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Diversity sourcing hour all presenters

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Diversity sourcing hour all presenters

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Diversity sourcing hour all presenters

  1. 1. DIVERSITY SOURCING HOUR INTRODUCTION BY GLENN GUTMACHER & FEATURING PRESENTATIONS BY SOME OF OUR INDUSTRY’S TOP SOURCERS: • SUSANNA FRAZIER • MARK TORTORICI • DEAN DA COSTA TALENT42 CONFERENCE, SEATTLE JUNE 6, 2018
  2. 2. DIVERSITY SOURCING TEAM STRUCTURE Some things you need: 1. Well-communicated goals by business unit, job level, etc. – not just an overall % or # 2. Clear metrics for your team, for the recruiters, for the hiring teams – all in sync 3. Rewards and disincentives (e.g., execs can’t get 100% of bonus if fall short) 4. Diverse interview slates and panels 5. Reasonable expectations – consider 80% candidates 6. Time to source (even paired sourcing) 7. Proper training (esp. for new hiring managers) 8. Commitment to supporting employment brand 9. Trained & equipped talent ambassadors
  3. 3. DIVERSITY SOURCING STRATEGY CHECKLIST Your sourcing strategy for each profile family should include a wide range of channels to insure your candidate pipelines are diverse: 1. Revisit past diverse applicants (e.g., search ATS for silver medalists) 2. Diversity and general job boards (when posting, use tools like Textio.com to make them D&I- friendly) 3. Diversity and general resume boards, profile aggregators, etc., that support diverse filters (e.g., military veterans on Indeed; diversity search on Entelo.com, HiringSolved.com, SeekOut.io, etc.) 4. Employee referrals focused on diversity 5. Colleges: for students & alumni with diverse populations relevant to your needs 6. Diversity-focused associations, virtual groups, etc., for your target industry and/or locations 7. Diversity-focused conferences/events (have a pre- through post-event strategy, encourage your diverse SMEs to present, have hiring managers on-site ready to interview/offer, etc.) Since it’s hard enough to source for many in-demand roles without having to consider diversity, focus on job families where you can define core skillsets in a broader base candidate profile that can match to multiple, recurring roles to increase the chance of future fit for the people you do find.
  4. 4. DIVERSITY SOURCING STRATEGY CHECKLIST (CONT.) 8. Honeypots (online forms with a targeted incentive, your own hosted events, have employees post updates to their networks with links, etc.) 9. Natural language queries on search engines focused on women, ethnicity, etc. 10. Search engines that support girls’ first name bulk search (e.g., LinkedIn) 11. Search engines that support human faces search (e.g., Google images) 12. Social networks that have critical mass and let you filter appropriately (e.g., Facebook search for women, members of diversity-focused groups) 13. If unable to convert after finding, use periodic calls and scalable recruitment e-marketing to keep in touch Procurement sourcing strategy: Besides talent sourcing, remember your suppliers. Organizations like these can help you identify minority-owned businesses to become part of your supply and value chain: • National Minority Supplier Development Council Women’s Business Enterprise National Council National Gay & Lesbian Chamber of Commerce (NGLCC) • WEConnect International for majority women-owned businesses outside US • Canadian Aboriginal Minority Supplier Council (CAMSC) • Minority Supplier Development – United Kingdom (MSD-UK) See Accenture’s strategy as an example.
