Profiles
The Resume Analytics
Sample Profiles
How and Why?
Dear Jobseeker / HR manager /
Headhunter:
The very first thing you want to
know is
- What is “Profiles”? How is it different from
a plain text resume?
- How do Profiles get generated?
- How do Profiles help – a jobseeker – a HR manager –
a headhunter?
A detailed explanation will take
many pages – but here are brief answers:
What is Profiles? How is it
different from a plain text resume?
A text resume contains lots of
data/facts, which are quite often difficult to locate/pinpoint and even more
difficult to grasp within a short time. Ours software "reads" these
data/facts and presents the same to you in a GRAPHICAL manner (Knowledge
Presentation), making it very easy for you to understand within a matter of
seconds. You may say, “Profiles are Personnel Analytics”. We say, “Profiles are
the new currency of recruitment”.
How do Profiles get generated?
Education Profile ( GuruMantra ) / Career
Track
These graphs are generated based
on the data furnished by a jobseeker in the “Submit Resume” form. These are
“Stand-Alone” charts (without any comparison with other registered candidates)
Tenure Profile / Salary Profile
Here you find “frequency
distribution curves” of all the candidates registered with us. The data of the
candidate whose Profiles you are looking at, is super-imposed on the curve.
This brings out his/her “relative standing” within the population.
For “Tenure Profile”, we are
super-imposing, that candidate’s current tenure (i.e. for how many years is
he/she working in the current job?). Similarly in “Salary Profile”, we
use his/her salary in the current job.
We expect/presume that the
candidates will come back and edit their data, at least once-a-year, to ensure
that his/her Profiles remain up-to-date. Editing more frequently will only
ensure accurate presentation.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles
The Resume Analytics
Note
For the moment, “Salary Profile”,
takes into account candidates who are at the same designation-level (i.e.
Senior level/Middle level/Junior level etc.). Before long, “Salary Profiles”
will only compare those candidates
- who are at same Designation-level, and
- who belong to same “Function”, and
- who belong to same “Industry”
In a similar way, as far as
“Tenure Profile” graph is concerned, we will present separate graphs for
frequency distribution of
- tenures during FIRST jobs
- tenures during SECOND jobs
- tenures during THIRD jobs
- tenures during CURRENT jobs etc etc.
This will give a true “Apple-for-Apple”
comparison.
Function/Industry Profiles
These, perhaps, are the most
intriguing (and the most valuable!) of all the Profiles! Writing a logic for
these was not easy. We had to literally mimic the way the brain of a Recruiter
deciphers the meaning/the context/the importance, of each & every word in
the resume. That helped us figure-out the level of \bullet Knowledge \bullet
Skills \bullet Expertise, of the concerned candidate, and then assign a “Raw
Score”. Having done that, computing “Percentile” was relatively straight
forward.
But, a human being (-and
therefore his/her resume) is not a binary phenomenon (Yes / No – Black/White –
True/False).
A living person is many
splendoured, with varying degrees of skills/expertise in many
areas/subjects/functions. So our algorithm measured these and assigned scores
on three top functions. This enables a recruiter to evaluate each candidate on
more than one function – (what any good recruiter does all the time – except
subconsciously).
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles
The Resume Analytics
Currently “Function Profiles”
compare all executives belonging to the same Function, ignoring their
“Designation Levels” (Senior/Middle/Junior). As soon as we accumulate
sufficient data, we will differentiate and display graphs for executives
belonging to same function and who are at the same
designation-level. This will give a better comparison.
How do Profiles help?
If you are a Jobseeker
- Now you know where you stand (along several
dimensions), vis-a-vis other similar professionals. You can compare
yourself with others. Afterall we live in a competitive/relative world.
- Profiles will get noticed by Recruiters – and get
read. You cannot say the same for a plain text resume. When you send
Profiles, you increase your chance of being called for interview. Of
course, you will enjoy this “Competitive Advantage” only so long as other
candidates continue to send plain text resumes!
If you are a HR Manager
- You can glance at – and comprehend – 200 Profiles
in a day (- but no more than 20 plain text resumes in same time! – a
productivity gain of 1000 percent!)
- You vastly improve the “Quality” of your
hiring decisions, when you insist upon Profiles. You are unlikely to make
a mistake.
- And if you decide to interview job-applicants
using (When we launch Interactive Interview Tool/IIT in the next
few weeks), you will have online access to over 160,000
job-knowledge related interview questions, specifically linked to the
keywords / skills/knowledge/expertise \ldots mentioned in a candidate’s
resume [-increasing your productivity by 10, 000 percent!
If you are a Headhunter
- If you send Profiles to your Corporate Clients, but
your competitor sends plain text resumes, then your candidates are
likely to get called for interview / get appointed.
- When you send Profiles (instead of plain text
resumes) to your Corporate Client, you are making a real “Value
Addition”, instead of acting like a postman.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles
The Resume Analytics
all, you are getting paid for
“adding value” to a Client’s recruitment process. That is your client’s main
reason for outsourcing!
- One important “Value Addition” that your
corporate Client expects you to make, is to ensure that the resumes you
send are not faked/fudged.
- In Profiles, it is very difficult for a candidate
to fake/fudge his resume (although not impossible). Any
anomaly/gaps (in Edu. Qualifications/Years of experience/Designation
levels etc.) get transparently highlighted in respective graphs.
- You will be able to catch such lapses (inadvertent
or deliberate) immediately – which is, always, much better than your
Corporate client discovering these !
- When you insist on Profiles, you save a lot of
embarrassment. Your corporate client will not call back to say,
- Why did you send me resumes of candidates with
poor/mediocre subject – knowledge? [Function Profiles/KarmaScope]
- Why did you send me resumes of guys who are
already drawing more salary than what I indicated to you? [Salary
Profile]
- Why did you send me resumes of job-jumpers?
Contented Cows? [Tenure Profile / Career Profile]
- Why did you send me resumes of “Slow-learners”?
