The 5 Levels of Talent Mining from SourceCon 2010 DC

The 5 Levels of Talent Mining
Glen CatheyV.P. National RecruitmentKforce

Paradigm Shift
Forget Boolean

Paradigm Shift
Anyone can perform Boolean search for any information need
Boolean search does not adequately describe what sourcers and recruiters do, nor does it do them justice

Paradigm Shift
Think Information Retrieval

Information Retrieval
The science of searching for documents, information within documents, and searching relational databases and the Internet

An information retrieval process begins when a user enters a query into a system

Queries are formal statements of information needs

Sourcing
As a sourcer or recruiter, what’s your
information need?

Information Need
Ultimately, you are looking to find people who have specific skills, experience and education, who live in a specific area, who are interested in your opportunity, and who you can recruit and hire

Talent Mining
Specialized form of text and data mining for recruiting
Querying and analyzing human capital data for talent discovery, identification and ultimately acquisition

Talent Mining
Transforming human capital data into an informational & competitive advantage
Data -> Information -> Knowledge -> Decisions

Quote
“Success in life comes from the identification, control and elimination of variables.”

Quote
In sourcing, what candidate variables can you identify, control, and even eliminate?

Candidate Variables
Experience, education & capabilities
Location
Desired opportunity
Compensation
Availability

Faceoff
Cold Calling
&
Referrals
Talent
Mining

Candidate Variables
What is the % of control you have
(0-100%) over candidate variables when you perform:
Cold calling?
Referral recruiting?
Talent mining?

Experience and Education?

Control of Exp. and Education
Cold calling?
You have very little, if any, control over the specific experience and education of the person you get on the phone
You have very little, if any, control over the specific experience and education of the person referred to you, regardless of what you specifically ask for
Talent mining?
Searching structured databases gives you a very high degree over the specific experience and education of the people you decide to call based on a search

Location?

Control of Location
Cold calling?
While you can be certain that a person you reach inside of a company lives in a specific metro area, you have no control over where they live within a 50 mile radius
Similar to cold calling, you have no control over where the people referred to you actually live, and thus would be interested in commuting to
Talent mining?
Searching structured databases gives you a very high degree over precisely where people live, down to a 5 mile radius or even a specific zip code

Desired Opportunity?

Control of Desired Opportunity
Cold calling?
You have very little, if any, control over the type of opportunity the person you get on the phone is looking for as the next step in their career
As with cold calling, you have no predictive ability to determine what a person who is referred to you is interested in doing as the next move in their career
Talent mining?
Searching structured databases enables you to target specific skills and experience, including years of experience in given industries, which gives you a predictive ability to make an educated guess as to what the next step in a person’s career path might be, and thus what the candidate might be interested in (aka career trajectory)

Compensation?

Control of Compensation
Cold calling?
You have very little, if any, control over the current or desired compensation of the person you get on the phone
You have very little, if any, control over the current or desired compensation of the person referred to you
Talent mining?
With the ability to control the years and type of experience of the people you return in your searches, with industry and market knowledge, you are granted a good idea of their current compensation level and what they would most likely be willing to accept for a new position

Availability?

Control of Availability
Cold calling?
You have no control over the job search status of the person you get on the phone
You have no control over the job search status of the person who is referred to you
Talent mining?
Searching databases can give you the ability to target recently posted resumes and recently created social network profiles, and people who have either recently posted or updated their resume or LinkedIn profile are at a higher probability of being available

Control of Availability
A random sample from any sourcing method other than job posting will yield mostly passive and non-job seekers (2 out of 3)

Availability
Job Seeker Status
Source: U.S. Bureau of Labor and Statistics

Control of Candidate Variables
Talent Mining affords a higher degree of predictive control over critical candidate variables over any other method of talent discovery

Control of Candidate Variables
Degree of Control

Speed of Identification

How many well-matched and qualified candidates per hour can you discover and identify through:
Cold calling?
Talent mining?

More Control
Deep, Structured Data
Resumes, LinkedIn Profiles (some),
Candidate Records…

More Control
The deeper and more structured the human capital data you are mining, the more predictive control you have over critical candidate matching and qualification variables

Less Control
Shallow, Unstructured Data
Press Releases, Articles, Directories, LinkedIn Profiles (many) Facebook, Twitter…

Less Control
The more shallow and less structured the human capital data you are mining, the less predictive control you have over critical candidate matching and qualification variables

The 5 Levels of Talent Mining
Keyword/Title Search
Conceptual Search
Implicit Search
Natural Language Search
Indirect Search

Level 1 Talent Mining
Keyword/Title Search
Unfiltered keyword and title searching
Lexical search/match from job title, description, and required skills

Benefits
It works
Easy - doesn’t require any skill or experience
Deep understanding of positions not necessary
Easily outsourced and automated
Low cost

Challenges
It works – gives false sense of ease and success
Superficial match
Creates Hidden Talent Pools, excluding qualified candidates who express experience differently
No competitive advantage

Conceptual Search
Synonymous and related terms, concepts, and titles
Examples:
Ruby, Rails, RoR, “Ruby on Rails”
Safety Physician, Associate Director of PVRM, Pharmacovigilance Physician, Senior Drug Safety Associate, Global Safety Senior Medical Scientist, Global Pharmacovigilance (Contract) Physician, and Medical Director

Benefits
Finds new/additional candidates
Finds candidates that Level 1 Talent Mining can’t
Can be automated

Challenges
Automated solutions not perfect
Static taxonomies and query clouds - related but not relevant, “once and done” approach
Requires deeper understanding of roles, skills, and technologies
Only human sourcers can judge relevance, adaptively learn, and run successive searches
Must have an awareness of excluded/missed candidates

