How to Reduce the Impact of Blockers on Your Delivery Times by Using Blocker Clustering
Managing blockers effectively is the first step towards revealing the obstacles that cause delays and hinder your delivery speed. One of the practices that drive continuous improvement is blocker clustering. The blocker clustering technique enables you to track the impact that blockers have on your performance and prioritize those that affect your delivery times the most.
The blocker clustering analysis consists of the following steps – identify your blockers, capture your total blockers’ time, and determine the root causes of the most impactful blockers. Let’s go through each of the steps in more detail.
Identify Your Blockers
The first step towards evaluating the obstacles that block your work from moving further in your workflow is to identify your blockers.
At the moment a work item is getting blocked, think about the reason behind it and identify what is causing the work to get stuck.
Collect all the blockers and organize them into groups. The groups might be External Dependency, Internal Dependency or Expedite Request, just to name a few.
Create a custom field on your board i.e. Blocked Reason and add the groups you have identified as options to your new custom field. Now, when a new item gets blocked, you can associate it with any of your blockers. You can also modify the custom field to include new blocker groups to keep it up to date.
Once the card is unblocked, remove the custom field option from it. The goal behind adding and removing a blocked reason to the card is to track the time that each card spends assigned with a certain blocker to be able to evaluate the impact blocked time has on your overall delivery time.
Capture Your Total Blocked Time
The next step of the blocker clustering analysis is to prioritize the most impactful blocker that causes delays in your delivery. The trick here is to count the total days your work spent blocked and split that data into each of the blocked reasons you have identified.
Our Cycle Time Breakdown Chart collects that information automatically, in order to help you identify the blocker that is increasing your delivery times the most.
The above Cycle Time Breakdown shows that 38% of the blocked time is being caused by Unclear Requirements and a further 32% by Expedite Requests. These two groups are the most impactful groups of blockers that cause delivery delays.
Determine the Root Causes of the Most Impactful Blockers
What possible solutions can we suggest to resolve these impediments? A very effective technique that you can use to figure out the root cause of the problems is the 5 Why’s approach. You ask ‘why’ multiple times over, and each answer leads you to the next question in the chain.
Blocked reason: Unclear Requirements
Why are the requirements supposedly unclear? Because a description of what is expected to be delivered has not been provided.
Why is that? Because there are no clear requirements on how a card should be structured before it is pulled into the system.
Why? Because we haven’t adopted concepts like Definition of Done, Definition of Ready or Acceptance Criteria.
What we have to focus on now is defining a clear DoD, DoR and AC, which would guarantee that the team knows exactly what they need to do to deliver results in a timely manner.
By eliminating this blocker, this team effectively reduced their delivery times by almost 40%. Drastically improving their overall performance all came down to a matter of introducing a new management practice.
Blocked reason: Expedite Requests
Why do expedite requests block work to such an extent? Because there are too many expedites in the system, which are constantly interrupting the work we have started.
Why is that? Because there is no clear definition of what an Expedite is, and most of the items just got assigned with this CoS based on intuition.
Why? Because we don’t prioritize our work based on the Cost of Delay and properly consider the risks that we have to manage.
Most likely, you need to look into the practices you have in place to better prioritize your work. Think about building a dynamic prioritization system based on the value your work brings to your customers, instead. In our Sustainable Predictability digital course, we explore the strategy of sequencing your work items, in accordance with the benefit they bring to your business, right from the moment you add them to your backlog. We’ve cut out the need to spend time reordering to-do lists.
By looking into the approach of prioritizing work based on the cost of delay and the market opportunities it realizes, this team has the potential to reduce their delivery times by a further 30%.
Manage Defects the Same Way You Manage Blockers
Although teams often track defects differently from blockers, defects can be clustered in exactly the same way as blockers, so you can investigate their root causes and work on their prompt resolution by going through these same steps.
Software defects are often the main obstacle to revealing the full potential of our solution to the market. Defects are expensive, especially when they make their way to production. The challenges behind developing quality software solutions, like constant market demand and lack of time, will remain. The cost of defects is likely to rise if we don’t commit to continuously improving our development practices.
To perform defect clustering, you can use the exact same approach that we described in the blocker clustering analysis, and use the Cycle Time Breakdown Chart to perform an analysis of the most impactful defect causes.
Improvement is not a one-off task – it happens over time, with each new improvement building on the one before. Very often, small tweaks in your management practices will lead to a significant improvement in your performance.
Prioritizing blockers and continuously working upon the root causes that prevent your work from moving smoothly through your process is a highly effective approach to take towards reducing delivery times and fostering an environment of continuous improvement.
Meet the Author
Sonya Siderova is a passionate product manager and a driving force behind Nave, a Kanban analytics suite that helps teams improve their delivery speed through data-driven decision making. When she's not catering to her two little ones, you might find Sonya absorbed in a good heavyweight boxing match or behind a screen crafting a new blog post.
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