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Evidence-Based Management: How Agile Forecasting and EBM Lead to Better Outcomes Evidence-Based Management (EBM) is a framework that helps organizations make smarter, more informed decisions by using empirical data to evaluate and improve performance. Developed by the creators of Scrum, EBM pairs seamlessly with agile practices, helping teams measure value delivery through Key Value Areas such as  Current Value ,  Time-to-Market , and  Unrealized Value . It ensures that decisions are grounded in evidence rather than assumptions. By continuously inspecting and adapting, EBM enables incremental improvements, allowing teams to deliver measurable outcomes that align with business goals. EBM ties into Agile Forecasting by providing a framework for using empirical data to guide decision-making, measure progress, and forecast outcomes. EBM focuses on outcomes and the evidence of value delivered, making it a natural complement to Agile Forecasting, which uses data and probabilistic methods to predict future performance. How Agile Forecasting and EBM Work Together EBM ties directly into Agile Forecasting by providing a framework for using data to guide decisions, measure progress, and forecast outcomes. EBM focuses on the evidence of value delivered, while Agile Forecasting, powered by tools like  ActionableAgile® Analytics , uses flow metrics and probabilistic methods to predict future performance with greater accuracy and transparency. Here’s how the two approaches align: 1. Focusing on Value Delivery EBM emphasizes maximizing value rather than focusing solely on  outputs . Agile Forecasting complements this by helping teams predict when and how much value they can deliver based on real historical data. For instance, with ActionableAgile® Analytics, teams can: Use  T hroughput forecasting  to estimate how many high-value features will be completed by a target date. Run  Monte Carlo simulations  to calculate the likelihood of delivering a prioritized set of features within a specific timeframe, ensuring alignment between delivery and strategic business goals. 2. Data-Driven Decision Making EBM relies on empirical evidence, using Key Value Areas such as Current Value, Time-to-Market, and Unrealized Value, to support informed decision-making. Similarly, Agile Forecasting uses historical data, such as Throughput and Cycle Time, to make accurate predictions about future performance. This shared reliance on data ensures that: Teams can prioritize work that maximizes value and deliver features faster to meet customer needs. Forecasting provides clear estimates of Time-to-Market for specific features or product increments, helping stakeholders understand delivery timelines and plan with greater confidence. 3. Continuous Improvement through Metrics Both EBM and Agile Forecasting thrive on continuous feedback loops. Agile Forecasting uses key flow metrics ( Cycle time , WIP , Throughput ) to refine predictions and identify improvement opportunities. EBM integrates these metrics into broader Key Value Areas, helping organizations evaluate how process changes impact business outcomes, such as reducing delays (Time-to-Market) or increasing stakeholder satisfaction (Current Value). This creates a data-informed culture where progress is visible, measurable, and continuously improving. 4. Risk Management In EBM, understanding risks is essential for managing  Unrealized Value , the gap between potential and actual value delivered. Agile Forecasting, especially when powered by ActionableAgile® Analytics, enhances risk management by providing probabilistic forecasts that reveal the likelihood of meeting specific delivery targets, enabling teams to plan for variability and uncertainty. It also helps surface bottlenecks and inefficiencies in delivery processes through flow metrics, allowing teams to identify where delays could threaten value delivery. 5. Transparency and Stakeholder Confidence EBM encourages transparency by using metrics to communicate progress and value delivery. Agile Forecasting supports this by: Providing clear, data-driven forecasts that help stakeholders make informed decisions with confidence. Demonstrating probabilities and scenarios (e.g., “There’s an 85% chance of delivering 15 features by the end of the quarter”) to set realistic expectations and foster trust between teams and stakeholders. These kinds of insights are easily visualized through ActionableAgile® Analytics. Better Together: Turning Data into Decisions When organizations combine EBM’s focus on measurable value with Agile Forecasting’s probabilistic insights, they unlock a new level of predictability and alignment. Together, these practices enable teams to: Improve predictability while maintaining agility and flexibility. Align team efforts with strategic goals. Use real-world data to guide decisions, reduce uncertainty, and deliver incremental value continuously. This partnership between  Leading EDJ E  and  55 Degrees  highlights how EBM and Agile Forecasting can work hand in hand to build truly data-driven organizations, where teams deliver the  right  value at the  right  time. Resources to Get Started Ebook: If you'd like a deeper dive into getting started with Flow Metrics, you can download the free ebook. Ready to get started and understand flow metrics? If you’ve been curious about Flow Metrics but unsure where to start, this guide breaks it down in a straightforward, human way. No jargon. No complexity. Just practical steps toward more predictable delivery.

