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The 5 Levels of Talent Mining from SourceCon 2010 DC

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My SourceCon 2010 DC Keynote at the International Spy Museum on the 5 Levels of Talent Mining. I explore the value of human capital data, how talent mining has significant advantages over the predictive control of candidate variables when compared to other methods of sourcing candidates, and what I believe to be the future of sourcing, which is Talent Intelligence and Analytics.

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The 5 Levels of Talent Mining from SourceCon 2010 DC

  1. 1. The 5 Levels of Talent Mining<br />Glen CatheyV.P. National RecruitmentKforce<br />
  2. 2. Paradigm Shift<br />Forget Boolean<br />
  3. 3. Paradigm Shift<br />Anyone can perform Boolean search for any information need<br />Boolean search does not adequately describe what sourcers and recruiters do, nor does it do them justice<br />
  4. 4. Paradigm Shift<br />Think Information Retrieval<br />
  5. 5. Information Retrieval<br />The science of searching for documents, information within documents, and searching relational databases and the Internet<br />
  6. 6. Information Retrieval<br />An information retrieval process begins when a user enters a query into a system<br />
  7. 7. Information Retrieval<br />Queries are formal statements of information needs<br />
  8. 8. Sourcing<br />As a sourcer or recruiter, what’s your <br />information need?<br />
  9. 9. Information Need<br />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<br />
  10. 10. Talent Mining<br />Specialized form of text and data mining for recruiting<br />Querying and analyzing human capital data for talent discovery, identification and ultimately acquisition <br />
  11. 11. Talent Mining<br />Transforming human capital data into an informational & competitive advantage<br />Data -> Information -> Knowledge -> Decisions<br />
  12. 12. Quote<br />“Success in life comes from the identification, control and elimination of variables.”<br />
  13. 13. Quote<br />In sourcing, what candidate variables can you identify, control, and even eliminate?<br />
  14. 14. Candidate Variables<br /> Experience, education & capabilities<br /> Location<br /> Desired opportunity<br /> Compensation<br /> Availability<br />
  15. 15. Faceoff<br />Cold Calling<br /> &<br /> Referrals<br /> Talent<br /> Mining<br />
  16. 16. Candidate Variables<br />What is the % of control you have <br />(0-100%) over candidate variables when you perform:<br />Cold calling?<br />Referral recruiting?<br />Talent mining?<br />
  17. 17. Experience and Education?<br />
  18. 18. Control of Exp. and Education<br />Cold calling?<br />You have very little, if any, control over the specific experience and education of the person you get on the phone<br />Referral recruiting?<br />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<br />Talent mining?<br />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<br />
  19. 19. Location?<br />
  20. 20. Control of Location<br />Cold calling?<br />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 <br />Referral recruiting?<br />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<br />Talent mining?<br />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 <br />
  21. 21. Desired Opportunity?<br />
  22. 22. Control of Desired Opportunity<br />Cold calling?<br />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<br />Referral recruiting?<br />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<br />Talent mining?<br />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)<br />
  23. 23. Compensation?<br />
  24. 24. Control of Compensation<br />Cold calling?<br />You have very little, if any, control over the current or desired compensation of the person you get on the phone<br />Referral recruiting?<br />You have very little, if any, control over the current or desired compensation of the person referred to you <br />Talent mining?<br />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<br />
  25. 25. Availability?<br />
  26. 26. Control of Availability<br />Cold calling?<br />You have no control over the job search status of the person you get on the phone<br />Referral recruiting?<br />You have no control over the job search status of the person who is referred to you<br />Talent mining?<br />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 <br />
  27. 27. Control of Availability<br />A random sample from any sourcing method other than job posting will yield mostly passive and non-job seekers (2 out of 3)<br />
