Cumulative Flow diagrams can contain quite a lot of information for observations. However, they can also be a little daunting for those who are not familiar with them. In this blog post I’ll share with you some tips and information for how to start to use cumulative flow diagrams.

Here’s an example of a CFD:

Each line is a count of the number of tickets moving through that part of the process – stacked on top of one another, hence the name “cumulative”.

  • Light Blue – Done items
  • Yellow – Deploying
  • Grey – Testing
  • Orange – Developing
  • Dark Blue – Analysing

Along the x-axis are the days – it’s quite common for CFDs to use days as the point of measurement.

Along the y-axis is the count of the tickets. For example, on day 0 there were no tickets in the Done area, whereas on day 1 there were now 3.

That’s actually one key part of being able to read these kinds of graphs. The distance in height between the two lines represents the number of tickets. Thus the larger the gap between the lines, the more tickets that are in that part of the process. Therefore, the further apart the lines the greater the Work in Process (WiP).

If you get lines that are continuing to grow apart, the you have a WiP growth problem and this is going to slow down your overall throughput. This is particularly useful if you use the top and bottom lines when viewing WiP growth because these represent the input and output of your overall system. If you’re not getting growth in you system, but lines within it a growing, it means that there’s likely a bottleneck inside the system.

Additionally, where these lines start to converge, it means you have decreasing WiP and may lead to starvation of a part / all of the system. This might not be a problem in the immediate short term, but left unchecked it may lead to an unnecessary spend / costs.

Using these observations, you can start to adjust WiP limits and control the point of input to either prevent extra work coming into the system / parts of the system, or alternatively allowing more work to flow through. Effectively, this is what managing flow is about – trying to match variations in demand and capability to achieve a balance.

Another key observation about CFDs is that the average lead time is denoted by the width of the graph. For example, if you look at the above graph at the dark blue mark on day 1 – this is when item 11 entered the system. If you track horizontally across the chart, you’ll see that this item left the system (the light blue line) on day 7. To determine the system lead time, you can deduct the entry time from the exit time giving you a lead time of 6 days.

Of course, this time will vary as things change in the system. If you look further up the chart to day 7 and the analysis count there and then track across to done, you’ll notice the lead time is down to approximately 4 days. That’s about a 30% reduction in lead time and can often be attributed to actions such as limiting WiP in the system (as Little’s law tells us that decreasing WiP can also lead to decreased lead time) or other improvements to the system.

The third key attribute of this is the angle of the bottom line of the graph. This is known as the delivery rate or throughput of the Kanban system (as an average). The flatter the angle, the less the throughput. The greater the angle (moving towards vertical), the greater the delivery rate / throughput.

You can see these three key attributes in this chart:

You don’t need to always have electronic tools – if you have physical boards you can maintain a physical chart with this data. Alternatively, you can capture this in a spreadsheet. There are also other tools out there such as SwiftKanban, Kanbanize and LeanKit that do these things for you as well.

You can now start to use cumulative flow diagrams to help make more informed decisions about your system of work. You can see bottlenecks that you can action, you can start to limit or increase input to balance flow and you can limit work through the process to help smooth the flow. You can also start to make plans around how to reduce lead time or increase throughput which will have positive impact to your customers and your financial bottom line.

The cumulative flow diagram is an essential tool for managing flow and improving the outcomes of your service delivery. If you aren’t using one, you now have the basic knowledge to get started.

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Lead time scatterplots are an important tool for a team working with Kanban. Sometimes these are referred to as a “Control Chart” which is often the case in manufacturing. However, in knowledge work I think it’s less about the “control” mechanism and more about using it to improve the capability of the term providing the services. Thus I usually just refer to these as “scatterplots” and if you look at the example below you can see why.

There’s quite a bit going on here, so lets look at each part in turn.

X-Axis – This contains a series dates, you can see they progress over about an 8-9 month period moving from left to right chronologically.

Y-Axis – Time in calendar days. This is the amount of time a work item took when it was completed. This is calendar days, so it includes weekends and public holidays.

Orange dots – These represent Standard class of service items. Each time an item is completed, an orange dot is added at the date of completion and the total lead time for the item.

Grey triangles – These represent Fixed date class of service items. Similarly to the orange dots, they represent when an item is completed and the lead time to completion.

Orange dotted horizontal line – This represents the 95th percentile mark for Standard class of service items. That is, 95% of the work items fall under the line and 5% above. This line is optional, plus you can add lines at different percentile’s as per your needs (eg 85%).

Grey dotted horizontal line – This represents the 95th percentile mark for Fixed date class of service items.

You may notice a few things:

  • Lead times are not necessarily uniform. This is often the case in knowledge work – thinking everything is exactly the same is a common misconception
  • Sometimes there are gaps – there may be holiday periods where there is less work going on. You should understand this as being part of the normal cycle / capability of your team.
  • Some items take a large amount of time – Often items that are blocked or have external dependencies cause work items to have their lead time blow out.
  • There are much fewer Fixed date items than standard.
  • Fixed date items have a much lower lead time

Things to look out for

  • Growing lead times – this would tend to indicate an underlying problem in the system that you need to attend to
  • Where batches are completed together – there may be some bottleneck in the process preventing things from getting done, or the items might not be independent – look at how you slice for independence.
  • In progress items – this only shows you the “Done” items, it doesn’t show you the ageing of currently open items. You can use a separate chart for this – it’s important to action problems early before it’s too late!

You don’t need a whole lot of data for this to get started. All you need is the start date and end date of each of your work items. A few years ago I did a lightnight talk at Agile Australia 2017 that talks about this. If you’re looking for a tool to help you do this, you should check out Troy Magennis’ “Throughput and Cycle Time Calculator” excel sheet in his Focused Objectives repository.

It’s good to understand the basics about how these scatterplots work. I’ve touched on some of the ways they can be used, but there’s more detail to it than that and it requires a few other charts, so I’ll save this for a future blog post.

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