New Trends in Human Capital Research and Analytics

8/12/2019 New Trends in Human Capital Research and Analytics.

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New Trends in Human CapitalResearch and nalytics

A l e x i s A . F i n k M i c r o s o f t C o r p o r a t i o n


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areseeingabroad trend toward data-driven decisions across myriad business areas.In HRen evolvingfor thepast se veralyears.Levenson openshis2005 HRStrategi

article with, HR Analyticsis anemerging discipline that can h elp enable HRtofulfillthofbecominga true strategicpartner p.28).

acFit?,-enz, one ofthefounders of the ana-lytics movement has said: Unquestionably,analyticsisgoing to give HR a major make-

ence and BI is a prerequisite for sustain-

r many years, HR has successfullyevasive action will block HRtable.The good news is that there

here.The days of anecdotal reporting arehard evidence is the new language.

e use of analytics.

w and intriguing ways.

n and leverage a broader range of

that end, we sought to understand theextendel, we

most recent work by key thoughteaders regarding the state-of-the-art in

Weconducted inter-with several thought leaders in the field,

ewed the recent literature. Here arehe findings of our inquiry.

Our StudyWe explored new and current trends inresearch and analytics in three ways: (1) a

review of relevant recent literature, includingthe practitioner literature, academic litera-ture and popular press, (2) interviews withpractitioners in a variety of organizations,representing a variety of industries, and(3) interviews with a set of thought leadersin the area of human capital analyticsand research.Reviews of the practitioner literature (pri-marily CLC and Conference Board WhitePapers) offered some intriguing case studies.However, they often were described in isola-tion, rather than delving into the broadercontext of an ongoing research and analyticsstrategy. Further, they did not explain theirresults and integration into organizationalsystems in satisfying detail. Reviews of theacademic literature were similarly unsatisfy-ing identifying intriguing methods andrelationships, but not connecting them tothe broader picture of business success orlong-term strategy (There are notable excep-tions, primarily meta-analyses, e.g., Birdiet al, 2008.).In contrast to the academic literature, there isa growing body of popular press books onthe topic of analytics generally, as well as anemerging body specific to HR. This body ofwork seems to embrace the term HumanCapital, rather than Human Resources.Our emphasis here is to aggregate insights,observations and reflections from the inter-views we conducted during summer and fall2009.These interviews do not reflect a ran-dom sample of organizations, nor do theyinclude all organizations that are pushing theboundaries of analytics within HR. However,they do reflect a range of industries, geogra-phies,organizational maturity and size. Moreimportantly, they show a range of effectiveapproaches to analytics and research onpeople issues within organizations.The list ofparticipant organizations is in Exhibit 1.Where we had permission, we shared firmnames. Otherwise, we used a consistent

masking scheme; that is, we always refer tCompany G to as Company G.

InterviewsWe conducted interviews with 22 leadinorganizations and a half-dozen thought leaers over the summer of 2009. Interviewexamined a standard set of aspects relevant managing an internal Human Capital Researcand Analytics function. We addressed:1. Content and topic areas:

a. Employee Surveysb. Linkagesc. Manager Assessmentd. Leadership Assessmente. Quality of Hiref. Selection/Staffingg. Retention/Turnoverh. Performance Managementi. Onboarding/I.ifecycle Culture/Employee Value Propositio

E V P 2. Methods -The primary approaches us

to answer research questions and infordecisions |

3 . Staffing - Talent profile of the team coducting the work

4. Work profile - Extent to which teams aleading an agenda, partnering with keexecutives, executing against a pre-detemined set of priorities, or executinagainst annual or recurring processes

5. Influence model - Where, on this continum, does the team primarily operateTOOLS/PLATFORMSDATAANALYS IS INS IGHTINFLUENCEDECISIONS.

