US20050033633A1 - System and method for evaluating job candidates - Google Patents

System and method for evaluating job candidates Download PDF

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US20050033633A1
US20050033633A1 US10/912,433 US91243304A US2005033633A1 US 20050033633 A1 US20050033633 A1 US 20050033633A1 US 91243304 A US91243304 A US 91243304A US 2005033633 A1 US2005033633 A1 US 2005033633A1
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candidate
survey
questions
reference
computer implemented
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Douglas LaPasta
Martha Mincer
David Ladouceur
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Skill Survey Inc
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Skillsurveycom Inc
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Assigned to SKILLSURVEY.COM, INC. reassignment SKILLSURVEY.COM, INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: LADOUCEUR, DAVID, LAPASTA, DOUGLAS G., MINCER, MARTHA
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G06Q10/105Human resources
    • G06Q10/1053Employment or hiring
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/10Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting

Abstract

Human resource system for collecting and analyzing survey data from reference providers identified by a job candidate for use by an employer. The system sends an electronic communication to the reference providers to request completion of survey questions and electronically receives the survey data from the reference providers, preferably through webpages. An analysis module combines the received survey data from the reference providers and generates a confidential candidate report for an employer which excludes identification of any ratings or comments by any reference providers. The system also generates customized interview probe questions for use during job interviews and coaching tactics for use after the hiring, based on the weak areas that have been identified from the completed surveys in order to assist the hiring manager to bring the new hires up to speed quickly and effectively.

Description

    CROSS REFERENCE TO RELATED APPLICATIONS
  • This application claims priority to U.S. provisional patent application No. 60/492,457, filed Aug. 4, 2003, which is incorporated herein by reference.
  • FIELD OF THE INVENTION
  • This invention relates to human resource management system, and more particularly to a system for collecting and analyzing information from references identified by job candidates.
  • BACKGROUND OF THE INVENTION
  • It has been estimated that errors in hiring cost companies more than 50 billion dollars per year in lost revenue, decreased productivity, squandered training expenses, legal liabilities, high turnover and other undesirable consequences. The result, in spite of the dramatic increase in the use of background checks and psychological profiles by many organizations, and the universality of selection interviews, is that annual turnover in U.S. companies of over 5,000 employees continues to be 25%. According to experts in the field, nearly 80% of turnover is caused by poor selection decisions.
  • Therefore, background checks have become even more important than in the past. One part of the background check, and more generally the hiring process, is the gathering of information from references, that is those individuals identified by a job candidate as being knowledgeable about the candidate's character and qualifications.
  • Unfortunately, traditional reference checking methods such as telephone interviews are very costly and time-consuming, require extensive training for interviewers and generally do not yield useful information due to lack of precision, lack of confidentiality and possible errors of filtering, amplification and interpretations by the intermediaries. Most important, perhaps, is the fact that in today's litigious society, business and professional reference givers are usually unwilling to provide more than basic information such as employment dates and positions held. Such information has little value in helping companies make effective hiring decisions.
  • Another problem with the conventional reference checking is that it's done very late in the hiring process, which is typically done after the candidate is hired. Ideally, it should be done during the screening and selection process. Moreover, the conventional background checking provides no guidance for the hiring manager to further explore areas of weakness in the candidate during the hiring process.
  • Therefore, it would be desirable to provide a more effective and inexpensive system and method for collecting and evaluating information provided by reference providers for job candidates. It would be also desirable to provide such a system that is substantially automated and that is used early in the hiring process.
  • SUMMARY OF THE DISCLOSURE
  • A system for collecting and analyzing survey data from reference providers identified by a job candidate for use by an employer is provided. The system includes a candidate database that stores survey data which are provided by the reference providers. A collection module running in the system sends an electronic communication to the reference providers requesting them to complete the survey questions and electronically receives the survey data. The electronic communication preferably contains a URL link that takes the reference provider to a dynamically generated webpage through which the survey data are entered.
  • An analysis module running in the system combines the received survey data from the reference providers and generates a candidate report. In one aspect, the candidate report is a confidential report which excludes identification of any ratings or comments by any reference providers. In another aspect, the system also generates customized interview probe questions for use during job interviews and coaching tactics for use after the hiring, based on the weak areas that have been identified from the completed surveys in order to assist the hiring manager to bring the new hires up to speed quickly and effectively.
  • The human resource system provides substantially automated collection and analysis which is inexpensive and yet accurate and useful.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 is a block diagram of a job candidate evaluation system according to the present invention.
  • FIG. 2 is a simplified process flow of a candidate evaluation process according to the present invention.
