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Planning across multiple teams can be a challenge. Different teams work in different ways, and their data reflects that. Yet, when stakeholders need a view of the bigger picture, combining everything into one massive forecast is tempting. Unfortunately, this often leads to inaccurate predictions and poor decision-making. That’s why we’re excited to introduce Forecast Portfolios , a new feature in Portfolio Forecaster  that provides a smarter way to align teams and plan across groups. What Are Forecast Portfolios? Forecast Portfolios allow you to view multiple team forecasts together in one unified, read-only portfolio. Instead of merging data into a single forecast—where differences in team practices and workflows can create errors—Forecast Portfolios respect the unique characteristics of each team’s forecast. Users can easily create a portfolio by selecting group forecasts and combining them into a shared view. These portfolios can also be filtered to focus on the most relevant work, and they can be shared with stakeholders for better visibility and collaboration. Why It’s a Game-Changer Forecast Portfolios  solve a critical problem: how to provide cross-team visibility without sacrificing accuracy. Here’s what makes it stand out: Accuracy Without Compromise:  Each team’s forecast remains intact, ensuring reliable insights for better decision-making. Enhanced Visibility:  Stakeholders can see the full picture across teams in one place. Time-Saving Simplicity:  Portfolios are quick to set up and easy to share, making cross-team planning seamless. Customizable Views:  Filters allow users to focus on the data that matters most to them. Who Benefits from Forecast Portfolios? Directors and Program Managers:  Easily align resources and strategies across teams. C-Level Executives:  Gain high-level visibility into progress and performance. Team Leads:  Share their group’s contributions transparently while maintaining the integrity of their data. Forecast Portfolios: Align Smarter, Plan Better If you’ve been struggling to align forecasts across teams without losing accuracy, Forecast Portfolios is here to help. By providing clarity, collaboration, and confidence in your forecasting, it’s the tool you need to navigate complexity and plan for success. Forecast Portfolios is on its way and will soon be available in Beta on Portfolio Forecaster. Get ready to explore this exciting feature to enhance your planning and decision-making. Stay tuned-more details coming soon!

In today’s fast-paced, ever-changing business world, the ability to adapt and plan for the unexpected is no longer a luxury—it’s a necessity. Teams constantly navigate shifting priorities, limited resources, and unpredictable demands. Organizations must think beyond static forecasts and embrace a more dynamic, flexible approach to succeed. Building on the foundation of probabilistic forecasting, Scenario Planning  in Portfolio Forecaster takes dynamic forecasting to the next level. Empowering teams to explore the “what-ifs” of their workflows provides an invaluable tool for risk planning and decision-making in an ever-uncertain environment. This capability revolutionizes forecasting, enabling smarter decision-making, greater agility, and improved outcomes. Here’s why Scenario Planning is a game changer—and how it transforms your experience with Portfolio Forecaster. What is Scenario Planning in Portfolio Forecaster? Scenario Planning within Portfolio Forecaster  allows teams to toggle on potential future scenarios and test the impact of changes—before they happen. By simulating various "what-if" scenarios, teams can answer critical questions like: What if we reduce the number of items we’re working on simultaneously? What happens to our timelines if priorities shift? How would working ahead on future tasks impact our forecast? When can we expect to complete upcoming items if we maintain our current pace? All of this is seamlessly integrated into Portfolio Forecaster , giving users the tools they need to prepare for the unexpected directly within their forecasting workflow. Why Scenario Planning in Portfolio Forecaster is a Game-Changer 1. Anticipate Outcomes with Confidence With Scenario Planning in Portfolio Forecaster, you can explore multiple outcomes, anticipate risks, and proactively adapt your plans to meet changing conditions. 2. Make Data-Driven Decisions Every decision involves trade-offs, and Portfolio Forecaster clearly outlines those trade-offs. Whether adjusting work-in-progress limits, shifting priorities, or changing workflows, Scenario Planning helps you understand the impact of your choices, enabling smarter and more strategic decisions. 3. Adapt to Change with Agility Change is inevitable—whether it’s a new customer demand, an unexpected delay, or a strategic pivot. Scenario Planning helps teams prepare for these changes before they occur. With Portfolio Forecaster, you can model the effects of changes on timelines and outcomes, empowering teams to respond with agility and confidence. 4. Optimize Resources and Throughput Balancing speed, quality, and resource allocation is a challenge for any team. Scenario Planning within Portfolio Forecaster allows you to experiment with changes, such as reducing the number of concurrent tasks or reordering priorities, to optimize efficiency and avoid bottlenecks or burnout. 5. Foster Collaboration and Transparency Portfolio Forecaster isn’t just for project managers—it’s a tool for aligning entire teams. With Scenario Planning, stakeholders gain a clear, shared view of potential outcomes. This transparency fosters collaboration and ensures that everyone is aligned, reducing misunderstandings and building trust. How Portfolio Forecaster Stands Out Portfolio Forecaster  is designed to make forecasting and planning both intuitive and powerful. The addition of Scenario Planning elevates its value by enabling teams to visualize and plan for multiple potential futures. Whether you’re managing complex projects, aligning cross-functional teams, or trying to optimize workflows, Portfolio Forecaster gives you the insights and tools to stay ahead of uncertainty. Key benefits of Scenario Planning in Portfolio Forecaster include: Ease of use:  Toggle between actual forecasts and simulated scenarios without disruption. Seamless integration:  Leverage Scenario Planning directly within your existing forecasting workflow. Actionable insights:  Translate “what-if” scenarios into concrete, informed decisions. The Bigger Picture: Why It Matters At its core, Scenario Planning in Portfolio Forecaster is about empowerment. It empowers teams to: Stay ahead of uncertainty  by exploring possibilities. Make informed decisions  that drive better results. Align around shared goals  with clear, data-backed insights. In an era where adaptability is crucial, Scenario Planning is more than a feature—it’s a strategic advantage. It helps organizations move from reactive to proactive, from static to dynamic, and from uncertainty to confidence. Explore the Future with Portfolio Forecaster If you’ve ever found yourself asking, “What if…?” Portfolio Forecaster’s Scenario Planning feature is the answer. Providing a forward-thinking approach to forecasting enables smarter workflows, faster decision-making, and better outcomes. The future isn’t static—why should your planning be? Start your free Portfolio Forecaster trial today to navigate complexity with clarity and thrive in an unpredictable world.  Scenario Planning is launching soon in Beta! Stay tuned and be among the first to try it out. Get ready to explore new possibilities and make smarter, data-driven decisions with Portfolio Forecaster.

