Analyze Flow Metrics

Owned by Couthaïer Farfra
Dec 16, 2024
3 min read

Wiveez allows you to analyze each indicator presented in a Dashboard (Product, Version, Feature, Label, Component, Sprint).

For the Flow Time indicators (Traversal Time, Reaction Time, Processing Time), Aging of tickets in progress and Efficiency, the analysis is based on the distribution via Quartiles, as well as on the quality of predictability.

Regarding throughput, the analysis will make it possible to measure the gap between incoming tickets and outgoing tickets, as well as the consistency of the outstanding amount in relation to the team's capacity to do so.

What are Quartiles?

Quartiles divide the data into four equal parts, allowing us to understand how they are distributed.

They are particularly useful for getting an overview of the performance distribution in a process.

Definition of Quartiles

  • Q1 (First quartile): 25% of data is below this value.

  • Q2 (Median or second quartile): 50% of the data is lower than this value.

  • Q3 (Third quartile): 75% of data is below this value.

Inter-quartile ranges (IQR) can also be used to detect outliers.

The IQR will represent the lower and upper limits admissible to have a predictable flow distribution. These are the famous mustaches. Values ​​falling outside must be considered as outliers and analyzed.

The IQR is defined as Q3−Q1.

A common rule is to consider any value outside of Q1 − 1.5 × IQR and Q3 + 1.5 × IQR as an outlier.

Example of calculating Quartiles

  1. Sort data in ascending order: 17; 18; 19; 19; 20; 20; 21; 22; 23; 24

  2. Calculate the First Quartile - Q1 by identifying the Cycle time of 25% of the measurements - Result: Q1 = 19

  3. Calculate the Second Quartile, i.e. the Median, representing 50% of the measured cycle times - Result Q2 = 20

    • Odd List: When the number of measures is odd, take the middle value

    • Even List: When the number of measurements is even, as in our example, add the 2 central values ​​and divide them by 2. The result represents the Median.

  4. Calculate the Third Quartile - Q3, representing 75% of the measurements taken - Result: Q3 = 22

  5. Identify the Whiskers, i.e. the lowest value and the highest value measured - Result:

  6. Calculate inter-quartile (IQR)

    • IQR = Q3 - Q1 = 22 - 19 = 3

    • Low limit = Q1 - 1.5*IQR = 19 + 1,5*3 = 14.5

    • High limit = Q3 + 1.5*IQR = 22 + 1*5*3 = 26.5

Utility

Quartiles are often used to visualize the distribution of data and identify points where the majority of values ​​fall. This allows you to see where the central values ​​are (using the median) and identify gaps or outliers.

Let's take the example of a development team that delivers tickets every two weeks. By analyzing the number of tickets delivered over multiple periods, quartiles give us insight into the distribution of deliveries. This helps understand how many tickets are delivered in the bottom 25%, middle 50%, and top 25%.