Description:FIELD OF INVENTION
[001] The present invention relates to a stakeholder(s) satisfaction analyzing system and a method thereof. Particularly, the present invention relates analyzing stakeholder(s) satisfaction by a system integrated through a machine learning model-based system.
BACKGROUND OF THE INVENTION
[002] Stakeholders have a pivotal role in managing an organization effectively. A stakeholder can be any individual 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, or communities. Stakeholder satisfaction is an important parameter that is to be measured to develop long-term strategies for business operations.
[003] A computing device can applicable to analyze stakeholder satisfaction. Key Performing Indicators (KPIs) are used to provide a picture of an organization with respect to stakeholder satisfaction. Diverse tools and software significantly enhance stakeholder satisfaction analysis and decision-making processes. Stakeholder satisfaction can be utilized using a calculating device by employing metrics and tools that yield actionable insights. Basic computing devices are limited in their analytical scope, unable to handle the complex metrics required for comprehensive analytical calculations related to performing stakeholder satisfaction metrics. These devices are limited in their analytical scope, unable to handle the complex metrics required for comprehensive business evaluations such as stakeholder satisfaction metrics.
[004] Measuring stakeholder satisfaction is a continuous process for strategic decision-making that fosters a culture of responsiveness and adaptability. There are several patent documents disclosing computer implemented stakeholder analysis system. One such patent document AU2010217178B2 discloses a computer implemented stakeholder analysis system and method for analyzing relationship of the stakeholder in an organization. The system used for capturing data associated with and measuring a plurality of predefined and interrelated latent variables representing stakeholder experiences, stakeholder attitudes and stakeholder behavioral intentions which are collectively incorporated in a plurality of stakeholder relationship causality models representing all manner of stakeholder relationship types and settings. However, the cited document does not disclose an advanced computing system to precisely analyze stakeholder satisfaction by using employee well-being and satisfaction metrics, work-life balance indicators for employees, and customer satisfaction and loyalty metrics.
[005] 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 satisfaction metric, thereby helping an organization to build enduring relationships with their stakeholder for long-term success and stability.
OBJECTIVE OF THE INVENTION
[006] The primary objective of the present invention is to provide a stakeholder(s) satisfaction analyzing system and a method thereof.
[007] Another objective of the present invention is to provide a machine learning-based stakeholder(s) satisfaction analyzing system, enabling an organization to make more informed and strategic decisions.
[008] Another objective of the present invention is to assist organizations in improving the efficiency of the organization based on employee well-being and satisfaction metrics.
[009] Yet another objective of the present invention is to utilize satisfaction scores indicating employee engagement, diversity, equity, and inclusion metrics for organizational improvement.
[0010] Another objective of the present invention is to utilize environmental sustainability parameters to evaluate the stakeholder(s) satisfaction.
[0011] Yet another objective of the present invention is to evaluate community engagement and social impact measures to improve customer retention and loyalty rates of the organization.
[0012] Yet another objective of the present invention is to assist organizations to improve the precision of organizational performance evaluation and reduce manual effort by leveraging advanced analytical capabilities.
[0013] 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
[0014] 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:
[0015] Figure 1 illustrates a block diagram of the system for analyzing the satisfaction of the stakeholder(s).
SUMMARY OF THE INVENTION
[0016] The present invention relates to a stakeholders’ satisfaction 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’ satisfaction 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’ satisfaction data. The input data may be selected from a group consisting of such as, but not limited to, employee well-being and satisfaction metrics, work-life balance indicators for employees, skills development and career growth opportunities provided, community engagement and social impact measures, environmental sustainability initiatives and outcomes, customer satisfaction and loyalty metrics, supplier relationship health and longevity, innovation and research & development investments, job creation and local economic impact , diversity, equity and inclusion progress, employee volunteer hours and community service initiatives, health and safety improvements for workers and customers, knowledge sharing and industry contributions, stakeholder trust and reputation scores, product quality and reliability improvements, supply chain ethics and fair trade practices, digital inclusion and accessibility efforts, educational partnerships and scholarship programs, patents filed and intellectual property created, customer time/cost savings from using products/services, or combination thereof.
[0017] The present invention also relates to a method for analyzing stakeholders' satisfaction 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’ satisfaction; storing the analyzed stakeholders’ satisfaction by the server (112) through a storage architecture; transmitting the analyzed stakeholders’ satisfaction data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ satisfaction data on a display (106) installed and connected to the computing device (102). The present invention provides machine learning based stakeholders’ satisfaction analyzing system that helps to build enduring relationships with their stakeholder for long-term success and stability.
DETAILED DESCRIPTION OF INVENTION
[0018] 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.
[0019] 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.
[0020] 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.
[0021] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
[0022] 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, integers, steps, components, or groups thereof.
[0023] Accordingly, the present invention relates to a stakeholder(s) satisfaction analyzing system and a method thereof. Particularly, the present invention relates analyzing stakeholder(s) satisfaction by a system integrated through a machine learning model-based system for storing, processing, analyzing, and displaying the output/score associated with a plurality of stakeholders to measure the employee well-being, satisfaction, work-life balance, skills development, career growth opportunities, community engagement, and social impact measures.
[0024] In an embodiment, as shown in Figure 1, the system (100) comprises 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).
[0025] 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’ satisfaction, 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.
[0026] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for analyzing the stakeholders' satisfaction. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, employee well-being and satisfaction metrics, work-life balance indicators for employees, skills development and career growth opportunities provided, community engagement and social impact measures, environmental sustainability initiatives and outcomes, customer satisfaction and loyalty metrics, supplier relationship health and longevity, innovation and research & development investments, job creation and local economic impact , diversity, equity and inclusion progress, employee volunteer hours and community service initiatives, health and safety improvements for workers and customers, knowledge sharing and industry contributions, stakeholder trust and reputation scores, product quality and reliability improvements, supply chain ethics and fair trade practices, digital inclusion and accessibility efforts, educational partnerships and scholarship programs, patents filed and intellectual property created, customer time/cost savings from using products/services, or a combination thereof.
