Context

As Agile Coaches at ASOS, we help teams continuously improve their way of working around flow, value, culture, and delivery in a framework-agnostic way. As part of this we often get asked about estimation techniques and, as a team of coaches, try to steer teams away from somewhat ‘old’ approaches such as story pointing. 

The Tesla team in our Promotions platform had been using labels/tags of Small, Medium, or Large to estimate their Product Backlog Items (PBIs). After reflecting on their way of working, they felt like this was not the most effective means of estimating and asked for help with alternative methods. After discussing amongst myself and another of our coaches, James, right-sizing was a suggestion provided, where you focus on making items no bigger than a certain size – the size being the number of calendar days it takes to typically complete items, which is calculated using your 85th percentile Cycle Time. In combination with this, you proactively track work item age (the amount of elapsed time between when a work item started and the current time) to ensure you keep on top of items in flight against your ‘right size’.

Improvements to the workflow

The team looked at their historical data for Cycle Time and settled on a right-size of 19 days or less (their 85th percentile). In addition to this, they also added a Work Item Age field/automation to their board that would automatically update every day with the age of items in progress, so that the team could prioritise these items compared to their right-size.

Impact of these changes and problems solved

Comparing the periods before (left) and after (right) the change to their approach, it’s clear that this has had a positive impact, as the 85th percentile Cycle Time has decreased by 58%.

Similarly, when comparing the two periods from a Throughput perspective, not only can we see that the trend has changed from a negative (downward) to a positive (upward), but in fact Throughput has increased by 44%.

Using right-sizing and the associated tools, this team now has a simpler, more effective means of estimation, no longer getting bogged down in what constitutes a Small Vs. a Medium or trying to waste effort in comparing the variance in items labeled/tagged as Small. The resulting changes have improved both the speed of completing work once started (as seen by the reduction in Cycle Time) and the increase in potential value the team is delivering (as seen by the increase in Throughput).