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Transcript of Sara Moss Partner, The Code Works Inc. Lana Moore Director of Product Mgmt & User Exp, itzbig...
Sara Moss Partner, The Code Works Inc.
Lana Moore Director of Product Mgmt & User Exp, itzbig
Keeping Up: Are You Using Yesterday's
Candidate Matching Technology?
26-Sep-07 Candidate Search & Match Page 2
Agenda
Business Value Technology Overview & Examples
Case Study: • Bi-directional matching
26-Sep-07 Candidate Search & Match Page 4
The Good News: There are more cool tools facilitating candidate search than ever before – and your recruiters are using many of them
The Bad News: Your competitors (i.e. those competing for the same talent) have access to the same tools and technologies
The Opportunity: One way to differentiate in the marketplace is to leverage search & match technology better than the competition to find qualified candidates faster
IntroductionLeverage search & match tools and technology to find qualified candidates faster
26-Sep-07 Candidate Search & Match Page 5
More cool tools than ever, but…There are more cool tools for candidate search than ever before ATS/FO Search Email Search Desktop Search Job board searches General web search Referral tools People directories & search engines Social networks & searches Blog search
150+ A few A few 40k A few A few Tens Tens+ Tens
Your recruiters are using many of these candidate search tools and so are your competitors
26-Sep-07 Candidate Search & Match Page 6
You’ve got to leverage technology better Use your internal candidate database to find candidates faster than your competitors & be smarter about leveraging 3rd party tools
1. Internal Candidate Database Candidate data that you have created is proprietary & differentiating If you are using keyword search alone, you are probably not
identifying all of the qualified candidates in your in-house database All ATS/FO have embedded search technology (e.g. out-of-the-box
SQL-based keyword search (Microsoft & Oracle), Verity, Engenium,…)
Use contextual search and/or match by leveraging, replacing or extending embedded technology
Train recruiters
2. External Candidate Databases
26-Sep-07 Candidate Search & Match Page 7
Leverage technology better, cont’d
2. External Candidate Databases
a. Automate the candidate sourcing & filling processes
b. Manage the impact of decentralized data
c. Ensure recruiters are using a variety of search & match technologies
26-Sep-07 Candidate Search & Match Page 8
Automate the search process Streamline the candidate search process to make it faster for recruiters to utilize multiple candidate sources
Acknowledge you will use as many 3rd parties as you can
Federate searches Consolidate results Bake-in business rules to results sort order Build a workflow so recruiters know what’s next Train users to be smart users since each search
experience & underlying technology is unique
26-Sep-07 Candidate Search & Match Page 9
Manage the impacts of decentralized data Utilize external tools to source additional qualified candidates but manage the impacts of decentralized candidate data
Utilize 3rd party tools (e.g. traditional & next gen job boards, referral sites, business networks)
Augment your internal database with additional passive candidates & active job seekers
Be aware that 3rd parties offer “CRM” functionality (e.g. folders, notes, email merge, tags & may track activities)
Don’t let proprietary data reside outside of your control Create a strategy for how and where you want recruiters to
manage talent pipelines, passive candidates & active job seekers
Communicate the criteria for moving candidates to your internal database & use technology to facilitate the process
26-Sep-07 Candidate Search & Match Page 10
Use a variety of search & match technology Each search & match engine will return different results and different rankings. Maximize access to your candidate data by using more than one type of search & match technology
Different underlying technology will return different candidates; scores & ranking will also differ
To get the most out of your internal candidate database and 3rd party databases – use a variety of search approaches to identify qualified candidates
26-Sep-07 Candidate Search & Match Page 12
Yesterday’s technology = keyword search The candidate search market is finally offering more than just keyword and fielded search. Conceptual search, tagging and matching are gaining momentum.
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26-Sep-07 Candidate Search & Match Page 13
Understand the underlying technology Smarter searching requires that you understand the latest search & match approaches Example: T-Mobile
Fielded Search & Keyword/Boolean Search Conceptual Search
Example: Dice.com Faceted Navigation
Example: itzbig Bi-directional matching
26-Sep-07 Candidate Search & Match Page 14
Conceptual search overview Key Functionality: Fielded, keyword and conceptual
results are offered by conceptual vendors
Dynamic, faceted navigation Recommended keywords Highlighted keywords Relevance score
Requires: Sample set of resumes
(unstructured)
HR/Staffing Focus:
HR/Staffing Experience:
Check search out at:
26-Sep-07 Candidate Search & Match Page 21
Match overview Key Functionality: One-way or bi-directional match Customizable or user-weighted match
score Thresholds Match detail & gap analysis
Requires: Structured data – through parsing &
manual data entry Taxonomy – definition and maintenance Matching algorithm
Vendors:
Check match out at:
26-Sep-07 Candidate Search & Match Page 23
CASE STUDY
• Matching
• Scoring
• Thresholds
• Filters
• Targeted Alerts
• Screening
• Comparative
• Gap Analysis
• No Resume Required
• Compliant
• Good User Experience
• Organization of Data
• Intelligent Engine
Benefits By-Products Requirements
26-Sep-07 Candidate Search & Match Page 25
CASE STUDY
Bi-Directional Matching
What you want vs. What they want
Bi-Directional Matching
What you want vs. What they want
STRUCTURED DATA : BENEFITS
26-Sep-07 Candidate Search & Match Page 26
CASE STUDY
MatchWhat you have today…
orWhat you want tomorrow…
MatchWhat you have today…
orWhat you want tomorrow…
STRUCTURED DATA : BENEFITS : MATCH
26-Sep-07 Candidate Search & Match Page 27
CASE STUDY
ScoreHow you score against
their requirements.