Semi-literate? [Education Profile]
- Why did you send me resumes of candidates who took
20 years to become “Manager”? [Career Track]
- Why did you send me resumes of candidates who have
only worked in small companies/small towns? [Experience Table]
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
The Resume Analytics
Unanswered Questions ?
Dear HR Manager / Headhunter
You always had many questions to
a candidate during a personal interview.
But unless you made meticulous
notes on the candidate’s text resume printout beforehand, you tend to forget (
to ask ), quite a few.
And, unfortunately, the text
resume itself cannot answer your questions !
Whereas, a “Profiles”, not only
raises relevant questions, our graphical / relational presentations, even
answers most.
Listed below, are these questions
that “Profiles” asks – and answers too !
Career History
- What is his total experience ? Does this match with
the experience required for our position/vacancy ?
- During this “total experience”, how many jobs has
he changed ?
- Does he seem to be a “job-jumper” ?
- Does he seem to have stuck to the same organisation
for a long time ? What could be the reason ?
- Does he seem to have stuck at the same “Designation
– Level “ for a long time ? Was he “un-promotable” ?
- He seems to have got very frequent promotions
/salary-raise. Does he come through as a “Fast Track” candidate ?
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
The Resume Analytics
- Given his “Average/Longest/Minimum” tenure with the
companies where he worked, how long can we expect him to stay with us ?
- He is in his current job for less than a year. Why
is he keen to quit within such a short period?
- Is he platueing? i.e. rose very rapidly in early
years but now seems to have slowed down.
- In terms of the size/turnover/reputation of the
companies where he has worked, does he seem to have steadily “progressed”?
Are there any reversals? i.e. leaving a large/organized company to join a
small/family owned company.
- Has he spent his entire career in one city or is he
mobile?
- Does his “Total Years of Experience” tally with his
current age? If not, does he seem to have “inflated” his experience? Or,
he should have got 20 years of experience by now, but graph shows only 12
years? Has he failed to “list” some “unfavourable” tenures? eg. where his
services were terminated or where the service was “temporary/contractual”
?
- Did any of the companies that he worked for, belong
to his father/relative ? If so, what was his designation/salary during
such tenure? Was that commensurate with his qualifications/experience ?
- During his career, were there any periods of
“self-employment” ? If so, has he listed those in his “Career History”
section ? What factors made him “start/give-up” such self employment ?
Salary
- He seems to have picked-up a huge salary-jump,
everytime he changed jobs. What kind of salary-increase would he expect us
to offer to motivate him to change ? Can we afford ? Would that upset a
lot of our existing employees and demotivate them ? Would we be upsetting
the apple-cart ?
- Has his salary kept pace with his rise up the
career ladder ? Is his salary lagging behind/way ahead of a majority of
his co-professionals ? How does it compare with similar professionals in
our organisation ?
- What seems to be his “trade-off” between
a) Salary
b) Designation Level ?
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles
The Resume Analytics
Would he be prepared to accept
Same salary ( his current salary
), if offered a higher/better designation ?
Same designation ( his current
designation ), if offered a higher salary ?
Academic Inputs
SSC
HSC
Bachelor’s Degree
Master’s Degree
Do these seem reasonable ?
- What no. of years did he take to pass
Bachelor’s Degree
Master’s Degree
Does he seem to have taken longer
than stipulated period ? Could he have failed once – or more?
- Were any of these qualifications obtained through
“Correspondence – Course” ? or through “Part-time study” in evenings ? If
so, for how long ?
- What about the educational
institutions/universities that he attended ? Are these
recognized/reputed/accredited institutions?
- Why did he not pursue higher studies in the same
institution/university ? Why did he have to go to another state/country ?
- Is there an “overlap” between
Completion of his education, and
Start of his first job ?
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles
The Resume Analytics
If yes, how did he manage that ?
- If there is a substantial “gap” between
Completion of his education and
Start of his first job
Then, what did he do during that
period ?
- He seems to have obtained more than one
degree/diploma during the same year. How did he manage that ?
Our Secret
Monkeys recognise each other by
comparing faces to an average stored in their brains, not by memorising what
every monkey looks like, scientists say. And that probably also goes for
people, explaining how humans can recognise faces in a fraction of second,
according to study published in Nature. The scientists found a monkey's brain
did not keep1 track of different parts of a face, storing and then accessing
the information to recognise others. Instead, it keeps statistical average of
the faces it has seen and uses it as a basis for comparison.
“When it sees a new face, it
compares it to this average and then it remarks upon the differences and that
is how the face is seen”, said David Leopold of the US National Institute of
Mental Health. “It elucidates how it is possible that you can so quickl2y and
effortlessly, in just a few hundred milliseconds, recognise faces.”
Source: The Times of India,
Mumbai
Friday, July 7, 2006
Patterns and Correlation
The world of data can be
dreadfully boring or wildly fascinating, depending on how you see it. For Thomas
Davenport, distinguished professor of management and information technology
at Babson College, USA, the right kind of numbers can open up a world of
endless possibilities, and take decision-making to a whole new level.
Data and analytics-the science, or art, of slicing and dicing data to arrive at
underlying patterns and correlations – may to be entirely new, but it’s
certainly changing how the world’s largest and most progressive companies like
Wal-Mart, P&G, Amazon and Dell, compete today. And Davenport is the most
passionate evangelist of this route to business success.
A widely acclaimed author and
speaker on information and knowledge management, business process reengineering
and electronic business and markets, Davenport contends that in a complex and
dynamic world, analytics is the CEO's best friend. Because numbers tell
the real story, devoid of biases and subjectivity that comes with
decision making done “from the gut”. Yet, most companies that use
analytics aren't able to fully leverage its benefits, relegating it to a
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
The Resume Analytics
backroom technique that mostly
validates decisions already made. In that respect, it's long way from becoming
a strategic tool in the corporate boardroom.
Companies need to realize that competing
on analytics is, first and foremost, about culture and mindsets. In
this exclusive interview, Davenport shares a few tips on how organisations can
maximize the benefit they can derive form analytics, and how they can deal with
some of challenges that come with it.
