Maximize Your Agile Potential with Agile Analytics

Unlock Full Visibility Across Project Management, Development, and Operations.
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Product Management Teams

Development Teams

Operational Teams

Transforming Agile Teams for Success

Are you in the process of transforming to Agile teams, or have you already completed the transition? Fantastic! Agile teams are the backbone of your organization, focusing on collective performance rather than individual excellence. At Agile Analytics, we believe in "Together, Everyone Achieves More." However, as your Agile transformation progresses, new challenges arise.

Traditional project management systems, like Jira and Azure DevOps, track milestones and progress, but they only show you a third of the complete picture. By solely relying on these tools, you risk encountering unpleasant surprises from the ‘gemba’ – the workplace or source. Agile Analytics bridges the gap between project management, development progress, and operational information, providing a comprehensive view of your software projects.

  • Agile teams drive collective performance

  • Agile transformation brings new challenge

  • Comprehensive view of software projects

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Overcoming Project Management Limitations

Most software projects are measured through a project management orientation, focusing on whether estimations are kept and if teams deliver as promised. However, this approach leaves out crucial development and operational insights. Agile Analytics argues that project management systems should not be the only source of truth.

By not linking project management information to development progress (such as failed deployments, tech debt, version control stock, and release frequency), you run the risk of unexpected setbacks before reaching important milestones. Agile Analytics connects these dots, ensuring you have a complete picture of your project’s health and progress.

  • Project management overlooks crucial insights

  • Crucial insights missed in project management

  • Agile Analytics connects project health dots

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Achieve Full Visibility with Agile Analytics

Agile Analytics links project management, development, and operational contexts into a central hub. This integration saves you the trouble of implementing custom scripts and ensures you don’t miss out on 66% of your critical information.

Our expertise in implementing these tools helps you kickstart your DevOps journey, providing comprehensive insights that align with your existing project management systems. Don’t limit yourself to a narrow view of your project’s health. With Agile Analytics, you get a full 360-degree insight into your software operation.

  • Gain Full Insight with Agile Analytics

  • Unify Management with Agile Analytics

  • Comprehensive Insights, No Custom Scripts

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What does Agile Analytics do

Sprint Insights for fully automatic work classification

Powered by deep learning technology, Sprint Insights identify maintenance and improvement tasks and tracks time spent on each, fostering greater focus and data-driven decision-making.

  • Creates insights in feature development balance

  • Uses AI and machine learning for analyzing your tickets

  • Automatically registers the time spent on feature & non-feature work

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Track your DevOps performance with DORA metrics

To make data driven decisions and improve your performance with DORA, you need to track these metrics continuously and automatically. With Agile Analytics you don’t have to worry about collecting data or spending time piecing together reports.

  • Clear and fair performance data about your software development team

  • Streamline development processes and increase the value of your software

  • Create happier developers while increasing engagement and motivation

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Unified SLI, SLO, and Error Budget Management

Error Budgets feature increases team autonomy and tells you everything you need to know about the quality of your production.

  • Monitors if your service level is outside SLA

  • Improves the autonomy of your agile team

  • Delivers actionable data about how you’re managing production

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Who Agile Analytics is for

Finally, a platform that performs analytics on all your agile tools and processes

Streamline Project Delivery with Targeted Insights

Agile Analytics empowers Project Managers to optimize project tracking and execution by using key metrics like lead time and average cycle time to compare planned vs. delivered work. Steer your projects toward timely and successful completion!

  • Lead Time. Understand the time it takes from project inception to delivery. Agile Analytics helps you track and reduce lead times, enabling faster time-to-market.

  • Average Cycle Time. Measure and manage the average time your team spends on various stages of project workflows, which is crucial for identifying bottlenecks.

  • Planned vs. Delivered. Compare what was planned versus what was actually delivered in a given time frame. Assess the accuracy of your project forecasts and the reliability of your delivery pipeline.

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Sounds awesome, but isn’t <tool X> doing this?

No: Existing tools all have a domain specialism. Some tools do parts, and no tool links all

For Project Managers

Agile Analytics provides several unique propositions that are unavailable if your organisation only uses Jira or Azure DevOps to manage projects and ensure their success.

