Other useful and nice to have stats during the assessment stage #4
Description
These would be statistics that would be nice to have during the assessment stage to make projections on the result before the end of the stage:
- Number of participating PAs
- Average number of assessments per participating PA
- Average length of assessments.
- Number of outlier PAs (PAs with a high number of assessment compared to the average)
- Number of assessment that would be automatically filtered out due to length.
- Number of first time PAs (might be difficult to get but would be a very good indicator of the quality to expect)
- Pareto statistics: how many different PAs are responsible for doing 80% of the job.
With the current system, which has no barrier against system abusers, we know that 30% to 40% of the assessments end up being filtered out.
An "in stage" on going statistic analysis could provide information about proposals at risk of having a low number of assessments after the quality assessment is done. If, for example, we can determine that 90% of the assessments on a proposal were done by new Ideascale accounts or by PAs who have only done 1 assessment or >100 assessments (or with a low reputation due to bad performance in previous funds) or simply because the average length of all the assessments on this proposal is very short, etc...