I should also say at the outset, that while I do write a lot about predictability, I’m terrible at prognostication without data, which means that what I have below is more of a wish list rather than a bold statement about what will happen in 2025. Also, so you know, this is not going to be some crass or trite blog post about how AI is going to change everything about Agile.  Yes, AI will have some impact, but I’d be willing to bet that impact (whatever it is) will not be in any area that is widely being talked about now. Without any further adieu, here goes: 1.       A continued shift away from prescriptive Agile frameworks.  With all due respect to practitioners of Scrum, Safe, etc., those frameworks have had their day, and unfortunately, our industry is no better off (and, in many cases, worse off) than when they first came into prominence.  My expectation is that companies continue to drop their investment in those failed Agile experiments and continue to shift toward understanding what drives efficiency, effectiveness, and predictability from first principles.  Yes, I am biased here.  And yes, I’ve said this before.  But I believe 2024 was a sea change in this regard, and I don’t see that trend reversing any time soon.  Plausibility :  Pretty good. 2.       Can we please stop talking about story points?  It is 2025, ffs.  Everybody and their brother’s neighbor’s dog know that story points don’t work, yet they still seem to be pervasive.  Even the person who created story points says don’t use them but somehow, I am still encountering them on a monthly basis.  Outside of fixed length timeboxes (see # 1), I believe story points are the single biggest factor that has held Agile back from achieving its full potential.  I know, I know, story points are not “Agile,” but pick a team at random that is doing “Agile,” and chances are they are using story points--in one form or another.  When the person who was responsible for introducing story points has repeatedly said not to use them, then I think it is time that we should heed his advice.  Plausibility :  Nil. 3.       Can Agile please finally fill its biggest hole? That is, it proves that adopting Agile practices actually improves either an organization's top line or bottom line or both.  The problem is that as long as we continue to follow the prescriptive frameworks of # 1, this will be hard to demonstrate.  Think about how many billions of dollars have been spent on Agile in the past twenty-ish years. Is there any proof that this investment has provided any real financial benefit?  Anecdotally, I would say it has not—which is the fundamental reason why Agile finds itself in the doldrums.  As long as Agile continues to rely on financially inefficient strategies like (as mentioned above) fixed length timeboxes, prescriptive roles, and story points (to name a few), then for all intents and purposes, Agile will continue its slow march toward death.  What we need to do is be able to prove to CFOs, that any investment in legitimate Agile practices will contribute to a company's overall financial health.  To date (with minimal exceptions), this has never been done.  Therefore, from a CFO’s perspective, they are thinking, “If the only way I can do this is to do it badly, then I’ll do it badly as cheaply as possible”.  Translation: no Agile.  I personally am hoping to help move the needle on this, but until we do, I see no hope for Agile. Plausibility :  Minimal. Maybe you were expecting something a bit more cheery and upbeat.  I’m sorry I couldn’t deliver on that.  Having said all of this, however, I still firmly believe that organizations that truly “get” Lean-Agile practices (not the faux ones provided by prescriptive frameworks) will survive, and the organizations that don’t won’t.  That will probably take longer than 2025 to play out.  But my guess is this is where it starts. On that note, let’s work together to make Agile better for everyone.  All the best to all of you in this year and beyond!

