What Do We Mean By 'System Stability'?

If you’ve ever felt like your team is constantly busy but nothing ever really gets done, chances are your system is unstable. If it feels like you’re using up more of your resources but getting less, that could be a signal that you have an unstable system. If you’re not able to give a trustworthy forecast of when something will be done, there’s a reasonable chance your system is unstable.

What do we mean when we talk about system stability and why does it matter so much in Kanban? Let’s break it down in simple, practical terms.

Stable, systems

Starting with a ‘system’. Kanban is all about managing flow. Flow refers to the movement of potential value through a process that is visually represented. We often refer to that visual process as a system. It’s how work begins, is worked on, and ultimately becomes something valuable for someone.

A ‘stable system’ means that work moves through a process consistently and predictably. One common way we create stable systems is to control the amount of work in a system at any one time. This is often referred to as limiting work in progress (WIP). In effect, we only pull work into our system when there is the capacity to work on it. Limit WIP and you’ll start to get better outcomes from your system. It’s all linked.

This is the opposite of a push system, where work is pushed in regardless of whether there is capacity to work on it at that time. Push systems are unstable and focus on keeping people busy, rather than on flow. As Henrik Kniberg says in his excellent video describing the resource utilisation trap, ‘if all you do is focus on keeping people busy, all you get is busy people’.

Think about it like this. In an unstable system, we’re likely working on too many items, with things feeling chaotic. Some tasks fly through our process in a short amount of time, while many others drag on for much longer. Priorities shift constantly and planning becomes a guessing game, based more on opinion than data.

Stability is like the foundation of a house. Without it, everything else starts to wobble.

Signs and benefits of a stable system

If you’re running a stable system, it will provide you with signals that everything is running smoothly.

You’re likely not seeing that work is piling up. Your WIP control is working and work is flowing through at a good pace. Your customers are getting what they want, when they want it.

Generally, items are completed within an acceptable timeframe, with few exceptions. If you have a clear statement of how long you expect items to take, such as a Service Level Expectation (SLE), you’ll regularly adhere to it. That’s because you’re delivering at a steady pace.

You can then make better forecasts. Using past data, you can generate metrics for your system, which will help you forecast the future with a high level of confidence. Your SLE will be based on real data, providing a forecast with an acceptable degree of uncertainty. Statements like ‘we deliver a work item in 8 days or less, 85% of the time’ will be something your stakeholders or customers can trust.

Flow Metrics are your friend!

Stability does not mean the absence of variability in your data. Some level of variation is expected, particularly in product management, where less is known upfront. Instead, a stable system means that the variation is manageable and understood. Stability enables teams to utilise data for actionable insights, whereas instability obscures signals and increases risk.

Use four simple metrics to monitor flow and assess your stability:

1. Cycle Time: The elapsed time between when a work item started and when a work item finished. Stable systems have relatively consistent cycle times. You can base your SLE on your Cycle Time data, just pick the level of risk you’re comfortable with.
2. Throughput: The number of work items finished per unit of time. Stability is reflected in steady throughput over time. You can forecast multiple items using your Throughput metric — a Monte Carlo Simulation is a great tool for that.
3. Work in Progress (WIP): The number of work items started but not finished. High and variable WIP often signals instability. Try to keep your WIP as steady and as controlled as possible.
4. Work Item Age: The elapsed time between when a work item started and the current date. Stable systems tend to have lower and more predictable work item ages. Along with controlling WIP, controlling the age of your items is one of the most effective ways to maintain system stability.

In summary, system stability is what makes a Kanban system effective, efficient and predictable. It helps you to stop firefighting and start delivering with confidence.

‍