Building a Solid Foundation with the Boolean Black Belt I Talent Connect London 2013

Glen Cathey

SVP, Strategic Talent Acquisition and Innovation

Kforce

Author, booleanblackbelt.com

LinkedIn Sourcing Building a Solid Foundation

Who is this guy?

SVP, Talent Acquisition Strategy and Innovation

– Architect Kforce's sourcing and recruiting strategy for 800+ recruiters

16+ years recruiting

– Professional staffing

I.T., Engineering F&A, Healthcare I.T., Federal, Clinical Research

– Global RPO delivery

Sourcing/Recruiting Blogger

– www.booleanblackbelt.com

– 15K+ unique visitors per week from 110+ countries

Speaker

– 6X LinkedIn Talent Connect speaker (US, CA, UK)

– 6X SourceCon speaker

– 2X Australasian Talent Conference (Sydney & Melbourne)

– 2X TruLondon

LinkedIn Certified, Top 25 most connected on LinkedIn globally, #5

in recruitment

http://www.booleanblackbelt.com/

Adaptive search,

maximum inclusion &

strategic exclusion

Query logic/syntax and other search methods (e.g., faceted

search)

The nature and limitations of the text you're interrogating, the behavior of the people

generating the text and of your competitors, and core information retrieval

Beinecke Library, Yale University

“The flood of data means more noise (i.e., irrelevant/useless information) but not

necessarily more signal (i.e., relevant results)”

Often we expect too much of computers and not enough of ourselves. People

blame systems “when they should be asking better questions.”

Nate Silver • Principal, FiveThirtyEight

• Author, The Signal and the Noise: Why So

Many Predictions Fail-but Some Don't

• Correctly predicted 50 out of 50 states in

the 2012 U.S. presidential election

Title only

Source: John Zappe, SourceCon

Title only

Source: Suzanne Chadwick, The Social Recruiter blog

Photo: JohnEdgarPark

Competitive Advantage?

LinkedIn members performed nearly 5.7 billion

professionally-oriented searches on the platform in

2012.

LinkedIn's corporate talent solutions are used by 90

of the Fortune 100 companies.

(How) Are your searches any different than anyone

else's?

Understanding Search and Retrieval

Every search you run includes

and excludes qualified people

You can only get what you search for

Do the best people necessarily

mention your search terms?

Common search terms may be

"overvalued" and yield no

competitive advantage

Who are you finding?

Relevance

How many results…

do you review per search?

can you review per search?

should you review?

25,000+ software engineers in

London

Nearly 14,000 accountants

Understand your target talent pool…

Why does the average person join

LinkedIn?

What does the average person use

LinkedIn for?

Why would someone who isn't looking for

a job fill out their LinkedIn profile as they

would a resume?

The answers to these questions are

critical in developing your search

strategies

Understand your target talent pool…

Understand the competition…

Your competitors and other companies are

using LinkedIn Recruiter to look for the same

people you are

Are your searches any different than your

competitors?

Are you processing search results in the same

way as your competitors?

Are you finding and fighting over the same

talent pool?

Boolean: Before and Beyond

Before & Beyond Boolean…

Information Retrieval is 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.

As Nate Silver suggests, you should learn to ask better questions.

LinkedIn's working on understanding your searches…

However…

No system or database: – will ever "know" what you want or need

– can determine "relevance"

Relevance – is the ability (as of an information retrieval

system) to retrieve material that satisfies the needs of the user*

Source: Gary Marchionini

When it comes to Human–Computer Information Retrieval (HCIR)*, it is

necessary for people to take responsibility for search results by expending

cognitive energy

AND

Mandatory inclusion

Typically reduces results

Unnecessary to type in LinkedIn

Use for required skills

"Objective C" Cocoa xcode iOS "software engineer"

OR

NOT either/or!

Inclusive – "at least one of"

Use parentheses to group terms

(A OR B OR C) (D OR E OR F)

Typically increases results

Use #1: searching for (un)related desired skills

OR

(MapReduce ETL OR SAS OR SPSS OR Sqoop OR Pig

OR NoSQL OR Hive OR Hbase OR Flume)

Use #2: searching for term variations and synonymous, related and relevant terms

OR

(tax OR taxes OR taxation)

(VP OR "V.P." OR SVP OR "S.V.P." OR "Vice President")

("software engineer" OR developer OR programmer)

("Objective C" OR ObjectiveC OR "Objective-C")

(develop OR developer OR developed OR developing OR development OR

develops)

(Deloitte OR PwC OR PricewaterhouseCoopers OR "Price Waterhouse" OR

"Pricewaterhouse" OR "E&Y" OR Ernst OR KPMG)

NOT/-

Exclusionary

Almost always decreases results

Can also use the minus sign

Use #1 Reducing/eliminating false positives

"Objective C" Cocoa xcode iOS "software engineer"

-(recruiter OR executive search OR recruiting)

iOS

Cocoa

xcode

"Objective C"

iPhone

Search #1 iOS "Objective C" Cocoa iPhone xcode

Search #2 iOS "Objective C" Cocoa iPhone -xcode

Search #3 iOS "Objective C" Cocoa -iPhone xcode

Use #2 Mutually exclusive search progressions/results

Query Modifiers

Quotation Marks " "

Exact phrase searching

Parentheses ( )

Grouping OR statements

Search Field Size

~3,000+ characters per field

Not Supported

Asterisk *

Root word/stemming

Near

Proximity search

(XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR

XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR

































XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX OR XXXXXXX)

Abigail OR Adrienne OR Aimee OR Alexandra OR Alexis OR Alice OR Alicia OR Alisha OR Alison

OR Allison OR Alyssa OR Amanda OR Amber OR Amy OR Ana OR Andrea OR Angel OR Angela

