KR102162696B1 - System and method for predicting the outcome of proposal evaluation based on big data using debriefing system - Google Patents

Abstract

Disclosed are a system and a method for predicting a proposal evaluation result based on big data using a debriefing system. The system of the present invention comprises: an order project information input module for receiving information on an order project to participate in a tender; a quantitative data storage module for storing quantitative data collected by a transfer system; and a big data-based evaluation result predicting module for analyzing the quantitative data stored in the quantitative data storage module by using information on the order project received from the order project information input module, and predicting an evaluation result of a proposal for the order project in accordance with an analysis result. According to the present invention, a proposal evaluation result for an order project to be bid in the future is predicted by using a debriefing system such that a reference for selecting whether to bid for an order is provided and data to be used for a proposal is selected and used by using an evaluation result for a past similar proposal. Therefore, ultimately, the quality of the proposal can be improved and the bidding possibility can increase.

Description

Big data based proposal evaluation result prediction system and method using the debriefing system {SYSTEM AND METHOD FOR PREDICTING THE OUTCOME OF PROPOSAL EVALUATION BASED ON BIG DATA USING DEBRIEFING SYSTEM}

The present invention relates to a system and method for predicting evaluation results, specifically, to a system and method for predicting evaluation results of proposals based on big data, and more specifically, to a system and method for predicting evaluation results of a proposal, and more specifically, to big data using a debriefing system. It is a system and method for predicting the evaluation results of proposals based on.

Prepare and submit a proposal that includes a large amount of data for order bidding in the field.

The proposal includes not only in-depth technical data in the defense industry, but also numerous evidences related to the manpower, R&D performance, contract performance, equipment status, and facility status of participating companies.

The amount of data that needs to be prepared to prepare a proposal for each order bid is vast.

A lot of effort and time is put into writing such a proposal.

However, despite this effort and time, it is not always possible to guarantee the success of the bidding.

Therefore, it is very important to select whether or not to bid for an order bidding project, and this selection can increase the efficiency of the time and effort spent on preparing a proposal.

Above all, it is important to write a proposal that can be successful in order bidding.

If you refer to examples of past proposals, evaluation results, and relevant technical fields, you can lead to better results.

The debriefing system is a system that discloses the evaluation results of order bids. The results of the debriefing evaluation can be an important reference material that enables us to gauge the likelihood of success for similar orders in the future.

However, there is still no data and data system to prepare a systematic proposal.

Unexamined Patent Publication 10-2016-0121042 Registered Patent Publication 10-0635733

An object of the present invention is to provide a system for predicting a proposal evaluation result based on big data using a debriefing system.

Another object of the present invention is to provide a method for predicting a proposal evaluation result based on big data using a debriefing system.

The system for predicting proposal evaluation results based on big data according to the object of the present invention as described above includes: an order-acceptance task information input module for receiving information on an order-acquired task to participate in a bidding; A quantitative data storage module for storing quantitative data collected from the transfer system; Based on big data that analyzes the quantitative data stored in the quantitative data storage module by using the information on the orders received from the order-winning task information input module, and predicts the evaluation result of the proposal for the order-winning task based on the analyzed result It may be configured to include a proposal evaluation result prediction module.

Here, the big data-based proposal evaluation result prediction module may be configured to provide the predicted evaluation result for use in preparing a proposal for a corresponding order-acquired project.

A method for predicting a proposal evaluation result based on big data according to another object of the present invention described above includes the steps of: receiving, by an order project information input module, information on an order received project to participate in a bidding; Storing the quantitative data collected from the transfer system in the quantitative data storage module; Analyzing, by a big data-based proposal evaluation result prediction module, the quantitative data stored in the quantitative data storage module by using the information on the order-acquired task received from the order-acquired task information input module; The big data-based proposal evaluation result prediction module may be configured to include a step of predicting the evaluation result of the proposal for the order-acquired project according to the analyzed result.

Here, the big data-based proposal evaluation result prediction module may be configured to further include the step of providing the predicted evaluation result for use in preparing a proposal for a corresponding ordered project.

According to the big data-based proposal evaluation result prediction system and method using the debriefing system described above, the debriefing system is configured to predict the evaluation result of the proposal for future orders to be bid. It has the effect of preparing the criteria for and using the evaluation results of past similar proposals to select and use data to be used for proposals.

Ultimately, it can improve the quality of the proposal and increase the possibility of bidding.

