Computer-implemented system and method for generating forecasts

• US 7,251,589 B1
• Filed: 05/09/2006
• Issued: 07/31/2007
• Est. Priority Date: 05/09/2005
• Status: Active Grant

• Current Assignee: SAS Institute Incorporated
• Original Assignee: SAS Institute Incorporated
• Inventors: Crowe, Keith E., Leonard, Michael J., Selukar, Rajesh S.
• Primary Examiner(s): NGHIEM, MICHAEL P
• Application Number:
  US11/431,089
• Time in Patent Office: 448 Days
• Field of Search: 702179-181, 702/189, 705/10
• US Class Current: 702/189
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202

Abstract

Computer-implemented systems and methods for performing forecast scoring based upon time series data that is indicative of a data generation activity occurring over a period of time. One or more data stores store historical data and future data. The historical data includes historical exogenous inputs. The future data includes future exogenous inputs. A dynamic statistical model receives the historical data and future data that are stored in the one or more data stores. The dynamic statistical model is to provide forecast scoring based upon the historical exogenous inputs and the future exogenous inputs. An optimizer having an objective function iteratively varies the future data, so that forecasts associated with the varying future data values are generated by the dynamic statistical model for evaluation by the objective function.

Claims

1. A computer-implemented system for performing forecast scoring based upon time series data that is indicative of a data generation activity occurring over a period of time, comprising:

one or more data stores to store historical data and future data;

wherein the historical data includes historical exogenous inputs;

wherein the future data includes future exogenous inputs;

a dynamic statistical model to receive the historical data and future data that are stored in the one or more data stores;

wherein the dynamic statistical model is to provide forecast scoring based upon the historical exogenous inputs and the future exogenous inputs; and

an optimizer having an objective function;

said optimizer iteratively varying the future data, wherein forecasts associated with the varying future data values are generated by the dynamic statistical model for evaluation by the objective function;

wherein the generated forecasts are provided to an external system or user.

2. The system of claim 1, wherein the dynamic statistical model is contained within a forecast scoring engine.

3. The system of claim 1, wherein the dynamic statistical model is an autoregressive integrated moving average (ARIMA) model or an unobserved component model (UCM).

4. The system of claim 1, wherein the future data includes future causal factor values.

5. The system of claim 1, wherein the one or more data stores include stores selected from the group consisting of data structures, RAM, ROM, computer hard drives, and combinations thereof.

6. The system of claim 1, wherein the historical data includes number of observations, time series data, and seasonality.

7. The system of claim 1, wherein the future data includes forecast horizon and decision variables.

8. The system of claim 1, wherein the generated forecast scores are for use in optimization or goal-seeking.

9. The system of claim 1, further comprising:

model selection software instructions to select one or more time series model to model the time series data.

10. The system of claim 9, further comprising:

forecast function generation software instructions to generate a forecast function based upon a selected time series model, the historical data and estimated parameters;

whereby the forecast function is for use in providing the forecast scoring.

11. The system of claim 10, wherein the system further comprises one or more computer storage mediums for storing the forecast function generation software instructions.

12. The system of claim 11, wherein the one or more computer storage mediums include mediums selected from RAM, ROM, CD-ROM, computer hard drives, and combinations thereof.

13. The system of claim 10, wherein the forecast function generation software instructions are instructions selected from the group consisting of machine code, source code, and combinations thereof.

14. The system of claim 1, wherein the forecast scoring specifies how to forecast a time series given a fitted model through iteratively varying future input values.

15. The system of claim 14, wherein the forecast scoring is for use in analyzing a dynamic price optimization situation;

wherein the demand series data of the historical data includes demand series in units data;

wherein the historical data includes price series per unit demand data;

wherein the future data includes future prices data;

wherein the dynamic statistical model is to provide forecast scoring based upon the historical data and the future data.

16. The system of claim 15, wherein the future prices data is representative of decision variables and one or more pricing policies.

17. The system of claim 1, wherein said optimizer iterates over a thousand iterations in varying the future data values.

18. A data signal that is transmitted using a network, wherein the data signal includes the future data of claim 1, wherein the data signal comprises packetized data that is transmitted through a carrier wave across the network.

19. A computer-implemented method for performing forecast scoring based upon time series data that is indicative of a data generation activity occurring over a period of time, comprising:

storing in one or more data stores historical data and future data;

wherein the historical data includes historical exogenous inputs;

wherein the future data includes future exogenous inputs;

using a dynamic statistical model to receive the historical data and future data that are stored in the one or more data stores;

wherein the dynamic statistical model is to provide forecast scoring based upon the historical exogenous inputs and the future exogenous inputs; and

using an optimizer having an objective function;

said optimizer iteratively varying the future data, wherein forecasts associated with the varying future data values are generated by the dynamic statistical model for evaluation by the objective function;

wherein the generated forecasts are provided to an external system or user.

20. Computer software stored on one or more computer readable mediums, the computer software comprising program code for carrying out a method for performing forecast scoring based upon time series data that is indicative of a data generation activity occurring over a period of time, said software comprising:

instructions for storing in one or more data stores historical data and future data;

wherein the historical data includes historical exogenous inputs;

wherein the future data includes future exogenous inputs;

instructions for using a dynamic statistical model to receive the historical data and future data that are stored in the one or more data stores;

wherein the dynamic statistical model is to provide forecast scoring based upon the historical exogenous inputs and the future exogenous inputs; and

instructions for using an optimizer having an objective function;

said optimizer iteratively varying the future data, wherein forecasts associated with the varying future data values are generated by the dynamic statistical model for evaluation by the objective function;

wherein the generated forecasts are provided to an external system or user.