System and method for managing and evaluating network commodities purchasing

• US 8,321,317 B2
• Filed: 05/18/2012
• Issued: 11/27/2012
• Est. Priority Date: 06/28/2000
• Status: Expired due to Fees

• Current Assignee: Buymetrics Incorporated
• Original Assignee: Buymetrics Incorporated
• Inventors: Hansen, Valerie
• Primary Examiner(s): Niquette, Robert
• Application Number:
  US13/475,900
• Publication Number:
  US 20120233056A1
• Time in Patent Office: 193 Days
• Field of Search: None
• US Class Current: 705/35
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 7/08 Sorting, i.e. grouping record carriers in numerical or other ordered sequence according to the classification of at least some of the information they carry by merging two or more sets of carriers in ordered sequence G06F7/16
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 20/201 Price look-up processing, e.g. updating
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 30/04 Billing or invoicing
• CPC Class Codes: G06Q 30/0603 Catalogue ordering
• CPC Class Codes: G06Q 30/0611 Request for offers or quotes
• CPC Class Codes: G06Q 30/0623 Item investigation
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/06 : Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 : Insurance
• CPC Class Codes: G06Q 40/12 : Accounting
• CPC Class Codes: G06Q 50/16 : Real estate
• CPC Class Codes: G06Q 50/188 : Electronic negotiation

Abstract

One or more price metrics are generated by retrieving, from a database, one or more price data sets representing a specified time period. Each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item, and is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items. In at least one embodiment, a combined item price total is divided by a combined item unit total to generate a metric price per unit for each item in the product specification data set. In another embodiment, a summed individual metric price per unit is divided by the number of individual metric prices to generate an overall metric price per unit for each item in the product specification data set.

Claims

1. A method of generating price metrics, comprising:

under control of instructions that are executed by one or more computing devices;

retrieving, from a database containing price data sets previously exchanged between buyers and sellers, one or more price data sets representing a specified time period, wherein each of the retrieved price data sets is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items, and wherein each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item;

for each responsive item in the retrieved price data sets, determining a total item price based on the quoted cost for the item in the respective price data set;

summing the total item price per item across the retrieved price data sets to produce a combined item price total;

for each responsive item in the retrieved price data sets, verifying the selling unit of measure is as specified for the corresponding item in the product specification data set, and if not, mathematically converting the selling unit of measure to the specified unit of measure;

summing the units of measure per item across the retrieved price data sets to produce a combined item unit total; and

dividing the combined item price total by the combined item unit total, thereby generating a metric price per unit for the specified time period for each item in the product specification data set.

2. The method of claim 1, wherein the parameter value pertains to at least one of grade, species, quantity, size, type, assembly, list or tally, method of delivery, delivery date, and location.

3. The method of claim 2, wherein the delivery date is one of a contemporaneous on-or-before delivery date or a future delivery date associated with a forward price.

4. The method of claim 2, further comprising:

retrieving a plurality of price data sets, wherein the parameter values in the price data sets vary by location of the items in the price data sets;

calculating an adjustment value for each location that adjusts the metric price per unit for each item and thereby minimizes the absolute value difference between the metric price per unit for that item and an average of the metric price per unit of all items for the specified time period; and

applying, for each item, the calculated adjustment value to each metric price per unit to produce a location-adjusted metric price per unit.

5. The method of claim 4, wherein the adjustment value is calculated to minimize the square of the difference between the metric price per unit for that item and the average of the metric price per unit of all items for the specified time period.

6. The method of claim 1, wherein the metric price per unit for the specified time period for each item in the product specification data set, along with corresponding metric price per unit values from one or more earlier time periods, are processed though a mathematical smoothing algorithm to produce a smoothed metric price per unit data series.

7. The method of claim 1, wherein the metric price per unit for the specified time period for each item in the product specification data set is divided by the metric price per unit for a predefined base time period, thereby producing a metric index value relative to the base time period.

8. The method of claim 1, wherein the metric price per unit of an item in the product specification data set is divided by the metric price per unit of another item over the specified time period, thereby producing a metric index value of the item relative to another item.

9. The method of claim 1, wherein one or more retrieved price data sets are excluded from processing based on validation rules that identify price data sets failing to meet a predetermined statistical criterion.

10. The method of claim 9, wherein the statistical criterion relates to a number or frequency of price data sets that are responsive to the product specification data set.

11. The method of claim 9, wherein the statistical criterion relates to a total volume per item unit of measure of price data sets that are responsive to the product specifications data set.

12. The method of claim 9, wherein the statistical criterion relates to a type of price data set, including RFQ/market-shop, catalog/pre-negotiated program, and unsolicited market offers.

13. The method of claim 1, wherein the retrieved price data sets are limited to price data sets that resulted in a purchase.

14. The method of claim 1, wherein the product specification data set contains a combined set of component items representing a bundled product, a list, a tally, or assembly, wherein the method further comprises:

pricing the component items as discrete product specification data sets using price values obtained from price data sets retrieved from the database, wherein the retrieved price data sets are responsive to the discrete product specification data sets and the specified time period;

extending the metric price per unit generated for each component item to produce an extended item price; and

summing the extended item prices to create a combined metric price.

