HR Analytics report

8/12/2019 HR Analytics report

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I n S e a r c h o f H R I n t e l l i g e n c e :E v id e n c e B a s e d H R A n a l y t i c s P r a c t i c e si n H i g i i P e r f o r m i n g C o m p a n ie s

D r S a l v a t o r e F a l l e t t a

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There is a dawningawareness that data and information as acom modity in and ofitself haslittle value to a n organization unless it is transformed into meaningful intelligence.Thesheervolume of B ig Data thatorganizations can and do amass isoverwhelming. What is neede d isthe type ofalchemythat transforms data and information into analytics and intelligence vis visanevidence based approach. In the context ofhumancapitalmanagement HR intelligence asderived from HR research and analytics practices is a fast em erging mandate fororganizationsseeking strategic competitive a dvantage.Advancing HRAnalytics

The topic of HR intelligence or what ismore popularly and perhaps narrowlyreferred to as human capital, talent,people, and/or HR analytics is one of the hot-test trends in the context of HR strategy anddecision ma king. Several notable thoug ht-leaders have called for the HR profession toadopt an evidence-based management, deci-sion science, HR intelligence, and predictiveanalytics approach to understanding andmanaging human capital in order to improveindividual and organizational performance(Pfeffer & S utton, 2006; Boudreau CRams-tad, 2007; Falletta, 2008; Fitz-enz, 2010respectively). W ith the exception ofahandful

of high-profile case studies (e.g., Google,IBM, and M organ Stanley), little is knownabout the extent to which Fortune 1000 andselect global companies are performingbroader HR research and analytics practices

This article summarizesthe results of The HRAnalytics Projectconducted by theOrganizational IntelligenceInstitute and DrexelUniversitybeyond simple descriptive metrics and score-cards, and more importantly how suchactivities are being used to facilitate HR strat-egy, decision m aking, and execution.This article summarizes the results of heHRAnalytics Project conducted by the Organiza-tional Intelligence Institute and Drexel

University. The HR A nalytics Project is thelargest study to date on the topic of HRresearch and analytics in terms of the numberof participating companies representing theFortune 1000 and select global firms.The purpo se of the study was to gain insightinto the extent to which these high perform-ing companies (i.e.,high performing firms interms of annual gross revenue) are conduct-ing a wider range of HR research andanalytics practices in the context of humanresource strategy and decision making. Sev-eral key areas related to HR research andanalytics were explored, including:1. The types of HR research and analyticspractices being performed in high perform-ing companies2.Org aniza tion and structured of HRresearch and analytics3.HR resea rch and analytics role in HRstrategy, decision-making, an d execution4.The meaning of HR intelligence5. The emerging ethical implications associ-ated with the predictive analytics movementMethodologyOver 3 000 HR professionals representing theentire F ortune 1000 as well as select global firmswere invited to participate in the survey. Thesurvey included 29 core items with a num ber ofsecondary items and various response alterna-tives (e.g., Likert-type scale, yes/no, rank order),as well as several open-ended questions. Someof the items were adapted from a benchmark-ing study conducted in 2001 by the principalresearcher on the topic of HR intelligence prac-tices (Falletta, 2008) while other variables wereadapted and used from a survey instrumentdeveloped by senior research scientists at theUniversity of Southern California's Center for

Effective Organization (Levenson, Lawler, &Boudreau,2005;Levenson, 2011). In additio n, atargeted, snowball sampling approach was usedto promote and generate interest in the projectthrough several notable membership consor-da such as The Mayflower Group, InformationTechnology Survey Group (ITSG), and Attritionand Retention Consortium (ARC), as well as anumber of Linkedin groups dedicated to HRmetric s and analytics, HR intelligence, employeeengagement surveys, workforce planning, andhuman capital strategy.

ParticipantsIn total, 220 distinct companies completedthe web-based survey representing 47 differ-ent industries. No duplicate responses werereceived (i.e., all recipients of the invitationto participate in the survey forwarded thesurvey URL to the best individual or groupresponsible for HR research and analyticswithin their compan y). Of the 220 com-panies that participated, 195 were Fortune1000 companies and 21 were global firmsheadquartered outside of the United States.Of significance, 39 participating compa-nies were Fortune 100 firms. In terms ofrespondent characteristics, 87% (n = 187)were senior HR leaders and specialists whoregularly perform broader HR research andanalytics work (e.g., metrics, employee/orga-nizational surveys, assessments, evaluation,applied human capital and organizationalbehavior research).

Evolving PracticesThe first research question focused on thetypes of HR research and analytics practicesthat are currently conducted in high per-forming companies. The survey asked par-ticipants to rate the importance of 18 HRresearch and analytics practices in terms ofinfluencing HR strategy and decision-mak-ing(seeTable 1). >-

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Employee and organizational sur-veys received the highest impor-tance ratings in the study, (overallmean rating of 4.15), which isn'ttoo surprising given that surveysare one of the most prevalent andwidely used methods for collect-ing data and information aboutemployee's thoughts, feelings,and behaviors. While a mainstayfor years among HR research-ers and skilled OD practitioners,employee and organizational sur-veys appear to be evolving in importancewith respect to HR research and analyticscapabilities at high-performing companies.

