THE SCIENCE OF RESUME SCREENING
The
Machines are here:
Software
systems are everywhere. From banking to shopping, from traveling
to education, from whatever-you-can-think-of to
whatever-you-cannot-even-think-of, software are all-pervasive and
resume screening is no exception. While this is a great advance for
HR departments, this can be quite a scary prospect for job seekers as
a majority of resumes sent to these HRs are not read by humans. In
this article, we would like to educate you on the inner workings of
the resume screeners, a key component of Applicant Tracking Systems
(ATS).
The
Applicant Tracking System (ATS):
The
Applicant Tracking System helps HR managers streamline the various HR
processes such as recruiting, payroll, etc. within their
organization. Resume screening is an integral part of the ATS. HR
departments receive resumes in the thousands for every job posting.
ATS makes life much simpler for them by doing the laborious task of
going through resumes to shortlist candidates for an interview,
thereby saving a lot of time. While it makes complete sense from the
HRs' standpoint, it can kill a job seeker's chances of landing an
interview. For a job seeker, it is the ATS's way or the highway. Let
us now go into how the ATS screens resumes in order to level the
playing field for job seekers to give them a fair chance. Once the
job candidate uploads the resume, the following are the steps
performed by the ATS:
1.
The resume is parsed.
2.
The resume is evaluated against the job for a fit.
1.
The Resume is parsed:
What
does this mean? The ATS expects the resume in a certain standardized
format. This standard has been adopted by the HR community in order
for HR systems to be able to communicate with each other easily.
Candidates
create resumes using different file formats and in very different
fashions. For example, one candidate could call the work history
section of the resume as "Work Experience", whereas another
candidate could call it "Professional Background". It is
the job of the resume parser to categorize these as work history so
they can be evaluated uniformly. The job seeker's job is to create a
parser-friendly format of the resume. It is important to understand
that resume parsers can only do so much. Higher the resume compliance
with the HR standards(something that the parser looks for), higher
the chances of correctly interpreting the information, which in turn
improves interview chances.
Here
is a list of standard sections(pay special attention to the
terminology) that the resume parser expects to see in the resume:
a.
Contact Info
• Person
Name
o
Given Name
o
Preferred Name
o
Middle Initial
o
Family Name
o
Suffixes, and suffix types (educational, generational, qualification)
o
Formatted Name
• Postal
Addresses
o
Use/Location (i.e. home, work, school)
o
Street Address lines
o
Municipality
o
Region(s)
o
Country
o
Postal Code
• Phone
Numbers
o
Use/Location (i.e. home, work, personal)
o
Phone Type: Telephone, Mobile, Fax, Pager, TTYTDD
o
Phone Number: Original Format, Normalized Format, or Structured When
Available
• Email
Addresses
• Use/Location
(i.e. home, work, personal)
• Personal
URLs
b.
Job Objective
c.
Executive Summary
d.
Qualification Summary
e.
Employment History
• Start
Date
• End
Date
• Employer
Name
• Position
Title
• Organization
Name (i.e. division, department, client)
• Location:
Municipality, Region, Country
• Job
Category
• Job
Level
• Full
Text / Job Description
• Support
for nested positions
f.
Education History
• Start
Date
• End
Date
• Graduation
Date
• School
Name
• Location:
Municipality, Region, Country
• Degree
Type (normalized)
• Degree
Name
• Major
• Minor
• GPA
(actual/scale)
• Full
Text / Description
g.
Competencies
• Skill
Name
• Date
Last Used (calculated by parser)
h.
Licenses and Certifications
• Name
• Date
i.
Achievements
• Description
j.
Foreign Languages
• Read
• Write
• Speak
• Fluent?
k.
Military History (WHERE APPICABLE)
• Unit
or Division
• Rank
• Start
Date
• End
Date
• Recognition
• Disciplinary
Action
• Discharge
Disposition
l.
Security Clearances
• Specific
clearances, or “has/does not have a clearance”
m.
Associations
• Organizatio
• Role
n.
Speaking Engagements
• Date
• Title
o.
Publications
• Authors
• Title
• Journal
• Volume
• Publisher
• Publication
Date
• Publication
Type
• ISBN
p.
Patents
• Patent
Name
• Inventors
• Patent
Status
• Patent
Date
q.
References
• Full
Contact info
• Full
Text of each
• Ancestors
(name of mother, father)
• Availability
• Birthplace
• Date
of Birth
• Driving
License
• Family
Composition (spouse, children)
• Gender
• Location
(Current, Preferred)
• Marital
Status
• Mother
Tongue
• Nationality
• National
Identity Numbers (multiples allowed, each with number, type, phrase)
• Passport
Number
• Visa
Status
• Willing
to Relocate
• Salaries
(Current, Expected) (number and currency)
• Total
years of all experience in career
• Total
years of management experience in career
• Is
current job management-level?
• Current
management level
• CXO
level/type
• Human-readable
synopsis of management history
The
list above is quite exhaustive, yet there are a few other parser
specific sections that are evolving to narrow the filter further. Not
all sections are mandatory. However, if one were to include certain
sections, it would be strongly advised to stick to the above
nomenclature and include all the necessary details that the resume
parser.
In
this manner, the resume parser first identifies the above sections
from the uploaded job seeker's resume. Hence, the higher the
compliance, the better the candidate information gathered for
evaluation purposes.This phase is followed by another very important
profile evaluation phase.
2.
Parsed resume evaluation:
Once
the resume has been parsed, the ATS gathers the required candidate
information in a standardized format. It is now time for the matching
engine to evaluate the candidate for the particular job. Matching
engines are extremely intelligent nowadays.
It
all starts with identifying the right keywords, which vary from job
to job. For example, if the job is for an iOS developer, the matching
engine would expect keywords like iOS, objective-C,
cocoa,object-oriented programming and so on. Knowing these keywords
is winning half the battle. However, matching engines are smart
enough to do more than just look for keywords in the resume. The
other factors are as follows:
a.
Context:
It
makes sure that the keywords appear in the right context. For
instance, it will look for the skill Objective-C in the relevant
sections of the resume such as competencies, work history, and so on,
and not in sections like contact info.
b.
Meaning:
It
ensures that the meaning of the keyword has been rightly found. For
instance, if the job is looking for a Product Manager, the engine
does not identify text like "...collaborated with the Product
Manager..." as a match. It looks for candidates with actual
Product Managerial experience.
c.
Value:
The
engines also check for the current position that a candidate is in.
For example, a person who was a Product Manager in the past, and is
CEO right now, might not be looking for a job as a Senior Product
Manager. The value of the match is judged as well.
d.
Experience:
The
current experience of the candidate is given priority. For instance,
if one is looking for a manager with 5 years of experience, the
engine will match only those candidates who have been managers in the
last 5 years.
e.
Skills:
Like
experience, the skill experience can also be given priority. If one
is looking for a programmer with 3 years of C++ experience, the
engine will match only those profiles who have at least 3 years of
C++ experience in the recent past.
f.
Data Range:
The
engine also has the ability to deal with ranges of values. A simple
example would be one of wanting profiles with a GPA above a certain
score.
This
is the level of sophistication that the ATS has reached. Hence, job
seekers need to be savvier than ever to maximize their chances of
landing an interview.
by
Bharadwaj
Krishnan
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