1 is a block diagram of a system for predicting a proposal evaluation result based on big data using a debriefing system according to an embodiment of the present invention.
2 to 13 are exemplary diagrams of quantitative data according to an embodiment of the present invention.
14 and 15 are exemplary views of past proposals and strategy sheets according to an embodiment of the present invention.
16 is a flowchart of a big data-based proposal evaluation result prediction method using a debriefing system according to an embodiment of the present invention.

In the present invention, various modifications may be made and various embodiments may be provided, and specific embodiments will be illustrated in the drawings and will be described in detail in specific details for carrying out the invention. However, this is not intended to limit the present invention to a specific embodiment, it is to be understood to include all changes, equivalents, and substitutes included in the spirit and scope of the present invention. In describing each drawing, similar reference numerals have been used for similar elements.

Terms such as first, second, A, and B may be used to describe various elements, but the elements should not be limited by the terms. These terms are used only for the purpose of distinguishing one component from another component. For example, without departing from the scope of the present invention, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element. The term and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

When a component is referred to as being "connected" or "connected" to another component, it is understood that it may be directly connected or connected to the other component, but other components may exist in the middle. Should be. On the other hand, when a component is referred to as being "directly connected" or "directly connected" to another component, it should be understood that there is no other component in the middle.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In the present application, terms such as "comprise" or "have" are intended to designate the presence of features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, but one or more other features. It is to be understood that the presence or addition of elements or numbers, steps, actions, components, parts, or combinations thereof, does not preclude in advance.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs. Terms as defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and should not be interpreted as an ideal or excessively formal meaning unless explicitly defined in this application. Does not.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of a system for predicting a proposal evaluation result based on big data using a debriefing system according to an embodiment of the present invention.

Referring to FIG. 1, a big data-based proposal evaluation result prediction system 100 using a debriefing system according to an embodiment of the present invention includes an order bidding project information input module 101, a quantitative data storage module 102 , Past proposal storage module 103, similar proposal search provision module 104, past proposal debriefing result storage module 105, similar proposal debriefing result provision module 106, big data-based proposal evaluation result prediction module 107 ), may be configured to include a proposal data selection module 108.

Hereinafter, a detailed configuration will be described.

The order bidding project information input module 101 may be configured to receive information on an order-acquired project to participate in the bidding. For example, it may be configured to receive information such as project ordering organization, project code name, technology classification, project name, various bidding requirements, and required documentary evidence.

The quantitative data storage module 102 may store quantitative data collected from the transfer system 10. Here, the quantitative data may include technical data holding status, similar research and development performance, equipment/facilities/tools holding status, manpower status, etc.

The technical data holding status can be composed of the status of holding the patent certificate of Fig. 2, the holding status of the program registration certificate of Fig. 3, the holding status of the paper specifying the name of the paper, author, and publishing organization shown in Fig. 4, the technical data list and supporting data of Fig. have.

Similar research and development results may include contracts and revised contracts (contract name, amount, start date, end date, ordering address, etc.) as the contract business performance illustrated in FIG. 6. In addition, it may be composed of a technology development completion report or a technology development plan as the self-task performance of FIG. 7 and may be composed of a R&D confirmation document as a part localization performance.

Equipment/facilities/tools holding status may include the equipment/facilities status currently in possession, and the detailed contents of the equipment status include a transaction statement, tax invoice, import report, equipment history card, calibration resume, photos, etc. Can include.

In addition, the equipment/facilities/tools holding status includes the status of the facilities currently in possession, and the detailed contents of the facilities can include a transaction statement, tax invoice, import declaration, facility history card, photo, facility contract, etc. have.

In addition, the equipment/facilities/tools holding status includes the status of tools currently in possession, and the detailed contents of the tools status may include a transaction statement, a tax invoice, an import declaration, and a photo as shown in FIG. 11.

As shown in FIG. 12, the status of manpower may include a certificate of experience, a certificate of enrollment in the national pension, a certificate of employment, a certificate of degree, a certificate, a resume, and the like.

In addition, as shown in FIG. 13, the quantitative data may include a quality-related certificate and certificate, a credit evaluation certificate, a credit evaluation grade confirmation, and an information protection countermeasure/security audit/measurement confirmation document as a countermeasure for preventing technology leakage.

The past proposal storage module 103 may be configured to store all past proposals that participated in the bidding in the past. 14 illustrates past proposals for the last three years, and FIG. 15 shows a strategic report for the last five years.

The similar proposal search providing module 104 may be configured to search for similar proposals among the past proposals of the past proposal storage module 103 based on various order received task information input from the order received task information input module 101. Similar proposals can be searched according to various criteria, such as similar ordering organizations, similar technology classifications or technical names, or relatively recent past proposals.