Surveys arestill the mostimportantHR researchand anaiyticstooi at ourdisposai

Surveys in general are com-monly used for varied pur-poses in the context of hum ancapital strategy and manage-ment (e.g., assessing trainingneeds, evaluating programsand solutions, measuringemployee perceptions andattitudes, conducting organi-zational research). The largercompanies in the sample(e.g., Fortune 100), however,tend to construct and deliverstrategically focused employee and organi-zational surveys that account for key fac-tors and variables that enable, inhibit, and

T A B L E 1 I M P O R T A N C E R A T IN G S O F H R R E S E A R C H A N D A N A L Y T IC S P R A C T IC E SHR Research Analytics Practice

Empioyee and organizational surveys(e.g.,employee opinion surveys, engagement surveys,organizationai cuiture/climate surveys, organizational health surveys, organizationai effective-ness surveys, organizational alignment surveys)Employee/talent profiiing(i.e.,tracking and modeling individual data on critical talent orhigh-potential employees)HR metrics and indicatorsPartnership or outsourced research Inciuding membership-based research consortia such asthe Corporate Leadership Councii,The Conference Board, university of Southern Caiifornia'sCenter for Effective Organizations, Corneii's Center for Advanced Human Resource Studies, andthe institute for Corporate Productivity (4CP) to name a few scorecards and dashboardsWorkforce forecasting(e.g.,workforce suppiy/dema nd and segmentation analysis to forecastand plan when to staff up or cut back)Ad hoc HRiS data mining and anaiysisHR benchmarkingTraining and HR program evaiuationLabor market, taient pool and site/loc ation identification researchTalent supply chain(e.g.,anaiytics to make decisions in reai time for optimizing immediatetalent demands in terms of changing business conditions)Advanced organizational behavior (OB) research and modeling(e.g.,linkage studies, driveranaiysis, correlation and regression anaiysis, factor analysis, path analysis, causai modeiing,and structural equation modeling procedures)Seiection research invoiving the use of validated personality instruments that measure variousempioyee traits, states, characteristics, attributes, attitudes, beiiefs, and/o r vaiuesReturn-on-investment (ROi) studiesQualitative research m ethods inciuding case studies, focus groups, and content or thematicanalysis360 degree or multi-rater feedback (e.g.,360 degree leadership and management assess-ments)Literature review(e.g.,a review and synthesis of existing or secondary data sources sucharticies and research reports including evidence-based and schoiarly/peer-reviewed journaiarticies)Operations research and management science(e.g.,optimization methods such as iinearprogramming; stochastic processes/Markov anaiysis; Bayesian statistics, computationalmodeiing, and simuiations)

Mean4.15

3.643.633.60

3.573.553.503.273.273.233.233.13

3.073.053.012.932.86

2.33

220

215218213

211215218215220215172208

210212212218214

148

Source: Falletta, S., Organizational Intelligence Institute , 20 13

in some cases predict employee engagementand other important individual and orga-nizational outcomes (Falletta, 2008 b). Formany, the annual, company-wide employeesurvey serves as the primary data feed forHR strategy formulation and human capitaldecision making.In terms of the type of HR research and a na-lytics practices, a closer examination of thedata gleaned the following observations andinsights. Fortune 100 and large global firms rated employee and organizational surveys asslightly more important (4.33 and 4.24respectively) as compared to the overallmean rating (4.15) and other Fortune cat-egories. High-performing com panies in terms ofsize and gross revenue tend to invest asignificant amount of resources and timeon employee and organizational surveyinitiatives. Over a third of all respondents(36.4%, n = 80) reported employee andorganizational surveys as the most ex-pensive or costly to perform and the thirdmost time-consuming HR research andanalytics practice. The larger companies, such as Bank ofAmerica, Dell, Eli Lilly, Ford, Google,Intel, Microsoft, Nike, IBM, Target,and SAP, benchmark and compare theirsurvey results through employee re-search membership consortiums, such asThe Mayflower Group (www.mayower-group.org) and Information TechnologySurvey Group (www.itsg.org). In doing

s member companies can make indus-try and cross-industry comparisons byjob family, similar groups, business units,and/or functions. Respondents rated advanced OB research

and modeling as the most time-consumingand most difficult to perform. Whereas,talent supply chain (e.g., analytics to makedecisions in real time for optimizing imme-diate talent demands in terms of changingbusiness conditions) was rated the secondmost difficult to perform, which is consis-tent with previous research and observa-tions (Davenport, Harris, CShapiro, 2010). Surprisingly, the literature review re-ceived the second lowest importance rat-ing (2.82), while global firm s (companies

headquartered outside of the US) ratedthe importance of literature reviews sig-0 PEOPLE STRATEGY


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nificantly higher than all other Fortunecategories, thereby suggesting a greaterinterest in and orientation towards evi-dence-based HR in terms of HR strategyand decision making.

