Description:FIELD OF INVENTION
[001] The present invention relates to a stakeholder(s) action analyzing system and a method thereof. Particularly, the present invention relates to analyzing the actions/decisions taken by the stakeholder(s) by a system integrated through a machine learning model-based system.
BACKGROUND OF THE INVENTION
[002] Management of projects in an organization to achieve the planned objectives are largely affected by the actions/decisions of stakeholders. Analysis of stakeholders’ actions helps to identify and understand the stakeholders’ involvement in a project, their interests, and their potential impact on the project. In an organization, a stakeholder can be any person, any party, or a group of people having an interest in an organization, affecting the business strategy of that organization. Stakeholders, at large, may include employees, customers, suppliers, communities, financiers, etc. The stakeholder action may affect the marketing strategy, political analysis, and infrastructure project proposals. In this regard, the application of diverse software-based systems are utilized for the analysis of stakeholders’ actions, which is essential for strategic decision-making.
[003] There are several patent applications related to the analysis of stakeholder action. One such patent document US20170103402A1 disclosed a system and method for utilizing one or more internet-based sources including internet social networks to perform automated stakeholder sentiment analysis relating to infrastructure projects. An analysis engine used in this invention modeled stakeholder data, such as social media comments, in the form of subject-sentiment dyads. A combination of the influence level of the person that generated the sentiment, the subject, and the sentiment of the sentiment data provide a numerical model of the social media data as a data point in the semantic space of the analysis. An aggregation of all data-points within a specific time interval then resulted in the profile of project-related discussions over that period. However, the cited prior art discloses stakeholder sentiment analysis utilizing social networks and fails to analysis providing quantitative results, such as an analyzed score between stated values and observed actions of stakeholders, thereby providing enhanced clarity regarding the effect of the stakeholders’ actions/decisions on various factors of the organization.
[004] Therefore, in order to overcome the challenges associated with the state of the art, there is a need to develop an efficient system for analyzing stakeholder action, thereby helping organization to build enduring relationships with their stakeholder for long-term success and stability.
OBJECTIVE OF THE INVENTION
[005] The primary objective of the present invention is to provide a stakeholder action analysis system and a method thereof.
[006] Another objective of the present invention is to provide an efficient system integrated with a machine learning model for analyzing the actions/decisions of the stakeholders and the resulting consequences, enabling the organization to accordingly make more informed and strategic decisions.
[007] Another objective of the present invention is to provide a system providing an alignment score between stated values and observed actions/decisions of stakeholders.
[008] Yet another objective of the present invention is to provide a system providing customer feedback on the company's ethical behaviour, and several ethical dilemmas resolved in alignment with stated values.
[009] Another objective of the present invention is to provide a system providing supplier ratings on fairness and transparency in dealings.
[0010] Yet another objective of the present invention is to provide a system analyzing the frequency of interactions between stakeholders and the projects/events in the organization.
[0011] Other objectives and advantages of the present invention will become apparent from the following description taken in connection with the accompanying drawings, wherein, by way of illustration and example, the aspects of the present invention are disclosed.

BRIEF DESCRIPTION OF DRAWINGS
[0012] The present invention will be better understood after reading the following detailed description of the presently preferred aspects thereof with reference to the appended drawings, in which the features, other aspects, and advantages of certain exemplary embodiments of the invention will be more apparent from the accompanying drawing in which:
[0013] Figure 1 illustrates a block diagram of the system for analyzing the actions of the stakeholders.
SUMMARY OF THE INVENTION
[0014] The present invention relates to a stakeholder action analyzing system. The system comprising, a computing device (102) to receive input data and instructions by a user; an input device (108) connected to the computing device (102); a processor (104) integrated into the computing device (102) to process the input data received from the user; a server (112) wirelessly connected to the processor (104) to receive and store the processed input data; a machine learning module (114) installed in the server (112) to evaluate stakeholders’ actions based on the processed input data; a display (106); and a memory (110) integrated into the computing device (102) and connected to the processor (104) to store the input data and evaluated stakeholders’ actions data. The input data may be selected from a group consisting of such as, but not limited to, alignment score between stated values and observed actions, consistency index of leadership and management practices, stakeholder trust metrics, number of instances where action contradicted formal communications, frequency of value-aligned behaviors demonstrated by leadership, employee perception of organizational values in practice, customer feedback on company's ethical behavior, supplier ratings on fairness and transparency in dealings, number of ethical dilemmas resolved in alignment with stated values, frequency of leadership “walking the talk’ incidents, stakeholder action with company's conflict resolution processes, rate of positive media coverage related to company actions, employee retention rate attributed to organizational culture, number of corporate social responsibility initiatives implemented, investor confidence based on governance practices, frequency of transparent communication on company decisions, number of whistleblowing incidents and their resolution, employee engagement scores related to company behavior, customer loyalty attributed to company's ethical practices, compliance adherence rate in day-to-day operations, number of community engagement activities reflecting company values, frequency of ethical decision-making, training for employees, stakeholder feedback on company's crisis management behavior, rate of successful conflict resolution with stakeholders, number of recognized instances of going above and beyond for stakeholders, frequency of value-based decision making in strategic choices, employee advocacy rate for company's ethical standards, number of sustainability initiatives, reflecting company values, stakeholder perception of company's long term commitment to its mission, frequency of leadership acknowledging and correcting misalignments, or a combination thereof.
