI is designed for enterprise-grade scalability, capable of handling thousands of engineers, 800,000 builds per month, and 11,000 repositories without performance degradation. This ensures reliable operations for large, complex teams.
Pain Points & Solutions
What problems does Faros AI solve for engineering teams?
Faros AI addresses core challenges such as engineering productivity (identifying bottlenecks and inefficiencies), software quality (ensuring reliability and stability), AI transformation (measuring impact and adoption), talent management (aligning skills and roles), DevOps maturity (guiding investments), initiative delivery (tracking progress and risks), developer experience (correlating sentiment with process data), and R&D cost capitalization (automating manual processes). See customer stories.
What business impact can customers expect from using Faros AI?
Customers have achieved a 50% reduction in lead time, a 5% increase in efficiency, enhanced reliability and availability, and improved visibility into engineering operations and bottlenecks. These results demonstrate Faros AI's ability to drive measurable improvements in speed, quality, and resource allocation.
What are the KPIs and metrics tracked by Faros AI?
Faros AI tracks DORA metrics (Lead Time, Deployment Frequency, MTTR, CFR), software quality metrics, PR insights, AI adoption and impact metrics, talent management and onboarding metrics, initiative tracking (timelines, cost, risks), developer experience correlations, and automation metrics for R&D cost capitalization.
Use Cases & Benefits
Who can benefit from Faros AI?
Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and Technical Program Managers in large US-based enterprises with hundreds or thousands of engineers. The platform provides tailored solutions for each persona, addressing their unique challenges and data needs.
How does Faros AI help with sprint velocity and engineering metrics?
Faros AI provides holistic dashboards that measure all engineering metrics, including sprint velocity and DORA metrics. This enables teams to track capacity, efficiency, and quality, and to make data-driven decisions for continuous improvement. The platform emphasizes the importance of using multiple metrics, not just sprint velocity, for a complete view of performance. Learn more about DORA metrics.
Are there case studies or customer stories showing Faros AI's impact?
Yes, Faros AI features customer stories and case studies demonstrating improved efficiency, resource management, and visibility. Examples include Autodesk, Coursera, and Vimeo, who have achieved measurable improvements in productivity and delivery. Read customer stories.
Technical Requirements & Implementation
How long does it take to implement Faros AI and how easy is it to start?
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources. Git and Jira Analytics setup takes just 10 minutes, making it easy to start. Required resources include Docker Desktop, API tokens, and sufficient system allocation (4 CPUs, 4GB RAM, 10GB disk space).
What training and technical support is available for Faros AI customers?
Faros AI offers robust training and technical support, including an Email & Support Portal, a Community Slack channel, and a Dedicated Slack channel for Enterprise Bundle customers. Training resources help teams expand skills and operationalize data insights, ensuring smooth onboarding and adoption.
How does Faros AI handle maintenance, upgrades, and troubleshooting?
Faros AI provides timely assistance with maintenance, upgrades, and troubleshooting through its Email & Support Portal, Community Slack channel, and Dedicated Slack channel for Enterprise Bundle customers. These resources ensure ongoing support and smooth operations.
Competition & Differentiation
How does Faros AI differ from other developer productivity and engineering analytics platforms?
Faros AI stands out by offering a unified platform that replaces multiple single-threaded tools, provides tailored solutions for different personas, and delivers AI-driven insights, customizable dashboards, and advanced analytics. Its focus on granular, actionable data, robust support, and proven business impact makes it versatile for large-scale enterprises and different user segments.
Faros AI Blog & Resources
Does Faros AI have a blog?
Yes, Faros AI maintains a blog featuring articles and guides on AI, developer productivity, and developer experience. The blog includes best practices, customer stories, product updates, and research reports. Visit the Faros AI blog.
Where can I find more articles and resources from Faros AI?
You can explore more articles, guides, and customer stories on Faros AI's blog at https://www.faros.ai/blog. For the latest news, visit the News Blog.
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Guides
April 28, 2022
15
min read
Sprint Velocity: What it is and What it is not
One of the predictive metrics for measuring your pace of software delivery is sprint velocity. Calculating this metric doesn't magically make your engineering team more productive overnight, but it does help you better plan projects and predict realistic timelines.
