U.S. patent application number 13/690691 was filed with the patent office on 2013-08-01 for system and method for creating a dynamic customized employment profile and subsequent use thereof.
This patent application is currently assigned to Clearfit Inc.. The applicant listed for this patent is Clearfit Inc.. Invention is credited to Ben Baldwin, Jamie Schneiderman.
Application Number | 20130198098 13/690691 |
Document ID | / |
Family ID | 41060238 |
Filed Date | 2013-08-01 |
United States Patent
Application |
20130198098 |
Kind Code |
A1 |
Schneiderman; Jamie ; et
al. |
August 1, 2013 |
SYSTEM AND METHOD FOR CREATING A DYNAMIC CUSTOMIZED EMPLOYMENT
PROFILE AND SUBSEQUENT USE THEREOF
Abstract
A system and method for dynamically generating a customized
profile for a company for a selected profile type, the customized
profile including a set of attribute types, each of the attribute
types having a customized attribute range. The system comprises a
receipt module for receiving a predefined profile having predefined
attribute types corresponding to the set of attribute types. Each
of the predefined attribute types has a predefined attribute range
representing a range of attribute values for the selected profile
type, and for receiving personal assessments of individuals related
to the company. Each of the personal assessments has questions
related to attributes. Each of the questions has a value assigned
by the respective related individual.
Inventors: |
Schneiderman; Jamie;
(Toronto, CA) ; Baldwin; Ben; (Toronto,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Clearfit Inc.; |
Toronto |
|
CA |
|
|
Assignee: |
Clearfit Inc.
Toronto
CA
|
Family ID: |
41060238 |
Appl. No.: |
13/690691 |
Filed: |
November 30, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
12400569 |
Mar 9, 2009 |
8346569 |
|
|
13690691 |
|
|
|
|
61064521 |
Mar 10, 2008 |
|
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Current U.S.
Class: |
705/320 |
Current CPC
Class: |
G06Q 30/08 20130101;
G06Q 10/105 20130101; G06Q 50/01 20130101 |
Class at
Publication: |
705/320 |
International
Class: |
G06Q 10/10 20120101
G06Q010/10 |
Claims
1-21. (canceled)
22. A system for dynamically generating a customized profile for a
company for a selected profile type, the customized profile
including a set of attribute types, each of the attribute types
having a customized attribute range, the system comprising a
receipt module for receiving a standard profile corresponding to
the selected profile type, the standard profile having standard
attribute types having a standard attribute range representing a
standard range of attribute values for the selected profile type,
such that each of the standard range of attribute values of the
standard profile is based on industry wide employee profiles
representing an industry benchmark for a plurality of companies, a
profile module for calculating determined attribute ranges for each
of the standard attribute types based on assessment values of the
questions, the determined attribute ranges corresponding to the
standard attribute types, and for generating customized attribute
ranges by combining the determined attribute ranges with the
standard attribute ranges by using a weighted combination of the
determined attribute ranges and the standard attribute ranges, the
weighted combination including an unequal weighting between the
determined attribute ranges and the standard attribute ranges, and
an output module adapted for providing the generated customized
ranges as the customized profile.
23. The system of claim 22, wherein a weighted combination for said
combining is based on a number of related individuals of the
company represented in a plurality of personal assessments,
providing the assessment questions such that the actual number of
related individuals represented in the plurality of personal
assessments or a reduced or otherwise revised number of related
individuals based on comparison of the number of related
individuals to a determined inclusion number threshold.
24. The system of claim 23 further comprising a plurality of filter
settings affecting the combination of the determined attribute
ranges with the predefined attribute ranges.
25. The system of claim 24, wherein the plurality of filter
settings is selected from the group comprising a weighted
combination based on minimum number of the related individuals
providing the plurality of personal assessments, an indication of
one or more of the related individuals to include in the
combination, an indication of one or more of the related
individuals to exclude in the combination, and an indication of a
performance rating assigned to one or more of the related
individuals for use in either excluding or including the respective
related individual in the combination.
26. The system of claim 25, wherein the indication is assigned by
the company to the one or more related individuals.
27. The system of claim 26, wherein the related individuals are
current or past employees of the company and the predefined
attribute range represents the range of attribute values for
individuals outside of the company.
28. The system of claim 22, wherein the selected profile type is
selected from the group comprising a defined employment position,
and a representative employment position as a combination of
defined employment definitions.
29. The system of claim 28, wherein the representative employment
position is a company department or grouping of company
departments.
30. The system of claim 22, further comprising selecting personal
assessments corresponding to one or more of the related individuals
and removing the corresponding attribute values from the
combination.
31. The system of claim 30, wherein the removal is based on the
selected one or more related individuals considered as outside of a
representative value of the determined attribute ranges.
32. The system of claim 31, wherein the representative value is an
average.
33. The system of claim 22, wherein the customized profile is one
of a plurality of customized profiles stored in a memory.
34. The system of claim 33 further comprising combining two or more
of the plurality of customized profiles to generate an aggregated
customized profile.
35. The system of claim 34, further comprising comparing at least
one of a plurality of aggregated customized profiles with one
another or a selected customized profile with one or more
aggregated profiles, the comparison for identifying a dynamic shift
in time in general company staff values associated with the
personal assessments.
36. The system of claim 35, wherein the comparison includes
historical aggregate customized profiles or a minimum company
desired attribute value for specified key attribute.
37. The system of claim 35, further comprising periodically
monitoring the dynamic shift in time in general company staff
values associated with the personal assessments.
38. The system of claim 22, wherein the customized profile has an
arcuate shape and a plurality of wedges distributed around a
central region of the arcuate shape, such that each of the
plurality of wedges represents one of the predefined attribute
ranges.
39. The system of claim 38, wherein each of the predefined
attribute ranges extends from an inner boundary to an outer
boundary in the respective wedge, such that the inner boundary is
distanced from the central region towards a periphery of the
arcuate shape and the outer boundary is distanced from the
periphery of the arcuate shape towards the central region.
40. The system of claim 39, wherein the arcuate shape is a
circle.
41. The system of claim 22, wherein said combining the determined
attribute ranges with the standard attribute ranges uses a weighted
combination of the determined attribute ranges and the standard
attribute ranges.
42. The system of claim 41, wherein the weighted combination
includes an unequal weighting between the determined attribute
ranges and the standard attribute ranges.
43. A method for dynamically generating a customized profile for a
company for a selected profile type, the customized profile
including a set of attribute types, each of the attribute types
having a customized attribute range, the method comprising
instructions stored on a memory and executable by a computer
processor, the instructions comprising receiving a standard profile
corresponding to the selected profile type, the standard profile
having standard attribute types corresponding to the set of
attribute types, each of the standard attribute types having a
standard attribute range representing a standard range of attribute
values for the selected profile type, such that each of the
standard range of attribute values of the standard profile is based
on industry wide employee profiles representing an industry
benchmark for a plurality of companies, calculating, using the
computer processor, determined attribute ranges for each of the
standard attribute types of the set of attribute types based on
values of assessment questions, the determined attribute ranges
corresponding to the standard attribute types, generating, using
the computer processor, customized attribute ranges by combining
the determined attribute ranges with the standard attribute ranges,
and providing the generated customized ranges as the customized
profile.
44. The method of claim 43, wherein said combining the determined
attribute ranges with the standard attribute ranges uses a weighted
combination of the determined attribute ranges and the standard
attribute ranges.
45. The method of claim 44, wherein the weighted combination
includes an unequal weighting between the determined attribute
ranges and the standard attribute ranges.
46. The method of claim 44, wherein the weighted combination is
determined based only on the determined attribute ranges obtained
from the values of the questions.
Description
CROSS-REFERENCE TO RELATED APPLICATION PARAGRAPH
[0001] This application is a continuation of U.S. Non-Provisional
application Ser. No. 12/400,569 filed on Mar. 9, 2009 that claims
the benefit of U.S. Provisional Application No. 61/064,521 filed on
Mar. 10, 2008, the content of which is hereby incorporated by
reference in its entirety.
FIELD
[0002] This invention relates to generation of profiles and use of
profiles to assess individuals such as employment candidates or
employees.
BACKGROUND
[0003] In today's world, the process of evaluating employment
candidates and employees for a company can be a daunting exercise
that can include a thorough manual investigation of all candidate
resumes received, which is considered inefficient and inaccurate.
It is recognised that effective employee selection and subsequent
employee hiring are key elements related to employee retention and
reduction of employee turnover. In addition, it is recognised that
there is a need for monitoring company culture and providing
updated reassessment and employee benchmarking in situations where
the cultural rate of change inside an organization is significant,
which can be done during annual employee reviews. It can be
important for a company to customize around their own employees
because each company and corresponding culture can be different.
Accordingly, the ability to benchmark accurately and to have an
ability to dynamically change benchmarking standards for a company
can be key to performance of the company in their market niche.
[0004] Companies also recognize that company culture is perpetuated
based on the employee make-up of the company. In areas where
company culture is identified as deviating from a desired standard,
companies tend to seek out and hire leadership individuals with
perceived beneficial traits to help get their company culture back
on the right track, e.g. increasing devaluation of a company's
stock in light of a perceived high performance, innovation driven
culture of the company which indicates a change in leadership may
be necessary. However, in view of ever increasing fluctuation in
employee loyalty behaviours to their employers, the current makeup
of company employees may be incompatible or otherwise out of sync,
at least partly, with the perceived beneficial traits of the newly
hired person (e.g. people in management) Therefore, it is even more
important in today's business to know what the overall character of
a company's employee makeup is through benchmarking, in order to
help recognize any dynamic evolutions in employee character and
ability.
[0005] Currently, employers use personality assessments to help
improve accuracy, but the process of customizing their personality
assessment to their job is still considered inefficient. Employers
(in particular small businesses) require an inexpensive,
easy-to-use, self-serve methodology for customizing their online
personality assessment to their own unique job. In particular, the
process of customizing the assessment using an organization's own
employees (benchmarking) can be particularly cumbersome. In terms
of larger businesses, the ability to have an efficient benchmarking
process that can be dynamically created and revised to correspond
to the ever changing employment needs of the company, is
desired.
[0006] Unfortunately, existing candidate and employee review
processes have a heavy manual component both from company staff and
their opinion, plus involvement of an employment consultant and
their "expertise" in trying to create a benchmark for the company's
job posting, based on a manual analysis of a plurality of
employment traits for selected company employees. The consultants
take all the employee data and use their best judgment to create
the ideal benchmark for the company employment position (i.e. job
posting) to be advertised. Each benchmark varies both by the data
inputs as well as through the individuals (from the company and/or
hired consultants) making the decision/influencing the process. One
disadvantage of the current benchmarking processes is that they can
be only suited to companies with a large, relatively static number
of employees from which to help create the benchmark. Further, the
creation of benchmarks can involve an inefficient use of company
resources, which would be better spent in attending to daily
affairs of the company. Further, current hiring practices using
benchmarks can be inefficient, requiring the review of a large
number of candidate resumes that match the benchmark, as well as
associated interview time.
SUMMARY
[0007] Accordingly, it is recognised that current customization
methodologies for benchmark creation are not practical self-serve,
involve a cumbersome process and often require manual intervention
from an expert in the field.
[0008] It is an object of the present invention to provide a
profile customization environment to obviate or mitigate at least
some of the above-presented disadvantages.
[0009] Currently, employers use personality assessments to help
improve accuracy, but the process of customizing their personality
assessment to their job is still considered inefficient. Employers
(in particular small businesses) require an inexpensive,
easy-to-use, self-serve methodology for customizing their online
personality assessment to their own unique job. In particular, the
process of customizing the assessment using an organization's own
employees (benchmarking) can be particularly cumbersome. In terms
of larger businesses, the ability to have an efficient benchmarking
process that can be dynamically created and revised to correspond
to the ever changing employment needs of the company, is desired.