The present invention also relates to a method for analyzing stakeholders' actions using the system. The method comprises the steps of: providing input data and instructions to a computing device (102) through an input device (108); storing the input data in a memory (110) integrated into the computing device (102); transmitting the input data to the processor (104) through the computing device (102) to process/analyze the input data based on the instructions received by the user; transmitting the processed input data through the processor (104) integrated in the computing device (102) to a server (112) wirelessly connected to the computing device (102); analyzing the processed input data received by the server (112) through a machine learning module (116) installed in the server (112) to analyze stakeholders’ actions; storing the analyzed stakeholders’ actions by the server (112) through a storage architecture; transmitting the analyzed stakeholders’ actions data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ actions data on a display (106) installed and connected to the computing device (102). The present invention provides an organization with a broader spectrum of factors in their decision-making, resulting in better strategic choices.

DETAILED DESCRIPTION OF INVENTION
[0015] The following detailed description and embodiments set forth herein below are merely exemplary out of the wide variety and arrangement of instructions, which can be employed with the present invention. The present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. All the features disclosed in this specification may be replaced by similar or other or alternative features performing similar or same or equivalent purposes. Thus, unless expressly stated otherwise, they all are within the scope of the present invention.
[0016] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
[0017] The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention.
[0018] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
[0019] It should be emphasized that the term “comprises/comprising” when used in this specification, is taken to specify the presence of stated features, integers, steps, or components but does not preclude the presence or addition of one or more other features, steps, components, or groups thereof.
[0020] Accordingly, the present invention relates to a stakeholder action analyzing system and a method thereof. Particularly, the present invention relates to analyzing the actions/decisions taken by the stakeholder(s) through a machine learning model-based system.
[0021] In an embodiment, as shown in Figure 1, the system (100) comprising a computing device (102), a processor (104) integrated into the computing device (102), a display (106) connected to the computing device (102); an input device (108) connected to the computing device (102) and communicably connected to the processor (104), a memory (110) integrated into the computing device (102) and connected to the processor (104), a server (112) wirelessly connected to the processor (104), and a machine learning module (114) installed in the server (112).
[0022] The computing device (102) may be configured to receive input data as well as the instructions for the processor (104) to initiate the analysis of the input data for analyzing stakeholders’ actions, provided by a user through an input device (108). In an exemplary embodiment, the computing device (102) may be selected from a group consisting of, such as, but not limited to, a computer, laptop, calculator, etc.
[0023] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for analyzing the stakeholders' actions/decisions. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, alignment score between stated values and observed actions, consistency index of leadership and management practices, stakeholder trust metrics, number of instances where action contradicted formal communications, frequency of value-aligned behaviors demonstrated by leadership, employee perception of organizational values in practice, customer feedback on company's ethical behavior, supplier ratings on fairness and transparency in dealings, number of ethical dilemmas resolved in alignment with stated values, frequency of leadership “walking the talk’ incidents, stakeholder action with company's conflict resolution processes, rate of positive media coverage related to company actions, employee retention rate attributed to organizational culture, number of corporate social responsibility initiatives implemented, investor confidence based on governance practices, frequency of transparent communication on company decisions, number of whistleblowing incidents and their resolution, employee engagement scores related to company behavior, customer loyalty attributed to company's ethical practices, compliance adherence rate in day-to-day operations, number of community engagement activities reflecting company values, frequency of ethical decision-making, training for employees, stakeholder feedback on company's crisis management behavior, rate of successful conflict resolution with stakeholders, number of recognized instances of going above and beyond for stakeholders, frequency of value-based decision making in strategic choices, employee advocacy rate for company's ethical standards, number of sustainability initiatives, reflecting company values, stakeholder perception of company's long term commitment to its mission, frequency of leadership acknowledging and correcting misalignments, or a combination thereof.
[0024] In an exemplary embodiment, the input device (108) may be selected from a group consisting of, such as, but not limited to, a physical keyboard, touch-screen keyboard, mouse, etc.