How can a company make the
transition from an intuition driven environment to that of fact-based decision
making?
There are two fundamentally
different approaches. One is, you have a senior executive, usually a CEO, who
really understands analytics, and what it can do for the business. There
are cases when a new leader came in and started it. This is true of dotcoms
like Yahoo and Amazon. When you have that level of execution support from the
beginning, it's very easy to build your company around it and make it more
tumorous. If you don't have that level of support then you need to create it by
demonstrating the value of analytics. Pick some areas of business for
a pilot and show what the results are, and try to spread it beyond that
department with sympathetic executives who are willing at least try it in their
business areas.
What about the experience and
knowledge that resides within people in traditional organisations?
I am not doubting the value of
experience overall, but I think there are certain problems that are way too
complex for companies to deal with purely through experience. Take banking, for
example. Figuring out at what point a customer will want a credit card is too
complex to do on the basis of experience. The other problem with the
experienced-team model is that they aren't fast enough. In the US, you can have
four mortgage offers in five minutes over the internet. So you really can't wok
with human experience based models, as humans can't decide quickly enough.
How does one deal with
resistance to change?
It's a major change to go from a
experience based approach and intuitive decision making to an analytical
approach. That's one reason why you need some support because it's hard for
people to change the way they have looked at their business for years. And if
you are one of the middle level managers, for example, and you want to create a
more analytical approach in your company, you have to go up and get
support for value that's demonstrated on smaller projects, and then with that
support, you can start changing the culture of the company. You don't really
change the decision-making culture without senior management support.
Why is this the best time for
companies to invest in analytics?
From a supply standpoint, a lot
of organisations have the data or they have been trying to put in place for a
number of years, either transaction data from ERP systems, or point of sales
data. In any case, companies are better equipped with data than before, and
there is a lot of software and
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
The Resume Analytics
hardware available. The software
vendors for analytics are producing much more capable software than what they
used. When they sourced software from a variety of vendors. Now they're
increasingly offering an integrated package. From a demand standpoint, companies
need to compete on the basis of key business processes and the way you optimize
those processes with analytics.
Source: The Economic Times, July
21, 2006
Q. Why “Profiles” ?
Ans: Profiles will make your
recruitment process
Better
From the keywords contained in a
given resume, “Profiles” determines, three FUNCTIONAL PROFILES of the
candidate concerned. “Profiles” automatically decides to which of the many
“Functions”, does this candidate belong to. Which are the top 3 functions in
which this candidate has maximum exposure ?
Not only does “Profiles”
automatically assign “raw score” for each functional profile, it also computes
the “percentile” of a given candidate !
So now, not only you get to know
- Which functions does this candidate belong to ?,
you also get to know,
- Where exactly he stands in relation to other
executives, belonging to the same function ? What is his rank amongst
“Co-professionals” ?
“Profiles” graphical/visual
representation of a candidate’s competence level (percentile) within a matter
of seconds, answers your following question :
“Is this person good enough to be
called for an interview ?”
In a normal course, you would
reach this conclusion only after you have carefully studied the entire resume
and formed a “global impression” of the candidate ( Viz : A = Excellent / B =
Good / C = Average / R = Reject etc. ). Then you would need to record your
“impression/rating” on a piece of paper or on the hardcopy of the resume.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
But at this stage, your
"rating" is kind of "isolated/stand-alone".
Your "rating" does not
tell you the relative "ranking/standing" of that candidate in
relation to hundreds/thousands of Co-professionals
For finding the
"relative" standing/ranking, you will need to
- Study all the resumes
- Rate all the resumes
- Arrange all candidates in descending order of their
"rating"
Even then, your approximation (
all As in top group / all Bs in middle group / Cs in bottom group etc.), does
not readily tell you the "percentile" position of a given
candidate.
Such a percentile-ranking is only
possible if, instead of simply rating a resume/candidate, as A/B/C/R, you were
to assign some "marks" to that resume, such as:
|
Function : Materials
Management
|
|
|
|
Candidate
|
Score
|
Out of
|
|
Mhatre
|
43
|
100
|
|
Patel
|
76
|
100
|
|
Venkat
|
55
|
100
|
Such refined/precise scoring
requires accurate judgment.
Such a judgment is a highly
complex mental process, which is possible for a highly trained/ experienced
expert who does not tire-out, even after scoring 1000 resumes!
In projection of Functional
Profile, graphically, it is such a complex mental process that IndiaRecruiter
mimics - and succeeds.
That is why it is "Better".
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
- Faster
How long does it take a human
expert to
- Carefully study a resume
- Conclude that this candidate is
- Excellent in "Marketing" (A)
- Good in "Sales" (B)
- Average in "After-Sales Services" (C)
I would say, 10 minutes/resume.
Some of you may be able to do this in 5 minutes. So, a clever/ hardworking
manager can "rate" 80/100 resumes in 8 working-hours.
But this is a theoretical
calculation.
In reality,
- You never get 400 undisturbed working minutes in a
day.
- Looking at / studying email resumes on a computers
screen for 8 hours/day, day-after-day, will wear you out, drain your
energies, cause you eye-strain and carpal tunnel syndrome, dim your mental
faculties, and impair your judgment \to It is very difficult to get rated
at the end of the day.
But even if you are a truly
exceptional person, you will find it very difficult to "rate" a
candidate on three different "Functional Areas", simultaneously, viz.
Marketing/Sales/After Sales Service.
If you try to juggle these 3
balls at a time, your output may well drop to 30/40 resumes in a day.
This is without taking into
account the fact that the next resume you pick-up for rating, belongs to an
executive, whose
- PRIMARY function is "Manufacturing"
- SECONDARY function is "Quality Control"
- TERTIARY function is "Materials
Management"
So, you have to be a
"Superman" to juggle more than a hundred functional-balls at the same
time! or else, your daily output would further drop to 10/15 resumes.
But when you are going through
"Profiles" (instead of plain text resumes) you can zero-in on 5 good
candidates ( out of 500 ) within 2 hours!
