Intelligent procurement agent

• US 20030149578A1
• Filed: 05/31/2002
• Published: 08/07/2003
• Est. Priority Date: 06/01/2001
• Status: Abandoned Application

• Current Assignee: Vientity Private Limited
• Original Assignee: Vientity Private Limited
• Inventors: Wong, Yek-Meng
• Application Number:
  US10/157,989
• Publication Number:
  US 20030149578A1
• Time in Patent Office: Days
• US Class Current: 705/1
• 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 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

A system for managing a supply of a good based on a request for the good includes a decision support module that evaluates the request against a plurality of indicators. The decision support system also determines whether the request involves an exception in accordance with exception data. The system further includes an execution module that receives the determination from the decision support module, triggers an action that is corrective and generates an interactive output. The exception is incorporated into the exception data if the exception is of a new type, and the exception data is modified if the exception is not of the new type and has changed, to dynamically adjust the at least one of the indicators in real-time. As a result, the exception is processed and corrected to prevent interruptions in the supply chain.

Claims

1. A system for managing a supply of a good based on a request for said good, comprising:

a decision support module that evaluates said request against a plurality of indicators and determines whether said request involves an exception that is indicative of a procurement problem in accordance with exception data; and

an execution module that, if said request involves said exception, receives said determination from said decision support module, triggers an action that is configured to correct said exception and generates an interactive output to an external entity, wherein said exception is incorporated into said exception data if said exception is of a new type, and said exception data is modified if said exception is not of said new type and has changed, to adjust said exception data in real-time to incorporate said exception.

2. The system of claim 1, said decision support module comprising:

an agent controller that receives said request and generates an output that is sent to a data module that stores first, second and third types of data comprising raw data, processed data and said exception data, respectively;

a categorization manager that retrieves said first type of data from said data module and categorizes said good in accordance with at least one of said indicators that comprise at least one of a plurality of procurement rules, to generate a categorization output that identifies a category of said exception based on said good; and

a session manager that receives said categorization output from said categorization manager and said second and third data types of data, and if said exception is of said new type, identifies said exception category for addition to said third data of said data module, wherein said session manager generates a first output and a second output.

3. The system of claim 2, said execution module comprising:

an action manager that, in response to said first output of said session manager, receives said third data and determines, in accordance with said plurality of procurement rules, said third data and said exception category, an action to be taken;

an auto trigger manager that receives said second and third types of data, activates said action and generates said interactive output;

an implication manager that determines an implication of said action performed in response to said exception, in accordance with a subset of said procurement rules that define at least one tolerance band specific to said execution category, and generates an output indicative of whether said message is within said at least one tolerance band;

an auto close manager that monitors said action in relation to said exception and in accordance with said output of said implication manager, determines whether a resolution action is required, and outputs an auto close message; and

a resolution manager that receives said auto close message and indicates one of;

(a) automatic management resolution, (b) manual management resolution and (c) automatic management non-resolution of said exception, wherein said data module is updated in accordance with said automatic management resolution of said exception, and said action manager is reactivated for additional processing when said automatic management non-resolution or a manual management non-resolution occurs.

4. The system of claim 3, wherein said session manager receives an input from said action library that comprises an identified exception and a corrective action, and identifies said corrective action for storage in said data module.

5. The system of claim 1, wherein said request comprises an initiation signal from an external source, and wherein said interactive output is transmitted to a relevant entity and is indicative of said corrective action.

6. The system of claim 1, wherein said at least one of said indicators can be modified based on at least one of a category of said good and at least one an external factor.

7. The system of claim 1, wherein if said exception is in said exception data, said at least one corrective action is taken immediately.

8. The system of claim 1, wherein said plurality of indicators can be reassessed based on a response from said external entity.

9. The system of claim 1, wherein a plurality of indicators are applied in said decision support module across a plurality of time periods to perform said evaluation.

10. The system of claim 9, wherein said time periods comprise past, present and future time periods.

11. The system of claim 1, wherein said evaluation performed by said decision support module has qualitative and quantitative components.