  • FIG. 3 illustrates a detailed process flow of a purchase and set-up step of FIG. 2.
  • FIG. 4 illustrates a detailed process flow of a candidate and reference identification step of FIG. 2.
  • FIG. 5 illustrates a detailed process flow of a collection step of FIG. 2.
  • FIG. 6 illustrates a detailed process flow of an analysis step of FIG. 2.
  • FIG. 7 illustrates a detailed process flow of a continuous update step of FIG. 2.
  • FIGS. 8A and 8B illustrate a sample survey form.
  • FIG. 9 is a sample email sent to a job candidate.
  • FIG. 10 is a sample email sent to each reference identified by the job candidate.
  • FIGS. 11A-11D illustrate a sample candidate report for use by a hiring manager.
  • FIGS. 12A-12B illustrate a sample set of interview questions for use by the hiring manager in a subsequent interview with the job candidate.
  • FIGS. 13-13C illustrate a sample set of coaching tactics for use by the hiring manager after the job candidate is hired.
  • FIG. 14 illustrates a group report which ranks multiple job candidates.
  • FIGS. 15A and 15B illustrate a sample vendor report that evaluates vendors supplying goods and services to a company.
  • FIG. 16 illustrates a sample report that shows the correlation between survey questions/competencies and performance of hired candidates.
  • DETAILED DESCRIPTION OF THE INVENTION
  • As an overview, the present invention uses a computer network such as the Internet and the resources of the network including emails and webpages to set up initial survey questions, send out emails to references identified by job candidates, collect confidential competency-based survey information via webpages from the identified references, analyze the collected information and generate candidate reports for use by a hiring manager. The system has integrated the screening and selection process with a competency based survey database that allows the comparative review of reference information against one or more candidates, the company's own employees, the industry or other normalized database by job type, organization or company competency.
  • Referring now to FIG. 1, a job candidate evaluation system 1 of the present invention involves a number of computers 10, 15 that are connected to each other through a computer network such as the Internet. The computers 10, 15 of the system 1 cooperate with each other to provide comprehensive collection and analysis of reference information that are made through the network 2. Computers 15 are similar to the computer 10, with the exception of some of the databases and software modules.
  • As illustrated in FIG. 1, the computer 10 is connected to the Internet 2 through, for example, an I/O interface 12, such as for a LAN, WAN, or fiber optic, wireless or cable link, which receives information from and sends information to other computers 15. The computer 10 is also connected to a keyboard 14 for controlling the computer.
  • The computer 10 includes, for example, memory storage 16, processor (CPU) 18, program storage 20, and data storage 22, all commonly connected to each other through a bus 24. The program storage 20 stores, among others, software programs such as set-up module 26, collection module 28, and analysis module 30 as will be explained in detail later herein. The data storage 22 stores, among others, candidate database 34, benchmark database 36 and survey database 318, all preferably stored in a relational database that relates all of the databases stored in the data storage. Any of the software program modules in the program storage 20 and data from the data storage 22 are transferred to the memory 32 as needed and is executed by the processor 18.
  • The computer 10 can be any computer such as a WINDOWS-based or UNIX-based personal computer, server, workstation or a mainframe, or a combination thereof. While the computer 10 is illustrated as a single computer unit for purposes of clarity, persons of ordinary skill in the art will appreciate that the system may comprise a group of computers which can be scaled depending on the processing load and database size and which can be remotely located to provide localized non-stop service.
  • FIG. 2 illustrates a high level process flow of the evaluation process according to the present invention. In step 42, a client company sets up an order for a job candidate or multiple candidates, and prepares one or more surveys for use in the hiring process as will be explained in detail with reference to FIG. 3. This step is executed by the set-up module 26. In the same step, the order for the job candidates is done by purchasing a certain number of candidate reports and specifying the purchase information. Purchase of one report provides unlimited generation of reports for each job candidate until the time of hire or rejection.
  • In step 44, the hiring manager identifies a job candidate and receives information about the references or reference providers that are identified by the job candidate, which include an email address for each reference as will be explained in more detail with reference to FIG. 4. A reference provider should be someone who has worked extensively with the job candidate in the past which include customers, supervisors, and peers. Step 44 is executed by the collection module 28.
  • In step 46, which is also executed by the collection module 28, the system 1 sends emails to all of the references that were identified by the job candidate. The email requests each reference to fill out the survey prepared by the hiring manager. The survey information is then collected from the identified references through web pages and stored in the survey database 38. Step 46 is more fully explained with reference to FIG. 5.
