Managing an inventory of service parts

• US 8,660,915 B2
• Filed: 07/16/2012
• Issued: 02/25/2014
• Est. Priority Date: 06/07/2004
• Status: Active Grant

• Current Assignee: Accenture Global Services Limited (Accenture PLC)
• Original Assignee: Accenture Global Services Limited (Accenture PLC)
• Inventors: Giacobbe, Robert A., Derrick, R. Douglas
• Primary Examiner(s): ADE, OGER GARCIA
• Application Number:
  US13/550,372
• Publication Number:
  US 20120323744A1
• Time in Patent Office: 589 Days
• Field of Search: 705/28
• US Class Current: 705/28
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

An inventory of service parts may be managed by assessing a company'"'"'s capability, optimizing the inventory and implementing a management program based on the assessment and optimization. Optimizing target stock levels for the inventory of parts may be accomplished by calculating an inventory baseline for understanding information about the currently held inventory; developing a service strategy for a set of segments; quantifying a service level for each of the segments; analyzing the segments and their service levels for identifying at least one logistically distinct business; assigning each of the segments to a “best-fit” planning model for indicating each segment'"'"'s deployment, replenishment, forecasting and review characteristics; identifying a probability distribution function for estimating a demand process of each of the segments; and calculating a target stock level for each segment.

Claims

1. A method implemented using a computer for generating a sampling, comprising:

determining a total population of an inventory of members;

segmenting the total population into a plurality of segments;

determining a sampling error for use in analyzing the plurality of segments;

calculating, using the computer, a sample size for each of the plurality of segments based at least in part on the sampling error;

using a criterion measure for ranking members of each of the plurality of segments;

generating, using the computer, a set of random numbers for at least one of the plurality of segments, wherein the set is equal to the sample size for the at least one segment; and

extracting, using the computer, from the at least one segment the members whose rankings match the set of random numbers.

2. The method of claim 1, wherein the segmenting is based on supplier lead time associated with a member of the inventory.

3. The method of claim 1, wherein the segmenting is based on supplier delivery performance associated with a member of the inventory.

4. The method of claim 1, wherein the segmenting is based on a cost associated with a member of the inventory.

5. The method of claim 1, wherein the plurality of segments represents a plurality of logistically distinct businesses.

6. The method of claim 5, wherein the plurality of logistically distinct businesses represents a plurality of different customer ordering profiles.

7. The method of claim 5, wherein the plurality of logistically distinct businesses represents a plurality of different supply chain flow patterns of members of the inventory.

8. The method of claim 1, wherein the criterion measure is based on a cost associated with a member of the inventory.

9. The method of claim 1, wherein the criterion measure is based on an item name associated with a member of the inventory.

10. The method of claim 1, wherein calculating a sample size for each of the plurality of segments is based on the formula:

n_x=N_x/1+N_x(e)²

where n_x represents the sample size, N_x represents the number of members in the total population, and e represents the sampling error.

11. A computer-based system for generating a sampling, the system comprising at least one processor and at least one nontransitory storage medium that stores a plurality of instructions, the plurality of instructions being executable by the at least one processor for:

determining a total population of an inventory of members;

segmenting the total population into a plurality of segments;

determining a sampling error for use in analyzing the plurality of segments;

calculating a sample size for each of the plurality of segments based at least in part on the sampling error;

using a criterion measure for ranking members of each of the plurality of segments;

generating a set of random numbers for at least one of the plurality of segments, wherein the set is equal to the sample size for the at least one segment; and

extracting from the at least one segment the members whose rankings match the set of random numbers.

12. The system of claim 11, wherein the segmenting is based on supplier lead time associated with a member of the inventory.

13. The system of claim 11, wherein the segmenting is based on supplier delivery performance associated with a member of the inventory.

14. The system of claim 11, wherein the segmenting is based on a cost associated with a member of the inventory.

15. The system of claim 11, wherein the plurality of segments represents a plurality of logistically distinct businesses.

16. The system of claim 15, wherein the plurality of logistically distinct businesses represents a plurality of different customer ordering profiles.

17. The system of claim 15, wherein the plurality of logistically distinct businesses represents a plurality of different supply chain flow patterns of members of the inventory.

18. The system of claim 11, wherein the criterion measure is based on a cost associated with a member of the inventory.

19. The system of claim 11, wherein the criterion measure is based on an item name associated with a member of the inventory.

20. The system of claim 11, wherein calculating a sample size for each of the plurality of segments is based on the formula:

n_x=N_x/1+N_x(e)²

where n_x represents the sample size, N_x represents the number of members in the total population, and e represents the sampling error.