No wonder, when you use
"Profiles", you recruitment process gets, truly "FASTER"
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
PEN: 121174 P - 121174
Name: Rahul Deodhar
Date of Birth: 9/29/1973 City:
Mumbai
My Function / Industry Profile
|
My Function / Industry
Profile
|
Raw Score
|
Percentile
|
Co-Professionals
|
|
Primary Function = IT -
Software Development
|
7256
|
86
|
11163
|
|
Secondary Function = IT -
ERP / CRM
|
838
|
85
|
1290
|
|
Tertiary Function = IT -
eCommerce / Internet
|
3218
|
46
|
4950
|
My score with respect to
population = 86 Percentile
My score with respect to
population = 85 Percentile
My score with respect to
population = 46 Percentile
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
The "Function / Industry
Profile" graph is a group of 3 graphs, which specify the top three
functions or industries for a particular candidate. What each of these graphs
shows is the standing of a candidate relative to his/co-professionals present
in our database. The graphs show the "Raw Score" of a candidate based
upon the keywords present in his resume and the "Percentile Score"
with respect to other co-professionals. The graphs also show the sample size
i.e. the no. of co-professionals with whom the candidate has been compared. The
graphs also show the mean, +1 \sigma (sigma) and -1 \sigma (sigma) values which
determine the trend followed by 68\% of the sample population. If a candidate's
standing falls before -1 \sigma (sigma) line, then it means that he/she hold a
very low score and if he/she falls beyond +1 \sigma (sigma) line, then
it means that he/she lies amongst the cream of the population.
ATTN: RECRUITERS
Based on the keywords present in
a candidate's resume, our AI Software determines
Determines the Function/Industry
of that person (primary/secondary/tertiary)
If a person has many skills- some
good, not so apparent
Assigns the Raw Score \to [a
standalone attribution] in each case
Computes the "Percentile
Score" [candidate's relative standing amongst co-professionals]
Charts the "Frequency
Distribution Curve" of the Raw Scores of all Co-Professionals
Calculates & displays, values
for Mean (standard average score) / standard deviation (\sigma)
Approx. 68\% of the
co-professionals' raw scores, lie between +1\sigma and -1\sigma (standard
deviation) of the Mean.
Obviously, HR Managers
Time-pressed HR Managers,
would want to go thru the rest of the Profile, only in those cases where "My
Standing" (a candidate's Raw Score) is better than +1\sigma.
Interpreting Profiles, saves them a lot of time/wasted effort, by zeroing onto
the most competent candidates. in matter of seconds! They can even interview
the candidate online by entering this candidate's Permanent Executive
Number (PEN) into our page IIT (Interactive Interview Tool).
ATTN: JOBSEEKERS
As more & more resumes get
added into our database, your Profile keeps changing dynamically (Raw
score/percentile/mean/std. deviation/No. of co-professionals). Get your
friends/collegues to register; then compare/contrast your Profiles. You can get
some bragging and download your Profile everymonth and re-discover your
standing amongst your friends.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Salary Profile
co-professionals = SENIOR
Level
|
SALARY IN LAKHS (Rs)
|
NUMBER OF EXECUTIVES
|
|
68% OF PEOPLE (\pm 1 \sigma
sigma)
|
11 - 17
|
1095
|
|
MY CURRENT SALARY
|
17
|
91
|
|
MORE SALARIED PEOPLE
|
|
0
|
|
LESS SALARIED PEOPLE
|
|
1
|
|
EQUAL SALARIED PEOPLE
|
|
1
|
|
TOTAL POPULATION
|
|
1157
|
The "Tenure Profile"
graph shows the relative standing of a candidate amongst his
co-professionals with respect to his salary. It is an indication that helps HR
to determine if the candidate is overpaid or underpaid \to Salary Profile.
The graph also shows the mean, -1 \sigma (sigma) and +1 \sigma (sigma) values.
The table below the graph shows the trend, the candidate's standing, and the
no. of candidates having tenure which is less than, equal to and more than the
tenure of the present candidate. It also shows the total sample population.
The heading of the graph
indicates what is the designation level of the co-professionals compared.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Tenure Profile
|
TENURE IN YEARS
|
NUMBER OF EXECUTIVES
|
|
68% OF PEOPLE (\pm 1 \sigma
sigma)
|
1 - 5
|
2397
|
|
MY CURRENT TENURE
|
2
|
364
|
|
PEOPLE WITH MORE TENURE
|
|
809
|
|
PEOPLE WITH LESS TENURE
|
|
4
|
|
PEOPLE WITH EQUAL TENURE
|
|
3570
|
|
TOTAL POPULATION
|
|
|
The "Salary Profile"
graph shows the relative standing of a candidate amongst his
co-professionals with respect to his salary. It is an indication that helps HR
to determine if the candidate is overpaid or underpaid. The graph also shows
the mean, -1 \sigma (sigma) and +1 \sigma (sigma) values. The table below the
graph shows the trend, the candidate's standing, and the no. of candidates
having tenure which is less than, equal to and more than the tenure of
the present candidate. It also shows the total sample population.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Career Profile
|
Score card as on 11/30/2006
|
|
|
|
1
|
Current Age
|
33
|
|
2
|
Age When Passed First
Degree/Diploma
|
21
|
|
3
|
Years taken to pass Second
Degree/Diploma
|
0
|
|
4
|
Age at which First Job
Started
|
22
|
|
5
|
Years Elapsed Since First
Degree/Diploma
|
12
|
|
6
|
Total Years Of Experience
Indicated
|
11
|
The "Career Profile"
graph shows the trend that a candidate has followed over the years of
his career. It indicates the no. of years he/she has remained at a particular
designation level. The graph also have a table which shows the date of
generation of the graph, the current age, the age when passed the first
degree/diploma, the years taken to pass the second degree/diploma, the age at
which the first job started, the years elapsed since first degree/diploma and
the total years of experience indicated.
