blog

January 31, 2021

•5 min read

8 scrum metrics to measure the effectiveness of your team

cover

What are scrum metrics?

By now most of us know the advantages of using agile for software development projects. Scrum helps agile teams organize their workflow. Scrum, according to scrumguides.org:

is a lightweight framework that helps people, teams and organizations generate value through adaptive solutions for complex problems.

Scrum, an agile methodology, uses time-boxed sprints to organize projects. Time-boxing simply means that the sprint has a fixed time in which the team must complete the sprint. Each sprint typically lasts from one to four weeks.

When operating within the scrum framework the software development team uses scrum events to manage iterations and control the process.

Related post: Scrum vs. Extreme Programming (XP): What’s the difference?

Scrum events include:

Sprint planning

The team meets at the beginning of a sprint to define tasks; they determine the scope of work they will accomplish during the sprint. The team reviews items in the backlog that they will add to the upcoming sprint. The sprint goal is being determined.

Daily scrum

The daily scrum is a short meeting each day where the development team discusses progress and possible problems. They should also discuss how much time remains in the sprint. This will help them set the burndown metric. Burndown metric refers to the rate at which the team completes the sprint.

Sprint retrospective

The meeting at the end of each sprint. In the sprint retrospective, the team reviews their process to establish where they did well and where they can improve with the next sprint. They will review backlog items and establish any new features to add. The team should be honest about flaws and bugs. Scrum relies on transparency.

So what exactly do we mean by scrum metrics? Scrum metrics help us measure how well we are managing our project. When we plan our sprints, we set out what we will achieve. We set out our goals using KPIs (Key Performance Indicators). KPIs help the scrum master and development team chart progress and meet goals.

Let’s examine 8 scrum metrics in three categories. The categories are:  Metrics that measure effectiveness, KPIs that measure deliverables, and metrics that track team productivity:

 

Metrics that measure effectiveness

Time to market

Time to market means the time that the project takes from the first idea until it begins to attract customers and generate revenue.

ROI (Return on Investment) 

ROI (Return on Investment) helps the team calculate the actual revenue generated after the costs of the sprints are taken into account. Scrum and agile typically deliver better returns because the development process is faster.

Capitol Redeployment

With capitol redeployment we determine whether the scrum project should continue with further sprints. The team analyses backlog and the cost of completing the needed sprints. If the team would prove move valuable on other projects, they should be redeployed to those projects.

Customer Satisfaction

Through surveys and user testing, the team can determine whether each sprint gives users more satisfaction. If users consistently report satisfaction with each release, then the team knows they are providing real value with each sprint.

KPIs that measure deliverables

Sprint burndown

Sprint burndown means the rate that the team accomplishes the tasks set out at the beginning of the sprint.  The burndown should be a gradual slope downward. This shows that the team planned the sprint well.

Velocity

Velocity refers to the average amount of work a development team accomplishes during a sprint. Velocity helps the scrum master and product owner predict how a development team will complete the project backlog. Velocity will change over the course of a project as the team becomes more experienced with the project. Most of the time this means that the velocity increases. A downturn in velocity may signal that some part of the process is not working properly. The team should discuss this in the new review meeting.

Metrics that track team productivity

Retrospective process improvement

The sprint retrospective is the metric by which we gauge the team’s ability to become more efficient. They do this by analyzing past springs and determining which changes will make the process more effective. They can do this by looking closely at the project backlog before and after the sprint.

Control charts

Control charts help us understand the time the team requires to complete new features or items in the backlog. Teams aim for consistent progress with quick, predictable results. Teams should not use control charts to micro-focus. Rather, they should use the charts to spot larger trends. Development teams need to pay special attention to increases in cycle time. Teams should also note when cycle time appears erratic. Either one could signal bottlenecks or bugs in the development project. Here is a list of agile tools each team should know about to measure productivity and spot trends.

So how can you scrum metrics to optimize delivery?

Scrum metrics help teams deliver optimal results by giving the team precise tools to measure success. Metrics allow development teams to analyze what works and doesn’t work in each sprint. This information helps them plan future sprints, making the process more streamlined and transparent. 

Agile development methodology sets out the framework. Scrum metrics provide specific feedback and quantify what the team does well and what they need to improve upon. Using metrics allows the team to collect data and measure the progress of each sprint in precise terms.

Using Time to market, ROI, and customer satisfaction metrics teams measure their effectiveness.  By using such metrics as velocity and spring burndown, they measure the deliverables the sprint produces. Through the use of retrospective process improvement and control charts, they track team productivity.