Contrary to current benchmarking system, there is provided a system
and method for A system for dynamically generating a customized
profile for a company for a selected profile type, the customized
profile including a set of attribute types, each of the attribute
types having a customized attribute range. The system comprises a
receipt module adapted for receiving a predefined profile
corresponding to the selected profile type, the predefined profile
having predefined attribute types corresponding to the set of
attribute types, each of the predefined attribute types having a
predefined attribute range representing a range of attribute values
for the selected profile type, and adapted for receiving a
plurality of personal assessments of individuals related to the
company, each of the personal assessments having questions related
to one or more attributes of the set of attribute types, each of
the questions having a value assigned by the respective related
individual. The system also comprises a profile module adapted for
calculating determined attribute ranges for each of the attribute
types of the set of attribute types based on the values of the
questions, and adapted for generating customized attribute ranges
as a combination of the determined attribute ranges with the
predefined attribute ranges. The system also comprises an output
module adapted for storing the generated customized ranges as the
customized profile.
[0010] An aspect provided is a system for dynamically generating a
customized profile for a company for a selected profile type, the
customized profile including a set of attribute types, each of the
attribute types having a customized attribute range, the system
comprising: a receipt module adapted for receiving a predefined
profile corresponding to the selected profile type, the predefined
profile having predefined attribute types corresponding to the set
of attribute types, each of the predefined attribute types having a
predefined attribute range representing a range of attribute values
for the selected profile type, and adapted for receiving a
plurality of personal assessments of individuals related to the
company, each of the personal assessments having questions related
to one or more attributes of the set of attribute types, each of
the questions having a value assigned by the respective related
individual; a profile module adapted for calculating determined
attribute ranges for each of the attribute types of the set of
attribute types based on the values of the questions, and adapted
for generating customized attribute ranges as a combination of the
determined attribute ranges with the predefined attribute ranges;
and an output module adapted for storing the generated customized
ranges as the customized profile.
[0011] A further aspect provided is where the combination is a
weighted combination of the determined attribute ranges and the
predefined attribute ranges, and can be based on a number of
related individuals of the company represented in the plurality of
personal assessments, such that the profile uses the actual number
of related individuals represented in the plurality of personal
assessments or a reduced or otherwise revised number of related
individuals based on comparison of the number of related
individuals to a determined inclusion number threshold.
[0012] A further aspect provided is the profile module adapted for
selecting personal assessments corresponding to one or more of the
related individuals and removing the corresponding attribute values
from the combination, wherein the removal is based on the selected
one or more related individuals considered as outside of a
representative inclusion value of the determined attribute
ranges.
[0013] A still further aspect is an aggregator module adapted for
combining two or more of the plurality of customized profiles to
generate an aggregated customized profile, wherein the aggregator
module is adapted for comparing at least one of a plurality of
aggregated customized profiles with one another or a selected
customized profile with one or more aggregated profiles, the
comparison for identifying a dynamic shift in time in general
company staff values associated with the personal assessments.
[0014] A still further aspect is a method for dynamically
generating a customized profile for a company for a selected
profile type, the customized profile including a set of attribute
types, each of the attribute types having a customized attribute
range, the method comprising instructions stored on a memory and
executable by a computer processor, the instructions comprising:
receiving a predefined profile corresponding to the selected
profile type, the predefined profile having predefined attribute
types corresponding to the set of attribute types, each of the
predefined attribute types having a predefined attribute range
representing a range of attribute values for the selected profile
type; receiving a plurality of personal assessments of individuals
related to the company, each of the personal assessments having
questions related to one or more attributes of the set of attribute
types, each of the questions having a value assigned by the
respective related individual; calculating determined attribute
ranges for each of the attribute types of the set of attribute
types based on the values of the questions; generating customized
attribute ranges as a combination of the determined attribute
ranges with the predefined attribute ranges; and storing the
generated customized ranges as the customized profile.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Exemplary embodiments of the invention will now be described
in conjunction with the following drawings, by way of example only,
in which:
[0016] FIG. 1 is a block diagram of components of an employment
profile generation and matching environment;
[0017] FIG. 2a shows an example customized employment
profile/benchmark of the environment of FIG. 1;
[0018] FIG. 2b shows an example standard employment
profile/benchmark of the environment of FIG. 1;
[0019] FIG. 2c shows an example individual candidate or employee
employment profile scores based on the customized profile of FIG.
2b;
[0020] FIG. 3 shows an example block diagram of the customization
engine of FIG. 1;
[0021] FIG. 4a is a flowchart of an example general operation of
the framework of the environment of FIG. 1;
[0022] FIG. 4b is a further embodiment of the general operation of
FIG. 4a;
[0023] FIG. 5 is a block diagram of an example computing device for
implementing the components of the environment of FIG. 1;
[0024] FIG. 6 shows example attributes with score scale for the
attributes of the employment profiles of FIGS. 2 and 3;
[0025] FIG. 7 is an example user interface as a Web page supplied
by the framework of FIG. 1;
[0026] FIG. 8 is a further example user interface as a Web page
supplied by the framework of FIG. 1;
[0027] FIG. 9 is a further example user interface as a Web page
supplied by the framework of FIG. 1;
[0028] FIG. 10 is a further example user interface as a Web page
supplied by the framework of FIG. 1;
[0029] FIG. 11 is an example block configuration of the framework
of the environment of FIG. 1;
[0030] FIG. 12 is a flowchart of an example operation of the
profile generator module of the framework of FIG. 11;
[0031] FIG. 13 is a flowchart of an example operation of the
candidate module of the framework of FIG. 11;
[0032] FIG. 14 is a flowchart of an example operation of the
matching module of the framework of FIG. 11;
[0033] FIG. 15 shows a list of example psychological attributes of
the system of FIG. 1;
[0034] FIG. 16 shows an example Look Up Table for Determining
w(BE); and
[0035] FIG. 17 shows a flowchart of an example operation of the
customization engine of FIG. 3.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT(S)
[0036] It is recognised in the following description, it may be
advantageous to set forth definitions of certain words and phrases
used throughout this patent document, such as: the terms "include"
and "comprise," as well as derivatives thereof, mean inclusion
without limitation; the term "or," can be inclusive, meaning
and/or; the phrases "associated with" and "associated therewith,"
as well as derivatives thereof, may mean to include, be included
within, interconnect with, contain, be contained within, connect to
or with, couple to or with, be communicable with, cooperate with,
interleave, juxtapose, be proximate to, be bound to or with, have,
have a property of, or the like; and the term "controller" "engine"
or "module" or "processor" means any device, system or part thereof
that controls at least one operation, such a device may be
implemented in hardware, firmware or software, or some combination
of at least two of the same. It should be noted that the
functionality associated with any particular "controller" "engine"
or "module" or "processor" may be centralized or distributed,
whether locally or remotely in the environment 10. Definitions for
certain words and phrases are provided throughout this patent
document, those of ordinary skill in the art should understand that
in many, if not most instances, such definitions apply to prior, as
well as future uses of such defined words and phrases.
Employment Determination Environment 10
[0037] Referring to FIG. 1, shown is an employment determination
environment 10 for generating a plurality of customized profiles
107 (e.g. job/position/company/department benchmarks--see FIG. 2a)
for companies 104, based on a selected predefined profile 100 (e.g.
industry job/position/company/department benchmarks--see FIG. 2b)
and employee information 105 that contains answers to personal
assessments 99 completed by employees of the respective companies
104. For example, it is recognised that the predefined profile 100
can be based on industry wide employee profile(s). Further, the
customized profiles 107 for a company 104 are a result of selected
personal assessment 99 results and can include other employment
definition information 98 (e.g. desired work experience, academic
qualifications, etc) contained in the employee information 105
submitted by the company 104, combined with one or more predefined
profile(s) 100, as implemented on a customization engine 250, for
example as separate from the framework 112 or as integrated with
the framework 112, as further described below.
[0038] The employee information 105 of the companies 104 includes
answers to a plurality of questions contained in the assessments 99
and can include other employment definition information 98 (e.g.
desired work experience, academic qualifications, etc). It is
recognised that the employee information 105 can be supplied by the
company to an employment framework 112 that helps to generate the
employment profiles 107, the employee information 105 can be
supplied directly by the company employees (e.g. via a network
device 101 coupled to the framework via a network 11 to the
employment definition framework 112, or a combination thereof. Also
included in the framework 112 (i.e. stored in a database 110) are
employment definitions 102 (e.g. job/position postings) that are
published for access by a plurality of employment candidates 114,
as further described below. It is recognised that the employment
definitions 102 can be associated with a corresponding one of the
employment profiles 107, as further described below.
[0039] Referring again to FIGS. 1 and 2c, once the customized
profiles 107 for the company 104 are generated by the customization
engine 250, a plurality of employment candidates 114 can
communicate with the framework 112 over a network 11, in order to
complete respective candidate assessments 99 and can include other
employment definition information 98 for use in determining a
respective candidate profile 108. It is recognised that the
candidate profile 108 can optionally include other employment
definition information 98 (e.g. desired work experience, academic
qualifications, etc). The completed candidate profile 108 (e.g. as
generated by the framework 112) can be used by the candidate 114 in
applying for selected employment definitions 102 (e.g. including
the customized profile 107 generated by the customization engine
250 on behalf of the company 104) as posted by the company 104 on
the framework 112, for access by the potential job candidates 114.
The generated candidate profile 108 can be based on the customized
employment profile 107 that is associated with the employment
definition 102, as selected by the candidate 114 from a list of
posted employment definitions 102, or as a result of an invitation
by the company 104 (or other entity, e.g. recruitment agency--not
shown) to complete as part of job application to the employer 104.
It is also recognised that the candidate profile 108 can be based
on the candidate's 114 general traits alone, in addition to their
comparison with the customized employment profile 107 for fit.
[0040] Communications between the company 104, the framework 112,
and the candidates 114 are facilitated via one or more
communication networks 11 (such as intranets and/or extranets--e.g.
the Internet). The employment determination environment 10 can
include multiple companies 104, one or more frameworks 112 (e.g.
each framework directed to a specified geographical region), a
plurality of candidates 114, and respective multiple hosting
devices 101, as desired. Examples of the devices 101 are provided
below (see FIG. 5).
[0041] Accordingly, in view of the above, it is recognised that the
framework 112 and associated customization engine 250 facilitate a
self-serve methodology for allowing companies 104 to customize
their online personality assessments (e.g. customized profiles 107)
that are directly related to their own unique job(s) of their
company 104, based at least in part on one or more selected
industry benchmarks 100 and employee data 99 and may or may not
include other employment definition information 98 (e.g. desired
work experience, academic qualifications, etc) collected from
company employees that are considered as having
employment/character traits that are related to the job(s) for
which the customized profile 107 is generated. It is recognised
that the customized profiles 107 can be defined for different
profile types, such as but not limited to: a job type; a department
type (e.g. collection of defined jobs specific to department within
the company 104); and a company type (e.g. collection of defined
jobs for the departments of the company 104). As further described
below, the customized profiles 107 can be used to facilitate the
use of customized profiles 107 for assessing different needs of an
organization, including needs such as but not limited to; hiring of
new staff; assessment/review of current staff; assessment/review of
department or other employee groups over time (i.e. track changes
in specific attributes 150 present in the customized profiles 107);
etc.
[0042] Accordingly, it is recognised that the customization
methodologies presented below, in view of the above environment 10,
for benchmark customization can be viewed as self-serve for the
companies 104, thereby inhibiting cumbersome benchmarking processes
that often require manual intervention from an expert in the field.
