There could indeed.....
To give a bit of context, what I am trying to produce is a comparison to an intra-day forecast and an actual day and trying to provide a mathematical explanation for the reasons for variances in Service Level achieved, ie X% variance because we had more/less calls than forecast, Y% because AHT differed and Z% because the actual heads we had differed from the forecasted net requirement, hence not using shrinkage in my calculations. Thus, the sum of X, Y and Z should equal the variance in forecasted and actual service levels give or take a bit.
1) Reported occupancy for the interval was lower than 80%.
2) I suspect it may be but can't get minute by minute call data from my ACD (due to the scale of the data) to verify this.
3) Agree abandon rate increases, for the interval I am analysing, the abandon rate was c.1%.
To provide a bit of background, I am using standard 80/20, 80% occupancy and our average patience value is over 10 minutes (very much driven by the nature of the business).
4) After spending 20 years in forecasting suggesting that Erlang may not be the be all and end all, I suspect this may be the piece of work which proves it...