At Blocshop, we use scrum metrics to deliver software projects on time and under budget. We believe agile and scrum give us the best tools to plan and measure success for our clients. If you’d like to learn more about how we can use the power of scrum metrics to help you in your software development project, please get in touch!

Learn more from our insights

cover-img

NOVEMBER 3, 2025 • 7 min read

CE marking software under the EU AI Act – who needs it and how to prepare a conformity assessment

From 2026, AI systems classified as high-risk under the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) will have to undergo a conformity assessment and obtain a CE marking before being placed on the EU market or put into service.

cover-img

October 19, 2025 • 7 min read

EU and UK AI regulation compared: implications for software, data, and AI projects

Both the European Union and the United Kingdom are shaping distinct—but increasingly convergent—approaches to AI regulation.

For companies developing or deploying AI solutions across both regions, understanding these differences is not an academic exercise. It directly affects how software and data projects are planned, documented, and maintained.

cover-img

October 9, 2025 • 5 min read

When AI and GDPR meet: navigating the tension between AI and data protection

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

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September 17, 2025 • 4 min read

6 AI integration use cases enterprises can adopt for automation and decision support

 

The question for most companies is no longer if they should use AI, but where it will bring a measurable impact. 

logo blocshop

Let's talk!

blog

January 31, 2021

•5 min read

8 scrum metrics to measure the effectiveness of your team

cover

What are scrum metrics?

By now most of us know the advantages of using agile for software development projects. Scrum helps agile teams organize their workflow. Scrum, according to scrumguides.org:

is a lightweight framework that helps people, teams and organizations generate value through adaptive solutions for complex problems.

Scrum, an agile methodology, uses time-boxed sprints to organize projects. Time-boxing simply means that the sprint has a fixed time in which the team must complete the sprint. Each sprint typically lasts from one to four weeks.

When operating within the scrum framework the software development team uses scrum events to manage iterations and control the process.

Related post: Scrum vs. Extreme Programming (XP): What’s the difference?

Scrum events include:

Sprint planning

The team meets at the beginning of a sprint to define tasks; they determine the scope of work they will accomplish during the sprint. The team reviews items in the backlog that they will add to the upcoming sprint. The sprint goal is being determined.

Daily scrum

The daily scrum is a short meeting each day where the development team discusses progress and possible problems. They should also discuss how much time remains in the sprint. This will help them set the burndown metric. Burndown metric refers to the rate at which the team completes the sprint.

Sprint retrospective

The meeting at the end of each sprint. In the sprint retrospective, the team reviews their process to establish where they did well and where they can improve with the next sprint. They will review backlog items and establish any new features to add. The team should be honest about flaws and bugs. Scrum relies on transparency.

So what exactly do we mean by scrum metrics? Scrum metrics help us measure how well we are managing our project. When we plan our sprints, we set out what we will achieve. We set out our goals using KPIs (Key Performance Indicators). KPIs help the scrum master and development team chart progress and meet goals.

Let’s examine 8 scrum metrics in three categories. The categories are:  Metrics that measure effectiveness, KPIs that measure deliverables, and metrics that track team productivity:

 

Metrics that measure effectiveness

Time to market

Time to market means the time that the project takes from the first idea until it begins to attract customers and generate revenue.

ROI (Return on Investment) 

ROI (Return on Investment) helps the team calculate the actual revenue generated after the costs of the sprints are taken into account. Scrum and agile typically deliver better returns because the development process is faster.

Capitol Redeployment

With capitol redeployment we determine whether the scrum project should continue with further sprints. The team analyses backlog and the cost of completing the needed sprints. If the team would prove move valuable on other projects, they should be redeployed to those projects.

Customer Satisfaction

Through surveys and user testing, the team can determine whether each sprint gives users more satisfaction. If users consistently report satisfaction with each release, then the team knows they are providing real value with each sprint.

KPIs that measure deliverables

Sprint burndown

Sprint burndown means the rate that the team accomplishes the tasks set out at the beginning of the sprint.  The burndown should be a gradual slope downward. This shows that the team planned the sprint well.

Velocity

Velocity refers to the average amount of work a development team accomplishes during a sprint. Velocity helps the scrum master and product owner predict how a development team will complete the project backlog. Velocity will change over the course of a project as the team becomes more experienced with the project. Most of the time this means that the velocity increases. A downturn in velocity may signal that some part of the process is not working properly. The team should discuss this in the new review meeting.

Metrics that track team productivity

Retrospective process improvement

The sprint retrospective is the metric by which we gauge the team’s ability to become more efficient. They do this by analyzing past springs and determining which changes will make the process more effective. They can do this by looking closely at the project backlog before and after the sprint.

