https://engineering-leadership-preview.hinshelwood.com/tags/forecasting/ Recent content in Forecasting on Engineering Leadership in AI & Software Hugo en Tue, 16 Jun 2026 17:40:35 +0000 https://engineering-leadership-preview.hinshelwood.com/articles/release-planning-and-predictable-delivery/ Tue, 24 Nov 2020 13:00:01 +0000 https://engineering-leadership-preview.hinshelwood.com/articles/release-planning-and-predictable-delivery/ Predictable delivery and agile release planning are not incompatible, but achieving them requires a shift in mindset, a focus on continuous quality, and embracing transparency. Key actions include making quality non-negotiable, refining backlog items to be small and clear, ensuring teams own the full delivery process, and minimizing dependencies. Development managers should prioritize building working software in regular increments, stop accumulating technical debt, and foster a culture of continuous improvement to improve delivery predictability. https://engineering-leadership-preview.hinshelwood.com/recipes/sprint-review-recipe/ Tue, 17 Sep 2024 00:00:00 +0000 https://engineering-leadership-preview.hinshelwood.com/recipes/sprint-review-recipe/ Step-by-step guide for running a Sprint Review, including presenting the increment, gathering feedback, updating the backlog, forecasting, and addressing stakeholder questions. https://engineering-leadership-preview.hinshelwood.com/articles/how-do-you-make-a-good-forecast/ Mon, 09 Sep 2019 11:20:33 +0000 https://engineering-leadership-preview.hinshelwood.com/articles/how-do-you-make-a-good-forecast/ To make better forecasts in agile projects, shift from using metrics like story points and velocity to flow-based metrics such as cycle time, throughput, and work in process, which improve predictability by encouraging smaller, more manageable work items. For budgeting and staffing, calculate team costs per sprint and extrapolate for annual needs, moving from project-based to team-based budgeting. Involve stakeholders early in this transition to address concerns and ensure smoother adoption. https://engineering-leadership-preview.hinshelwood.com/videos/overview-of-'applying-metrics-for-predictability'-kanban-course/ Tue, 20 Feb 2024 07:00:27 +0000 https://engineering-leadership-preview.hinshelwood.com/videos/overview-of-'applying-metrics-for-predictability'-kanban-course/ The “Applying Metrics for Predictability” Kanban course teaches teams how to use key Kanban metrics and probabilistic forecasting to improve delivery predictability, enabling more accurate planning and increased stakeholder trust. Participants learn to interpret data, identify bottlenecks, and make informed decisions that drive efficiency and consistent value delivery. Development managers whose teams struggle with predictability should consider this course to enhance forecasting and workflow reliability. https://engineering-leadership-preview.hinshelwood.com/articles/can-you-really-commit-to-delivering-work/ Sat, 26 Nov 2011 20:24:42 +0000 https://engineering-leadership-preview.hinshelwood.com/articles/can-you-really-commit-to-delivering-work/ Explores why Scrum shifted from “commitment” to “forecasting” work delivery, highlighting the risks of overpromising and the benefits of transparency in Agile teams. https://engineering-leadership-preview.hinshelwood.com/videos/rethinking-software-estimation-embrace-probabilistic-forecasting-for-agile-success/ Thu, 05 Dec 2024 06:30:00 +0000 https://engineering-leadership-preview.hinshelwood.com/videos/rethinking-software-estimation-embrace-probabilistic-forecasting-for-agile-success/ Traditional software estimation is often inaccurate and burdens teams, so shifting to probabilistic forecasting based on historical data provides more realistic delivery predictions and reduces pressure. Breaking work into smaller pieces and aiming for high confidence levels, such as 85 percent, helps teams adapt to uncertainty and improve outcomes. Development managers should move away from precise estimates and instead use probability-based forecasts to guide planning and decision-making. https://engineering-leadership-preview.hinshelwood.com/tags/service-level-expectation/ Mon, 05 May 2025 09:46:11 +0000 https://engineering-leadership-preview.hinshelwood.com/tags/service-level-expectation/ A Service Level Expectation (SLE) is a forecast used by Scrum Teams to estimate the time it should take for a work item to move from initiation to completion within their workflow. Originating from practices that combine elements of Scrum and Kanban, the SLE is defined by two components: a specific range of elapsed days and the probability that work items will be completed within that timeframe, such as stating that 85 percent of items should be finished in eight days or less. The SLE is calculated using the team’s historical cycle time data, which measures how long work items have taken to complete in the past. If such data is not yet available, teams are encouraged to make an informed estimate and refine it as more data becomes available. The SLE is made transparent to all team members and stakeholders, serving as a tool for identifying flow issues and prompting inspection and adaptation when expectations are not met. In agile and DevOps contexts, the SLE is valuable because it enhances predictability, supports continuous improvement, and helps teams manage stakeholder expectations by providing a clear, data-driven understanding of delivery timelines. Keeping the SLE shorter than the length of a Sprint further improves the team’s ability to deliver