In addition, it is recognised that there is a need for updated
reassessment and employee benchmarking in situations where the rate
of change inside an organization 104 can be significant, which can
be done during annual employee reviews, for example. Accordingly,
the ability to produce customized profiles 107 (e.g. job benchmark)
efficiently and to be able to dynamically change benchmarking
standards for a company 104 can be beneficial to performance of the
company 104 in their market niche. For example, the customized
profile 107 can change as the company 104, via the customization
engine 250, adds more employees for consideration (e.g. the
customization engine 250 may choose to add or not to add the
additional employees to the customized profile 107, as further
described below. It is recognised that the content of the
predefined profiles 100 can over time, for example as published by
the framework 112.
[0043] It is also recognised that at least some of the customized
profiles 107 may not be related to a particular employment
definition 102, rather some of the profiles 107 may be
representative of all employment positions at a company or a group
of generic employment positions (e.g. management, sales, human
resources, research positions, assistants, or other
aggregations/combinations of selected customized profiles 107, as
generated by the customization engine 250, see below). It is also
recognised that the candidate profile 108 can also represent an
employee profile, which indicates how they scored specifically in
terms of the overall customized profile 107, as compared by the
customization engine 250, further described below.
Assessment 99
[0044] The assessment 99, for use in generating the customized
profiles 107 and/or the candidate profiles 108 has a plurality of
questions for answering by the employee/candidate 114, for example
as to the degree of agreement to the question (e.g. strongly agree,
agree, disagree, strongly disagree). Each of the answers has a
value attached to it, such that all of the answer scores are
combined for each of the assessment 99 questions that are grouped
into the same question category. Accordingly, each of the
assessment 99 questions relate to one or more of predefined
categories (e.g. psychological attributes 151--see FIG. 15). The
combined question scores are converted (e.g. using a normative
scoring curve, see "Example Raw Score Conversion Process" provided
below as an example conversion method) to representative values of
the predefined categories (e.g. psychological attributes 151). As
further described below, the psychological attributes 151 are
transformed into the attributes 150 present in the customized
profile 107 (see FIG. 2a) included in the customized profile 107.
It is also recognised that the attributes 150 could be the
predefined categories of the assessment 99 questions, as desired.
It is recognised that the profiles 107 may or may not be
confidential with respect to the company 104.
[0045] Referring to FIG. 6, shown is an example set of attributes
150 and attribute scale 160 that is used to store the derived
attribute results from the personal assessments 99 completed by the
candidates 114 and company 104 employees. Each individual scores
once across each horizontal line (i.e. attribute 150). For example,
there can be 3 interest/motivation traits & 12 personality
(e.g. worker attribute) attributes 150, with each of the attributes
150 having sub attributes 150. Opposing attributes 150 are
extremes/opposites. Further, the social desirability attribute 150
can indicate the probability of intentional or unintentionally
distorted/manipulated results in view of how the candidate/employee
filled out the assessment 99.
[0046] It is recognised that for example, the scale 160 can
represent a normative scale, such that the majority of individual's
scores would fall between 4 and 7, such that scores 1 and 10 would
be considered extreme scores.
Customization Profiles 107
[0047] Referring to FIG. 2a, shown is an example of the customized
profiles 107 that has a series of employee attributes 150 that each
has attribute data characteristics such as an overall range 152 for
the attribute 150. The ranges 152 extend from a first boundary 154
(e.g. an outside circle) to a second boundary 156 (e.g. an inner
circle), such that an identified/target portion 158 in each range
152 represents a region that a candidate's 114 score (for that
attribute 150) should fall into, in order to be potentially
considered for the job(s) 102 associated with the profile 107. For
example, the outer boundary 154 can represent a lowest score (e.g.
one) for the attributes 150 and the inner boundary 156 can
represent the highest score (e.g. ten) for the attributes 150,
according to an attribute scale 160 (e.g. 1-10) that is either
displayed or is implicit to the profile 107. The attributes 150 can
also be grouped into attribute categories 162, as desired. It is
recognised that the profiles 107 can be based on shapes other than
circular (e.g. square, rectangular, three-dimensional shapes,
etc.), as desired.
[0048] Also, certain attributes 150 of the customized profile 107
can be indicated as important (e.g. a top number such as 5) that
are more indicative (e.g. key) of attributes 150 that a candidate
114 should have, as an appropriate indicator of success in the
job/group of jobs represented by the customized profile 107.
Predefined Profiles 100
[0049] The predefined profiles 100 contain what are
believed/perceived to be the key personality and motivation traits
of proven top performers in many industries for a selected
employment position or group of positions (e.g. job title). For
example, certain attributes 150 of the profile 100 can be indicated
as important (e.g. a selected number such as 5) that are more
indicative (e.g. key) of attributes 150 that a candidate 114 should
have, as an appropriate indicator of success in the job/group of
jobs represented by the profile 100 for the industry. It is
recognised that the key personality and motivation traits of the
standard profile 100 may be changed by the customization process of
the engine 250, thus providing for key personality and motivation
traits in the customized profile 107 that are different (e.g. more
representative of the assessment data of the company 104 employees)
from the standard profile 100 (i.e. the standard profile has key
personality and motivation traits that are selected from
assessments 99 done for employees from a plurality of companies 104
in the industry).
[0050] Referring to FIG. 2b, shown is an example of the standard
profiles 100 that has a series of employee attributes 150 that each
has attribute data characteristics such as has an overall range 152
for the attribute 150, as an average for the industry for that
particular job or grouping of jobs represented by the standard
profile 100. The ranges 152 extend from a first boundary 154 (e.g.
an outside circle) to a second boundary 156 (e.g. an inner circle),
such that an identified/target portion 158 in each range 152
represents a region that a candidate's 114 score (for that
attribute 150) should fall into, in order to be potentially
considered for the job(s) 102 associated with the customized
profile 107. For example, the outer boundary 154 can represent a
lowest score (e.g. one) for the attributes 150 and the inner
boundary 156 can represent the highest score (e.g. ten) for the
attributes 150, according to an attribute scale 160 (e.g. 1-10)
that is either displayed or is implicit to the profile 107. The
attributes 150 can also be grouped into attribute categories 162,
as desired. It is recognised that the profiles 100 can be based on
shapes other than circular (e.g. square, rectangular,
three-dimensional shapes, etc.), as desired. It is recognised that
the main components of the original profile 100 are similar to the
customized profile 107, as the customized profile 107 is viewed as
an amended version of the original profile 100, i.e. through the
customization process implemented by the customization engine
250.
Candidate Profiles 108
[0051] As discussed above, the employment candidates 114 can
communicate with the framework 112 over a network 11, in order to
complete respective candidate assessments 99 and can include other
employment definition information 98 for use in determining a
respective candidate profile 108. The completed candidate profile
108 (e.g. as generated by the framework 112) can be used by the
candidate 114 in applying for selected employment definitions 102
(e.g. including the customized profile 107 generated by the
customization engine 250 on behalf of the company 104) as posted by
the company 104 on the framework 112, for access by the potential
job candidates 114.
[0052] Referring to FIG. 2c, shown is an example of the candidate
profiles 108 that has a series of employee attributes 150 that each
has an overall range 152 for the attribute 150, as an average for
the industry for that particular job or grouping of jobs
represented by the standard profile 100. The ranges 152 extend from
a first boundary 154 (e.g. an outside circle) to a second boundary
156 (e.g. an inner circle), such that an identified/target portion
158 in each range 152 represents the region that the candidate's
114 score 166 (for that attribute 150) should fall into, in order
to be potentially considered for the job(s) 102 associated with the
customized profile 107. For example, the outer boundary 154 can
represent a lowest score (e.g. one) for the attributes 150 and the
inner boundary 156 can represent the highest score (e.g. ten) for
the attributes 150, according to an attribute scale 160 (e.g. 1-10)
that is either displayed or is implicit to the profile 108. The
attributes 150 can also be grouped into attribute categories 162,
as desired. It is recognised that the profiles 108 can be based on
shapes other than circular (e.g. square, rectangular,
three-dimensional shapes, etc.), as desired. It is recognised that
the main components of the candidate profile 108 are similar to the
customized profile 107, as the candidate profile 108 is viewed as a
version of the customized profile 107 specific to the candidate
114, i.e. through the candidate process implemented by the
framework 112.
Overview of Customized Employment Profile 107 Generation
[0053] Referring to FIG. 1, the customization engine 250
facilitates a turnkey/self-serve environment 10 for generation of a
customized profile 107 for a company 104, based on assessment
information 99 of company 104 employees and a selected standard
profile 100 (or profiles 100) by the company 104 from a profile 100
list provided by the framework 112. In terms of customizing, each
employer 104 gets their own unique job profile 107, because each
job profile 107 incorporates the scores of their own top performer
employees (which are unique to only them, obviously), as well as
potentially their underperformers as well (e.g. a customized
undesirable profile 107 can be generated as a tool for use in
weeding out undesirable employee candidates--where matches to the
customized undesirable profile 107 would result in disqualification
of the potential candidate 114 for any jobs at the company 104).
Otherwise, it is recognised that a combination of both together,
where both the high and low performers results can be explicitly
represented in the customized profile 107 (e.g. desired attributes
150 and/or undesired attributes 150 can be included with
corresponding ranges 152 in the profile 107.
[0054] In terms of balance, as implemented by the customization
engine 250, each employer starts with a (i) a standard job profile
100, customizing it by (ii) adding the profiles (e.g. assessment
information 99) of their own top or mid or bottom performers. The
customization engine 250 can be configured to put more weight on
the (i) standard job profile 100 if there are fewer (e.g. less that
an minimum number employee threshold) top employees or less weight
on the standard job profile 100 if there are several (e.g. greater
than a minimum number employee threshold) top or mid or bottom
employees.
[0055] For example, the number of employees considered by the
customization engine 250 (as submitted by the company 104), can be
a driver of the weighting (e.g. the number of submitted employees
and their personal assessment data 99), when the number of
submitted employees is measured against the minimum number employee
threshold. Otherwise, or in addition to, the number of employees
considered by the customization engine 250 can be different than
the employee number submitted by the company 104. For example the
customization engine 250 can reduce/filter the number of employees
for consideration by removing (e.g. filtering out) employee
assessments 99 (from use in determination of the attribute ranges
152 in the customized profile 107), which are determined to be
outside (e.g. greater than or less that employee max/min inclusion
thresholds) of a determined average (or other normative
combination) range 152 for each of the attributes 150 (e.g. the
determined employee attributes are extreme compared to the rest of
the employee attributes 150 determined from the submitted
assessment data 99). In this case, the resultant reduced or
otherwise filtered number of employees can be the driver of
weighting in calculation of the customized profile 107 by
homogeneity of the employees, as further described below.
[0056] It is recognised that there can also be a number or
thresholds, thereby facilitating a graduated weighting from the
customized profile 107 being composed of attribute 150 data
characteristics (ranges, etc.) mostly from the standard profile
100, to the customized profile 107 being composed of attribute 150
data characteristics (ranges, etc.) mostly from the employee
assessments 99 information.
[0057] It is recognised that in situation where the company 104 has
a large number of employees, the attribute 150 characteristics in
the customized profile 107 would be based only on the employee
assessment data 99 (e.g. the degree of homogeneity of employees can
determine the weighting of their scores verses the predetermined
profile 100 in creation of the customized profile 107), while in
the situation at the other extreme where the company 104 has a
small number of employees, the attribute 150 characteristics in the
customized profile 107 would be based predominantly on the standard
profile 100 attributes 150. However, even in the case where the
company only has a single employee for providing assessment data 99
appropriate to the job(s) represented by the standard profile(s)
100, the customization engine 250 would still provide for a
weighted combination of the attribute 150 data from the standard
profile 100 and the attribute 150 data calculated from the employee
assessment data 99.