15. The method of claim 1, further comprising:

receiving a plurality of product specification data sets; and

combining the plurality of product specification data sets to create a combined product specification data set,

wherein the one or more retrieved price data sets are responsive to the combined product specification data set.

16. The method of claim 1, wherein one or more of the retrieved price data sets includes an item having an alternate or adjusted parameter value that is different than the parameter value of the same item in the product specification data set.

17. The method of claim 1, further comprising generating an output that reports at least one metric price per unit for an item to one or more recipients.

18. The method of claim 17, wherein the output further reports information regarding the retrieved price data sets in which the retrieved price data sets are ranked or categorized by quartile of all retrieved price data sets over the specified time period.

19. The method of claim 17, wherein the output further reports a price per unit indicative of the price per unit of the latest responsive price data set within the specified time period.

20. The method of claim 17, wherein the output further reports a price per unit indicative of the lowest price per unit and/or the highest price per unit in the retrieved price data sets within the specified time period.

21. The method of claim 17, wherein the product specification data set is pre-configured, and wherein an item-specific metric price per unit is automatically generated at a pre-configured time interval and output to the one or more recipients.

22. The method of claim 17, further comprising associating a link with a reported metric price per unit that enables the one or more recipients to view data values used to calculate the reported metric price per unit.

23. The method of claim 1, wherein the method steps are repeated using the same product specification data set for a different specified time period.

24. The method of claim 23, further comprising comparing a resulting metric price per unit of one time period to a resulting metric price per unit of another time period.

25. The method of claim 24, wherein the difference is expressed as a ratio or index.

26. The method of claim 24, wherein the comparing comprises dividing the metric price per unit of a latest specified time period by the metric price per unit of an earlier time period.

27. The method of claim 1, wherein the retrieved price data sets are responsive to product specification data sets that were generated by a predetermined buyer or group of buyers.

28. The method of claim 1, wherein the retrieved price data sets include price data sets that were generated by a predetermined seller or group of sellers.

29. The method of claim 1, wherein metric data is obtained from at least one external source for the items in the product specification data set, wherein the metric data for each time includes a price per unit that is indicative of a market price for the item, and wherein the method further comprises generating a price total for each item and summing all item price totals, thereby generating a combined metric price for the product specification data set.

30. The method of claim 29, further comprising generating an output to one or more recipients that reports metric price per unit values based on data from the external source and from the retrieved price data sets.

31. The method of claims 30, further comprising associating a link with the reported metric price per unit values that enables the one or more recipients to view data values used to calculate the reported metric price per unit values.

32. A computer-readable storage medium having executable instructions stored thereon, wherein the instructions, in response to execution by one or more computing devices, cause the one or more computing devices to:

retrieve, from a database containing price data sets previously exchanged between buyers and sellers, one or more price data sets representing a specified time period, wherein each of the retrieved price data sets is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items, and wherein each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item;

for each responsive item in the retrieved price data sets, determine a total item price based on the quoted cost for the item in the respective price data set;

sum the total item price per item across the retrieved price data sets to produce a combined item price total;

for each responsive item in the retrieved price data sets, verify the selling unit of measure is as specified for the corresponding item in the product specification data set, and if not, mathematically convert the selling unit of measure to the specified unit of measure;

sum the units of measure per item across the retrieved price data sets to produce a combined item unit total; and

divide the combined item price total by the combined item unit total to thereby generate a metric price per unit for the specified time period for each item in the product specification data set.

33. A method of generating price metrics, comprising:

under control of instructions that are executed by one or more computing devices;

specifying a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items;

retrieving, from a database containing price data sets previously exchanged between buyers and sellers, one or more price data sets representing a specified time period, wherein each of the retrieved price data sets is responsive to the product specification data set and includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item;

for each responsive item in the retrieved price data sets;

determining a total item price based on the quoted cost for the item;

verifying the selling unit of measure is as specified for the corresponding item in the product specification data set, and if not, mathematically convert the selling unit of measure to the specified unit of measure; and

dividing the total item price by the selling unit of measure, thereby generating an individual metric price per unit for the item;

summing the individual metric price per unit for the item across the retrieved price data sets; and

dividing the summed individual metric price per unit by the number of individual metric prices, thereby generating an overall metric price per unit for the specified time period for each item in the product specification data set.

34. A computer-readable storage medium having executable instructions stored thereon, wherein the instructions, in response to execution by one or more computing devices, cause the one or more computing devices to:

retrieve, from a database containing price data sets previously exchanged between buyers and sellers, one or more price data sets representing a specified time period, wherein each of the retrieved price data sets is responsive to a product specification data set that includes at least one parameter value and a unit of measure for each of one or more items, and wherein each of the retrieved price data sets includes at least a parameter value, a quoted cost, and a selling unit of measure for at least one item;

for each responsive item in the retrieved price data sets;

determine a total item price based on the quoted cost for the item;

verify the selling unit of measure is as specified for the corresponding item in the product specification data set, and if not, mathematically convert the selling unit of measure to the specified unit of measure; and

divide the total item price by the selling unit of measure to thereby generate an individual metric price per unit for the item;

sum the individual metric price per unit for the item across the retrieved price data sets; and

divide the summed individual metric price per unit by the number of individual metric prices to thereby generate an overall metric price per unit for the specified time period for each item in the product specification data set.