OR Angelica OR Angie OR Anita OR Ann OR Anna OR Anne OR Annette OR Annie OR April OR

Arlene OR Ashlee OR Ashley OR Audrey OR Autumn OR Barbara OR Becky OR Belinda OR Beth

OR Bethany OR Betty OR Beverly OR Bonnie OR Brandi OR Brandy OR Brenda OR Brianna OR

Bridget OR Brittany OR Brittney OR Brooke OR Caitlin OR Candace OR Candice OR Carla OR

Carmen OR Carol OR Carole OR Caroline OR Carolyn OR Carrie OR Casey OR Cassandra OR

Cassie OR Catherine OR Cathy OR Charlene OR Charlotte OR Chelsea OR Cheryl OR Christie

OR Christina OR Christine OR Christy OR Cindy OR Claudia OR Colleen OR Connie OR

Constance OR Courtney OR Cristina OR Crystal OR Cynthia OR Dana OR Danielle OR Darlene

OR Dawn OR Deanna OR Debbie OR Deborah OR Debra OR Delores OR Denise OR Desiree OR

Diana OR Diane OR Dianne OR Dolores OR Dominique OR Donna OR Doreen OR Doris OR

Dorothy OR Ebony OR Eileen OR Elaine OR Elizabeth OR Ellen OR Emily OR Erica OR Erika OR

Erin OR Eva OR Evelyn OR Felicia OR Frances OR Gail OR Gayle OR Geraldine OR Gina OR

Glenda OR Gloria OR Grace OR Gwendolyn OR Hannah OR Heather OR Heidi OR Helen OR

Holly OR Irene OR Jackie OR Jaclyn OR Jacqueline OR Jaime OR Jamie OR Jan OR Jane OR

Janet OR Janice OR Janis OR Jasmine OR Jean OR Jeanette OR Jeanne OR Jenna OR Jennifer

OR Jenny OR Jessica OR Jill OR Jillian OR Jo OR Joan OR Joann OR Joanna OR Joanne OR

Jodi OR Jody OR Jordan OR Josephine OR Joy OR Joyce OR Juanita OR Judith OR Judy OR

Julia OR Julie OR June OR Kara OR Karen OR Kari OR Karla OR Katelyn OR Katherine OR

Kathleen OR Kathryn OR Kathy OR Katie OR Katrina OR Kay OR Kayla OR Kelli OR Kellie OR

Kelly OR Kelsey OR Kendra OR Kerri OR Kerry OR Kim OR Kimberly OR Krista OR Kristen OR

Kristi OR Kristie OR Kristin OR Kristina OR Kristine OR Kristy OR Krystal OR Lacey OR Latasha

OR Latoya OR Laura OR Lauren OR Laurie OR Leah OR Leslie OR Lillian OR Linda OR Lindsay

OR Lindsey OR Lisa OR Lois OR Loretta OR Lori OR Lorraine OR Louise OR Lynda OR Lynn OR

Lynne OR Mallory OR Mandy OR Marcia OR Margaret OR Maria OR Marianne OR Marie OR

Marilyn OR Marissa OR Marjorie OR Marlene OR Marsha OR Martha OR Mary OR Maureen OR

Meagan OR Megan OR Meghan OR Melanie OR Melinda OR Melissa OR Melody OR Meredith

OR Michele OR Michelle OR Mildred OR Mindy OR Miranda OR Misty OR Molly OR Monica OR

Monique OR Morgan OR Nancy OR Natalie OR Natasha OR Nichole OR Nicole OR Nina OR

Norma OR Olivia OR Pam OR Pamela OR Patricia OR Patsy OR Patti OR Patty OR Paula OR

Peggy OR Penny OR Phyllis OR Priscilla OR Rachael OR Rachel OR Rebecca OR Rebekah OR

Regina OR Renee OR Rhonda OR Rita OR Roberta OR Robin OR Robyn OR Rosa OR Rose OR

Rosemary OR Roxanne OR Ruby OR Ruth OR Sabrina OR Sally OR Samantha OR Sandra OR

Sandy OR Sara OR Sarah OR Shannon OR Shari OR Sharon OR Shawna OR Sheena OR Sheila

OR Shelia OR Shelley OR Shelly OR Sheri OR Sherri OR Sherry OR Sheryl OR Shirley OR Sonia

OR Sonya OR Stacey OR Stacie OR Stacy OR Stefanie OR Stephanie OR Sue OR Susan OR

Suzanne OR Sylvia OR Tabitha OR Tamara OR Tami OR Tammie OR Tammy OR Tanya OR Tara

OR Tasha OR Taylor OR Teresa OR Terri OR Terry OR Theresa OR Tiffany OR Tina OR Toni OR

Tonya OR Tracey OR Traci OR Tracie OR Tracy OR Tricia OR Valerie OR Vanessa OR Veronica

OR Vicki OR Vickie OR Vicky OR Victoria OR Virginia OR Vivian OR Wanda OR Wendy OR

Whitney OR Yolanda OR Yvette OR Yvonne

This search finds 49% of all U.K. women on LinkedIn

Facets

Facets

Joined

Active Job Seekers

(seeking OR seeker OR "looking for"

OR "in search of" OR "open to" OR

"new job" OR "actively pursuing" OR

"pursuing new" OR "searching for"

OR "new opportunity " OR "new

opportunities" OR "available for")

Critical Questions

Would people with the skills and experience I'm looking for use my title(s) and

explicitly mention my search terms?

How can I retrieve profiles I've previously excluded?

How can I search LinkedIn specifically to find people that no one else has?

How many ways could someone possibly express the skills and experience I

am looking for?

Am I overlooking people because I don't see the right keywords?

Q&A

Business

Building a Solid Foundation with the Boolean Black Belt I Talent Connect London 2013