55 Degrees is proud to announce the successful renewal of our SOC 2 compliance, reaffirming our commitment to maintaining the highest standards in data security and customer trust. This milestone underscores our dedication to safeguarding customer data by adhering to rigorous security protocols and continuously enhancing our security and compliance program. As a renewed achievement—not our first SOC 2 audit—this accomplishment reflects our ongoing efforts to meet and exceed industry standards, ensuring our customers’ data is handled with the utmost care and integrity. What is SOC 2, and why is it important? SOC 2, or Service Organization Controls 2, is a framework that is governed by the American Institute of Certified Public Accountants (AICPA). With a SOC 2 audit, an independent service auditor will review an organization’s policies, procedures, and evidence to determine if their controls are designed and operating effectively. A SOC 2 report communicates a company’s commitment to data security and the protection of customer information.   Improving your security posture  SOC 2 compliance exemplifies an organization’s commitment to customer trust and is a major milestone toward improving its overall security posture. With increasing cybersecurity threats and data breaches, it is paramount that organizations prioritize information security and the protection of their systems and data. By undergoing a SOC 2 audit, our controls and processes were validated by a third party who attests to the functioning of the controls relevant to our application.  Why did we pursue SOC 2 now? SOC 2 compliance is integral in proving to customers, stakeholders, and interested parties that our organization values their trust and has effectively implemented security controls. At our company’s stage, we realized that it was an ideal time to pursue this as it is important to protect data and mitigate potential security risks early and on an ongoing basis.  55 Degrees’s journey to SOC 2 compliance Compliance Partners   The task would have seemed insurmountable without the right compliance partners to guide us on our journey. Some key partners were involved in our SOC 2 compliance journey. Vanta  We partnered with Vanta , the leader in the Trust Management space, to help us automate the collection of our audit evidence. Vanta provides us with the strongest security foundation to protect our customer data. Advantage Partners  Our audit firm, Advantage Partners , was extremely helpful in creating a seamless audit experience. With their guidance and support, we were able to achieve SOC 2 compliance in a swift, efficient manner.  Process  While SOC 2 can be a big undertaking, our compliance partners streamlined the process. We leveraged Vanta to integrate our key systems and guide us in implementing policies and procedures to quickly become audit-ready. Vanta gave us the direction we needed to pursue our compliance journey.  Advantage Partners then confirmed our audit readiness, and we kicked off our Type II audit. Advantage evaluated the controls we have in place for the audit and opined on their state.  Advantage Partners drafted and issued our report shortly after our audit window ended.  Timeline  One key takeaway is that improving our security posture and achieving compliance is monumental. This can be made easier with the right compliance partners, but it will take dedicated focus and time from your organization. The readiness period can take the most time, but we were able to prioritize compliance to get the audit ready in weeks rather than months.  We also found it important to review the audit timeline with Advantage Partners, set an ideal audit date, and then work backward to be ready in time. However, now that controls are implemented and security is a priority for our team, subsequent SOC 2 audits will be even more seamless.  Lessons we learned  Start the process early.   It is easier to implement policies earlier than later, and doing so as early as possible helps you build a more secure organization. Building secure procedures and infrastructure is key to a successful security program. Focus on improving security posture, not checking boxes. Compliance is not one size fits all. Ensure you are spending time understanding the frameworks you’re working towards so you can know how to best comply for your organization. Your entire organization will be involved in improving security and adhering to procedures. Help them to understand how they impact your ability to stay compliant! Security is a continuous project that should be prioritized in an organization. Don’t snooze your alerts - aim to stay at 100% readiness in Vanta all the time! The right partners and tools are key.  Finding a compliance management tool like Vanta to guide you through the process makes it much easier to know what to do and do it quickly. Not only does it make it easier to get started, but it makes it (nearly) painless to maintain your audit readiness! Leveling up our licenses in tools like Snyk Enterprise has really alleviated the pain of managing certain aspects of our compliance and providing the necessary proof.  Finally, partnering with an audit firm dedicated to your success makes the process much less scary! Make sure you find a firm that you feel comfortable with, and that is comfortable in your compliance management system. You can read more about our trust stance at https://55degrees.se/trust . If you would like to request access to our SOC 2 report or see information about the controls currently in place and other publicly available documents, you can visit our Vanta Trust Center at https://trust.55degrees.se . If you have any other questions, please contact us !

If you thought Portfolio Forecaster 1.0 was good, buckle up—Portfolio Forecaster 2.0 is ready to take your forecasting experience to a whole new level. Packed with new features and a ton of flexibility, it’s designed to help you dive deeper, forecast more accurately, and ensure everyone’s on the same page. What Makes Portfolio Forecaster 2.0 a Game-Changer? Goodbye, Limitations: Forecast Any Issue Type Gone are the days when you could only forecast by epics and versions. With 2.0, you can now create forecasts using any issue type, meaning you can track and predict across all your tasks and work items. This newfound flexibility lets teams get a complete, customized picture of every project. Now, you’re not just scratching the surface—you’re seeing every aspect of your work, from the big-picture initiatives down to those essential, smaller tasks. Enhanced Group Forecasts for Real Collaboration Group forecasts were always a cornerstone of Portfolio Forecaster, but in 2.0, they’re sharper and more team-focused than ever. With enhanced group forecasts, you can now capture the full dynamic of collaboration within your team, aligning forecasts more closely with how your people actually work together. This means you get a crystal-clear view of each team’s contributions to a project, empowering better decision-making and transparency. All-New Configuration Options for Customization Freedom Every team operates differently, and Portfolio Forecaster 2.0 respects that with its flexible configuration settings. Now, with features like JQL filters and a variety of issue link types, you can customize each forecast to fit precisely within your workflows. Need to filter down to specific status category? Done! Prefer forecasting using different issue types? No problem! It’s a configuration playground where you decide how detailed or broad each forecast should be, ensuring they mirror exactly how your team functions. Streamlined Sharing and Access Control Transparency and teamwork just got a serious upgrade. With Portfolio Forecaster 2.0, forecasts are no longer confined to just the creator. Now you have complete control over sharing, from who can view a forecast to who can help manage it. This level of access makes it easy to involve others and ensure everyone is aligned with the latest forecast data. Portfolio Forecaster 2.0 transforms your forecasts into a shared tool that fosters collaboration and alignment across the board. Introducing Forecast Portfolios One of the most anticipated features coming to Portfolio Forecaster 2.0 is  Forecast Portfolios . Imagine being able to combine multiple group forecasts into one streamlined view, capturing the progress across projects, programs, or departments—all in a single place. This upcoming feature lets you see the big picture while still preserving the precision of each individual forecast. With Forecast Portfolios, you can monitor your entire project landscape and stay on top of all the moving parts without losing any accuracy. It’s the ultimate way to keep everything organized and in focus, supporting smooth project execution at every level. Forecast Portfolios will be available in our beta release in the second week of November, with additional updates rolling out in stages. The full release is set for January 2025. Fast, Direct Access with Deep Linking Portfolio Forecaster 2.0 makes it easier than ever to jump directly to the information you need. Deep linking allows you to copy a forecast’s URL and share it with team members, giving them one-click access straight to the data. No more digging around or long email chains—just a simple link that brings your team exactly where they need to be. How Portfolio Forecaster 2.0 Enhances Your Forecasting Experience Building on the strengths of Portfolio Forecaster 1.0, Portfolio Forecaster 2.0 brings an exciting new level of depth and precision to your forecasting experience. While the original version was a great start, this update addresses the needs of users managing complex projects with diverse issue types. With enhanced features and functionalities, 2.0 empowers you to make more informed decisions and drive successful outcomes, transforming the way you approach forecasting! New and Improved in Portfolio Forecaster 2.0: Forecast Any Issue Type  – No more limits to epics and versions—now every task, issue, and detail can be accounted for. Enhanced Group Forecasts  – Align your forecasts more closely with team dynamics and collaboration. Flexible Configuration  – Tailor each forecast to your unique workflows with JQL filters, link options, and more. Improved Sharing and Access Management  – Keep everyone on the same page by sharing access and granting admin permissions. Deep Linking  – Get your team where they need to go, instantly. And with  Forecast Portfolios  on the horizon, Portfolio Forecaster 2.0 is primed to bring a whole new level of clarity and coordination to your organization. It’s coming soon—get ready to take your project visibility, precision, and collaboration to the next level with Portfolio Forecaster 2.0!

