Generating an optimized price schedule for a product
Generating a price schedule involves generating a graph ( 50 ) having paths that include states ( 52 ) with values ( 54, 56, 58 ). The graph ( 50 ) is generated by determining the values ( 56, 58 ) of a successor state ( 52 ) from the values ( 56, 58 ) of a predecessor state ( 52 ). An optimal path is selected, and a price schedule is determined from the optimal path. Computing an elasticity curve involves having a demand model, values for demand model, and filter sets that restrict the values. Elasticity curves are determined by filtering the values using filter sets, and calculating the elasticity curve using the demand model. An best-fitting elasticity curve is selected. Adjusting a demand forecast value ( 56 ) includes estimating an inventory and a demand at a number of locations ( 24 ). An expected number of unrealized sales at each location ( 24 ) is calculated. An sales forecast value ( 56 ) is determined according to the expected number.
1 - 26 . (canceled)
27 . A method for computing an elasticity curve, comprising:
selecting a demand model having a plurality of variables;
receiving a plurality of values for each variable;
defining a plurality of filter sets, each filter set operable to restrict the values for at least one variable;
determining an elasticity curve for each filter set by:
filtering the values for at least one variable using the filter set; and
calculating the elasticity curve from the filtered values by performing a regression analysis using the demand model as a regression equation;
measuring a quality value for each elasticity curve; and
selecting an optimal elasticity curve according to the quality values.
28 . The method of claim 27 , wherein the variables comprise:
a dependent variable comprising a demand variable; and
a plurality of independent variables comprising a price variable and time variables.
29 . The method of claim 27 , wherein:
the variables comprise a dependent variable and a plurality of independent variables; and
determining the elasticity curve comprises using the demand model as a regression equation of the dependent variable over the independent variables.
30 . The method of claim 27 , wherein:
the values are associated with a plurality of products; and
determining the elasticity curve for each filter set comprises:
determining an elasticity curve for each product using the values associated with the product;
measuring a quality value for each elasticity curve;
determining an unsatisfactory elasticity curve according to the quality values; and
eliminating the values associated with the unsatisfactory elasticity curve.
31 . The method of claim 27 , wherein:
the values are associated with a plurality of products; and
determining the elasticity curve for each filter set comprises:
determining an elasticity curve for each product using the values associated with the product;
calculating an elasticity value from each elasticity curve; determining an unsatisfactory elasticity value; and
eliminating the values associated with the unsatisfactory elasticity value.
32 . The method of claim 27 , wherein the variables comprise an independent variable comprising a promotional variable.
33 . The method of claim 27 , wherein the variables comprise an independent variable comprising a seasonality index variable.
34 . A system for computing an elasticity curve, comprising:
a database operable to store a demand model having a plurality of variables, a plurality of values for each variable, and a plurality of filter sets, each filter set operable to restrict the values for at least one variable; and
a server coupled to the database and operable to:
determine an elasticity curve for each filter set by filtering the values for at least one variable using the filter set, and calculating the elasticity curve from the filtered values by performing a regression analysis using the demand model as a regression equation;
measure a quality value for each elasticity curve; and
select an optimal elasticity curve according to the quality values.
35 . The system of claim 34 , wherein the variables comprise:
a dependent variable comprising a demand variable; and
a plurality of independent variables comprising a price variable and a time variable.
36 . The system of claim 34 , wherein:
the variables comprise a dependent variable and a plurality of independent variables; and
the server is operable to perform a regression analysis using the demand model as a regression equation of the dependent variable over the independent variables.
37 . The system of claim 34 , wherein:
the values are associated with a plurality of products; and
the server is operable to determine the elasticity curve for each filter set by:
determining an elasticity curve for each product using the values associated with the product;
measuring a quality value for each elasticity curve;
determining an unsatisfactory elasticity curve according to the quality values; and
eliminating the values associated with the unsatisfactory elasticity curve.
38 . The system of claim 34 , wherein:
the values are associated with a plurality of products; and
the server is operable to determine the elasticity curve for each filter set by:
determining an elasticity curve for each product using the values associated with the product;
calculating an elasticity value from each elasticity curve; determining an unsatisfactory elasticity value; and eliminating the values associated with the unsatisfactory elasticity value.
39 . The system of claim 34 , wherein the variables comprise an independent variable comprising a promotional variable.
40 . The system of claim 34 , wherein the variables comprise an independent variable comprising a seasonality index variable.
41 . Logic for computing an elasticity curve, the logic encoded in media and when executed operable to:
select a demand model having a plurality of variables;
receive a plurality of values for each variable;
define a plurality of filter sets, each filter set operable to restrict the values for at least one variable;
determine an elasticity curve for each filter set by:
filtering the values for at least one variable using the filter set; and
calculating the elasticity curve from the filtered values by performing a regression analysis using the demand model as a regression equation; measure a quality value for each elasticity curve; and
select an optimal elasticity curve according to the quality values.
42 . The logic of claim 41 , wherein the variables comprise:
a dependent variable comprising a demand variable; and
a plurality of independent variables comprising a price variable and a time variable.
43 . The logic of claim 41 , wherein:
the variables comprise a dependent variable and a plurality of independent variables; and
the logic is further operable to use the demand model as a regression equation of the dependent variable over the independent variables.
44 . The logic of claim 41 , wherein:
the values are associated with a plurality of products; and
the logic is further operable to determine the elasticity curve for each filter set by:
determining an elasticity curve for each product using the values associated with the product;
measuring a quality value for each elasticity curve;
determining an unsatisfactory elasticity curve according to the quality values; and
eliminating the values associated with the unsatisfactory elasticity curve.
45 . The logic of claim 41 , wherein:
the values are associated with a plurality of products; and
the logic is further operable to determine the elasticity curve for each filter set by:
determining an elasticity curve for each product using the values associated with the product;
calculating an elasticity value from each elasticity curve;
determining an unsatisfactory elasticity value; and
eliminating the values associated with the unsatisfactory elasticity value.
46 . The logic of claim 41 , wherein the variables comprise an independent variable comprising a promotional variable.
47 - 71 . (canceled)