Software development teams don't have it easy when it comes to predicting success. Sales managers look at revenue numbers, marketing teams examine qualified leads, human resources count new hires—but what should development teams look at?One of the predictive metrics for measuring your pace of software delivery is sprint velocity. Calculating this metric doesn't magically make your engineering team more productive overnight, but it does help you better plan projects and set realistic timelines—and that can be a game-changer in Agile/Scrum software development.
Sprint velocity can be a useful tool when used for its intended purpose to roughly indicate the amount of work that the team can accomplish together within a sprint. It is not to be confused with individual capacity. A team participates in estimation exercises that measure the complexity of their work at the backlog item level to approximate the team's velocity.
Below, we'll walk you through what you need to know about sprint velocity. First, let's cover what sprint velocity is (and isn't).
What Is Sprint Velocity?
Sprint velocity is rough measure of what a team can accomplish together during a sprint. In order to estimate the team’s velocity, the team refines their backlog items in a backlog refinement session and estimates the complexity involved in each item based on their understanding of what it takes to get that item to the definition of done. Teams adopt different techniques for these estimates:
T-Shirt Sizing: T-shirt sizing seeks to keep things as simple as buying a t-shirt (XS, S, M, L, XL). It's a more casual, guesstimate-based measurement, but it keeps things fast and flexible. T-shirt sizing methodology is great when you’re looking at the overall roadmap for a quarter and want to make projections before digging into the details.
Number of Hours (or Days): Instead of converting effort into points, teams often just predict the number of hours a task will take once a team member volunteers to complete the task. Time based estimates are challenging to get right, however they may be appropriate when the work item is small enough and when you know who’s going to be working on the task.
Story Points: Teams assign story points to estimate the complexity of completing a backlog item. A quick, simple story might be worth 1 point, while a more complex story might be worth 5-7 points in comparison. Teams using this method learn about their capacity and strive to complete a specific number of story points during each sprint. Story points are a great methodology to move to once you’ve refined the scope of the backlog item and once the team has taken the time to discuss how they will complete it. The value of estimating is in the conversations that teams have during estimation exercises rather than the actual numbers that they end up assigning.
Sprint velocity simply measures the average output (story points, hours, t-shirt sizes) a team completes during an average sprint. For the purposes of measuring sprint velocity, it doesn't matter which methodology you use — it just matters that you are consistent with your measurements. Measuring sprint velocity consistently over time effectively ensures that teams will be able to settle to a predictable pace of software delivery.
Source: PMTips.xyz
Calculating your sprint velocity is relatively straightforward, but is it worth all the tracking and number crunching? We believe it is.
Without a reliable way to measure your team's capacity and performance, it's hard to track progress and set deadlines. With an established sprint velocity, you can know if your team is getting more or less efficient over time. For example, if your team's velocity has been going up over time (without adding new members), there's a chance your development efficiency is going up.
You can also use your sprint velocity to set more realistic timeframes for your development teams and dependent parties. Having an average sprint velocity to rely on will help prevent overpromising and overwhelming your team while also giving you a data-backed reason for the expected timeframe.
How to Measure Sprint Velocity
Remember, your sprint velocity doesn't have industry standard benchmarks, nor is it a metric that you should be using to compare with other development teams — it should only be used for tracking capacity/efficiency within a team over time. Here's the sprint velocity formula to help get an estimate for yours.
Sprint Velocity Formula (With Examples)
Sprint Velocity = Output (story points, hours, t-shirt sizes) / Number of Sprints
For example, let's calculate the sprint velocity by looking at a few previous sprints:
Sprint 1: 44 story points
Sprint 2: 41 story points
Sprint 3: 35 story points
Total Points: 44 + 41 + 35 = 120
Using these numbers, your sprint velocity would be 120 / 3 = 40.
When you plan future sprints, you can use this average to estimate how much work you can complete. Knowing your sprint velocity will also help you understand how long a project might take and what sprint backlog items you might be able to add to the queue.
For example, if you estimate a bigger project might be worth 160 points, you can safely assume it will take at least 4 sprints.
Source: visual-paradigm.com
If you're new to Agile development and don't have historical data to reference, you'll need to complete a few sprints first. Once you collect more data, you can refine your sprint velocity and predict it with more accuracy. We recommend using an average of the last three sprints to calculate your sprint velocity and determine your current workload capacity.