science received the lowest rating (2.33)in terms of facilitating HR strategy anddecision making although interestin optimization methods as well as theemerging application of artificial intelli-gence (i.e., expert systems and machinelearning) to HR management decisionsare likely to increase as advancements inskills, capabilities, and technology con-tinue (Sesil, 2014).

comp anies. Over three- n = 169) indicated that they have

In terms of staff

to this function. Additional analy-

nt to note tha t these results merelycs groups. Itisquitey tha t ove rall staffing levels of those who

ypically decentralize and embed HR

(e.g., IT or Finance specialists) do-

T A B L E 2 . M O S T C O M M O N F U N C T I O N O R G R O U P N A M E SHR AnalyticsHR IntelligenceWorkforce AnalyticsTalent AnalyticsHR InsightsHR ReportingEmployee InsightsGlobal HRInsightsHR TechnologyHRISHuman Capital intelligenceTalent Managem ent &AnalyticsEmpicyee Surveys &Insights

N = 13N =7N =7N =6N - 5N= 5N =4N =3N =3N =3N = 3N =3N - 2

HR Quality &AnalyticsHR ResearchHR StrategyOrganizational InsightsPeople AnalyticsPeople MetricsPeopie ResearchSurveys & AssessmentsWorkforce IntelligenceWorkforce MeasurementWorkforce PlanningWorkforce Research

N =2N =2N - 2N = 2N = 2N = 2N = 2N = 2N = 2N = 2N = 2N = 2

Nearly a third (31.4% N=53) of all dedicat-ed HR research and analytics groups reportdirectly to the Chief HR Officer (i.e., head ofHR) suggesting that these functions are stra-tegically positioned in terms of organiza tionalstructure, whereas, the mean and mode wereonly two levels down from the top, indicatinga substantial degree of organizational statusbeing accorded to this function.

Source: Falletta, S., Organizational Intell igence Institute, 2013

While the function or group nam es vary,the nature and content of the practices andactivities appear to be HR research and ana-lytics related. Table 2 lists the m ost com monfunctional or group names. HR analyticswas the most common function or groupname (N = 13), followed by HR intelligence(n=7), workforce analytics (N=7), and tal-ent analytics (n=6) respectively.

E X H IB I T 1 . H R R E S E A R C H A N D A N A L Y T I C S R O L E IN F A C IL IT A T IN G H R S T R A T E G Y

60 A N D D E C I S IO N M A K I N G

50%40 I l l s30%30%20%10%

0%

Overall (N= 218) Fortune 1-100 (N=3 9) Fortune 101-500 (N=74)B Fortune 501-10 00 (N=82)

Global (N=21)Select 1 bil l ion + (N=4)

HR anaiyticsplaysn orole

in HR strategyformulat iona n ddecis ion m aking

6.4%2.6%9.6%7.3%0.0%0.0%

nil h l l | |J H .iB LR a naiyt icsis involvedin

imp iement ing /executing HR

strategy

3 0 . 32 1 . 13 2 . 92 9 . 33 8 . 15 0 . 0

HR analyticsprovides inputt othe HR strategy

and helpsimpiement it

after it hasbeenformulated4 9 . 55 0 . 05 0 . 74 7 . 65 7 . 12 5 . 0

1 iHR analyticspiaysa

central roleinformulat iona ndimplementat ionof HR strategy

1 3 . 82 6 . 3

6.8%1 5 . 94 . 8

2 5 . 0

Source: Falletta,S .,Organizational Intelligence Institute, 2013

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Role in HR Strategy &Decision MakingThe third research question addressed theextent to which HR research and analyticsfacilitate HR strategy, decision-making, andexecution.The response alternatives and their frequen-cies of choice are reported in Exhibit 1.HR analytics is characterized as having inputinto HR strategy formulation but not play-ing a central role in its formulation in abouthalf (49.5%) of the companies in the study.A central role in HR strategy was reportedfor less than 15% of the companies, whereasin nearly 37% of the sample, HR analyticsis characterized as playing little or n o role inHR strategy formulation.When asked to elaborate or provide addi-tional informa-tion about theHR research andanalytics role ininfiuencing HRstrategy formula-tion and decision-making specifical-ly, an overarching

theme emerged inwhich broader HRresearch and ana-lytics pr ctices werelargely described asan exhaustive datagathering exercise(i.e.,a data dump),whereby pre-con-ceived notions orand decisions drove

T h e r o l e of H Rr e s e a r c h a n da n a l y t i c s isl a r g e l y a n e n a b i e ra n d / o r d a t a f e e dt o t h e s t r a t e g yf o r m u i a t i o n a n dd e c i s i o n - m a k i n gp r o c e s s .

after-the-fact, HR strategiesthe actual data requirements.In short, HR analytics has a long way to go.More often than not, data and analytics areused to support decisions that have alreadybeen made rather than to question the cur-rent path of HR strategy and planning withinlarge companies.According to Pfeffer and Sutton, in theirbook Hard Facts Dangerous Half Truthsand Total Nonsense (2006), the idea ofusing data to make decisions changes thepower dynamics in a company. For ex-ample, a powerful and/or narcissistic leaderwould probably prefer to make decisionsbased upon his or her opinions and intu-

ition rather than relying on the good factsand figure s (i.e., evidence). Similarly, Sesilexplains in his recent book. Applying Ad-v n edAnalytics to HR Management Deci-sions (2014) that those in positions of pow-er might have fragile egos and be primarilyconcerned with advancing their own agen-da rather than dealing with actual facts.Indeed, further work is needed in terms of