  28. 28. Availability<br />Job Seeker Status<br />Source: U.S. Bureau of Labor and Statistics<br />
  29. 29. Control of Candidate Variables<br />Talent Mining affords a higher degree of predictive control over critical candidate variables over any other method of talent discovery<br />
  30. 30. Control of Candidate Variables<br />Degree of Control<br />
  31. 31. Speed of Identification<br />
  32. 32. Speed of Identification<br />How many well-matched and qualified candidates per hour can you discover and identify through:<br />Cold calling?<br />Referral recruiting?<br />Talent mining?<br />
  33. 33. Speed of Identification<br />
  34. 34. More Control<br />Deep, Structured Data<br />Resumes, LinkedIn Profiles (some),<br />Candidate Records…<br />
  35. 35. More Control<br />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<br />
  36. 36. Less Control<br />Shallow, Unstructured Data<br />Press Releases, Articles, Directories, LinkedIn Profiles (many) Facebook, Twitter…<br />
  37. 37. Less Control<br />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<br />
  38. 38. The 5 Levels of Talent Mining<br />Keyword/Title Search<br />Conceptual Search<br />Implicit Search<br />Natural Language Search<br />Indirect Search<br />
  39. 39. Level 1 Talent Mining<br />Keyword/Title Search<br />Unfiltered keyword and title searching<br />Lexical search/match from job title, description, and required skills<br />
  40. 40. Level 1 Talent Mining<br />Benefits<br />It works<br />Easy - doesn’t require any skill or experience<br />Deep understanding of positions not necessary<br />Easily outsourced and automated<br />Low cost<br />
  41. 41. Level 1 Talent Mining<br />Challenges<br />It works – gives false sense of ease and success<br />Superficial match<br />Creates Hidden Talent Pools, excluding qualified candidates who express experience differently<br />No competitive advantage<br />
  42. 42. Level 2 Talent Mining<br />Conceptual Search<br /><ul><li>Synonymous and related terms, concepts, and titles
  43. 43. Examples:
  44. 44. Ruby, Rails, RoR, “Ruby on Rails”
  45. 45. Safety Physician, Associate Director of PVRM, Pharmacovigilance Physician, Senior Drug Safety Associate, Global Safety Senior Medical Scientist, Global Pharmacovigilance (Contract) Physician, and Medical Director</li></li></ul><li>Level 2 Talent Mining<br />Benefits<br /><ul><li>Finds new/additional candidates
  46. 46. Finds candidates that Level 1 Talent Mining can’t
  47. 47. Can be automated</li></li></ul><li>Level 2 Talent Mining<br />Challenges<br /><ul><li>Automated solutions not perfect
  48. 48. Static taxonomies and query clouds - related but not relevant, “once and done” approach
  49. 49. Requires deeper understanding of roles, skills, and technologies
  50. 50. Only human sourcers can judge relevance, adaptively learn, and run successive searches
  51. 51. Must have an awareness of excluded/missed candidates</li></li></ul><li>Level 3 Talent Mining<br />Implicit Search<br /><ul><li>Searching for and identifying candidates based on what isn’t explicitly mentioned
  52. 52. Not everyone will express their experience in their resume or profile. However, you can search for predictive clues to potential experience</li></li></ul><li>Level 3 Talent Mining<br />Implicit Search<br /><ul><li>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</li></li></ul><li>Level 3 Talent Mining<br />Benefits<br /><ul><li>Finds new/additional candidates
  53. 53. Finds candidates that Level 1 and Level 2 approaches cannot and do not find
  54. 54. Taps into Hidden Talent Pools/”Dark Matter” of databases and sites</li></li></ul><li>Level 3 Talent Mining<br />Challenges<br /><ul><li>Can’t be automated
  55. 55. Requires deep understanding of intrinsic limitations of resumes and profiles
  56. 56. Skill that can only be developed over time from observation and experience </li></li></ul><li>Level 4 Talent Mining<br />Natural Language Search<br /><ul><li>User-defined semantic search at the sentence level</li></ul>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.<br /><ul><li>Searching for responsibilities and capabilities, not just keywords and titles</li></li></ul><li>Level 4 Talent Mining<br />Responsibilities = Verbs & Nouns<br /><ul><li>Responsible for installing and configuring over 100 Exchange servers
  57. 57. Audited several not-for-profit organizations for tax compliance
  58. 58. Coded DRGs to inpatient medical records
  59. 59. System design and performance modeling using DoDAFnotation</li></li></ul><li>Level 4 Talent Mining<br />Benefits<br /><ul><li>Produces highly relevant results by tapping into powerful sentence-level semantics