6. Consumpt ion - Who consumes twork, and what is the engagement modwith them

7. Organization - Reporting structure aorganization alignment

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Content AreasParticipants reported various content areaswhere research and analytics are influentialin their organizations. Rep resentation acrosscontent areas is shown in Exhibit 2. Some ofthe most commonly described focus areas forresearch and analytics were: Employee Sur-veys, Linkages, Manager Assessment,I eadersh ip Assessm ent, Quality of H ire,Selection/Staffing, Retention/Turnover, Per-f o r m an ce Man ag em en t , On b o a r d in g /Lifecycle, and Culture/EVP.However, the list above simply captures someofthemost frequently cited topic areas. Mostorganizations incorporated diversity andcompetencies into their analyses; tho se effortsare not represented separately here.Other areas were identified that are less well-represented, such as CompanyA'swork withtheir emerging country strategy and overallstructural assessments. Additionally, Com-panyA'sresearch and analytics team providessupport beyond their core scope of researchand analytics, working on high-level projectssuch as major reorganizations or big acquisi-tions. Company N reported intriguing workabout how people are working, such as officespace utilization, and the interaction betweenwork location (office, home, remote location)and performance. Beyond informing HRdecisions, those analyses also inform realestate and security decisions.At least one organization, PepsiCo, has devel-oped an integrated model that reflects alltheir areas of inquiry, shown in Exhibit 3.Some of the key questions addressed by Pep-siCo's four areas of inquiry are: External Marketplace

o Workforce planningo Demographicso Com petitors from employment brand-ingo Expected demand for talent

Internal Marketplaceo Jobs - what's the work we have? What are the promotion rates.'o Which roles have the highest turnove r? What are the feeder roles?o Are there structura l issues with any of

these jobs? Talent

o Who do you have?o Wh at are the capacities?

O Inventory of peopleo Gapso Projections of wha t will be needed

Perceptions and Surveyso What do people think?o How do they feel about the company?

Employee Surveys. Everyone included in thisproject delivered an em ployee survey. This islikelyaselection biasasmany ofthecompanycontacts came through survey benchmarkingconsortia. Typically, these surveys focus onemployee engagement, manager capability,etc.,and are distinct from (yet related to) otheremployee survey efforts, such as onboardingor exit surveys. Most are annual or biennialsurveys. Some (notably Company B) do roll-ing surveys, sampling one-twelfth of theirpopulation every month. Company L, in par-ticular, has done some intriguing things withits employee survey, developing a discretion-ary effort subscale and a propensity to quitsubscale. Microsoft has moved to name spec-ificity in its surveys, pre-populating managernames, and, for senior employees, seniorleader names. This has helped drive account-ability for survey results.Linkages. Most organizations reportedexpanding their usage of linkages to drawinsights across multiple data sets. hethoughtleaders included in this study also sawincreased use of linkage analyses, includingsome intriguing ones linking, for example,FBI branch-level engagement to outcomeslike compliance.When leaders discussed linkage analyses, theanalyses are often linkages among differentHR da tasets, rather than linkages to non-HRdata.Wewonder ifthis isthe best approachJay Jamrog has described one of thechallenges for HR/Human Capital as ourtendency as a function to focus on projectsbest described as HR tryin g to fix itselfrather than demonstrating compelling link-ages to key business issues.A handful of organizations (Unilever andCompany K, among others) link HR data tofinancial or other non-HR data. Target isdeveloping multi-level models to examinerelationships among individual assessmentscores, team level engagement and satisfac-tion, and store or organizational leveloutcomes, such as customer satisfaction andfinancial outcomes.Some organizations expressed frustration atthe infrastructure barriers to conducting

linkage research. One company noted mthan 30 legacy HR systems and four srate instances of Peoplesoft in NAmerica alone.Where they discussed linkage studies, often found the findings quite useful, illnating relationships or patterns that weither previously undetectable, or intuitiobvious but unproven in degree. Best demonstrated that engaged retail emplodeliver more rewarding customer experie(as measured via customer satisfaction veys), and,inturn, produce significantly sales than their disengaged colleagues. Oparticipants used results of linkage studiedrive such things as specific leader behavthat were shown to be effective, or refiselection criteria.ManagerAssessment.While several orgations went into depth describing tpractices around leadership assessment, feseemed particularly excited about their mager level assessment program s. Howethose that described processes around bmanager and leader effectiveness often approaches that are well-aligned up down the organization. For example, bPepsiCo and Company B reported extenuse of assessments (e.g., personality assments) for their manager populations. Pepsaiditshifted to greater depth an dlessbrein its 360-degree manager assessment, deling a greater overall impact for the compLike many companies, PepsiCo does anupward feedback for all managers.Target uses simulations for multiple levelmanager assessments; e.g., a first level mager might participate in a simulated direport meeting, whereas an upper level lemay be asked to lead a simulated strasession. These simulations, and the laassessments in which they are embeddedcontinually evaluated to ensure that taccurately predict subsequent performaon the job.Leadership Assessment. The majorityorganizations include leadership assessmaspartof their approach to research and alytics. Company G has invested heavily italent processes and has found strong lages between leadership assessment data performance. Three interesting insights fthat body of work include:1. The profile of what predicts success tenlook different at different levels oftheonization. There is not one good prof