Results describe the limitations of analyticsand the role of quantitative and qualitativedata. For example, a purely analytical anddispassionate approach to human capital de-cisions is a recipe for organizational analysisparalysis. Likewise, making critical HR deci-sions solely based on prior experience, intu-ition, gut feelings, and/or management fad dujourcould have disastrous effects. Inshort we

EXHIBIT 2 . T H E H R INTELL IG ENCE VALUE CHAINintuition intelligence

Human capital decisionsare arge ybased onprior experiences,opinions, gut feelings,current trends and/or fads.0 1 2 3 4 5 6 7 8 9 10

data information analytics

Human capital decisionsare based on insightfui HRanalytics that are largelypredictive and supported bya synthesis of the best availablescientific evidence(i.e. evidence-based HR).

Source; Falletta, S,, Organizational Intelligence Institute, 20 13

elevating the status and legitimacy of HRanalytics and its infiuence on HR strategyand decision making.The beauty of advancedanalytics, according to Sesil, isthat it does not care who itannoys (2014, pg 11).

While speaking truth to power can be risky(and a little fun), we need to recognize thatHR analytics is both an art and science. Thatis, we shouldn't abandon our intuition andwell-seasoned expertise (Sesil, 2014). Daven-port, Harris, & Morison (2010) in their bookAnalytics at W ork: Smart Decisions Better

need to balance the art and the science of HRanalytics while adopting an evidence-basedHR orientation and raising the bar in terms ofadvanced analytics literacy (Bassi, 2011).Core HR Intelligence Capabilitiesand ProcessesThe second group of survey items included 24HR practices and processes that were rated onan 11-point scale of HR Intelligence, refiecdngdegrees of HR research and analytics capabilities(i.e., level of sophistication) in terms of humancapital decision-making (refer to Exhibit 2).For the purpose s of this study, the HR Intelli-

T A B L E 3. HR IN T E L L IG E N C E C A P A B I L IT IE S B Y H R P R A C T I C E S , P R O G R A M S ,A N D P R O C E S S E S T O P 12

Highest rated HR practices in terms ofHR inteliigence capabilities1,Employee organizational surveys2, Employee engagement retention3, Compensation4,HR strategy5, Workforce planning6. Competency talen t assessments7. Benefits8. Performance appraisal management9. Reduction in force downsizing10, HR legal comp liance11 , Succession planning12, Recruitment

Mean6,596,055,905,625,545,355,345,295,145,115,095,03

N21 4212215215215214215214206212215214

Source; Falletta, S., Organizational Intelligence Ins titute, 201 3

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TABLE 4. HR INTELLIGENCE CAPABILITIES BY HR PRACTICES,PROGRAMS, AND PROCESSES BOTTOM 12 )

Lowest rated HR practices in terms of HR intelligence capabilities1 Knowledge management2 Organization design3. Organizational learning4 Employee on-boarding5. Career development6. Diversity inciusion7. Change management8. Selection9. Advancement promotions1 0 Organization deveiopment11.Training and development1 2 Management leadership development

Mean3.483.863.923.954.074.534.584.764.814.834.884.99

N21 321 221 321 421 521 1212214215213215211

gence Value Ghain was ada pted from HR In-telligence H ierarchy w hich included threelevels namely Data, Information, and In-telligence (Falletta, 2008). While the HR In-telligence Value Ghain is by no means a vali-dated scale in terms of measurement validityand reliability, it does provide a practicalframework with which to estimate and gaugeHR intelligence capabihties as a first step inconducting applied research on the topic.The ratings of these 24 HR activities are re-ported in Table 3 and Table 4 respectively.Employee and organizational surveys re-ceived the highest HR intelligence ratings(mean score of 6.59 on the 11-point scale)

Source: Falietta, S., Organizational Intelligence Institu te, 201 3

and was the only HR practice on the cuspof what could be considered analytics(7 and 8 on the scale) in terms of HR intelli-gence capabilities and level of sophistication.Employee engagement and retention (6.05),compensation (5.90), HR strategy (5.62),and workforce planning (5.54) rounded outthe top five. As expected, the larger Fortune100 firms were slightly ahead of the curve interms of their HR intelligence rating acrossall of the HR practices.Knowledge management received the low-est HR intelligence ratings (mean scoreof 3.48 on the 11 point scale) in terms ofHR intelligence capabilities and level of so-phistica tion. Organ ization design (3.86),