  60. 60. Searching for responsibilities and capabilities, not just keywords and titles
  61. 61. Targets what people DO, not just what they SAY</li></li></ul><li>Level 4 Talent Mining<br />Challenges<br /><ul><li>No automated solution exists at this time
  62. 62. Requires search engine that supports proximity
  63. 63. Monster, Bing, Exalead, Some ATS’s
  64. 64. Example: manag* near SAP near (implement* or deploy*)
  65. 65. Requires more experienced and insightful sourcers/recruiters to perform</li></li></ul><li>Level 5 Talent Mining<br />Indirect Search<br /><ul><li>Searching for the “wrong” people to find the “right” people
  66. 66. Targeting under/overqualified professionals
  67. 67. Targeting people who likely work with or know the professionals you need to find</li></ul>First and only level to deviate from searching directly for what is needed<br />
  68. 68. Level 5 Talent Mining<br />Indirect Search<br /><ul><li>Targeting under/overqualified professionals
  69. 69. 3 year old resume or profile of a person who had 2 years of experience now represents someone with 5 years of experience
  70. 70. Under/overqualified people with the right skills and experience may know others who are at the target level of experience
  71. 71. Targeting people who likely work with or know the professionals you need to find
  72. 72. Searching for software engineers to lead you to software testers</li></li></ul><li>Level 5 Talent Mining<br />Benefits<br /><ul><li>Leads to discovery of people who could not otherwise be found via Levels 1 – 4 Talent Mining
  73. 73. Accelerates targeted referral recruiting, </li></ul> (a.k.a. crowdsourcing)<br />
  74. 74. Level 5 Talent Mining<br />Challenges<br /><ul><li>Can be laborious
  75. 75. Not guaranteed to produce results</li></li></ul><li>The Future of Sourcing<br />Talent Intelligence &Analytics<br />
  76. 76. Business Intelligence<br />To understand the new concepts of Talent Intelligence and Talent Analytics, it is important to understand the established concepts of Business Intelligence and Analytics<br />
  77. 77. Business Intelligence & Analytics<br />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<br />Examples: reporting, business performance management, text mining, and predictive analytics<br />
  78. 78. Data Warehouse<br />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 <br />
  79. 79. Talent Intelligence & Analytics<br />Computer-based techniques used in discovering, identifying, analyzing and gaining insight into internal & structured human capital datato make better hiring decisions, faster<br />
  80. 80. Talent Warehouse<br />A specialized and centralized repository of human capital data specifically designed to enable talent mining/intelligence<br />Populated with current employee data and information fed from social networks, resume databases, the Internet, etc.<br />
  81. 81. Competitive Intelligence<br />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)<br />
  82. 82. Talent Warehouse<br />A Talent Warehouse contains the deepest, most structured human capital data of any data source, and is more searchable<br />
  83. 83. Talent Warehouse<br />The deeper, more structured, and more searchable the data, the more control you have over exerting predictive control over critical candidate variables<br />
  84. 84. Depth, Structure, Searchability<br />
  85. 85. Current State<br />There are “Talent Intelligence” and “Human Capital Analytics” solutions currently available today<br />However, these focus exclusively on workforce management, workforce planning, retention modeling and talent scorecarding<br />
  86. 86. Current State<br />There are no Talent Intelligence and Analytics solutions available today designed specifically for Talent Discovery, Identification, and Acquisition…but there should be! <br />
  87. 87. Future State<br />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<br />
  88. 88. The Power of Data<br />“What if you could increase revenue by 66% using your data to make confident, fact-based decisions?”<br />Source: SAS ad<br />
  89. 89. The Power of Data<br />“What if you could increase revenue by 66% using human capital data to make confident, fact-based recruiting decisions?”<br />
  90. 90. The Power of Data<br />“What if you could see up to a 400% ROI by using business analytics to achieve your goals?”<br />Source: SAS ad<br />
  91. 91. The Power of Data<br />“What if you could see up to a 400% ROI by using talent analytics to achieve your recruiting goals?”<br />
  92. 92. Thank You & Connect!<br />

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