Organisation & People Analytics

Transcription

1 Organisatin & Peple Analytics Research study prepared fr the Peple Analytics Optimis Cnference, 5 June 2014, Geneva A research initiative cnducted by: Optimis Human Capital Management Authrs: Laurent Jaquenud Michael Hathrn Date: 2 July 2014

2 Table f cntents PURPOSE OF THE STUDY... 3 RESEARCH STUDY PARTICIPATION... 5 CURRENT AREAS OF HR METRICS... 7 PREDICTION OF BUSINESS IMPACT... 9 HR METRICS CHALLENGES THE KEY HR METRICS AREAS FOR MANAGEMENT CONCLUSIONS AND FUTURE OUTLOOK HOW CAN OPTIMIS SUPPORT YOU NOW ANNEX A: ABOUT OPTIMIS

3 Purpse f the study Peple Analytics is nw recgnised as a strategic driver used t demnstrate the value f HR related prgrammes and t take better business decisins The purpse f this study is t investigate current practices, challenges and pririties in the field f Peple Analytics. The individuals taking part in the survey demnstrated a keen interest in this tpic, viewing it as a pririty fr HR leaders and the Business. The imprtance f Peple Analytics is increasingly recgnised as a strategic driver used t demnstrate the value f HR related prgrammes and t take better business decisins. HR prfessinals struggle t establish the business impact f HR initiatives, prcesses and prgrammes and cmmunicate with business managers n the value f their activities. With the increasing availability f data, it is nw pssible t link HR related infrmatin t business and rganisatinal impact using mdern analytical techniques and tls. It becmes pssible nt nly t better explain the utcme f HR activities, but als t predict future success. Hence HR Analytics can be a key cntributr t the business decisin- making prcess and help ensure future rganisatinal perfrmance. As Prfessr Wayne Casci, pineer and thught leader n the tpic, says: HR measurement is valuable t the extent it imprves vital decisins abut talent and hw it is rganized. It is difficult t select and access data fr the HR measures that have demnstrable business impact, and it is ften easy t track specific HR measures where there is readily available data that has little r unknwn business value. Fr instance, a measure f staff turnver has relevance nly when we g belw the high level measure and explre the cntext and drivers fr turnver. S several imprtant challenges are n the way and we will discver sme f them in this study. Optimis ran this research prject at the same time as the Peple Analytics, Driving Business Success event held in Geneva the 5 th June The event featured a panel f presenters and thught leaders that included Prfessr Wayne Casci (University f Clrad), Prfessr Bill Fisher (IMD), Antni Vegezzi (Bard Member, Pineer Investments) and Thmas Waterhuse (HR COO f Pictet Bank). Sme utcmes f this study were shared at the event and participants enthusiastically participated in a l discussin n Peple Analytics. Finally, an interview f Wayne Casci was held prir t the event and was published in Swiss HRTday Magazine. Yu can find a cpy f the interview in English and in French n the Optimis web site hcm.cm/intelligence/research- articles- - - white- papers.html 3

4 Methdlgy The study was cnducted in 2014 using the Optimis nline survey platfrm ver the perid May 12 th t June 4 th. The research questinnaire was designed t capture respndents perspectives n their Peple Analytics challenges and pririties. Survey participants were heavily represented by the cnference attendees, as well as HR prfessinals in the Suisse Rmande, cming frm a brad variety f rganisatins and industries. The findings f this study are nt meant t be statistically representative f the HR ppulatin generally in the Suisse Rmande, but d hwever uncver sme cmmn themes and findings which are endemic in this area. It is ur hpe that these findings will prvide sme clarity abut the cmmn challenges that rganisatins face and what can be dne t address them. HR measurement is valuable t the extent it imprves vital decisins abut talent and hw it is rganised. Prf. Wayne Casci Reprt f High Level Findings This reprt prvides an verview f the cnslidated findings and is available n the Optimis website Demgraphic data was cllected t facilitate cmparisns amng subgrups f participants and acrss rganisatin types, althugh nly a limited number f these cmparisns are reprted in this paper. Shuld survey participants r ther readers wish t delve deeper int the findings please cntact Optimis directly. 4

