Claims:WE CLAIM:
1. A method of identifying root causes in a supply chain network, the method comprising:
receiving, via a risk analyzing device, a user query;
performing, via the risk analyzing device, natural language processing and text analysis on the user query to derive contextually relevant keywords from the user query;
categorizing, via the risk analyzing device, the contextually relevant keywords into a risk category selected from a plurality of risk categories;
identifying, via the risk analyzing device, a risk in the supply chain network based on the contextually relevant keywords and the risk category; and
detecting, via the risk analyzing device, a root cause from amongst a plurality of root causes associated with the risk using a causal analysis algorithm.
2. The method of claim 1, wherein the user query comprises at least one of an audio query and a text query.
3. The method of claim 1 further comprising receiving a plurality of supply chain inputs associated with the supply chain network.
4. The method of claim 3, wherein the plurality of supply chain inputs are selected from a group comprising supply chain contributors, supply chain parameters, and supply chain data sources, the supply chain data sources being selected based on the supply chain parameters.
5. The method of claim 4, wherein the supply chain parameters are selected from a group comprising supply, demand, transportation, process, storage, information, finance, environment.
6. The method of claim 1, wherein performing the text analysis comprises iteratively classifying the user input to determine problem faced by the user based on the contextually relevant keywords derived.
7. The method of claim 1, wherein performing the text analysis comprises ignoring stop words in the user input.
8. The method of claim 1, wherein the plurality of risk categories comprises at least one of an external to supply chain category, an internal to supply chain category, and a management related category.
9. The method of claim 1 further comprising implementing incremental intelligence using machine learning techniques for future data analysis.
10. A system identifying root causes in a supply chain network, the system comprising:
at least one processors; and
a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
receiving, via a risk analyzing device, a user query;
performing, via the risk analyzing device, natural language processing and text analysis on the user query to derive contextually relevant keywords from the user query;
categorizing, via the risk analyzing device, the contextually relevant keywords into a risk category selected from a plurality of risk categories;
identifying, via the risk analyzing device, a risk in the supply chain network based on the contextually relevant keywords and the risk category; and
detecting, via the risk analyzing device, a root cause from amongst a plurality of root causes associated with the risk using a causal analysis algorithm.
11. The system of claim 10, wherein the user query comprises at least one of an audio query and a text query.
12. The system of claim 10, wherein the operations further comprise receiving a plurality of supply chain inputs associated with the supply chain network.
13. The system of claim 12, wherein the plurality of supply chain inputs are selected from a group comprising supply chain contributors, supply chain parameters, and supply chain data sources, the supply chain data sources being selected based on the supply chain parameters.
14. The system of claim 13, wherein the supply chain parameters are selected from a group comprising supply, demand, transportation, process, storage, information, finance, environment.
15. The system of claim 10, wherein the operation of performing the text analysis comprises operation of iteratively classifying the user input to determine problem faced by the user based on the contextually relevant keywords derived.
16. The system of claim 10, wherein the operation of performing the text analysis comprises operation of ignoring stop words in the user input.
17. The system of claim 10, wherein the plurality of risk categories comprises at least one of an external to supply chain category, an internal to supply chain category, and a management related category.
18. The system of claim 10, wherein the operations further comprise implementing incremental intelligence using machine learning techniques for future data analysis.

Dated this 27th day of November, 2015

Swetha S.N.
Of K&S Partners
Agent for the Applicant
, Description:TECHNICAL FIELD
This disclosure relates generally to supply chain networks and more particularly to methods and systems for identifying risks and associated root causes in supply chain networks.