Gathering the Data
Forecasts are just as much an art as a science. Forecasts are projections; they are not goals and objectives. Forecasts provide an expectation of the future based on facts, historical data, experience and insight.
Step one is gathering the data., You want stacks of historical data. Past history is the best indicator of the future. The first place to check is your contact center platform. A robust platform will have historical reports stored for up to a year. If your platform emails or FTP’s reports automatically, many managers save those reports. Seek out those managers. Can you get two years’ worth of data? Much more than two years isn’t relevant with the fast pace of change. Less than 12 months doesn’t represent the full picture.
Then scour the data for any one-offs., Look for data that looks abnormally low or high, or missing data. Then determine what is triggering this out of ordinary data. Is that “zero” you see on a holiday and the contact center was closed? Does that holiday change to a different day each year like July 4th or is it the same day like Memorial Day, which is the last Monday in May?
For example, If July 4th moves from a Saturday to a Tuesday how does that impact call volumes on the days preceding and the days following? This is the “art” part of forecasting where your experience, intuition and judgment come into play. The data is factual but not always representative.
In this next step, you want to “normalize” the data up or down. , Let’s say on Thursdays, call volume is easily 5000 calls for the day, but you notice that on the second Thursday it is only 3000 calls. Further research shows that the contact center experienced an outage for four hours that day. Since that’s not a normal Thursday event, you can assume that if there wasn’t an outage, the contact center would have handled 5000 calls on that day as well. The actual number for that day is correct yet you want to use the normal day of 5000 calls for forecasting purposes.
On the other hand,, if every third Thursday the contact center completes mandatory compliance training then the lower number is an accurate one and for forecasting this would be the correct number to use. If the event is repeatable and predictable then these lower numbers are realistic.
The key is to determine what is driving the data aberration. You must get to the bottom of that question.