Big Data in HR: Insight on the Meaning and the Opportunity


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Many companies today are talking about the opportunities associated with “Big Data,” but what are they doing about it? This webinar provides answers through first-hand insight on practical innovation approaches to putting today’s data-rich HR environment to work. Donna Quintal, senior manager of strategic sourcing at Sears Holdings Corporation joins Glen Cathey, VP, global sourcing and talent strategy with Randstad Sourceright, to explore how companies and recruiters are exploring vast stores of human data capital, including that found on job sites, social media and other sources, to find, attract, retain, and promote best-in-class employees.

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  • Great presentation, although I believe there are a lot more possibilities for HR and Big Data. Think only about the insights that can be gained from analyzing workplace behavior or analyzing all knowledge present within an organization. You can find more information in my article:
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  • Moneyball: The Art of Winning an Unfair Game, a book by Michael Lewis about the Oakland Athletics baseball team and its general manager Billy Beane.Paul is now vice president of player development and scouting for the New York Mets
  • Sabermetrics is the specialized analysis of baseball through objective evidence, especially baseball statistics that measure in-game activity. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research. It was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face
  • The Oakland Athletics' 2002 season featured the A's finishing 1st in the American League West with a record of 103 wins and 59 losses, despite losing three free agents to larger market teams: 2000 AL MVP Jason Giambi to the New York Yankees, outfielder Johnny Damon to the Boston Red Sox, and closer Jason Isringhausen to the St. Louis Cardinals. They are most notable for having set an American League record of winning 20 consecutive games between August 13 and September 4, 2002.[1]
  • Conventional wisdom can be a significant obstacle to advancement because it is often made of ideas that are convenient, appealing and deeply assumed.
  • Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch. image shows datasets that have been published in Linked Data format, by contributors to the Linking Open Data community project and other individuals and organizations. It is based on metadata collected and curated by contributors to theCKAN directory. Clicking the image will take you to an image map, where each dataset is a hyperlink to its homepage.
  • The size of the indexed Internet is estimated at 10.82 billion pages
  • How's that for velocity?
  • The variety of data sources and types should be obvious, especially when it comes to human capital data – LinkedIn profiles (which can now be converted into resumes/CVs) and updates, Facebook, Google+ and Twitter profiles and updates, recommendations/awards/endorsements, blogs, blog comments, mobile updates, press releases, and much, much more.
  • If you knew the answers to these questions your sourcing and recruiting model would already be shifting to a more proactive data based strategic sourcing/recruitment team.You would know your future needs for talent communities and targeted recruitment areasYou would know companies were it would be beneficial to gather competitive intelligenceYou would be developing more accurate job descriptions that are skill and competency basedYou would have identified the top training managers to ensure the new hires start off on the right track Then begin to consider the monetary impacts in knowing the answers to these questions.
  • Many companies still do not have transparency between HR and Recruiting. The common goal that these departments share is the desire to influence their business partners. Bringing down the wall between HR data and TA data will allow both departments to begin to create proactive predictive reporting. The insightful analytics derived from reporting will enable influence and create strategy models for both departments. HR impacts will be in TM with internal movement and ready succession plans. There is also a monetary value that can be placed on open key positions within organizations having internal and external plans ready can impact profitability. It is not only cost per hire there are many hidden costs such as payroll for coverage, training expenses, loss of VPC (variable profit contribution).
  • This is a HR/TA Data Warehouse Model there are vendors that offer these solutions or it can be done using SQL server with an analytics software package managed in house. If you are not ready to dive right into the data warehouse, MS Access and a survey provider is a good way to get started. Pick a topic and start to build your business case study to share with HR partners.
  • In this example Competitor 2, 7 and 4 are the where you had the best ROI. This is where I would begin to compile competitive intelligence such as (press releases/news, org structure, incumbent contact lists, and total rewards information (benefits, comp and incentives)
  • Gathering data on competencies and skills not only helps recruiting it is a guide for HR and Managers displaying skill gaps in incumbents to build development plans for future success
  • This data builds a solid case to attend on campus recruiting events in some locations and only post online for others. There are also some opportunities to build longer term partnerships with each University (speaking engagements, preferred internships and sponsorship)
  • offers a talent community solution “The Hive” it shares big data insights into the community you have built. This cloud tag is an example of Social Media trends that candidates share in the hive. This data could help you recruit with a known marketing strategy “product placement” Are your jobs mentioned in places that passive candidate may stumble across?