T A B L E 5 E F F E C T IV E N E S S R A T I N G S O F C O R E H R I N T E L L IG E N C E A C T I V IT I E SCore HR Intelligence ActivityPerforming value-added HR research and analytics that enables strategyformulation, decision-making, execution, and organizational learning.Gathering external or competitive data and information on other best-in-class companies/organizationsGathering internai data and information to better understand your people,taient and workforce in the context of the businessLinking multiple data and information sources to predict, modei andforecast individual, group and organizational behavior and performanceoutcomesAnaiyzing and transforming data and information into knowledge, insightand foresightCommunicating and reporting insightfui and usefui research findings andinteiligence result

Mean3.423.563.732.71

3.28

3.42

N21 421 821 821 8

21 7

21 7Source: Falletta, S., Organizational Intelligence In stitute, 201 3; Falletta, S., HR Intelligence, 200 8

organizational learning (3.92), employeeon-boarding, (3.94), and career develop-ment (4.07) rounded o ut the bottom five.Again, the larger Fortune 100 firms wereslightly ahead of the curve in terms of theirHR intelligence capabilities across all of theHR practices.It shouldn't be too surprising that knowl-edge management and organizational learn-ing were in the bottom five. Definitionalproblems persist and many companies stillstruggle to effectively implem ent these evolv-ing practices. Organization design has beenaround for years in OD circles and there area number of excellent publications on thetopic, yet internal HR or OD practitionersrarely get to play in this space. Senior execu-tives typically sort out such matters on theirown behind closed-doors - either as a seniorleadership team or in consultation with oneof the big Ivy-League consulting firms.Lastly, it should be noted tha t no H R practicewas rated at the intelligence level (9 to 10)for any of the Fortune categories - therebysuggesting that HR inteUigence is much moreof an analytical aspiration at this point formany companies. The route to building HRintelligence capability that can improve hu-man capital decision making will depend onthe level of HR analytical maturity as wellas the extent to which a given company em-braces evidence-based HR.The third and final group of survey items inthe Core HR Analytics Capabilities cPro-cesses section of the survey asked partici-pants to rate their effectiveness on a 5 pointscale (1 = very ineffective, to 5 = very effec-tive) on six core activities associated withHR research and analytics work (see Table5 . These six statements were derived froma previous study conducted in 2001 whichasked participants to describe what HRintelligence (i.e., broader HR research andanalytics activities) meant to them (Falletta,2008).The mean rating for linking multiple dataand information sources to predict modeland forecast individual group and orga-nizational behavior performance outcomeswas relatively low. For many participatingcompanies, this particular activity is still avery challenging and emerging core capabil-ity. As described earlier, respondents rate d advanced O B research and modeling as themost timing-consuming as well as most dif-ficult to H R research and analytics practiceto perform.

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O B S E R V A T I O N S & IN S IG H T S - W H OS H O U L D O R C A N D O A N A L Y T IC S ?Driving a proactive HR research and anaiyticsagenda is a critically important capability interms of enabling strategic human capitaldecisions.Therefore, HR researchers andanalysts should bring their own HRintel-ligence and expertise to the table. Many ofthe respondents in this study hold advanceddegrees in the social, behavioral, and organi-zational sciences and are arguably in the bestposition to design and interpret robust HRresearch and analytics results. While an HRIS,IT,and/or financial analyst might possess thetechnological and statistical chops to mineand model data, it takes an applied research-er with the right disciplinary background toaccurately interpret the data and identify anypredictive insights in the context of individual,group, and organizational behavior.

Source: Falletta,S., OrganizationalIntelligence Institute, 20 13

Who DeterminestheHR Research andAnalytics Agenda?Respondents were askedtoindicate whetherthe company conductsaformal HR researchand analytics agenda process. Interestingly,only 39.5 % (N =87) of participants reportedhavingaformalHRresearchandanalyticsagenda process despitethefact that 76.8 %(n=169)of allparticipating companiesin-dicated that they haveafunction or groupdedicated to HR research and analytics. Thismight suggest thatHRresearchandanalyt-ics activitiesand itsprioritizationarelarge-ly reactive and stakeholder and customerdriven rather than proactive and researchand analyst driven. However,on average,nearly 4 0% ofall HR research and analyticswork was identified as proactive (39.3%,n =215) and determined by the HR researchor analytics team (40.3%,n =215), whileapproximately 60%of all HRresearchandanalytics work wasidentified as reactive(59.7%,n = 215 andstakeholder or cus-tomer driven (60.7 %, n =215). In short, thisdemonstratesarelatively balanced approachin terms of determining theactualHR re-search and analytics agenda.

EXHIBIT 3. THE HR INTELLIGENCE CYCLE

1 :determine stakeholder requirements tactical

7: enable strategy+decision makingimitator+ improver+innovator* iconoclast

6: connmunicateintelligence resultsdescriptive prdictive prescriptive

2 :define HR research+analytics agenda

3: identify data sourcespuMc- private

4 : gather data5: transform data

meta-aiulytics

Source; Falietta, S., Organizationai intaiiigence Institute, 20 13

The MeaningofH RIntelligenceThe forth research question explored themeaningof HR intelligence bythosewhoperform HR research and analytics. Respon-dents were asked to rank in order seven itemsin terms of how accurately they describe whatHR research and analytics means. The rank-

ings of these items are reported in Table6.The rank orderispresentedinordinal fash-ion (i.e.,1,2,3, 4, 5, 6, and 7) for the sake ofsimplicity and includes the actual mean rank .The overall mean rank was 4.09 . W hile thereare certainly a diversity of views, thefirstwo(Rank and 2) emerged as significantly moredescriptive thantheothersas to thecentralactivitiesofHR research and analytics.