  5. 5. BEFORE YOU NARROW, BROADEN •Federally-mandated diversity categories (women, POC, veterans, disabled, etc.) tend to narrow your pool •So make sure you have the largest relevant talent pool before you start digging for diverse prospects
  6. 6. HAVE AN ORDERED, ORGANIZED PROCESS • Group related job description and candidate keywords (e.g., see Color coding method) • Enter them into a Boolean template (e.g., see first tab of my Google sheet – many more comprehensive diversity sourcing resources on subsequent worksheet tabs in that file!) • TIP: Alphabetically sort keywords in each string to keep organized/avoid term duplication as you expand/enhance later
  7. 7. KEYWORDS • JOB TITLES: Be creative, many companies use alternate titles • SKILLS: Carefully select keyword being sure to use synonyms • LOCATION: Narrow results using cities, states, regions • COMPANIES: Target companies you want people from • AWARDS: Best X, Top Y • EDUCATION – degrees (MBA, PhD, etc.) & certs (PMP, etc.) • INDUSTRY EVENTS - conferences, meetups, etc. • HASHTAGS - #sourcecon #girlswhocode (esp. in Twitter advanced search) Try searching for KEYWORD (credential OR certification OR certified OR degree) to find things like this
  8. 8. EXPAND YOUR TERMS EVEN MORE Find more synonyms by comparing with additional candidates, competitor job descriptions, and searching for terms on synonym sites: • Indeed job search is the most comprehensive • If it’s a job title or other type of keyword, try search tools: Recruit’Em, SourceHub, etc. • Cluster search engines like Biznar, Yippy, etc. • Nothing wrong with Wikipedia entries – they can be quite informative (e.g., RNA-Seq) • If it’s an acronym, use AcronymFinder for the spelled-out version
  9. 9. 9 SINCE YOU WANT PEOPLE… OTHER KEY TERMS IN TITLE OR URL Profiles now outnumber resumes online, so also try words like: • bio, profile, about, us, our • team, staff, people, alumni • roster, list, directory, members, attendees, board • speakers, panel, agenda, officers, minutes • Examples: "high performance computing" "scientist" (intitle:alumni OR intitle:people OR intitle:staff OR intitle:about OR intitle:bio OR intitle:profile OR intitle:team OR intitle:our OR inurl:about OR inurl:bio OR inurl:profile OR inurl:our OR inurl:team OR inurl:alumni OR inurl:people OR inurl:staff) -intitle:jobs -inurl:jobs • himss 2015..2018 ("Dr." OR Director) (intitle:"delegates" OR intitle:"attendees" OR intitle:"speakers" OR intitle:"members") • (inurl:directory OR inurl:staff OR inurl:team) (attorney OR counsel) (cell OR ext OR phone OR mobile) -site:gov -site:edu
  10. 10. site:bizjournals.com (she OR her) software site:nsbe.org "about the author" (she OR her) SITE SEARCH (A/K/A X-RAY) When you have identified a particular website that is robust (think competitors, associations, industry publications, etc.), you can easily find people within it. X-Ray search narrows results to a specific website Use root domain (exclude http://www.) after site: command Review “all results” so you can decide if extra keywords need to be used to narrow your search While its not typically needed, if you find your search returns too much static, switch to images.
  11. 11. COUNTER-INTUITIVE METHODS Don’t inadvertently discriminate against people whose attention to detail (missing keywords or command of English is slightly lacking). Find candidates that most other recruiters miss! • Purposeful typos: use Keyword Typo Generator • Purposeful NOT search: selectively eliminate *one* term you’d expect on every matching resume/profile • Use Pierre’s Boolean Iterative Generator google sheet • Different results but still relevant! • Also works with variants of company names (e.g., PriceWaterhouse NOT PwC)
  12. 12. 12 DIVERSITY SEARCH FOR WOMEN: NAMES & PRONOUNS 1. Use (female OR woman OR women OR she OR her) as part of your searches. 2. Particularly on LinkedIn search (free or paid), enter any keywords, but click the All Filters button in the upper bar to allow you to filter by location, job titles and -- particularly for diversity -- first name field filter with common girls’ first names. You can add more names up to the max. allowed (about 2,000 chars/field). (Christa OR Christal OR Christen OR Christi OR Christie OR Christin OR Christina OR Christine OR Christy OR Chrystal OR Ciara OR Ciji OR Cindy OR Claire OR Clara OR Clare OR Clarissa OR Claudia OR Colette OR Colleen OR Connie OR Constance OR Cora OR Cori OR Corina OR Corinne OR Corrie OR Corrine OR Cortney OR Cory OR Courtney OR Cristal OR Cristin OR Cristina OR Cristy OR Crystal OR Cynthia OR Daisy OR Damaris OR Danelle OR Danica OR Daniela OR Daniella OR Danielle OR Dannielle OR Danyelle OR Daphne OR Dara OR Darci OR Darcie OR Darcy OR Darla OR Darlene OR Davina OR Dawn OR Dayna OR Deana OR Deanna OR Debbie OR Deborah OR Debra OR Deena OR Deidra OR Deidre OR Deirdre OR Delia OR Delilah OR Demetria OR Dena OR Denise OR Desirae OR Desiree OR Destiny OR Diana OR Diane OR Dianna OR Dianne OR Dina OR Dolores OR Dominique OR Donna OR Dora OR Doris OR Dorothy OR Eboni OR Ebony OR Echo OR Edith OR Edna OR Eileen OR Elaina OR Elaine OR Eleanor OR Elena OR Elisa OR Elisabeth OR Elise OR Elisha OR Elissa OR Eliza OR Elizabeth OR Ellen OR Elsa OR Elyse OR Emilee OR Emilie OR Emily OR Emma OR Erica OR Ericka OR Erika OR Erin OR Esmeralda OR Esther OR Eugenia OR Eva OR Eve OR Evelyn OR Faith OR Fallon OR Falon OR Fatima OR Felicia OR Felisha OR Frances OR Francesca OR Francine) The lists in our Google sheet correspond to popular girls names in the US, China, India, and Taiwan. Even if searching for talent in the US, consider using the overseas girls’ names, too.