The Ongoing Battle of Agile vs Waterfall Agile teams often face challenges in predicting project timelines and delivery dates due to the framework's inherent flexibility, which prioritizes adaptability over rigid schedules. While this approach aligns with Agile principles, most IT departments operate within yearly budgets that require some level of forecasting to understand when funded initiatives are to be completed. But scoping out an entire year’s worth of work is not only inefficient but also counterproductive to Agile’s iterative nature. Traditional approaches, such as deterministic forecasting (forecasting to a single date) commonly used in waterfall methodologies, attempt to map out the entire scope, timeline, and resource allocation for a project upfront. However, this assumes that requirements, priorities, and team performance will remain static Throughout the project lifecycle, a notion that rarely aligns with the realities of modern software development. When unexpected changes arise (e.g., shifting priorities, evolving customer needs, or unforeseen technical challenges), deterministic plans become obsolete, leading to missed deadlines, mismanagement, and stakeholder frustration. So, what's a team to do when they are stuck in this conundrum? How can teams forecast work enough to satisfy the planning and budgetary needs of most IT departments while staying nimble enough to produce high-quality, useful software features? This is where Agile Forecasting using Flow Metrics and Monte Carlo Simulation comes in handy. A Smarter Way to Forecast In contrast to more rigid waterfall planning, predictive approaches like Agile Forecasting are better suited for today’s dynamic software development environment. By leveraging historical data and probabilistic models, Agile Forecasting embraces variability and uncertainty, allowing teams to provide a realistic range of outcomes associated with a probability of success, rather than a fixed, single date that often results in unrealistic predictions. Techniques like Monte Carlo Simulations and flow metrics help teams forecast delivery timelines and Throughput with greater accuracy, enabling more informed decision-making and proactive risk management. Agile Forecasting bridges the gap between the adaptability of Agile and the need for predictability in IT planning. It empowers teams to achieve realistic goals without compromising flexibility, delivering value iteratively while meeting business expectations. In this post, we’ll delve into how Agile Forecasting, powered by tools like Monte Carlo Simulations and flow metrics, can revolutionize the way teams plan, execute, and deliver their work. The Case for Agile Forecasting Agile forecasting is a method used to predict how much work a team can complete within a given timeframe by leveraging historical data and current performance metrics. Unlike deterministic approaches, such as the upfront, rigid project planning typical of the waterfall methodology, it embraces variability and applies probabilistic thinking to deliver a more accurate range of potential outcomes. By adopting agile forecasting, teams can: Set achievable goals: Use historical data and flow metrics to make realistic predictions about what the team can complete. Manage risks effectively: Leverage probabilistic forecasting to account for variability and visualize bottlenecks with Cumulative Flow Diagrams (CFD) and flow metrics. Use Monte Carlo Simulations to create contingency plans and apply Work in Progress (WIP) limits to reduce Cycle Times. Improve stakeholder confidence in delivery timelines: Provide data-driven forecasts using Monte Carlo Simulations and refine them continuously with updated metrics. Flow Metrics: The Foundation of Agile Forecasting Flow metrics are essential for understanding how efficiently work moves through a development process. The key metrics include: Cycle Time : The time it takes for a work item to move from start to finish. Work in Progress (WIP) : The number of active items being worked on. Throughput : The number of items completed in a given time period. Work Item Age : The elapsed time since work on an item started. Applying Flow Metrics in Practice: Sprint Planning: Use throughput to determine how much work to pull into a sprint, moving away from deterministic velocity metrics. Retrospectives: Analyze Cycle Time scatterplots to identify patterns or outliers and improve processes. WIP Limits: Leverage Little’s Law (a principle linking WIP, Throughput, and Cycle Time) to understand how limiting WIP improves Cycle Time and overall flow efficiency. Monte Carlo Simulations: A Powerful Tool for Forecasting Monte Carlo Simulations (MCS) is a computational algorithm that uses repeated random sampling to generate probabilities for a range of outcomes. In agile forecasting, MCS helps answer critical questions: How many items can we close by a target date? When will a specific number of items be completed? How many items can we close by a target date? This question is answered by running simulations using historical Throughput data (e.g., the average number of items completed per sprint). By analyzing this data, the simulation generates a probability distribution that predicts how many items are likely to be completed by a specific date. For example, the output might indicate