5 Research study participatin Participants by industry The survey attracted a ttal f 123 respndents, which gives us a reasnable sample given the time frame and the ttal ppulatin wh were invited. We fcused ur study n prfessinals wrking with Internatinal and Multi- natinal rganisatins lcated in the Suisse Rmande area. As indicated by Figure 1 belw, a wide range f nn- prfit rganisatins tk part in the study, representing the largest grup f rganisatin at 39% f the ttal. This was fllwed by three ther main participants grups represented as fllws: Banking (12%), Services (10%) and Manufacturing (9%). The Other (17%) categry is cmprised f several types f rganisatins including fr example legal, health and trading rganisatins. A ttal f 123 participants tk part in this research study (fcus in Suisse Rmande) which illustrates a strng interest in the area f Peple Analytics. Services, cnsulting; 10% Educatin; 3% Medical; 3% Industry f participants Other?; 17% Manufacturing; 9% Nn- prfit, gvernment, NGO; 39% Cnsumer gds; 5% Bitechnlgy, Chemical; 2% Banking, Finance; 12% Figure 1: Participants by industry Rles f participants Amng survey participants, apprximately 36% f the survey ppulatin were at senir levels (see Figure 2) either HR Directrs, HR Managers r Business Leaders. An additinal 25% are classified as HR prfessinals. The Other categry (27%) includes peple frm ther supprt functins such as Finance r IT, as well as cnsultants r peple in the educatin sectr. And finally, 10% f respndents were HR assistants, indicating a significant level f interest n this tpic frm that ppulatin. 5

6 Rle f participants Head f HR; 9% Other?; 27% HR Manager; 12% HR Cnsultant; 3% Business leader; 15% HR Assistant; 10% HR Prfessinal; 25% Figure 2: Participants by psitin Participants by rganisatin size Peple ften believe that Peple Analytics is f interest nly fr large rganisatins. Our research shws (see Figure 3) that while 33% f respndents cme frm rganisatins between 1000 and 5000 staff, half f the respndents (49%) cme frm smaller rganisatins with less than 1000 staff, and 40% frm rganisatins with less than 500 staff. This suggests that small rganisatins als have a strng interest in HR related analytics t better understand the value f their HR prgrammes in terms f business impact. Almst half f the survey respndents cme frm rganisatins with less than 1000 emplyees. Mre than 10'000 emplyees; 13% 5'001 t 10'000 emplyees; 7% Organisatin size f participants < 10 emplyees; 10% 11 t 100 emplyees; 23% 1'001 t 5'000 emplyees; 33% 501 t 1'000 emplyees; 9% 101 t 500 emplyees; 7% Figure 3: Participants by size f their rganisatin 6

7 Current areas f HR Metrics Respndents were asked if they currently track HR related metrics and in which areas. 67% f respndents track HR related metrics Recruitment is the categry with the greatest fcus fr ur participants, bth frm a recruitment success utcme and frm a prcess efficiency pint f view. The fur tp categries f metrics tracked were selected by ver 30% f survey participants. Recruitment (prcess and success rates) was the leader with 48% reprting that they gathered data in this area. Turnver was secnd with 40% identifying this classical HR indicatr. Emplyee Engagement and Perfrmance Management registered 34% each. The survey did nt identify what data was cllected r hw it was analysed, nly that the rganisatin made an effrt t cllect data in this area. 60% Currrent areas f analytics 50% 40% 30% 20% 10% 0% Recruitment Turnver Emplyee engagement Perfrmance Management Cmpensatin & Benefits Other Talent Management Mbility and transprt Figure 4: Current areas f analytics The Other categry includes tpics such as Headcunt/FTE, Health, Cmpliance and Absenteeism. Main fcus tday Recruitment was identified as the tp categry by participants in this research, suggesting that recruitment is an area f fcus fr cllecting data. Frm ur perspective, the current war fr talent leads t greater pressure n recruiting the best and in an efficient manner. Many rganisatins measure the number f staff recruited versus pen psitins and average time t fill a psitin. These numbers are nly a beginning and d little t specify the business cntributin f the recruitment prcess. In effect, what we knw is that the psitin is filled, but nt the quality f the recruitment utcme. We recmmend that recruitment success be measured based n the demnstrated value t the business f the staff hire. Fr instance, an rganisatin can measure the Perfrmance level f new hires after 6 mnths r Retentin rate f high perfrmers hired in the last 12 mnths. The abve example shws the linkage f the perfrmance 7