You can easily come to know of
any ambiguity in the data provided by the candidate by glancing through the
table/The number in the 5^th row and 6^th row should normally match. Similarly,
the number in the 5^th row and 6^th rows should match. Plus, the sum of the
numbers in the 2^nd and 3^rd, or 2^nd and 3^rd, or 4^th and 5^th, or 5^th and 6^th
rows should be equal to the number in the first row.
"Career Profile"
makes it very easy to detect a fake/fudged resume! No place to hide!
No ambiguity - NO anomaly - NO
incongruence!
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Experience
|
Employer Name
|
No. of Years
|
Designation
|
Designation Level
|
City
|
Annual Salary (In Lakhs)
|
|
TCS
|
2
|
Project Manager
|
Senior Manager
|
Mumbai
|
17.00
|
|
Orient Software
|
5
|
Team Leader
|
Manager
|
Mumbai
|
10.00
|
|
RecruitGuru
|
4
|
Software Developer
|
Entry Level
|
Mumbai
|
2.00
|
My KarmaScope
|
Primary Function: IT -
Software Development
|
Secondary Function: IT -
ERP / CRM
|
Tertiary Function: IT -
eCommerce / Internet
|
|
.NET
|
APPLICATION DEVELOPMENT
|
ASP
|
|
ASP.NET
|
DATABASE
|
JAVA
|
|
APPLICATION DEVELOPMENT
|
LAN
|
JSP
|
|
C++
|
ORACLE
|
OPERATING SYSTEMS
|
|
DEVELOPMENT.
|
PROGRAMMING
|
WEB DESIGNING
|
|
JAVA
|
REPORTS
|
OPERATING SYSTEMS
|
|
JDK
|
SQL
|
PL/SQL
|
|
JSP
|
OPERATING SYSTEMS
|
PROGRAMMING
|
|
MS-ACCESS
|
PERSONAL
|
REPORTS
|
|
OBJECT ORIENTED
|
PROGRAMMING
|
SQL SERVER
|
|
OPERATING SYSTEMS
|
REPORTS
|
VB
|
|
PL/SQL
|
TESTING
|
OPERATING SYSTEMS
|
|
PROGRAMMING
|
|
OBJECT ORIENTED
|
|
REPORTS
|
|
|
|
SQL SERVER
|
|
|
|
VB
|
|
|
The "KarmaScope"
is basically the list of keywords for the three top functions or industries
that the candidate claims to have knowledge about. You can ask questions based
on the keywords shown in the KarmaScope.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Education Profile
The "Education
Profile" graph shows the trend that a candidate has followed
over the years of his academic career. It indicates the no. of years he/she has
taken to pass a particular education level. Plus, it shows the degree passed at
each level and the no. of years taken to successfully pass the degree.
My Educational Qualifications
|
Degree
|
Branch
|
Level
|
Pass Year
|
Institution
|
|
B. E.
|
Computer Science
|
Graduate
|
1994
|
K. G. C. O. E., Karjat
|
|
12^th Std.
|
Science
|
H.S.C. OR Equivalent
|
1990
|
G. N. Khalsa College
|
|
10^th Std.
|
N/A
|
S.S.C. OR Equivalent
|
1989
|
I. E. S. S. Eng. Med. Secondary
School
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
Profiles: The Resume Analytics
My Personal Details
|
Contact Information
|
|
|
|
Address
|
: 168/E, Ganesh Niwas, Vikas
Wadi, Dr. Ambedkar Road, Dadar (E), Mumbai - 400014.
|
Home Phone
|
|
|
Work Phone
|
|
Country
|
: INDIA
|
Mobile
|
|
|
Email
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
At this point of time, because we
don't have enough data, the graphs are generated taking into consideration only
the designation level and the function/industry of the candidate. When we have
accumulated enough data, we will generate the graphs based on designation
level, function/industry, age, salary, etc. so that it becomes a true apple to
apple comparison.
(My Text Resume)
Profiles
The Resume Analytics
My Text Resume
Rahul Deodhar
|
Detail
|
|
Information
|
|
Permanent Address
|
:
|
168/E, Ganesh Niwas, Vikas
Wadi, Dr. Ambedkar Road, Dadar (E), Mumbai - 400014.
|
|
Telephone Number
|
:
|
(Residence) 022 – 24144203
(Mobile) 9820649667
|
|
E – mail
|
:
|
rahul_d@yahoo.com
|
|
Date of Birth
|
:
|
29th September 1973
|
|
Nationality
|
:
|
Indian
|
|
Marital Status
|
:
|
Married
|
Job Objective:
To be a part of an esteemed
organization like yours and to gain experience in various stages of project
development that will help me excel in the field of software development.
Special Achievements:
- Completed the SL275 course for Java from Sun
Microsystems with 'Outstanding' grade.
(Educational Background &
Top Skills)
Profiles
The Resume Analytics
Educational Background:
|
Detail
|
|
Information
|
|
Highest Education Level
|
:
|
Bachelor of Engineering (B.E)
|
|
Field of Study
|
:
|
Engineering (Computers)
|
|
Percentage
|
:
|
59%
|
|
University
|
:
|
Mumbai
|
Current Functional Area:
Requirement gathering and
analysis, Logic development, Modularisation, UML Modelling, Flowcharting,
Scheduling.
Top Skills:
|
Skill
|
Experience
|
Proficiency
|
|
Project Designing, Management
& Development
|
1 Year
|
Advanced
|
|
Unified Modelling Language
(UML)
|
1 Year
|
Advanced
|
|
Core Java
|
6 Months
|
Advanced
|
|
Java Servlets
|
1 Month
|
Intermediate
|
|
HTML
|
2 Months
|
Intermediate
|
|
C++ Language
|
1 Year
|
Intermediate
|
|
C Language
|
1 Year
|
Intermediate
|
|
Programming in Assembly
Language (8085, 8086, 80386)
|
1 Month
|
Intermediate
|
|
Development of Electronic
Gadgets
|
2 Years
|
Intermediate
|
|
Visual Basic 6.0
|
1 Month
|
Beginner
|
(Experience & Projects)
Profiles
The Resume Analytics
Experience:
- Currently working in TCS for 2 years as Project
Manager.
