Method and system for evaluating consumer demand for multiple products and services at remotely located equipment

• US 8,484,068 B2
• Filed: 12/14/2005
• Issued: 07/09/2013
• Est. Priority Date: 12/14/2005
• Status: Active Grant

• Current Assignee: Crane Payment Innovations, Inc. (Crane Company)
• Original Assignee: Crane Merchandising Systems Incorporated (Crane Company)
• Inventors: Godwin, Bryan W., Kalter, William J.
• Primary Examiner(s): Boyce, Andre
• Assistant Examiner(s): JACKSON, ERNEST ADEYEMI
• Application Number:
  US11/302,759
• Publication Number:
  US 20070136125A1
• Time in Patent Office: 2,764 Days
• Field of Search: 705/10, 705/7.31
• US Class Current: 705/7.31
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06314 Calendaring for a resource
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G07F 9/001 Interfacing with vending machines using mobile or wearable devices
• CPC Class Codes: G07F 9/002 Vending machines being part of a centrally controlled network of vending machines

Abstract

A method and system are provided for estimating consumer demand at remotely located equipment and establishing dispatch schedules for servicing the remotely located equipment. Data from the remotely located equipment may be classified into a hierarchy or various levels of reliability for use in calculating a consumer demand estimate for each product and/or each service available at the remotely located equipment. A full set of sales data for each product or service over multiple time intervals with no equipment problems, no out of stock conditions and no other operating problems may be classified as the highest level of reliability and predictability possible for calculating a consumer demand estimate. The lowest level of data used to calculate a consumer demand estimate may be a historical average of daily sales for all products or services sold over a long period of time at the remotely located equipment.

Claims

1. A method for estimating consumer demand for a product based on sales data for the product at remotely located equipment comprising:

receiving in an application server first inventory level data from the remotely located equipment, wherein the first inventory level data represents product inventory levels in the remotely located equipment, the product inventory levels recorded at multiple time intervals;

receiving in the application server equipment operating status data from the remotely located equipment, wherein the equipment operating status data represents equipment operating status of the remotely located equipment, the equipment operating status recorded at multiple time intervals;

arranging in the application server the received first inventory level data and the received equipment operating status data in associated levels of a data hierarchy of reliability, quality and quantity;

storing in the application server the received first inventory level data and the received equipment operating status data and associated levels of the data hierarchy; and

calculating in the application server a consumer demand estimate for the product based on the levels of the data hierarchy of the stored first inventory level data and the stored equipment operating status data.

2. The method of claim 1 further comprising using highly reliable, rich historical sales data and equipment operating status to calculate in the application server a consumer demand estimate for the product corresponding approximately with a conventional store operating satisfactorily twenty four hours per day with an optimum staff and an optimum inventory of the product for sale at the same location as the remotely located equipment.

3. The method of claim 1 further comprising:

receiving in the application server first actual sales data from the remotely located equipment, wherein the first actual sales data represents actual sales of the product at the remotely located equipment for a first time period;

storing in the application server the received first actual sales data;

comparing in the application server the stored first actual sales data of the product for the first time period with projected sales of the product using the estimated consumer demand;

identifying in the application server from the first comparison a corrective action at the remotely located equipment to improve actual sales of the product;

receiving in the application server second actual sales data from the remotely located equipment, wherein the actual sales data represents actual sales of the product at the remotely located equipment for a second time period;

storing in the application server the received second actual sales data;

comparing in the application server the stored second actual sales data for the second time period with a consumer demand estimate for the second time period; and

the application server identifying from the second comparison a further corrective action at the remotely located equipment to improve actual sales of the product.

4. The method of claim 1 further comprising censoring in the application server time periods from calculation of the consumer demand estimate when the remotely located equipment is not operating satisfactorily.

5. The method of claim 1 further comprising estimating in the application server consumer demand by evaluating product sales for only those time periods when adequate inventory of the product was available at the remotely located equipment and the remotely located equipment was operating satisfactorily.

6. The method of claim 1 further comprising receiving in the application server second inventory level data from the remotely located equipment, wherein the second inventory level data represents inventory levels for each stock keeping unit, the inventory levels recorded at the remotely located equipment.

7. The method of claim 1 further comprising predicting in the application server future sales, future inventory and potential lost sales of the product based on the calculated consumer demand estimates.

8. The method of claim 1 further comprising receiving in the application server third inventory level data from the remotely located equipment, wherein the third inventory level data represents inventory levels for different types of the same product, the inventory levels recorded at the remotely located equipment.

9. The method of claim 1 further comprising:

receiving in the application server equipment problem data, wherein the equipment problem data represents equipment problems occurring at the remotely located equipment recorded at the remotely located equipment;

storing in the application server the received equipment problem data; and

revising in the application server an associated dispatch schedule in response to the stored equipment problem data.

10. The method of claim 1 further comprising comparing in the application server actual product sales at the remotely located equipment with predicted product sales based on the consumer demand estimate to identify mechanical errors and equipment problems at the remotely located equipment which require corrective action.