September has brought exciting developments as we focus on enhancing your experience with ActionableAgile™ Analytics. We’ve listened to your feedback, and we’re thrilled to share the latest features designed to improve your workflow and data management capabilities. Here’s a look at what’s new this September! Save and Access Data Sets Easily We’ve been listening to your feedback and are excited to share the latest updates we’ve been working on to improve your experience with ActionableAgile™ Analytics for Azure DevOps! Launching in Q4, we're excited to release the beta version of the new Saved Data Sets feature. We recognize that many of our users frequently return to specific configurations, often spending valuable time reloading and setting up their preferred data sets. By allowing you to save your customized configurations, we help you streamline your workflow, enabling you to focus on what truly matters—driving insights and making data-driven decisions. You'll have a simple dialog to open or edit your saved data sets, giving you full control and flexibility. What Problems Does the Saved Data Sets Feature Aim to Solve? The Saved Data Sets feature addresses several key challenges faced by our customers: Time Efficiency:  Users often spend significant time reconfiguring data sets to match their previous setups. By allowing the saving of custom configurations, we eliminate repetitive tasks, enabling you to load your preferred settings instantly. Consistency:  For users relying on specific configurations for reporting or analysis, the risk of human error during manual setup can lead to inconsistencies. Saved Data Sets ensure that you can retrieve your exact configurations, enhancing accuracy and reliability in your work. User Experience:  Navigating through complex data configurations can be overwhelming. This feature simplifies the process, making it more intuitive and user-friendly, especially for new users or those managing multiple projects. Enhanced Focus:  By reducing the time spent on setup, users can dedicate more attention to analyzing data and deriving insights, ultimately improving productivity and decision-making. But that’s just the beginning! Shortly after the beta release, we’re adding more improvements based on what you’ve asked for. You’ll be able to mark your favorite data sets and access quick links to recent and favorite data sets directly from the data sets dropdown —making navigation a breeze. Once we've gathered your feedback and fine-tuned the experience, we aim to move out of beta in early January. Our goal is to make it effortless for you to manage and update your data sets in a way that best fits your workflow. We can’t wait for you to try it out! External File Loader Last month, we shared an update on loading external data files, and we’re thrilled to announce that it’s officially live for our Standalone version! After a successful validation period, we’re gearing up to roll it out to all other versions soon, with full deployment expected by the end of the month. Why the Update?  Our previous data loading system often felt restrictive, leading to user frustration with unclear error messages and cumbersome formatting requirements. To resolve these issues, we’ve implemented several key enhancements: Simplified File Formatting:  We’ve integrated direct links to file format requirements within the loader and added a download button for the template—eliminating the need to check the documentation. Smart Column Mapping:  Users can now map file columns to specific types such as ID, Title, or Workflow Stage. While the system is designed to map certain column types, you have the flexibility to override our suggestions. Date Format Detection:  The system now displays the detected date format (e.g., MM/DD vs. DD/MM), allowing you to verify and adjust as needed, resolving a common pain point. Comprehensive File Analysis:  After mapping, we analyze the entire file and identify any cleanup actions needed. You can correct these for future uploads or proceed with loading the file as is. If there are rows with errors, we’ll provide detailed information and allow you to export a list, noting that any problematic rows will be removed if they continue. New Global Date Range Filter This month, we will be rolling out the new global date range filter, which allows you to choose which portion of your data set you want to analyze at any given time. Once set, it will apply to all charts until you change it. You will no longer have to go into the date control of each chart to analyze a smaller time period. Explore Our Product Roadmap Page! Have you explored our  product roadmap page  yet? If not, you’re missing out! It’s your exclusive gateway to all the exciting developments in ActionableAgile™ Analytics. Curious about what features might be next? Our "Under Consideration" section showcases ideas inspired by your feedback. Our "Planned" features highlight what we’re prioritizing based on your input. Stay informed with "In Progress" updates to follow the development of actively worked-on features. Plus, check out the "Released" section to see the latest improvements we’ve rolled out to enhance your experience. Your insights truly matter to us! If you have ideas or features you’d love to see, please share them. By visiting our product roadmap page, you can stay updated on our latest developments and actively contribute to the future of ActionableAgile™ Analytics. Take a moment to explore the roadmap and let your voice be heard—together, we can create something amazing! Thank you for being a valued member of the ActionableAgile™ Analytics community! We look forward to your feedback on these new features.