- Worked in Orient Software for 5 years as Team
Leader.
- Worked in RecruitGuru for 4 years as Software
Developer.
- Part of the core group responsible in the formation
of 'Techworks Technologies and Consultancy Services', which is a small
startup and is an integrated software development workgroup.
- Used to do freelance software development before
joining 'Techworks', for a period of 1 Year.
Projects:
1) "Automatic Temperature
Control System"
- Features:
- A system that controls the temperature for any
process.
- It has the ability to work continuously for huge
intervals of time, which may be as long as six to eight months.
- Has the ability to work under severe working
conditions and can handle massive temperature changes.
- Has a tolerance rating as low as 0.001\%.
2) Database Management Project
for a private dealer of bakery products.
- Features:
- Storing of customer and order data into the
database.
- Security of the customer data and order data.
- Access control for the system.
- Preparation of manufacture schedule.
(Projects & Extra
Curricular Activities)
Profiles
The Resume Analytics
Projects:
- Preparation of delivery schedule.
- Inventory management.
- Also includes customer reminders and inventory
alerts.
3) Employee data management
system
- Features:
- User friendly employee data handling system.
- Gives comprehensive information about each
employee.
- Extremely secure.
- Windowing technique used so that every person gets
access only to the data that he/she is concerned with.
4) Development of the website
IndiaRecruiter.net and GlobalRecruiter.net
- Features:
- Basically these websites are search engines for
the domain of recruitment.
- They have many features like Resume Parsing,
generation of profiles (7 graphs that analyse the skills, personality and
many other characteristics of candidates).
Extra Curricular Activities:
- Winner of Debate Competition held by K.G.C.E.,
Karjat in Second Year Engineering.
- Involved in the formation of a Training and
Placement Committee and was elected as the Vice – President of the
committee.
- Have designed and prepared many electronic gadgets
like Sonic controlled switch, Seven Digit Code Lock for bank vaults, Infra
Red Intruder alarm, Automatic water level controller, etc.
- Have taken part and won prizes in many Group
Discussion, Dramatics, Drawing, Martial Arts and Singing Competitions.
- Have taken N.C.C. (Air Wing) training and was
selected as the Best Cadet for the course. Also stood first in the school
for the 'A' Certificate Examination.
(Personal Information)
Profiles
The Resume Analytics
Personal Information:
|
Detail
|
|
Information
|
|
Willing to Travel
|
:
|
Light
|
|
Willing to Relocate
|
:
|
Will Consider
|
|
Possess Own Transport
|
:
|
No
|
|
Expected Monthly Salary
|
:
|
Rs. 15,000 (Negotiable)
|
|
Availability
|
:
|
Immediate
|
(My Function/Industry Profile)
Profiles
The Resume Analytics
|
Detail
|
|
Information
|
|
PEN:
|
121174
|
Name: Rahul Deodhar
|
|
Date of Birth:
|
9/29/1973
|
City: Mumbai
|
My Function/Industry Profile
Primary Function = IT –
Software Development
- Raw Score: 7256
- No. of Co-professionals: 11163
- My score with respect to population = 86
Percentile
Secondary Function = IT – ERP
/ CRM
- Raw Score: 838
- No. of Co-professionals: 1290
- My score with respect to population = 85
Percentile
Tertiary Function = IT –
eCommerce / Internet
- Raw Score: 3218
- No. of Co-professionals: 4950
- My score with respect to population = 46
Percentile
(Attn: Recruiters and
Jobseekers)
Profiles
The Resume Analytics
Attn: Recruiters
- Based on the keywords present in the candidate's
resume, our AI software determines the Function / Industry of that person
(primary / secondary / tertiary) – a person has many skills many are not
apparent.
- assigns the "Raw Score" [a stand-alone
attribute] in each case.
- computes the "Percentile Score"
[candidate's relative standing amongst co-professionals]
- charts the "Frequency Distribution Curve"
of the Raw Scores [of co-professionals] for each function.
- calculates and displays values for Mean (weighted
average score) / Standard Deviation. Approx. 68\% of the co-professionals'
raw scores lie between +1 Sigma and -1 Sigma (Standard Deviation of the
Mean).
Time-pressed HR Managers, would
want to go through the rest of the Profile, only in those cases where "My
Standing" (A candidate's raw score) is better than 12+1 Sigma.
Interpreting Profiles saves them a lot of time / wasted effort, by zeroing ont3o
the most competent candid4ates in a matter of seconds. They can even
interview the candidate by entering the Permanent Executive Number (PEN), into
our page IIT (Interactive Interview Tool).
Attn: Jobseekers
As more and more Resumes get
added to our database, your Profile keeps changing dynamically [Raw Score /
Percentile / Mean / Std. Deviation / No. of co-professionals]. Get your friends
/ colleagues to register; then compare / contrast your standing amongst your
friends. Come back and download your Profile every month and re-discover your
latest standing amongst your friends.
Moreover, as our database keeps
getting richer with more and more resumes, the comparison amongst
co-professionals will be done on the basis of their Salary scale, Age,
Designation Level, Function / Industry, etc. to have a true apple for apple
comparison.
(My Salary Profile)
Profiles
The Resume Analytics
My Salary Profile
co-professionals = SENIOR
Level
|
Salary in Lakhs (Rs.)
|
|
68\% OF PEOPLE ( \pm 1
SIGMA)
|
|
MY CURRENT SALARY
|
|
NUMBER OF EXECUTIVES
|
|
MORE SALARIED PEOPLE
|
|
LESS SALARIED PEOPLE
|
|
EQUAL SALARIED PEOPLE
|
|
TOTAL POPULATION
|
The "Salary Profile"
graph shows the relative standing of a candidate amongst his co-professionals
with respect to his salary. It is an indication that helps HR Manager to
determine if the candidate is overpaid or underpaid. The graph also shows the
mean, \pm 1 sigma and \pm 1 sigma values. The table below the graph shows the
salary range for 68\% of the co-professionals, the candidate's standing, and
the no. of candidates having tenure which is less than, equal to and more than
the salary of the present candidate. It also shows the total sample population.