12. The system of claim 1, said interactive output comprising at least one of a supplier message, a message activating an online auction directly in an external B2B portal and a message launching a new transaction such as purchase order directly in an Enterprise Resource Planning (ERP) system.

13. The system of claim 11, wherein said qualitative component comprises at least one of:

(a) a historical support level of a supplier;

(b) market supply conditions;

(c) a result of an analysis of relative buyer power and seller power, and (d) an analysis of the relationship between individuals in at least one of said buying organization and said selling organization.

14. The system of claim 1, wherein said plurality of indicators are used to categorize a procurement environment, analyze relevant conditions and assign risk.

15. The system of claim 14, wherein said assigned risk is handled by selecting said action by evaluating said indicators based on past, current and future time period analysis.

16. The system of claim 1, wherein said exception comprises at least one of excess supply, poor responses, inaccurate pricing, shortage of supply and shortage due to a quality failure.

17. The system of claim 1, wherein said corrective action is performed one of sequentially and simultaneously.

18. The system of claim 3, wherein after said request, said agent controller loads said procurement rules, initializes said categorization manager and said session manager, and calculates agent-specific key performance indicators (KPIs), and

after said determination that said request is said exception, initializes said action manager, and prevents reporting of said exception if said action manager indicates that no action corresponds to said exception.

19. The system of claim 18, wherein said categorization manager applies said KPIs to generate said categorization.

20. The system of claim 3, wherein said session manager monitors said request for relevance and consistency when said request is not of said new type.

21. The system of claim 3, further comprising an action library that selects said action based on requests from said action manager and invokes said selected action based on a request from said auto trigger manager.

22. The system of claim 3, wherein said implications comprise cost, availability, responsiveness and quality.

23. The system of claim 3, wherein said business rules are classified based on at least one of a term, a fact, a mandatory constraint, an action enabler, a computation and an inference, to provide an intelligent decision system for said system.

24. The system of claim 3, wherein said exception data comprises (a) extracted raw data related to external supply chain information, (b) a processed version of said raw data as processed by said categorization manager, and (c) exception data generated by said resolution manager.

25. The system of claim 1, further comprising:

an assurance of supply (AOS) agent that resolves supply problems;

a response agent that improves flexibility and supply of a back-end supply chain;

a cost agent that ensures proper pricing of purchases and manages delivery of reduction objectives;

a quality agent that generates an alert replenishes supply when a prescribed lower quality threshold has been reached; and

a session agent that responds to a response from interacting parties based on said action when said exception is being processed by said system, wherein a self-learning agent correlates statistical data with a plurality of business rules to refine said at least one indicator in accordance with a change in said exception.

26. The system of claim 3, wherein said action comprises one of a primary action that affects supply quantity, and a secondary action that does not directly impact supply quantity.

27. The system of claim 3, wherein said action comprises integrating at least one of a sale and a purchase of said good in a business to business (B2B) portal.

28. The system of claim 3, wherein said interactive output is channeled through an application interface module to deliver at least one transactional output.

29. The system of claim 28, wherein said at least one transaction output comprises a post B2B purchase request.

30. The system of claim 5:

wherein said initiation signal is raw data and said external source is an Enterprise Resource Planning (ERP) system.

101. The system of claim 1, further comprising a message formatting component configured to map actions generated with said interactive output that comprises a B2B compliant process message.

102. The system of claim 101, further comprising a listener that enables the system to translate and interpret an incoming message.

31. A method for managing a supply of a good based on a request for said good, comprising:

(a) evaluating said request against a plurality of indicators and determining whether said request involves an exception, said exception being indicative of a procurement problem, in accordance with exception data, in a decision support module;

(b) if said request involves an exception, receiving said determination from said decision support module, triggering an action that is configured to resolve that exception, and generating an interactive output to an external entity, in an execution module; and

(c) incorporating said exception into said exception data if said exception is of a new type and modifying said exception data if said exception is not of said new type and has changed, to adjust said exception data in real-time.