Implicit Search
Searching for and identifying candidates based on what isn’t explicitly mentioned
Not everyone will express their experience in their resume or profile. However, you can search for predictive clues to potential experience

Implicit Search
If you were in need of an Accountant with experience with SAP, after performing Level 1 & 2 Talent Mining and searching directly for explicitly expressed experience with SAP, you can exclude SAP from your queries and instead search for people who have worked at companies that you know use SAP for their accounting software, leading you to additional qualified candidates

Benefits
Finds new/additional candidates
Finds candidates that Level 1 and Level 2 approaches cannot and do not find
Taps into Hidden Talent Pools/”Dark Matter” of databases and sites

Challenges
Can’t be automated
Requires deep understanding of intrinsic limitations of resumes and profiles
Skill that can only be developed over time from observation and experience

Natural Language Search
User-defined semantic search at the sentence level
Semantics is the study of meaning of language inherent at the word, phrase, and sentence level. Sentence level semantics is the most powerful and predictive.
Searching for responsibilities and capabilities, not just keywords and titles

Responsibilities = Verbs & Nouns
Responsible for installing and configuring over 100 Exchange servers
Audited several not-for-profit organizations for tax compliance
Coded DRGs to inpatient medical records
System design and performance modeling using DoDAFnotation

Benefits
Produces highly relevant results by tapping into powerful sentence-level semantics
Searching for responsibilities and capabilities, not just keywords and titles
Targets what people DO, not just what they SAY

Challenges
No automated solution exists at this time
Requires search engine that supports proximity
Monster, Bing, Exalead, Some ATS’s
Example: manag* near SAP near (implement* or deploy*)
Requires more experienced and insightful sourcers/recruiters to perform

Indirect Search
Searching for the “wrong” people to find the “right” people
Targeting under/overqualified professionals
Targeting people who likely work with or know the professionals you need to find
First and only level to deviate from searching directly for what is needed

Indirect Search
Targeting under/overqualified professionals
3 year old resume or profile of a person who had 2 years of experience now represents someone with 5 years of experience
Under/overqualified people with the right skills and experience may know others who are at the target level of experience
Targeting people who likely work with or know the professionals you need to find
Searching for software engineers to lead you to software testers

Benefits
Leads to discovery of people who could not otherwise be found via Levels 1 – 4 Talent Mining
Accelerates targeted referral recruiting,
(a.k.a. crowdsourcing)

Challenges
Can be laborious
Not guaranteed to produce results

The Future of Sourcing
Talent Intelligence &Analytics

Business Intelligence
To understand the new concepts of Talent Intelligence and Talent Analytics, it is important to understand the established concepts of Business Intelligence and Analytics

Business Intelligence & Analytics
Business intelligence (BI) refers to computer-based techniques used in discovering, identifying and analyzing mostly internal & structured business data to gain insight and to support better business decision-making
Examples: reporting, business performance management, text mining, and predictive analytics

Data Warehouse
Business Intelligence & Analytics are enabled through the collection of data from multiple sources into a data warehouse, which is a specialized and centralized repository data, designed to facilitate reporting and analysis

Talent Intelligence & Analytics
Computer-based techniques used in discovering, identifying, analyzing and gaining insight into internal & structured human capital datato make better hiring decisions, faster

Talent Warehouse
A specialized and centralized repository of human capital data specifically designed to enable talent mining/intelligence
Populated with current employee data and information fed from social networks, resume databases, the Internet, etc.

Competitive Intelligence
In contrast to Talent Intelligence, Competitive Intelligence is gained by gathering, analyzing and disseminating information, with or without support from technology and applications, and focuses on mostly external all-source information and data (unstructured or structured)

Talent Warehouse
A Talent Warehouse contains the deepest, most structured human capital data of any data source, and is more searchable

Talent Warehouse
The deeper, more structured, and more searchable the data, the more control you have over exerting predictive control over critical candidate variables

Depth, Structure, Searchability

Current State
There are “Talent Intelligence” and “Human Capital Analytics” solutions currently available today
However, these focus exclusively on workforce management, workforce planning, retention modeling and talent scorecarding

Current State
There are no Talent Intelligence and Analytics solutions available today designed specifically for Talent Discovery, Identification, and Acquisition…but there should be!

Future State
The next frontier in Human Capital & Talent Analytics is to harness the power of human capital data and transform it into an informational and competitive advantage – by enabling companies to quickly and predictively discover, identify, and acquire top talent

The Power of Data
“What if you could increase revenue by 66% using your data to make confident, fact-based decisions?”
Source: SAS ad

The Power of Data
“What if you could increase revenue by 66% using human capital data to make confident, fact-based recruiting decisions?”

The Power of Data
“What if you could see up to a 400% ROI by using business analytics to achieve your goals?”
Source: SAS ad

The Power of Data
“What if you could see up to a 400% ROI by using talent analytics to achieve your recruiting goals?”

Thank You & Connect!

http://www.booleanblackbelt.com	2780
http://paper.li	20
http://vadaliprakash.blogspot.com	9
http://www.ecruiters.nl	1
http://webcache.googleusercontent.com	1
http://hrbloggers.com	1

The 5 Levels of Talent Mining from SourceCon 2010 DC

by Glen Cathey on Sep 30, 2010

Accessibility

Categories

Tags

Upload Details

Usage Rights

6 Embeds 2,812

Statistics

The 5 Levels of Talent Mining from SourceCon 2010 DC — Presentation Transcript