Lead time distribution charts are very useful for making improvements to your system of work. Understanding what to target and when will ensure that you get the best “bang for your buck” in improvements. Making these improvement will help you stablise your system of work and improve predictability which will open the door for the next level of possibilities for your organisation.
Here’s an example of a lead time distribution chart:
To recap what your looking at here (for more info, please refer to https://evogility.com.au/lead-time-distribution-charts/):
- X-axis: Number of days from when something was committed to, to when it was completed (ie the Lead Time). Note that in the above they are recorded at 5 day increments. So, the value for 10, represents the number of items greater than the last measure (5) and 10.
- Y-Axis: Count of the number of items that fall within that range. The number at the top of each column represents the total count for that item.
Lets look at how you can use these to make improvements.
You can see there are a number of items coming through at the 70-85 day mark. We need to be genuinely curious about what is going on here. There may be a couple of things going on here:
Different class of service – Perhaps these are items with a low cost of delay that are continually getting pushed back. Perhaps it’s worth capturing this in a different lead time chart so that you understand the lead times for each class of service independently.
Different work item type – Similar to class of service, maybe this is the lead time for a certain work item type – it may be naturally longer than the others. Again, you might want to separate those out into their own chart and create different lead time expectations and control WiP for them.
Refutable demand – Looking at these items, is there a way that they can be identified and not accepted in your system? Is their cost of delay valuable enough or is there some other organisational imperative that is pushing this into your system needlessly. Keeping out undesirable work and not “auto-commiting” to every piece gives you better ability to manage your system.
External dependencies – This is often one of the most common causes for delays – a dependency external to your control blocks these work items. Is there a way you can remove the dependency (perhaps you can upskill one or more of your team to do this work)? If you can’t do this, then is there a better way to identify the dependency early and coordinate with that group to avoid the delays?
Once you get rid of that outside tail element, the end of the tail shifts, and we’re now looking at the 30-50 day range. All of the above are still applicable. With a larger volume of items, you might want to also try:
Blocker Clustering – There might be multiple different causes for blockers that you want to explore and prioritise for removal / reduction. See this article by Klaus Leopold and Troy Magennis to learn more on blocker clustering.
Once you’ve gotten through these things, congratulations, you’ve now “trimmed the tail”, let’s look at what else you can do.
Look at the left hand side of the chart. The bulk of the requests are in the 10 day or less mark. There may be something you can do here:
Automation – There are lots of these items and they are fast, perhaps they don’t necessarily need a lot of brain power to actually get done. A subset of these you may be able to remove from your request queue through automating the process. Try to categorise these requests and look at what your automation options are for these.
Avoidance – Avoidance of these requests might also be possible. A great example of that is an IT service desk that put together a process for people to automatically, or through their manager, reset their own password. This reduces a great deal of calls to the service desk and frees up time for more important requests.
Work Item Type – As we saw in the XIT case study in our Kanban System Design course, you can often identify a particular work item type and negotiate it out of the system.
All of the options above free up capacity for your team to do more “knowledge work”. That is, the kind of work that is human intensive and valuable to customers. These improvements will help you “trim the tail” and make it more predictable.
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