  • Big Data in HR: Insight on the Meaning and the Opportunity

    1. 1. Big Data in HR: Insight on theMeaning and the OpportunityDonna QuintalSenior Manager of Strategic SourcingSears Holdings CorporationGlen CatheyVice President, Sourcing andRecruiting Center of ExpertiseRandstad Sourceright
    2. 2. 2Agenda• The Moneyball phenomenon• What do we mean by Big Data?• The Opportunity• Big data in action: Moneyball recruiting• Creating real workforce intelligence• Wrap up: transforming HR and changing the conversation
    3. 3. 3The Meaning
    4. 4. 4Moneyball: The Art of Winning an UnfairGame,• a book by Michael Lewis about the OaklandAthletics baseball team, its general manager BillyBeane and his assistant Paul DePodesta• premise: the collected wisdom of baseball insiders(including players, managers, coaches, scouts, andthe front office) over the past century with regardto player selection is subjective and often flawed.Moneyball
    5. 5. 5The Oakland A’s didn’t have the money tobuy top players, so they had to findanother way to be competitive.Billy and Paul took ananalytical, statistical, sabermetric*approach to assembling their team, pickingplayers based on qualities that defiedconventional wisdom and the beliefs ofmany baseball scouts and executives.Moneyball*Sabermetrics is the specialized analysis of baseball through objective evidence, especially baseballstatistics that measure in-game activity. The term is derived from the acronym SABR, which stands forthe Society for American Baseball Research.
    6. 6. 6In 2002, with approximately $41million in salary, the Oakland A’swere competitive with larger marketteams such as the New YorkYankees, who spent over $125million in payroll that same season.They finished 1st in the AmericanLeague West and set an AL record of20 consecutive wins.Moneyball
    7. 7. 7Much of what is accepted assourcing, recruiting, interviewingand hiring, and talentmanagement best practices todayis largely based uponconventional wisdom - ideas orexplanations that are generallyaccepted as true.However, the problem with anyconventional wisdom is thoughthe ideas or explanations arewidely held, they are also largelyunexamined and untested, andthus not necessarily true.MoneyballThe Moneyball approach a real opportunity forcompanies today
    8. 8. 8Analyzing massive data sets (30K – 100Kemployees), Evolv has identified undervaluedcharacteristics and discovered non-intuitiveinsights, such as:• For hourly workers, people who fill out onlineapplications with 3rd party browsers (Firefox orChrome) rather than IE perform better andchange jobs less often• For call center employees, people with acriminal background actually perform a bitbetter than those who do not, and "jobhoppers" are no more likely to quickly quitthan those who have stayed in previous jobsfor long periods of timeMoneyballSource: The Economist, Robot Hiring
    9. 9. 9A large financial services firm believed that employees with goodgrades who came from highly respected universities made goodsales performers.MoneyballSource: Forbes, Josh Bersin productivity andturnover analysis wasperformed for newsales employees overtheir first 2 years ofemployment andcorrelated with totalperformance andretention againstvarious demographicfactors.
    10. 10. 10Big Data
    11. 11. 11What Big Data IsWikipedia claims that "Big data is a term applied to datasets whose size is beyond the ability of commonly usedsoftware tools to capture, manage, and process the datawithin a tolerable elapsed time.""Big data sizes are a constantly moving target currentlyranging from a few dozen terabytes to many petabytes ofdata in a single data set.”
    12. 12. 12What Big Data IsOther sources attempting to define big data include "thetools, processes and procedures allowing an organizationto create, manipulate, and manage very large data sets…"Regardless ofdefinition, the bigdata concept centersaround huge amountsof data that are notonly increasing involume, but also invelocity and variety.
    13. 13. 13Data VolumeSource: Mashable
    14. 14. 14The data velocity aspect is the speed at which new data isgenerated. One example of the increasing velocity ofhuman capital data would be social media posts/updates.For example, Twitter crossed the 400,000,000 tweets/daymark on March 21, 2013 - that’s 2.8 billion updates everyweek!Data Velocity
    15. 15. 15Human Capital Data:• ATS CVs• LinkedIn, Facebook, Twitter, Google+, etc. profiles and updates• Youtube, Quora, Flickr, Github, Stack Overflow, etc.• Mobile check-ins and updates• Recommendations/awards/endorsements• Blog posts and comments• Press releases/announcements• and much, much more!Data Variety
    16. 16. 16Big Data & AnalyticsMany people use the term "big data" when theyre reallyreferring to analytics.Big data refers to data sets that are typically high in volume,variety and velocity. A large volume of data doesnt qualify as"big data" unless the other attributes are present – velocityand variety (structured and unstructured).Analytics is the discovery and communication of meaningfulpatterns in data, which can be achieved with any data set.Correlating employee performance and retention data withdemographic data or assessments is an example of analytics,but not "big data."
