In last week’s BiLog , we talked about report usage, and how you can utilize a variety of mechanisms, including reports, KPIs or result sets to monitor which reports your users are and are not using. Report usage information is also critical in identifying your reports which take to longest time to execute, as you want to insure these are optimized for report performance.
Why is this important? Like so many things, reports follow the 80/20 rule, where 80% of your report processing is done by only 20% of your reports. So as you analyze the report usage data, you will find that you have a wide range of report execution times – but the key is in identifying those 20% of reports with the longest execution times.
This pie chart highlights the 80/20 rule of report complexity. Standard, transactional reports execute fairly quickly, and are the largest percentage of your report types. Complex and very complex reports often make up 20% of your report portfolio, and take the longest time to execute due to the number of subreports they encompass or the hierarchy levels they span through. This complexity is derived by the processing the report has to do – not by the number of records it displays. So, for example, a fifty page list report could execute ten times faster than a complex two page report due to the processing defined within the report’s design.