[0058] Referring to FIG. 4, the company 104 communicates with the
framework 112 over the network 11 (e.g. via a Website of the
framework 112 presented as a series of interactive Web pages
140--see FIGS. 7-10) in order to generate the customized employment
profile 107 and any associated employment definition 102. For
example, first an existing standard job profile 100 is selected 200
from a profile library (e.g. via a drop-down menu) 144, 142, which
can be available in the database 110 for a plurality of different
jobs 142 in different industries 144. When the standard job profile
100 is selected, a preview of it can appear below the drop down
menu (see FIG. 7) on the user interface 302 of the company device
101 (see FIG. 5).
[0059] For example, the standard job profile 100 can appear similar
to the profile 107 shown in FIG. 2b, prior to the addition of
company employee scores as further described below. Referring again
to FIG. 2b, the standard profiles 100 (and customized profiles 107
in FIG. 2a) can have the series of employee attributes 150 that
each has the overall range 152 for each of the attributes 150. The
ranges 152 extend from the first boundary 154 to the second
boundary 156, such that the identified portion 158 in each range
152 represents the region that a candidate's 114 score (for that
attribute 150) should fall into, in order to be potentially
considered for the job(s) 102 associated with the profile 107, as
further described below. Further, it is recognised that the name of
the standard job profile 100 can be re-named (see FIG. 8) from the
template name to any custom job name 146 the employer 104 prefers.
Also envisioned is that the employer registers with the framework
112 to start an employer/company account within which to save their
customized profile 107 and/or other company 104 information, such
as employment definitions 102.
[0060] The next step is for the company 104 to invite 202 (see FIG.
4) to fill out the personal assessments 99 and may include other
employee definition information 98 (either at the company 104
and/or via the Website of the framework 112). Once the assessments
99 and 98 are completed, the company 104 may or may not choose 204
which of the employee assessments 99 they wish to combine with the
standard profile 100 to create the customized profile 107. For
example, a list of employees 148 (see FIG. 9) they have assessed
(assuming employer has already assessed several of their employees,
using our assessment 99) can be presented/displayed to the company
with check boxes (selection means checking their corresponding box,
for example) 149 beside their names. In one example embodiment, the
employer 104 can rate all employees and assign them for inclusion
in calculation of a selected customized profile 107 (e.g. by
selecting the associated predetermined profile 100 from a list
provided by the framework 112), regardless of the employees
indicated level of performance. The employer 104 can also include
all employees for inclusion in the profile 107 calculation, through
a single click on or off. Alternatively, the employer 104 can
choose to not include an employee's results by not linking them for
inclusion in the profile 107 calculation.
[0061] When a check box is checked, a few things happen: (a) that
corresponding employee is "added" to the employers job profile 107,
changing the blue target ranges 158 (see FIG. 2b) from those of the
standard job profile 100 to include the selected employees' scores
of the attributes 150 determined from their completed personal
assessments 99, further described below. This customizes the
profile 107 for each employer 104 because each employee's scores
are considered unique from the employer 104 perspective; and (b) if
more than one employee is checked, those 2+ employees' scores can
both be added (if determined appropriate for inclusion by the
customization engine 250) to the employer's job profile 107 and the
target ranges 158 dimensions (e.g. upper and lower bounds 164 with
respect to the scale 160) change to include those 2+ employees'
scores. It is recognised that the upper and lower bounds 164 may or
may not coincide (either one or both bounds) with the first 154 and
second 156 boundaries of the ranges 152 of the attributes 150.
Another example is where when the box is checked, it includes all
the employees that are linked to that job.
[0062] In generation of the customized profile 107, the
customization engine 250 can put more weight on the standard job
profile 100 if there are fewer top employees (e.g. measured as
actual number submitted/selected by the employer 104 and/or the
reduced/filtered number determined by the customization engine 250)
or less weight on the standard job profile 100 if there are several
top employees, in terms of combining the attribute scores of the
profile 100 with the attribute scores of the employees derived from
their completed personal assessments 99. Once completed, the
company 104 saves their final custom job profile 107 for subsequent
use in comparing against any of the personal assessment attribute
scores obtained from potential candidates 114 that are applying to
the company 104 (either in general and/or for specific selected
employment definitions 102). After saving, company 104 can resume
this process later, further modifying their custom profile 107, as
they choose to select new employees and remove old employees from
the custom profile 107.
[0063] Further to the above, it is recognised that a possible
driver of the weighting preformed by the profile module 258 is the
homogeneity (i.e. relatedness of the employees to one another in
terms of their analyses assessments 99)--regardless of the numbers.
Outliers can get removed and then all the remaining employees are
included in the calculation of the profile 107. The collective
homogeneity of those remaining employees may or may not be very
high and that can drive the weighting on standard profile 100
verses using employees' results 99. For example, a determined
degree of homogeneity of the remaining employees (e.g. those not
filtered out as outliers) can be used to determine the degree of
weighting on the standard profile 100 verses using employees'
results 99, in calculation of the profile 107. For example, for
homogeneity below and/or above a specified relatedness threshold, a
corresponding predefined weighting value of the standard profile
100 can be used to combine with the determined profile values (e.g.
attribute values 150, ranges 152, etc based on the personal
assessment data 99 used in the determination).
[0064] At step 206, the company 104 can add more criteria (e.g.
employment definition information 98) to be associated with the
employment definition 102 associated with the customized profile
107. The company 104 can also build 208 a customized Web page (e.g.
including the employment profiles 102 and other company
information) for access by the candidates 114.
[0065] In view of the above, it is recognised that in creation of
the customized profile 107, the customization engine 250 and/or the
company 104 can omit certain actions, such as but not limited to:
manual intervention from the vendor (i.e. phone, email, web help);
showing of individual employees' scores as they are just combined
with the standard profile 100 without letting the employer 104 see
how each of their invited employees scored on the personal
assessments 99; and do not show a profile 107 to the employer 104
that's based only on the employees scores, as all job profiles 107
originate from the standard job profile 100 selected from the
library.
[0066] It is recognised that the above-described generation of the
customized profile 107 can be done using attribute scores (from the
personal assessment 99) obtained from one or more employees. Once
completed (e.g. the profile 107 and optionally the associated
definition 102), the company 104 can invite 210 potential
candidates 114 to apply for employment positions at the company
104, as coordinated by the framework 112. Also realized is that the
company 104 can obtain individual candidate 114 profiles 108 (refer
to FIG. 2c) that have the individual attribute scores 166
positioned on the attribute ranges 152, can get candidate profile
reports (e.g. individual attribute scores 166 of the employee(s)
positioned on the attribute ranges 152), can get employee profile
reports, can generate profile 107 reports, and can further edit the
profiles 107 and analyze the candidate and employee scores using
other tools, as desired.
[0067] Accordingly, in view of the above, the profiles 107 are
configured so as to facilitate the visual determination by the
company 104 of target applicants (i.e. candidates 114) who fit the
profile 107 (e.g. have attribute values 166 within the ranges 152
and 158), based in part on those company 104 employees that are
selected by the company 104 as those who were top-rated over time.
As can be seen, the candidate profiles 108 can be used to visually
access how close is each applicant 114 is to the `bull's eye` (e.g.
upper boundary of 164, or 156) as well as how far an applicant 114
strays from the `bull's eye`.
[0068] Further, it is recognised that the ability to produce
customized profiles 107 (e.g. job benchmark) efficiently and to be
able to dynamically change benchmarking standards for a company 104
can be beneficial to performance of the company 104 in their market
niche, when using the generated customized profiles 107 to
facilitate assessment of the company staffing, as further described
below, including any trending in company staff profiles over
time.
Customization Engine 250
[0069] Referring to FIG. 3, shown is an example embodiment of the
customization engine 250. The customized profiles 107 for a company
104 are a result of selected personal assessment 99 results
contained in the employee information 105, as submitted by the
company 104, combined with one or more predefined profile(s) 100,
as implemented on the customization engine 250, for example as
separate from the framework 112 or as integrated with the framework
112, as further described below.
[0070] The customization engine 250 has a receipt module 252 for
receiving the standard profile(s) 100 selected by the company 104,
any readjustment parameters 254 (e.g. specification of desired top
attributes 150 in the resultant profile 107, including any desired
ranges 152 thereof, as well as all assessment data 99 submitted by
the company 99 (on behalf of the employees) and/or submitted
directly by the employees. Further, it is recognised that the
assessment data 99 can include indications 255 by the company
concerning 1) specification of which employees should be included
in the profile 107 calculation, 2) specification of which employees
should be removed from the profile 107 calculation, 3) submission
of performance rating results (e.g. top, mid, weak performer) as
identified/specified by the company 104 for selected employees as
compared to a simple manual selection (e.g. tick box) of the
employees that should be included/excluded in the profile 107
calculation, and/or employee type (e.g. performer rating, employee
status such as new, fired, resigned, indefinite/definite layoff,
etc.), as desired.
[0071] The customization engine 250 also has a set of filter
settings 256 (e.g. previously submitted/stored indications 255) for
use in guiding the calculation of the customized profile 107
through the systematic inclusion and/or exclusion of specified
employees that satisfy the indication(s) 255
conditions/definitions. The customization engine 250 also a profile
module 258 for use in generation the customized profile 107 in view
of any appropriate filter settings 256 in combination with any
readjustment parameters 254, assessment data 99, and/or indications
255, and selected standard profile(s) 100, as further described
below.
[0072] Further, the customization engine 250 can also have an
aggregation module 260 for use in determining aggregated customized
profiles 109 (i.e. a combination of assessment data 99 for
different profiles 107 and/or directly from the collected
customization profiles 107 themselves), for use in tracking or
otherwise monitoring/comparing any dynamic shifts in general
company staff culture/characteristics/attributes, as further
described below. The customization engine 250 can also have a
remove module 262 for tacking/maintaining a list of employees that
are excluded from selected profiles 107 (e.g. as manually specified
by the company 104 and/or for those employees failing to satisfy
inclusion thresholds further described below). Further, the
customization engine 250 also has an output module 264 for
outputting the generated customized profile 107 for use/receipt by
the company 104.
Profile Module 258
[0073] The profile module 258 is configured for generation of the
customized profile 107, in view of any appropriate filter settings
256 in combination with any submitted readjustment parameters 254,
assessment data 99, and/or indications 255, and selected standard
profile(s) 100, as further described below.
[0074] Referring to FIGS. 1, 2 and 12, the following is an example
generation process 400 (e.g. of the profile generator module
404--see FIG. 11--using generation rules 121 in the case of
implementation on the framework 112) and/or by the profile module
258 in the case where hosted in the customization engine 250.
[0075] The process 400 is for customizing the standard employment
profile(s) 100 (also referred to as the Benchmark Fingerprint
Profile 100) to result in the customized employment profile 107
(also referred to as the Customized Fingerprint 107). At step 401,
Select Benchmark Fingerprint, the Benchmark Fingerprint Profile 100
is identified for the target job (e.g. associated with the job
definition 102). For example, the Fingerprints 100 are expressed in
terms of 17 Worker Attribute values 150, not Core Psychological
Attributes that are calculated from the assessments 99, and 3 Work
Interest values 150. All values 150 are expressed on a 1-10 numeric
scale, for example. The Benchmark Fingerprint Profile 100 provides
a Benchmark Value (e.g. range 158) for each of the 20 scales. At
step 402, gather responses from Best Employees, the responses on
the Assessments 99 are gathered from all present (e.g. selected as
Best or mid or weak) Employees (BEs), where Number=N. At step 403,
Determine sten scores on Core Psychological Attributes and Work
Interest scales, for each BE, derive, based in the individual
answers of the assessment 99 for each individual/BE, intermediate
scores on (e.g. 15) Core Psychological Attributes 151 (not
including Socially Desirable Responding) and the (e.g. 3) Work
Interest scales (e.g. interest in things, interest in data,
interest in people) on a psychological attribute 151 scale that is
similar to the scale 160 of the attributes 150. These intermediate
scores are considered each BE's core profile. Further, all the
psychological attribute 151 scale scores are organized into a
(N.times.18) matrix (e.g. one row for each BE and one column for
each of the 18 core scales, including the 3 Work Interest
scales).