8 We ften measure what is easy t measure rather than what is imprtant t measure assessment f staff and recruitment, and nly adds value t the extent that accurate and reliable data are cllected in bth areas. The bttm line is that we must shift ur fcus t include measures f the business impact f the activity, rather than nly the efficiency f the effrt. This ges back t the idea that we ften measure what is easy t measure rather than what is imprtant t measure. It als illustrates the understand the areas f interactin and impact. Interestingly, Emplyee Engagement has becme a tp pririty fr many f the respndents, nt nly because many rganisatins d Emplyee Engagement surveys, but als because many realise that Emplyee Engagement is tday the main surce f Organisatin Perfrmance. But hw many rganisatins ptimise the prcess and get real results frm their investment in cllecting the data? Our experience is that rganisatins ften view the survey as the main activity and capture few if any f the imprvement pprtunities that the Emplyee Engagement data suggest, preferring t reprt back the cnslidated data and mve n. The real pprtunity here is t use the data t understand rt causes f rganisatinal issues and implement a prcess t address the specific rganisatinal challenges that are identified. Again we cme t the challenge f ging deeper int the data and identifying pprtunities t leverage infrmatin t take management decisins that will imprve the rganisatin and have a business impact. At Optimis, we recmmend that rganisatins cnduct an Emplyee Engagement survey nly if they plan t fllw the survey with a rbust prcess t analyse the data and drive imprvements in the rganisatin. We believe that rganisatins that cnduct survey prcesses t identify imprvement pprtunities and d little with the data actually destry trust with staff. Participants t such survey have the reasnable expectatin that imprvements will be made based upn the findings and ften want t participate in the imprvement prcess. 8

9 Predictin f business impact We asked the respndents if they believed they culd predict the business impact f their HR activities. This is key in the area f HR analytics as the purpse is t be able justify and predict the anticipated real business utcme. 27% f respndents believe they can predict business impact with their HR activities A selectin f business impact pprtunities mentined is as fllws: A ttal f 27% f respndents reprt that they can measure business impact cmpared t 67% wh measure HR activities. This shws a significant pprtunity t take the next step in using HR metrics. Recruitment cst and success Develp and enhance best practices Imprvement f custmer service Increased business prcess efficiency Cst per hire influences surcing strategies within recruitment Increased mtivatin and retentin based n turnver measure and adequate actin Retentin f best perfrmers (Cmpensatin & Benefits and annual perfrmance management apprved at bard level) Cst f internal transfers Business cntinuity impact due t recruitment time t hire Cst f absenteeism As nly 27% f respndents believe they can measure the business impact versus 67% invlved in cllecting HR date f sme type, this shws the difficulty f linking HR measures t business value. On the ther hand, there is a significant pprtunity present t take the next step in using HR metrics by building the business case fr impact and value. 9