ScoreHow you score against
their requirements.
STRUCTURED DATA : BENEFITS : SCORE
26-Sep-07 Candidate Search & Match Page 28
CASE STUDY
How many matches do I have?How many matches do I want to see?
Filter those that aren’t a good match.
Let me decide how I want to weight criteria based on how important it is to me.
STRUCTURED DATA : BENEFITS : THRESHOLDS & FILTERS
26-Sep-07 Candidate Search & Match Page 29
CASE STUDY
Visibility PreferencesLet me decide who sees my profile.
Visibility PreferencesLet me decide who sees my profile.
AnonymityDon’t force me to
provide contact information.
AnonymityDon’t force me to
provide contact information.
STRUCTURED DATA : BENEFITS : NO RESUME REQUIRED & COMPLIANCE
26-Sep-07 Candidate Search & Match Page 30
CASE STUDYSTRUCTURED DATA : BENEFITS
CANDIDATEACQUISITION
MARKETING MIX
QUALIFIED
Targeted Email CampaignPostings on Job Boards SEM
SEOAggregators
Social Networks
INTERESTED
TOP CANDIDATES
26-Sep-07 Candidate Search & Match Page 31
CASE STUDYWhat does my pipeline look like?
How many professionals:•Are in the network for this job?•Meet my thresholds?•Submitted a profile?•Submitted a resume?
What does my pipeline look like?
How many professionals:•Are in the network for this job?•Meet my thresholds?•Submitted a profile?•Submitted a resume?
STRUCTURED DATA : BENEFITS
26-Sep-07 Candidate Search & Match Page 33
CASE STUDY
Gap Analysis & Comparative Value
STRUCTURED DATA : BY-PRODUCTS : GAP ANALYSIS & COMPARATIVE VALUE
26-Sep-07 Candidate Search & Match Page 34
CASE STUDY
Optimal User ExperienceProgressive Profiling
Theory of Social ExchangeArtificial Intelligence
Optimal User ExperienceProgressive Profiling
Theory of Social ExchangeArtificial Intelligence
STRUCTURED DATA : REQUIREMENTS : GOOD USER EXPERIENCE & AI ENGINE
26-Sep-07 Candidate Search & Match Page 35
CASE STUDY
User Experience and Data Entry
• Attrition
•Time to complete profile / job
• Automation accuracy
Challenges
Organization of Data
• Intuitive and discoverable selection
• User-contributed data
• Mapping “like” terms
STRUCTURED DATA : CHALLENGES
26-Sep-07 Candidate Search & Match Page 36
CASE STUDY
Is more accurate than keyword searching.
Provides user control to set thresholds, filters and alerts.
Structured Data, implemented with the user experience in mind,
Compares what matters attracting QWPS & is compliant.
Is a more efficient, smarter way to source.
STRUCTURED DATA : SUMMARY
26-Sep-07 Candidate Search & Match Page 37
CASE STUDY
Find better candidates faster.
STRUCTURED DATA : NET RESULT
26-Sep-07 Candidate Search & Match Page 38
Use conceptual search and/or match to access all of the qualified candidates in your internal candidate database
Utilize the tool embedded in your ATS/FO Replace the embedded tool, custom build a candidate search application or
license/leverage 3rd party technology Train users
Plan on using a lot of 3rd party candidate search tools to access additional candidate pools, but also plan on
Managing the flow of candidates & their data into your internal database Streamlining the search process (e.g. federate, consolidate, sort and facilitate workflow) Making sure recruiters are using a variety of search & match tools to access passive
candidates and active job seekers
Being strategic about candidate search & match will reduce your sourcing costs and help you to find qualified (perhaps even better) candidates faster than the competition
In SummaryLeverage search & match tools & technology to find qualified candidates faster
26-Sep-07 Candidate Search & Match Page 39
Contact Information
Sara Moss
Lana Moore