[0076] At step 404, Derive scores on 18 Worker Attributes, for each
BE, a score is computed on each of the 17 Worker Attributes 150.
Each computed Worker Attribute 150 score is a predefined
combination 256 (e.g. weighted--e.g. linear--combination) of a
selected number of the Core Psychological Attribute 151 sten scores
calculated at step 403. An example of the predefined combination
weights are provided in the attached Translation Matrix 256 (see
FIG. 15). For example, "stress tolerance" attribute 150 is
calculated as 0.5 times the "resilient" 151 value plus 0.25 times
the "tolerates ambiguity" 151 value plus 0.25 times the
"self-regulated" 151 value. Further, the weights used to compute
Worker Attribute 150 scores can result in Worker Attribute 150
scores that are on the same numeric 1-10 scale as the sten scores
for the Core Psychological Attributes 151, for example. From this
point forward, all analyses use the computed scores on the 17
Worker Attributes 150 and the original 3 Work Interest sten
Attributes 150. These 20 attributes 150 are the basis of the
Fingerprint profiles 100,107,108. All 20 of the attributes 150 are
on a common predefined scale 160 (e.g. 1-10), for example.
[0077] At step 405, Compute Average (e.g. mathematical combination)
BE Profile, for each of the 20 attributes 150, compute the Average
(e.g. mathematical combination) Scale Score achieved by all BEs.
These 20 Average (e.g. mathematical combination) Scale Scores form
the Average (e.g. representative mathematical combination) BE
Profile (which in the case of a candidate 114 would be the
individual values 166--see FIG. 2c). Compute the Overall Average
(e.g. mathematical combination) of the 20 Average (e.g.
mathematical combination) Scale Scores. If the Number of BEs is
less than (or equal to) a predefined N minimum employee number
threshold 256 (e.g. 4 or lower), for example to promote statistical
significance of the impact of the BE scores on the standard profile
100, w(BE)=0.50, the Recomputed Average (e.g. mathematical
combination) BE Profile=Average (e.g. mathematical combination) BE
Profile, and Go to Step 413.
[0078] At step 406, For each BE, correlate Average (e.g.
mathematical combination) BE Profile with that BE's profile, for
each BE, compute the correlation/homogeneity/relatedness (e.g. in
probability theory and statistics, correlation, for example
measured as a correlation coefficient, indicates the strength and
direction of a linear relationship between two random variables. In
general statistical usage, correlation or co-relation refers to the
departure of two variables from independence). In this broad sense
there are several coefficients, measuring the degree of
correlation, adapted to the nature of data--for example on a scale
of 0-1.0) between his/her own 20 scale scores and the 20 average
(e.g. mathematical combination) scale scores in the Average BE
Profile. In step 408 each BE's correlation (e.g. the correlation is
an example of a cut-off value 256) is compared to a predefined
lower bound 256 of acceptable BE profiles.
[0079] At step 407, Compute "d" for each BE, For each BE, compute
the average (e.g. mathematical combination) of his/her 20 scales
scores, for each BE, compute "d", for example defined as the
absolute difference (e.g. mathematical combination) between that
BE's average (e.g. mathematical combination) scale score (across
all 20 scales) and the Overall Average (e.g. mathematical
combination) of the 20 Average (e.g. mathematical combination)
Scales Scores in the Average (e.g. mathematical combination) BE
Profile. In step 408 each BE's (e.g. "d" is an example of a cutoff
value 256) compared to a predefined upper bound threshold 256 of
acceptable BE profiles.
[0080] At step 408, to promote homogeneity of the attributes values
included in the customized profile 107, Remove All "Outlier" BEs,
meaning remove all BEs who have the lowest 20% 456 (for example) of
all correlations computed in Step 406a. Remove all BEs who have the
highest 20% 456 (for example) of all "d" values computed in Step
407. NOTE: the two 20% inclusion thresholds 456 (predefined upper
and lower bounds) can be separately adjustable parameters 456. It
should be noted that all (i.e. a complete individual) attribute 150
scores associated with a removed individual BE can be deleted (i.e.
not included) from the calculation for the customized profile 107.
The purpose of the predefined bounds 456 is to remove those scores
from calculation of the profile 107 that are associated with the
BEs that are deemed least (e.g. not homogeneous) like all other BE
scores. In this case, the customization engine 250 has
reduced/filtered the number of employees (i.e. their corresponding
attribute values) that will be included in the determination of the
customized profile 107.
[0081] At step 409, Recompute Average (e.g. mathematical
combination) BE Profile, Recompute Average (e.g. mathematical
combination) BE Profile (see Step 402) based only on all retained
Bes. At step 410, Recompute Average (e.g. mathematical combination)
BE Profile correlations, where for each retained BE, compute the
correlation between his/her 20 scale scores and the 20 Average
(e.g. mathematical combination) Scale Scores in the Recomputed
Average (e.g. mathematical combination) BE Profile. At step 411,
compute average (e.g. mathematical combination) correlations,
compute the average (e.g. mathematical combination) of all
correlations computed in Step 410a across all retained Bes. At step
412, Compute/Select the weight, "w(BE)" for the Recomputed Average
(e.g. mathematical combination) BE Profile, where w(BE)=See
attached example Look Up Table (FIG. 16) for Determining w(BE)
based on the average (e.g. mathematical combination) retained BE
correlation computed in step 411.
[0082] At step 413, Compute the weight, "w (Bench)", for the
employer's Benchmark Profile, where w(Bench)=1.0-w(BE), for
example. At step 414, Compute the Customized Fingerprint Value for
each of the 20 scales, for each of the 20 scales of the attributes
150, the Customized Fingerprint Value (i.e. of the customized
profile 107) for each attribute 105 is equal to Customized
Fingerprint Value=[w(BE)*Recomputed Average Profile
Value]+[w(Bench)*Benchmark Value] (e.g. mathematical
combination).
[0083] At step 415, Apply the 20 Customized Fingerprint values to
define the graphical "Target" display, where referring to FIG. 2b,
the circular Customized Fingerprint 107 display on the user
interface 302 of the company device 101 (as generated by the engine
250 and/or framework 112) includes a "wedge" 152 for each of the 20
Worker Attributes-Work Interests 150. Within each wedge, an arc 156
is drawn some distance from the center point. The full distance of
the wedge from the center point of the circle to the outer edge of
the circle is 10 units on a 1-10 scale 160, for example, with 10
being the center point and 1 being the out edge for example. For
each of the 20 wedges, the Customized Arc 164 is placed at that
point equal to the Customized Fingerprint Value computed in Step
414, resulting in the drawing of the identified portion 158
(representing the range in which a candidate 114 calculated
attribute is desired by the company 104).
Aggregation Module 260
[0084] The aggregation module 260 is configured for determining
aggregated customized profiles 109 (i.e. a combination of
assessment data 99 for different profiles 107 and/or directly from
the collected customization profiles 107 themselves), for use in
tracking or otherwise monitoring/comparing any dynamic shifts in
general company staff culture/characteristics/attributes. For
example, the settings 256 can include minimum company desired
attribute 150 values for specified key attributes 150 for different
company categories 457, such as but not limited to: a specific job;
a specific department being a collection of different jobs; and/or
a collection of departments representing a portion or all of the
company staff, etc. Further, the settings 456 can also include
stored historical aggregate profiles 109 for selected company
categories 457 (e.g. an annual profile 107 for a number of years
over time determined for the sales department of the company).
[0085] Accordingly, upon periodic (either manually triggered and/or
automatically triggered such as during annual/semi-annual staff
reviews), the aggregation module 260 can determine the current
corresponding aggregate profile 109 using the latest available
assessment data 99 appropriate for the staff of the selected
company category 457. In turn, the aggregate module 260 can compare
the currently generated aggregate profile 109 with the
corresponding historical aggregate profiles 109 and/or the minimum
company desired attribute 150 values for specified key attributes
150. A report of this comparison can be made available to
management of the company, in order to facilitate the
identification of a rate of change and/or absolute change of staff
attributes 150 inside the selected company category 457.
[0086] In this manner, the management of the company 104 can
monitor the dynamic company culture shifts that invariably occur
over time within an organization 104. Further, the company 104 can
also use the aggregate profiles 109 as a snapshot of current
company staff attributes 150 characteristics for the selected
company categories 457, in order to compare the customized profile
of a new hire to the company (e.g. a new CEO and/or manager of
department), in order to see if the attribute 150 characteristics
of the staff correspond (e.g. are compatible with) with the
attribute 150 characteristics of the new hire. It is recognised
that this is a subtly different application of the customized
profiles 107, as the aggregated attributes of staff of the selected
company category 457 are being used to evaluate compatibility (e.g.
fit) between the staff and the new hire, rather than the comparison
between the new hire candidate profile 108 and the customized
profile 107 for the employment position associated with the new
hire. For example, a match may be provided between the new hire
candidate profile 108 and the customized profile 107 for the
employment position, however the comparison between the new hire
candidate profile 108 and the aggregated profile 109 representing
the attributes 150 shared by the staff of the selected company
category 457 may denote or otherwise identify some
incompatibilities in certain attributes between the new hire and
the staff (i.e. an indication of potential lack of fit between the
new hire and their department).
[0087] Once in the database 110, companies 104 can access the
profiles 100,107,108 via a Web portal through a Web search engine
provided by the framework 112, i.e. the companies 104 via their
browser access the contents of the electronic database 110 over the
Internet via the Web portal that hosts the Web search engine. Also
provided is the capability to perform periodic updates of the
employment definitions 102 and the profiles 107 (e.g. by adding
more employee assessments 99) by the company 104.
Framework 112
[0088] Referring to FIG. 11, shown is an example of the framework
112 for determining profiles 107, by the company information module
400, the plurality of profiles 108 of the plurality of the
candidates 114 for matching against the profiles 107 (e.g. as
selected via the job definitions 102 by the candidates 114). It is
recognised that the information from the companies 104 and the
candidates 114 can come to the framework 112 synchronously and/or
asynchronously with respect to communications between the framework
112 and the company 104 candidate sources 114. The profiles 107,108
can be stored in the database 110. Once stored, for example, the
profiles 107,108 are accessed, via matching module 408, for
determining matching indicators between the company 104 and the
candidates 114. A network interface module 402 is used to collect
the assessment 99 results of the candidates 114 and the company
information module 400 is used to collect company 104 information
and employee information 105. A candidate module 406 is used to
calculate the profiles 108 and a profile generator module 404 is
used to calculate the profiles 107. The framework 112 can also
provide a match score, in addition to just plotting their scores
166 on the profile 108, such as; Strong Match, Match, No Match,
and/or Distortion (if they intentionally or unintentionally tried
to manipulate the assessment 99 test.)
[0089] In an alternative embodiment, the framework 112 can
implement a scoring system that combines personality with skills
and experience. Scores are Strong Fit, Fit, Weak Fit and
Distortion, for example. Strong Fit can be derived by the framework
112 matching through a combination of Strong Match and Match (for
skills and experience). Fit can be derived through a Match and
Match. Weak Fit can be any combination that includes either or both
a No Match or No Match. Any result including distortion can be
automatically scored a distortion.
