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

• US 20070136125A1
• Filed: 12/14/2005
• Published: 06/14/2007
• 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, Kalter, William
• Granted Patent: US 8,484,068 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• 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:

recording product inventory levels at multiple time intervals at the remotely located equipment;

recording equipment operating status at multiple time intervals at the remotely located equipment; and

calculating a consumer demand estimate for the product based on a hierarchy of reliability, quality and quantity of the recorded inventory levels and recorded equipment operating status.

2. The method of claim 1 further comprising using highly reliable, rich historical sales data and equipment operating status to calculate 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:

measuring actual sales of the product at the remotely located equipment for a first time period;

comparing the actual sales of the product for the given time period with projected sales of the product using the estimated consumer demand;

taking corrective action at the remotely located equipment to improve actual sales of the product;

measuring actual sales of the product for a second time period;

comparing the actual sales for the second time period with consumer demand estimate for the second time period; and

taking further corrective action at the remotely located equipment to improve actual sales of the product.

4. The method of claim 1 further comprising censoring 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 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 recording inventory levels for each stock keeping unit at the remotely located equipment.

7. The method of claim 1 further comprising predicting 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 recording inventory levels for different types of the same product at the remotely located equipment.

9. The method of claim 1 further comprising recording each time an equipment problem occurs at the remotely located equipment and revising an associated dispatch schedule in response to equipment problems.

10. The method of claim 1 further comprising comparing 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:

recording service inventory levels at multiple time intervals at the remotely located equipment;

recording equipment operating status at multiple time intervals at the remotely located equipment; and

calculating a consumer demand estimate for the service based on a hierarchy of reliability, quality and quantity of the recorded inventory levels and recorded equipment operating status.

12. The method of claim 11 further comprising using highly reliable rich historical sales data and equipment operating status to calculate 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:

measuring actual sales of the service at the remotely located equipment for a first time period;

comparing the actual sales of the service for the given time period with projected sales of the service using the estimated consumer demand;

taking corrective action at the remotely located equipment to improve actual sales of the service;

measuring actual sales of the service for a second time period;

comparing the actual sales for the second time period with consumer demand estimate for the second time period; and

taking further corrective action at the remotely located equipment to improve actual sales of the service.

14. The method of claim 11 further comprising censoring 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 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 recording inventory levels of materials required to perform each service at the remotely located equipment.

17. The method of claim 11 further comprising predicting 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 recording inventory of materials required to perform for different types of the same service at the remotely located equipment.

19. The method of claim 11 further comprising recording each time an equipment problem occurs at the remotely located equipment and revising an associated dispatch schedule in response to equipment problems.

20. The method of claim 11 further comprising comparing 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 at remotely located equipment and calculating a consumer demand estimate for at least one product sold at the remotely located equipment comprising:

the remotely located equipment operable to receive a request for information from a network operations center;

an external network for communicating information between the network operations center and the remotely located equipment;

a data block having at least one set of product sales records and at least one set of equipment operating status records stored at the remotely located equipment;

the remotely located equipment operable to communicate the product sales records and the equipment operating status records to the network operations center using the external network;

the network operations center operable to store product sales records and equipment operating status records;

the network operations center operable to analyze product sales records and equipment operating status records; and

a predictive algorithm at the network operations center operable to calculate a consumer demand estimate for each product sold at the remotely located equipment based on a hierarchy of reliability, quality and quantity of the 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 the data with the network operations center.

23. The system of claim 21 further comprising the predictive algorithm 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 further comprising a dispatch algorithm 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 at remotely located equipment and calculating a consumer demand estimate for at least one service provided at the remotely located equipment comprising:

the remotely located equipment operable to receive a request for information from a network operations center;

an external network for communicating information between the network operations center and the remotely located equipment;

a data block having at least one set of service sales records and at least one set of equipment operating status records stored at the remotely located equipment;

the remotely located equipment operable to communicate the service sales records and the equipment operating status records to the network operations center using the external network;

the network operations center operable to store service sales records and equipment operating status records;

the network operations center operable to analyze product sales records and equipment operating status records; and

a predictive algorithm at the network operations center operable to calculate a consumer demand estimate for each service sold at the remotely located equipment based on a hierarchy of reliability, quality and quantity of the 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 the data with the network operations center.

27. The system of claim 25 further comprising the predictive algorithm operable to calculate future service sales, future service inventory and predicted lost service sales based on the calculated consumer demand estimate.

28. The system of claim 25 further comprising a dispatch algorithm 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.