The heading of the graph indicates what is the designation level of the
co-professionals compared.
(My Tenure Profile)
Profiles
The Resume Analytics
My Tenure Profile
|
TENURE IN YEARS
|
|
68\% OF PEOPLE (\pm 1 SIGMA)
|
|
MY CURRENT TENURE
|
|
NUMBER OF EXECUTIVES
|
|
PEOPLE WITH MORE TENURE
|
|
PEOPLE WITH LESS TENURE
|
|
PEOPLE WITH EQUAL TENURE
|
|
TOTAL POPULATION
|
The "Tenure Profile"
graph shows the relative standing of a candidate amongst his co-professionals
with respect to his tenure. It is an indication that shows how stable a
candidate is. It helps you to determine if the candidate is a 'job jumper' or a
'contented cover'. The graph also shows the mean, \pm 1 sigma and \pm 1 sigma
values. The table below the graph shows the trends, the candidate's standing,
and the no. of candidates having tenure which is less than, equal to and more
than the tenure of the present candidate. It also shows the total sample
population.
(My Career Profile)
Profiles
The Resume Analytics
My Career Profile
|
|
|
Score Card as on 11/30/2006
|
|
|
Current Age
|
33
|
|
Age When Passed First
Degree/Diploma
|
21
|
|
Years taken to pass Second
Degree/Diploma
|
0
|
|
Age at which first job
started
|
22
|
|
Years Elapsed Since First
Degree/Diploma
|
12
|
|
Total Years Of Experience
Indicated
|
11
|
The "Career Profile"
graph shows the path that a candidate has followed over the years of his
career. It indicates the no. of years he/she has remained at a particular
designation level. The graph also have a table which throws up some very revealing
analytics. A recruiter can easily come to know of any ambiguity in the data
provided by the candidate by glancing through the table. Hence, it becomes very
easy to detect a faked / fudged resume! No place to hide! No ambiguity – No
anomaly – No incongruence!
Profiles: The Resume Analytics
My Experience
|
Employer Name
|
No. of Years
|
Designation
|
Designation Level
|
City
|
Annual Salary (In Lakhs)
|
|
TCS
|
2
|
Project Manager
|
Senior Manager
|
Mumbai
|
17.00
|
|
Orient Software
|
5
|
Team Leader
|
Manager
|
Mumbai
|
10.00
|
|
RecruitGuru
|
4
|
Software Developer
|
Entry Level
|
Mumbai
|
2.00
|
My KarmaScope
|
Primary Function
|
Secondary Function
|
Tertiary Function
|
|
IT - Software Development
|
IT - ERP / CRM
|
IT - eCommerce / Internet
|
|
.NET
|
APPLICATION DEVELOPMENT
|
ASP
|
|
APPLICATION DEVELOPMENT
|
DATABASE
|
JAVA
|
|
ASP
|
LAN
|
JSP
|
|
ASP.NET
|
ORACLE
|
OPERATING SYSTEMS
|
|
C++
|
PROGRAMMING
|
WEB DESIGNING
|
|
DEVELOPMENT.
|
REPORTS
|
OPERATING SYSTEMS
|
|
JAVA
|
SQL
|
PHP
|
|
JSP
|
OPERATING SYSTEMS
|
PROGRAMMING
|
|
J2EE
|
PL/SQL
|
REPORTS
|
|
MS-ACCESS
|
PROGRAMMING
|
SQL SERVER
|
|
OBJECT ORIENTED
|
REPORTS
|
VB
|
|
OPERATING SYSTEMS
|
TESTING
|
OPERATING SYSTEMS
|
|
PL/SQL
|
|
OBJECT ORIENTED
|
|
PROGRAMMING
|
|
|
|
REPORTS
|
|
|
|
SQL SERVER
|
|
|
|
VB
|
|
|
The “KarmaScope” is basically the
list of keywords for the three top functions or industries that the candidate
claims to have knowledge about. You can ask questions based on the keywords
shown in the KarmaScope.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
My Resume Profile
The “Education Profile” graph
shows the path that a candidate has followed over the years of his academic
career. It indicates the no. of years he/she has taken to pass a particular
education level. Plus, it shows the degree passed at each level and the no. of
years taken to successfully pass the degree.
My Educational Qualifications
|
Degree
|
Branch
|
Level
|
Pass Year
|
Institution
|
|
B. E.
|
Computer Science
|
Graduate
|
1994
|
K. G. C. O. E., Karjat
|
|
12th Std.
|
Science
|
H.S.C. OR Equivalent
|
1990
|
G. N. Khalsa College
|
|
10th Std.
|
N/A
|
S.S.C. OR Equivalent
|
1989
|
I. E. S. Eng. Med. Secondary
School
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
My Personal Details
Contact Information
|
|
|
|
|
Address
|
: 168/E, Ganesh Niwas, Vikas
Wadi, Dr. Ambedkar Road, Dadar (E), Mumbai – 400014.
|
Home Phone
|
: 022–24144203
|
|
|
Work Phone
|
: 022–67060303
|
|
|
Mobile
|
: 98206 49667
|
|
Country
|
: INDIA
|
Email
|
: rahul_d@yahoo.com
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
My Text Resume
Rahul Deodhar
|
|
|
Permanent Address
|
: 168/E, Ganesh Niwas, Vikas
Wadi, Dr. Ambedkar Road, Dadar (E), Mumbai – 400014.
|
|
Telephone Number
|
: (Residence) 022 – 24144203
(Mobile) 9820649667
|
|
E – mail
|
: rahul_d@yahoo.com
|
|
Date of Birth
|
: 29th September 1973
|
|
Nationality
|
: Indian
|
|
Marital Status
|
: Married
|
Job Objective:
To be a part of an esteemed
organization like yours and to gain experience in various stages of project
development that will help me excel in the field of software development.