11. A method for estimating consumer demand for a service based on sales data for the service at remotely located equipment comprising:

receiving in an application server first inventory level data from the remotely located equipment, wherein the first inventory level data represents service inventory levels in the remotely located equipment recorded at multiple time intervals;

receiving in the application server equipment operating status data from the remotely located equipment, wherein the equipment operating status data represents equipment operating status of the remotely located equipment recorded at multiple time intervals;

arranging in the application sever the received first inventory level data and the received equipment operating status data in associated levels of a data hierarchy of reliability, quality and quantity;

storing in the application server the received first inventory level data and the received equipment operating status data and associated levels of the data hierarchy; and

calculating in the application server a consumer demand estimate for the service based on the levels of the data hierarchy of the stored first inventory level data and the stored equipment operating status data.

12. The method of claim 11 further comprising using highly reliable rich historical sales data and equipment operating status to calculate in the application server a consumer demand estimate for the service corresponding approximately with a conventional store operating satisfactorily twenty four hours per day with an optimum staff and an optimum inventory of materials to perform the service for sale at the same location as the remotely located equipment.

13. The method of claim 11 further comprising:

receiving in the application server first actual sales data from the remotely located equipment, wherein the first actual sales data represents actual sales of the service at the remotely located equipment for a first time period;

storing in the application server the received first actual sales data;

comparing in the application server the stored first actual sales data of the service for the first time period with projected sales of the service using the estimated consumer demand;

identifying in the application server from the first comparison a corrective action at the remotely located equipment to improve actual sales of the service;

receiving in the application server second actual sales data from the remotely located equipment, wherein the actual sales data represents actual sales of the service at the remotely located equipment for a second time period;

storing in the application server the received second actual sales data;

comparing in the application server the stored second actual sales data for the second time period with a consumer demand estimate for the second time period; and

the application server identifying from the second comparison a further corrective action at the remotely located equipment to improve actual sales of the service.

14. The method of claim 11 further comprising censoring in the application server time periods from calculation of the consumer demand estimate when the remotely located equipment is not operating satisfactorily.

15. The method of claim 11 further comprising estimating in the application server consumer demand by evaluating service sales for only those time periods when adequate inventory of the service was available at the remotely located equipment and the remotely located equipment was operating satisfactorily.

16. The method of claim 11 further comprising receiving in the application server second inventory level data from the remotely located equipment, wherein the second inventory level data represents inventory levels of materials required to perform each service, the inventory levels recorded at the remotely located equipment.

17. The method of claim 11 further comprising predicting in the application server future sales, future inventory of materials required to provide services and potential lost sales of services based on the calculated consumer demand estimate.

18. The method of claim 11 further comprising receiving in the application server third inventory level data from the remotely located equipment, wherein the third inventory level data represents inventory levels of materials required to perform different types of the same service, the inventory levels recorded at the remotely located equipment.

19. The method of claim 11 further comprising receiving in the application server equipment problem data, wherein the equipment problem data represents equipment problems occurring at the remotely located equipment recorded at the remotely located equipment;

storing in the application server the received equipment problem data; and

revising in the application server an associated dispatch schedule in response to the stored equipment problem data.

20. The method of claim 11 further comprising comparing in the application server actual service sales at the remotely located equipment with predicted service sales based on the consumer demand estimate to identify mechanical errors and equipment problems at the remotely located equipment which require corrective action.

21. A system for acquiring product sales data from remotely located equipment and calculating a consumer demand estimate for at least one product sold at the remotely located equipment, the system comprising:

a network operations center; and

an external network operable to communicate information between the network operations center and the remotely located equipment,

wherein the network operations center is operable to;

send a request for data to the remotely located equipment;

receive product sales records and equipment operating status records from the remotely located equipment;

arrange the product sales records and equipment operating status records in associated levels of a data hierarchy of reliability, quality and quantity;

store the product sales records and equipment operating status records and associated levels of the data hierarchy;

analyze product sales records and equipment operating status records; and

calculate a consumer demand estimate for each product sold at the remotely located equipment based on the levels of the data hierarchy of the stored product sales records and the equipment operating status records.

22. The system of claim 21 further comprising a handheld device operable to request data from the remotely located equipment and to communicate data received from the remotely located equipment to the network operations center.

23. The system of claim 21 wherein the network operations center is further operable to calculate future product sales, future product inventory and predicted lost sales based on the calculated consumer demand estimate.

24. The system of claim 21 wherein the network operations center is further operable to prepare a dispatch schedule for the remotely located equipment based on the predicted future inventory and potential lost sales for the product.

25. A system for acquiring service sales data from remotely located equipment and calculating a consumer demand estimate for at least one service provided at the remotely located equipment, the system comprising:

a network operations center; and

an external network operable to communicate information between the network operations center and the remotely located equipment,

wherein the network operations center is operable to;

send a request for data to the remotely located equipment;

receive service sales records and equipment operating status records from the remotely located equipment;

arrange the service sales records and equipment operating status records in associated levels of a data hierarchy of reliability, quality and quantity;

store the service sales records and equipment operating status records and associated levels of the data hierarchy;

analyze product sales records and equipment operating status records; and

calculate a consumer demand estimate for each service sold at the remotely located equipment based on the levels of the data hierarchy of the stored service sales records and the equipment operating status records.

26. The system of claim 25 further comprising a handheld device operable to request data from the remotely located equipment and to communicate data received from the remotely located equipment to the network operations center.

27. The system of claim 25 wherein the network operations center is further operable to calculate future service sales, fixture service inventory and predicted lost service sales based on the calculated consumer demand estimate.

28. The system of claim 25 wherein the network operations center is further operable to prepare a dispatch schedule for the remotely located equipment based on the predicted future service inventory and potential lost service sales for the product.