Sustainable predictability can be achieved by enabling stable delivery systems. And Little’s Law ultimately defines that phenomenon. Let’s look into some little-known facts about the law and reveal the true value that it brings to our management practices.

## What is the Little’s Law Equation?

Imagine you run a hip and trendy taco truck. You’re famous for your organic, grass-fed shitake mushroom and carne asada burritos. Your freshly-made tortilla chips with a tangy salsa verde are the hit of the season, and your customers love you for it.

Now, let’s say that 20 people visit your taco truck every hour. They stick around for half an hour eating and chatting with each other. **At any given time, how many customers would you have standing around your food truck?**

Little’s Law states the following:

**λ** represents the customer’s arrival rate. In our example λ = 20 customers/hour

**W** refers to the average amount of time your customers spend with you, W = 0.5 hours

**L** symbolizes the average number of customers you serve at any one time

And here is the Little’s Law equation **L = λ * W**

Based on that formula we can calculate that the average number of customers you handle at once is L = 20 * 0.5 = 10 customers.

So why does it matter?

## The Purpose of the Law in Project Management

Let’s explore how corporate leaders apply Little’s Law in practice, and leverage it to improve the predictability of their workflows.

Little’s Law can be used to calculate the capacity of your systems. To this end, the formula can be expressed a little bit differently:

λ is **Throughput** (how many items you complete for a certain period of time) instead of customers’ arrival rate.

W is **Cycle Time** (the elapsed time an item spends to go through your workflow) instead of the time people spend at a business.

L is **Work in Progress** (or how many items stay in your system at any one time) instead of customer volume.

So L = λ * W becomes

**WIP = Throughput * Cycle Time**

There are three very important things that you have to remember about Little’s Law:

**Little’s Law is an unreliable approach to making delivery commitments****Little’s Law is an equation of averages****Little’s Law is about examining what has happened in the past**

Let’s look into all three in more detail.

### Little’s Law Is an Unreliable Approach to Making Delivery Commitments

Most people would argue that the true value of Little’s Law lies in being able to make predictions in the future. So the question is, does the law serve this purpose?

Let’s look into the following example. Let’s say you have an average WIP of 6 items and an average throughput of 2 items per day. This configuration gives your team an average cycle time of 3 days

What happens if we raise our WIP? The fact is, you cannot say that if you increase the average WIP to 12 tasks and keep the average cycle time constant of 3 days, then your average throughput will increase to 4 tasks/day.

Little’s Law won’t make that prediction.** All Little’s Law will tell you is that an increase of average WIP will result in a change to one (or both) of two key metrics – average cycle time and average throughput. **

For the Little’s Law equation to hold water, all the assumptions behind it have to apply for the time period we are investigating. More about that in a moment.

### Little’s Law Is an Equation of Averages

Furthermore, as each component in the relationship is an average, Little’s Law is a relationship of averages. This calculation will produce an average. So, we cannot make any probabilistic forecasts using this approach.

Making predictions based on an average is risky. Forecasts based on averages would only make sense if you know something about the shape of the underlying distribution of your data. If you don’t, there is no way to determine whether there is exactly a 50%, much more than 50%, or a significantly less than 50% chance of achieving your goal.

Would you commit to a delivery date that comes with a 20% chance of being met? We certainly don’t recommend doing so.

### The Law Is All about Examining What Has Happened in the Past

Little’s Law is about looking back in time and analyzing the predictability of your system. It was specifically developed to use data that had already been gathered as a basis to evaluate the stability of a delivery workflow.

On the Cumulative Flow Diagram at Nave, you’ll see the Process Metrics widget that enables you to evaluate your average arrival rate, average throughput, average WIP and average cycle time.

In a stable system, the average arrival rate will be roughly equal to the average throughput rate. This means that the tasks arrive in the process at the same speed as they leave it. Furthermore, if you’re in charge of your management practices and you are maintaining a predictable workflow, the Little’s Law equation applied to your past performance data will be highly accurate.

Apply Little’s Law to your process metrics to see whether the equation breaks down. You can use Little’s Law to analyze your work by process states. The same principle holds here. The more precise the equation, the more stable your system is. And stable systems translate to predictable systems.

**If you’re striving to achieve more predictability in your delivery workflows, I’d be thrilled to invite you to explore our proven approach to enabling and maintaining stable systems in the Sustainable Predictability program.**

## The Little-Known Fact about Little’s Law Everyone Should Be Aware Of

The truth is, the equation itself is not that important. The actual value behind Little’s Law lies in its ability to help us develop a deeper understanding of how the three basic flow metrics are connected.

The most common pattern I see in my practice is a constant increase in WIP. Little’s Law states that with an increase in WIP, your Cycle Times increase as well. **How could you be predictable in a world in which Cycle Time is constantly increasing?** You simply can’t.

There is one little-known fact about Little’s Law that each and every one of you should be aware of. Whether or not you can apply the Little’s Law equation is almost beside the point. The power of the law lies in the assumptions behind it. It provides a guide to adopting a set of process policies, in order to drive consistency and improve the predictability of your workflow. To explore the assumptions behind the law, which will enable you to maintain a stable system, download our guide to **Little’s Law Process Policies.**

## Little's Law Process Policies

Explore the assumptions behind Little’s Law to enable stable delivery systems.

The Little’s Law equation helps us understand how the three main flow metrics are connected and how changing one will inevitably affect one (if not both) of the others. Furthermore, it provides a blueprint of process policies to introduce, in order to improve your predictability and establish sustainable delivery workflows.

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### 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.

Dear Sonya

Thank you for this excellent article on Little’s Law. I can understand that Little’s Law in its original form is written down as L =𝝀 * W.

In a (more or less) stable Kanban system, the average arrival rate is equal to the average departure rate and corresponds to the average Throughput TH: The ‘agilists’ then usually note:

CT = WIP / TH with CT = average Cycle Time; WIP = average Work in Progress; TH = average Throughput.

Unfortunately, the equation is always written without average sign ∅. That already bothered me in Daniel Vacanti’s excellent but lengthy book.

Kind regards Stephan