Control charts

Control charts help us understand the time the team requires to complete new features or items in the backlog. Teams aim for consistent progress with quick, predictable results. Teams should not use control charts to micro-focus. Rather, they should use the charts to spot larger trends. Development teams need to pay special attention to increases in cycle time. Teams should also note when cycle time appears erratic. Either one could signal bottlenecks or bugs in the development project. Here is a list of agile tools each team should know about to measure productivity and spot trends.

So how can you scrum metrics to optimize delivery?

Scrum metrics help teams deliver optimal results by giving the team precise tools to measure success. Metrics allow development teams to analyze what works and doesn’t work in each sprint. This information helps them plan future sprints, making the process more streamlined and transparent. 

Agile development methodology sets out the framework. Scrum metrics provide specific feedback and quantify what the team does well and what they need to improve upon. Using metrics allows the team to collect data and measure the progress of each sprint in precise terms.

Using Time to market, ROI, and customer satisfaction metrics teams measure their effectiveness.  By using such metrics as velocity and spring burndown, they measure the deliverables the sprint produces. Through the use of retrospective process improvement and control charts, they track team productivity.

At Blocshop, we use scrum metrics to deliver software projects on time and under budget. We believe agile and scrum give us the best tools to plan and measure success for our clients. If you’d like to learn more about how we can use the power of scrum metrics to help you in your software development project, please get in touch!

Learn more from our insights

cover-img

NOVEMBER 3, 2025 • 7 min read

CE marking software under the EU AI Act – who needs it and how to prepare a conformity assessment

From 2026, AI systems classified as high-risk under the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) will have to undergo a conformity assessment and obtain a CE marking before being placed on the EU market or put into service.

cover-img

October 19, 2025 • 7 min read

EU and UK AI regulation compared: implications for software, data, and AI projects

Both the European Union and the United Kingdom are shaping distinct—but increasingly convergent—approaches to AI regulation.

For companies developing or deploying AI solutions across both regions, understanding these differences is not an academic exercise. It directly affects how software and data projects are planned, documented, and maintained.

cover-img

October 9, 2025 • 5 min read

When AI and GDPR meet: navigating the tension between AI and data protection

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

cover-img

September 17, 2025 • 4 min read

6 AI integration use cases enterprises can adopt for automation and decision support

 

The question for most companies is no longer if they should use AI, but where it will bring a measurable impact. 

logo blocshop

Let's talk!

blog

January 31, 2021

•5 min read

8 scrum metrics to measure the effectiveness of your team

cover-img

What are scrum metrics?

By now most of us know the advantages of using agile for software development projects. Scrum helps agile teams organize their workflow. Scrum, according to scrumguides.org:

is a lightweight framework that helps people, teams and organizations generate value through adaptive solutions for complex problems.

Scrum, an agile methodology, uses time-boxed sprints to organize projects. Time-boxing simply means that the sprint has a fixed time in which the team must complete the sprint. Each sprint typically lasts from one to four weeks.

When operating within the scrum framework the software development team uses scrum events to manage iterations and control the process.

Related post: Scrum vs. Extreme Programming (XP): What’s the difference?

Scrum events include:

Sprint planning

The team meets at the beginning of a sprint to define tasks; they determine the scope of work they will accomplish during the sprint. The team reviews items in the backlog that they will add to the upcoming sprint. The sprint goal is being determined.

Daily scrum

The daily scrum is a short meeting each day where the development team discusses progress and possible problems. They should also discuss how much time remains in the sprint. This will help them set the burndown metric. Burndown metric refers to the rate at which the team completes the sprint.

Sprint retrospective

The meeting at the end of each sprint. In the sprint retrospective, the team reviews their process to establish where they did well and where they can improve with the next sprint. They will review backlog items and establish any new features to add. The team should be honest about flaws and bugs. Scrum relies on transparency.

So what exactly do we mean by scrum metrics? Scrum metrics help us measure how well we are managing our project. When we plan our sprints, we set out what we will achieve. We set out our goals using KPIs (Key Performance Indicators). KPIs help the scrum master and development team chart progress and meet goals.

Let’s examine 8 scrum metrics in three categories. The categories are:  Metrics that measure effectiveness, KPIs that measure deliverables, and metrics that track team productivity:

 

Metrics that measure effectiveness

Time to market

Time to market means the time that the project takes from the first idea until it begins to attract customers and generate revenue.

ROI (Return on Investment) 

ROI (Return on Investment) helps the team calculate the actual revenue generated after the costs of the sprints are taken into account. Scrum and agile typically deliver better returns because the development process is faster.