TABLE 6. THE MEANING OF HR RESEARCH AND ANALYTICS RANK ORDER)

The MeaningofH R Research and Analytics (Rank Order)Making better human capital decisions by using the best available scientificevidence and organizational facts with respect to evidence-based HR (i.e., get-ting beyond myths, misconceptions, and plug and play HR solutions, fads, andtrends)Moving beyond descrip tive HR metrics (i.e., lagging indicators -something thathas already occurred) to predic tive HR metrics(i.e.,leading indicators-some-thing that may occur in the future)Segmenting the workforce and using statistical analyses and predictive modelingprocedures to identify key drivers (i.e., factors and variables) and cause and ef-fect relationships that enable and inhibit important business outcomesUsing advanced statistical analyses, predictive modeling procedures, and humancapital investment analysis to forecast and extrapolate 'wh at-if scenarios fordecision makingStandard track ing, reporting, and benchmarkingofH R metricsAd-hoc querying, drill-down, and reportingofH R metrics and indicators throughsome typeofa HRIS and HR scorecard/dashboard reporting toolOperations research and management science methods for HR optimization (i.e.,what's the best that can happenifw e do XV Z or what is the optimal solution for aspecific human capital problem?)

Rank Order1

2

3

4

56

7

Mean Rank(N)2.63 (N = 219)

2.66 N = 219)

3.47 (N = 21 9

4.37 N = 219)

4 . 6 7 ( N - 2 1 9 )4.92 (N = 219)

5.90 N = 219)

S o u r c e : F a l l e t t a , S ., O r g a n i z a t io n a l I n t e l li g e n c e i n s t i t u t e , 2 0 1 3

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HR intelligence is defined as a

(Falletta, 20 08 , pg. 21) . In order

ee Exhibit 3 ).

HR intelligence en-

on insightful H R analytics which are largelypredictive and supported by a synthesis ofthe best available scientific evidence (i.e.,evidence-based HR) (see Exhibit 2). Thekey differentiator between HR analyticsand HR intelligence is that the latter is sup-ported by empirical and theoretical research(i.e., scholarly evidence that resides outsideof your organization).Lastly, merely mining and modeling yourinternal employee data is tantamount to atheory free, correlation fishing expeditionunless such data and insights can be analyzedand supp orted in relation to other sources ofinternal and external d ata. Only then can youmake valid and reliable predictive assertionsand prescriptive recommendations.

D on 't Be EvilAll professions, like HR, are built aroundnorms, values, and ethical principles abouthow professionals and organizations are toconduct themselves. In this study, an a ttemptwas made to investigate ethical judgments as-sociated with H R research and predictive an-alytics. Ethical questions have begun to ariseabout the potential abuses of HR analyticswith respect to technological advancementsand mining and modeling Big Da ta (Bassi,2011).Twenty-one practices were selected and in-cluded in the survey some of which havehad a long history of controversy from

TABLE 7 APPROPRIATENESS OF SELECT WORKFORCE DATA COLLECTION AND HR PRACTICES

Workforce Data Coiiection andHRAnaiytics PracticesPerformance appraisai/evaluation ratingsPre-coding seemingiy harmiess demographic data for an organizationai or empioyee engagement survey project (e.g. identifying, linking, and retain-ing employee information in advance such as business unit, iocation, grade or band level on each survey respondent)Pre-coding top taien t em ployees(e.g.,high performers, high potentiais) empioyee demographic data for an organizational or employee engagementsurvey project (e.g.,identifying, iinking, and retaining employee information in advance such as performance appraisai rating, promotion readinessstatus, and other high-potentiai attributes on each survey respondent)The use of 360 degree feedback results designed soieiy for the leadership development purposes (e.g., research has shown that ieadership quaiity/effectiveness as measured by the 360 degree instrument predicts actuai employee turnover)Personality assessment results(e.g.,Hogan's Big-Five pe rsonaiity, 16PF)The reiative rank of empioyees derived from forced ranking process as part of a company's performance appraisal/evaluation system (i.e.,a perfor-mance management approach that assesses employee performance relative to peers rather than against predetermined goals)The use of emotionai intelligence (EQ) test scoresPre-coding diversity related demographic data for organizationai or empioyee engagement survey project(e.g.,identifying, linking, and retainingempioyee information in advance such as gender,age,ethnicity, and marital status on each survey respondent)The use of Myers-Briggs typologiesThe use of inteiiigence (iQ) test scores(e.g.,Wechsier's Aduit Intelligence Scale or the Stanford-Binet inteiiigenceTest)The use of gnerai surveys that explorea job applicant or employee's attitudes, preferences, values and behavior which include seemingiy innocuousand irrelevant items/ques tions pertaining to their personal life(e.g., what magazines do you subscribe to? and what pets do you have? )Public data and information obtained from social media w ebsites (e.g.,Facebook and the iike)The use of standardized academic achievement test scores (e.g.,SAT, GMAT, GRE)The use of electronic performance monitoring technologies (e.g.,tracking the number of computer key strokes an employee performs each day or theamount of daiiy code a computer programmer generates)Conducting email analysis to identify workgroups/teams who aiways copy (cc) or biind copy (bcc) their boss as a possibie indicator of trust issuesTracking whether a new empioyee signed up for the company retirement program as an indicator of eariy turnoverThe use of surveiilance video to monitor work patterns and behaviorAn individu ai employee's personal data and information obtained from a company-sponsored Weiiness website or empioyee services portal job applicant's hometown or where they were born and raisedPrivate data and information obtained from social media websites (e.g.,Facebook and the like) whereby the empioyer asks a candidate or employeeto furnish his /her user-id and passwordAn individual employee's prescription drug usage obtained legally