You would be easily forgiven for answering “Mount Everest” to the title question.  After all, that’s what most of us are taught in school (assuming we were awake during geography class).  But if you have read any of my material over the years, you know that most of what we have been taught is misleading, if not downright wrong. To determine the tallest one, we first have to measure all of the mountains on the planet. And it turns out that measuring the world’s mountains is much more complicated than you might think.  In fact, over the years, there have been several contenders for the crown: In 1792, Mount Chimborazo (Ecuador) was thought to be the tallest Then, in 1808, it was Mount Dhaulagiri (Nepal) Then, in 1847, it was Kangchenjunga (Nepal/India) It wasn’t until 1852 that the peak we now know as Mount Everest was officially named the tallest mountain in the world. Why did it take so long to name a winner?  As you’ve probably guessed, changes in technology, measuring methodology, and even changes to the earth’s crust due to plate tectonics have all contributed to updated rankings over time (as an interesting side note, because of plate tectonics, Mount Nanga Parbat is currently growing faster than Everest and in 241,000 years will be the world’s tallest, ceteris paribus).  But in reality, the hardest thing about measuring a mountain is defining what it is. In other words, when we call something a mountain, we first need to decide where it " starts” and where it " finishes.”  To most of us, spotting where a mountain “peaks” is fairly obvious.  Just look for the one above all of the other ones.  But finding the top is only half of the equation.  It’s deciding where a mountain starts, that is the tricky bit.  For example, Mauna Kea is the highest point in Hawaii—that’s easy to see.  However, more than half of Mauna Kea's mountain is submerged.  Measuring Mauna Kea from its base (underwater) to its summit gives 10,211 meters—which is about 20% taller than Everest. If we only consider mountains with a base on land, then Denali in Alaska is actually “taller” (with a base-to-summit measurement about 1,000 meters more than Everest). So why have all of us been taught that Everest is the tallest?  That’s because when measuring mountains, scientists generally use a “sea level” hack as the starting point for all their calculations.  Why is the sea level a hack?  As you may have guessed, the sea isn’t so level.  The following graphic from the European Space Agency is a brilliant illustration of this point: Due to factors like the earth’s rotation, tides, differences in the strength of gravity at different spots, etc., the sea actually has dramatically different levels around the globe.  Scientists attempt to “smooth out” these differences by calculating an arithmetic mean to use as “sea level.”  That’s right, they use an average.  And as we all know, an average is (generally) a hack.  Therefore, Everest gets its award due to an arbitrary starting point for a calculation that creates a baseline that doesn’t in any meaningful way exist anywhere on Earth. I don’t know about you, but that doesn’t seem quite right to me.  Why not pick a more objective starting point to measure from the center of the earth?  If we do that, then our good friend Mount Chimborazo, whom we saw earlier, regains the crown (due to the fact that the planet bulges around the equator). I’ll leave it up to you to decide what you think the tallest mountain is, but the point here is that all measurements require agreement on what started and finished mean.  And you can get radically different answers depending on those agreed points.  Flow metrics, in particular, are not immune to this difficulty.  When they think about predictability, most people think only about the ability to answer the question, “When will it be done?”  But that question ignores half the problem.  How long something will take depends BOTH on when something starts AS WELL AS when something finishes.  Your process could be Everest, Mauna Kea, or Chimborazo, depending on how you look at it. Therefore, take the time to carefully consider what “started” and “finished” mean in your context.   Your customers—and your predictability—will thank you for it. *This post was inspired by and based on the “Be Smart” video series on America’s Public Broadcasting Service (PBS).  If you haven’t checked that series out, do so.  Most videos are available on YouTube.

August has been a busy month for ActionableAgile™ Analytics , with exciting updates and enhancements designed to improve your user experience. From streamlined data loading processes to critical bug fixes and new control features, here's a rundown of what's new this month. Enhanced data file loading experience Starting this week, we’re rolling out a significant upgrade to the process of loading external data files across all versions of ActionableAgile™ Analytics. The improvements address longstanding challenges, ensuring a smoother and more intuitive experience. Why the Update? Our previous data loading system was often restrictive, leading to frustration as users encountered unclear error messages and cumbersome formatting requirements. To resolve these issues, we’ve implemented the following key enhancements: Simplified File Formatting:  We’ve integrated direct links to file format requirements right in the loader, and added a download button for the template—eliminating the need to go to the documentation. Smart Column Mapping:  Users can now map file columns to specific types such as ID, Title, or Workflow Stage. While the system is designed to map certain column types, you have the flexibility to override our guesses. Date Format Detection:  We now show the detected date format (e.g., MM/DD vs. DD/MM), allowing you to verify and adjust as needed, resolving a common pain point for users. Comprehensive File Analysis:   After mapping, we analyze the entire file and identify any cleanup actions needed. Users can correct these for future uploads or proceed with loading the file as is. If there are rows with errors, we display the details and allow users to export the list, noting that any problematic rows will be removed if they continue. These enhancements are designed to make your data loading process more seamless, allowing you to focus on what matters most—your analysis. Key Bug Fixes to the Beta Process Behavior Chart Starting this week, we're rolling out key bug fixes to the Beta Process Behaviour Chart across all versions to improve readability in dark mode and correct inaccuracies in tooltip data. Saved Data Sets for Azure: Major Update Work on Saved Data Sets for Azure is progressing well, with the goal of eliminating the need to recreate data set configurations. Stay tuned here or subscribe to our newsletter for beta release updates.  Global Date Range Control To view a segment of your data set, you currently need to apply date range changes to each chart individually. With the new global date range control, you can set the date range in one place and apply it across your entire data set at once. This feature is next and on its way. Stay tuned for more updates.  Additional Display options for stalled or blocked items Our current dimming feature is designed to highlight non-stalled or non-blocked items but lacks support for users who need to see all items while distinguishing between them. The upcoming feature will offer new options for displaying stalled and blocked items in charts, supporting more use cases. Penetration testing underway for ActionableAgile™ Analytics for Jira Cloud We’ll be making the report available for download via our Trust Center  as soon as it is ready. Did you know that you can subscribe to our trust center to be updated of changes and additions as they happen? Explore Our Product Roadmap and Shape the Future We invite you to explore our  Product Roadmap —your go-to page for all things development! Here, you can get a behind-the-scenes look at what we’re working on and have a say in what comes next. Under Consideration:  Explore the ideas and features we’re currently evaluating based on user feedback. Planned:  Get a sneak peek at the features and updates that have been prioritized and are scheduled for development. In Progress:  Stay updated on the features that are actively being worked on, and track their progress. Released:  Check out the latest features and improvements that are now live. Submit Your Idea:  Have a feature in mind that you’d like to see? Submit your ideas and help shape the future of ActionableAgile. Visit our Product Roadmap  today to stay informed, give feedback, and make sure your voice is heard. Together, let's build something amazing! Stay tuned for more updates and continue exploring all that ActionableAgile™ Analytics has to offer.

