Empirically, I don’t think that this has happened very much. We have a “withdrawn by applicant status”, which would include this, but the status is very rarely used.
In any case, the numbers above will factor those applications in, but I would guess that if we didn’t, the numbers would decrease by less than a day.
My point is more around the fact that if a person withdraws their application, then they never received a decision and so the time till decision is unknown/infinite, it’s not the time until they withdrew.
Oh, right—I was counting “never receiving a decision but letting us know” as a decision. In this case, the number we’d give is days until the application was withdrawn.
We don’t track the reason for withdrawals in our KPIs, but I am pretty sure that process length is a reason for a withdrawal 0-5% of the time.
I might be missing why this is important, I would have thought that if we were making an error it would overestimate those times—not underestimate them.
My point was that if someone withdraws their application because you were taking so long to get back to them, and you count that as the date you gave them your decision, you’re artificially lowering the average time-till-decision metric.
Actually the reason I asked if you’d factored in withdrawn application not how was to make sure my criticism was relevant before bringing it up—but that probably made the criticism less clear
Hmm so I currently think the default should be that withdrawals without a decision aren’t included in the time-till-_decision_ metric, as otherwise you’re reporting a time-till-closure metric. (I weakly think that if the withdrawal is due to the decision taking too long and that time is above the average (as an attempt to exclude cases where the applicant is just unusually impatient), then it should be encorporated in some capacity, though this has obvious issues.)
Are you factoring in people who withdraw their application because of how long the process was taking?
Empirically, I don’t think that this has happened very much. We have a “withdrawn by applicant status”, which would include this, but the status is very rarely used.
In any case, the numbers above will factor those applications in, but I would guess that if we didn’t, the numbers would decrease by less than a day.
My point is more around the fact that if a person withdraws their application, then they never received a decision and so the time till decision is unknown/infinite, it’s not the time until they withdrew.
Oh, right—I was counting “never receiving a decision but letting us know” as a decision. In this case, the number we’d give is days until the application was withdrawn.
We don’t track the reason for withdrawals in our KPIs, but I am pretty sure that process length is a reason for a withdrawal 0-5% of the time.
I might be missing why this is important, I would have thought that if we were making an error it would overestimate those times—not underestimate them.
My point was that if someone withdraws their application because you were taking so long to get back to them, and you count that as the date you gave them your decision, you’re artificially lowering the average time-till-decision metric.
Actually the reason I asked if you’d factored in withdrawn application not how was to make sure my criticism was relevant before bringing it up—but that probably made the criticism less clear
What would you consider the non-artificial “average time-till-decision metric” in this case?
Hmm so I currently think the default should be that withdrawals without a decision aren’t included in the time-till-_decision_ metric, as otherwise you’re reporting a time-till-closure metric. (I weakly think that if the withdrawal is due to the decision taking too long and that time is above the average (as an attempt to exclude cases where the applicant is just unusually impatient), then it should be encorporated in some capacity, though this has obvious issues.)