Company Module 400
[0090] The module 400 is responsible for communicating with the
companies 104 over the network 11, in order to receive various
employee information 105 and candidate information 114. The
information 105 and 114 can be defined using a structured
definition language such as but not limited to the Standard
Generalized Markup Language (SGML), which defines rules for how a
document can be described in terms of its logical structure
(headings, paragraphs or idea units, and so forth). SGML is often
referred to as a meta-language because SGML provides a "language
for how to describe a language." A specific use of SGML is called a
document type definition (DTD), which defines exactly what the
allowable language is. For example, Hypertext Markup Language
(HTML) is an example of a structured definition language for
defining the information 105. A further example of the structured
definition language is Extensible Markup Language (XML), which
defines how to describe a collection of data.
[0091] Further, it is recognised that the module could be
configured as a Web portal/site for interaction with the companies
104 over the network 11, via a series of structured (e.g. XML)
messages between the framework 112 and the company 104 and/or via
an interactive series of Web pages, as desired. Further, it is also
recognised that the information 105 could be supplied by other
communication modes, e.g. email, facsimile, telephone, mail,
etc.
[0092] The module 400 can also facilitate registration of the
companies 104 with the framework 112. The company 104 would provide
their registration information, such as name, location, and contact
details. The communication of this registration information can
include communication modes such as but not limited to: voice
communication via phone; written communication via network
messaging (e.g. email, facsimile); and/or others as desired. We can
also offer promotions and products (ours or other companies') to
employers, candidates or employees via email or through their
Account page.
[0093] It is recognised that the companies 104 registered with the
framework 112 could be issued framework ID and password (optional),
which uniquely identifies the particular company 104. The framework
ID could be associated with the information 105 and the profiles
107 and definitions 102, as well as any matched candidates 114,
thus facilitating the receipt of subsequent results information 106
and processing by the framework 112 for storage in the database
110.
[0094] The module 400 can include receipt and transmit sub-modules
can be part of the network connection interface module 400.
Network Interface Module 402
[0095] The module 402 can be part of the network connection
interface 300 (see FIG. 5) of the device 101 operating the
framework 112. The module 402 can communicate synchronously or
asynchronously with the device 101 of the candidate 114 over the
network 11 to receive or otherwise collect the candidate
information. For example, the module 402 could be a Web service as
a software system designed to support interoperable
machine-to-machine interaction over the network 11, between the
framework 112 and the candidates 114. The Web service of the
framework 112, as facilitated by the module 402 can be configured
as a series of Web APIs (and/or Web pages) that can be accessed
over the network 11 by the candidates 114 and then executed on the
framework 112 hosting the requested services.
[0096] The Web service definition can encompass many different
systems, such as clients and servers that communicate using XML
messages that follow the SOAP standard. Also, the module 402 could
provide a machine-readable description of the operations supported
by the framework 112 written in the Web Services Description
Language (WSDL).
[0097] For example, the module 402 provides to the candidates 114
an electronic interface for access to the definitions 102, as
searched in the database 110 through any subset of the product
details via the search parameters. For example, the electronic
interface can be a Web portal offering a structured employment
search engine, i.e. the candidates 114 via their browser access the
definition 102 contents of the electronic database 110 over the
network 11 via the framework 112 that hosts the search engine. For
example, the candidates 114 could search jobs offered by selected
companies 104 and/or selected job categories in the database 110 to
suitable employment opportunities across the country.
[0098] Examples of user interface control elements of the interface
can include such as but not limited to a dropdown list that is
similar to a list box, which allows the candidates 114 to choose
one or more values from the list. When the dropdown list is
inactive it displays a single value. When activated, the dropdown
list displays (drops down) a list of values (e.g. job titles), from
which the candidates 114 may select. When the candidates 114
selects a new value the control element reverts to its inactive
state, displaying the selected value. The control elements can
include, for example, a combo box having an editable entry portion
of the list. The navigation field of a web browser is an example of
a combo box. A further example of the control elements is a list
box or tabs that provide for the selection of one or more
jobs/companies at a time by the candidates 114. A further type of
example control element is a Pop-up/down menu, whereby pop-ups are
used to select a single job/company from a list while pop-downs are
used to issue commands (e.g. customized search terms) or in cases
where multiple jobs/companies can be selected. In any event, it is
recognised that the control elements can be used by the candidates
114 to formulate at least some of the search parameters for
suitable employment opportunities defined in the database 110, for
example. Further, the module 402 also facilitates the candidates
114 accessing and filling out the assessments 99, as well as
selecting which of the companies/jobs they would like their
assessment results applied/compared to. Also radio button control
elements that allow you to put a dot into a circle to indicate that
is your selection. They are frequently used when you are allowed
only one choice out of several options. Radio buttons are like
checkboxes except that they are mutually exclusive: when one is
switched `on`, all others within a grouping are switched `off`.
[0099] The module 402 can include receipt and transmit sub-modules
can be part of the network connection interface module 402. In view
of the above, the functionality of the modules 400, 402 can be
separate or combined, as desired.
[0100] Further, it is recognised that the modules 400, 402, 404,
406, 408 can be configured to operate interactively as shown, the
operations/functionality of the selected modules 400, 402, 404,
406, 408 can be combined or the operations/functionality of the
selected modules 400, 402, 404, 406, 408 can be further subdivided,
as desired. Further, it is recognised that the modules 400, 402,
404, 406, 408 can communicate or otherwise obtain their calculated
results from one another (and/or to the candidates 114/companies
104 over the network 11) or can store their respective calculated
results in the storage 110 for subsequent retrieval by another
module 400, 402, 404, 406, 408 there-from.
Computing Devices 101
[0101] Referring to FIGS. 1 and 5, each of the above-described
components of the environment 10, i.e. the company 104, the
framework 112, the customization engine 250, the candidates 114 and
the employees can be implemented on one or more respective
computing device(s) 101. The devices 101 in general can include a
network connection interface 300, such as a network interface card
or a modem, coupled via connection 318 to a device infrastructure
304. The connection interface 300 is connectable during operation
of the devices 101 to the network 11 (e.g. an intranet and/or an
extranet such as the Internet), which enables the devices 101 to
communicate with each other as appropriate. The network 11 can
support the communication of the employee information 105 and
corresponding results 106 (that can include employee and/or
candidate results) between the framework 112 and the company 104,
as well as between the candidates 114 and employees 105 and the
framework 112 for on-line completion of the individual assessments
99 and 98, and between the framework 112 and the engine 250 and
between the engine 250 and the company 104 and/or employees
directly.
[0102] Referring again to FIG. 5, the devices 101 can also have a
user interface 302, coupled to the device infrastructure 304 by
connection 322, to interact with a user (e.g. candidate 114,
company 104 human resources coordinator, framework 112/engine 250
administrator, etc.). For example, the company 104 to view and
interact with the electronic interface supplied by the interface
module 202 uses the user interface 302 of the device 101. The user
interface 302 can include one or more user input devices such as
but not limited to a QWERTY keyboard, a keypad, a trackwheel, a
stylus, a mouse, a microphone and the user output device such as an
LCD screen display and/or a speaker. If the screen is touch
sensitive, then the display can also be used as the user input
device as controlled by the device infrastructure 304. For example,
the user interface 302 for the devices 101 used by the company 104
can be configured to interact with a web browser (e.g. applications
307) to collect the information 105 as well as process the received
results 106 (e.g. review the various details of the candidates and
employees in reports). For the devices 101 used by the framework
112, the user interfaces 302 can be used by a framework 112
administrator to monitor (e.g. manually or automated through
software--e.g. applications 307) the registration of the companies
104 and performance of the matching between candidates and
employment profiles 107 and performance of generation of the
profiles 107 and any desired reports by the company 104. It is also
recognised that the candidates 114 and employees can complete
paper-based assessments 99 too, for data entry as digital data 99
for use by the customization engine 250.
[0103] Referring again to FIG. 5, operation of the devices 101 is
facilitated by the device infrastructure 304. The device
infrastructure 304 includes one or more computer processors 308 and
can include an associated memory 110,115 (e.g. a random access
memory). The computer processor 308 facilitates performance of the
device 101 configured for the intended task through operation of
the network interface 300, the user interface 302 and other
application programs/hardware 307 of the device 101 by executing
task related instructions. These task related instructions can be
provided by an operating system, and/or software applications 307
located in the memory 110, and/or by operability that is configured
into the electronic/digital circuitry of the processor(s) 308
designed to perform the specific task(s).
[0104] Further, it is recognized that the device infrastructure 304
can include a computer readable storage medium 312 coupled to the
processor 308 for providing instructions to the processor 308
and/or to load/update client applications 307. The computer
readable medium 312 can include hardware and/or software such as,
by way of example only, magnetic disks, magnetic tape, optically
readable medium such as CD/DVD ROMS, and memory cards. In each
case, the computer readable medium 212 may take the form of a small
disk, floppy diskette, cassette, hard disk drive, solid-state
memory card, or RAM provided in the memory module 110. It should be
noted that the above listed example computer readable mediums 312
can be used either alone or in combination. The device memory 110
and/or computer readable medium 312 can be used to store the
registration information of the companies 104 and the results of
the individual assessments 99 as completed. Further, the device
memory 110 can also be used by the framework 112 as a means to
store and access profiles 107 for use in matching with the scores
of the candidates 114 (i.e. to determine which candidates 114
should be indicated as a potential interviewee for the company
104).
[0105] Further, it is recognized that the computing devices 101 can
include the executable applications 307 comprising code or machine
readable instructions for implementing predetermined
functions/operations including those of an operating system, a web
browser, the framework 112 for example. The processor 308 as used
herein is a configured device and/or set of machine-readable
instructions for performing operations as described by example
above. As used herein, the processor 308 may comprise any one or
combination of, hardware, firmware, and/or software. The processor
308 acts upon information by manipulating, analyzing, modifying,
converting or transmitting information for use by an executable
procedure or an information device, and/or by routing the
information with respect to an output device.
[0106] The processor 308 may use or comprise the capabilities of a
controller or microprocessor, for example. Accordingly, any of the
functionality of the framework 112 (e.g. modules 400, 402, 404,
406, 408, and subset thereof) may be implemented in hardware,
software or a combination of both. Accordingly, the use of a
processor 308 as a device and/or as a set of machine-readable
instructions is hereafter referred to generically as a
processor/module for sake of simplicity. Further, it is recognised
that the framework 112 can include one or more of the computing
devices 101 (comprising hardware and/or software) for implementing
the modules 400, 402, 404, 406, 408, or functionality subset
thereof, as desired.
[0107] It will be understood that the computing devices 101 of the
consumers 104 may be, for example, personal computers, personal
digital assistants, mobile phones. Server computing devices 101 can
be configured for the framework 112 and the companies 104 as
desired. Further, it is recognised that each server computing
device 101, although depicted as a single computer system, may be
implemented as a network of computer processors, as desired.
Algorithm for Generating the Candidate Profile 108
[0108] Referring to FIGS. 1, 2, 3 and 13, the following is an
example generation process 500 by the candidate profile generation
module 406 (see FIG. 11), using generation rules 122, for
customizing the candidate profile 108 (based on the calculated
customized profile 107) using the computed candidate attributes
150.
[0109] At step 501, Candidate 114 completes assessment, the
candidate 114 accesses the network interface module 402 of the
framework 112 and completes the personal assessment 99. The
candidate can also select which job definitions 102 their
assessment results should be applied to (i.e. plotted on the
customized profile 107 associated with the job definition 102).
Conversely, the employer 104 may search database 110 for candidates
108 who may match their job profiles 107 or job definitions
102.
[0110] At step 502, Calculate candidate attribute 150 values, the
candidate module 406 subsequently calculates (by following steps
similar to steps 403 and 404 of the process 400) the attribute 150
values for the candidate 114, based on the assessment 99 and 98
results collected by the network interface module 402.