32. The method of claim 31, said step (a) comprising:

(d) receiving said request in an agent controller, and generating an output that is sent to a data module that stores first, second and third types of data;

(e) receiving said first type of data from said data module and categorizing said good, in a categorization manager, in accordance with at least one of said indicators that comprise a plurality of procurement rules, to generate a categorization output that identifies said good based on a category of exception; and

(f) receiving said categorization output, in a session manager, from said categorization manager and said second and third types of data, and determining whether said exception is of said new type, and if said exception is of said new type, identifying said exception category for addition to said data module, wherein said session manager generates a first output and a second output.

33. The method of claim 32, said steps (b) and (c) comprising:

(g) in response to said first output of said session manager, receiving said third data output in an action manager, and determining, in accordance with said plurality of procurement rules and said exception category, an action to be taken;

(h) receiving said second and third types of data in an auto trigger manager, and activating said action and generating said interactive output;

(i) determining the implications of said action performed in response to said exception in an implication manager, in accordance with a subset of said procurement rules that define at least one tolerance band specific to said execution category, and generating an output indicative of whether said message is within said at least one tolerance band;

(j) in an auto close manager, monitoring said action in relation to said exception, determining whether a resolution action is required, and outputting an auto close message; and

(k) receiving said auto close message in a resolution manager, and indicating one of automatic management resolution, manual management resolution and automatic management non-resolution of said exception, wherein said data module is updated in accordance with said automatic management resolution of said exception, and said action manager is reactivated for additional processing when said automatic management non-resolution or a manual management non-resolution occurs.

34. The method of claim 33, further comprising said session manager receiving an input from said action library, said input including an identified exception and a corrective action, and identifying said corrective action for storage in said data module.

35. The method of claim 31, wherein said request is received as an initiation signal received from an external source, and said interactive output, indicative of said corrective action, is transmitted to a relevant entity.

36. The method of claim 31, further comprising modifying said at least one of said indicators based on at least one of a category of said good and at least one an external factor.

37. The method of claim 31, wherein if said exception is in said exception data, said action is taken immediately.

38. The method of claim 31, further comprising reassessing said plurality of indicators based on a response from said external entity.

39. The method of claim 31, further comprising applying said plurality of indicators across a plurality of time periods to perform said steps (b) and (c).

40. The method of claim 31, further comprising:

categorizing a procurement environment in accordance with said plurality of indicators, analyzing relevant conditions and assigning risk, wherein said assigned risk is handled by selecting said action by evaluating said indicators based on past, current and future time period analysis.

41. The method of claim 31, wherein said corrective action is performed one of sequentially and simultaneously.

42. The method of claim 33, wherein after said request, said agent controller loads said procurement rules, initializes said categorization manager and said session manager, and calculates agent-specific key performance indicators (KPIs), and

after said determination that said request is said exception, initializes said action manager, and prevents reporting of said exception if said action manager indicates that no action corresponds to said exception.

43. The method of claim 42, wherein said categorization manager applies said KPIs to generate said categorization.

44. The method of claim 33, wherein said session manager monitors said request for relevance and consistency when said request is not of said new type.

45. The method of claim 33, further comprising selecting said action in an action library based on requests from said action manager, and invoking said selected action based on a request from said auto trigger manager.

46. The method of claim 33, wherein said implications comprise cost, availability, responsiveness and quality.

47. The method of claim 33, wherein said business rules are classified based on at least one of a term, a fact, a mandatory constraint, an action enabler, a computation and an inference, to provide an intelligent decision system for said system.

48. The method of claim 33, wherein said exception data is generated by extracting raw data related to external supply chain information, said categorization manager processing a version of said raw data, and said resolution manager generating exception data.