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There tends to be a curvilinear pattern forderailers. Some level of a derailer is okay,and they only become problematic atmore extreme levels.. Self-awareness tends to predict perfor-mance among leaders.

ndividual level. Company Q does analyses toincludes the people it needs to accomplish itsfuture objectives. So, rather than assessingpproach), it takes a workforce-planningpproach to the leadership bench, and proj-cts capability demands into the future.

Although a number of individual companiesdo this exceptionally well, some thoughtleaders noted that, as afield we need analyt-icsaround tracking individuals and skills setsacross multiple jobs, feeding into successionplans and promotional opportunities in effi-cient ways.Quality of Hire. Particularly among thoseorganizations describing a close relationshipwith their staffing and recruiting teams.

Quality of Hire was a popular topic. Com-panyBhas an effective program centered ona 12-month check-in with each new-hire'smanager, assessing people skills, technicalskills and overall performance. It has beenable to feed useful information back to theorganization by analyzing the data by severalvariables, such as profession/function (e.g.,science vs. sales), or individual recruiter.Intriguingly, Synopsys has begun linking itsquality of hire work to its onboarding survey.Synopsys also is looking explicitly at vari-ables such as how manager quality influencesthe quality of hire. Microsoft has been evolv-ing an approach to quality of hire assessmentthat examines data over a two-year period,and has yielded some surprising findingsabout variables such as hire source.Bill Macey of Valtera noted, The ove rarch-ingquestion [across selection and diagnosticsIis the same - how do I put the best people inthe best environment for organizational suc-cess? Quality of hire is emerging as a bodyof work that represents an opportunity toanswer this question by taking a holisticapproach to choosing and deploying humancapital assets in organ izations. Thus, it's dis-appointing that some still use the termQuality of Hire to refer only to hiring processefficiency (itself an impo rtant concern) ra therthan the more comprehensive approa ch someof the leading organizations take.Selection/Staffing. Several of the teamsreported work in the area of selection andstaffing.Ingeneral, these analyses centered ondeveloping and validating selection proce-dures, a classic specialty area in I/Opsychology. PepsiCo employs a tight integra-

t ion be tween assessment ( se lec t ionsuccession planning, and how those connewith recruitment. Those teams, with tiglinkages to workforce planning groups, aldescribed some forecasting work. few pticipants (Company T, Company Q anCompany H) are involved in workforce planing activities within their research ananalytics functions. Company N conducfairly extensive forecasting around its worforce, including level, mix and the externlabor market for that talent.R e ten t io n /T u r n o v e r . Mo s t co m p an idescribed some analytical work with retetion and turnover. couple (Company C aCompany Q) do intriguing forecasting woaround turnover, rather than simply post-hanalytics on individuals who left the company. Company C's work resulted in a set 12 predic tor variables for retention thtogether predict more than 80 percent attrition over several years. Company Qwork examines anticipated turnover trenand their impact on several variables, such demographics. Separately, Company Q preents attrition data as part of a larger storThey always present context with data.Others go beyond traditional exit surveysintriguing w ays. Company E developed vesophisticated models of its employee popution to predict retention. This work involvcluster analysis to identify four core segmetations in the employee p opulation, centerion engagement and com mitment. UltimateCompany E was able to predict quite effetively voluntary terminations (resignationand incorporate those accurate projectiointo staffing plans .