The past proposal debriefing result storage module 105 may be configured to store the result of the debriefing system to disclose evaluation data on order bidding of the defense industry. The past proposal debriefing result storage module 105 may store a debriefing result of the past proposal.

The similar proposal debriefing result providing module 106 may be configured to search and provide a debriefing result for the similar proposal searched by the similar proposal search providing module 104 by the past proposal debriefing result storage module 105. Similar proposals may be determined according to criteria such as similar technology fields, similar ordering organizations, similar technology names, and proposals within a predetermined period.

The big data-based proposal evaluation result prediction module 107 analyzes each similar proposal provided by the similar proposal search and provision module 104, and debriefs the similar proposal provided by the similar proposal debriefing result provision module 106 It can be configured to predict the evaluation result for a newly created or newly created order proposal using the result.

The big data-based proposal evaluation result prediction module 107 is to include a similarity grasping unit 107a, an acquisition score prediction unit 107b for each proposal table of contents, a strength/weakness grasp unit 107c, and a proposal evaluation result prediction unit 107d. Can be configured. Hereinafter, a detailed configuration will be described.

The similarity determining unit 107a may be configured to determine the similarity of similar proposals provided by the similar proposal search providing module 104. Similarity in technical fields, similarity in technical composition, similarity in technical use, similarity in delivery goods, etc. can be grasped. In addition, the similarity grasping unit 107a may be configured to grasp the similarity of the bidding project itself, the similarity of the ordering organization, and continuity with the past project.

The obtained score predictor 107b for each table of contents of a proposal may be configured to predict the score obtained for each table of contents of a newly created or newly prepared proposal based on a debriefing result for each table of contents of a past similar proposal.

The strengths/weaknesses grasping unit 107c reflects the score prediction results of the score prediction unit 107b obtained for each proposal table of contents based on the similarity grasped by the similarity grasping unit 107a. It can be configured to identify weaknesses.

Proposal evaluation result prediction unit 107d is the similarity identified by the similarity grasping unit 107a, the score prediction result of the score prediction unit 107b obtained for each proposal table of contents, strengths/weaknesses of the proposal identified by the strengths/weaknesses grasping unit 107c It can be configured to predict the evaluation result of a newly created or newly created proposal using weaknesses, etc.

The proposal data selection module 108 may be configured to select each proposal data from several similar proposals according to the proposal evaluation result predicted by the proposal evaluation result prediction unit 107d. In other words, it can be configured to select the contents of the table of contents that each has strengths in the A-like proposal, B-like proposal, and C-like proposal.

For example, if there are similar proposals in the 30th place and similar proposals in the 37th place as a result of the past debriefing, it may be advantageous to obtain a high score to write a proposal with a similar proposal in the 30th place. However, in some cases, even if the score is a little lower, if the similar proposal at 37th has more similarities than the similar proposal at 30th, it may be more advantageous to take a similar proposal at 37th and rewrite it even if the score is a little lower. In addition, by grasping the strengths of similar proposals at No. 30 and similar proposals at No. 37, you can select and use the necessary contents of the table of contents.

The automatic provisional proposal module 20 may be configured to automatically create a provisional proposal using the proposal data selected by the proposal data selection module 108.

16 is a flowchart of a big data-based proposal evaluation result prediction method using a debriefing system according to an embodiment of the present invention.

Referring to FIG. 16, the order-acquired task information input module 101 receives information on the order-acquired task to participate in the bidding (S101).

Next, the quantitative data collected from the transfer system is stored in the quantitative data storage module 102 (S102).

Next, the big data-based proposal evaluation result prediction module 107 analyzes the quantitative data stored in the quantitative data storage module 102 by using the information on the order-acquired task received from the order-order task information input module 101 (S103). ).

Next, the big data-based proposal evaluation result prediction module predicts the evaluation result of the proposal for the order-acquired task according to the analyzed result (S104).

Next, the big data-based proposal evaluation result prediction module 107 provides the predicted evaluation result for use in preparing a proposal for a corresponding ordered project (S105).

Although described with reference to the above embodiments, those skilled in the art can understand that various modifications and changes can be made to the present invention without departing from the spirit and scope of the present invention described in the following claims. There will be.