  • In step 48, executed by the analysis module 30, the system 1 analyzes the collected information and generates a report that includes the overall assessment of the candidate's competency in each of the several competency areas and includes any comments supplied by the references. Competency is a well known concept that represents a particular characteristic of an individual or organization performing a task, function or project at a particular point in time that leads to successful performance. The report can be a final report with all surveys completed by the references, or it can be a real time interim report with analysis of partially completed survey information which can be requested by the hiring manager at any time. Based on the analysis, the system 1 also generates “interview probes” for those areas where the candidate did not score as highly as others, a sample of which is shown in FIGS. 12A-12B. The probes guide an interviewer to obtain more information about the candidate's level of accomplishments or experience with regard to specific lower scoring competencies. The report may also include coaching tactics to manage and develop the candidate assuming the candidate is hired, a sample of which is shown in FIGS. 13A-13C. Like the interview probes, the coaching tactics are also based on analysis of those areas where the candidate did not score as highly as others. The coaching tactics are suggested “micro-behaviors” that the hiring manager can use to help the candidate to develop his strengths in lower-scoring competencies. Step 48 is more fully explained with reference to FIG. 6.
  • In step 50, the system 1 continuously monitors the job candidates after the hiring process. The system tracks the progress of the hired candidates and collects additional data such as performance levels of the hired candidates. The additional data for all the candidates are then analyzed to generate additional reports containing the correlation between various competencies and high retention/performance. The reports are preferably graphical in nature and graphically illustrate the competencies that are most closely correlated with the high retention/performance of the candidates. The reports can also be customized by a user to specify whether the correlation is based on position-specific, company-wide or industry-wide benchmarks as will be explained in detail with reference to FIG. 7.
  • FIG. 3 illustrates a detailed process flow of the purchase and set-up step 42 of FIG. 2. In step 52, a client company uses an Internet enabled computer 15 to access web pages of the system 1 through the Internet 2. The web pages are generated by a conventional database web page generating engine such as PHP (Hypertext Preprocessor) in conjunction with a relational database program stored in the program storage 20 and the web engine is executed by the processor 18. The Internet enabled computer 15 is equipped with a web browser capable of handling forms.
  • In step 54, order information such as the client company's address and contact information of various hiring managers working for the client company are filled out in the web page form that was generated by the computer 10. In step 56, purchase information such as the number of reports purchased and credit card data are also entered through the web page. The data entered by the client company are stored in the data storage 22. In step 58, the credit card information provided by the client company is verified and in step 60 a client record is created in a client database in the storage 22 with the contact and purchase information. The client record includes an allocation of reports to specific hiring managers and the user id and password for each hiring manager. In step 62, the computer 10 generates a confirmation message confirming the number of reports purchased and the set-up of the client company in the system 1.
  • As can be appreciated by persons of ordinary skill in the art, the above steps 52-62 are optional and can be omitted by using a billing arrangement where the client company is billed on a periodic basis for the candidate evaluation services that have been rendered.
  • FIG. 4 illustrates a detailed process flow of the candidate and reference identification step 44 of FIG. 2. When a hiring manager needs to fill a particular position, the manager accesses the computer 10 through a web browser. In step 66, the hiring manager designates a survey that is to be used for that position. The manager can choose from a set of pre-designed or pre-selected surveys stored in the data storage 22, design his own by selecting survey questions from an existing set of questions stored in the data storage, create his own set of questions, or modify an existing survey. The questions are stored in a master table in data storage 22. Each survey also has a corresponding record in the database, which points to the questions in the master table that are included for that survey. Each survey question relates to a specific job-related and validated competency, selected from a bank of competencies that have been derived, tested and validated from experience and research.
  • FIGS. 8A-8B illustrate a sample survey that is used for a management position. The survey of FIG. 8A contains 16 questions that relate to various competencies that are known to be important for a management position. For example, the fist three questions relate to a competency known as “Managing the Business”. Each of the 16 questions requires the reference to select a value of “1” through “7” by clicking on an appropriate radio button. The survey also contains two comment boxes as shown in FIG. 8B. It includes one for describing the candidate's strengths and one for describing the candidate's weaknesses.
  • Once a particular survey is selected or created, the hiring manager enters the job candidates' information in step 68 through the computer 15 and sets the required minimum number of references that must be provided by each job candidate. The entered information is stored by the computer 10 in the candidate database 34 of the data storage 22. In step 68, the computer 10 also generates a unique 16 character alphanumeric identifier for that job candidate which is also stored in the candidate database 34. The alphanumeric identifiers are used for security purposes since they ensure that only known and authorized job candidates can enter or access the information in the system 1.