In today's fast-paced software development environment, achieving predictable workflows and rapid delivery is essential for developers, agile coaches, project managers, scrum leaders, and leadership alike. ActionableAgile™ Analytics offers a solution that enhances efficiency, reduces delays, and boosts productivity, ultimately leading to substantial time and cost savings. The Problem Software development's primary challenge is the necessity for predictable workflows and rapid delivery. This issue affects all roles, causing misalignment within teams, frequent delays, and a diminished ability to adapt swiftly to market changes. Repercussions include lower customer satisfaction, delayed product releases, and financial losses. The Importance of Predictability and Speed According to the 2023 'The State of Agile' report by Praecipio, a leading Atlassian Solution Partner, velocity (the amount of work delivered in a given time frame) and predictability (the ability to accurately forecast delivery times) are critical metrics for measuring team performance. Teams that can deliver predictably and quickly are better positioned to meet customer expectations and achieve business goals. Case Analysis of a UK-based Financial Services Firm implementing ActionableAgile™️ Analytics Current Situation Significantly Low Productivity:   The team faced extended lead times and cycle times. High Work-in-Progress (WIP):  An unusually large amount of WIP for a single team. Challenges in Prediction:  Difficulty in accurately forecasting completion times. Manual Tracking:  Cycle time is tracked through spreadsheets, leading to challenges. Desired Improvements Better Prediction of Delivery Outcomes. Utilization of Flow Metrics. Increased Planning Accuracy Time and cost savings on manual tasks. The result after five sprints? Over a year - What would the savings from automating cycle time calculations look like?  How do our users save time with ActionableAgile ™️  Analytics? Joanna Doyle, Agile Delivery Manager: "Before ActionableAgile™️ Analytics, I was nothing numbers within an Excel sheet. Now , it's really easy to discuss with stakeholders without having to explain what the numbers mean ." Alex Priestley, Product Leader at John Lewis / Pro Kanban Trainer: ‘We use the Aging Work In Progress chart during our daily standups to see in real time the issues to jump on and fix as a team. If we want to make decisions today that will make demonstrable improvements for tomorrow, that's my go-to'  Elaine Tittanegro Correa, Agility Transformation Director: "ActionableAgile™️ Analytics' proactive nature makes it a powerful tool for driving efficiency and addressing challenges promptly" Ben Parry, Partner & Integration Delivery Lead:  "The best benefit of ActionableAgile™️ Analytics is speed. The time between loading a board from JIRA and inspecting the related CFD is less than 5 minutes . There is no data refinement required." To sum it all up… ActionableAgile™ Analytics cuts through the clutter of misleading metrics, focusing on what truly matters—time and money. By leveraging Monte Carlo simulations for real-time forecasting and using the Aging Work In Progress Chart to highlight delays, teams can make informed decisions swiftly and streamline their workflow for better results.  Spend your time completing work, not forecasting, with ActionableAgile™ Analytics. If you or someone you know is suffering from a manual data entry prison, help is on its way! Start a free trial here.

