So how many people do you need to run an out of hours service for property during those overnight?
Below is a hastily put together graph of the pattern over the last 3 years of calls whilst looking after between 400,000 in 2017 and 600,000 properties now. Although I did remove the number of calls axis it shows the way data can be used to predict expected volumes i.e don’t be fooled when it gets up to 2.30am and calls have been dropping. It is remarkable that the patterns remain no matter how many units you model on.
I will leave you to draw your own conclusions of why specific days and times have these spikes which are probably not that difficult to do.
We have data-sets similar to this for all days and times of the year to help us set requisite staffing levels so if you do not use us but could use this or similar insights reach out and we are happy to share the overarching patterns if it would help
PS it works even better when you plug unit numbers in to extrapolate out actual call numbers or combine with different times of years patterns of volume increase or decrease.