SYSTEM AND METHOD FOR PROVIDING WORKFORCE AND WORKLOAD MODELING

1 . A method comprising:

presenting a portal configured to receive input from a user, wherein the input relates to forecasting workload and workforce for providing a communication service, the workload including ticket loads relating to repair and provisioning, the workforce including human resources and equipment; and

outputting a load prediction in response to the input, wherein the load prediction is generated by a forecast model that utilizes regression analysis of historical data and real-time information that includes workforce availability data and one or more factors impacting the workload.

2 . A method according to claim 1 , wherein the factors include weather information, the method further comprising:

detecting a change in one of the factors; and

generating a notification to the user to update the load prediction based on the change.

3 . A method according to claim 1 , further comprising:

notifying the user that the load prediction results in a particular quantity of incomplete jobs.

4 . A method according to claim 1 , further comprising:

receiving another input from the user, wherein the input specifies one or more of the factors including workload interval, workforce capacity, workforce productivity, or a combination thereof; and

modifying the load prediction in response to the other input.

5 . A method according to claim 1 , wherein the portal provides a collection point for the real-time information from a plurality of third party data sources.

6 . A method according to claim 1 , wherein the load prediction is self-correcting based on a moving average of prior load predictions.

7 . A method according to claim 1 , further comprising:

periodically retrieving new real-time information, wherein the load prediction is updated in response to new real-time information

8 . An apparatus comprising:

a communication interface configured to present a portal configured to receive input from a user, wherein the input relates to forecasting workload and workforce for providing a communication service, the workload including ticket loads relating to repair and provisioning, the workforce including hum an resources and equipment; and

a processor configured to output a load prediction in response to the input, wherein the load prediction is generated by a forecast model that utilizes regression analysis of historical data and real-time information that includes workforce availability data and one or more factors impacting the workload.

9 . An apparatus according to claim 8 , wherein the factors include weather information, the processor is further configured to detect a change in one of the factors, and to generate a notification to the user to update the load prediction based on the change.

10 . An apparatus according to claim 8 , wherein the processor is further configured to notify the user that the load prediction results in a particular quantity of incomplete jobs.

11 . An apparatus according to claim 8 , wherein the portal is further configured to receive another input from the user, the input specifying one or more of the factors including workload interval, workforce capacity, workforce productivity, or a combination thereof, the processor being further configured to modify the load prediction in response to the other input.

12 . An apparatus according to claim 8 , wherein the portal provides a collection point for the real-time information from a plurality of third party data sources.

13 . An apparatus according to claim 8 , wherein the load prediction is self-correcting based on a moving average of prior load predictions.

14 . An apparatus according to claim 8 , wherein new real-time information is periodically retrieved, and the load prediction is updated in response to new real-time information.

15 . A computer-implemented method comprising:

defining a plurality of prediction periods;

determining a quantity of tickets corresponding to each of the prediction periods;

computing an average for the tickets for a predetermined duration;

determining average amount of precipitation, or average amount of relative humidity, or a combination thereof, for a corresponding plurality of locations;

retrieving coefficients corresponding to the locations, wherein the coefficients indicate degree of influence of weather condition or prior load for the respective locations; and

outputting a predicted ticket load based on the ticket average, the average amount of precipitation, the average amount of relative humidity, and the coefficients.

16 . A method according to claim 15 , wherein data about the precipitation and the relative humidity are retrieved in real-time.

17 . A method according to claim 15 , further comprising:

receiving workforce information; and

determining quantity of incomplete jobs based on the workforce information and the predicted ticket load.

18 . A method according to claim 15 , wherein the predicted ticket load is based on a moving average of prior predictions of the ticket loads.

19 . A method according to claim 15 , further comprising:

receiving a user command from a browser; and

updating the predicted ticket load in response to the user command.

20 . A method according to claim 15 , wherein the predicted ticket load relates to repair of a communications equipment or provisioning of a communication service.