  • In step 70, the computer dynamically generates a web page asking whether the reference information will be provided by the job candidate. If the hiring manager answers yes, the computer 10 in step 72 generates and send an email message to the job candidate with a URL link to a dynamically generated web page and requesting the job candidate to click on the link to provide information on the references he chooses. A sample email to a job candidate is shown in FIG. 9.
  • In step 74, the job candidate receives the email and accesses the web page generated by the computer 10 by clicking on the link provided in the email. In response, the computer transmits through the Internet 2 a sample of the survey questions for display on the candidate's computer 15 along with a dynamically generated web page form to provide information on the references. The sample survey questions assist the candidate in determining which individuals would be appropriate references. In step 76, the job candidate enters via the web page form the names, email addresses and relationship of the references. The relationship field only allows “Business” or “Professional” as “Personal” references tend to give scores that are severely skewed towards the positive, and may not have specific knowledge about the job-related competencies of the candidate. The candidate also indicates the dates and location of the relevant employment. The candidate then submits the form to the computer 10.
  • The collection module 28 of the system 10 then verifies that each email address is in a valid format and that there are no duplications. As part of the validity check, the collection module 28 checks the domain portion of each email address against the registered location using industry standard databases (WHOIS) to provide the hiring manager additional information if needed. Once the candidate is determined to have submitted a valid list, the computer 10 stores the data on references in the candidate database 34.
  • If the answer to step 70 is no, however, then the hiring manager already has the information of references. That information is entered by the hiring manager in step 78. The same type of data checking that are performed in step 76 is also performed in step 78 to ensure that no errors are made.
  • FIG. 5 illustrates a detailed process flow of the collection step of FIG. 2. In step 80, the computer 10 generates a unique identifier for each reference and send an email message to each reference explaining the purpose of the email and directing the reference to click on a URL link to a dynamically generated web page. The unique identifier is generally used internally to uniquely identify the reference within the system 1. A sample email to each reference is shown in FIG. 10. The sample email contains a statement that the operator of the system 1 will maintain strict confidentiality of responses provided by the references and that their responses will be aggregated and analyzed so that all of the information generated in a report for the hiring manager will be confidential. This statement is important because it encourages the references to provide more honest responses.
  • In step 82, the email is received by the computer 15 of the reference. In step 84, the reference accesses the web page generated by the computer 10 by clicking on the link provided in the email. In response, the computer transmits through the Internet 2 a dynamically generated web page form for display on the reference's computer 15 along with instructions on how to properly complete the form, a sample of which is shown in FIGS. 8A-8B.
  • In step 86, the job candidate enters via the web page form answers to the questions in the survey. For each question, the reference indicates the level of competency possessed by the job candidate using a seven-point scale. The reference is also shown the employment information submitted by the job candidate and is asked to confirm whether the information is accurate. The candidate then submits the completed form to the computer 10 in step 88.
  • In step 90, the collection module 28 of the system 10 stores the survey data in the survey database 38. In step 92, the collection module 28 determines whether there is a sufficient number of completed surveys to provide a meaningful report to the hiring manager. For example, in one case that requires seven references, four references might be considered to provide a meaningful report. If no, then the collection module 28 waits for additional surveys to be completed. If yes, however, step 94 is executed.
  • Alternatively, the hiring manager has three additional options at this stage. The first option is to override the minimum number of completed surveys and to request an interim candidate report reports regardless. A second option is to set a predetermined time period from the job candidate identifies the references and checking to see whether the predetermined time period has passed. If it has, then step 94 is executed. The third option is to simply allow the hiring manger to close the job candidate's record. That option may be convenient in situations such as the job candidate voluntarily withdrawing from the job opening.
  • In step 94, an email to the hiring manager is generated to let him know that at least an interim report is available, which email is received by him in step 98. In step 96, reminder emails are sent to those references that have not provided the survey data within a predetermined time period.
  • FIG. 6 illustrates a detailed process flow of the analysis step of FIG. 2. In step 100, the hiring manager accesses the web page generated by the computer 10 by either clicking on the link provided in the email or logging on to the website of the computer 10 independent of the email. At this stage, the analysis module 30 displays a “dashboard” for the current status of the job opening. The status includes the state of each candidate's progress for the completion of the reference information. In step 102, a request for report on a particular candidate is made.
  • In response, the analysis module 30 in step 104 analyzes the received survey data stored in the survey database 38 and generates a candidate report. A sample report is shown in FIGS. 11A-11D.
