Opportunity driven system and method based on cognitive decision-making process

1. A method for continuous optimization of an organization based on a cognitive decision-making process, the method comprises:

receiving, by a processor, a stream of raw data from one or more sources internal or external to an organization;

generating, by the processor, an opportunity input data package based on an analysis of the stream of raw data using one or more predefined instructions, wherein the one or more predefined instructions comprise one or more data structures, and one or more pattern recognition algorithm associated with an opportunity from a set of opportunities, wherein the opportunity input data package is generated by:

filtering noise data from the stream of raw data using the one or more pattern recognition algorithms to generate filtered data; and

reorganizing the filtered data using the one or more data structures;

identifying, by the processor, the opportunity from the set of opportunities based on an analysis of the opportunity input data package, wherein the analysis comprises one or more of a time-series analysis, an incremental analysis, a prediction model, and a computational model; wherein the prediction model and the computational model are generated using a machine learning methodology and historical data;

generating, by the processor, an opportunity instance package associated with the opportunity from the set of opportunities associated with the organization based on the analysis of the stream of raw data, wherein the opportunity instance package indicates the filtered data associated to the opportunity;

generating, by the processor, a strategy using the opportunity instance package and one or more of a predictive technique, a prescriptive technique and an optimization technique; and

generating, by the processor, a set of instruction associated with one or more actors associated with the organization based on the strategy, thereby enabling continuous optimization of the organization based on a cognitive decision-making process, wherein the one or more actors is one of an employee of the organization, or a computer program associated with the organization.

2. The method of claim 1 , further comprising

tracking, by the processor, an implementation of the set of instruction;

computing, by the processor, an expected outcome based on the set of instruction;

generating, by the processor, an actual outcome based on analysis of the stream of raw data, received post implementation of the set of instructions;

computing, by the processor, a deviation based on a comparison of the expected outcome and the actual outcome; and

identifying one or more predefined instruction, to be modified if the deviation is over a predefined threshold.

3. The method of claim 1 , further comprises modelling the organization as an opportunity driven system configured to cognitively sense one or more parameter and execute one or more actions, wherein the one or more parameters is internal or external to the organization.

4. The method of claim 1 , further comprising:

synthesizing, by the processor, an opportunity document, and a strategy document from a machine readable format to a human readable format using one of a natural language generating methodology and predefined templates, and the opportunity instance package;

displaying, by the processor, the opportunity document and the strategy document to the user; and

modifying, by the processor, the opportunity and the strategy based on a user input.

5. The method of claim 1 , wherein generating the opportunity input data package further comprises the step of collecting, by the processor, the filtered data for one of a predefined time interval, or a predefined data size.

6. The method of claim 1 , further comprising

generating, by the processor, a reason for identifying the opportunity based on the analysis of the opportunity input data package; and

appending, by the processor, the reason to the opportunity instance package.

7. An opportunity driven system for continuous optimization of an organization based on a cognitive decision-making process, the system comprising:

a memory; and

a processor coupled to the memory, wherein the processor is configured to:

receiving a stream of raw data from one or more sources internal or external to an organization;

generating an opportunity input data package based on an analysis of the stream of raw data using one or more predefined instructions, wherein the one or more predefined instructions comprise one or more data structures, and one or more pattern recognition algorithm associated with an opportunity from a set of opportunities, wherein the opportunity input data package is generated by:

filtering a noise data from the stream of raw data using the one or more pattern recognition algorithms to generate filtered data; and

reorganizing the filtered data using the one or more data structures; and

identifying the opportunity from the set of opportunities based on an analysis of the opportunity input data package, wherein the analysis comprises one or more of a time-series analysis, an incremental analysis, a prediction model, and a computational model wherein the prediction model and the computational model are generated using a machine learning methodology and historical data;

generating an opportunity instance package associated with the opportunity from the set of opportunities associated with the organization based on the analysis of the stream of raw data, wherein the opportunity instance package indicates the filtered data associated to the opportunity;

generating a strategy using the opportunity instance package and one or more of a predictive technique, a prescriptive technique and an optimization technique; and

generating a set of instruction associated with one or more actors associated with the organization based on the strategy, thereby enabling continuous optimization of the organization based on a cognitive decision-making process, wherein the one or more actors is one of an employee of the organization, or a computer program associated with the organization.

