{"id":848,"date":"2018-08-24T08:00:55","date_gmt":"2018-08-24T06:00:55","guid":{"rendered":"https:\/\/getnave.com\/blog\/?p=848"},"modified":"2023-03-15T21:42:03","modified_gmt":"2023-03-15T19:42:03","slug":"kanban-throughput-histogram","status":"publish","type":"post","link":"https:\/\/getnave.com\/blog\/kanban-throughput-histogram\/","title":{"rendered":"Evaluate Process Performance: Throughput Histogram"},"content":{"rendered":"
<\/div>\n

In the Kanban Method<\/a>, throughput is the key measure of workflow efficiency. No matter how many tasks are being worked on, throughput only measures what has been completed.<\/p>\n

While kanban throughput is commonly displayed as a bar chart, you can gain much better insights into your process by using a throughput histogram<\/a>. Histograms display the frequency distribution of your data. Learning to read these charts enables you to track your workflow performance over time, determine your team capacity and assess your process efficiency.<\/p>\n

The Kanban throughput histogram<\/h2>\n

Average throughput<\/a> is one of the most accurate approaches to track workflow performance, and the preferred method of visualizing this metric over a period of time is using a throughput histogram.<\/p>\n

Histograms<\/a> show the shape and distribution of your data. The greatest benefit that comes with their use is the ability to monitor basic information about the dataset, such as the median value, the width of spread and the overall distribution of the assignments of your team.<\/p>\n

\"Kanban<\/a><\/p>\n

Throughput histogram allows you to visualize how consistently your team is delivering results. On the horizontal axis is the throughput (number of tasks completed), while the vertical axis shows the frequency (number of days) that had a certain throughput. The vertical percentile lines indicate the probability that throughput will be repeated in the future \u2013 for example, using the graph above, there is a 50% chance that the future throughput of this team will be 5 items\/day or fewer. There is an 85% chance that the throughput will be fewer than 7 items a day. These values can be used to define service level agreements<\/a>.<\/p>\n

Plotting a throughput histogram<\/h2>\n

Let\u2019s look at plotting a histogram to show the throughput of a team over a month. Here is how the team performed in table form:<\/p>\n

\"Daily<\/a><\/p>\n

It is difficult to make sense of the numbers using such a simple table. One thing that does stand out is the two zero values cropping up every seven days \u2013 weekends. Let\u2019s try displaying this data on a scatterplot:<\/p>\n

\"Throughput<\/a><\/p>\n

This makes more sense \u2013 it\u2019s easy to see how the team\u2019s throughput has varied from day to day over the month. However, we can\u2019t easily see the average throughput of our team or work out trends over time.<\/p>\n

Let\u2019s make a histogram of this data. First, count the number of days that have a certain throughput.<\/p>\n

\"Throughput<\/a><\/p>\n

Let\u2019s plot this data as a histogram diagram.<\/p>\n

\"Throughout<\/a><\/p>\n

Now that we have a histogram, can you work out what useful conclusions and insights can be drawn from it?<\/p>\n

<\/div>\n

How to read throughput histograms<\/h2>\n

Average throughput measures how much work has been done on average during a week or month, tracking how trends develop over time. We can also use this value to perform rough estimation and commit to how many items a team can deliver for a certain time period.<\/p>\n

Our team\u2019s average throughput over the month is the most important metric we want to discover. There are three ways to calculate an average \u2013 they can give the same result, but frequently have some differences and mean slightly different things.<\/p>\n

One important thing to note about a typical throughput data set is the appearance of zero values due to non-work days \u2013 weekends, public holidays, vacations etc. This can make it seem like your team is less productive than they are!<\/p>\n

However, it is useful to be aware of the average throughput calculated both with and without weekend values. Including the weekend lows gives you an accurate throughput value to calculate over longer periods of time, while leaving them out will give you a more accurate throughput average for the typical business day.<\/p>\n