  13. 13. 13 DIVERSITY SEARCH LEVERAGING SCHOOL/ORG NAMES This isn’t just for students. Alumni are proud of these affiliations and keep them as part of their online footprint. – Diverse fraternities/sororities: Black females (e.g., Alpha Kappa Alpha), Black males (e.g., Alpha Phi Alpha). Latinas (e.g., Kappa Delta Chi), Latinos (e.g., Omega Delta Phi), Asians (e.g., Lambda Phi Epsilon is a cross-national Asian fraternity; Beta Chi Theta focuses on South Asians). See NMGC for multicultural Greek organizations and NALFO for just Latino ones. – Universities: the majority of alumni of the 114 Historically Black Colleges and Universities (HBCUs) are African-American, there’s a Hispanic US college association list and over 40 women’s colleges. Search through each school website with the site: command to find relevant points of contact, or use school names in resume or profile searches. – Professional associations: acronyms are good keywords, such as NSHMBA (National Society of Hispanic MBAs), SHPE (Society of Hispanic Professional Engineers), NBMBAA (National Black MBA Association) or NSBE (National Society of Black Engineers), etc. TIPS LinkedIn supports really long strings (approx. 2000 characters per field) so you can include most of these in one OR statement.
  14. 14. DIVERSITY SEARCH – LANGUAGE & NATURAL LANGUAGE These techniques are not foolproof in part because many candidates don’t promote their diverse status. • Ethnicities: “natural phrase” keywords put in an OR clause such as (“African American” OR “Asian American” OR “Latin American”) added to a string of professional/educational associations can be effective in expanding results. • Languages: combine with natural phrases like “native Spanish”, “fluent Cantonese” or “fluent Korean”. Searching for both the words “Cantonese” and “Mandarin” is a great way to find Chinese candidates because typically only native speakers list both on a resume. This works well for other ethnicities that commonly speak multiple languages (e.g., “Hindi” and “Urdu.” Also try using the native spelling of their language as a search keyword, e.g., Español CPA Miami FL (he OR she) 14 TIP: You CAN combine English & non- English keywords with Boolean in one string – e.g., (Consultant OR Developer OR Developpeur OR Programmeur) - sourcing -sourcer - recruiter - recruitment - recrutement -talent -staffing -humain - human -hr
  15. 15. Diversity Sourcing –Brogrammers– 💁‍♀️ Female Software Engineers 🤓 Susanna Frazier @ohsusannamarie
  16. 16. Understanding Female Talent – Job Attraction & Sourcing Insights
  17. 17. Fishing for Talent in Local Watering Holes with Targeted Boolean Bait (females OR girls OR ladies OR women) + (coders OR coding OR developers OR developing OR development OR engineers OR engineering OR programmers OR programming) + (computer OR software OR technology) + (alliance OR association OR club OR community OR conference OR event OR group OR guild OR league OR organization OR society) + “Seattle” bit.ly/MeetupCSE
  18. 18. Top 5 Catches → Meetup Groups – Members → Training Programs – Participants → Conferences – Attendees → Networking Groups – Members → Networking Events – Attendees Group Members, Training Program Participants, Event Attendees
  19. 19. Casting a Wider Net • Ada Developers Academy • Association for Women in Computing (AWC) • ChickTech – Advancing the Careers of Technical Women (ACT-W) • Geek Girls Carrots • Girl Develop It • Girls in Tech • Girls Who Code • Inspiring Girls Now In Technology Evolution (IGNITE) • Kal Academy • Ladies in Seattle Tech • Leading Women in Technology (LWT) • International Association of Microsoft Channel Partners (IAMCP) Women in Technology • National Center for Women & Information Technology (NCWIT) • Seattle Girl Geek Dinner • She’s Coding • She Codes Now • Society of Women Engineers (SWE) • Women in Science & Engineering Conference • Women in Technology (WiT) • Women Who Code (WWCode) • Write/Speak/Code #GirlsWhoCode #ILookLikeAnEngineer #WiT #WITRegatta #WomenInSTEM #WomenInTech