[0111] At step 503, Gather the Candidate's 20 Scores for each
selected definition 102, for the candidate 114 to be plotted onto
the customized Fingerprint 107, for example for each of the job
profiles 102 selected) gather all 17 computed Worker Attribute 150
scores and all 3 original Work Interest 150 sten scores for the
candidate's 114 calculated core attributes 151, which were derived
from the completed personal assessment 99 and 98 of the candidate
114. Each of these 20 scores is on a 1-10 numeric scale.
[0112] At step 504, Place a symbol 166 (e.g. a numbered dot) for
the candidate 144 in each wedge for each candidate profile 108
calculated, referring to FIG. 3, the circular Customized
Fingerprint display includes 20 "wedges", one for each of the 20
Worker Attributes and Work Interests 150. The full distance of the
wedge from the center point of the circle to the outer edge of the
circle is 10 units on a 1-10 scale, with 10 being the center point
and 1 being the out edge. For each of the 20 wedges, a point/symbol
166 representing the candidate's score is placed along the
imaginary center-line (for example) of the wedge at a point equal
to the candidate's score on that attribute scale 160. For example,
a score of 10.0 on, say, Recovers from Setbacks, would place the
candidate's symbol right on the center point at the inner tip of
the wedge (i.e. upper boundary 164) associated with Recovers from
Setbacks. A score of 1.0 would place the candidate symbol 166 on
the outer edge of the circle at the center of the arc defining that
wedge (i.e. at the lower boundary 164). A score of 9.0 would place
the candidate's 114 symbol 166 one unit away from the center point
(i.e. upper boundary 164), along the wedge's center line, toward
the outer edge, for example. And so on. Same process for employee
profiles.
[0113] At step 505, Provide candidate profile to company, it is
recognized that at this stage, the determined candidate profile 108
can be made available to the company 104, if desired (for example
based on the matching results described below). The company 104 can
elect to pay for the candidate profiles 108 desired, based on a
graduated cost scale (e.g. the company 104 can pay on a profile 108
by profile 108 basis, can buy a set number of profiles 108, and/or
can buy a subscription for an unlimited number of profiles 108 for
all job definitions 102 or on a definition 102 by definition 102
basis), as part of the results information 106.
Algorithm for Matching the Candidate Profile 108 to Ranges
[0114] Referring to FIGS. 1, 2, 3, 11 and 14, the following is an
example matching process 600 by the matching module 406 (see FIG.
11), using matching rules 123, for determining if the candidate
profile 108 matches thresholds (e.g. matching attribute ranges 158
of all or selected represented in the profile 108, a framework
score that identifies the number of/percentage of customized
profiles 107--associated with job definitions 102--that the
candidate 114 has matched via their calculated attribute scores 150
for all or a selected grouping of customized profiles 107 in the
database 110, and/or job definition 102 criteria such as academic
qualifications, work experience, selected skills/capabilities,
etc.) using the computed candidate attributes 150 and any other
candidate information supplied by the candidate 114 that is not
part of the computed candidate attributes 150 (e.g. resume details
such as grade point average, specific academic qualifications,
languages spoken, personal interests/hobbies, etc.) For example,
the match formula for these criteria might be structures as an all
or nothing. One example is the idea is minimum criteria, so it acts
like a threshold that must be met or exceeded.
[0115] It is recognised that the ranges 152 (see FIG. 3) extend
from the first boundary 154 (e.g. an outside circle) to the second
boundary 156 (e.g. an inner circle), such that the
identified/target portion 158 in each range 152 represents a region
that a candidate's 114 score 166 (for that attribute 150) should
fall into, in order to be potentially considered for the job(s) 102
associated with the profile 107,108.
[0116] At step 601, Gather the Candidate's 20 scores, for the
candidate to be "matched" against a customized Fingerprint, gather
all 17 computed Worker Attribute scores and all 3 original Work
Interest sten scores. Each of these 20 scores 166 is on a 1-10
numeric scale. For each of the 20 attribute scales 160, record the
Customized Fingerprint Value that defines the location of the
Fingerprint arc(s) 164 for that particular attribute. (These
Customized Fingerprint Values were computed in Step 414a of the
algorithm 400 to combine Best Employee profiles with Benchmark
Fingerprints.).
[0117] At step 602, Define and Count "Hits", "Misses" and "Big
Misses", For each of the 20 attributes 150, determine whether the
Candidate's score 166 is classified as a "Hit", "Miss", or "Big
Miss" according to the following example rules: [0118] A score is
classified as a "HIT" if it is equal to or higher than the
Customized Fingerprint Value (or is otherwise inside of the bounds
164 of the portion/target 158) for that attribute 150 [0119] A
score is classified as a "MISS" if it is not more than 2.5 points
lower/outside than the Customized Fingerprint Value/portion. [0120]
A score is classified as a "BIG MISS" if it is more than 2.5 points
lower/outside than the Customized Fingerprint Value/portion.
[0121] Note, the value of 2.5 is a variable parameter that can be
adjusted.
[0122] At step 603, Define 5 Most Important Attributes, among the
20 attributes, identify the 5 (for example) with the highest
Customized Fingerprint Values. These are the 5 Most Important
Attributes, for example. It is recognized that this determination
could be done at the process 400 stage, as desired. For example,
this attribute type (e.g. top or otherwise better that other less
desired attributes) is most likely the smallest target areas, the
most difficult to hit, therefore the attributes most predictive of
job success and therefore deemed desirable by the company. Count
the number of "Hits" among the 5 Most Important Attributes.
[0123] At step 604, Assign the candidate a "Match" status or a
plurality of Match statuses, Assign the candidate a status of
"Strong.Match" if all the following conditions apply, for example:
[0124] 16 or more Hits among the 20 attributes [0125] no Big Misses
among the 20 attributes [0126] 4 or more Hits among the 5 Most
Important Attributes [0127] assign the candidate a status of
"Match" if all the following conditions apply: [0128] Candidate is
not a "Strong Match" [0129] At least 14 Hits among the 20
attributes [0130] no more than 2 Big Misses among the 20 attributes
[0131] 3 or more Hits among the 5 Most Important Attributes [0132]
Otherwise, assign a status of "No Match" [0133] Note, all critical
values for Hits, ie 16 and 14, the critical values among Most
Important Attributes, ie 4 and 3, and the critical value for Big
Misses, i.e. 21, could be variable parameters than can be adjusted.
[0134] Further, it is recognized that varying degrees of matching
of the candidate 114 to the employment definition 102 (or otherwise
to the company 104 generically) can be calculated based on the
other employment criteria/information (e.g. other than the target
ranges 158 of the attributes 150) given by the company 104 as
described above, matching to employment criteria such as but not
limited to academic qualifications, work experience,
interests/hobbies, specified skill/qualifications, etc. For
example, matching information supplied by the candidate 114 (e.g.
via the Web pages of the network module 402 and/or a resume) with
the other employment criteria/information can be done by keyword
matching or other matching techniques as apparent to a person
skilled in the art.
[0135] Accordingly, in view of the above, it is apparent that the
candidate 114 can be matched to a variety of different matching
criteria. One match indicator can be the degree (e.g. as simple as
match or no match) between the candidate attribute 150 scores and
the target ranges 158 of the employment profile 107. Another match
indicator can be part of the overall attribute 150 matching or
separate as to the number of critical/more important attributes 150
(e.g. top 5 out of the 20) as identifies by the company 104 that
the candidate scores within the target range 158 of those
critical/more important attributes 150. A further match indicator
is the framework score of the ranking of the candidate's attribute
150 score matching with a plurality of different customized
profiles 107 for a plurality of different companies 104 or at least
for a defined subset of the plurality of different customized
profiles 107 available in the database 110. For example, this
framework score can be calculated as a percentage and/or total
number of profiles 107 that the candidate's attributes 150 matched
(as described above).
[0136] At step 605, Assign the candidate a "Flag" status based on
his/her "Socially Desirable Responding" or "distorted" score,
Separate from the "Match" status, assign the candidate a status of
"Flag" or "No Flag" based on his/her score on the Socially
Desirable Responding (SDR) scale. This score is an original sten
score and is may not be a combination of any other attributes 150.
[0137] "Flag" status is assigned if the candidate's SDR score is
equal to or higher than 9.0 or equal to or lower than 2.0, as
example SDR thresholds. [0138] "No Flag" status is assigned
otherwise. (i.e. the SDR score is lower than 9.0 and higher than
2.0).
[0139] A score for "distortion" or "distorted" score may be
comprised of social desirability and may or may not include a
consistency measure, re: how applicants are responding to the
questions in a consistent manner, or one that indicates they may
not be answering in an honest or frank manner.
[0140] At step 606, Provide match status(es) of the candidate 114
to the company 104, the determined match status(es) can be provided
to the company 104 via the company info module 400 and/or the
matching module 408, for example, as candidate information that can
be paid for/purchased by the company 104 as described above with
reference to the candidates profile 108, as desired, as part of the
results information 106.
[0141] In any event, in view of the above described match
indicators, it is recognised that only a portion of the degree of
match of a candidate 114 with the company 104 (e.g. job profile
102) may be provided to the company 104 as a first stage (see
attached example screen shots of the Web pages) evaluation of the
candidate 114. An example of the first stage is such as but not
limited to: a profile 107 match indicator (e.g. strong match,
match, no match, strong mismatch) without further details of the
candidates profile 108; some details of the profile match 107 (e.g.
the number of and/or which of the critical/top attributes were
matched/missed); match indicators on the employment criteria not
being the attribute 105 scores (e.g. rating on the degree of match
to qualifications, skills, abilities, etc.); and/or the framework
score as discussed above as a representative score of the
desirability of the candidate 114 as considered by other companies
104, for example; or a combination thereof. Based on the first
stage, the company 104 can decide to purchase or otherwise be
provided with second or subsequent stage results 106, such as
detailed candidate reports including the candidate profile 108 that
shows all of the attribute scores of the candidate 114 and/or the
candidate resume or other information submitted to the framework
112 by the candidate 114.
[0142] The framework score can be based on current active
customized profiles 107 in the database 110 and/or on all inactive
(e.g. historical) and active profiles 107, as desired, such that
active means that there is an employment position that remains
unfilled with the company 104 and inactive means that the profile
107 was used to already match a candidate 114 to the company 104
that resulted in a filled company 104 employment position. Further,
the match scores can be dynamic as well, since they can change as
the customized profiles 107 are updated with the
addition/subtraction of assessment data 99 (e.g. as
submitted/selected by the employer 104). This can mean that a
dynamic shift in the profile 107 can force a rescore of all current
candidates against the job represented by the profile 107 using the
matching criteria. Someone could be a match one day and no match
the next without changing their respective original assessment data
99. Accordingly, the use of dynamic changing match scores (in view
of dynamically changing assessment data 99 input to the
customization engine 250 over time by the employer 104) can result
in previously selected employees as suitable for a position become
unsuitable for the same position, in light of the subsequently
reassessed match between their original data 99 and the newly
revised profile 107.
[0143] For example, a revised profile 107 can be used to determine
if a present manager/C-level member of the company is now no longer
suitable to the needs of the company 104, as indicated by the
match/mismatch of the present manager's/C-level member's original
assessment data 99 with the revised profile 107. It is also
recognised that the revised profile 107 can also be a revised
aggregate profile 109 determined by the aggregation module.
[0144] Employers 104 are able to match people regardless of whether
they are looking to fill a vacant position or not. In addition,
employers can purchase reports on employees 105, but the employee
reports may not include the benchmark 107 or 102 or 100--only the
scores 166 of that employee 105 on the profile 102/107.
