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?

Page 2 26-Sep-07Candidate Search & Match Agenda §Business Value §Technology Overview & Examples l Case Study: Bi-directional matching

Page 3 26-Sep-07Candidate Search & Match Business Value: Why Search Matters?

Page 4 26-Sep-07Candidate Search & Match §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 Introduction Leverage search & match tools and technology to find qualified candidates faster

Page 5 26-Sep-07Candidate Search & Match More cool tools than ever, but… There are more cool tools for candidate search than ever before §ATS/FO Search § Search §Desktop Search §Job board searches §General web search §Referral tools §People directories & search engines §Social networks & searches §Blog search §150+ §A few §40k §A few §Tens §Tens+ §Tens Your recruiters are using many of these candidate search tools and so are your competitors

Page 6 26-Sep-07Candidate Search & Match You’ve got to leverage technology better Use your internal candidate database to find candidates faster than your competitors & be smarter about leveraging 3 rd party tools 1.Internal Candidate Database l Candidate data that you have created is proprietary & differentiating l If you are using keyword search alone, you are probably not identifying all of the qualified candidates in your in-house database l All ATS/FO have embedded search technology (e.g. out-of-the-box SQL-based keyword search (Microsoft & Oracle), Verity, Engenium,…) l Use contextual search and/or match by leveraging, replacing or extending embedded technology l Train recruiters 2.External Candidate Databases

Page 7 26-Sep-07Candidate Search & Match 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

Page 8 26-Sep-07Candidate Search & Match 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 3 rd 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

Page 9 26-Sep-07Candidate Search & Match 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, 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

Page Sep-07Candidate Search & Match 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 3 rd party databases – use a variety of search approaches to identify qualified candidates

Page Sep-07Candidate Search & Match Search & Match Technology Overviews & Examples

Page Sep-07Candidate Search & Match 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. Fielded Search Keyword Search Conceptual Search Tagging Matching Recommendation 90s Are you here? s03

Page Sep-07Candidate Search & Match Understand the underlying technology Smarter searching requires that you understand the latest search & match approaches §Example: T-Mobile l Fielded Search & Keyword/Boolean Search l Conceptual Search §Example: Dice.com l Faceted Navigation §Example: itzbig l Bi-directional matching

Page Sep-07Candidate Search & Match 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:

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Page Sep-07Candidate Search & Match 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:

Page Sep-07Candidate Search & Match Bi-directional Matching Example:

Page Sep-07Candidate Search & Match 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

Page Sep-07Candidate Search & Match CASE STUDY STRUCTURED DATA

Page Sep-07Candidate Search & Match 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

Page Sep-07Candidate Search & Match CASE STUDY Match What you have today… or What you want tomorrow… Match What you have today… or What you want tomorrow… STRUCTURED DATA : BENEFITS : MATCH

Page Sep-07Candidate Search & Match CASE STUDY Score How you score against their requirements. Score How you score against their requirements. STRUCTURED DATA : BENEFITS : SCORE

Page Sep-07Candidate Search & Match 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

Page Sep-07Candidate Search & Match CASE STUDY Visibility Preferences Let me decide who sees my profile. Visibility Preferences Let me decide who sees my profile. Anonymity Don’t force me to provide contact information. Anonymity Don’t force me to provide contact information. STRUCTURED DATA : BENEFITS : NO RESUME REQUIRED & COMPLIANCE

Page Sep-07Candidate Search & Match CASE STUDY STRUCTURED DATA : BENEFITS CANDIDATE ACQUISITION MARKETING MIX QUALIFIED Targeted Campaign Postings on Job Boards SEM SEO Aggregators Social Networks INTERESTED TOP CANDIDATES

Page Sep-07Candidate Search & Match CASE STUDY 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? 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

Page Sep-07Candidate Search & Match CASE STUDY STRUCTURED DATA : BY-PRODUCTS : ALERTS

Page Sep-07Candidate Search & Match CASE STUDY Gap Analysis & Comparative Value STRUCTURED DATA : BY-PRODUCTS : GAP ANALYSIS & COMPARATIVE VALUE

Page Sep-07Candidate Search & Match CASE STUDY Optimal User Experience Progressive Profiling Theory of Social Exchange Artificial Intelligence Optimal User Experience Progressive Profiling Theory of Social Exchange Artificial Intelligence STRUCTURED DATA : REQUIREMENTS : GOOD USER EXPERIENCE & AI ENGINE

Page Sep-07Candidate Search & Match 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

Page Sep-07Candidate Search & Match 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

Page Sep-07Candidate Search & Match CASE STUDY Find better candidates faster. STRUCTURED DATA : NET RESULT

Page Sep-07Candidate Search & Match §Use conceptual search and/or match to access all of the qualified candidates in your internal candidate database l Utilize the tool embedded in your ATS/FO l Replace the embedded tool, custom build a candidate search application or license/leverage 3 rd party technology l Train users §Plan on using a lot of 3 rd party candidate search tools to access additional candidate pools, but also plan on l Managing the flow of candidates & their data into your internal database l Streamlining the search process (e.g. federate, consolidate, sort and facilitate workflow) l 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 Summary Leverage search & match tools & technology to find qualified candidates faster

Page Sep-07Candidate Search & Match Contact Information Sara Moss Lana Moore