10 Resurces invlved in HR metrics Larger rganizatins tend t have internal specialists t cmplement external expertise. Participants were asked t indicate wh usually deals with HR metrics within their rganisatin. See Figure 5 fr the distributin: 60% 50% 40% 30% 20% 10% 0% Varius HR prfessinal(s) (generalists) Dedicated HR prfessinal(s) (specialists) Other (please specify): Finance prfessinal(s) External prfessinal(s) Figure 5: Wh deals with HR metrics Generalists are the biggest ppulatin in ur study wh have respnsibility fr HR metrics, representing 55% f the respndents. The Other categry includes CEO s, Tp Management and varius administratin departments. Lking at hw the split is spread based n rganisatin size, we fund that External Prfessinals are mainly hired by SME s with less than 100 staff (wh are prbably nt always equipped with specialists internally) r by big rganizatins wh are engaging deep expertise that they d nt have in- huse. Als, the larger rganisatins tend t have internal specialists t cmplement external expertise, whereas Generalists are in charge f HR analytics in smaller rganisatins and may nt be as cmfrtable with the technical aspects f Peple Analytics. Our experience is that a level f specialist knwledge is needed t structure and develp the Peple Analytics prcesses within an rganisatin, especially the identificatin f what t measure and the mdels that are used t relate the measures t business impact. In additin, the data analysis requirements can be quite specialised and must be carefully undertaken t ensure that the linkages t business impact are clearly specified. A further challenge is t then explain the analysis prcess and utcmes in clear business terms. 10

11 HR Metrics Challenges Research shws that practitiners f HR Analytics have many challenges. Many authrs n the tpic, including Wayne Casci, recgnize that it is usually nt easy t chse the right things t measure, t get access t the right data, t analyse the data crrectly and t reprt it in a way that demnstrates business impact and supprts the decisin making prcess. The participants ranked their challenges in the fllwing way: (see figure 6) 60% Biggest challenges abut HR metrics 50% 40% 30% 20% 10% 0% Lack f Difficult t expertise in acquire data this area Nt a business pririty Other Nt an HR pririty Cst Figure 6: HR Metrics Challenges Many authrs write that is it nt easy t chse the right things t measure, t get access t the right data, t analyse the data crrectly and t reprt it in a way that supprts the decisin making prcess. Tw main challenges came ut frm the study: Lack f expertise in this area was reprted by 52% f respndents. Althugh tw thirds (67%) f participants d track HR related indicatrs, mre than half believe that they lack the expertise t fully explit the data. The secnd main challenge reprted by 43% f respndents was that it is Difficult t acquire data. This relates t the reality that HR data is ften spread acrss varius Infrmatin Systems (IS) such as: Finance IS, HR IS, Excel files, departmental data bases and ther repsitries. This limits the use f enterprise wide ff- the- shelf systems that cannt pssibly accmmdate the multitude f data surces that exist in this area. Cst is the least imprtant challenge (9%), but abut 20% f respndents believe that Peple Analytics is neither a Business nr an HR pririty. This is ften linked t the fact that it is difficult t build a stry and interpret HR related data/infrmatin fr effective decisin making, hence is nt perceived as a pririty. The Other categry includes challenges such as: Lack f accuracy / quality f HR data Linking HR data t business impact Internal plitical reasns Cultural reasns (HR is imprtant, but nt a hard business discipline ) 11

12 The key HR Metrics areas fr Management Respndents were asked t give what their Management wants t knw when it cmes t Peple related data and analytics. This was an pen questin and we categrized the answers int 15 categries as in Figure 7 belw. 25% Key areas that Management want t knw 20% 15% 10% 5% 0% Figure 7: The key HR metrics areas that Management wants t knw There is sme alignment between what is measured tday and what management wants t knw, in particular when it cmes t Emplyee Engagement and Perfrmance. The main difference is that Management fcuses n wanting t knw the utcme f HR activities (e.g. level f Engagement/perfrmance, Recruitment success, turnver, prductivity, level f cmpetence) and hw this will make a difference t the business, whereas what is measured tday by HR is mainly linked t the HR activities themselves (prcess efficiency and effectiveness) and nt always their utcme. In reality, nly 1% f respndents indicated that their Management is interested in the success f HR prgrammes. As Wayne Casci pints ut: There is little crrelatin between what is usually measured in the terms f HR and the business main bjectives. Our study cnfirms this dilemma. 12