8. The opportunity driven system of claim 7 , further comprising tracking an implementation of the set of instruction;

computing an expected outcome based on the set of instruction;

generating an actual outcome based on analysis of the stream of raw data, received post implementation of the set of instructions;

computing a deviation based on a comparison of the expected outcome and the actual outcome; and

identifying one or more predefined instruction, to be modified if the deviation is over a predefined threshold.

9. The opportunity driven system of claim 7 , further comprises modelling the organization as an opportunity driven system configured to cognitively sense one or more parameters and executed one or more actions, wherein the one or more parameters is internal or external to the organization.

10. The opportunity driven system of claim 7 , further comprising:

synthesizing an opportunity document, and a strategy document from a machine readable format to a human readable format using one of a natural language generating methodology and predefined templates, the opportunity instance package;

displaying the opportunity document and the strategy document to the user; and

modifying the opportunity and the strategy based on a user input.

11. The opportunity driven system of claim 7 , wherein generating the opportunity input data package further comprises the step of collecting the filtered data for one of a predefined time interval, or a predefined data size.

12. The opportunity driven system of claim 7 , further comprising generating a reason for identifying the opportunity based on analysis of the opportunity input data package; and appending the reason to the opportunity instance package.

13. A non-transitory computer readable medium embodying a program executable in a computing device for continuous optimization of an organization based on a cognitive decision-making process, the program comprising a program code for:

receiving a stream of raw data from one or more sources internal or external to a organization;

generating an opportunity input data package based on an analysis of the stream of raw data using one or more predefined instructions, wherein the one or more predefined instructions comprise one or more data structures, and one or more patter recognition algorithm associated with an opportunity from a set of opportunities, wherein the opportunity input data package is generated by:

filtering a noise data from the stream of raw data using the one or more pattern recognition algorithms to generate filtered data; and

reorganizing the filtered data using the one or more data structures; and

identifying the opportunity from the set of opportunities based on an analysis of the opportunity input data package, wherein the analysis comprises one or more of a time-series analysis, an incremental analysis, a prediction model, and a computational model wherein the prediction model and the computational model are generated using a machine learning methodology and historical data;

generating an opportunity instance package associated with the opportunity from the set of opportunities associated with the organization based on the analysis of the stream of raw data, wherein the opportunity instance package indicates the filtered data associated to the opportunity;

generating a strategy using the opportunity instance package and one or more of a predictive technique, a prescriptive technique and an optimization technique; and

generating a set of instruction associated with one or more actors associated with the organization based on the strategy, thereby enabling continuous optimization of the organization based on a cognitive decision-making process, wherein the one or more actors is one of an employee of the organization, or a computer program associated with the organization.

14. The non-transitory computer readable medium of claim 13 , further comprises

tracking an implementation of the set of instruction;

computing an expected outcome based on the set of instruction;

generating an actual outcome based on analysis of the stream of raw data, received post implementation of the set of instructions;

computing a deviation based on a comparison of the expected outcome and the actual outcome; and

identifying one or more predefined instruction, to be modified if the deviation is over a predefined threshold.

15. The non-transitory computer readable medium of claim 13 , further comprises modelling the organization as an opportunity driven system configured to cognitively sense one or more parameters and executed one or more actions, wherein the one or more parameters is internal or external to the organization.

16. The non-transitory computer readable medium of claim 13 , further comprising:

synthesizing an opportunity document, and a strategy document from a machine readable format to a human readable format using one of a natural language generating methodology and predefined templates, the opportunity instance package;

displaying the opportunity document and the strategy document to the user; and

modifying the opportunity and the strategy based on a user input.

17. The non-transitory computer readable medium of claim 13 , wherein generating the opportunity input data package further comprises the step of collecting the filtered data for one of a predefined time interval, or a predefined data size.

18. The non-transitory computer readable medium of claim 13 , further comprising

generating a reason for identifying the opportunity based on the analysis of the opportunity input data package; and

appending the reason to the opportunity instance package.