[0145] Further, it is recognised that the matching module 208 can
generate the format of the results 106 (e.g. match indicators
and/or profile 108) as display data suitable for use in subsequent
rendering of the candidate results 106 on a display (e.g. user
interface 302 of the consumer device 101--see FIG. 5).
Summary
[0146] The following are example summary features of the
above-described environment 10. "Turnkey/self-serve": Customization
can be done online, without expert intervention. "Customizing":
Each employer gets their own unique job profile, because each job
profile incorporates the scores of their own top performers and
occasionally mid and bottom performers (which are unique to only
them, obviously). "Balance": Each employer starts with a (i)
standard job profile, customizing it by (ii) adding the profiles of
their own top, mid, or bottom performers. Our system puts more
weight on the (i) standard job profile if there are fewer (ii) top,
mid, or bottom employees or less weight on the (i) standard job
profile if there are several (ii) top, mid, or bottom
employees.
[0147] Further features can include, for example: 1) Our 20 unique
Worker Attributes are built from a matrix that's based on standard
Core Attributes ("Big 5"); 2) 20 Worker Attributes are represented
using a "target" shape, with 20 "wedges"--one for each attribute;
3) Adding best employees to the Industry Standard JobFingerprint
(ISJF) in different ways: (a) if 1-4 employees added, average all
employees together and weighting is 50/50 with ISJF or (b) if 5+
employees added, remove individuals with (i) bottom 20% of
correlation with average of all employee scores or (ii) bottom 20%
of variance from average of all employee scores. (Each elimination
category may contain the same individual); 4) Employees' scores are
not shown when employer is adding them to their ISJF, per above
process; 5) Weighting between ISJF and best employees depends on
how many best employees are included in the JobFingerprint: more
employees means more weighting on employees, while fewer employees
means more weighting on ISJF (e.g. derivation of homogeneity of the
employee assessment data 99 can be a function of uniqueness of
responses--difference between their top (e.g. 5) traits and bottom
(e.g. 5) traits and correlation between the employees; 6) "Blind"
employer process of getting candidate results. Candidates may or
may not be anonymous (no identifiable info before gaining their
permission): (a) Review mini "teaser" match result that includes
(i) match-type rating, (ii) A+-type rating in 4 criteria (e.g.
work/academic qualifications/skills) and (iii) framework Score. (b)
If they have not already, gain candidate's permission (via
standardized internal program message to candidate's framework 112
inbox) before being able to view a report on them (that includes
their personally-identifiable information). (c) If permission is
granted, employer can choose to pay money (e.g. financial
compensation to the framework 112) to see a candidate's report,
with more extensive information than simple the "teaser" ratings
and framework Score, as described above; and 7) "framework Score",
per candidate, based on number of overall employer searches (active
and inactive jobs) that this candidate has matched. These are
searches from any employer, so this is like an overall "popularity
rating" for that candidate. We may or may not refine this rating to
be industry specific, so the score does not favour "general"
candidates so much.
[0148] Further, the "framework" aka "Careerious Score" can be based
on employer 104 activity around a particular candidate 114 or
employee 105, such as how many times that candidate 114 or employee
105 matches employer 104 searches of the database 110 or how many
employers have profiles 107 that match that candidate 114 or
employee 105. In this way the framework score can be considered as
a way the framework 112 can recommend candidates 114 to companies
104, based on what other companies 104 thought of that candidate
(e.g. if the candidate matched other particular attributes, other
information 98, and/or complete profiles 107). The framework 112
may use this framework score to create a marketplace for candidates
across industries. The following is an example of calculating the
framework score, where the formula or calculating said score may
change from time to time:
Careerious Score=25
[0149] A candidate's 114 or employee's 105 Careerious Score
increases each time a candidate 114 or employee 105 are awarded
Careerious Match Points. For example, all candidates may start with
25 Points and additional Careerious Match Points are
awarded/deducted for what may resemble the following:
[0150] 1 Point Candidate's profile 114 matches 1 employer 104
search.
[0151] 3 Points 1 employer 107 orders a Candidate Hiring Report on
candidate.
[0152] Erase All Points 1 employer (who orders a Candidate Hiring
Report) rates candidate's information as inaccurate.
[0153] Permanent Score of zero 2 employers (who order a Candidate
Hiring Report) rate candidate's information as inaccurate.
[0154] Each employer may only score 1 match per employer job
profile 102, 107, 100, to avoid employers abusing the system by
running-up their friends' Careerious Score for them. In other
words, if an employer has 3 job profiles, the highest score they
can give any one candidate is 3 matches (3 points), for example. 3
Points for a Hiring Report can only be scored once per employer,
per candidate. In other words, an employer can only award a
candidate 3 Hiring Report points ONCE.
[0155] Accordingly, in view of the above example framework score
determination, it is recognised that the framework score can be
based on a plurality of different match results of the candidate,
including the desired as well as determined quality of the match
results 106. Further, it is noted that the framework score can be
based on information obtained about the candidate from not only the
company 104 but from other companies 104 as well via their
experiences with the candidate and their profiles 107. It is
recognised that any of the above-provided parameter values are
given by example only for the various numbers.
Example Operation of the Customization Engine 250
[0156] Referring to FIG. 17, example operation 800 of the
customization engine 250 is shown for dynamically generating a
customized profile 107 for a company 104 for a selected profile
type, the customized profile 107 including a set of attribute 150
types, each of the attribute types having a customized attribute
range 152. At step 802, a receipt module 252 receives a predefined
profile 100 corresponding to the selected profile type, the
predefined profile 100 having predefined attribute 150 types
corresponding to the set of attribute types, each of the predefined
attribute types having a predefined attribute range 152
representing a range of attribute values for the selected profile
type. At step 804, the receipt module 252 receives a plurality of
personal assessments 99 of individuals (e.g. employees,
past/present/future) related to the company 104, each of the
personal assessments 99 having questions related to one or more
attributes 150 of the set of attribute types, each of the questions
having a value assigned by the respective related individual. At
step 806, a profile module 258 calculates determined attribute
ranges 152 for each of the attribute types of the set of attribute
types based on the values of the questions, and generates the
customized attribute ranges 152 as a combination of the determined
attribute ranges 152 with the predefined attribute ranges 152. At
step 808, an output module 264 stores or otherwise outputs the
generated customized ranges 152 as the customized profile 107.
Optionally, at step 810, the profile module 258 selects personal
assessments 99 corresponding to one or more of the related
individuals and removes the corresponding attribute values from the
combination prior to generating the customized profile 107.
Optionally, at step 812, an aggregator module 260 combines two or
more of the plurality of customized profiles 107 to generate an
aggregated customized profile 109. At step 812, the aggregator
module 260 compares at least one of a plurality of aggregated
customized profiles 109 with one another 109 or a selected
customized profile 107 with one or more aggregated profiles 109,
the comparison for identifying a dynamic shift in time in general
company staff values associated with the personal assessments.
Example Raw Score Conversion Process
Converting Raw Scores on Core Personality Attributes and Work
Interest to "Sten-Like" 1-10 Scales
The Problem
[0157] To put scales scores on a sten scale, CareerXact's scoring
methodology must convert raw scores (I don't know the formula for
producing raw scores) into sten scores by applying a normative
percentile rank distribution of raw scores to create sten scores.
Each sten score is defined as the score achieved by a certain
percentage of respondents. For example, 10 is defined as the score
achieved by the top 3%, approximately. All these percentages are
shown here for the sten scale
TABLE-US-00001 Sten Score Percentage of Respondents 10 3% 9 4% 8 9%
7 15% 6 19% 5 19% 4 15% 3 9% 2 4% 1 3%
For the new Careerious scales, in cases where one doesn't yet have
any normative data so we don't know what raw scores are achieved
by, say, 3% of the respondents to know what raw scores should be
assigned a sten score of 10.
Interim Solution
[0158] One interim solution until we have accumulated enough
Careerious data to have stable estimates of the percentile rank
distributions of raw scores on each attribute (ie all 16 core
psychological attributes and 3 Work Interests), we cannot convert
the Careerious raw scores into true sten scores for any attribute.
However, we can transform the raw scores on each attribute into a
1-10 scale such that the highest possible transformed score is 10
and the lowest is 1
Proposed Transformations for Converting Careerious Raw Scores to
1-10 Scale Scores
[0159] Different transformations are used for (a) the Socially
Desirable Responding scale, (b) the other 15 core personality
scales, and (c) the 3 Work Interest scales. This is because there
are different numbers of items in these three groups of
scales--there are 10 items in the Soc Des Responding scale, 6 items
each in the 15 core personality scales, and 12 items each in the 3
Work Interest scales. The number of items directly impacts the
maximum and minimum possible raw score values.
Step 1. Compute Raw Score.
[0160] The process of transforming raw scores into 1-10 scales
scores begins in the same way for all 19 attributes for each
person. The first step is to compute that person's raw scores on
all 19 attributes. (NOTE: for any particular attribute, a person's
raw score is simply the sum of assigned score points for his/her
chosen responses across all the items that comprise that attribute.
Remember, for the core personality attributes and the Soc Des
Responding scale, the assigned score points must take into account
the sign of the item. This is not the case for the Work Interest
items because they are all, in effect, positively signed items.)
For the 16 core personality attributes, including Soc Des
Responding, the response scale is -3, -1, +1, and +3. That means
for the core personality attributes that use 6 items, the maximum
raw score is +18 (if the person choose the most "highest" response
for all 6 items, s/he would accumulate +18 raw score points; +3
points for each of the 6 items.). The minimum raw score is -18.
Similarly, for the 10-item Soc Des Responding attribute, the
maximum raw score is +30 and the minimum raw score is -30. For the
3 Work Interest scales, we have not confirmed a response scale.
However, the -3, -1, +1, and +3 response scale would work just as
well for the Work Interests as it does for the core personality
attributes so this transformation process will assume that the same
response scale is used for all Careerious raw scores scales. In
that case, the maximum possible raw score on a Work Interest scale
is +36; the minimum possible score is -36. All of these scales must
be transformed to scales that have a maximum value of 10 and a
minimum value of 1. These example transformations are shown below,
15 Core Personality Scales (6 Items) (Changed from the Original
Process) Transformed Score=See table-look-up in "Revised Core
Psychological Attribute Scoring Process" table below. Socially
Desirable Responding Scale (10 Items) (No Change from the Original
Process)
Transformed Score=[[Raw Score.times.3]/20]+5.50
Work Interest Scales (12 Items) (No Change from the Original
Process)
Transformed Score={Raw Score/8.00]+5.50
TABLE-US-00002 Revised Core Psychological Attribute Scoring Process
Table Current Scoring Rule Raw Score [Raw/4 + 5.5] New Rule 1 New
Rule 2 18 10.00 10.0 17 9.75 10.0 16 9.50 10.0 15 9.25 9.8 14 9.00
9.6 13 8.75 9.4 12 9.50 9.2 11 8.25 8.7 10 8.00 8.3 9 7.75 7.7 8
7.50 7.3 7 7.25 6.8 6 7.00 6.5 5 6.75 6.2 4 6.50 5.7 3 6.25 5.3 2
6.00 4.7 1 5.75 4.3 0 5.50 3.8 -1 5.25 3.5 -2 5.00 3.2 -3 4.75 2.8
-4 4.50 2.5 -5 4.25 2.2 -6 4.00 1.8 -7 3.75 1.8 -8 3.50 1.8 -9 3.25
1.5 -10 3.00 1.5 -11 2.75 1.5 -12 2.50 1.2 -13 2.25 1.2 -14 2.00
1.2 -15 1.75 1.0 -16 1.50 1.0 -17 1.25 1.0 -18 1.00 1.0
* * * * *