Estimating demand for a supply chain according to order lead time

• US 20040230473A1
• Filed: 04/29/2004
• Published: 11/18/2004
• Est. Priority Date: 05/12/2003
• Status: Active Grant

• Current Assignee: Blue Yonder Group, Inc. (Panasonic Holdings Corporation)
• Original Assignee: JDA Technologies US, Inc. (Panasonic Holdings Corporation)
• Inventors: Dogan, Koray, Raman, Ramesh, Najmi, Adeel
• Granted Patent: US 7,827,049 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 10/063 Operations research, analysis or management
• 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 30/0202 Market predictions or forecasting for commercial activities

Abstract

In one embodiment, estimating demand for a supply chain includes accessing a probability distribution for expected order lead time of the supply chain. The supply chain has nodes including a starting node and an ending node and a path from the starting node to the ending node. The probability distribution for expected order lead time describes ending node demand for the ending node versus order lead time. The path is divided into order lead time segments, and the order lead time segments are associated with the probability distribution for expected order lead time by associating each order lead home segment with a corresponding order lead time range of the probability distribution for expected order lead time. A demand percentage is estimated for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain. Each demand percentage describes a percentage of a total ending node demand associated with the corresponding order lead time segment.

Claims

1. A method for estimating demand for a supply chain, comprising:

accessing a probability distribution for expected order lead time associated with a supply chain comprising a plurality of nodes including a starting node and ending node and a path from the starting node to the ending node, the probability distribution for expected order lead time describing ending node demand for the ending node versus order lead time;

dividing the path into a plurality of order lead time segments;

associating the plurality of order lead time segments with the probability distribution for expected order lead time, each order lead time segment being associated with a corresponding order lead time range of the probability distribution for expected order lead time; and

determining a demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain, each demand percentage describing a percentage of a total ending node demand associated with the corresponding order lead time segment.

2. The method of claim 1, further comprising:

generating a plurality of probability distribution for expected order lead time options, each probability distribution for expected order lead time option associated with one of a plurality of categories;

identifying one of the plurality of categories that corresponds to a customer of the supply chain; and

selecting a probability distribution for expected order lead time option associated with the identified category as the probability distribution for expected order lead time.

3. The method of claim 1, further comprising modifying the probability distribution for expected order lead time to reflect a predicted change of ending node demand.

4. The method of claim 1, wherein dividing the path into the plurality of order lead time segments comprises:

establishing a plurality of cumulative cycle times for the plurality of nodes, each cumulative cycle time comprising a time difference between a time item arrives at the corresponding node and a time the item is available to leave the ending node considering all required processing cycle times; and

determining an order lead time segment comprising a difference between a first cumulative cycle time for a first node and a second cumulative cycle time for a second node.

5. The method of claim 1, wherein determining the demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain comprises:

selecting an order lead time segment defined by a first point and a second point;

identifying a first ending node demand corresponding to the first point according to the probability distribution for expected order lead time;

identifying a second ending node demand corresponding to the second point according to the probability distribution for expected order lead time; and

calculating a demand percentage for the order lead time segment according to the first ending node demand and the second ending node demand.

6. The method of claim 1, further comprising calculating an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes.

7. The method of claim 1, further comprising calculating an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes by repeating the following for at least a subset of the plurality of nodes:

selecting a node of the subset of the plurality of nodes;

establishing the demand percentage of the order lead time segment associated with the selected node; and

determining an inventory of the selected node that satisfies the demand percentage.

8. The method of claim 1, wherein the probability distribution for expected order lead time is generated from an order lead time profile.

9. A system for estimating demand for a supply chain, comprising:

a database operable to store a probability distribution for expected order lead time associated with a supply chain comprising a plurality of nodes including a starting node and an ending node and a path from the starting node to the ending node, the probability distribution for expected order lead time describing ending node demand for the ending node versus order lead time; and

a server system coupled to the database and operable to;

divide the path into a plurality of order lead time segments;

associate the plurality of order lead time segments with the probability distribution for expected order lead time, each order lead time segment being associated with a corresponding order lead time range of the probability distribution for expected order lead time; and

determine a demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain, each demand percentage describing a percentage of a total ending node demand associated with the corresponding order lead time segment.

10. The system of claim 9, the server system further operable to:

generate a plurality of probability distribution for expected order lead time options, each probability distribution for expected order lead time option associated with one of a plurality of categories;

identify one of the plurality of categories that corresponds to a customer of the supply chain; and

select a probability distribution for expected order lead time option associated with the identified category as the probability distribution for expected order lead time.

11. The system of claim 9, the server system further operable to modify the probability distribution for expected order lead time to reflect a predicted change of ending node demand.

12. The system of claim 9, the server system operable to divide the path into the plurality of order lead time segments by:

establishing a plurality of cumulative cycle times for the plurality of nodes, each cumulative cycle time comprising a time difference between a time item arrives at the corresponding node and a time the item is available to leave the ending node considering all required processing cycle times and distribution cycle times; and

determining an order lead time segment comprising a difference between a first cumulative cycle time for a first node and a second cumulative cycle time for a second node.

13. The system of claim 9, the server system operable to determine the demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain by:

selecting an order lead time segment defined by a first point and a second point;

identifying a first ending node demand corresponding to the first point according to the probability distribution for expected order lead time;

identifying a second ending node demand corresponding to the second point according to the probability distribution for expected order lead time; and

calculating a demand percentage for the order lead time segment according to the first ending node demand and the second ending node demand.

14. The system of claim 9, the server system further operable to calculate an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes.