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Performance Management. Like selectionand staffing, those com panies w ho describedinvolvement with performance managementweren't managing the programs or even nec-essarily reporting on results, but rather weretesting the overall effectiveness and efficiencyof their performance management systems(e.g., Gom panyS),especially as tho se systemsrelated to key populations of interest (e.g.,Gompany G's work with leaders). For exam-ple,Gompany N analyzesratingsdistributionsto determine whether the overall perfor-mance management system is functioningproperly: As a system, was it too harsh ortoo lenient?Onboarding/Lifecycle. Several companiespursue a lifecycle approach to understand-ing the employee experience. Rather thansurveying at one fixed point in the calendaryear and simply analyzing by, say, tenure,these companies reach out to specific at spe-cific points in the employment lifecycle.Comp any B described its comprehensiveapproach, gathering specific data at thetwo-, six-, and 12-month marks of eachemployee's tenure. Company L has an evenmore comprehensive lifecycle assessmentstrategy, including surveys at six months, 15months, five years and 10 years of tenure.Then it analyzes those data for retentiondrivers and strategies.

While this is most commonly done as part ofan onboarding and/or exit process, somecompan ies, like C ompany K, have identifieda key point in the lifecycle, after which attri-tion drop s off dramatically. Com pany usessurvey data to identify predictors for thosewho choose to leave at that pivot point vs.those who choose to stay long term.

Gulture/EVP. While many of the organiza-tions mentioned are engaged in some workaround culture and EVP,few w ent into detailabout their current efforts. One exceptionwas PepsiGo, which described a significantcampaign aro und its Employee Value Propo-sition (EVP), involving a team of businesspeople, a consultant and a creative firm todevelop supporting collateral. While manymentioned culture, few described specificqualitative or quantitative efforts targeteddirectly at capturing culture.In contrast, Microsoft has tackled both cul-ture and EVP very directly from a researchstandpoint, gatheringdeep,global q ualitativeand quantitative data. These data have beenused to inform investment decisions and cur-riculum decisions across a wide range ofofferings. Microsoft also uses its cultureassessment methodology as part of acquisi-tion integration.

MethodsParticipants primarily use fairly standardanalytical too ls, such as regression. Some usemore advanced techniques such as Struc-tural Equation Modeling (SEM) or discretechoice analysis. A few, notably Procter cGamble, report valuable findings from tech-niques like latent growth curve modeling.Others, like Company N and Company Fusefinancialmodeling effectively (e.g., long-termfinancialpayoffs of different scenarios).In many cases, however, they did not gaininsight through the most sophisticated ana-lytics. However they did gain insight throughlinking multiple data sources and mining forpatterns across data sets that were undetect-able within a set.

tives; it find s it is often fully sufficienprovide descriptives.While most organizations mentioned quative analyses, they typically described iadding texture to the quantitative analyrather than being the primary analytic segy. Procter & Gamble makes extensiveof text analytics, such as word clouds.Beyond the usual range of social science tistics, some (Gompany G) use ethnogramethods to uncover trends in areas sucleadership, or uniquely developed methologies, such as Mercer's internal lamarket analysis.The thought leaders we interviewed adcated for broader methodological statistical range. Bill Macey said that methods used in developmental psychol(e.g.,life-spanmodeling,cf.McArdle,GrimHamagami, Bowles, & Meredith, 2009) hpotential for addressing some of the mcomplex measurement issues in studyorganizational change where i tems responden ts differ across measurement ocsions. He also noted that economemethods offer some intriguing and usapproaches to examining difficult measment challenges, such as the use of discchoice modeling as an alternative to raimportance, and models for assessing setion bias such as occurs in censoredtruncated samples. John Boudreau suggethat our analytical models need to reflectcore businesses of our organizations. example, Gompany Q monitors emplomorale using an approach akin to statistprocess control, a common method of qity management in manufacturing.

Several companies pursue a lifecycle approach tounderstanding the employee experience. Rather thansurveying at one fixed point in the calendar ye a r.. .these companies reach out to employees at specificpoints in the employment lifecycle.A few organizations are doing lifecycleresearch with a bit of a twist. For example,Gompany G applies a lifecycle approach toits leadership popu lation, identifying naturalcareer paths, which they then can replicateintentionally.