[0027] 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.
[0028] 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' satisfaction 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.
[0029] 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’ satisfaction based on the processed input data. The server (112) wirelessly transmits the analyzed stakeholder satisfaction data to the computing device (102) through such as, but not limited to, Wi-Fi, Bluetooth, etc., for displaying the analyzed stakeholder satisfaction 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.
[0030] The machine learning module (114) may be trained on datasets encompassing a wide range of pre-defined parameters to determine/evaluate stakeholders’ satisfaction, thereby providing an assessment of the stakeholders’ satisfaction, 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.
[0031] The memory (110) may be configured to store the input data provided by the user as well as the evaluated/analyzed stakeholders’ satisfaction 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.
[0032] The instructions provided by the user include the instructions for analyzing the input data by the processor for analyzing stakeholders’ satisfaction.
[0033] In an embodiment, the machine learning module (116) is configured to analyze employee well-being and satisfaction metrics, community engagement and social impact measure metrics, customer satisfaction and loyalty metrics, and environmental sustainability metrics.
[0034] In an exemplary embodiment, the environmental sustainability metrics may include, such as, but not limited to, greenhouse gas emissions, energy consumption, and efficiency, water consumption and management, waste generation and recycling rates, use of renewable energy sources, sustainable packaging and product design, deforestation, and biodiversity impact.
[0035] In another exemplary embodiment, employee well-being and satisfaction metrics may include, such as, but not limited to, employee engagement and satisfaction scores, diversity, equity, and inclusion metrics, investment in training and professional development, workplace health, safety, and well-being initiatives, work-life balance and flexible work arrangements, fair compensation and living wage practices, labor relations, and collective bargaining agreements.
[0036] In yet another exemplary embodiment, community engagement, and social impact measure metrics may include, such as, but not limited to, corporate philanthropy and community investments, local job creation and economic development, partnerships with non-profit organizations, access to essential products and services indigenous rights and community relations, support for education and skill development programs, disaster relief and humanitarian aid efforts. Customer Satisfaction and Value Creation can be measured by Net Promoter Score (NPS) or customer satisfaction ratings, product quality, safety, and reliability, customer complaint resolution and response time, customer privacy and data protection, accessibility and affordability of products/services, innovation and new product/service launches, customer retention and loyalty rates.
[0037] In an embodiment, the present invention also provides a method for analyzing stakeholders' satisfaction 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’ satisfaction;
• storing the analyzed stakeholders’ satisfaction by the server (112) through a storage architecture;
• transmitting the analyzed stakeholders’ satisfaction data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ satisfaction data on a display (106) installed and connected to the computing device (102).
[0038] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for analyzing the stakeholders' satisfaction. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, employee well-being and satisfaction metrics, work-life balance indicators for employees, skills development and career growth opportunities provided, community engagement and social impact measures, environmental sustainability initiatives and outcomes, customer satisfaction and loyalty metrics, supplier relationship health and longevity, innovation and research & development investments, job creation and local economic impact , diversity, equity and inclusion progress, employee volunteer hours and community service initiatives, health and safety improvements for workers and customers, knowledge sharing and industry contributions, stakeholder trust and reputation scores, product quality and reliability improvements, supply chain ethics and fair trade practices, digital inclusion and accessibility efforts, educational partnerships and scholarship programs, patents filed and intellectual property created, customer time/cost savings from using products/services, or a combination thereof.
[0039] 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.
[0040] 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’ satisfaction, 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.
[0041] In another 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.
[0042] In yet another 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.
[0043] In an 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.
[0044] The advantages of the present invention are enlisted herein:
• The present invention covers wide range of parameters to analyse organizational stakeholder satisfaction.
• The present invention utilizes machine learning models to offer insights on the future performance planning and decision making.
• The present invention provides improve stakeholder management by identification of stakeholders, their satisfaction, and understanding their preferences.
• The present invention provides the improvement of organization’s reputation and long term profit making strategies.
• The present invention provides machine learning based data driven insights, enabling an organization to make more informed and strategic decision.

[0045] 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:1. A stakeholder satisfaction 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’ satisfaction;
• 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’ satisfaction based on the processed input data; and
• a display (106) installed and connected to the computing device (102) to display the analyzed stakeholder satisfaction 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’ satisfaction 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 employee well-being and satisfaction metrics, work-life balance indicators for employees, skills development and career growth opportunities provided, community engagement and social impact measures, environmental sustainability initiatives and outcomes, customer satisfaction and loyalty metrics, supplier relationship health and longevity, innovation and research & development investments, job creation and local economic impact , diversity, equity and inclusion progress, employee volunteer hours and community service initiatives, health and safety improvements for workers and customers, knowledge sharing and industry contributions, stakeholder trust and reputation scores, product quality and reliability improvements, supply chain ethics and fair trade practices, digital inclusion and accessibility efforts, educational partnerships and scholarship programs, patents filed and intellectual property created, customer time/cost savings from using products/services, or a combinations 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 satisfaction 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, employees, communities, suppliers, workers, customers, members, shareholders, referral sources, distribution partners, financiers, functional areas, departments
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' satisfaction 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 (116) installed in the server (112) to analyze stakeholders’ satisfaction;
• storing the analyzed stakeholders’ satisfaction by the server (112) through a storage architecture;
• transmitting the analyzed stakeholders’ satisfaction data from the server (112) to the computing device (102) wirelessly to display the analyzed stakeholders’ satisfaction data on a display (106) installed and connected to the computing device (102).