Special Achievements:
Completed the SL275 course for
Java from Sun Microsystems with ‘Outstanding’ grade.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
Educational Background:
|
|
|
Highest Education Level
|
: Bachelor of Engineering (B.E)
|
|
Field of Study
|
: Engineering (Computers)
|
|
Percentage
|
: 59%
|
|
University
|
: Mumbai
|
Current Functional Area:
Requirement gathering and
analysis, Logic development, Modularisation, UML Modelling, Flowcharting,
Scheduling.
Top Skills:
|
Skill
|
Experience
|
Proficiency
|
|
Project Designing, Management
& Development
|
1 Year
|
Advanced
|
|
Unified Modelling Language(UML)
|
1 Year
|
Advanced
|
|
Core Java
|
6 Months
|
Advanced
|
|
Java Servlets
|
1 Month
|
Intermediate
|
|
HTML
|
2 Months
|
Intermediate
|
|
C++ Language
|
1 Year
|
Intermediate
|
|
C Language
|
1 Year
|
Intermediate
|
|
Programming in Assembly
Language(8085, 8086, 80386)
|
1 Month
|
Intermediate
|
|
Development of Electronic
Gadgets
|
2 Years
|
Intermediate
|
|
Visual Basic 6.0
|
1 Month
|
Beginner
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
Experience:
- Currently working in TCS for 2 years as Project
Manager.
- Worked in Orient Software for 5 years as Team
Leader.
- Worked in RecruitGuru for 4 years as Software
Developer.
- Part of the core group responsible in the formation
of ‘Techworks Technologies and Consultancy Services’, which is a
small startup and is an integrated software development workgroup.
- Used to do freelance software development before
joining ‘Techworks’, for a period of 1 Year.
Projects :
1) “Automatic Temperature Control
System”
Features:
» A system that controls the
temperature for any process.
» It has the ability to work
continuously for huge intervals of time, which may be as long as six to eight
months.
» Has the ability to work under
severe working conditions and can handle massive temperature changes.
» Has a tolerance rating as low
as 0.001%.
2) Database Management Project
for a private dealer of bakery products.
Features:
» Storing of customer and order
data into the database.
» Security of the customer data
and order data.
» Access control for the system.
» Preparation of manufacture
schedule.
» Preparation of delivery
schedule.
» Inventory management.
» Also includes customer
reminders and inventory alerts.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
3) Employee data management
system
Features:
» User friendly employee data
handling system.
» Gives comprehensive information
about each employee.
» Extremely secure.
» Windowing technique used so
that every person gets access only to the data that he/she is concerned with.
4) Development of the website
IndiaRecruiter.net and GlobalRecruiter.net
Features:
» Basically these websites are
search engines for the domain of recruitment.
» They have many features like
Resume Parsing, generation of profiles (7 graphs that analyse the skills,
personality and many other characteristics of candidates).
Extra Curricular Activities:
- Winner of Debate Competition held by
K.G.C.E., Karjat in Second Year Engineering.
- Involved in the formation of a Training and
Placement Committee and was elected as the Vice – President of
the committee.
- Have designed and prepared many electronic
gadgets like Sonic controlled switch, Seven Digit Code Lock
for bank vaults, Infra Red Intruder alarm, Automatic water
level controller, etc.
- Have taken part and won prizes in many Group
Discussion, Dramatics, Drawing, Martial Arts and Singing Competitions.
- Have taken N.C.C. (Air Wing) training and
was selected as the Best Cadet for the course. Also stood first in
the school for the ‘A’ Certificate Examination.
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
Profiles: The Resume Analytics
Personal Information:
|
|
|
Willing to Travel
|
: Light
|
|
Willing to Relocate
|
: Will Consider
|
|
Possess Own Transport
|
: No
|
|
Expected Monthly Salary
|
: Rs. 15,000 (Negotiable)
|
|
Availability
|
: Immediate
|
Profiles: The new currency of
Recruitment. Issued by, www.IndiaRecruiter.net
RecruitGuru - The FUTURE of
Recruitment Web-Services
The Future of Recruitment
Web-Services
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Why RecruitGuru?
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Why Web-Service?
Team
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GuruMine
GuruSearch
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FAQ
GuruMine
Dear Recruiter,
You are getting thousands of
unstructured resumes against your job-advts, but these remain "unsearchable"
because, these are unstructured. And you end-up generating again & again
for identical vacancies | What GuruMine does, is to convert these unstructured
resumes into a structured database automatically, accurately, speedily.
GuruMine "extracts" nearly 23 "fields" from an
unstructured resume | So, anytime (now or in future), you can search this
database, for
- Name
- Age
- Experience
- Educational
- Qualification
- City / Country
- Function
- Industry
- Designation
- Current Employer
- Reports
- Address
- Phone No. / Email-Id
Our GuruMine even develops for
each candidate, a "Functional Exposure Profile" graph, for top
three functions, where his expertise lies. Not only does GuruMine
"score" each candidate's knowledge/skills (it even compares his
"score" with thousands of similar candidates in the database and
computes his "percentile" (his "standing" amongst
pear-group). So, now you can decide, whom to call for interview - just by
looking at the graph!
Key Features & Benefits
- Extracts key information from resumes automatically
and stores into a structured database
- Facilitates quick reading of incoming / existing
resumes by highlighting important keywords found in the resume
- Identifies keywords that are unique or uncommon
amongst similar profiles
- Helps in interviewing the candidate by displaying
highlight of what is mentioned in resume compared to an ideal profile
- Eliminates the manual entry of the data from the
resume to the Application Tracking System
- Reduces data entry errors, time consumed and
duplicate storing of the resumes
- Need not go through the entire resume manually in
order to identify the core skills of the candidates. The "Function
Exposure Profile" would enable the user to instantly identify the
core areas of a candidate's functional background.
- Process Resumes of various formats such as Word
Document, Email bodies, File folders, HTML documents etc.
http://recruitguru.com/GuruMine.asp 9/23/2003