Two companies (Gompany A and GompanyQ) are moving into forecasting. However,several organizations intentionally focusedon data that were easy to understand and/orconsume. GompanyTreported that abou t 90percent of its analyses result in just descrip-

StaffingAlthough most participants reported that psychologists are instrumental in their teamany reported that other disciplines contute key capabilities to their teams' ageand work. Some said it is helpful to hsomeone on the team who is an SME oncompany itself (Gompany K). Severeflected on the importance of multiple pspectives (e.g. HR, Line, MBA) in ensurthe end product is consumable. Many see need for balancing capabilities among team, although the types of at tr ibudescribed varied, from educational bagrounds (I/O psychologists vs. MBAs),personality factors (balancing intuition data). Another (Company G) said it browed needed resources from other gro


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than ow ning them directly. Target

ines, such as labor economics, account-and engineering.Inkeeping

ion is actually deve loping the research

an R& D shop, pursuing intriguing orconsultingteam.CompanySsaidit hasafew PhD's to high impact problems

now will have a big impact.ome respondents noted that they occasion-lly face challenges with the more leading-edgework, in that their organizations are notlways ready to accept it. One said, We triedto do I a specific project | for three years beforeit was accepted and valued and used. Gettingthe right audience at the right time often takesa few tries. Some of the relatively smallerorganizations (Synopsys and Company M)reported having greater leeway and ability todrive an agenda than the larger organizations.

The thought leaders were all consultants, andthus had a slightly different perspective on thetypes of talent they typically see inside organi-zations. They reflected that their role is oftento present ideas the client had not considered,thus to a certain extent leading the agenda.

Influence ModelConsistent with broader trends suggestingincreasing attention to research and analyticsin decision making, many in the study report-ed that their work is evolving from simplyreporting data to delivering insight and influ-ence. They described this shift as somethingquite simple, such as a conscious effort tosimply ask wh y on a more regular basis,and ensuring that research and analyticsresources are dedicated only to projects witha clear potential impact, rather than thoseprimarily serving curiosity. In this case, thisshift was portrayed as from analyst to con-sultant - looking for simple and concise, notfor mountains of charts.

tion to operating on the influence/decisionend of the continuum . Jay Jamrog said, Itnot just about being data-driven, you neethe story. Effective influencers have the databut they don't bludgeon people with it - thinfluence isaround telling the story, and beinrooted in the data. Similarly, John B oudreanoted, It may be more about the storytellinthan about the math...the analytics donlook that different depending on disciplinebut the way the storyistoldisdifferent ac rodisciplines.The research and analytics team's power texert influence may be rooted more in mentamodels than in capabilities. The ways thes

The research and an alytics te am s power toexert influencemay be rooted more in mentalmodels than in capabi l i t ies.Some of the teams operating more at theInfluence i Decisions end of this spectrum(Company A, Company H) have gone as faras to separate out the tools, data and basicreporting, so they can focus their resourceson advanced analytics and insight. In con-trast, others (Company Q) have aggregatedthe entire analytic stack, from the data in thepeople systems up through the sophisticatedanalytics, into a single organization. Com-pany S aggregated broad analytic capabilityacross HR specialty areas such as compensa-tion, benefits, and staffing. Target specificallymentioned investing in resources to enabledeeper analytics,whilesimultaneously invest-ing in building awareness and visibility forthe work.Several companies cited the challenges inmoving to becoming more strategic in anenvironment of resource constraint, whetherthose constraints were imposed organiza-t ional ly (C omp any B) o r somew hatself-inflicted (Com pany K, who said, It'shard to have the time to be strategic whenyou're spending all your time doing all thead-hoc kinds of requests...we only rarely oroccasionally say no. ).Thought leaders confirmed this, noting thatthey also see a broad trend toward peopleaggressively pursuing getting towards thedecision side. Seymour Adler indicated tha tsometimes trust was an essential pre-condi-

teams think about themselves, and the waytheir organizations think about them may ba greater determining factor in their influencthan their native capabilities or professionexpertise. One interviewee said with frustrtion that HR leaders don 't know what theneed, and so end up with a random pile odata. Thus, moving along this continuum more complex that it may at first appear.One organization thought that the theoretcal continuum (TOOLS/PLATFORMSDATAANALYSISINSIGHTINFLUENCEDECISIONS) actually goes too faAccording to this company, it is undesirabfor the research and analytics groups to havdecision-making responsibility. Rather, orgnization leaders need to have ownership ftheir decisions.