there is an 85% chance of completing 20 items, or 70% chance of completing 25 items, by the end of the next sprint. This insight helps teams set realistic expectations and manage scope effectively within a defined timeframe. When will a specific number of items be completed? To answer this, the simulation uses the same historical Throughput or Cycle Time data to estimate the range of dates by which a set number of items can be delivered. The result is expressed as probabilities, such as a 90% likelihood of completing 30 items within 25 days. This information is particularly valuable for fixed-scope projects, where knowing the approximate completion date is critical for planning and stakeholder communication. Monte Carlo Simulations in Action with ActionableAgile® Analytics Monte Carlo Simulations can be run using general analytics tools, but those often require extra setup and manual work. ActionableAgile® Analytics streamlines the process, making forecasting faster and easier. It automatically collects your historical Throughput and Cycle Time data from Jira (or Azure DevOps) and runs thousands of simulations in seconds, delivering clear, visual probability forecasts without the need for complex setup. With  ActionableAgile® Analytics , teams can: Instantly generate probability charts showing the likelihood of hitting specific delivery targets. Visualize forecasts alongside real-time flow metrics such as WIP, Throughput, and Cycle Time for a complete picture of performance. Adjust variables dynamically to explore  what-if scenarios  and assess how changes in WIP, scope, or team Throughput might affect outcomes. This blend of empirical data and simulation-based forecasting gives teams and stakeholders the confidence to plan realistically, manage risk proactively, and adapt without losing predictability. How It Works Gather Historical Data:  Collect Throughput or Cycle Time data (e.g., completed tasks per sprint). Even a few weeks’ worth of data is enough to start. Run Simulations:  Use this data to simulate thousands of possible outcomes, accounting for variability and uncertainty. Generate Probabilities:  Calculate the likelihood of achieving specific delivery goals, instantly visualized through tools like  ActionableAgile® Analytics . For example, an MCS might show there’s an 85% chance of completing 20 items in the next sprint. This approach is especially useful for fixed-scope or fixed-date projects, providing actionable insights into what’s achievable. Continuous Improvement with Agile Forecasting Agile Forecasting isn’t a one-time activity. It’s a continuous cycle of inspection, adaptation, and learning. By regularly analyzing flow metrics and leveraging probabilistic tools like  Monte Carlo Simulations  through  ActionableAgile® Analytics , teams can refine their workflows, improve predictability, and deliver value more consistently. Tools and Resources to Get Started Ebook: If you'd like a deeper dive into getting started with Flow Metrics, you can download the free ebook. Ready to get started and understand flow metrics? If you’ve been curious about Flow Metrics but unsure where to start, this guide breaks it down in a straightforward, human way. No jargon. No complexity. Just practical steps toward more predictable delivery. Books: When will it be done by Daniel Vacanti and Actionable Agile Metrics for Predictability : Tenth Anniversary Edition by Daniel Vacanti Tools:   ActionableAgile® Analytics By adopting these techniques and tools, your team can shift from guesswork to reliable, evidence-based forecasting, delivering work with confidence, clarity, and predictability. This article is part of a collaboration between 55 Degrees and Leading EDJ E , combining expertise in agile forecasting and evidence-based management to help teams plan smarter and deliver value predictably.

Struggling to trust your delivery dates? If you’ve ever struggled to explain flow metrics, get buy-in from leadership, or simply make delivery more predictable, this guide is for you. We partnered with innovative technology leader, Leading EDJE  to produce a clear, conversational, and practical introduction to Flow Metrics. Perfect for teams taking their first step into data-driven delivery. This free resource breaks down the fundamentals, shows how to get started without changing your entire process, and gives you real-world examples you can take straight into your organization. What You’ll Learn What flow metrics are and how they differ from traditional estimation The four core metrics to start with: WIP, Cycle Time, Work Item Age, and Throughput How to introduce flow metrics without disrupting your current process How to build a simple business case for leadership Common challenges teams face and how to overcome them "Using Flow Metrics and Probabilistic Forecasting gave me the clarity I needed as a Product Manager to understand delivery dates and actual risk. It took the guesswork out of the equation and made my conversations with stakeholders much more realistic and productive" Product Manager - David's Bridal Ready to get started and understand flow metrics? If you’ve been curious about Flow Metrics but unsure where to start, this guide breaks it down in a straightforward, human way. No jargon. No complexity. Just practical steps toward more predictable delivery.