49. The method of claim 31, further comprising:

(d) resolving supply problems in an assurance of supply (AOS) agent;

(e) improving flexibility and supply of a back-end supply chain by using a response agent;

(f) ensuring proper pricing of purchases and managing delivery of reduction objectives via a cost agent;

(g) in a quality agent, generating an alert replenishes supply when a prescribed lower quality threshold has been reached; and

(h) using a session agent, responding to a response from interacting parties based on said action when said exception is being processed by said system, wherein a self-learning agent correlates statistical data with a plurality of business rules to refine said at least one indicator in accordance with a change in said exception.

50. The method of claim 33, wherein said action comprises one of a primary action that affects supply quantity, and a secondary action that does not directly impact supply quantity.

51. The method of claim 33, wherein said action comprises integrating at least one of a sale and a purchase of said good in a business to business (B2B) portal.

52. The method of claim 33, further comprising channeling said interactive output through an application interface module to deliver at least one transactional output.

53. The method of claim 35, wherein said initiation signal is raw data and said external source is an Enterprise Resource Planning (ERP) system.

54. A computer program product for enabling a computer to operate, and so comprising software instructions for enabling the computer to perform predetermined operations, and a computer readable medium bearing the software instructions, the predetermined operations comprising the steps of:

(a) evaluating said request against a plurality of indicators and determining whether said request involves an exception, said exception being indicative of a procurement problem, in accordance with exception data, in a decision support module;

(b) if said request involves said exception, receiving said determination from said decision support module, triggering an action that is configured to correct said exception, and generating an interactive output to an external entity, in an execution module; and

(c) incorporating said exception into said exception data if said exception is of a new type and modifying said exception data if said exception is not of said new type and has changed, to adjust said exception data in real-time.

55. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, said step (a) comprising:

(d) receiving said request in an agent controller, and generating an output that is sent to a data module that stores first, second and third types of data;

(e) receiving said first type of data from said data module and categorizing said good, in a categorization manager, in accordance with at least one of said indicators that comprise a plurality of procurement rules, to generate a categorization output that identifies said good based on a category of exception; and

(f) receiving said categorization output, in a session manager, from said categorization manager and said second and third data types of data, and determining whether said exception is of said new type, and if said exception is of said new type, identifying said exception category for addition to said data processing subsystem, wherein said session manager generates a first output and a second output.

56. The computer program product of claim 55, said computer readable medium bearing said software instructions to further perform said predetermined operations, said steps (b) and (c) comprising:

(g) in response to said first output of said session manager, receiving said third data output in an action manager, and determining, in accordance with said plurality of procurement rules and said exception category, an action to be taken;

(h) receiving said second and third data types of data in an auto trigger manager, and activating said action and generating said interactive output;

(i) determining the implications of said action performed in response to said exception in an implication manager, in accordance with a subset of said procurement rules that define at least one tolerance band specific to said execution category, and generating an output indicative of whether said message is within said at least one tolerance band;

(j) in an auto close manager, monitoring said action in relation to said exception, determining whether a resolution action is required, and outputting an auto close message; and

(k) receiving said auto close message in a resolution manager, and indicating one of automatic management resolution, manual management resolution and automatic management non-resolution of said exception, wherein said data module is updated in accordance with said automatic management resolution of said exception, and said action manager is reactivated for additional processing when said automatic management non-resolution or a manual management non-resolution occurs.

57. The computer program product of claim 56, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising said session manager receiving an input from said action library, said input including an identified exception and a corrective action, and identifying said corrective action for storage in said data processing subsystem.

58. The computer program product of claim 54, wherein said request is received as an initiation signal received from an external source, and said interactive output, indicative of said corrective action, is transmitted to a relevant entity.

59. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising modifying said at least one of said indicators based on at least one of a category of said good and at least one an external factor.

60. The computer program product of claim 54, wherein if said exception is in said exception data, said action is taken immediately.

61. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising reassessing said plurality of indicators based on a response from said external entity.

62. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising applying said plurality of indicators across a plurality of time periods to perform said steps (b) and (c).

63. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising:

categorizing a procurement environment in accordance with said plurality of indicators, analyzing relevant conditions and assigning risk, wherein said assigned risk is handled by selecting said action by evaluating said indicators based on past, current and future time period analysis.