15. The system of claim 9, the server system further operable to calculate an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes by repeating the following for at least a subset of the plurality of nodes:

selecting a node of the subset of the plurality of nodes;

establishing the demand percentage of the order lead time segment associated with the selected node; and

determining an inventory of the selected node that satisfies the demand percentage.

16. The system of claim 9, wherein the probability distribution for expected order lead time is generated from an order lead time profile.

17. Software for estimating demand for a supply chain, the software embodied in a computer-readable medium and when executed by a computer operable to:

access a probability distribution for expected order lead time associated with a supply chain comprising a plurality of nodes including a starting node and an ending node and a path from the starting node to the ending node, the probability distribution for expected order lead time describing ending node demand for the ending node versus order lead time;

divide the path into a plurality of order lead time segments;

associate the plurality of order lead time segments with the probability distribution for expected order lead time, each order lead time segment being associated with a corresponding order lead time range of the probability distribution for expected order lead time; and

determine a demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain, each demand percentage describing a percentage of a total ending node demand associated with the corresponding order lead time segment.

18. The software of claim 17, further operable to:

generate a plurality of probability distribution for expected order lead time options, each probability distribution for expected order lead time option associated with one of a plurality of categories;

identify one of the plurality of categories that corresponds to a customer of the supply chain; and

select a probability distribution for expected order lead time option associated with the identified category as the probability distribution for expected order lead time.

19. The software of claim 17, further operable to modify the probability distribution for expected order lead time to reflect a predicted change of ending node demand.

20. The software of claim 17, operable to divide the path into the plurality of order lead time segments by:

establishing a plurality of cumulative cycle times for the plurality of nodes, each cumulative cycle time comprising a time difference between a time item arrives at the corresponding node and a time the item is available to leave the ending node considering all required processing cycle times and distribution cycle times; and

determining an order lead time segment comprising a difference between a first cumulative cycle time for a first node and a second cumulative cycle time for a second node.

21. The software of claim 17, operable to determine the demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain by:

selecting an order lead time segment defined by a first point and a second point;

identifying a first ending node demand corresponding to the first point according to the probability distribution for expected order lead time;

identifying a second ending node demand corresponding to the second point according to the probability distribution for expected order lead time; and

calculating a demand percentage for the order lead time segment according to the first ending node demand and the second ending node demand.

22. The software of claim 17, further operable to calculate an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes.

23. The software of claim 17, further operable to calculate an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes by repeating the following for at least a subset of the plurality of nodes:

selecting a node of the subset of the plurality of nodes;

establishing the demand percentage of the order lead time segment associated with the selected node; and

determining an inventory of the selected node that satisfies the demand percentage.

24. The software of claim 17, wherein the probability distribution for expected order lead time is generated from an order lead time profile.

25. A system for estimating demand for a supply chain, comprising:

means for accessing a probability distribution for expected order lead time associated with a supply chain comprising a plurality of nodes including a starting node and an ending node and a path from the starting node to the ending node, the probability distribution for expected order lead time describing ending node demand for the ending node versus order lead time, the probability distribution for expected order lead time being generated from an order lead time profile;

means for dividing the path into a plurality of order lead time segments;

means for associating the plurality of order lead time segments with the probability distribution for expected order lead time, each order lead time segment being associated with a corresponding order lead time range of the probability distribution for expected order lead time; and

means for determining a demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain, each demand percentage describing a percentage of a total ending node demand associated with the corresponding order lead time segment.

26. A method for estimating demand for a supply chain, comprising:

accessing a description of a supply chain comprising a plurality of nodes including a starting node and an ending node and a path from the starting node to the ending node;

generating a plurality of probability distribution for expected order lead time options, each probability distribution for expected order lead time option associated with one of a plurality of categories;

identifying one of the plurality of categories that corresponds to a customer of the supply chain;

selecting a probability distribution for expected order lead time option associated with the identified category as a probability distribution for expected order lead time, the probability distribution for expected order lead time describing ending node demand for the ending node of the supply chain versus order lead time;

modifying the probability distribution for expected order lead time to reflect a predicted change of the ending node demand;

dividing the path into a plurality of order lead time segments by;

establishing a plurality of cumulative cycle times for the plurality of nodes, each cumulative cycle time comprising a time difference between a time item arrives at the corresponding node and a time the item is available to leave the ending node considering all required processing cycle times and distribution cycle times; and

determining an order lead time segment comprising a difference between a first cumulative cycle time for a first node and a second cumulative cycle time for a second node;

associating the plurality of order lead time segments with the probability distribution for expected order lead time, each order lead time segment being associated with a corresponding order lead time range of the probability distribution for expected order lead time;

determining a demand percentage for each order lead time segment in accordance with the probability distribution for expected order lead time in order to estimate demand for the supply chain, each demand percentage describing a percentage of a total ending node demand associated with the corresponding order lead time segment, the demand percentage estimated by;

selecting an order lead time segment defined by a first point and a second point;

identifying a first ending node demand corresponding to the first point according to the probability distribution for expected order lead time;

identifying a second ending node demand corresponding to the second point according to the probability distribution for expected order lead time; and

calculating a demand percentage for the order lead time segment according to the first ending node demand and the second ending node demand; and

calculating an inventory at each node of the plurality of nodes according to the demand percentages of the plurality of nodes by repeating the following for at least a subset of the plurality of nodes;

selecting a node of the subset of the plurality of nodes;

establishing the demand percentage of the order lead time segment associated with the selected node; and

determining an inventory of the selected node that satisfies the demand percentage.