13 The psitive aspect is that respndents are aware f what management wants, which is mre related t the utcme/impact f their HR prgrammes, but nly 27% f them believe they can measure business impact as indicated earlier. Other specific areas f interest mentined by participants are as fllws: Measuring innvatin and new prject cntributin t the business Hurs f Management cmmitment/perfrmance Cst f recruitment/tenure f emplyee within the rganisatin Measuring the cmpany specific and ften unstated recruitment bjectives nt captured by SAP r ther enterprise systems Ttal value f emplyee lifetime cntributins/cst f emplyee departure Develpment bjectives vs. prgress actually made Business Unit csting In sum, we fund that respndents had sme insights n what Management wuld like t knw but were nt necessarily delivering these results in their current HR metrics practices. This suggests that there is a great pprtunity t develp the Peple Analytics capability and supprt Management further in business decisin- making and in adding business value. 13

14 Cnclusins and future utlk Organisatins tday measure Peple related data and indicatrs, but they are nt necessarily crrespnding t what Management expects. Indeed, Management wuld like t knw the value f HR prgrammes in terms f utcme and business value. This research prject demnstrated a number f prminent challenges and areas that can be explred. It is clear that rganisatins tday measure Peple related data/indicatrs, but that they are nt necessarily crrespnding t what Management expects. Indeed, Management wuld like t knw the value f HR prgrammes in terms f utcme and business value. HR faces a number f main challenges: HR prfessinals must cllect the right data, frmulate the analytical framewrk, analyse the data and cmmunicate business relevant infrmatin in a way that tells a cmpelling stry fr decisin making. We recmmend that HR begin the prcess f Peple Analytics with a fcus n strategic business questins. When HR prfessinals are able t start with imprtant strategic questins then they have a relevant cntext t develp the Peple Analytics mdels, prcesses and data needed t address that questin. They are als ensuring business relevance and that the tpic will be f interest t senir leadership. Fr example, business leaders will be interested in the turnver by key talent grups, what types and prfiles they are lsing, the ptential impact t the business, the reasns why key talent is leaving and what pssible slutins can address the turnver that has a significant business cst. HR usually tracks verall r average turnver, at a minimum, and ften des a pr jb in assessing the results f exit interviews. Overall turnver figures ften d nt say much. It is impssible t determine the impact f x% turnver withut a deeper analysis f what is behind that number. Our slutin is t analyze HR metrics that answer a strategic questin. This prvides a strategic perspective, structure and relevance t the peple analytics effrts. In rder t meet the abve challenges HR functins must develp r surce the expertise t frame the key strategic questins, structure the peple analytics mdel, cllect and analyse the data, translate the analysis results int the language f business, and develp cntextual stries t cmmunicate the business impact pssibilities. T summarise, we at Optimis believe that the key success factrs required t succeed in implementing a rbust Peple Analytics apprach are the fllwing: HR analysis framewrks and data respnd t key strategic questins Cllect and analyse the data required by the analytics framewrk Integrate peple data frm multiple surces Segment metrics and analytics by talent grups Include qualitative analysis where ever pssible Stry telling when distributing analytics t Management Integrate business data in yur analysis Demnstrate business impact pprtunities Optimis has experience in develping the Peple Analytics practices in bth public and private sectr rganisatins. We wuld be pleased t discuss further this pprtunity and t share further ur experience. Our strng cnvictin is that rganisatins can benefit enrmusly frm linking peple data t business perfrmance thrugh Peple Analytics. 14

