This year, I’ve had the privilege of coaching my children’s ski racing team at Buffalo Ski Center. This experience has provided valuable insights that directly translate to my work in product development and coaching others.

In ski racing, training comprises two key elements: drills and gate training.

• Drills focus on skill development through repetition. We emphasize fundamental techniques like maintaining forward weight, keeping drills simple and consistent. The primary objective is to refine form, not speed. As my fellow coach, Ethan Hallet, wisely stated, “Don’t worry about going fast today; good form comes first, speed comes later.”
  • Feedback is paramount. Athletes ski short sections, receive immediate feedback, and repeat the drill. This reinforces correct form, ensuring it translates to race performance.
• Gate training integrates learned skills into a race scenario. Athletes ski a set course, receiving feedback at the finish to incorporate into their next run. This often involves reminders of previously practiced drills, such as “Don’t forget pole plants.”

My own approach to improvement and coaching mirrors these principles. I use kata’s– simple, repetitive exercises – to solidify desired skills. This deliberate practice builds confidence and fluency in individual techniques, much like drills in skiing. Practicing with a partner allows for continuous feedback and reinforces these skills.

When creating a forecast first ask yourself whether you are forecasting One Thing or Multiple Things. It’s not always clear which of these situations you are in but the approach you take to creating the forecast will differ significantly. This post will help you to figure out which approach to take.

When forecasting Multiple Things the best approach to take is to use a Monte Carlo forecast. This approach creates a statistically significant probability distribution of delivery on various dates based on thousands of simulations using historical throughput data. To turn this into a forecast you will choose a confidence level (I recommend starting with 85%) and find either the date by which 85% of those simulations were finished with all of the work or the number of items finished at least 85% of the time by that date.

Over the past 15 years of working with various agile techniques, practices, frameworks, and strategies I’ve found that there is one thread that ties them all together. They are all focused on improving our ability to learn and to apply that learning to our future work.

• Test Driven Development creates a seconds long feedback loop to help us better understand our business logic and learn immediately whether the code changes we make have the intended effect.
• Scrum creates an opportunity to learn whether we are creating the right product at the right time at least once per sprint when we create and deliver our Product Increment to our customers.
• Daily coordination meetings or scrums enable us to talk to each other about what we have learned over the past day and how we’re going to apply that learning to continue moving our work forward in the next day.

Learning in Kanban

As a Kanban practitioner and trainer this focus on learning is at the core of everything we do.

One of the key practices supporting continuous improvement is making your work, and how you do the work, visible. This starts by tracking the progress of that work in a highly visual way, often by using a kanban board. Once that work is being tracked we can begin to gather that data and start to gain insights into where our biggest opportunities for improvement are, often by using the metrics defined in The Three Flow Metrics (Plus One).

Some of the best indicators of team performance are the flow of both new information into the team and of value out of the team. If we can improve visibility into these indicators, and therefore the opportunities for the team to improve the way they work, it becomes possible for the team to support their organization in ways they couldn’t before. There are three standard metrics that are core to understanding the effectiveness of any flow-based system. The relationship between the three metrics is defined by Little’s Law. When applied to the systems used to enable knowledge work the law is usually restated in terms of Throughput, Work In Progress (WIP), and Cycle Time.

Every organization needs some form of planning. Public companies often plan and budget quarterly. Large software companies like Google and Apple often have launch events scheduled far in advance. Other companies need to plan their launches around training cycles. Even small startups need to have some confidence that they can deliver their product before they run out of money.

The problem that each of these organizations face is how to plan effectively - and cheaply. Every team will eventually be asked “When will you deliver?” If they aren’t prepared to answer this question they will often find themselves in a very stressful - and expensive - exercise of trying to estimate all of the remaining work, take into account all of the possible risks, and commit to a delivery date. Because they know people will be disappointed when they miss that delivery date they will likely pad the date by adding 20-40% additional time for “unknowns” or unpredictable events.