  20. 20. Fishing in CSEs Google Custom Search Engine bit.ly/wogrammers42
  21. 21. Catching Facebook Talent Intelligence Search chrome.google.com/webstore/detail/intelligence-search/dipfggodcibdmflidbceoaanadclgomm?hl=en-US
  22. 22. Catching Twitter Talent Phantombuster phantombuster.com
  23. 23. Catching Meetup Talent Instant Data Scraper chrome.google.com/webstore/detail/instant-data-scraper/ofaokhiedipichpaobibbnahnkdoiiah
  24. 24. Catching GitHub Talent SeekOut seekout.io/talent42
  25. 25. Diversity Sourcing <Talent42 edition> Transform Talent Acquisition
  26. 26. About Mark Tortorici Mark Tortorici is the Founder & Training Expert at Transform Talent Acquisition. Since 1997, Mark has trained thousands of technical staffing professionals including hundreds at Google, where he taught sourcers and recruiters onsite throughout the company's global staffing organization. Other companies include Apple, Facebook, Disney, Pinterest, Twitter, Nvidia, eBay, Yahoo and AppNexus. Mark also helped launch the MARS (Master Accreditation in Recruiting and Sourcing) certification program with netPolarity, which creates expert staffing professionals with little or no previous industry experience. He has managed staffing teams with great success and is an expert technical sourcer & recruiter.
  27. 27. Selected Diversity Sourcing • Bio/ Profile Searches - • Google CSE - • Image Sourcing - • Bio/ Profile Searches - Create a natural language string • Google CSE - Use Mark's Diversity CSE • Image Sourcing - Natural language for Google Images
  28. 28. Diversity Sourcing Natural Language
  29. 29. Natural Language • For female engineering candidates, you can use Natural Language in your searches • Use Natural Language keywords that will capture sentences like "she works at" or "she is an engineer" • Add bio / profile keywords • Add titles and secondary keywords • Remove LinkedIn pages and jobs pages (bio OR profile) "(she OR her) (is OR was OR works OR work)" ("software engineer" OR programmer OR developer) ("data services" OR "big data" OR "data science" OR "data visualization") -site:linkedin.com -jobs
  30. 30. Natural Language
  31. 31. Natural Language
  32. 32. Diversity Sourcing Image Searching
  33. 33. Image Searching • Use Google Image search in conjunction with a Diversity search • Go to Google, click on "Images" and search a bio/profile string variation: "(she OR her) (is OR role OR work OR works)" ("project manager" OR "program manager") (engineering OR technical OR epm OR product)
  34. 34. Image Searching "(she OR her) (is OR role OR work OR works)" ("project manager" OR "program manager") (engineering OR technical OR epm OR product)
  35. 35. Image Searching
  36. 36. Image Searching
  37. 37. Image Searching Use Google Image search with diversity organizations or female pronouns Go to http://images.google.com and search: (her OR she) ("engineering manager" OR "software manager" OR "manager software" OR "manager of software" OR "engineering director" OR "director of engineering")
  38. 38. Image Searching
  39. 39. Image Searching
  40. 40. Image Searching
  41. 41. Google CSE Mark's Diversity CSE
  42. 42. Mark's Diversity CSE Mark's Diversity CSE • A Google Custom Search Engine that searches LinkedIn, Twitter, GitHub, open resumes and open profiles • bit.ly/mark_diversity_cse • Also contains diversity refinements for Women in Engineering, African- Americans, and Hispanic-Americans • Makes search easier by taking common titles, SW strings, & site searches, and turning them into single word refinements
