The category incorporates data on the most common risks. The data is presented in blocks, where each block is divided into three metrics:
Issues created - the first block presents how many issues that has been created, distributed between issues that has been created from inspections and observations (non-incident reports).
Most common issue category - presents most common issue category created from inspections (
Most common deviation category - this block presents the most common risk category from deviations created from inspections. (
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:
Which risks are most common and why do these particular risks occur the most?
Is there any risk that over time is more frequent and occurs a lot more than others? What can be done to prevent this risk?
How does the distribution look between what is found during inspections compared to what is being reported between inspections (observations)?
Are the same types of risks found during inspections compared to what is being reported through observations?
Can more done on the proactive side, meaning that more risks could be identified through observations between the inspections and not only during inspections?
Are there risks being reported between inspections that aren't reported during inspections or vice versa? If risks are discovered during inspections but haven't been reported earlier, what is this due to? Have people passed the risk without reporting?
Are there some risks that are more prevalent than other during certain phases in the projects? How can this be prevented?
TIP! Hoover with the pointer above the graphs and trend lines in order to see data on specific dates.