Inventory early warning agent in a supply chain management system
First Claim
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1. A computer-implemented method comprising:
- applying machine learning techniques to historical supply chain data to build a conditional probabilistic model including patterns of behavior related to consumption and replenishment activities in a supply chain;
receiving inventory data relating to stock in an inventory;
applying the inventory data to a conditional probabilistic predictive statistical algorithm, wherein the conditional probabilistic predictive statistical algorithm uses the conditional probabilistic model to process the inventory data and to calculate a predicted inventory level based on a supply prediction and a demand prediction, the supply prediction factoring in variability in supply chain activities;
using the calculated predicted inventory level to determine whether to order additional stock for the inventory; and
automatically ordering a replenishment of the inventory when the calculated predicted inventory level falls below a predetermined minimum.
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Abstract
An inventory agent operating on software includes instructions operable to cause a programmable processor to receive inventory data relating to stock in an inventory, apply the inventory data to a conditional probabilistic predictive statistical algorithm, calculate a predicted inventory level, and use the calculated predicted inventory level to determine whether to order additional stock for the inventory. The statistical algorithm uses a conditional probabilistic model to process the data. The inventory agent may be implemented in a supply chain management system.
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Citations
39 Claims
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1. A computer-implemented method comprising:
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applying machine learning techniques to historical supply chain data to build a conditional probabilistic model including patterns of behavior related to consumption and replenishment activities in a supply chain; receiving inventory data relating to stock in an inventory; applying the inventory data to a conditional probabilistic predictive statistical algorithm, wherein the conditional probabilistic predictive statistical algorithm uses the conditional probabilistic model to process the inventory data and to calculate a predicted inventory level based on a supply prediction and a demand prediction, the supply prediction factoring in variability in supply chain activities; using the calculated predicted inventory level to determine whether to order additional stock for the inventory; and automatically ordering a replenishment of the inventory when the calculated predicted inventory level falls below a predetermined minimum. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A system comprising one or more computer systems and an inventory agent computer coupled to the computer systems over a network, the inventory agent computer being operable to:
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apply machine learning techniques to historical supply chain data to build a conditional probabilistic model including patterns of behavior related to consumption and replenishment activities in a supply chain; receive inventory data relating to stock in an inventory; apply the inventory data to a conditional probabilistic predictive statistical algorithm, wherein the conditional probabilistic predictive statistical algorithm uses the conditional probabilistic model to process the inventory data and to calculate a predicted inventory level, an upside 10% confidence bound of the predicted inventory level and a downside 10% confidence bound of the predicted inventory level, based on a supply prediction and a demand prediction, the supply prediction factoring in variability in supply chain activities; and use the calculated predicted inventory level to determine whether to order additional stock for the inventory. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. A machine readable medium having instructions therein which when executed by a computer cause the computer to perform a set of operations comprising:
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applying machine learning techniques to historical supply chain data to build a conditional probabilistic model including patterns of behavior related to consumption and replenishment activities in a supply chain; receiving inventory data relating to stock in an inventory; applying the inventory data to a conditional probabilistic predictive statistical algorithm, wherein the conditional probabilistic predictive statistical algorithm uses the conditional probabilistic model to process the inventory data and to calculate a predicted inventory level based on a supply prediction and a demand prediction, the supply prediction factoring in variability in supply chain activities; using the calculated predicted inventory level to determine whether to order additional stock for the inventory; and automatically ordering a replenishment of the inventory when the calculated predicted inventory level indicates a likely undesirable variation in inventory. - View Dependent Claims (28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39)
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Specification