    17. 17. 17The Opportunity
    18. 18. 18Big Data in Action: How can the Moneyball approachimprove your competitive edge in talent acquisition?A few ways we could apply the Moneyballconcept/analogy to talent acquisition:1. Assessing Talent: Moving away from usinglargely subjective means of assessing talent andmaking hiring decisions to more objective, factand empirical data-based means2. Out-recruiting Traditional TalentAcquisition: Identifying and acquiring top talentlooking for traits, experience, accomplishmentsand information overlooked by traditionalrecruiting and assessment methods3. Looking in New Places: Challengingconventional wisdom of what top talent looks likeand where it comes from (Ivy league schools, highG.P.A., certifications, M.B.A’s, experience atcertain companies, etc.)
    19. 19. 19Big Data in Action: What Could Moneyball RecruitingLook Like?Talent Competitive Edge (cont’d.):4. Real Measures of Performance:Developing objective performancemeasurements that are relevant acrossany role, responsibility, company, andindustry and that stick with each personas they move through their career, similarto a credit score5. Secret Sauce: Individual companiesdeveloping “secret sauces” for sourcing,analyzing and evaluating potential hiresbased on their own data and factualstatistical analysis of the makeup of theirideal hire and employee
    20. 20. 20Can you answer? How many current employees areretiring in 2013? How many current employees areunder preforming? What companies provided your topand bottom performers in 2012? What skills do current incumbentshave in common with one another? What are each managers 360Leadership scores or rank?
    21. 21. 21Moneyball in Action: What data should be shared?Personnel Data Education Level/SchoolOutside Work History 360 Leadership ScoresTalent Management Mobility Review ScoresBusiness Results SkillsInfluenceProactivePredictiveTransparency
    22. 22. 22Moneyball in Action: Getting the DataTalent Management Data, HRIS, & ATSData WarehouseCreateReportingShareAnalyticsMakeDecisionsTakeActionShowValue
    23. 23. 23Gaining Details of Competitive Hires2.5 & Below Below AVG 3.2 & Above Above AVG Grand Total Total RankCompetitor #1 10 16.13% 6 9.68% 62 -6.45%Competitor #2 2 5.00% 16 40.00% 40 35.00%Competitor #3 6 15.38% 8 20.51% 39 5.13%Competitor #4 8 24.24% 13 39.39% 33 15.15%Competitor #5 9 31.03% 11 37.93% 29 6.90%Competitor #6 2 7.41% 6 22.22% 27 14.81%Competitor #7 6 23.08% 10 38.46% 26 15.38%*Example Only Data Invalid
    24. 24. 24Example of Skills and Competencies by Position*Example Only Data InvalidManaging Hourly TeamsMicrosoft Word or equivalentManaging Salaried TeamsMicrosoft Excel or equivalentDelivering/facilitating training to othersServing as a MentorManaging a P&L statementTurning around a Poor PerformingMicrosoft PowerPoint or equivalentDelivering formal/informal presentations to various audiences
    25. 25. 25What Schools Did Top Performers attend?*Example Only Data InvalidUniv of South Alabama ALFlorida State University FLUniv of Iowa IAFlorida A & M University FLPennsylvania State University PA
    26. 26. Talent CommunityBuilds patentedSocial Talent GraphCaptureOne click, once.Performs real-time social updatesInfo is always up to can captureactive candidates,passive visitorsand employees tobuild a large TalentHive. Capture,Engage, and SaveJob BoardsCareer SiteFacebookLinkedInATSFile UploadiPadSmart PhoneEmployeesEmail & more...
    27. 27. 27Big Data: Social Media Trends*Example Only Data Invalid
    28. 28. 28Wrap up: transforming HRand changing the conversationData is the Great Equalizer Recruiters and hiring managersa two-way street The proverbial “seat at the table”Objective measurable intelligenceconnects talent to the business Changing “what matters” to reflectreal talent performance and potential
    29. 29. 29Thank You!Donna QuintalSenior Manager of Strategic Sourcing, Sears Holdings CorporationGlen CatheyVice President, Sourcing and Recruiting Center of ExpertiseRandstad SourcerightQ&