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Chapter 10A of Daniel S. Vacanti’s Actionable Agile Metrics for Predictability: An Introduction (buy a copy today) is a very short chapter (I should have planned to include this in chapter 10B, but hindsight is 20/20) covering a discussion of histograms but given the time and space we can spend additional time with an example.  The chapter is titled Cycle Time Histograms.  

What is a histogram?  A histogram is a graph that shows the population of a data set within ranges. How the data is spread across those ranges is called the distribution.  The shape of the distribution will generate questions.

Given that histograms are a visualization of data, nothing tells the story better than an example.  We will use the data that we used in the discussion of scatter plot diagrams in the main section of Chapter 10. (I have appended the list of data at the end of the entry)

A histogram is constructed by putting data into ranges (called bins) and then counting the number of occurrences in each bin.  Using a range of 10 for each bin yields the following histogram.

Bin Size of 10Looking at the histogram generates questions that the team could use to make changes to how they are working and to become more predictable.  For example, one question might be what caused the one story to be between 30 – 40 days and could/should the team take action to avoid that issue in the future.  The goal of collecting and analyzing any measurement data is to ask questions and take action.  If you are not going to do anything with the data don’t waste your time collecting the data.

Data are grouped together to help viewers of the data to see the distribution. If we set the bin size to 1 (the same as no range) the histogram of the same data would be less useful.  An example:

Bin Size of 1

There are a number of ways to determine bin size (here is a great article on establishing bin sizes).] While some of the techniques  for establishing bin size can be very technical, start simple and remember that the ranges should include all of the data, the bins should be the same size, and don’t go crazy with the number of bins.

Histograms are another way to plot data suggest questions so that problems can be diagnosed and changes made.

Previous Installments

Introduction and Game Plan

Week 2: Flow, Flow Metrics, and Predictability

Week 3: The Basics of Flow Metrics

Week 4: An Introduction to Little’s Law

Week 5: Introduction to CFDs

Week 6: Workflow Metrics and CFDs

Week 7: Flow Metrics and CFSs

Week 8: Conservation of Flow, Part I

Week 9: Conservation of Flow, Part II

Week 10: Flow Debt

Week 11: Introduction to Cycle Time Scatterplots


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Data for graphs:

Date Cycle Time
Story 1 1/1/2018 1
Story 2 1/2/2018 4
Story 3 1/3/2018 7
Story 4 1/4/2018 3
Story 5 1/5/2018 7
Story 6 1/6/2018 9
Story 7 1/7/2018 0
Story 8 1/8/2018 11
Story 9 1/9/2018 40
Story 10 1/10/2018 1
Story 11 1/11/2018 6
Story 12 1/12/2018 8
Story 13 1/13/2018 1
Story 14 1/14/2018 11
Story 15 1/15/2018 15
Story 16 1/16/2018 6
Story 17 1/17/2018 5
Story 18 1/18/2018 11
Story 19 1/19/2018 12
Story 20 1/20/2018 13