  • As can be seen in FIG. 11A, the report includes a list of references, email addresses, identification of company and relation to the job candidate, dates worked by the candidate and whether the survey was completed. The report also notes any changes or discrepancies between the information provided by the candidate and the reference. For example, reference named “Roger Brown” reported that the dates worked by the candidate of “02/00 To 02/03” is different from “01/00 To 02/03”. FIG. 11B explains the score for each competency in FIG. 11C which is based on benchmark scores that are stored in the benchmark database 36. The benchmark scores represent competencies that are stored on an industry-wide basis, company-wide basis or company-specific job position type basis.
  • As seen in FIG. 11C, scores for each question are averaged and converted to “very low” to a “very high” score. The scores to questions that are related to the same competency are averaged into the same “very low” to a “very high” score. For example, the average scores for questions 1-3 have been converted to a “Medium”, “High” and “Medium”, respectively. Also, the three questions are grouped into the competency of “Managing the business” and the average scores for each of questions 1-3 are averages and converted to the score of “Medium”.
  • One third of the questions where the candidate has received the lowest raw numerical averages are weak areas the analysis module has identified and are indicated using asterisks which are used as the basis for generating interview probe questions and coaching tactics as discussed below in step 106. Alternatively, the weak areas are identified by comparing an averaged score for each question against a benchmark score from the benchmark database 36 and those scores that fall below the benchmark score by a predetermined amount are identified as the weak areas and are indicated as such using asterisks.
  • To further make the report useful, it may contain three additional columns: Company Comparison, Industry Comparison and Overall Rating. The Company Comparison and Industry Comparison correspond to the benchmark scores on company-wide job type basis, and industry-wide job type basis. The Overall Rating is derived from taking the average of the raw scores from each normalized database for that job type for the company, industry or other organization and the average of responses from the candidate's reference providers. This score is converted to a verbal descriptor from very-low to very-high based on lookup table for that value. For example a 4.2-5.9 inclusive, could return a “High”, each descriptor range can be set based on selection standards.
  • As shown in FIG. 11C, questions 3, 8, 11 and 16 are highlighted using a rectangular box. The highlighted questions mean that those questions are most closely associated with high performance and retention of job candidates that have been hired which are based on a statistical analysis of performance data of the hired candidates as will be explained in detail with reference to FIG. 7.
  • The report also contains an overall average score (“High” in FIG. 11C) which is an average of scores from all the references for all of the questions. Alternatively, the analysis module 30 can use the correlation data from the continuous update step 50 of FIG. 2 and generate an overall score on a weighted scale in which the weight used for each question or competency is based on the correlation to the performance data with higher weight being used for higher correlation.
  • FIG. 11D contains the “Strengths” and “Could Improve” comments provided by the references. It is important to note that the candidate report maintains strict confidentiality of responses provided by the references. In other words, the candidate report decouples the reference individuals from the responses the reference individuals provide so as to provide anonymity of the reference individuals from the hiring company/hiring manager. This is important as it encourages the references to provide more candid responses.
  • FIG. 14 illustrates a group report which ranks multiple candidates. For each candidate, the group report includes averaged scores for each question, averaged score for each competency, and an overall summary score. The group report also includes questions 3, 8 and 16 which are highlighted using a rectangular box. The highlighted questions mean that those questions are most closely associated with high performance and retention of job candidates that have been hired which are based on a statistical analysis of performance data of the hired candidates.
  • In step 106, the hiring manager, after reviewing the report, determines whether to continue with the hiring process for the candidate. If the answer is no, then the analysis step 48 ends at step 111. If the answer is yes, the analysis step 48 continues with step 108. In step 108, the analysis module generates interview questions (see FIGS. 12A-12B) based on the identified weak areas in the report. Specifically, the interview questions are associated with the questions in the survey and are stored in the data storage 22. For each weak area, the analysis module retrieves those interview questions that are associated with the questions that correspond to the weak areas.
  • For example, the report in FIG. 11C has identified questions 1, 2, 7, 9, 12 and 13 as the weak areas. For those questions, the analysis module 30 retrieves associated interview questions from the data storage 22 as shown in FIGS. 12A-12B.
  • In step 110, the hiring manager, after having interviewed the candidate, determines whether to hire the candidate. If the decision is no, then the analysis step 48 ends. If the decision is a yes, then the analysis module in step 112 generates coaching suggestions that allow the employer to improve the identified weak areas after the candidate is hired. Like the interview questions, the coaching suggestions are associated with the questions in the survey and are stored in the data storage 22. For each weak area, the analysis module 30 retrieves those coaching suggestions that are associated with the questions that correspond to the weak areas as shown in FIGS. 13A-13C.