Capitol Redeployment

With capitol redeployment we determine whether the scrum project should continue with further sprints. The team analyses backlog and the cost of completing the needed sprints. If the team would prove move valuable on other projects, they should be redeployed to those projects.

Customer Satisfaction

Through surveys and user testing, the team can determine whether each sprint gives users more satisfaction. If users consistently report satisfaction with each release, then the team knows they are providing real value with each sprint.

KPIs that measure deliverables

Sprint burndown

Sprint burndown means the rate that the team accomplishes the tasks set out at the beginning of the sprint.  The burndown should be a gradual slope downward. This shows that the team planned the sprint well.

Velocity

Velocity refers to the average amount of work a development team accomplishes during a sprint. Velocity helps the scrum master and product owner predict how a development team will complete the project backlog. Velocity will change over the course of a project as the team becomes more experienced with the project. Most of the time this means that the velocity increases. A downturn in velocity may signal that some part of the process is not working properly. The team should discuss this in the new review meeting.

Metrics that track team productivity

Retrospective process improvement

The sprint retrospective is the metric by which we gauge the team’s ability to become more efficient. They do this by analyzing past springs and determining which changes will make the process more effective. They can do this by looking closely at the project backlog before and after the sprint.

Control charts

Control charts help us understand the time the team requires to complete new features or items in the backlog. Teams aim for consistent progress with quick, predictable results. Teams should not use control charts to micro-focus. Rather, they should use the charts to spot larger trends. Development teams need to pay special attention to increases in cycle time. Teams should also note when cycle time appears erratic. Either one could signal bottlenecks or bugs in the development project. Here is a list of agile tools each team should know about to measure productivity and spot trends.

So how can you scrum metrics to optimize delivery?

Scrum metrics help teams deliver optimal results by giving the team precise tools to measure success. Metrics allow development teams to analyze what works and doesn’t work in each sprint. This information helps them plan future sprints, making the process more streamlined and transparent. 

Agile development methodology sets out the framework. Scrum metrics provide specific feedback and quantify what the team does well and what they need to improve upon. Using metrics allows the team to collect data and measure the progress of each sprint in precise terms.

Using Time to market, ROI, and customer satisfaction metrics teams measure their effectiveness.  By using such metrics as velocity and spring burndown, they measure the deliverables the sprint produces. Through the use of retrospective process improvement and control charts, they track team productivity.

At Blocshop, we use scrum metrics to deliver software projects on time and under budget. We believe agile and scrum give us the best tools to plan and measure success for our clients. If you’d like to learn more about how we can use the power of scrum metrics to help you in your software development project, please get in touch!

Learn more from our insights

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From 2026, AI systems classified as high-risk under the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) will have to undergo a conformity assessment and obtain a CE marking before being placed on the EU market or put into service.

cover-img

October 19, 2025 • 7 min read

EU and UK AI regulation compared: implications for software, data, and AI projects

Both the European Union and the United Kingdom are shaping distinct—but increasingly convergent—approaches to AI regulation.

For companies developing or deploying AI solutions across both regions, understanding these differences is not an academic exercise. It directly affects how software and data projects are planned, documented, and maintained.

cover-img

October 9, 2025 • 5 min read

When AI and GDPR meet: navigating the tension between AI and data protection

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

cover-img

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6 AI integration use cases enterprises can adopt for automation and decision support

 

The question for most companies is no longer if they should use AI, but where it will bring a measurable impact. 

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The quiet cost of AI: shadow compute budgets and the new DevOps blind spot

AI projects rarely fail because the model “isn’t smart enough.” They fail because the money meter spins where few teams are watching: GPU hours, token bills, data egress, and serving inefficiencies that quietly pile up after launch.

NOVEMBER 13, 2025 • 7 min read

The quiet cost of AI: shadow compute budgets and the new DevOps blind spot

AI projects rarely fail because the model “isn’t smart enough.” They fail because the money meter spins where few teams are watching: GPU hours, token bills, data egress, and serving inefficiencies that quietly pile up after launch.

cover-img

N 19, 2025 • 7 min read

CE Marking Software Under the EU AI Act – Who Needs It and How to Prepare a Conformity Assessment

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

cover-img

NOVEMBER 13, 2025 • 7 min read

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When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

cover-img

N 19, 2025 • 7 min read

CE Marking Software Under the EU AI Act – Who Needs It and How to Prepare a Conformity Assessment

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime

cover-img

NOVEMBER 13, 2025 • 7 min read

The quiet cost of AI: shadow compute budgets and the new DevOps blind spot

When AI-powered systems process or generate personal data, they enter a regulatory minefield — especially under the EU’s General Data Protection Regulation (GDPR) and the emerging EU AI Act regime