In my 3.5 years of working with diverse teams across various industries, one thing is crystal clear—everyone hopes to leverage agile methodologies to enhance work delivery. With a plethora of options available, it’s puzzling why issues persist. Could it be that everyone is doing it wrong? Or could bad habits be holding them back from success? I’m betting on the latter, and I’d wager that you’re making at least one of these five mistakes: 1. A Poorly Designed Workflow A workflow, as the name implies, should illustrate how work progresses through your system. While this may sound straightforward, it can be complex depending on your team’s dynamics. There's no one-size-fits-all formula for creating the perfect workflow, but keeping a few key principles in mind can help you visualize the various stages your tasks undergo from start to finish. The primary challenge often lies in identifying bottlenecks and issues within the workflow. To address this, it is essential to find a method to measure the time it takes for work to progress from start to finish. To achieve more precise metrics for decision-making, design a detailed workflow that isolates specific stages of the work’s lifecycle. For example, by distinguishing between active and waiting stages, you can determine whether issues stem from prolonged waiting times or inefficiencies during active phases. Once bottlenecks are identified, you can collaborate with your team to investigate the causes and develop an action plan to improve the situation. 2. Lack of WIP (Work in Progress) Management Starting tasks without focusing on finishing them and allowing work to age without valid reasons will eventually cause problems. If you let items age, you'll eventually need to close these tickets and might be facing some that are several hundred days old, which can drastically impact your Cycle Times. If 85% of your tasks are completed within 13 days or less, imagine the repercussions of finalizing items that are over 100 days old! To prevent accumulating too many "old" tickets, discuss them with your team and decide on a course of action, such as moving them back to the backlog for resizing or splitting them up into smaller items. By using Work Item Age as an indicator of potential issues, you can initiate conversations early and address problems before they escalate. While it may not be possible to eliminate all old items, you will likely have significantly fewer on your board. Consequently, if items move faster through your workflow, your Cycle Times will decrease. Additionally, the fewer outliers you have, the more predictable you will become. 3. Having a Blocked Column This is the worst approach of them all. It doesn’t do what you think it does. You might argue, “But Margaux, it brings visibility to all currently blocked items and helps us manage the blockage better.” (Insert skeptical Margaux face). Yes, it does provide visibility, but does it actually help manage the blockage? To handle blockages or dependencies effectively, you need to identify where the blockage occurred in your workflow: Was it during the testing phase? The development phase? Or while waiting for UAT? You also need to know how long the item has been blocked because different durations may require different approaches (e.g., escalation). Moreover, if you have WIP (Work In Progress) limits, what happens when the item is unblocked but no slots are available in the workflow to address it? It will have to gather dust until a slot opens up, extending the time required to handle it. There are better ways to highlight blocked items without moving them to a different column or status (don’t do that either). For example, in Jira, you can flag an item, which will then change color to make it easily identifiable. This method provides more accurate analytics on time spent in each workflow stage, helping you identify bottlenecks where work often gets stuck. This insight can help you improve your processes and hopefully reduce blocked time. 4. Focusing too much on WIP Limits WIP limits are an effective way to maintain a balanced workflow, ensuring you neither overload nor underutilize your system. However, they can sometimes mask underlying issues in your process. Consider a scenario where your In Progress stage has a WIP limit of 10, and you adhere strictly to this limit. While you may not exceed or fall short of this number, the age of the items in progress becomes a critical factor. You might be advancing 6-7 items swiftly, but what about the remaining 3 that have stagnated for days? Merely observing WIP limits won't prevent work from aging. To manage your flow effectively, you must monitor both the quantity and age of your WIP. This relates to our third point: actively monitoring and managing the age of your work can resolve numerous issues. 5. Not Slicing Your Work When work takes too long, it might be because the task is too complex and could benefit from being divided into smaller yet still valuable pieces. What are the smallest deliverable components that still provide value? If a component doesn’t add value, should it even be worked on or released? Having this discussion ensures that you always focus on potential value and avoid discovering at the end of the sprint or project that half of the work was irrelevant. More refined tasks are likely to move smoothly through your workflow, ensuring a steady stream of completed work ready for release. This approach enables you to receive feedback much faster, allowing you to adapt and make better data-driven decisions. In Conclusion Let's recap the 5 points and use more familiar terms: #1: Bad workflow design- ineffective Cycle Time  management. #2: Ignoring WIP Management - overlooking Work Item Age . #3: Maintaining a blocked column - poor WIP  oversight. #4: Mismanaging WIP limits - inadequate handling of Work Item Age  and poor WIP  control. #5: Failing to break down tasks - poor Throughput  management. You might be thinking, "Wait a minute... aren't these the key flow metrics?" And you'd be right! Flow metrics are crucial to achieving better workflow and agility. They're a fundamental concept in Kanban, but they are equally beneficial whether you practice Scrum or SAFe. Definitions: Cycle Time: total elapsed time an item took to be completed from start to finish Work Item Age: total elapsed time since the work started WIP:  amount of work that has started but not yet finished Throughput: amount of work finished in a given time period Ultimately, these metrics help you better predict the amount of work that can be planned for the next PI or sprint. Imagine spending minimal time on metrics while confidently forecasting and achieving accurate predictions. It’s entirely possible! You don't have to choose between methodologies; you can integrate them to achieve your desired outcomes. Shake things up and give it a try 😄 Interested to hear more? Curious but not yet convinced? Feel free to reach out to me at support@55degree.se  or on our community at https://community.55degrees.se/ .

