Jira Tool Usage Regularity Analysis

Project: LIBCLOUD

Introduction

This report provides an analysis of how regularly a team uses the Jira tool. Any tool usage, for example such as opening or closing a story or task, changing a value associated with a bug, or commenting on an epic, is counted when determining Jira usage regularity.

This report examines activities between 2015-06-24 and 2019-06-06.

Based on parameters selected when this report was generated, the analysis was done with the expectation that the team regularly used Jira at least every week. Of course, no team’s actions are performed in a perfect mechanical cadence. To reflect that a team’s actions are not mechanically perfect and some variation is reasonable, this report features two values:

• Is the team currently using Jira every week?
• What is the team’s tool usage process performance index¹ (P_pk), where
  • P_pk = 1 is considered to be good,
    
  • P_pk > 1 is excellent, and
    
  • P_pk < 1 indicates that improvement is desirable given a target tool usage of weekly.

Results:

• The team is typically using Jira:
  • On average, every 0.53 weeks,
  • 50% of entries are made at a time interval of less than 0.32 weeks and 50% at a greater time interval,
  • The largest time interval between team entries into Jira is 4 weeks made on 2018-07-31.
• The team’s Jira usage is meeting expectations, on average.
  
• The team’s process performance index is P_pk = 0.55. This indicates that the team should work to improve how regularly it uses Jira. Note: p_pk indicates the team’s potential for meeting expectations on a consistent basis, not whether it met expectations at a particular point in time.

A run chart of team Jira activities (rounded to the week-level)

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1. The process performance index, denoted P_pk, indicates if the team’s process is generally capable of meeting tool usage performance expectations, regardless of if the team meets the expectations or not on any specific day. In this report, a one-sided upper bound P_pu is used. The equation is \[P_{pu} = \displaystyle \frac{(USL - \overline{x})}{\hat{s}}\] where USL = week, \(\overline{x}\) is the mean of the data point values, and \(\hat{s}\) is the \(99.7^{th}\) quantile of the exponential distribution with \(\lambda = \frac{1}{\overline{x}}\).↩︎