Hi, Tom - happy to provide a few tips, for what they're worth. Dave Appleby's response will give you some great ideas, as well. There's certainly more to forecasting than can be covered in a single posting, but we'll give it a shot.
It *is* a monumental task to account for various call volume drivers, but the good news is that it's been done before. I've got a half dozen clients in the utilities sector for whom we've created accurate forecasts, and while all markets are slightly different, the basic drivers are the same.
WFM tools are great at creating optimal schedules and helping to manage adherence. Forecasting accurately (+/-3% per day) is not usually their forte.
Regression analysis on a single line will do exactly what you said - assume a constant growth. However, a *multivariate* regression analysis works much better. I'll detail that in a moment.
In a basic sense, there are two types of call volume: base and variable. The base call volume is driven by the number of customers that you have. Variable call volume is driven by billing (you nailed that one, Tom), seasonality, holidays, marketing (particularly in a deregulated environment), etc.
The first line of your regression should be based on the total number of customers you have per month (going back as far as you can). The second line should be the number of new customers, the third should be the number of dropped customers. This will give you a base call volume.
The variable volume should include specific billing cycles for each day. Each drop is assigned a response rate (2-5%, depending on the season) and a response curve (percentage of total calls arriving week one, week two, etc). This variable volume is then layered over your base volume.
Seasonality is a big factor with most utilities. You can adjust for this by either changing the billing response rate on a monthly basis, or accounting for it as a percentage increase/decrease on the total volume each month. I recommend the former.
Holidays can stump a forecast if not accounted for. For instance, the Tuesday after a Monday holiday will be much busier (25-35%) than an ordinary Tuesday.
Also, there must be good communciation between your billing department and/or fulfillment group. A mistake on a batch of bills will generate unforseeable call volume, late billing drops will throw your forecast off by a number of days, etc. Other culprits for daily volume spikes are: higher volumes due to poor abandoned rate the previous day/week, newspaper articles or other (sometimes negative) press, surprise advertising (isn't it all?), power outages, etc.
There are some starters. Sounds like you already have a sound understanding of forecasting, Tom, hope this isn't too rudimentary. Please let me know if this leaves more questions than answers -