Optimize Customer Value with a Proven Partner in Your Corner As the premier vendor of agile / forecasting apps, 55 Degrees empowers partners beyond mere transactions. We work alongside our partners to deliver customer value fast and effectively. Become a Partner Get Partner Support Proud Marketplace Partner Our Educational Partners Our Partners Can Enjoy These Benefits Dedicated Partner Support Discounts & Incentives Free Internal Licenses Access to Partner Portal & Resources (and more!) Customized Product Training To Suit You Co-Marketing & Event Support Frequently asked questions DC Customers General ActionableAgile Analytics Inspekt Portfolio Forecaster Klar Short-form Chat Dialog questions Partners Will ActionableAgile® Analytics continue to support Jira Data Center? Yes. We will continue supporting Jira Data Center customers throughout Atlassian’s end-of-life timeline. Core updates such as charts, insights, and calculations will still be delivered. Why won’t all new features come to Data Center? Some features require extensive development and testing that are specific to the Data Center platform. With Atlassian planning to sunset Jira DC, it’s important for us to focus resources on updates that bring the greatest long-term value to customers across platforms. Which types of features are affected? Platform-dependent updates — such as native Jira dashboard gadgets or certain integrations with Jira internals — may not be delivered to Data Center. Instead, we’re prioritizing improvements to the ActionableAgile® Analytics experience itself, which will benefit both Data Center and Cloud users. What new improvements can I expect on Data Center? You will still see enhancements including: • A new app landing page • Data set views for easier navigation • Consistent chart templates • Expanded chart insights What if my team plans to move to Jira Cloud later? We will be ready to support you with a smooth transition when that time comes. ActionableAgile® Analytics for Jira Cloud includes the same core capabilities and ongoing innovation. Brodie Chivers Partner Manager Meet your Partner Manager As our Partner Manager, Brodie oversees new and existing partnerships. He’s here to support our partners wherever possible. His dedication and expertise aim to maximize the success and growth of every collaboration Contact Brodie Partnering for Success Join our Partner Network. Together, we can achieve more. Become a Partner Get Partner Support

55 Degrees AB delivers apps that focus on helping you get more done with less stress. Be predictable. Be confident. Be agile. Trusted by the world's leading brands Powerful solutions that take you from busy to effective Agile Flow Metrics for Jira, Azure DevOps, or standalone SaaS Measure and improve Flow. Be Predictable. Answer "When will it be done?" Learn More Portfolio Forecaster Continuous Forecasting for Jira Forecast any issue type, not just epics, with confidence using probabilities. Learn More Inspekt for Jira Cloud Analyze raw workflow data for cumulative time in status and how items move in the workflow. Learn More Products “ActionableAgile® Analytics has elevated our depth of meaningful discussions within the team. Having trust in the data and how we represent it is beneficial. It painted this bigger picture for us." Company Size Enterprise Ben Richards Industry Food & Restaurant SYSTEMS COACH KFC Read Customer Story Recent Blog Posts Agile Forecasting: Leading to Better Outcomes Evidence-Based Management: How Agile Forecasting and EBM Lead to Better Outcomes Evidence-Based Management (EBM) is a framework that helps organizations make smarter, more informed decisions by using empirical data to evaluate and improve performance. Developed by the creators of Scrum, EBM pairs seamlessly with agile practices, helping teams measure value delivery through Key Value Areas such as Current Value , Time-to-Market , and Unrealized Value . It ensures that deci 55 Degrees Jan 22 3 min read Agile Forecasting: Monte Carlo Simulations and Flow Metrics The Ongoing Battle of Agile vs Waterfall Agile teams often face challenges in predicting project timelines and delivery dates due to the framework's inherent flexibility, which prioritizes adaptability over rigid schedules. While this approach aligns with Agile principles, most IT departments operate within yearly budgets that require some level of forecasting to understand when funded initiatives are to be completed. But scoping out an entire year’s worth of work is not only 55 Degrees Jan 20 5 min read Downloadable E-Book: Flow Metrics Explained Struggling to trust your delivery dates? If you’ve ever struggled to explain flow metrics, get buy-in from leadership, or simply make delivery more predictable, this guide is for you. We partnered with innovative technology leader, Leading EDJE to produce a clear, conversational, and practical introduction to Flow Metrics. Perfect for teams taking their first step into data-driven delivery. This free resource breaks down the fundamentals, shows how to get started without ch Brodie Chivers Jan 15 1 min read Read more > A culture based on security and privacy An important part of living up to our values is our commitment to data privacy and security throughout all aspects of our organization. We don't take a single step without ensuring we've taken all reasonable steps to protect your data and privacy. Protect customer and personal data at all times Comply with applicable privacy regulations Avoid processing or storing unneeded data Compliance Certifications and Standards GDPR ISO 27001 SOC 2 Type II Atlassian Security Programs Get Your Free Guide Still relying on story points? It's time to move beyond estimation. Learn how flow-based insights give you clearer visibility into delivery, where work is slowing down, what is likely to finish, and how to lead delivery with confidence using real data. Get Your Guide Webinars Check out our upcoming webinars and explore some of our most popular ones! Explore All Webinars Interact with us at an upcoming event No events at the moment More events >

