In the realm of software development, the pursuit of accurate project estimation has been a perpetual challenge. Despite the rise of Agile methods, the specter of inaccurate estimation continues to cast a shadow over projects, leading to missed deadlines, exceeded budgets, and frustrated stakeholders. Consider this: a groundbreaking study by the Standish Group in 1995 revealed that a staggering 31.1% of software projects were canceled before completion, with over 50% ending up costing nearly twice their initial estimates. Fast forward to the present day, and while Agile has undeniably transformed development practices, the issue of project estimation remains a thorny one. While Agile projects boast a commendable success rate three times higher than traditional waterfall approaches, over 50% still grapple with time and cost overruns. The question then arises: why has Agile, with its iterative approach and emphasis on collaboration, not completely eradicated the problem of inaccurate estimation? Agile introduced relative estimation, epitomized by story points, in contrast to the upfront man-day estimations of the past. However, the journey towards accurate estimation has been fraught with challenges. Despite their widespread adoption, story points have often fallen short, leading to counterintuitive outcomes. A case study within a prominent corporation revealed that stories rated lower in complexity took longer to complete than ostensibly more complex ones. This dilemma underscores a fundamental truth: the challenge of estimation transcends estimation methods; it is deeply rooted in human nature. Our innate biases and tendencies toward optimism color our estimations, rendering them prone to error. To break free from this cycle, a paradigm shift is necessary—one that embraces a data-driven approach. The answer: actionable agile metrics and probabilistic forecasting. By leveraging historical data, teams can move beyond guesswork toward informed decision-making. These metrics provide nuanced insights into team performance and project dynamics, empowering teams to make accurate predictions about future outcomes. During this talk/presentation, I will share: - the results of two studies by the Standish Group (1995, 2020) - a case study about story points from one US corporation - what metrics we need to gather as well as how (and why) - some cool models and tools (through quick demos or screenshots) In this illuminating talk, we'll demystify agile estimation, drawing from real-world examples and personal experiences. Attendees will gain practical insights into the tools and techniques that underpin effective estimation practices. By the end of the session, participants will be armed with actionable strategies and newfound knowledge to navigate the estimation challenge confidently, ensuring smoother sailing on their Agile journey.