Mean4.473.81

3.75

3.71

3.643.26

3.163.08

3.063.052.79

2.692.672.53

2.422.242.161.811.571.48

1.44

N215217217

217217217216217212215217213217214215215215216217215215

Source: Falletta, S., Organizational Intelligence Institute, 201 3

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intelligence (IQ) and personality testing toforced-ranking in performance appraisals toemployee performance monitoring and sur-veillance technologies. These practices havealways incited spirited debates among aca-demicians and practitioners with respect tothe appropriateness of using such methodsand tools for human capital decisions.Pre-coding employee survey demographicvariables have raised a few questions inrecent years (Saari c Scherbaum, 2011).A handful of emerging and unconventionalpractices, such as Google's elaborate surveythat explores a job applicant or employee'sattitudes, preferences, and values on seem-ingly innocuous aspects of their personallife (e.g., wh at magazines do you subscribeto? and what pets do you have? ) (Han-sell, 200 7), as well as identifying a job ap -plicant's hom etow n as a relatively accu-rate predictor of attrition (Ganguly, 2007),are dubious at best. More recently, privatedata and information obtained from socialmedia websites (e.g., Facebook), wherebyemployers ask a candidate or employee tofurnish his/her user-ID and password, havegarnered national attention.The fifth and final research question in thisstudy attempted to gain insight into the ethi-cal implications associated with the HR re-search and predictive analytics movement.Respondents were asked to rate 21 work-force data collection and HR analytics prac-tices on a five-point scale of approp riatenessranging from absolutely inappropriate toabsolutely appropriate. The appropriatenessratings of these 21 practices are reported inTable 7.There were five practices that had meanratings which were bo th significantly high-er than the overall mean (2.80) and fellinto the appropriate scale interval. Theseare listed below from highest-rated down-ward.

Performance appraisal/evaluation rat-ings Pre-coding survey demographic datain general Pre-coding survey demographic datafrom top talent employees 360 degree feedback results for leader-ship development purposes Personality assessment resultsFive of the practices had means that wereboth significantly lower than the overallmean and which fell into the inappropriate

scale interva l. These are listed below (or-dered from lowest upward): An individual employee's prescrip tiondrug usage obtained legally Private data and information obtainedfrom social media websites (e.g.. Face-book and the like) whereby the em-ployer asks a candidate or employee tofurnish his/her user-ID and password A job applicant's hometow n orwhere they were born and raised Surveillance video to monitor workpatterns and behavior Tracking whether a new employeesigned up for the company retirementprogram as an indicator of early turn-over

It is noteworthy that 76% of the listed prac-tices were considered neutral or inappropri-ate by the sample as a whole. Needless tosay, much more research is needed on ethi-cal issues associated with HR research andpredictive ana lytics. This study attem pted toexplore ethical judgments on select practicespertaining to human capital decisions in thebroadest sense. However, it is quite likelythat individual ethical judgments will varyand depend on the type of human capitaldecision being made (e.g., hiring, job/workassignments, performance management, ad-vancement/promotion, demotion, reduction-in-force efforts).

OBSERVATIONS & INSIGHTS -FIRST DO NO HARMOne disturbing trend I've experienced first-iiand involves HR professionals iiaving dif-ficuity distinguishing between the iaw andethics. For example, during a recent confer-ence in which i was invited to speak on HRintelligence, i shared a few questionable HRanaiytics practices, including the one aboutan applicant's hometown being used as arelatively accurate predictor of attrition. Af-terwards, a weii-known and highiy respectedHR metrics consu itant stood-up andsaid, Ihave no problem with it as long as it's le-gal and doesn't involve a protected group.While sharing the same exampies duringa recent presentation, I've received mixedreactions, surprisingiy, from a few very ex-perienced and competent industrial andorganizationai psychologists who seem tobe grappling with their company's w orkforcedata collection and HR anaiytics practices 1 in terms of their own underlying valuesand professional code of conduct (i.e.,APA's Ethical Principles o f Psycho logists andCode of Conduct and in particular the gen- erai principle - First, Do No Harm). Cleariy,further discussion and debate are neededabout ethics in general and the applicationof Ranaiytics in particular(Bassi,2011).Ali of this begs the question: should Riprofessionais and iine managers makehuman capital decisions based on an ap-piicant's hometown? What about an em-ployee's pet preferences or favorite icecream flavor? i suppose dog iovers fromsmall towns are more loyal and commit-ted than cat peopie born and raised in ^the urban jungie, and jus t maybe - bu tter pecan employees have a higher EQ and 'make better leaders than piain oie vaniiiafoiks. Irrespective to any predictive utiiity,how appropriate is it to use such data andinformation for human capital decisions?When I got off my soapbox, a quick-wittedcoiieague and oid friend said to me thatthe genie is aiready out of the bottie andit will probably take Federal legislationto sort it out. Mean while, if HR profes-sionais are willing to proactlveiy addresssuch ethicai quandaries and challengequestionable HR anaiytics practices re-gardless of any real or perceived predic-tive vaiue - there is indeed a bright futurefor HR analytics.

