Open topic with navigation

Change Failure Factors dashboard

The Change Failure Factors dashboard helps you predict the outcome of a Change through a set of configured failure factors. The failure factor values of closed unsuccessful changes enable you to identify the possible causes for a failure, thereby, helping you plan for a successful implementation.

The Change Failure Prediction Failure Factors dashboard help Change Executives answer the following business questions:

• What is the trend of unsuccessful changes over the last one year?
• What is the overall failure rate of all implemented changes?
• Are the change failures related to a specific CI Class or Business Service?
• How are changes, which are implemented on a specific day of the week faring?

You can use the filters in the dashboard to analyze changes related to Departments, specific Assignment Group Manager Level 1, Primary CI Class, or Primary CI.

The Change Failure Factors dashboard consists of the following sections:

• Change Failure Trend: Displays the total number of closed changes in each month for the last 13 months and a line graph indicating the failure rate across these months.
• KPIs
  • Unsuccessful Changes: Displays the total number of failed changes in the last 13 months
  • Closed Changes: Displays the total number of changes that are closed in the last 13 months.
  • Failure Rate: Displays the failure rate for all changes that were implemented in the last 13 months.
• Failure Factors: Displays the top 8 failure factors that are determined by the Change Failure Prediction ML model. Failure factors help you in identifying failures associated with a change and enables you to plan the changes for a successful implementation.

  The failure factor values are denoted as squares in the heat map. The size of these squares indicate the number of closed changes across each failure factor value and the colors represent the threshold values configured for the failure rate.

  You can also hover over the squares to view the tooltip, which displays the failure factor value, number of closed changes, failure rate, and number of unsuccessful changes.

  For example, for a CI Class failure factor, the squares in the heat map denote CI Class, size of the squares indicate the number of closed changes for the respective CI Class, and the color indicates the percentage of unsuccessful changes.

  

  The threshold colors for failure rate are configured as follows:

  • Dark Green: Between [>=0] and [<=0.75*Overall Failure Rate]
  • Light Green: Between [>0.75*Overall Failure Rate] and [<=1*Overall Failure Rate]
  • Light Red: Between [>1*Overall Failure Rate] and [<=1.25*Overall Failure Rate]
  • Red: >1.25*Overall Failure Rate

  Note: These failure factors are dynamically fetched depending on the deployed Change Failure Prediction ML model. The factors are based on the list of predictor variables or failure factors that are provided out-of-the-box and can be configured to suit your business needs.

Metrics Used