As I sit here in my office, I’m excited to share some insights from my recent experiences in the world of Agile training and the innovative approaches we’re adopting to enhance our learning environments. This week, I want to delve into a couple of key topics: the new training programme I’ve launched and the concept of continuous forecasting, which I discussed with Daniel Vacanti during our recent Professional Scrum with Kanban class.
Office Hours and Engagement
Every Wednesday at 6 p.m. BST, I host office hours where I’m available to answer your questions. This is a fantastic opportunity for anyone looking to deepen their understanding of Agile practices or seeking advice on specific challenges they face in their teams. I encourage you to join in, whether live or by submitting questions in advance. If you prefer anonymity, there’s a simple form you can fill out, no identification required.
Virtual Training Setup
Over the past few months, I’ve been conducting all my classes virtually, and I must say, it’s been a rewarding experience. I’ve taught various courses, including Professional Scrum Foundations and Professional Agile Leadership, using Microsoft Teams. This platform has proven to be incredibly effective for managing classes, offering features like breakout rooms, file sharing, and persistent channels for ongoing interaction with students.
Here’s a quick overview of how I prepare for these classes:
-
Tech Checks: A week before each class, I conduct a tech check to ensure everyone can connect seamlessly. This involves guiding participants on how to log in correctly, as there are multiple ways to access Teams, and I want to avoid any hiccups on the day.
-
Utilising Tools: We also use Mural, a digital whiteboarding tool, which allows for interactive sessions. I ensure that all outputs from our sessions are accessible to students post-class, enhancing their learning experience.
-
Reification Sessions: I’ve introduced what I call “reification sessions” two weeks after the class. This is a chance for students to revisit concepts, discuss challenges they’ve encountered, and solidify their understanding. It’s an informal yet valuable way to reinforce learning.
Continuous Forecasting
Now, let’s talk about continuous forecasting. This concept emerged during our Professional Scrum with Kanban class, and it’s a game-changer for how we approach sprint planning and daily scrums.
The Scrum Guide doesn’t mandate that we plan our entire sprint upfront. Instead, it emphasises having enough of a plan to get started. This means we can adopt a more flexible approach, focusing on the immediate next steps rather than trying to predict every task for the entire sprint. Here’s how I suggest we can implement this:
-
Start Small: Begin with a plan for the next few days, allowing the team to adapt as they progress. This dynamic planning approach helps teams respond to changes more effectively.
-
Utilise Metrics: Professional Scrum teams should leverage metrics from the Kanban guide, such as throughput, cycle time, work in progress, and work item aging. These metrics provide valuable insights that can inform our planning and forecasting.
-
Monte Carlo Simulations: By collecting and analysing these metrics, teams can perform Monte Carlo simulations to predict outcomes more accurately. This statistical approach can help in understanding potential delivery timelines and managing stakeholder expectations.
Conclusion
As we continue to navigate the complexities of Agile training and implementation, I’m committed to providing valuable resources and support to help teams thrive. If you’re interested in exploring training opportunities, please visit Naked Agility, where you’ll find a range of accredited classes designed to enhance your Agile journey.
I look forward to seeing you in my office hours or in one of my upcoming classes. Let’s keep the conversation going, and together, we can foster a deeper understanding of Agile practices that truly make a difference in our organisations. Thank you for joining me today!
Smart Classifications
Each classification [Concepts, Categories, & Tags] was assigned using AI-powered semantic analysis and scored across relevance, depth, and alignment. Final decisions? Still human. Always traceable. Hover to see how it applies.
What to read next
Scaling Agility: Navigating the Dragons of Change in the Future of Work
Explores practical strategies for scaling agile practices, key metrics, virtual training adaptations, and global insights to navigate change …
Navigating Agile Learning: Embrace Change and Community in Uncertain Times
Explores adapting agile learning to remote environments, emphasising flexibility, flow, gamification, and community support during uncertain …
Transforming Management into Agile Leadership: The Power of Virtual Training
Explores how virtual training supports the shift from traditional management to agile leadership, highlighting benefits like flexibility, …
Transforming Agile Training into Action: Experimentation and Engagement in the Workplace
Explores practical ways to apply agile training at work, using experimentation, group engagement techniques, and virtual tools to boost …
Navigating Agile Transformation: Empowering Teams for Success in a Rapidly Changing Landscape
Explores effective Agile transformation by empowering teams, improving collaboration, focusing on value delivery, and fostering continuous …
How do you make a good Forecast?
Explains how to create reliable forecasts in agile projects by using flow metrics like cycle time and throughput, and shifting from …
Detecting agile theatre with real delivery signals
Why Most Companies Operating Models Fail in Dynamic Markets
A concise comparison of Predictive and Adaptive Operating Models, explaining why traditional structures fail in dynamic markets and how …
Don’t Manage Dependencies, Remove Them
Explains why dependencies are a sign of poor system design and outlines steps to eliminate them by aligning teams, clarifying ownership, and …
The Estimation Trap: How Tracking Accuracy Undermines Trust, Flow, and Value in Software Delivery
Tracking estimation accuracy in software delivery leads to mistrust, fear, and distorted behaviours. Focus on customer value, flow, and …
Flow of Value vs Flow of Work – Misnomer or Useful Shorthand?
Compares “flow of value” and “flow of work” in Kanban, explaining why only validated outcomes count as value and stressing the need for …
Why Outsourcing DevOps Fails, and How Real Engineering Excellence Starts With Your Team
Avoid DevOps vendor lock-in, discover how true engineering excellence starts with partnership, not outsourcing. Ready to transform your …
The Definition of Done is a Commitment to Quality
Defines the Definition of Done in Scrum as a clear, shared standard for quality, ensuring increments are releasable, transparent, and …
Why Your Definition of “Done” Is Holding Back Quality, Agility, and Trust, And How to Raise the Bar
Is your team’s “done” really done? Discover how a clear, objective definition of done boosts quality, agility, and trust in product …
Acceptance Criteria vs Definition of Done: Why Getting This Right Builds Trust and Delivers Quality Faster
Stop confusing acceptance criteria with definition of done, learn the crucial difference to boost quality, speed, and trust in your agile …
How to Evolve Your Definition of Done: Start Small, Grow Smarter, and Build Lasting Momentum
Unlock a smarter Definition of Done, start small, evolve standards, and build team momentum without overwhelm. Discover how progress drives …
Why Most Transformations Fail Without Honest Conversations
Most transformations fail without open, honest conversations that address real issues, making transparency and tough dialogue essential for …
Why Your Definition of Done Is the Secret Weapon for Real Business Impact and Agile Growth
Transform your definition of done into a strategic advantage, deliver real value, reduce risk, and drive business impact with every sprint.