PEOPLE & STRATEGY


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s imple metr ics

No ne of these SaaS-based tools,all of the Big Da ta at our disposal.

ll done manually by expert HR researchers,

ur success hinges upon our collec-

s, and practices. In sum, proactive

HR intelligence arms strategists and decision-makers with pertinent knowledge and insightto make critical decisions pertaining to hu-man cap ita l. i ^ S

ReferencesBassi, L. (2011). Raging debate in HR ana-lytics.People Strategy, 34(2), 14-18.Boudreau J. c Ramstad, P. (2007). BeyondHR: The New Science of Human Capital,Boston, MA: H arva rd Business School Press.Davenport, T., Harris, J. , & Morison, R.(2010) . Analytics at Work: Smarter Deci-sions, Better Results, Boston , MA : HarvardBusiness School Press.Davenpor t , T , H arris, J. , & S hapiro, J.(2010). Competing on talent analytics. Har-vard Business Review, 5 2 -5 8 .Falletta, S. (2008). HR intelligence: Advanc-ing people research and analytics. Interna-tional HR Information Management Jour-nal. 7 (3), 21-31.Falletta, S. (2008b). Organizational intel-ligence surveys. Training Development,52-58.Fitz-enz, J. (2010). The New HR Analytics:Predicting Economic Value of Your C ompa-ny's Human Capital Investments. New York ,N Y : A M A C O M .Ganguly, D. (2007, February 23). Tamingthe beast: Psychometric profiling, demo-

graphic regression models, and predictivealgor i thms. The Economic Times.Hanse ll, S., (2007, Janu ary 3rd). Google'sanswer to filling jobs is an algorithm. Th eNew York Times Online.Levenson, A. (2011). Using targeted analyt-ics to improve talent decisions. PeopleStrategy, 34(2), 34-43 .Levenson, A., Lawler, E., & Boudreau, J.(2005). Survey on HR Analytics and HRTransformation: Feedback Report. Genterfor Effective Organizations, University ofSouthern California.Pfeffer, J. &: Sutton, R. I. (2006). Hard Facts,Dangerous Half-Truths, Total Nonsense:Profiting from Evidence-Based Manage-ment. Boston, MA : Ha rvard Business SchoolPress.Saari, L. & Scherba um, G. (2011). Identifiedemployee surveys: Potential promise, perils,and professional practice guidelines. Indus-trial and Organ izational Psych ology, 4(4) ,4 3 5 -4 4 8 .Sesil. J. G. (2014). Applying advanced ana-lytics to HR management decisions: Meth-ods for selection, developing incentives, andimproving collaboration. Saddle River, NJ:Pearson.

Dr. Salvatore Falletta is EVP and Man-aging Director for the OrganizationalIntelligence Institute (www.oi-institute.com) - a Skyline Group company. Dr.Falletta also is Associate Professor andProgram Director for Human ResourceDevelopment at Drexel University.Prior to Organizational IntelligenceInstitute and Drexel, he was Presidentand GEO of Leadersphere, served as aVice President and Ghief HR Officer ata Fortune 1000 firm based in the SiliconValley, and has held senior mana gemen tpositions in human resources at sev-eral global companies, including NortelNetworks, Alltel, Intel, SAP AG, andSun Microsystems respectively.Dr. Falletta is an accomplished speaker,researcher, and author and is currentlywrit ing a book on HR In tel l igence,Strategy, and Decision Making . He canbe reached at [email protected].

VOLUME 36 ISSUE 4 2014 37


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C o p y r i g h t o f P e o p l e & S t r a t e g y i s t h e p r o p e r t y o f H R P e o p l e & S t r a t e g y a n d i t s c o n t e n t m a y

n o t b e c o p i e d o r e m a i l e d t o m u l t i p l e s i t e s o r p o s t e d t o a l i s t s e r v w i t h o u t t h e c o p y r i g h t h o l d e r ' s

e x p r e s s w r i t t e n p e r m i s s i o n . H o w e v e r , u s e r s m a y p r i n t , d o w n l o a d , o r e m a i l a r t i c l e s f o r

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