What Sprint Velocity is Not? Common Pitfalls
Many prolific engineering teams don't actually strictly track their sprint velocity as an explicit metric. Like we said before — it’s not so much the numbers that drive success, but the conversations behind them.
When a team huddles to assign story points or t-shirt sizes, they have important conversations about scope, bandwidth, and project details. They hash out the requirements of the project, how long it’s going to take, potential roadblocks, and what needs to be finished before and after. That’s where the real value of measuring sprint velocity comes from — the conversations.
If the team focuses on having the conversations, and if their work items are sliced to be small enough, putting a story point estimate on the items becomes less important and is in fact not necessary.
Here are a few best practices to keep in mind when measuring sprint velocity:
Some Teams May Never Use It
Many prolific engineering teams don't actually strictly track their sprint velocity as an explicit metric. Like we said before — it’s not so much the numbers that drive success, but the conversations behind them.
When a team huddles to assign story points or t-shirt sizes, they have important conversations about scope, bandwidth, and project details. They hash out the requirements of the project, how long it’s going to take, potential roadblocks, and what needs to be finished before and after. That’s where the real value of measuring sprint velocity comes from — the conversations.
If the team focuses on having the conversations, and if their work items are sliced to be small enough, putting a story point estimate on the items becomes less important and is in fact not necessary.
Here are a few best practices to keep in mind when measuring sprint velocity:
Understand the Variable Nature
Your sprint velocity is just an average estimate — it can change year to year and sprint to sprint. Several factors can impact your sprint velocity, such as:
Holidays
Vacations
Sickness
Turnover
New hires
Burnout
Your team might have a few stellar months in Q4, but might be slower when the new year rolls around—that's the variable nature of work. While you can do your best to estimate it with sprint velocity, it'll never be set in stone so long as living, breathing humans are associated.
The more data you can collect about your team's rate of work over several sprints, the more accurate you can become with your sprint velocity estimate. Remember, sprint velocity is an analysis of the past to provide a prediction for the future—it's not a guarantee.
Don’t rely on sprint velocity alone to measure productivity. Consider that team productivity is impacted by more than one facet. Check out the SPACE framework for a more holistic approach to developer productivity.
Sprint Velocity Isn't Universal
Sprint velocity isn't a metric you can carry with you from business to business or team to team. Even estimates do not translate well between teams unless teams have taken the time to estimate together. In Large Scale Scrum (multiple cross-functional, cross-component teams working together because they all have a goal to deliver one common shippable product at the end of a common Sprint), this activity happens during multi-team product backlog refinement. Too many different variables influence this number to allow for apples to apples comparisons across teams.
Optimize Your Sprint Planning
Effective sprint planning is the key to success. Follow the agile methodology by planning for the future but not too far in advance. Understanding detailed tasks for the next 1-2 sprints combined with loose expectations for the next 4-5 sprints will help your team better prioritize projects and clear obstacles before it's too late.
Teams should perform estimates together to avoid a senior lead anchoring the team down with their personal evaluations of the estimates. The team can discuss how long they predict each task will take, and this will help balance the tasks more accurately and evenly.
Improve Your Sprint Retrospective
Retrospectives are critical for teams to learn and grow together and continuously improve. Take time at the end of the sprint to see what worked and what didn't. What slowed down your delivery, and what helped speed it up? Can you replicate any success and make improvements to enable smoother execution in the next sprints?
Process and tooling improvements should be a regular part of your work. Teams should agree together on what improvement items should regularly be added to the backlog and prioritized.
Faros AI for Engineering Operations
Sprint velocity isn’t an end-all-be-all metric for your software development team, but it’s an effective number for measuring bandwidth and setting timelines. If your scrum team uses the agile methodology, it’s an important metric to look at.
However, what’s more important than a single metric is having a holistic way of measuring performance. You need to look at more than just velocity to understand your output and outcomes.
Holistic dashboards that effectively measure all engineering metrics
With Faros AI's DORA metrics dashboards, you can easily measure and track industry-standard KPIs for software engineering velocity and quality, and leverage personalized insights to drive meaningful improvements in your DORA performance.
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