  • Sprint Insights for fully automatic work classification. Tools like Jira and Azure DevOps do not provide work classification distinction in their analytics, which can lead project managers to be uninformed about resource usage and risks in planning.

  • Hours A.I. for Detailed Labor Analytics. Advanced analytics on who spent what hours on specific topics. Other tools may track time, but the insights offered by Agile Analytics are based on actual data-driven evidence.

Project Management
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Azure DevOps
Agile Analytics

Frequently Asked Questions about our platform

  • What is DevOps?

    DevOps is a set of practices that combines software development (Dev) and IT operations (Ops). It aims to shorten the systems development life cycle and provide continuous delivery with high software quality. DevOps emphasizes collaboration, automation, and monitoring throughout the software development and operation processes.

  • How can your Agile Analytics platform do what Jira or Azure DevOps cannot?

    That’s easy: all major vendors have incentives to keep you inside their tool. We don’t believe in walled gardens or silos. That’s why we created Agile Analytics to connect all critical data sources. This allows you to implement DevOps and Site Reliability Engineering easily.

  • What tools can I connect to Agile Analytics?

    We support all major vendors for Cloud and Development tools like AWS, GCP, Azure, Prometheus, Datadog, Elasticsearch, Atlassian Jira, Microsoft Azure DevOps, Gitlab, Bitbucket, Github, Slack and Microsoft Teams.

  • What are SRE and Toil?

    Site Reliability Engineering (SRE) is a discipline that incorporates aspects of software engineering and applies them to infrastructure and operations problems. The goal is to create scalable and highly reliable software systems. SRE focuses on automating and optimizing processes, managing incidents, and establishing clear metrics and Service Level Objectives (SLOs) to ensure performance aligns with business requirements. Toil, in the context of SRE, refers to the repetitive, mundane, manual tasks that are necessary for the day-to-day maintenance of a system but do not add value in the long term. SRE seeks to minimize toil by automating these tasks wherever possible, thus allowing engineers to focus more on creative problem-solving and innovations that enhance system reliability and efficiency.

  • What is a Service Level Objective (SLO)?

    A Service Level Objective (SLO) is a crucial component of a service level agreement (SLA) that defines the level of service a customer expects from a service provider. It outlines specific performance, availability, and reliability metrics the service provider commits to meeting.

    Error Budgets are closely tied to SLOs in reliability engineering and service management. An Error Budget represents the acceptable downtime or errors in a service within a given period, as defined by the SLO. It allows teams to balance innovation and reliability by setting thresholds for acceptable service disruptions. When errors or downtime exceed the budget, it may trigger a review or adjustment of processes to improve reliability.

  • What are Engineering Metrics?

    Engineering metrics are quantitative measures that provide insights into the processes and effectiveness of engineering teams. These metrics help managers and leaders gauge productivity, quality, efficiency, and the overall health of software development processes. Agile Analytics leverages these metrics to optimize team performance, improve project outcomes, and foster a better understanding of team dynamics.

  • Can Agile Analytics really reduce Toil (Operations overhead) by up to 50%?!

    Yes, Agile Analytics can indeed reduce toil (operations overhead) by up to 50% by implementing Service Level Objectives (SLOs) and Error Budgets and managing these effectively. By leveraging Agile Analytics, teams can set precise, data-driven SLOs that align closely with business objectives and user expectations. This structured approach ensures that all team members are focused on maintaining these objectives, which enhances operational efficiency. Additionally, managing Error Budgets through Agile Analytics allows teams to balance the need for innovation against the imperative for system stability, minimizing unnecessary or reactive work. This proactive management cuts down on toil and encourages a more collaborative and accountable framework within Agile teams, leading to significant reductions in operational overhead

Do you have more questions?

Tools Ecosystem

Agile Analytics integrates all monitoring and management systems to provide clear and 360-degree insights. These are the integrations used by our customers:

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Agile Analytics reduced operational toil by 40%. Implementing Service Level Objectives and DevOps showed us where to place focus: Feature development or non-functional aspects.



"Smiling, collar-clad figure with happy forehead hair-do
Jeroen Bultje
Development Manager at Maxeda DIY Group (Praxis, Brico)