Shorten and Reduce Variability in Lead Times using Kanban

When I start talking about speeding up work and reducing variability in lead time to a group of software developers, the initial reaction is often, “We can’t do that. This is knowledge work. You can’t reduce variability in the work itself. The hard stuff just takes longer and the easy stuff is shorter.” This is often followed by, “You don’t want to take the creativity out of our work”, or “You can’t treat us like machines.” So, it is important to point out up front that I agree with all of these statements. So, why would you want to shorten and reduce variability in lead times and how can you reduce lead time and variability without inhibiting the creativity required to do the work.

Why Reduce Variability and Lead Times?

Lead time is the average time it takes for one work item to go through the entire process – from start to finish – including time waiting and time consumed by rework. In most cases, unless you are intentionally managing your lead time, you will have lead times that are highly variable and probably excessively long. Why would you want to reduce lead time duration or variability?

Increase Predictability

Reducing variability in lead time will allow you to consistently know and commit when something can be delivered. Delivering consistently will help to increase the trust within the system. One of the very beneficial outcomes from increasing trust in the system is that it leads to a dramatic reduction in expediting. Once the system becomes predictable, the business may be able to make new offers to customers based on the high level of predictability.

Faster Feedback

Reducing lead time duration results in faster feedback. Faster feedback can result in increased quality. There are number of reasons for this.  Less work is done based on work items that require rework. Shorter cycles result in better fit since the feedback can be gathered and applied frequently. Also, faster feedback means that the team can minimize the work required to meet the objectives.

Flexibility and Responsiveness

Shorter lead times and trust based on predictability increases options for flexibility. You can delay some decisions until very late – deciding just before you pull into the system the details of solution. Expediting now means putting an item into the queue as the next item. Also, you can make new promises to customers based on this increased level of flexibility and responsiveness.

Wimbledon

Okay, so there are some benefits to reducing variability and duration in lead time. But, how can you reduce lead time duration and variability without inhibiting the creativity required to do the work.

Wimbledon provides some insight into this. At Wimbledon, the games take as long as they take. The number of games played is determined up front – they have to play all the games. There are Men’s and Women’s Singles, Men’s and Women’s Doubles, Mixed Double’s and many players participate in multiple events. Games can’t play in darkness (except on center court). Games can’t be played in the rain. Players can’t overlap doubles with mixed doubles or with singles play.

Wimbledon has been played 142 times and the finals have been delivered late twice. That’s pretty amazing given the wide level of variation in the length of games and the other constraints that must be addressed.

How does Wimbledon accomplish this? They have policies that impact the timing of the games – for the most part without impacting the way the game is played.  For example:

  • A tie breaker in the first four sets. This tie breaker is open ended as it requires a player to win by two points – only the final set requires winning by two games.
  • Games can start earlier on a day if games are behind.
  • The gap between games can be shortened to get in additional play each day.
  • The tournament director may have players warm up on other courts to bring games closer together.
  • Additional courts can be opened for play as long as it doesn’t create a conflict across events.
  • They minimize the impact of rain by covering courts during rain delays.
  • They have added lights and a roof over Center Court to allow games to run longer and during rain.

Combined, these policies allow the games to take as long as they take – while allowing the tournament to deliver a fixed number of games in a fixed time.

Reducing Variability and Lead Time in Software Development

Just as software development isn’t manufacturing, it isn’t tennis either. What the example shows is that lead time duration and variability can be reduced without changing restricting the way the game is played and with minimal impact on the rules of the game. This concept can be translated to software development.

Reduce Waiting

How much time is a work item actually actively being worked on? If you pay careful attention to flow of work through your system you will likely find that a typical work item spends more time waiting to be worked on then being worked on. It is not unusual to find 5-10x wait time to work time. With wait time being a large portion of lead time, reducing wait time will have a significant impact on reducing lead time. Limiting WIP and pulling work are key techniques to reducing waiting.

Rework: Or Failure Load

Another big cost on lead time – and typically a huge impact on variability – is rework. Rework is the result of a defect that unintentionally escapes from one work queue and is identified in another. The result is that work moves backwards through the system – increasing lead time not just of the current work item, but of other work items. Leveraging techniques that minimize or eliminate rework are important to reducing variability and duration of lead time. Test driven development, automated test frameworks, continuous integration, and coding standards are methods of reducing or eliminating rework. Investing into reducing rework reduces lead time duration and variability.

Making Work Ready

One cause of variability and extended lead times is when work is pulled that isn’t ready to be worked on. This can happen when dependent work items aren’t prepared, required external resources aren’t standing by, or when the outcome (not the how) is not well understood. Making work ready requires understanding and aligning dependent work items. Minimizing dependencies during design helps reduce negative impact. Using scheduling methods like Kanban to schedule external (non-instantly available) performers helps coordination of external performers so work can continue to flow.  Feature injection, where outcomes are defined during analysis and presented as testable examples is an excellent method of understanding and clearly communicating the expected outcome. Extra effort put into making work ready often results in reduced lead time.

Relatively Small and Similar Size Work

Large work items – or high variability in size and complexity of work items will result in higher variability and duration of work items. Breaking work into relative small and similar size work is a good method for reducing variability and duration of lead time. Breaking solutions down into small work can also result in improved design, higher testability, and more flexibility in the solution. This doesn’t mean that work should be broken down arbitrarily. Work should be broken down to the smallest level that is reasonable and no smaller.

Swarming

Swarming is when team members work together on work items to move them forward faster. Sometimes this is increasing the number of developers doing development – often it involves having generalists work in areas outside of their specialization. You will want to have the performers work on work items that are in risk of being late against their  SLA.

Tracking The Data

To track lead time, track the entered day and exit day from the Kanban. Do this by having the performer who pulls the card into the first queue write the date it was pulled. When it is moved to the last queue, write that date on the card. Lead time will be the difference between the two days.

To track waiting time, put a blue dot on the card for each day it sits waiting to be pulled into any queue. Count the dots when you pull the card off the board to see how many of the lead time days were waiting days.

To track defect days, you can create a defect card when a defect in a piece of work is identified downstream from its source. Move the card back to the source location and move it forward through the system until it catches up with its card. Put the start date on the card when it is created and the end date on the card when it catches up with the original card. Defect days is the difference between the start date and the end date of the defect card. Track the cumulative defect days on the work item card.

Track blocked days when the card is blocked. This can be done by putting a red dot on the card for each day it is  blocked.

Reducing Lead Time Duration and Variability in Kanban

So, by tracking data related to Lead Time, waiting time, defect time, and blocked time, the team can identify where to act to reduce the lead time duration and variability. Then, identify and leverage strategies like reducing waiting, reducing rework, making work ready, defining small size work, and swarming, to improve lead time. Tracking causes of defects and blockages can help make decisions to focus these strategies appropriately. Reducing lead time duration and variability will result in increased predictability, faster feedback, improved flexibility and responsiveness.

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One Response to “Shorten and Reduce Variability in Lead Times using Kanban”

  1. Does A Kanban System Eschew Estimation? | AvailAgility says on :

    [...] Once we understand our past (or current) capability we can use that information to forecast future capability. By understanding how long things have typically taken in the past (with natural variability) we can determine how long things will take in the future (with natural variability). Dennis Stevens has recently written some great posts discussing knowing when we will be done, using classes of service and service level agreements to manage variability. [...]

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