64. The computer program product of claim 54, wherein said corrective action is performed one of sequentially and simultaneously.

65. The computer program product of claim 56, wherein after said request, said agent controller loads said procurement rules, initializes said categorization manager and said session manager, and calculates agent-specific key performance indicators (KPIs), and

after said determination that said request is said exception, initializes said action manager, and prevents reporting of said exception if said action manager indicates that no action corresponds to said exception.

66. The computer-readable medium of claim 65, wherein said categorization manager applies said KPIs to generate said categorization.

67. The computer program product of claim 56, wherein said session manager monitors said request for relevance and consistency when said request is not of said new type.

68. The computer program product of claim 56, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising selecting said action in an action library based on requests from said action manager, and invoking said selected action based on a request from said auto trigger manager.

69. The computer program product of claim 56, wherein said business rules are classified based on at least one of a term, a fact, a mandatory constraint, an action enabler, a computation and an inference, to provide an intelligent decision system for said system.

70. The computer program product of claim 56, wherein said exception data is generated by extracting raw data related to external supply chain information, said categorization manager processing a version of said raw data, and said resolution manager generating exception data.

71. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising:

(d) resolving supply problems in an assurance of supply (AOS) agent;

(e) improving flexibility and supply of a back-end supply chain by using a response agent;

(f) ensuring proper pricing of purchases and managing delivery of reduction objectives via a cost agent;

(g) in a quality agent, generating an alert replenishes supply when a prescribed lower quality threshold has been reached; and

(h) using a session agent, responding to a response from interacting parties based on said action when said exception is being processed by said system, wherein a self-learning agent correlates statistical data with a plurality of business rules to refine said at least one indicator in accordance with a change in said exception.

72. The computer program product of claim 56, wherein said action comprises one of a primary action that affects supply quantity, and a secondary action that does not directly impact supply quantity.

73. The computer program product of claim 56, wherein said action comprises integrating at least one of a sale and a purchase of said good in a business to business (B2B) portal.

74. The computer program product of claim 54, said computer readable medium bearing said software instructions to further perform said predetermined operations, further comprising channeling said interactive output through an application interface module to deliver at least one transactional output.

75. The computer program product of claim 58, wherein said initiation signal is raw data and said external source is an Enterprise Resource Planning (ERP) system.

76. A system for managing a supply of a good based on a request for said good, comprising:

means for evaluating said request against a plurality of indicators and determining whether said request involves an exception that is indicative of a procurement problem in accordance with exception data; and

means for receiving said determination from said decision support module, triggering an action that is configured to resolve said exception and generating an interactive messaging means to an external entity,

wherein said exception is incorporated into said exception data if said exception is of a new type, and said exception data is modified if said exception is not of said new type and has changed, to adjust said exception data in real-time.

77. The system of claim 76, said means for evaluating comprising:

means for generating an output that is sent to a data processing means for storing first, second and third types of data, in accordance with said request;

means for generating a categorization output that identifies said good based on a category of exception by categorizing said good in accordance with at least one of said indicators that comprise a plurality of procurement rules, and further based on said first type of data received from said data processing means; and

means for determining whether said exception is of said new type, and if said exception is of said new type, identifying said exception category for addition to said data processing means, based on said categorization output received from said means for generating said categorization output and said second and third types of data, wherein said means for determining generates first and second determination result outputs.

78. The system of claim 77, said execution module comprising:

means for generating an action to be taken in response to said first determination result output and said third data output, in accordance with said plurality of procurement rules and said exception category, an action to be taken;

means for generating said interactive messaging means in accordance with said second and third types of data;

means for determining the implications of said action performed in response to said exception, in accordance with a subset of said procurement rules that define at least one tolerance band specific to said execution category, said means for determining said implications generating an output indicative of whether said message is within said at least one tolerance band;

means for monitoring said action in relation to said exception and determining whether a resolution action is required, and outputting an auto close message; and

means for indicating one of;

(a) automatic management resolution, (b) manual management resolution and (c) automatic management non-resolution of said exception event, in accordance with said auto close message, wherein said data processing means is updated in accordance with said automatic management resolution of said exception, and said means for generating said action is reactivated for additional processing when said automatic management non-resolution or a manual management non-resolution occurs.