Improve Flow. Be Predictable. Understand how work really moves through your process so you can ask the right questions, drive meaningful improvement, and accurately forecast outcomes in uncertain situations. Try it for free Overview Pricing Roadmap FAQ Training Cycle Time Scatterplot Set Service Level Expectations (SLEs) By looking at how quickly you finish work in the past, you can understand how long it may to take you to complete future work. SLEs help the team know what they are capable of! Aging Work in Progress Chart Secret weapon to improve predictability. Know exactly how old your current work is and compare it to past data for context. Begin to control aging and maintain or improve your current level of predictability. Monte Carlo Simulations Forecast in uncertainty with probabilities Our Monte Carlo simulations help you get an idea of how likely any forecast is for any set of work. We use the variation in your historical data to run more than 10,000 trials! We have simulations for both fixed dates and fixed scope. free-trial Free Trial Try ActionableAgile® Analytics for free. All free trials are 30 days or more! Compare features by version Standalone SaaS Import your data from Jira, Trello using our built-in wizards, or any external app via file upload Start your free trial Embedded in Jira Get the power of ActionableAgile without leaving Jira. Available for Cloud, Server and Data Center Start your free trial Embedded in Azure Analyze flow directly in Azure DevOps Cloud. For single users or whole organizations Start your free trial Don't take our word for it, listen to our customers ActionableAgile helped us improve our ability to anticipate delivery outcomes by using probabilistic forecasting and flow metrics. Our throughput almost doubled, and the team got better at splitting and sizing work into meaningful, valuable chunks. Our cycle times were reduced by almost 50% or more for 85% of our completed work items. Our WIP significantly reduced, so we had teams that were not overwhelmed or overburdened. As a result, we reduced context switching and enabled the teams to experiment with pairing and swarming to get things done. Haroon Khalil , Executive Agility Coach By regularly forecasting with ActionableAgile, we could clearly show when circumstances impacted our delivery timescales; previously, these would have been recognized as affecting our delivery. Monte Carlo simulation's what-if scenario planning function has enabled us to discuss what is happening and if trends are changing with stakeholders and teams. This allowed us to take meaningful action at the soonest possible opportunity and put the decisions with the right people. Julie Starling , Agile Delivery CoP Manager Get Your Free Guide Still relying on story points? It's time to move beyond estimation. Learn how flow-based insights give you clearer visibility into delivery, where work is slowing down, what is likely to finish, and how to lead delivery with confidence using real data. Get Your Guide Get all the latest news about ActionableAgile® Analytics! Subscribe and receive monthly emails tailored especially for ActionableAgile® Analytics users. Get news on recent releases, upcoming events, and more! Manage Subscriptions Got Questions? We've Got Answers! Frequently asked questions DC Customers General ActionableAgile Analytics Inspekt Portfolio Forecaster Klar Short-form Chat Dialog questions Partners Will ActionableAgile® Analytics continue to support Jira Data Center? Yes. We will continue supporting Jira Data Center customers throughout Atlassian’s end-of-life timeline. Core updates such as charts, insights, and calculations will still be delivered. Why won’t all new features come to Data Center? Some features require extensive development and testing that are specific to the Data Center platform. With Atlassian planning to sunset Jira DC, it’s important for us to focus resources on updates that bring the greatest long-term value to customers across platforms. Which types of features are affected? Platform-dependent updates — such as native Jira dashboard gadgets or certain integrations with Jira internals — may not be delivered to Data Center. Instead, we’re prioritizing improvements to the ActionableAgile® Analytics experience itself, which will benefit both Data Center and Cloud users. What new improvements can I expect on Data Center? You will still see enhancements including: • A new app landing page • Data set views for easier navigation • Consistent chart templates • Expanded chart insights What if my team plans to move to Jira Cloud later? We will be ready to support you with a smooth transition when that time comes. ActionableAgile® Analytics for Jira Cloud includes the same core capabilities and ongoing innovation. Our dedicated support team is always ready to assist you. Empower yourself with knowledge and make the most of your experience with us!