  43. 43. Mark's Diversity CSE Mark's Diversity CSE • For example, if you use the more:aa_edu1 refinement string to your search, then you are running: ("Alabama State University" OR "Albany State University" OR "Alcorn State University" OR "Allen University" OR "American Baptist College" OR "University of Arkansas at Pine Bluff" OR "Arkansas Baptist College" OR "Barber Scotia College" OR "Benedict College" OR "Bennett College" OR "Bethune Cookman University" OR "Bishop State Community College" OR "Bluefield State College" OR "Bowie State University" OR "Central State University" OR "Cheyney University of Pennsylvania" OR "Claflin University" OR "Clark Atlanta University" OR "Clinton Junior College" OR "Coahoma Community College" OR "Concordia College, Alabama" OR "Coppin State University" OR "Delaware State University")
  44. 44. Mark's Diversity CSE Mark's Diversity CSE • Another example, if you use the more:female1 refinement string to your search, then you are running: (intitle:Abigail OR intitle:Adrienne OR intitle:Aimee OR intitle:Alexandra OR intitle:Alexis OR intitle:Alice OR intitle:Alicia OR intitle:Alisha OR intitle:Alison OR intitle:Allison OR intitle:Alyssa OR intitle:Amanda OR intitle:Amber OR intitle:Amy OR intitle:Ana OR intitle:Andrea OR intitle:Angel OR intitle:Angela OR intitle:Angelica OR intitle:Angie OR intitle:Anita OR intitle:Ann OR intitle:Anna OR intitle:Anne OR intitle:Annette OR intitle:Ashlee OR intitle:Ashley OR intitle:Audrey OR intitle:Becky OR intitle:Belinda OR intitle:Beth OR intitle:Bethany OR intitle:Betty OR intitle:Beverly OR intitle:Bonnie OR intitle:Brandi OR intitle:Brandy OR intitle:Brenda OR intitle:Brianna OR intitle:Bridget OR intitle:Brittany OR intitle:Brittney OR intitle:Brooke OR intitle:Caitlin OR intitle:Candace OR
  45. 45. Mark's Diversity CSE Mark's Diversity CSE • Another example, if you use the more:hispanic1 refinement string to your search, then you are running: (intitle:Abigail OR intitle:Abril OR intitle:Adrián OR intitle:Adriana OR intitle:Agustín OR intitle:Agustina OR intitle:Aitana OR intitle:Alejandra OR intitle:Alejandro OR intitle:Alessandra OR intitle:Alma OR intitle:Alonso OR intitle:Álvaro OR intitle:Amelia OR intitle:Ana OR intitle:Andrés OR intitle:Antonella OR intitle:Antonia OR intitle:Ariadna OR intitle:Ariana OR intitle:Axel OR intitle:Bautista OR intitle:Benjamín OR intitle:Bianca OR intitle:Camila OR intitle:Camilo OR intitle:Carla OR intitle:Carlos OR intitle:Catalina OR intitle:Constanza OR intitle:Cristóbal OR intitle:Damián OR intitle:Daniela OR intitle:Dante OR intitle:Delfina OR intitle:Diego OR intitle:Eduardo OR intitle:Elena OR intitle:Elías OR intitle:Emilia OR intitle:Emiliano OR intitle:Emilio)
  46. 46. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: more:sfbay will search that specific location (WARNING - only use for GitHub, Twitter, resume or profile searches) Refinement What it's for more:linkedin For searching LinkedIn profiles more:linkedin_sf This + more:linkedin to search SF Bay profiles more:linkedin_sea This + more:linkedin to search Seattle profiles more:resumes For searching open resumes on the internet more:profiles For searching open profiles on the internet more:twitter For searching Twitter profiles more:github For searching GitHub profiles
  47. 47. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: Refinement What it's for more:swe For software engineering titles more:deep For deep learning keywords more:ai For artificial intelligence / machine learning more:systems For systems / production engineering more:sales For sales roles more:infosec For information security / software security