[0025] The processor (104) may be configured to process/analyze input data on receiving the user’s instructions from the computing device (102) and thereafter wirelessly transmit data to the server (112) for evaluation of stakeholders' actions by the machine learning module (114). In an exemplary embodiment, the processed input data may be transmitted to the server (112) through Wi-Fi, Bluetooth, Ethernet, GPRS module, and the like.
[0026] The server (112) receives processed data from the processor (104) and stores the processed input data through an architecture. The machine learning module (114) installed in the server (112) evaluates stakeholders’ actions based on the processed input data. The server (112) wirelessly transmits the analyzed stakeholder actions data to the computing device (102) through such as, but not limited to, Wi-Fi, Bluetooth, etc., for displaying the analyzed stakeholder actions data through the display (106) for the user. In an exemplary embodiment, the architecture to store the processed input data may be selected from, but not limited to, Recurrent Neural Network (RNN), Autoencoder, and the like.
[0027] The machine learning module (114) may be trained on datasets encompassing a wide range of pre-defined parameters to determine/evaluate stakeholders’ actions, thereby providing an assessment of the stakeholders’ actions, of the organizations. The machine learning module (114) is trained to assign weightage to each pre-defined parameter, which involves segregating the data for training the machine learning module (114) into training data, which is used to train the machine learning module (114) and testing data, which is used to determine the performance of the trained machine learning module (114). The machine learning module (114) may also be configured. In an exemplary embodiment, the machine learning module (114) may be selected from a group consisting of such as, but not limited to, linear regression, polynomial regression, random forest model, and the like, thereby making the process of assigning weight dynamic and automatic.
[0028] The memory (110) may be configured to store the input data provided by the user as well as the evaluated/analyzed stakeholders’ actions data. In an exemplary embodiment, the memory may be selected from a group consisting of, such as, but not limited to, flash memory, secondary memory, cache memory, and the like.
[0029] The instructions provided by the user include the instructions for analyzing the input data by the processor for analyzing stakeholders’ actions.
[0030] In an embodiment, the present invention also provides a method for analyzing stakeholders' actions using the system of the present invention. The method comprises the following steps:
• providing input data and instructions to a computing device (102) through an input device (108);
• storing the input data in a memory (110) integrated into the computing device (102);
• transmitting the input data to the processor (104) through the computing device (102) to process/analyze the input data based on the instructions received by the user;
• transmitting the processed input data through the processor (104) integrated in the computing device (102) to a server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through a machine learning module (116) installed in the server (112) to analyze stakeholders’ actions;
• storing the analyzed stakeholders’ actions by the server (112) through a storage architecture;
• transmitting the analyzed stakeholders’ actions data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ actions data on a display (106) installed and connected to the computing device (102).
[0031] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for analyzing the stakeholders' actions/decisions. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, alignment score between stated values and observed actions, consistency index of leadership and management practices, stakeholder trust metrics, number of instances where action contradicted formal communications, frequency of value-aligned behaviors demonstrated by leadership, employee perception of organizational values in practice, customer feedback on company's ethical behavior, supplier ratings on fairness and transparency in dealings, number of ethical dilemmas resolved in alignment with stated values, frequency of leadership “walking the talk’ incidents, stakeholder action with company's conflict resolution processes, rate of positive media coverage related to company actions, employee retention rate attributed to organizational culture, number of corporate social responsibility initiatives implemented, investor confidence based on governance practices, frequency of transparent communication on company decisions, number of whistleblowing incidents and their resolution, employee engagement scores related to company behavior, customer loyalty attributed to company's ethical practices, compliance adherence rate in day-to-day operations, number of community engagement activities reflecting company values, frequency of ethical decision-making, training for employees, stakeholder feedback on company's crisis management behavior, rate of successful conflict resolution with stakeholders, number of recognized instances of going above and beyond for stakeholders, frequency of value-based decision making in strategic choices, employee advocacy rate for company's ethical standards, number of sustainability initiatives, reflecting company values, stakeholder perception of company's long term commitment to its mission, frequency of leadership acknowledging and correcting misalignments, or a combination thereof.
[0032] The computing device (102) may be configured to receive input data as well as the instructions for the processor (104) to initiate the analysis of the input data for analyzing stakeholders’ actions, provided by a user through an input device (108). In an exemplary embodiment, the computing device (102) may be selected from a group consisting of, such as, but not limited to, a computer, laptop, calculator, etc.
[0033] In an exemplary embodiment, the input device (108) may be selected from a group consisting of, such as, but not limited to, a physical keyboard, touch-screen keyboard, mouse, etc.
[0034] In an exemplary embodiment, the memory may be selected from a group consisting of, such as, but not limited to, flash memory.