101: Module for entering information on order bidding assignments
102: quantitative data storage module
103: Save Past Proposal Module
104: similar proposal search providing module
105: Module for saving past proposal debriefing results
106: Similar proposal debriefing result provision module
107: Big data-based proposal evaluation result prediction module
107a: similarity grasping unit
107b: Proposal score prediction unit for each table of contents
107c: strength/weakness identification
107d: Proposal evaluation result prediction unit
108: proposal data screening module

Claims (4)

An order-acquired project information input module for receiving the project ordering organization, project code name, technology classification, project name, bidding requirements, and required supporting documents as information on the order-taking project to participate in the bidding;
Quantitative data storage module that stores technical data holding status, similar research and development results, equipment/facilities/tools holding status and manpower status as quantitative data collected from the enterprise system;
A past proposal storage module in which past proposals that participated in the bidding in the past are stored;
A similar proposal search providing module for searching for similar proposals from the past proposals of the past proposal storing module based on information on the order received project input by the order winning task information input module;
A module for storing past proposal debriefing results in which past proposals debriefing results are stored according to the debriefing system to disclose evaluation data of past proposals for order bidding of the defense industry;
A similar proposal debriefing result providing module for searching and providing a debriefing result of the similar proposals searched by the similar proposal search providing module by the past proposal debriefing result storage module;
Based on big data that analyzes the quantitative data stored in the quantitative data storage module by using the information on the orders received from the order-winning task information input module, and predicts the evaluation result of the proposal for the order-winning task based on the analyzed result Proposal evaluation result prediction module;
And a proposal data selection module for selecting proposal data from the similar proposals according to the proposal evaluation result predicted by the proposal evaluation result prediction unit,
The big data-based proposal evaluation result prediction module,
Analyzing each similar proposal provided by the similar proposal search providing module, and using the debriefing result of similar proposals provided from the similar proposal debriefing result providing module, It is configured to predict the outcome of the evaluation in advance,
The big data-based proposal evaluation result prediction module,
For similar proposals provided by the similar proposal search and provision module above, similarity in technical fields, similarity in technical composition, similarity in technical use, similarity in delivery goods, similarity in the bidding project itself, similarity in ordering organizations and continuity with past tasks A similarity grasping unit for grasping;
An acquisition score prediction unit for each table of contents of proposals for predicting an acquisition score for each table of contents of the ordered proposal to participate in the bidding based on the debriefing result for each table of contents of the past similar proposals;
A strength/weakness grasping unit for grasping strengths and weaknesses of an order-winning proposal of an order-winning project to participate in a bidding by reflecting a score prediction result of the acquisition score prediction unit for each proposal table of contents based on the similarity identified by the similarity grasping unit;
The similarity of the technical field identified in the similarity grading unit, the similarity of the technical composition, the similarity of the technical use, the similarity of the goods to be delivered, the similarity of the bidding task itself, the similarity of the ordering organization and continuity with the past tasks, and the above proposals obtained by table of contents It is configured to include a proposal evaluation result prediction unit that predicts the evaluation result of the order-winning proposal of the order-winning project to participate in the bidding by using the score prediction result of the score prediction unit and the strengths and weaknesses of the proposal identified by the strength/weakness identification unit. ,
The similar proposal search providing module,
It is configured to search for similar proposals by grasping the degree of similarity based on technology field, ordering agency, and technology name among past proposals within the latest predetermined period,
The proposal data selection module,
Based on the strengths and weaknesses identified by the strengths/weaknesses grasping unit, it is configured to select each of the contents of the proposals for each table of contents according to the scores obtained for each table of contents predicted by the prediction unit,
The above technical data holding status is,
It is composed of the current status of the patent certificate, the current status of the program registration certificate, the title of the paper, the current status of the manuscript holding the author and publisher, a list of technical data, and supporting data.
The above similar research and development results are:
Consists of a contract specifying the contract name, amount, start date, end date and ordering party as the contract business performance, a technology development completion report or technology development plan as a self-project performance, and a R&D confirmation document as part localization performance,
The above equipment/facilities/tools holdings are:
It includes the current status of equipment/facilities, and the detailed contents of the equipment status are composed of a transaction statement, tax invoice, import declaration, equipment history card, calibration resume, and equipment/facility photos.
The above equipment/facilities/tools holdings are:
As the current status of the facility, it consists of a transaction statement, tax invoice, import declaration, facility history card, facility picture and facility contract.
The above manpower status is,
It is composed of personnel's career certificate, national pension enrollment certificate, employment certificate, degree certificate, certificate and resume,
The above quantitative data,
A big data-based proposal evaluation result prediction system using a debriefing system, which consists of a quality-related certificate, accreditation, credit evaluation, credit evaluation grade confirmation, and information protection measures/security audit/measurement confirmation as a measure to prevent technology leakage. .
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