79. The system of claim 78, wherein said means for determining whether said exception is of said new type receives an input that comprises an identified event and a corrective action, and identifies said corrective action for storage in said data processing subsystem.

80. The system of claim 76, wherein said at least one of said indicators can be modified based on at least one of a category of said good and at least one an external factor.

81. The system of claim 76, wherein if said exception is in said exception data, said at least one corrective action is taken immediately.

82. The system of claim 76, wherein said plurality of indicators can be reassessed based on a response from said external entity.

83. The system of claim 76, wherein a plurality of indicators are applied in said means for evaluating said request across a plurality of time periods to perform said evaluation.

84. The system of claim 76, wherein said evaluation performed by said decision support module has qualitative and quantitative components.

85. The system of claim 84, wherein said qualitative component comprises at least one of:

(a) a historical support level of a supplier;

(b) market supply conditions;

(c) a result of an analysis of relative buyer power and seller power, and (d) an analysis of the relationship between individuals in at least one of said buying organization and said selling organization.

86. The system of claim 76, wherein said plurality of indicators are used to categorize a procurement environment, analyze relevant conditions and assign risk.

87. The system of claim 86, wherein said assigned risk is handled by selecting said action by evaluating said indicators based on past, current and future time period analysis.

88. The system of claim 76, wherein said exception comprises at least one of excess supply, poor responses, inaccurate pricing, shortage of supply and shortage due to a quality failure.

89. The system of claim 76, wherein said corrective action is performed one of sequentially and simultaneously.

90. The system of claim 78, wherein after said request, said means for generating said output loads said procurement rules, initializes said means for generating said categorization output and said means for determining whether said exception is of said new type, and calculates agent-specific key performance indicators (KPIs), and after said determination that said request is said exception, initializes said means for generating said action, and prevents reporting of said exception if said means for generating said action indicates that no action corresponds to said exception.

91. The system of claim 90, wherein said means for generating said categorization output applies said KPIs to generate said categorization.

92. The system of claim 78, wherein said means for determining whether said exception is of said new type monitors said request for relevance and consistency when said request is not of said new type.

93. The system of claim 78, further comprising means for selecting said action based on requests from said means for generating said action, and invoking said selected action based on a request from said means for generating said interactive messaging means.

94. The system of claim 78, wherein said business rules are classified based on at least one of a term, a fact, a mandatory constraint, an action enabler, a computation and an inference, to provide an intelligent decision system for said system.

95. The system of claim 78, wherein said exception data comprises (a) extracted raw data related to external supply chain information, (b) a processed version of said raw data as processed by said means for generating said categorization output, and (c) exception event data generated by said means for indicating.

96. The system of claim 76, further comprising a management means that includes,

means for resolving supply problems;

means for improving flexibility and supply of a back-end supply chain;

means for ensuring proper pricing of purchases and manages delivery of reduction objectives;

means for generating an alert replenishes supply when a prescribed lower quality threshold has been reached; and

means for responding to a response from interacting parties based on said action when said exception is being processed by said system, wherein a self-learning means correlates statistical data with a plurality of business rules to refine said at least one indicator in accordance with a change in said exception.

97. The system of claim 78, wherein said action comprises one of a primary action that affects supply quantity, and a secondary action that does not directly impact supply quantity.

98. The system of claim 78, wherein said action comprises integrating at least one of a sale and a purchase of said good in a business to business (B2B) portal.

99. The system of claim 78, wherein said interactive output is channeled through a means for interfacing with a user to deliver at least one transactional output.

100. The system of claim 99, wherein said at least one transaction output comprises a post B2B purchase request.