  • It is important to note that the steps of survey collection 46 and analysis 48 can be used in an iterative process to screen out job candidates. For example, a hiring manager might use a simple survey containing 4 questions against 100 job candidates to narrow the list down to 10 candidates, then design a new survey containing 16 questions to narrow the 10 candidates down to 3 candidates, and then design another survey containing 20 questions to select one candidate for hire. Accordingly, the present invention can be used to both as a screening tool and a selection tool.
  • FIG. 7 illustrates a detailed process flow of the continuous update step of FIG. 2 which is also part of the analysis module 30. In step 120, the computer 10 waits for a predetermined time period after the final candidate report was generated. In the embodiment shown, the predetermined time period is one month. In step 122, the computer 10 prepares and sends an email to the hiring manager with a URL link to a dynamically generated web page. The web page asks whether a particular job candidate is hired. Alternatively, the email may include two links asking the hiring manager to click on one link if the candidate was hired and to click on the other link is the candidate was not hired.
  • In step 124, the computer 10 receives the response of the hiring manager and determines whether the job candidate was hired. If no, then that fact is noted and stored in the candidate database 34 in step 126 for later analysis and reporting. If the candidate was hired, then control passes to step 128. At step 128, the computer 10 waits for a predetermined time period after the final candidate report was generated. In the embodiment shown, the predetermined time period is one year from the final report. In step 130, the computer 10 prepares and sends an email to the hiring manager with a URL link to a dynamically generated survey web page. The survey web page asks retention and performance information. In the embodiment shown, the survey web page asks two questions: (1) is the candidate still employed; and (2) how well the candidate has performed based on a survey containing multiple questions or based on a single question on a predefined scale, e.g., scale of 1-10. In step 126, the response to the two questions from the hiring manager are stored in the candidate database 34 for later analysis and reporting.
  • In step 132, the analysis module 30 analyzes the hiring data stored in the candidate database 34. Specifically, the retention and performance data are statistically correlated with the various scores received by that candidate in the surveys to identify the questions where high ratings are most closely associated with high performance and retention. The correlation can be calculated on an industry-wide position type basis, on a company-wide basis without regard to the position type or on a company-wide position type basis. Thus, when the candidate reports such as shown in FIG. 11C are generated, the questions where high ratings are most closely associated with high performance and retention are graphically indicated based on the latest data accumulated up to that point.
  • FIG. 16 illustrates a sample report that shows the correlation between survey questions/competencies and performance of hired candidates. As shown, the report includes raw correlation scores and corresponding ratings. For example, question 3 has a raw score of 4.7 and a “Very High” rating.
  • These reports can be used by the hiring manager to continuously improve the survey. For example, the hiring manager can choose to delete the two questions that have the lowest correlation to the performance data and add two new questions from the competency area that has the highest correlation to the performance data. In the example shown, the two lowest scoring questions are questions 1 and 2, and the competency area having the highest score of 4.66 is “Teamwork”.
  • Once step 132 is executed, control passes to step 128 where the computer waits a programmable amount of time usually 6 to 15 months to repeat the steps 130 to 132 to continuously monitor the performance of the job candidates that have been hired in order to continuously improve the survey questions and competency categories.
  • Application of the principles of the present invention are many. For example, principles of the survey selection, collection of responses and analysis of the responses can be used to evaluate a large number of vendors who supply products and services to a company through a group of buyers working for the company. The buyers for the company are acting as “reference providers”. A sample vendor report as shown in FIGS. 15A-15B can be used to better manage the large number of vendors.
  • The foregoing specific embodiments represent just some of the ways of practicing the present invention. Many other embodiments are possible within the spirit of the invention. Accordingly, the scope of the invention is not limited to the foregoing specification, but instead is given by the appended claims along with their full range of equivalents.

Claims (36)

1. A human resource information system employing competency based performance evaluation parameters for providing an analysis of an object person's competency to a client through interrogation of reference individuals, comprising:
a data processor,
a predetermined set of competency based questions requesting quantitative responses to provide a set of predetermined competency parameters for the object person,
an I/O interface operable to transmit through the internet a predetermined subset of said competency based questions to a set of reference individuals and to receive through the internet the responses from members of said set of reference individuals,
said data processor coupled to said I/O interface to merge the responses from the members of said set of reference individuals to provide a continuing cumulative quantitative analysis of each parameter in said subset of competency based questions,
a client terminal coupled to said client computer to permit client interrogation of said cumulative quantitative analysis,
said analysis being decoupled from the reference individuals to provide anonymity for said reference individuals.
