Performance evaluation through benchmarking using an on-line questionnaire based system and method

• US 6,877,034 B1
• Filed: 08/31/2000
• Issued: 04/05/2005
• Est. Priority Date: 08/31/2000
• Status: Active Grant

• Current Assignee: Benchmark Portal Incorporated
• Original Assignee: Benchmark Portal Incorporated
• Inventors: Anton, Jon, Machin, David R.
• Primary Examiner(s): Prieto, Beatriz
• Application Number:
  US09/652,029
• Time in Patent Office: 1,678 Days
• Field of Search: 709/223, 709/224, 706/20, 706/50, 706/934, 706/925, 705/10, 705/416, 702/127, 702/182, 702/188, 707/101
• US Class Current: 709/223
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

An on-line benchmarking system and method that enables requesting users to define customized peer groups within an extensive database of participants, and to be compared with such customized groups in a wide range of performance categories. The system and method incorporates a range of detailed reporting options that not only present comparison data, but also financially quantify performance gaps and identify and rank a range of solution options.

Claims

1. A computerized method for conducting on-line benchmarking using a distributed computer network to connect a plurality of participants with computers to a host web site and host web site database, comprising the steps of:

receiving data from a user over the distributed computer network;

inputting, at the host site, the data to the database;

performing, using software at the host site, a data validity check on the database to identify suspect data;

confirming, on an automated basis, a validity status of the suspect data;

deleting data confirmed by the validity status check to be incorrect;

killing gaps in the database created by the step of data deletion, using software, to create a gap-killed database;

identifying a peer group;

generating, on an automated basis using the gap-killed database, a report comparing user data with data associated with said peer group.

2. The method as set forth in claim 1, the step of receiving data including the step of presenting to a user accessing the host site via the distributed computer network with a data input questionnaire.

3. The method as set forth in claim 1, the step of receiving data including the step of receiving electronic mail from the user over the distributed computer network, said electronic mail containing user data and being generated automatically by a user system.

4. The method as set forth in claim 3, the step of inputting the data being done automatically and including the step of extracting the user data from said electronic mail using a customized module.

5. The method as set forth in claim 1, further comprising after the step of inputting, the steps of:

copying the database to a mirror database; and

performing all subsequent steps using the mirror database.

6. The method as set forth in claim 1, the step of performing a data validity check comprising the step of comparing a data value to a predetermined data comparator range.

7. The method as set forth in claim 6, the step of confirming a validity status comprising the steps of:

generating, on an automated basis, electronic mail to each user from which data believed to be incorrect was originally received;

receiving from each user, on an automated basis, data validity status.

8. The method as set forth in claim 7, further comprising the steps of:

deleting data confirmed by a user to be invalid; and

modifying the data comparator range for data confirmed by the user to be valid.

9. The method as set forth in claim 1, the step of killing gaps in the database comprising the steps of:

selecting at least one data index from the database;

scanning the database to identify records in which the identified data index has been answered;

deleting records in which the identified data index is blank to leave a remaining set of records;

analyzing, for a current record having a gap and an associated gap index, a value of the identified data index;

comparing the value of the identified data index in the current record to corresponding values of the identified data index in the remaining set of records;

selecting from the remaining set of records those records whose corresponding values of the identified data index are within a preset number of standard deviations from the value of the identified data index in the current record; and

filling the gap using the selected records.

10. The method as set forth in claim 9, the step of filling comprising the steps of:

inserting an average value of the gap index values from the selected records when the gap index value is a real number;

determining a most likely response value in view of the gap index values from the selected records, and inserting the most likely response value, when the gap index value is a nominal value.

11. The method as set forth in claim 1, the step of identifying a peer group including the steps of:

comparing, by the host site, identification data received from the user with corresponding identification data received from other participants; and

selecting from the other participants a group of participants having identification data comparable with the identification data received from the user, the group of participants selected forming the peer group.

12. The method as set forth in claim 1, the step of identifying a peer group including the steps of:

receiving, by the host site, peer group identification parameters specified by the user;

matching, by the host site, the peer group identification parameters with records in the database meeting the parameters, the records meeting the specified parameters forming the peer group.

13. The method as set forth in claim 1, further comprising the steps of:

receiving, by the host site, data parameters specified by a user, said data parameters including at least one database index and at least one qualifying limitation; and

generating a report containing database values associated with said index and said limitation.

14. The method as set forth in claim 1, the step of generating comprising the steps of:

identifying a performance gap between said user data and data associated with said peer group;

identifying a plurality of solutions to close said performance gap;

measuring, for each of said plurality of solutions, a cost to implement, a time to implement, a risk to implement, and a return on investment to implement;

taking a weighted average of said cost, time, risk and ROI to determine an optimal solution from among said plurality of solutions.

15. The method as set forth in claim 1, the step of generating comprising the steps of:

identifying a plurality of performance gaps between said user data and data associated with said peer group;

converting each of said plurality of performance gaps into a respective monetary value; and

comparing the respective monetary values to determine a performance gap resulting in a largest financial loss.

16. A system for conducting on-line benchmarking comprising:

means for receiving data over a distributed computer network and for inputting said data to a database;

means for performing a data validity check on the database to identify suspect data;

means for confirming, on an automated basis, a validity status of the suspect data and for deleting data confirmed to be incorrect;

means for killing gaps in the database created by data deletion to create a gap-killed database;

means for defining a peer group;

means for generating, on an automated basis using the gap-killed database, a report comparing user data with data associated with said peer group.

17. The system as set forth in claim 16, said database including a mirror database representing a copy of said database and being regenerated on a regular basis, said data validity check being performed on said mirror database.

18. The system as set forth in claim 17, said means for confirming including a delinquent data checker for checking data validity of said mirror database, said delinquent data checker automatically initiating electronic mail to the user in response to suspect data.

19. The system as set forth in claim 17, said means for killing gaps including a gap killer for selecting database records within a preset number of standard deviations from an identified data index having a gap, and for filling the gap using values from the selected records.