  48. 48. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: NOTE: Because of false positives, these first names are only searching web pages with the intitle: operator (i.e. intitle:Alexa) Refinement What it's for more:female1 For popular female first names A - Ca more:female2 For popular female first names Ca - Fe more:female3 For popular female first names Fr - Ke more:female4 For popular female first names Ke - Me more:female5 For popular female first names Me - Sh more:female6 For popular female first names Sh - Z
  49. 49. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: Refinement What it's for more:sorority1 For sorority names (Alpha Chi - Alpha Sigma) more:sorority2 For sorority names (Alpha Sigma - Delta Tao) more:sorority3 For sorority names (Delta Xi - Kappa Phi) more:sorority4 For sorority names (Lambda Pi - Sigma Alpha) more:sorority5 For sorority names (Sigma Delta - Sigma Sigma or the word sorority)
  50. 50. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: Refinement What it's for more:aa_fr For African American fraternities and sororities more:aa_edu1 For Historically Black Universities (A - De) more:aa_edu2 For Historically Black Universities (De - Li) more:aa_edu3 For Historically Black Universities (Ma - So) more:aa_edu4 For Historically Black Universities (So - Xa)
  51. 51. Mark's Diversity CSE Current refinements for Mark's Diversity CSE: NOTE: Because of the commonality of Spanish names and cities, these first names are only searching web pages with the intitle: operator (i.e. intitle:Fernando) Refinement What it's for more:hispanic1 For popular Hispanic first names (A - Em) more:hispanic2 For popular Hispanic first names (Em - Ma) more:hispanic3 For popular Hispanic first names (Ma - Xi)
  52. 52. Mark's Diversity CSE Example Search in Mark's Diversity CSE: • LinkedIn profile search for Hispanic SW Engineers with AI focus in the Bay Area: more:linkedin_sf more:swe more:ai more:hispanic1
  53. 53. Mark's Diversity CSE • Is really running this in the background: site:linkedin.com/in "san francisco bay area" ("software engineer" OR programmer OR developer OR "sw engineer" OR "embedded engineer" OR "firmware engineer" OR "data scientist" OR "research scientist") ("deep learning" OR "machine learning" OR algorithm OR "artificial intelligence" OR "neural networks" OR "machine vision" OR "neural net" OR "augmented reality") (intitle:Abigail OR intitle:Abril OR intitle:Adrián OR intitle:Adriana OR intitle:Agustín OR intitle:Agustina OR intitle:Aitana OR intitle:Alejandra OR intitle:Alejandro OR intitle:Alessandra OR intitle:Alma OR intitle:Alonso OR intitle:Álvaro OR intitle:Amelia OR intitle:Ana OR intitle:Andrés OR intitle:Antonella OR intitle:Antonia OR intitle:Ariadna OR intitle:Ariana OR intitle:Axel OR intitle:Bautista OR intitle:Benjamín OR intitle:Bianca OR intitle:Camila OR intitle:Camilo OR intitle:Carla OR intitle:Carlos OR intitle:Catalina OR intitle:Constanza OR intitle:Cristóbal OR intitle:Damián OR intitle:Daniela OR intitle:Dante OR intitle:Delfina OR intitle:Diego OR intitle:Eduardo OR intitle:Elena OR
  54. 54. Mark's Diversity CSE more:linkedin_sf more:swe more:ai more:hispanic1
  55. 55. Awesome, Possum!!! Getting Results
  56. 56. Awesome, Possum!!! Local possum found on Google CSE Getting Results
  57. 57. site:twitter.com inurl:(lists OR list) inurl:(female OR woman OR Women)
  58. 58. site:twitter.com inurl:(lists OR List) inurl:(spanish OR hispanic OR Latino OR Latina)
  59. 59. site:twitter.com inurl:(lists OR List) inurl:(Black OR "African American") Developer
  60. 60. any QUESTIONS? Mark Tortorici | Founder & Training Expert | Transform Talent Acquisition | mark.nexus@gmail.com

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