2. The system of claim 1, wherein:
the client inputs a portion of the contents of said predetermined subset of competency based questions.
3. The system of claim 1, wherein:
said client interrogation is restricted to a stage wherein said cumulative analysis is based on more than a predetermined number of responses received from the reference individuals.
4. The system of claim 2, wherein:
said client interrogation is restricted to a stage wherein said cumulative analysis is based on more than a predetermined number of responses received from the reference individuals.
5. The system of claim 1, wherein said data processor is further operable to provide a comparison of said cumulative quantitative analysis of any one or more of said parameters to the corresponding parameter analysis to a predetermined set of individuals whose performance assessment parameters have been processed by the system.
6. The system of claim 2, wherein said data processor is further operable to provide a comparison of said cumulative quantitative analysis of any one or more of said parameters to the corresponding parameter analysis to a predetermined set of individuals whose performance assessment parameters have been processed by the system.
7. The system of claim 3, wherein said data processor is further operable to provide a comparison of said cumulative quantitative analysis of any one or more of said parameters to the corresponding parameter analysis to a predetermined set of individuals whose performance assessment parameters have been processed by the system.
8. The system of claim 4, wherein said data processor is further operable to provide a comparison of said cumulative quantitative analysis of any one or more of said parameters to the corresponding parameter analysis to a predetermined set of individuals whose performance assessment parameters have been processed by the system.
9. The system of claim 1, wherein said data processor merges the responses from the members of said set of reference individuals to provide a continuing cumulative quantitative analysis upon a request from the client.
10. A method of providing personnel analysis for a client based on competency based performance evaluation questions of an object individual comprising the steps of:
providing a set of competency based questions requesting quantitative responses to provide a set of predetermined competency parameters,
transmitting said set of questions over the internet to each member of a set of reference individuals provided by the object individual for use by a client interested in determining the object individual's competency for a given position,
receiving responses to said set of questions over the internet from members of said set of reference individuals,
merging said responses to provide a quantitative score of each of said parameters based on the quantitative responses provided for each of the parameters,
executing said step of merging continuously to provide continuous up-to-date quantitative scores,
providing said quantitative scores to a client terminal to permit continuous client interrogation of said quantitative scores subsequent to processing responses from a predetermined number of reference individuals in said step of merging.
11. The method of claim 10, wherein said step of providing said quantitative scores to a client terminal is limited to a state in said step of executing wherein responses from more than a predetermined number of reference individuals have been merged.
12. The method of claim 10, wherein executing said step of merging continuously to provide continuous up-to-date quantitative scores is performed upon a request from the client.
13. In a computer network, a computer implemented system for collecting and analyzing survey data from a plurality of reference providers identified by a job candidate for use by an employer, the system comprising:
a candidate database that stores survey data provided from a plurality of reference providers for a job candidate;
a collection module operable to send an electronic communication to the plurality of reference providers to request completion of a survey containing survey questions and to electronically receive through a computer network the survey data from the plurality of reference providers for storage in the candidate database;
an analysis module operable to combine the received survey data from the plurality of reference providers and generate a candidate report for an employer.
14. The computer implemented system according to claim 13, further comprising:
a survey database that stores a plurality of survey questions for different job types;
a set-up module that allows the employer to select a job type and customize a survey for the selected job type.
15. The computer implemented system according to claim 13, wherein the survey questions are related to competencies that represent the characteristics of an individual.
16. The computer implemented system according to claim 13, wherein the collection module is further operable to generate a web page containing the survey questions and to receive the survey data through the web page.
17. The computer implemented system according to claim 16, wherein the survey includes a plurality of questions and an answer to each of the plurality of questions is a number within a numerical range and the collection module generates a graphical button for each number in the numerical range through which the survey data are collected.
18. The computer implemented system according to claim 13, wherein the collection module is operable to provide status information regarding the progress of completing the survey questions by the reference providers.
19. The computer implemented system according to claim 13, wherein the analysis module generates the candidate report which contains a score for each survey question, the score representing an average of all answers to the each question by the plurality of reference providers.
20. The computer implemented system according to claim 13, wherein the survey questions are grouped into categories, and the analysis module generates a candidate report which contains a score for each category, the score being based on answers from the plurality of reference providers to all questions that belong to the each category.
21. The computer implemented system according to claim 13, wherein the analysis module generates the candidate report which contains an identification of weak areas for the job candidate based on benchmark scores.
22. The computer implemented system according to claim 13, wherein the analysis module generates the candidate report which contains an identification of weak areas for the job candidate based on benchmark scores and which contains interview questions that allow the employer to further explorer the identified weak areas during a subsequent interview with the job candidate.