ConsumptionAlthough HR is by far the mostly commonmentioned consumer of the work from thegroups, some (Company G, CompanyA scifically mentioned other stakeholders, suas boards of directors, and/or direct busineleaders (Company R). Others, notably PesiCo, described employees as a key consumnoting the range of direct-to-employee p roucts and programs they deliver (e.gemployee survey, performance managem e360,manager quality). This mirrors the Cfindings (2008) regarding the customers

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HR metrics. Its HR Metrics Team Surveyrevealed that HR was a customer for 100percent of respondents; Executives, 67 per-cent; Boards of Directors, 50 percent, andCFO's 33 percent.Several companies noted that consumptionvaries with the executives in role. For exam-ple. Company Q began weekly businessmetric updates to the CEO when its new,more data-oriented CEO took the reins andbrought an insistence that we make deci-sions based on data . This enabled theresearch group to develop new metrics andget higher visibility for existing ones.Tho ught leaders are naturally in a position tobe influential at the senior executive levels ofan organization, and thus might be expectedto work with a different consumption modelthan internal groups. Rick Guzzo reflectedtha t, Some of the great experiences areworking with a strategy committee, andshared that a substantive portion of engage-ments involved direct work with a companypresident or CEO - a model that has provedvery effective. Similarly, Bill Macey indicatedthat some of his most interesting work hasbeen in engagements with strategy leaders.This presents an interesting problem forthose of us in HR. Is it possible to create anappetite for compelling analytics on HumanCapital problems by doing the work outsideHR and thus relieving the work of the stigmaof HR? If so, at what point does HR riseto reclaim that work? Or, as Boudreau andRamstad (2007) suggest, it is necessary toevolve a specific decision science forHR problems?

Organizational StructureFinally, the bulk of respondents saw theirwork as primarily H R, both in terms of orga-nizational structure and in clients andconsumers. In some cases, these are fairly

linear relationships, while others have dot-ted l ine accountabil i t ies everywhere.However, one of the key analytics groups atCompany L reports up to a strategy g roupand up through a separate VP (the entiregroup sits outside HR).Some of the thought leaders stated that theopportunity for impact can be limited byworking through HR, rather than workingdirectly with business leaders. omeacknowl-edged that sitting within HR was a bit of adouble-edged sword, in that being in HRprovides access to volumes of data , but it alsoimposes a credibility problem in organiza-tions where HR is not a strong partner indriving the business. In con trast, some of theorganizations said that a central role in HRprovides them with an enterprise view andbroad data access that would not otherwisebe possible.

RecommendationsThis inquiry leads the aspiring Human Cap-ital Analytics professional to a few naturalconclusions around the importance of themindset we bring to approaching problems,the tantamount importance of good data,and the opportunities afforded by makingconnections.First, and perhaps most impo rtant, may sim-ply be the mindset. Boudreau and Ramstead(2007) draw the analogy to the transac-tional approach of accounting versus thestrategic approach of finance. It is difficultto credibly eschew good data as a decisionaid. Unfortunately, all too often data are anafterthought, rather than being an integralpart of the way problems are identified, ana-lyzed and solved.Second, this project made it abundantly clearthat poor quality or missing data are signifi-cant barriers to good analytical work. Whilethis seems obvious, many organizationsexpressed frustration at the difficulties theirdata quality or structure posed. Sometimesthis could be addressed with significant man-ual effort; in other cases, data simply neverwere captured in the first place. Perhaps thesingle most important data integrity item isusing consistent variables and identifiers, sothat data can be mapped or merged The valuethat Human Capital analytics delivers to orga-nizations in terms of retention, organizationaleffectiveness and even bottom-line resultsshould be considered as part of the ROI inupgrading or synthesizing HR data systems.