[0035] In an exemplary embodiment, the stakeholders may include such as, but not limited to, employees, communities, suppliers, workers, customers, members, shareholders, referral sources, distribution partners, financiers, functional areas, departments, etc.
[0036] The advantages of the present invention are enlisted herein:
• The present invention provides an organization with a broader spectrum of factors in their decision-making, resulting in better strategic choices.
• The present invention covers a wide range of parameters to analyze organizational stakeholder action.
• The present invention utilizes machine learning models to offer insights into future performance planning and decision-making.
• The present invention provides improve stakeholder management by identification of stakeholders and understanding their preferences/actions.
• The machine learning module provides data-driven recommendations based on stakeholders' action.

[0037] While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims. , Claims:WE CLAIM:
1. A stakeholder action analyzing system, comprising:
• a computing device (102) to receive input data and instructions by a user;
• an input device (108) connected to the computing device (102) and communicably connected to the processor (104) for the user to provide input data and instructions to initiate analysis of the input data for analyzing stakeholders’ actions;
• a processor (104) integrated into the computing device (102) to process the input data received from the user;
• a server (112) wirelessly connected to the processor (104) to receive and store the processed input data through a model architecture;
• a machine learning module (114) installed in the server (112) to evaluate stakeholders’ actions based on the processed input data; and
• a display (106) installed and connected to the computing device (102) to display the analyzed stakeholder action data; and
• a memory (110) integrated into the computing device (102) and connected to the processor (104) to store the input data and evaluated stakeholders’ actions data.
2. The system as claimed in claim 1, wherein the computing device (102) is selected from computer, laptop, calculator.
3. The system as claimed in claim 1, wherein the input data comprises of a selected from a group consisting of alignment score between stated values and observed actions, consistency index of leadership and management practices, stakeholder trust metrics, number of instances where action contradicted formal communications, frequency of value-aligned behaviors demonstrated by leadership, employee perception of organizational values in practice, customer feedback on company's ethical behavior, supplier ratings on fairness and transparency in dealings, number of ethical dilemmas resolved in alignment with stated values, frequency of leadership “walking the talk’ incidents, stakeholder action with company's conflict resolution processes, rate of positive media coverage related to company actions, employee retention rate attributed to organizational culture, number of corporate social responsibility initiatives implemented, investor confidence based on governance practices, frequency of transparent communication on company decisions, number of whistleblowing incidents and their resolution, employee engagement scores related to company behavior, customer loyalty attributed to company's ethical practices, compliance adherence rate in day-to-day operations, number of community engagement activities reflecting company values, frequency of ethical decision-making, training for employees, stakeholder feedback on company's crisis management behavior, rate of successful conflict resolution with stakeholders, number of recognized instances of going above and beyond for stakeholders, frequency of value-based decision making in strategic choices, employee advocacy rate for company's ethical standards, number of sustainability initiatives, reflecting company values, stakeholder perception of company's long term commitment to its mission, frequency of leadership acknowledging and correcting misalignments, or a combination thereof.
4. The system as claimed in claim 1, wherein the input device (108) is a physical keyboard, touch-screen keyboard, and mouse.
5. The system (100) as claimed in claim 1, wherein the server (112) employs a trained Recurrent Neural Network (RNN) model architecture for data storage, encompassing a wide range of pre-defined input parameters to evaluate/analyze stakeholder actions to improve decision-making by the organization.
6. The system (100) as claimed in claim 1, wherein machine learning module (114) is configured for continuous refinement through iterative training to alleviate reliance on human intervention.
7. The system (100) as claimed in claim 1, wherein machine learning module (114) is configured to attribute weightage to pre-defined input data as compared to the standard industrial norms.
8. The system (100) as claimed in claim 1, wherein the stakeholder is, employee, a community, supplier, worker, and customer.
9. The system (100) as claimed in claim 1, wherein the machine learning module (114) may be selected from a group consisting of linear regression, polynomial regression, and random forest model.

10. The method for analyzing stakeholders' actions using the system (100) as claimed in claim 1, comprises the steps of:
• providing input data and instructions to a computing device (102) through an input device (108);
• storing the input data in a memory (110) integrated into the computing device (102);
• transmitting the input data to the processor (104) through the computing device (102) to process/analyze the input data based on the instructions received by the user;
• transmitting the processed input data through the processor (104) integrated in the computing device (102) to a server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through a machine learning module (114) installed in the server (112) to analyze stakeholders’ actions;
• storing the analyzed stakeholders’ actions by the server (112);
• transmitting the analyzed stakeholders’ actions data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ actions data on a display (106) installed and connected to the computing device (102).