Method and System for Evaluating Consumer Demand for Multiple Products and Services at Remotely Located Equipment

• US 20080140515A1
• Filed: 02/21/2008
• Published: 06/12/2008
• Est. Priority Date: 12/14/2005
• Status: Abandoned Application

• Current Assignee: Crane Merchandising Systems Incorporated (Crane Company)
• Original Assignee: Crane Merchandising Systems Incorporated (Crane Company)
• Inventors: Godwin, Bryan W.
• Application Number:
  US12/035,074
• Publication Number:
  US 20080140515A1
• 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 10/06314 Calendaring for a resource
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/1093 Calendar-based scheduling for persons or groups
• 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: G06Q 30/0205 Location or geographical consideration
• 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 at least one of;

the occurrence of one or more events at the remotely located equipment;

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

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 at least one of the recorded inventory levels, recorded equipment operating status, and recorded occurrences of one or more events.

2. The method of claim 1, wherein recording the occurrence of one or more events comprises recording the occurrence of one or more events communicated via a multi-drop bus (MDB).

3. The method of claim 2, wherein recording the occurrence of one or more events comprises recording the occurrence of events associated with at least one of a cashless reader, bill validator, and coin mechanism.

4. The method of claim 1 further comprising:

determining actual sales of one or more products at the remotely located equipment for a first time period based at least on the recorded occurrences of one or more events;

comparing the actual sales of the one or more products for the given time period with projected sales of the one or more products using the estimated consumer demand;

taking corrective action at the remotely located equipment to improve actual sales of the one or more products;

determining actual sales of the one or more products for a second time period based at least on the recorded occurrences of one or more events;

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 one or more products.

5. 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.

6. 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.

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

8. 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.

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

10. 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.

11. 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.

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

recording at least one of;

the occurrence of one or more events at the remotely located equipment;

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

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 at least one of the recorded inventory levels, recorded equipment operating status, and recorded occurrences of one or more events.

13. The method of claim 12, wherein recording the occurrence of one or more events comprises recording the occurrence of one or more events communicated via a multi-drop bus (MDB).

14. The method of claim 13, wherein recording the occurrence of one or more events comprises recording the occurrence of events associated with at least one of a cashless reader, bill validator, and coin mechanism.

15. The method of claim 12, further 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, recorded equipment operating status, and recorded occurrences of one or more events.

16. The method of claim 12 further comprising:

determining actual sales of the service at the remotely located equipment for a first time period based at least on the recorded occurrences of one or more events;

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;

determining actual sales of the service for a second time period based at least on the recorded occurrences of one or more events;

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.

17. The method of claim 12 further comprising censoring time periods from calculation of the consumer demand estimate when the remotely located equipment is not operating satisfactorily.

18. The method of claim 12 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.

19. The method of claim 12 further comprising recording inventory levels of materials required to perform each service at the remotely located equipment.

20. The method of claim 12 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.

21. The method of claim 12 further comprising recording inventory of materials required to perform for different types of the same service at the remotely located equipment.

22. The method of claim 12 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.

23. The method of claim 12 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.

24. 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 stored at the remotely located equipment and having at least one of;

a set of product sales records, a set of equipment operating status records and a set of event occurrence records;

the remotely located equipment operable to communicate the data block to the network operations center using the external network;

the network operations center operable to store the data block;

the network operations center operable to analyze the data block; 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 at least one of the product sales records, the equipment operating status records, and the event occurrence records.

25. The system of claim 24, wherein the event occurrence records include a record of at least one event occurring on a multi-drop (MDB) bus.

26. The system of claim 25, wherein the event occurrence records include a record of at least one event associated with at least one of a cashless reader, bill validator, and coin mechanism.

27. The system of claim 24 further comprising a handheld device operable to request data from the remotely located equipment and to communicate the data with the network operations center.

28. The system of claim 24 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.

29. The system of claim 24 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.

30. 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 stored at the remotely located equipment and having at least one of;

a set of service sales records, a set of equipment operating status records and a set of event occurrence records;

the remotely located equipment operable to communicate the data block to the network operations center using the external network;

the network operations center operable to store the data block;

the network operations center operable to analyze the data block; 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 at least one of the service sales records, the equipment operating status records, and the event occurrence records.

31. The system of claim 30, wherein the event occurrence records include a record of at least one event occurring on a multi-drop (MDB) bus.

32. The system of claim 31, wherein the event occurrence records include a record of at least one event associated with at least one of a cashless reader, bill validator, and coin mechanism.

33. The system of claim 30 further comprising a handheld device operable to request data from the remotely located equipment and to communicate the data with the network operations center.

34. The system of claim 30 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.

35. The system of claim 30 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.