Finally, as we discussed before, oftengreatest insights came from linking muldatasets and identifying patterns across thDoing this well requires getting out ofweeds and examining systems as a wholidentify potentially useful connectionsdoes not necessarily require sophisticanalytics, although those can be quite heat times. It does require high-quality da taMany quite useful analyses, such as examing the difference in revenue results betwhighly engaged salespeople and less engasalespeople, can be done fairly simplyExcel or other desktop spreadsheet appltions,as long as the identifiers to connectwo results sets are in place. Where sophcated techniques are required, exteconsultants or university faculty memtypically can be effective partners for heavy lifting.ConclusionsKeith Hammonds' 2007 article inFastCpany Why we hate HR ) suggested thatof the core problems with HR today is HR pursues efficiency in lieu of value. WBecause it's easier and easier to measuResearch and analytics groups are a dicontradiction to that indictment. The wwe've highlighted here representsamovemtoward sophisticated analyses on issues actually do matter to the b ottom line of bnesses, rather than simply applying the mreadily available numbers and calling itaric. The evidence suggests that our field tris in the midst of a sea change. Jac Fitz-describes it as a radical shift, like the sfrom analog to digital, from steel to plastiAlthough the findings and perspectives pticipants share here are excit ing, cautionary note is in order. Data from Laer & Boudreau (2009) suggest that, whHR's perceptions may be that we are signcantly more data-oriented and strategic twe were several years ago, examining perct i on da t a a c r oss t im e ( r a the r t hretrospectively) reveals that the extentwhich HR makes rigorous, data-based desions has been flat over a three-year tiframe (2004 - 2007). These data were baon HR as a whole profession, not the anaics functions specifically. At least amoparticipants in our inquiry, most were ablecite specific examples of their evolving inence over the past several years.A review of the scope of work covered by organizations included in this inquiry reve


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broad range of analytic al insight beingca l i b r a t ion o f pe r fo rm ance

perspectives that their own work isfieldas a whole is moving in a more stra-

swe cotitinue to evolve methodologies, andsetscontinues

Organizations that can make thisr markets.

ReferencesMcArdk', |. J., CIrimm. K. |., Hamagami, K, Bowles, R. P.,.Meredith.W (2009). Modeling l i te-span growth curves ofcognit ion using longitudinal data with multiple samplesand changing scales of measure ment. Psychological Meth-luh. I4{2}, 126-149.Birdi. K., Clegg, C, Patte rson. M ., Robins on. A.. Stride. C.B. ,Wall ,T. D. . Wood, S. | . (2O8).The Impact of HumanResource and Operat ional Management P ract ices onCompany Productivity; A Longitudinal Study. Personnelpsychology, i, 4 6 7 - 5 0 1 .Boudreau, J. W., Ram stad, P. M. (2007). Beyond HR:The neu science of human capital. Boston, MA: HarvardBusiness School Press.Corporate Leadership Council (2008). Workforce analyt-ics function: Understanding the importance, role andstriiclure (CLC Catalog Number CLC6473932) .Hamm onds , K. H (2007, December) . Why We Hate HR.Hast Company. Retrieved from http:/ /www .fastcornpany.C()m/niagazine/97/open_hr.htmlLawler, E. E., Boudreau, J. W. (2009).Achieving excel-lence in human resources management. Stanford , CA:Stanford University Press.

Levenson, A. (2005). Harnessing the Power of HR Analyics. HR strategic review. 4(3 - March/April), 2 8 - 3 1 .

Alexis A. Fink Ph.D. .Microsoft C orp .,Redmond, W ash., works in the peopleand organization capability functionat Microsoft. C'urrcntly, she is groupmanager, culture and talent transfor-mation. In this role, she is responsiblefor execution of and deriving insightsfrom Microsoft's suite of employeeengagement research programs, fordriving enterprisewide c ulture change,and for building out an enterprisewidetalent strategy and framework. Finkreceived her doctorate from OldDominion University, in Norfolk, Va.A productive scholar as well as anaccomplished practitioner, she hasmore than 30 publications and aca-demic presentations to her credit.

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requires the right perspectiveA new point of viewAt Tov\/ers W atson, our focus is on giving you the clarity to make the right decisions . Whether you re conce rned aboutmanaging risk, keeping top talent or providing the right benefits at the right cost, we bring the right perspective.Towers Watson. A global company with a singular focus on our clients.

BenefitsRisk and Financial ServicesTalent and Rewardstowerswatson.com TOWERS WATSON

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New Trends in Human Capital Research and Analytics