15 Hw can Optimis supprt yu nw At Optimis we can supprt yu in taking the necessary steps t increase the business value added impact f yur HR initiatives. It can be daunting t knw where t begin in the Peple Analytics jurney fr yur rganisatin. The cnstant peratinal demands, the legacy HR metrics, the new enterprise level HR system cnspire t prvide a cnfusing envirnment within which t make a strng start. At Optimis we can supprt yu in taking the necessary steps t increase the business value added impact f yur HR initiatives. Belw are sme typical services that we prvide: Peple Analytics Audit and Feasibility Study We recgnise that there is n ne size fits all slutin and that yu have an peratinal and cultural legacy t wrk with. We als knw that it can be expensive t mdify existing IT systems and that the wrk needs t be dne right the first time. T supprt yu in this prcess we suggest a Peple Analytics Audit and Feasibility Study where we will make recmmendatins based n yur cmpany cntext and the level f maturity f yur current analytics effrts. Assess yur current practices, data surces, HR prcesses, IT envirnment and the business perating envirnment Gather data frm key stakehlders t understand the key strategic challenges, the cntext and the pprtunities fr making an impact with Peple Analytics Prepare a set f recmmendatins based n the abve assessment Design, Pilt and Implement Peple Analytics Slutins in key Strategic Areas In rder t demnstrate the pwer f Peple Analytics and its value t the business we can supprt yu in the chice f a few strategic areas which are suitable fr initial pilt prjects. This may be in the high pririty area f recruitment, in staff mtivatin (engagement), in cmpensatin and benefits, r in any strategic area where there is management interest and an expectatin t imprve. Select the strategic areas Design the framewrks and mdels Identify key data required, plus cllectin methds Select data analysis methds and prtcls fr the analysis Design easy t use, flexible and pwerful tls that allw cllectin and distributin f the analytics Pilt the slutin Cnduct the data analysis and cnfirm results Translate results int business language Create the stry t demnstrate impact Prepare the team t present t senir management 15

16 Onging supprt fr yur Peple Analytics effrts We are cmmitted t supprting yur Peple Analytics effrts and the type f supprt can be tailred t yur requirements. Fr instance, sme initiatives are best handled by utside agents due t cnfidentiality requirements. In the case f an Emplyee Engagement Survey, Optimis can handle the full survey prcess and guarantee cnfidentiality f the respnses. We als take it a step further and prvide a full service actin planning prcess t supprt yur rganisatin in reaping the full benefits frm a particular initiative that yu have undertaken. As well, we measure the impact f the change initiatives. In sum, Optimis can fill the gaps in yur internal expertise fr develping and implementing Peple Analytics slutins and the change initiatives that are assciated with them. We will wrk flexibly with yu t ensure that the value prpsitin remains attractive. 16

17 Annex A: Abut Optimis Optimis is an internatinal cnsultancy grup based in. We supprt private and public sectr rganisatins in the achieving greater rganisatinal effectiveness by reviewing, develping and ptimizing their Organisatinal and Human Resurce Management strategies, structures, prcesses and systems. We are a grup f senir prfessinals cmmitted t measuring the benefits f ur client s investment and perating as a strategic advisr t help achieve ptimal returns, financial as well as rganisatinal. Our service areas are split int three main sectrs: Optimis Strategy Cnsulting Belw are several areas where Optimis ffers strategic cnsulting services: Organisatinal Diagnstics and Research We are cmmitted t understanding the rganisatinal cntext, challenges and issues f ur clients thrugh rganisatinal surveys, rganisatinal analysis, research and functinal audits. We prvide ur diagnstic services n three levels: rganisatinal, functinal- team and individual Develping Strategy Initiatives We supprt ur clients in defining and develping apprpriate rganisatinal and HR strategies, structures, plicies, prcesses and systems t address rganisatinal issues and deliver business strategies Implementing Prgrams and Prjects As a partner, we supprt the implementatin f slutins thrugh rigrus change management and learning activities t ensure successful executin Optimis Learning Optimis prvides custmised learning prgrammes designed t meet the rganisatin s needs and t build management and leadership capabilities. Optimis delivers enterprise wide learning slutins fr yur leadership and management teams. We use experiential applied learning techniques and seasned facilitatrs t draw ut the ptential f individuals, grups and entire rganisatins. Our learning architects assist in the design f custm prgrammes that are linked t ur clients pririties and the specific capabilities required achieving their gals. Thrugh a mix f learning and caching, we help them create an envirnment where engagement, perfrmance and learning are fully integrated int the day- t- day activities and are everyne s pririty. Optimis Surcing We supprt yur strategic change initiatives with expert selectin and assessment services t ensure yu have the right talent t implement yur rganisatinal strategy. In additin, we prvide interim management placement t supprt ur clients in accessing difficult t find prfiles 17

18 Hw will yu take it t the next level? Rte de la Gare 17, CH 1026 Echandens, Tel : , Fax : inf@ptimis.ch 18