reliably and respond to change. https://engineering-leadership-preview.hinshelwood.com/tags/throughput/ Wed, 09 Apr 2025 14:41:23 +0000 https://engineering-leadership-preview.hinshelwood.com/tags/throughput/ Throughput is a critical observability metric that quantifies the volume of work completed by a system within a defined timeframe, serving as an indicator of the flow of value delivered by teams. Originating from Agile and Lean methodologies, throughput is utilised to assess system performance holistically rather than focusing on individual contributions. By monitoring throughput, teams can uncover trends, pinpoint bottlenecks, and evaluate the impact of workflow modifications on overall efficiency. Visualisation tools such as cumulative flow diagrams and flow analytics facilitate real-time tracking of throughput data, enabling teams to inspect flow health alongside other metrics like lead time and cycle time. This empirical approach fosters informed decision-making, guiding adjustments in work-in-progress limits, team structures, and planning processes. Ultimately, throughput enhances transparency and supports a culture of continuous improvement, allowing organisations to optimise their processes without relying on subjective evaluations of performance. https://engineering-leadership-preview.hinshelwood.com/tags/cycle-time/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering-leadership-preview.hinshelwood.com/tags/cycle-time/ Cycle time is a key performance metric that measures the total duration required to complete a unit of work, from initiation to delivery. It is widely used in agile and DevOps methodologies to enhance team efficiency and predictability in value delivery. By monitoring cycle time, organisations can pinpoint bottlenecks, streamline processes, and optimise workflows, which leads to quicker product and service delivery. Understanding cycle time empowers teams to make data-driven decisions, fostering a culture of continuous improvement and enabling better forecasting and planning based on historical data. This predictability is crucial for aligning stakeholder expectations and meeting customer needs promptly. Furthermore, cycle time promotes a holistic view of value delivery, encouraging teams to consider the entire workflow rather than focusing on individual tasks. By minimising cycle time, organisations can improve their responsiveness to market dynamics and customer feedback, thereby gaining a competitive edge. In an era where rapid and sustainable value delivery is essential, the emphasis on cycle time is vital for organisational success. https://engineering-leadership-preview.hinshelwood.com/tags/estimation/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering-leadership-preview.hinshelwood.com/tags/estimation/ Estimation is a fundamental practice within Agile and Scrum methodologies that allows teams to predict the effort and time necessary to complete tasks or deliver features. Originating from the need to manage uncertainty in project management, estimation employs empirical data and collaborative techniques to align stakeholder expectations and foster a shared understanding of project scope and timelines. This practice transcends mere numerical assignment; it involves engaging the entire team in discussions that utilise collective knowledge and experience, thereby enhancing both accuracy and team buy-in. Effective estimation is crucial as it enables teams to deliver value in a predictable and sustainable manner, facilitating improved planning and resource allocation. It also supports continuous improvement through a feedback loop that compares past estimates with actual outcomes, refining future forecasting. This iterative process promotes a culture of transparency and accountability, which is vital for high-performing teams. Unlike broader concepts such as Agile Planning or Backlog Refinement, estimation focuses on the tactical execution of tasks, serving as a foundational element for successful Agile practices. By incorporating estimation into their workflows, organisations can improve their agility and responsiveness in a rapidly changing market, ultimately leading to better outcomes for customers and stakeholders. https://engineering-leadership-preview.hinshelwood.com/tags/forecasting/ Tue, 11 Feb 2025 10:17:24 +0000 https://engineering-leadership-preview.hinshelwood.com/tags/forecasting/ Forecasting is the practice of utilising empirical data to predict delivery timelines, manage risks, and optimise value delivery within Agile and Scrum frameworks. It draws from historical performance and current capacity metrics, such as cycle time, lead time, and throughput, enabling teams to make informed decisions that lead to a more predictable and sustainable approach to product development. This practice is vital for promoting transparency and accountability, as it encourages teams to reflect on their processes and outcomes, moving beyond subjective estimations to data-driven insights that enhance decision-making. By anticipating challenges and adapting proactively, teams can improve overall efficiency and effectiveness. Integrating forecasting into Agile practices not only aids in achieving immediate project goals but also fosters long-term organisational agility, creating a resilient environment that can adapt to changing market demands. This systemic approach ultimately enhances the ability to deliver high-quality products that align with customer needs and business objectives, thereby cultivating a culture of continuous improvement and innovation.