23. The computer implemented system according to claim 13, wherein the analysis module generates the candidate report which contains an identification of weak areas for the candidate based on benchmark scores and which contains coaching suggestions that allow the employer to improve the identified weak areas after the candidate is hired.
24. The computer implemented system according to claim 13, wherein the analysis module generates a group candidate report which ranks multiple candidates.
25. The computer implemented system according to claim 13, wherein the analysis module upon request is operable to generate an interim candidate report that includes all of the survey data that have been provided by the reference providers.
26. The computer implemented system according to claim 13, wherein the analysis module generates a report that correlates the survey questions to performance of hired candidates.
27. In a computer network, a computer implemented system for collecting and analyzing survey data from a plurality of reference providers identified by a job candidate for use by an employer, the system comprising:
a candidate database that stores survey data provided from a plurality of reference providers for a job candidate, the survey data representing responses to a survey containing a predetermined set of survey questions;
a benchmark database that contains benchmark data;
a collection module operable to send an electronic communication to the plurality of reference providers to request completion of survey questions and to electronically receive survey data from the plurality of reference providers through a computer network;
an analysis module operable to compare the received survey data against the benchmark database and generate a candidate report based on the comparison, the candidate report being anonymous so that the identities of the reference providers are excluded from the candidate report.
28. The computer implemented system according to claim 27, wherein the collection module is further operable to dynamically generate a web page containing the survey questions and to receive the survey data through the web page.
29. The computer implemented system according to claim 28, wherein the survey includes a plurality of questions and an answer to each of the plurality of questions is a number within a numerical range and the collection module generates a graphical button for each number in the numerical range through which the survey data are collected.
30. The computer implemented system according to claim 27, wherein the analysis module generates the candidate report which contains a score for each survey question, the score representing an average of all answers to the each question by the plurality of reference providers.
31. The computer implemented system according to claim 27, wherein the analysis module generates the candidate report which contains an identification of weak areas for the job candidate based on the benchmark data.
32. The computer implemented system according to claim 27, wherein the analysis module analyzes performance data of hired candidates and generates a report that correlates the survey questions to performance of the hired candidates.
33. A computer implemented method of collecting and analyzing survey data from a plurality of reference providers identified by a job candidate for use by an employer, the method comprising:
sending an electronic communication to a plurality of reference providers for a job candidate to request completion of survey questions;
electronically receiving through a computer network the survey data from the plurality of reference providers for storage in the candidate database; and
combining the received survey data from the plurality of reference providers and generating a candidate report for an employer.
34. The method according to claim 33, further comprising generating a web page containing the survey questions and the step of electronically receives the survey data through the web page.
35. The computer implemented system according to claim 33, wherein the step of generating a candidate report includes generating the candidate report which contains an identification of weak areas for the job candidate based on benchmark scores.
36. The computer implemented system according to claim 33, wherein the step of generating a candidate report includes generating the candidate report which contains an identification of weak areas for the job candidate based on benchmark scores and which contains interview questions that allow the employer to further explorer the identified weak areas during a subsequent interview with the job candidate.
US10/912,433 2003-08-04 2004-08-04 System and method for evaluating job candidates Abandoned US20050033633A1 (en)

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US14/275,633 US20140250025A1 (en) 2003-08-04 2014-05-12 System and method for evaluating job candidates
US14/476,448 US8939768B2 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/476,403 US8888496B1 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/476,425 US8894416B1 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/805,201 US20150324750A1 (en) 2003-08-04 2015-07-21 System and method for evaluating job candidates
US15/444,737 US20170169395A1 (en) 2003-08-04 2017-02-28 System and method for evaluating job candidates
US15/828,000 US20180158028A1 (en) 2003-08-04 2017-11-30 System and method for evaluating job candidates
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US14/275,633 Abandoned US20140250025A1 (en) 2003-08-04 2014-05-12 System and method for evaluating job candidates
US14/476,403 Active US8888496B1 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/476,448 Active US8939768B2 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/476,425 Expired - Fee Related US8894416B1 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
US14/805,201 Abandoned US20150324750A1 (en) 2003-08-04 2015-07-21 System and method for evaluating job candidates
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US14/476,403 Active US8888496B1 (en) 2003-08-04 2014-09-03 System and method for evaluating job candidates
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US8721340B2 (en) 2014-05-13
US20190050816A1 (en) 2019-02-14
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US8939768B2 (en) 2015-01-27
US20140250025A1 (en) 2014-09-04
US20140372332A1 (en) 2014-12-18
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