The category covers the handling of deviations with focus on the number of reported and resolved deviations as well as how the deviations are being resolved. 

The data is presented in four blocks, where the top blocks are divided into three metrics: 

  1. Resolved / Reported - the number of resolved and reported deviations, displaying the total number as well as the number of deviations per risk level. 
  2. Average time to resolve - actual time to resolve and planned time (the planned time is the deadline that has been given to resolve the deviations), displaying the average time across all deviations as well as per risk level. 
  3. Resolved on time - the number of deviations being resolved on time, displaying total as well as per risk level. 

The fourth block is a top 5-list displaying the five projects with the most reported deviations and how these projects are handling these.

Through Insights you have access to updated data from all projects at all times, data that can be used to ensure safer and more efficient projects. Filter the data by projects and over different time periods to identify positive and negative trends - capture areas for improvement and take appropriate actions based on data. 

In order to help you with the analysis of the data, we have collected a couple of questions to work with: 

  • How does the number of deviations look in relation to the number of active projects? How is the distribution between the risk levels looking? 
  • How does the average time to resolve look - total average as well as per risk level? Is there any of the risk levels that stands out in terms long time to resolve and what can be the reasons for this? 
  • How does the planned time and actual time to resolve relate? Are deadlines (planned time) being set in accordance with the standards you are working with for the different risk levels? Are the deadlines set short or long? 
  • How does metric on deviations resolved on time look - total average and per risk level? What is an okay number for deviations resolved on time? Why aren't more deviations resolved on time? 
  • Are the any connections between the number of deviations and different stages of the projects? Do certain stages in the projects generate more deviations and how can you work in order to improve processes to prevent this from happening? 
  • Is there any of the projects that stands out in terms of longer time to resolve? Are they in need of support? 

TIP! Hoover with the pointer above the graphs and trend lines in order to see data on specific dates. 

Did this answer your question?