When you talk about forecasting with your colleagues you are apt to hear about a wide range of experiences and opinions. There is almost always a difference of opinion on how to actually determine a forecast and there's often disagreement on whether or not you should be forecasting at all. #NoEstimates anyone? I believe that both of these disagreements exist because traditional estimation processes are so time-consuming, and often inaccurate. At 55 Degrees we don't think forecasting should be avoided, but we do need to find a way to create forecasts that can work in uncertainty and doesn't waste time and sanity in the process. What forecasting technique does ActionableAgile use? The strategy we use in our flagship product, ActionableAgile Analytics, uses a technique called probabilistic forecasting. As the name implies it helps you provide a forecast that examines possible outcomes and the likelihood of each. This makes it perfect for situations where there's not a single obvious, inarguable outcome. A probabilistic forecast includes a range of possible outcomes and the probability you'll land on one of the outcomes in that range. Here are some examples: "We have an 85% chance of finishing a work item in 7 days or less." "There's a 95% chance we can finish 6 items or more in a sprint." "There's a 70% chance that we'll finish these 20 items on or before November 1." In ActionableAgile we figure out the range of outcomes and related probabilities by using your data and looking at the Cycle Time and Throughput of your past work. What can I forecast with Cycle Time? Using our Cycle Time Scatterplot you can forecast how long it is likely to take to finish a future work item based on how long it took to complete items in the past. Read more about our Cycle Time Scatterplot! What can I forecast with Throughput? While with Cycle Time you can create forecasts for individual items, Throughput allows you to create forecasts for larger efforts containing multiple work items. This can mean a number of things such as sprints, projects, releases, and more. Using your Throughput, our Monte Carlo simulations take the rate at which you finished work in the past to answer questions like "How many items can I finish by X date?" (Fixed date) and "When will this set of work be finished?" (Fixed Scope). Learn more about how our Monte Carlo Simulations work. What do I need to get started? If you haven't already, start a free trial of ActionableAgile - either in our SaaS version or install our app in your Jira or Azure DevOps instance. Then load in your data and you're off to the races. Our charts and simulations will automatically provide you with forecasts you can use based on your data. You can use the included chart controls to segment or filter your data any way you want to have ultimate control over what you're forecasting. We are always available to help via our support portal located at https://55degrees.se. We hope to hear from you soon!

One of the things leaders often say they want most is predictability. Fortunately there are 2 things you can do every day to be more predictable. Predictability is defined as the consistent repetition of a state, course of action, behavior, or the like, making it possible to know in advance what to expect. Dictionary.com If you read that definition carefully, you may notice that the words good or bad are missing. Predictability itself is value-neutral. Being predictable is the attainment of the skills required to allow customers and other interested parties to have the advantage of knowing what to expect. Now, we all can think of an organization that we think of as predictably horrible at customer service (erm… certain cable TV companies come to mind) or a restaurant that has predictably bad food. So, it is fair to say that leaders want value-driving predictability, especially in regards to an organization’s ability to deliver value to its customers on a regular basis. How can we tell how predictable we are? Pretty easily! You can tell how predictable you are just two pieces of data for each work item you finish: the date you started the work item and the date you finished it. Using that data, you can create a Cycle Time Scatterplot and get a very visual view of your predictability. Each dot on a Cycle Time Scatterplot represents a single piece of work that was completed and where the dot is placed tells us how long it took to deliver that piece of work. This duration is referred to as cycle time. If more than one item finishes on the same day with the same Cycle Time, you just make the dot bigger and write the number of items on the dot. In the beginning, when you have little to no predictability, the dots will be widely scattered all over the chart. As you learn how to become more predictable, the range of space the dots inhabit will become vertically narrower. Read our previous blog post “Quick and accurate forecasts with ActionableAgile” to learn how to use this chart to make your forecasts reliable, even when your work and circumstances aren’t varied. Two things you can do daily to be more predictable! Now, that you know how to determine your level of predictability, you probably want to know what to do to improve it! Well, there are two simple, domain-agnostic things that you can do each day to improve your predictability: Thing 1: Stop starting, start finishing One of the biggest culprits of lengthening Cycle Time is multi-tasking. Well, we think we’re multitasking but what we’re actually doing is something called task switching — putting one thing aside to work on another and then coming back to the first thing later. Implementing a limit to the number of things you will work on at a time can help individuals, teams, or even organizations focus on fewer items at a time, allowing them to deliver the items faster and, usually, with better quality. This limit is called a work-in-progress limit, or WIP limit, and is a key component of a Kanban system. These limits can be implemented per person, per team as a whole, or even by activity in a workflow or value stream as seen above. The important thing is that you establish a threshold and adhere to it as often as possible. So, each day, as you make choices about what to work on, finish what you’ve already started before you pick up anything new! Thing 2: Pay attention to the age of work-in-progress Once you have WIP limits in place you can start an effort to make sure no one work item ever sits and ages for too long. To do this, you need to be able to see how old an item is. If you are tracking your cycle time, you already know when you started an item and you probably know the current date. With those two data points, you can get a good picture of how old your work-in-progress is. That information can be used in daily meetings to ensure you prioritize work that’s in danger of getting old. Much like the Cycle Time Scatterplot, the Aging Work In Progress Chart has a dot for each work item but the axes are different. The Y-axis is the age of the item so far. The X-axis represents which stage of your workflow the item is in. The dot is placed at the intersection of these two data points. It is important to remember that all of these dots will (hopefully) end up as a dot on your cycle-time scatterplot. So, we want to make sure they don’t get super old and, even better, that they stay within an expected range. When you take the percentile lines from your Cycle Time Scatterplot and overlay them onto your Aging Work in Progress Chart, you can get a much more detailed understanding of how at risk an item is for finishing in your expected timeframe. The percentile lines tell you how likely your work is to finish by a certain age. So, if you are at the very beginning of your process for an item and it is already older than 60% of your items are when they’re finished, you know that item is at risk of negatively impacting your predictability. And, while one item may be nothing to freak out about, if this happens often enough, you become less predictable and have to provide longer estimates to your stakeholders. So, if you’ve been looking for a leading indicator of predictability, the Aging Work in Progress Chart is just what you asked for! Yes, you can really do it! What’s great about this is that you really don’t need to be a data geek and you don’t need to be using a specific methodology, framework, or toolset to improve your predictability. By focusing on finishing over starting by implementing WIP limits and working on older items first, you can greatly improve your predictability without a huge overhaul of your processes — though it might end up being the start of something quite transformative! If this topic gets you pumped up and wanting to learn more, consider taking a workshop offered by 55 Degrees AB or try out ActionableAgile for free!